AMES_Test-Part-2-Exploratory-Data-Analysis.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/stawiskm/QSAR_Modelbuilding_amesTest/blob/main/AMES_Test-Part-2-Exploratory-Data-Analysis.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "l0Y7_lgN4jzM"
      },
      "source": [
        "# **Bioinformatics Project - Computational Ames test [Part 2] Exploratory Data Analysis**\n",
        "\n",
        "Marc Jermann\n",
        "\n",
        "In this Jupyter notebook, we will be building a real-life **data science project**. Particularly, we will be building a machine learning model using the ChEMBL bioactivity data.\n",
        "\n",
        "In **Part 2**, we will be performing Descriptor Calculation and Exploratory Data Analysis.\n",
        "\n",
        "---"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "o-4IOizard4P"
      },
      "source": [
        "## **Install conda and rdkit**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "H0mjQ2PcrSe5",
        "outputId": "7ab627ac-e3aa-4971-a7c6-b2d140bf7a4b",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "--2022-05-18 13:42:30--  https://repo.anaconda.com/miniconda/Miniconda3-py37_4.8.2-Linux-x86_64.sh\n",
            "Resolving repo.anaconda.com (repo.anaconda.com)... 104.16.131.3, 104.16.130.3, 2606:4700::6810:8303, ...\n",
            "Connecting to repo.anaconda.com (repo.anaconda.com)|104.16.131.3|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 85055499 (81M) [application/x-sh]\n",
            "Saving to: ‘Miniconda3-py37_4.8.2-Linux-x86_64.sh.3’\n",
            "\n",
            "Miniconda3-py37_4.8 100%[===================>]  81.12M   110MB/s    in 0.7s    \n",
            "\n",
            "2022-05-18 13:42:31 (110 MB/s) - ‘Miniconda3-py37_4.8.2-Linux-x86_64.sh.3’ saved [85055499/85055499]\n",
            "\n",
            "PREFIX=/usr/local\n",
            "Unpacking payload ...\n",
            "Collecting package metadata (current_repodata.json): - \b\b\\ \b\b| \b\b/ \b\b- \b\bdone\n",
            "Solving environment: | \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\bfailed with initial frozen solve. Retrying with flexible solve.\n",
            "Solving environment: / \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\bfailed with repodata from current_repodata.json, will retry with next repodata source.\n",
            "Collecting package metadata (repodata.json): \\ \b\bdone\n",
            "Solving environment: / \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\bfailed with initial frozen solve. Retrying with flexible solve.\n",
            "Solving environment: | \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \n",
            "Found conflicts! Looking for incompatible packages.\n",
            "This can take several minutes.  Press CTRL-C to abort.\n",
            "\b\b/ \b\bfailed\n",
            "\n",
            "UnsatisfiableError: The following specifications were found to be incompatible with each other:\n",
            "\n",
            "Output in format: Requested package -> Available versions\n",
            "\n",
            "Package readline conflicts for:\n",
            "wheel==0.34.2=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> readline[version='>=7.0,<8.0a0']\n",
            "mkl_random -> python[version='>=3.7,<3.8.0a0'] -> readline[version='>=7.0,<8.0a0']\n",
            "bottleneck -> python[version='>=3.7,<3.8.0a0'] -> readline[version='>=7.0,<8.0a0']\n",
            "pyparsing -> python[version='>=3.6'] -> readline[version='>=7.0,<8.0a0']\n",
            "pycparser==2.19=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> readline[version='>=7.0,<8.0a0']\n",
            "cffi==1.14.0=py37h2e261b9_0 -> python[version='>=3.7,<3.8.0a0'] -> readline[version='>=7.0,<8.0a0']\n",
            "idna==2.8=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> readline[version='>=7.0,<8.0a0']\n",
            "numexpr -> python[version='>=3.7,<3.8.0a0'] -> readline[version='>=7.0,<8.0a0']\n",
            "chardet==3.0.4=py37_1003 -> python[version='>=3.7,<3.8.0a0'] -> readline[version='>=7.0,<8.0a0']\n",
            "pillow -> python[version='>=3.7,<3.8.0a0'] -> readline[version='>=7.0,<8.0a0']\n",
            "cryptography==2.8=py37h1ba5d50_0 -> python[version='>=3.7,<3.8.0a0'] -> readline[version='>=7.0,<8.0a0']\n",
            "certifi==2019.11.28=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> readline[version='>=7.0,<8.0a0']\n",
            "conda==4.8.2=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> readline[version='>=7.0,<8.0a0']\n",
            "six==1.14.0=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> readline[version='>=7.0,<8.0a0']\n",
            "numpy-base -> python[version='>=3.7,<3.8.0a0'] -> readline[version='>=7.0,<8.0a0']\n",
            "py-boost -> python[version='>=3.7,<3.8.0a0'] -> readline[version='>=7.0,<8.0a0']\n",
            "pyopenssl==19.1.0=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> readline[version='>=7.0,<8.0a0']\n",
            "ruamel_yaml==0.15.87=py37h7b6447c_0 -> python[version='>=3.7,<3.8.0a0'] -> readline[version='>=7.0,<8.0a0']\n",
            "urllib3==1.25.8=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> readline[version='>=7.0,<8.0a0']\n",
            "conda-package-handling==1.6.0=py37h7b6447c_0 -> python[version='>=3.7,<3.8.0a0'] -> readline[version='>=7.0,<8.0a0']\n",
            "mkl-service -> python[version='>=3.7,<3.8.0a0'] -> readline[version='>=7.0,<8.0a0']\n",
            "mkl_fft -> python[version='>=3.7,<3.8.0a0'] -> readline[version='>=7.0,<8.0a0']\n",
            "tqdm==4.42.1=py_0 -> python -> readline[version='>=7.0,<8.0a0']\n",
            "pysocks==1.7.1=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> readline[version='>=7.0,<8.0a0']\n",
            "rdkit -> python[version='>=3.7,<3.8.0a0'] -> readline[version='>=7.0,<8.0a0']\n",
            "setuptools==45.2.0=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> readline[version='>=7.0,<8.0a0']\n",
            "numpy -> python[version='>=3.7,<3.8.0a0'] -> readline[version='>=7.0,<8.0a0']\n",
            "packaging -> python[version='>=3.6'] -> readline[version='>=7.0,<8.0a0']\n",
            "pandas -> python[version='>=3.7,<3.8.0a0'] -> readline[version='>=7.0,<8.0a0']\n",
            "python-dateutil -> python -> readline[version='>=7.0,<8.0a0']\n",
            "python==3.7.6=h0371630_2 -> readline[version='>=7.0,<8.0a0']\n",
            "readline==7.0=h7b6447c_5\n",
            "pycosat==0.6.3=py37h7b6447c_0 -> python[version='>=3.7,<3.8.0a0'] -> readline[version='>=7.0,<8.0a0']\n",
            "pip==20.0.2=py37_1 -> python[version='>=3.7,<3.8.0a0'] -> readline[version='>=7.0,<8.0a0']\n",
            "requests==2.22.0=py37_1 -> python[version='>=3.7,<3.8.0a0'] -> readline[version='>=7.0,<8.0a0']\n",
            "pytz -> python -> readline[version='>=7.0,<8.0a0']\n",
            "\n",
            "Package openssl conflicts for:\n",
            "bottleneck -> python[version='>=3.7,<3.8.0a0'] -> openssl[version='>=1.1.1d,<1.1.2a']\n",
            "setuptools==45.2.0=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> openssl[version='>=1.1.1d,<1.1.2a']\n",
            "pyparsing -> python[version='>=3.6'] -> openssl[version='>=1.1.1d,<1.1.2a']\n",
            "six==1.14.0=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> openssl[version='>=1.1.1d,<1.1.2a']\n",
            "cryptography==2.8=py37h1ba5d50_0 -> openssl[version='>=1.1.1d,<1.1.2a']\n",
            "pytz -> python -> openssl[version='>=1.1.1d,<1.1.2a']\n",
            "requests==2.22.0=py37_1 -> python[version='>=3.7,<3.8.0a0'] -> openssl[version='>=1.1.1d,<1.1.2a']\n",
            "pysocks==1.7.1=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> openssl[version='>=1.1.1d,<1.1.2a']\n",
            "certifi==2019.11.28=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> openssl[version='>=1.1.1d,<1.1.2a']\n",
            "idna==2.8=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> openssl[version='>=1.1.1d,<1.1.2a']\n",
            "pillow -> python[version='>=3.7,<3.8.0a0'] -> openssl[version='>=1.1.1d,<1.1.2a']\n",
            "numpy-base -> python[version='>=3.7,<3.8.0a0'] -> openssl[version='>=1.1.1d,<1.1.2a']\n",
            "cffi==1.14.0=py37h2e261b9_0 -> python[version='>=3.7,<3.8.0a0'] -> openssl[version='>=1.1.1d,<1.1.2a']\n",
            "packaging -> python[version='>=3.6'] -> openssl[version='>=1.1.1d,<1.1.2a']\n",
            "numexpr -> python[version='>=3.7,<3.8.0a0'] -> openssl[version='>=1.1.1d,<1.1.2a']\n",
            "urllib3==1.25.8=py37_0 -> cryptography[version='>=1.3.4'] -> openssl[version='>=1.1.1d,<1.1.2a']\n",
            "wheel==0.34.2=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> openssl[version='>=1.1.1d,<1.1.2a']\n",
            "mkl_fft -> python[version='>=3.7,<3.8.0a0'] -> openssl[version='>=1.1.1d,<1.1.2a']\n",
            "python-dateutil -> python -> openssl[version='>=1.1.1d,<1.1.2a']\n",
            "pycosat==0.6.3=py37h7b6447c_0 -> python[version='>=3.7,<3.8.0a0'] -> openssl[version='>=1.1.1d,<1.1.2a']\n",
            "pip==20.0.2=py37_1 -> python[version='>=3.7,<3.8.0a0'] -> openssl[version='>=1.1.1d,<1.1.2a']\n",
            "tqdm==4.42.1=py_0 -> python -> openssl[version='>=1.1.1d,<1.1.2a']\n",
            "pandas -> python[version='>=3.7,<3.8.0a0'] -> openssl[version='>=1.1.1d,<1.1.2a']\n",
            "mkl-service -> python[version='>=3.7,<3.8.0a0'] -> openssl[version='>=1.1.1d,<1.1.2a']\n",
            "rdkit -> python[version='>=3.7,<3.8.0a0'] -> openssl[version='>=1.1.1d,<1.1.2a']\n",
            "pyopenssl==19.1.0=py37_0 -> cryptography[version='>=2.8'] -> openssl[version='>=1.1.1d,<1.1.2a']\n",
            "python==3.7.6=h0371630_2 -> openssl[version='>=1.1.1d,<1.1.2a']\n",
            "numpy -> python[version='>=3.7,<3.8.0a0'] -> openssl[version='>=1.1.1d,<1.1.2a']\n",
            "openssl==1.1.1d=h7b6447c_4\n",
            "py-boost -> python[version='>=3.7,<3.8.0a0'] -> openssl[version='>=1.1.1d,<1.1.2a']\n",
            "conda-package-handling==1.6.0=py37h7b6447c_0 -> python[version='>=3.7,<3.8.0a0'] -> openssl[version='>=1.1.1d,<1.1.2a']\n",
            "chardet==3.0.4=py37_1003 -> python[version='>=3.7,<3.8.0a0'] -> openssl[version='>=1.1.1d,<1.1.2a']\n",
            "conda==4.8.2=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> openssl[version='>=1.1.1d,<1.1.2a']\n",
            "pycparser==2.19=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> openssl[version='>=1.1.1d,<1.1.2a']\n",
            "ruamel_yaml==0.15.87=py37h7b6447c_0 -> python[version='>=3.7,<3.8.0a0'] -> openssl[version='>=1.1.1d,<1.1.2a']\n",
            "mkl_random -> python[version='>=3.7,<3.8.0a0'] -> openssl[version='>=1.1.1d,<1.1.2a']\n",
            "\n",
            "Package tk conflicts for:\n",
            "tqdm==4.42.1=py_0 -> python -> tk[version='>=8.6.8,<8.7.0a0']\n",
            "requests==2.22.0=py37_1 -> python[version='>=3.7,<3.8.0a0'] -> tk[version='>=8.6.8,<8.7.0a0']\n",
            "idna==2.8=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> tk[version='>=8.6.8,<8.7.0a0']\n",
            "certifi==2019.11.28=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> tk[version='>=8.6.8,<8.7.0a0']\n",
            "six==1.14.0=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> tk[version='>=8.6.8,<8.7.0a0']\n",
            "pip==20.0.2=py37_1 -> python[version='>=3.7,<3.8.0a0'] -> tk[version='>=8.6.8,<8.7.0a0']\n",
            "pillow -> python[version='>=3.7,<3.8.0a0'] -> tk[version='>=8.6.8,<8.7.0a0']\n",
            "bottleneck -> python[version='>=3.7,<3.8.0a0'] -> tk[version='>=8.6.8,<8.7.0a0']\n",
            "numpy -> python[version='>=3.7,<3.8.0a0'] -> tk[version='>=8.6.8,<8.7.0a0']\n",
            "mkl-service -> python[version='>=3.7,<3.8.0a0'] -> tk[version='>=8.6.8,<8.7.0a0']\n",
            "python-dateutil -> python -> tk[version='>=8.6.8,<8.7.0a0']\n",
            "pycosat==0.6.3=py37h7b6447c_0 -> python[version='>=3.7,<3.8.0a0'] -> tk[version='>=8.6.8,<8.7.0a0']\n",
            "cryptography==2.8=py37h1ba5d50_0 -> python[version='>=3.7,<3.8.0a0'] -> tk[version='>=8.6.8,<8.7.0a0']\n",
            "pyopenssl==19.1.0=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> tk[version='>=8.6.8,<8.7.0a0']\n",
            "numpy-base -> python[version='>=3.7,<3.8.0a0'] -> tk[version='>=8.6.8,<8.7.0a0']\n",
            "pysocks==1.7.1=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> tk[version='>=8.6.8,<8.7.0a0']\n",
            "python==3.7.6=h0371630_2 -> tk[version='>=8.6.8,<8.7.0a0']\n",
            "pandas -> python[version='>=3.7,<3.8.0a0'] -> tk[version='>=8.6.8,<8.7.0a0']\n",
            "tk==8.6.8=hbc83047_0\n",
            "pytz -> python -> tk[version='>=8.6.8,<8.7.0a0']\n",
            "cffi==1.14.0=py37h2e261b9_0 -> python[version='>=3.7,<3.8.0a0'] -> tk[version='>=8.6.8,<8.7.0a0']\n",
            "mkl_random -> python[version='>=3.7,<3.8.0a0'] -> tk[version='>=8.6.8,<8.7.0a0']\n",
            "pyparsing -> python[version='>=3.6'] -> tk[version='>=8.6.8,<8.7.0a0']\n",
            "chardet==3.0.4=py37_1003 -> python[version='>=3.7,<3.8.0a0'] -> tk[version='>=8.6.8,<8.7.0a0']\n",
            "wheel==0.34.2=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> tk[version='>=8.6.8,<8.7.0a0']\n",
            "pycparser==2.19=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> tk[version='>=8.6.8,<8.7.0a0']\n",
            "conda-package-handling==1.6.0=py37h7b6447c_0 -> python[version='>=3.7,<3.8.0a0'] -> tk[version='>=8.6.8,<8.7.0a0']\n",
            "conda==4.8.2=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> tk[version='>=8.6.8,<8.7.0a0']\n",
            "mkl_fft -> python[version='>=3.7,<3.8.0a0'] -> tk[version='>=8.6.8,<8.7.0a0']\n",
            "setuptools==45.2.0=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> tk[version='>=8.6.8,<8.7.0a0']\n",
            "rdkit -> pillow -> tk[version='>=8.6.8,<8.7.0a0']\n",
            "packaging -> python[version='>=3.6'] -> tk[version='>=8.6.8,<8.7.0a0']\n",
            "ruamel_yaml==0.15.87=py37h7b6447c_0 -> python[version='>=3.7,<3.8.0a0'] -> tk[version='>=8.6.8,<8.7.0a0']\n",
            "urllib3==1.25.8=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> tk[version='>=8.6.8,<8.7.0a0']\n",
            "numexpr -> python[version='>=3.7,<3.8.0a0'] -> tk[version='>=8.6.8,<8.7.0a0']\n",
            "py-boost -> python[version='>=3.7,<3.8.0a0'] -> tk[version='>=8.6.8,<8.7.0a0']\n",
            "pillow -> tk\n",
            "\n",
            "Package libgcc-ng conflicts for:\n",
            "numexpr -> python[version='>=3.7,<3.8.0a0'] -> libgcc-ng[version='>=7.3.0']\n",
            "bottleneck -> libgcc-ng[version='>=7.5.0']\n",
            "pip==20.0.2=py37_1 -> python[version='>=3.7,<3.8.0a0'] -> libgcc-ng[version='>=7.3.0']\n",
            "cffi==1.14.0=py37h2e261b9_0 -> libffi[version='>=3.2.1,<4.0a0'] -> libgcc-ng[version='>=7.2.0']\n",
            "urllib3==1.25.8=py37_0 -> cryptography[version='>=1.3.4'] -> libgcc-ng[version='>=7.3.0']\n",
            "cffi==1.14.0=py37h2e261b9_0 -> libgcc-ng[version='>=7.3.0']\n",
            "libwebp -> giflib[version='>=5.2.1,<5.3.0a0'] -> libgcc-ng[version='>=7.3.0']\n",
            "cryptography==2.8=py37h1ba5d50_0 -> libgcc-ng[version='>=7.3.0']\n",
            "openssl==1.1.1d=h7b6447c_4 -> libgcc-ng[version='>=7.3.0']\n",
            "libffi==3.2.1=hd88cf55_4 -> libgcc-ng[version='>=7.2.0']\n",
            "pandas -> python[version='>=3.7,<3.8.0a0'] -> libgcc-ng[version='>=7.3.0']\n",
            "readline==7.0=h7b6447c_5 -> libgcc-ng[version='>=7.3.0']\n",
            "numpy -> python[version='>=3.7,<3.8.0a0'] -> libgcc-ng[version='>=7.3.0']\n",
            "lcms2 -> libgcc-ng[version='>=7.3.0']\n",
            "python-dateutil -> python -> libgcc-ng[version='>=7.3.0']\n",
            "ncurses==6.2=he6710b0_0 -> libgcc-ng[version='>=7.3.0']\n",
            "conda-package-handling==1.6.0=py37h7b6447c_0 -> libgcc-ng[version='>=7.3.0']\n",
            "yaml==0.1.7=had09818_2 -> libgcc-ng[version='>=7.2.0']\n",
            "pycparser==2.19=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> libgcc-ng[version='>=7.3.0']\n",
            "numpy -> libgcc-ng[version='>=7.5.0']\n",
            "bzip2 -> libgcc-ng[version='>=7.3.0']\n",
            "zstd -> libgcc-ng[version='>=7.3.0']\n",
            "freetype -> libgcc-ng[version='>=7.5.0']\n",
            "ruamel_yaml==0.15.87=py37h7b6447c_0 -> libgcc-ng[version='>=7.3.0']\n",
            "libxml2 -> icu[version='>=58.2,<59.0a0'] -> libgcc-ng[version='>=7.3.0|>=7.5.0']\n",
            "cairo -> freetype[version='>=2.10.4,<3.0a0'] -> libgcc-ng[version='>=7.5.0']\n",
            "pyparsing -> python[version='>=3.6'] -> libgcc-ng[version='>=7.3.0']\n",
            "chardet==3.0.4=py37_1003 -> python[version='>=3.7,<3.8.0a0'] -> libgcc-ng[version='>=7.3.0']\n",
            "libedit==3.1.20181209=hc058e9b_0 -> libgcc-ng[version='>=7.3.0']\n",
            "icu -> libgcc-ng[version='>=7.3.0']\n",
            "cairo -> libgcc-ng[version='>=7.3.0']\n",
            "numexpr -> libgcc-ng[version='>=7.5.0']\n",
            "pillow -> libgcc-ng[version='>=7.5.0']\n",
            "fontconfig -> freetype[version='>=2.10.4,<3.0a0'] -> libgcc-ng[version='>=7.5.0|>=9.3.0']\n",
            "mkl_random -> libgcc-ng[version='>=7.5.0']\n",
            "certifi==2019.11.28=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> libgcc-ng[version='>=7.3.0']\n",
            "numpy-base -> libgcc-ng[version='>=7.5.0']\n",
            "requests==2.22.0=py37_1 -> python[version='>=3.7,<3.8.0a0'] -> libgcc-ng[version='>=7.3.0']\n",
            "libwebp-base -> libgcc-ng[version='>=7.5.0']\n",
            "six==1.14.0=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> libgcc-ng[version='>=7.3.0']\n",
            "ruamel_yaml==0.15.87=py37h7b6447c_0 -> yaml[version='>=0.1.7,<0.2.0a0'] -> libgcc-ng[version='>=7.2.0']\n",
            "python==3.7.6=h0371630_2 -> libffi[version='>=3.2.1,<4.0a0'] -> libgcc-ng[version='>=7.2.0|>=7.5.0']\n",
            "cryptography==2.8=py37h1ba5d50_0 -> openssl[version='>=1.1.1d,<1.1.2a'] -> libgcc-ng[version='>=7.5.0']\n",
            "rdkit -> freetype[version='>=2.10.3,<3.0a0'] -> libgcc-ng[version='>=7.5.0']\n",
            "zlib==1.2.11=h7b6447c_3 -> libgcc-ng[version='>=7.3.0']\n",
            "mkl-service -> python[version='>=3.7,<3.8.0a0'] -> libgcc-ng[version='>=7.3.0']\n",
            "numpy-base -> python[version='>=3.7,<3.8.0a0'] -> libgcc-ng[version='>=7.3.0']\n",
            "mkl_fft -> libgcc-ng[version='>=7.5.0']\n",
            "glib -> libgcc-ng[version='>=7.5.0']\n",
            "lz4-c -> libgcc-ng[version='>=7.5.0']\n",
            "libxml2 -> libgcc-ng[version='>=9.3.0']\n",
            "libxcb -> libgcc-ng[version='>=7.5.0']\n",
            "jpeg -> libgcc-ng[version='>=7.5.0']\n",
            "bottleneck -> python[version='>=3.7,<3.8.0a0'] -> libgcc-ng[version='>=7.3.0']\n",
            "mkl-service -> libgcc-ng[version='>=7.5.0']\n",
            "packaging -> python[version='>=3.6'] -> libgcc-ng[version='>=7.3.0']\n",
            "pandas -> libgcc-ng[version='>=7.5.0']\n",
            "pycosat==0.6.3=py37h7b6447c_0 -> libgcc-ng[version='>=7.3.0']\n",
            "libboost -> xz[version='>=5.2.5,<6.0a0'] -> libgcc-ng[version='>=7.5.0']\n",
            "sqlite==3.31.1=h7b6447c_0 -> libgcc-ng[version='>=7.3.0']\n",
            "libuuid -> libgcc-ng[version='>=7.5.0']\n",
            "wheel==0.34.2=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> libgcc-ng[version='>=7.3.0']\n",
            "conda==4.8.2=py37_0 -> conda-package-handling[version='>=1.3.0'] -> libgcc-ng[version='>=7.3.0']\n",
            "libgcc-ng==9.1.0=hdf63c60_0\n",
            "pixman -> libgcc-ng[version='>=7.5.0']\n",
            "fontconfig -> libgcc-ng[version='>=7.3.0']\n",
            "pyopenssl==19.1.0=py37_0 -> cryptography[version='>=2.8'] -> libgcc-ng[version='>=7.3.0']\n",
            "libtiff -> libgcc-ng[version='>=7.3.0']\n",
            "libboost -> libgcc-ng[version='>=7.3.0']\n",
            "tqdm==4.42.1=py_0 -> python -> libgcc-ng[version='>=7.3.0']\n",
            "giflib -> libgcc-ng[version='>=7.3.0']\n",
            "pytz -> python -> libgcc-ng[version='>=7.3.0']\n",
            "mkl_random -> python[version='>=3.7,<3.8.0a0'] -> libgcc-ng[version='>=7.3.0']\n",
            "pillow -> lcms2[version='>=2.12,<3.0a0'] -> libgcc-ng[version='>=7.3.0']\n",
            "python==3.7.6=h0371630_2 -> libgcc-ng[version='>=7.3.0']\n",
            "lcms2 -> jpeg[version='>=9b,<10a'] -> libgcc-ng[version='>=7.5.0']\n",
            "glib -> libffi[version='>=3.3'] -> libgcc-ng[version='>=7.3.0']\n",
            "freetype -> libpng[version='>=1.6.37,<1.7.0a0'] -> libgcc-ng[version='>=7.3.0']\n",
            "libpng -> libgcc-ng[version='>=7.3.0']\n",
            "xz==5.2.4=h14c3975_4 -> libgcc-ng[version='>=7.2.0']\n",
            "idna==2.8=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> libgcc-ng[version='>=7.3.0']\n",
            "pcre -> libgcc-ng[version='>=7.5.0']\n",
            "libwebp -> libgcc-ng[version='>=7.5.0']\n",
            "libtiff -> jpeg[version='>=9b,<10a'] -> libgcc-ng[version='>=7.5.0']\n",
            "py-boost -> libgcc-ng[version='>=7.3.0']\n",
            "mkl_fft -> python[version='>=3.7,<3.8.0a0'] -> libgcc-ng[version='>=7.3.0']\n",
            "pysocks==1.7.1=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> libgcc-ng[version='>=7.3.0']\n",
            "tk==8.6.8=hbc83047_0 -> libgcc-ng[version='>=7.3.0']\n",
            "setuptools==45.2.0=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> libgcc-ng[version='>=7.3.0']\n",
            "rdkit -> libgcc-ng[version='>=7.3.0']\n",
            "zstd -> lz4-c[version='>=1.9.3,<1.10.0a0'] -> libgcc-ng[version='>=7.5.0']\n",
            "\n",
            "Package xz conflicts for:\n",
            "py-boost -> libboost[version='>=1.73.0,<1.73.1.0a0',build=h3ff78a5_11] -> xz[version='>=5.2.4,<6.0a0|>=5.2.5,<6.0a0']\n",
            "requests==2.22.0=py37_1 -> python[version='>=3.7,<3.8.0a0'] -> xz[version='>=5.2.4,<6.0a0']\n",
            "numexpr -> python[version='>=3.7,<3.8.0a0'] -> xz[version='>=5.2.4,<6.0a0']\n",
            "mkl_fft -> python[version='>=3.7,<3.8.0a0'] -> xz[version='>=5.2.4,<6.0a0']\n",
            "pycparser==2.19=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> xz[version='>=5.2.4,<6.0a0']\n",
            "libwebp -> libtiff[version='>=4.1.0,<5.0a0'] -> xz[version='>=5.2.5,<6.0a0']\n",
            "conda-package-handling==1.6.0=py37h7b6447c_0 -> python[version='>=3.7,<3.8.0a0'] -> xz[version='>=5.2.4,<6.0a0']\n",
            "urllib3==1.25.8=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> xz[version='>=5.2.4,<6.0a0']\n",
            "six==1.14.0=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> xz[version='>=5.2.4,<6.0a0']\n",
            "mkl-service -> python[version='>=3.7,<3.8.0a0'] -> xz[version='>=5.2.4,<6.0a0']\n",
            "pandas -> python[version='>=3.7,<3.8.0a0'] -> xz[version='>=5.2.4,<6.0a0']\n",
            "mkl_random -> python[version='>=3.7,<3.8.0a0'] -> xz[version='>=5.2.4,<6.0a0']\n",
            "xz==5.2.4=h14c3975_4\n",
            "numpy-base -> python[version='>=3.7,<3.8.0a0'] -> xz[version='>=5.2.4,<6.0a0']\n",
            "packaging -> python[version='>=3.6'] -> xz[version='>=5.2.4,<6.0a0']\n",
            "conda==4.8.2=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> xz[version='>=5.2.4,<6.0a0']\n",
            "idna==2.8=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> xz[version='>=5.2.4,<6.0a0']\n",
            "numpy -> python[version='>=3.7,<3.8.0a0'] -> xz[version='>=5.2.4,<6.0a0']\n",
            "pysocks==1.7.1=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> xz[version='>=5.2.4,<6.0a0']\n",
            "pyopenssl==19.1.0=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> xz[version='>=5.2.4,<6.0a0']\n",
            "pyparsing -> python[version='>=3.6'] -> xz[version='>=5.2.4,<6.0a0']\n",
            "bottleneck -> python[version='>=3.7,<3.8.0a0'] -> xz[version='>=5.2.4,<6.0a0']\n",
            "cryptography==2.8=py37h1ba5d50_0 -> python[version='>=3.7,<3.8.0a0'] -> xz[version='>=5.2.4,<6.0a0']\n",
            "libxml2 -> xz[version='>=5.2.5,<6.0a0']\n",
            "python-dateutil -> python -> xz[version='>=5.2.4,<6.0a0']\n",
            "python==3.7.6=h0371630_2 -> xz[version='>=5.2.4,<6.0a0']\n",
            "libboost -> xz[version='>=5.2.5,<6.0a0']\n",
            "cffi==1.14.0=py37h2e261b9_0 -> python[version='>=3.7,<3.8.0a0'] -> xz[version='>=5.2.4,<6.0a0']\n",
            "pillow -> libtiff[version='>=4.1.0,<5.0a0'] -> xz[version='>=5.2.4,<6.0a0|>=5.2.5,<6.0a0']\n",
            "rdkit -> libboost[version='>=1.73.0,<1.74.0a0'] -> xz[version='>=5.2.4,<6.0a0|>=5.2.5,<6.0a0']\n",
            "tqdm==4.42.1=py_0 -> python -> xz[version='>=5.2.4,<6.0a0']\n",
            "setuptools==45.2.0=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> xz[version='>=5.2.4,<6.0a0']\n",
            "chardet==3.0.4=py37_1003 -> python[version='>=3.7,<3.8.0a0'] -> xz[version='>=5.2.4,<6.0a0']\n",
            "wheel==0.34.2=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> xz[version='>=5.2.4,<6.0a0']\n",
            "pycosat==0.6.3=py37h7b6447c_0 -> python[version='>=3.7,<3.8.0a0'] -> xz[version='>=5.2.4,<6.0a0']\n",
            "ruamel_yaml==0.15.87=py37h7b6447c_0 -> python[version='>=3.7,<3.8.0a0'] -> xz[version='>=5.2.4,<6.0a0']\n",
            "pytz -> python -> xz[version='>=5.2.4,<6.0a0']\n",
            "fontconfig -> libxml2[version='>=2.9.10,<2.10.0a0'] -> xz[version='>=5.2.5,<6.0a0']\n",
            "certifi==2019.11.28=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> xz[version='>=5.2.4,<6.0a0']\n",
            "lcms2 -> libtiff[version='>=4.1.0,<5.0a0'] -> xz[version='>=5.2.5,<6.0a0']\n",
            "zstd -> xz[version='>=5.2.5,<6.0a0']\n",
            "pip==20.0.2=py37_1 -> python[version='>=3.7,<3.8.0a0'] -> xz[version='>=5.2.4,<6.0a0']\n",
            "libtiff -> xz[version='>=5.2.5,<6.0a0']\n",
            "\n",
            "Package blas conflicts for:\n",
            "numexpr -> blas==1.0=mkl\n",
            "mkl_random -> numpy[version='>=1.16,<2.0a0'] -> blas==1.0=mkl\n",
            "bottleneck -> numpy[version='>=1.16.6,<2.0a0'] -> blas==1.0=mkl\n",
            "numpy -> blas==1.0=mkl\n",
            "pandas -> numexpr[version='>=2.7.0'] -> blas==1.0=mkl\n",
            "mkl_fft -> blas==1.0=mkl\n",
            "rdkit -> numpy[version='>=1.12'] -> blas==1.0=mkl\n",
            "numpy-base -> blas==1.0=mkl\n",
            "mkl_random -> blas=[build=mkl]\n",
            "numpy -> mkl_random -> blas=[build=mkl]\n",
            "blas\n",
            "\n",
            "Package numpy-base conflicts for:\n",
            "numexpr -> numpy[version='>=1.16.6,<2.0a0'] -> numpy-base==1.21.5=py37hf524024_2\n",
            "rdkit -> numpy[version='>=1.12'] -> numpy-base==1.21.5=py37hf524024_2\n",
            "pandas -> numpy[version='>=1.19.2,<2.0a0'] -> numpy-base==1.21.5=py37hf524024_2\n",
            "mkl_fft -> numpy[version='>=1.16,<2.0a0'] -> numpy-base==1.21.5=py37hf524024_2\n",
            "bottleneck -> numpy[version='>=1.16.6,<2.0a0'] -> numpy-base==1.21.5=py37hf524024_2\n",
            "numpy-base\n",
            "numpy -> numpy-base==1.21.5=py37hf524024_2\n",
            "mkl_random -> numpy[version='>=1.16,<2.0a0'] -> numpy-base==1.21.5=py37hf524024_2\n",
            "\n",
            "Package bzip2 conflicts for:\n",
            "bzip2\n",
            "rdkit -> libboost[version='>=1.73.0,<1.74.0a0'] -> bzip2[version='>=1.0.8,<2.0a0']\n",
            "libboost -> bzip2[version='>=1.0.8,<2.0a0']\n",
            "py-boost -> libboost[version='>=1.73.0,<1.73.1.0a0',build=h3ff78a5_11] -> bzip2[version='>=1.0.8,<2.0a0']\n",
            "\n",
            "Package libstdcxx-ng conflicts for:\n",
            "pip==20.0.2=py37_1 -> python[version='>=3.7,<3.8.0a0'] -> libstdcxx-ng[version='>=7.3.0']\n",
            "conda==4.8.2=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> libstdcxx-ng[version='>=7.3.0']\n",
            "glib -> libstdcxx-ng[version='>=7.5.0']\n",
            "urllib3==1.25.8=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> libstdcxx-ng[version='>=7.3.0']\n",
            "icu -> libstdcxx-ng[version='>=7.3.0']\n",
            "numexpr -> libstdcxx-ng[version='>=7.5.0']\n",
            "libtiff -> libstdcxx-ng[version='>=7.3.0']\n",
            "mkl_random -> python[version='>=3.7,<3.8.0a0'] -> libstdcxx-ng[version='>=7.3.0']\n",
            "cairo -> libstdcxx-ng[version='>=7.3.0']\n",
            "ruamel_yaml==0.15.87=py37h7b6447c_0 -> python[version='>=3.7,<3.8.0a0'] -> libstdcxx-ng[version='>=7.3.0']\n",
            "libedit==3.1.20181209=hc058e9b_0 -> ncurses[version='>=6.1,<7.0a0'] -> libstdcxx-ng[version='>=7.3.0']\n",
            "zstd -> lz4-c[version='>=1.9.3,<1.10.0a0'] -> libstdcxx-ng[version='>=7.5.0']\n",
            "readline==7.0=h7b6447c_5 -> ncurses[version='>=6.1,<7.0a0'] -> libstdcxx-ng[version='>=7.3.0']\n",
            "rdkit -> libstdcxx-ng[version='>=7.3.0']\n",
            "ncurses==6.2=he6710b0_0 -> libstdcxx-ng[version='>=7.3.0']\n",
            "python-dateutil -> python -> libstdcxx-ng[version='>=7.3.0']\n",
            "cryptography==2.8=py37h1ba5d50_0 -> python[version='>=3.7,<3.8.0a0'] -> libstdcxx-ng[version='>=7.3.0']\n",
            "certifi==2019.11.28=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> libstdcxx-ng[version='>=7.3.0']\n",
            "idna==2.8=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> libstdcxx-ng[version='>=7.3.0']\n",
            "libffi==3.2.1=hd88cf55_4 -> libstdcxx-ng[version='>=7.2.0']\n",
            "setuptools==45.2.0=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> libstdcxx-ng[version='>=7.3.0']\n",
            "libwebp -> libtiff[version='>=4.1.0,<5.0a0'] -> libstdcxx-ng[version='>=7.3.0']\n",
            "numpy-base -> libstdcxx-ng[version='>=7.5.0']\n",
            "mkl_fft -> python[version='>=3.7,<3.8.0a0'] -> libstdcxx-ng[version='>=7.3.0']\n",
            "pillow -> libstdcxx-ng[version='>=7.5.0']\n",
            "numexpr -> python[version='>=3.7,<3.8.0a0'] -> libstdcxx-ng[version='>=7.3.0']\n",
            "pyopenssl==19.1.0=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> libstdcxx-ng[version='>=7.3.0']\n",
            "pytz -> python -> libstdcxx-ng[version='>=7.3.0']\n",
            "cairo -> glib[version='>=2.67.4,<3.0a0'] -> libstdcxx-ng[version='>=7.5.0']\n",
            "packaging -> python[version='>=3.6'] -> libstdcxx-ng[version='>=7.3.0']\n",
            "wheel==0.34.2=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> libstdcxx-ng[version='>=7.3.0']\n",
            "requests==2.22.0=py37_1 -> python[version='>=3.7,<3.8.0a0'] -> libstdcxx-ng[version='>=7.3.0']\n",
            "python==3.7.6=h0371630_2 -> libstdcxx-ng[version='>=7.3.0']\n",
            "pandas -> libstdcxx-ng[version='>=7.5.0']\n",
            "conda-package-handling==1.6.0=py37h7b6447c_0 -> python[version='>=3.7,<3.8.0a0'] -> libstdcxx-ng[version='>=7.3.0']\n",
            "mkl_fft -> libstdcxx-ng[version='>=7.5.0']\n",
            "rdkit -> numpy[version='>=1.12'] -> libstdcxx-ng[version='>=7.5.0']\n",
            "glib -> libffi[version='>=3.3'] -> libstdcxx-ng[version='>=7.3.0']\n",
            "libxml2 -> icu[version='>=58.2,<59.0a0'] -> libstdcxx-ng[version='>=7.3.0']\n",
            "pycosat==0.6.3=py37h7b6447c_0 -> python[version='>=3.7,<3.8.0a0'] -> libstdcxx-ng[version='>=7.3.0']\n",
            "tqdm==4.42.1=py_0 -> python -> libstdcxx-ng[version='>=7.3.0']\n",
            "libboost -> libstdcxx-ng[version='>=7.3.0']\n",
            "pyparsing -> python[version='>=3.6'] -> libstdcxx-ng[version='>=7.3.0']\n",
            "py-boost -> libstdcxx-ng[version='>=7.3.0']\n",
            "numpy -> python[version='>=3.7,<3.8.0a0'] -> libstdcxx-ng[version='>=7.3.0']\n",
            "zstd -> libstdcxx-ng[version='>=7.3.0']\n",
            "lz4-c -> libstdcxx-ng[version='>=7.5.0']\n",
            "pcre -> libstdcxx-ng[version='>=7.5.0']\n",
            "numpy-base -> python[version='>=3.7,<3.8.0a0'] -> libstdcxx-ng[version='>=7.3.0']\n",
            "chardet==3.0.4=py37_1003 -> python[version='>=3.7,<3.8.0a0'] -> libstdcxx-ng[version='>=7.3.0']\n",
            "six==1.14.0=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> libstdcxx-ng[version='>=7.3.0']\n",
            "python==3.7.6=h0371630_2 -> libffi[version='>=3.2.1,<4.0a0'] -> libstdcxx-ng[version='>=7.2.0']\n",
            "bottleneck -> numpy[version='>=1.16.6,<2.0a0'] -> libstdcxx-ng[version='>=7.3.0|>=7.5.0']\n",
            "pycparser==2.19=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> libstdcxx-ng[version='>=7.3.0']\n",
            "numpy -> libstdcxx-ng[version='>=7.5.0']\n",
            "pillow -> libtiff[version='>=4.1.0,<5.0a0'] -> libstdcxx-ng[version='>=7.3.0']\n",
            "mkl_random -> libstdcxx-ng[version='>=7.5.0']\n",
            "cffi==1.14.0=py37h2e261b9_0 -> libffi[version='>=3.2.1,<4.0a0'] -> libstdcxx-ng[version='>=7.2.0|>=7.3.0']\n",
            "mkl-service -> python[version='>=3.7,<3.8.0a0'] -> libstdcxx-ng[version='>=7.3.0']\n",
            "libstdcxx-ng==9.1.0=hdf63c60_0\n",
            "pysocks==1.7.1=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> libstdcxx-ng[version='>=7.3.0']\n",
            "lcms2 -> libtiff[version='>=4.1.0,<5.0a0'] -> libstdcxx-ng[version='>=7.3.0']\n",
            "pandas -> python[version='>=3.7,<3.8.0a0'] -> libstdcxx-ng[version='>=7.3.0']\n",
            "\n",
            "Package sqlite conflicts for:\n",
            "python==3.7.6=h0371630_2 -> sqlite[version='>=3.30.1,<4.0a0']\n",
            "pysocks==1.7.1=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.30.1,<4.0a0']\n",
            "numpy-base -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.30.1,<4.0a0']\n",
            "urllib3==1.25.8=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.30.1,<4.0a0']\n",
            "py-boost -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.30.1,<4.0a0']\n",
            "mkl_fft -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.30.1,<4.0a0']\n",
            "pytz -> python -> sqlite[version='>=3.30.1,<4.0a0']\n",
            "cffi==1.14.0=py37h2e261b9_0 -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.30.1,<4.0a0']\n",
            "idna==2.8=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.30.1,<4.0a0']\n",
            "numexpr -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.30.1,<4.0a0']\n",
            "python-dateutil -> python -> sqlite[version='>=3.30.1,<4.0a0']\n",
            "tqdm==4.42.1=py_0 -> python -> sqlite[version='>=3.30.1,<4.0a0']\n",
            "chardet==3.0.4=py37_1003 -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.30.1,<4.0a0']\n",
            "pyparsing -> python[version='>=3.6'] -> sqlite[version='>=3.30.1,<4.0a0']\n",
            "bottleneck -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.30.1,<4.0a0']\n",
            "conda-package-handling==1.6.0=py37h7b6447c_0 -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.30.1,<4.0a0']\n",
            "pycosat==0.6.3=py37h7b6447c_0 -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.30.1,<4.0a0']\n",
            "wheel==0.34.2=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.30.1,<4.0a0']\n",
            "numpy -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.30.1,<4.0a0']\n",
            "ruamel_yaml==0.15.87=py37h7b6447c_0 -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.30.1,<4.0a0']\n",
            "rdkit -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.30.1,<4.0a0']\n",
            "mkl-service -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.30.1,<4.0a0']\n",
            "six==1.14.0=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.30.1,<4.0a0']\n",
            "pip==20.0.2=py37_1 -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.30.1,<4.0a0']\n",
            "certifi==2019.11.28=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.30.1,<4.0a0']\n",
            "mkl_random -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.30.1,<4.0a0']\n",
            "setuptools==45.2.0=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.30.1,<4.0a0']\n",
            "pycparser==2.19=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.30.1,<4.0a0']\n",
            "cryptography==2.8=py37h1ba5d50_0 -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.30.1,<4.0a0']\n",
            "pyopenssl==19.1.0=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.30.1,<4.0a0']\n",
            "requests==2.22.0=py37_1 -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.30.1,<4.0a0']\n",
            "packaging -> python[version='>=3.6'] -> sqlite[version='>=3.30.1,<4.0a0']\n",
            "pandas -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.30.1,<4.0a0']\n",
            "conda==4.8.2=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.30.1,<4.0a0']\n",
            "pillow -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.30.1,<4.0a0']\n",
            "sqlite==3.31.1=h7b6447c_0\n",
            "\n",
            "Package _openmp_mutex conflicts for:\n",
            "mkl_fft -> libgcc-ng[version='>=7.5.0'] -> _openmp_mutex\n",
            "numpy-base -> libgcc-ng[version='>=7.5.0'] -> _openmp_mutex\n",
            "libtiff -> libgcc-ng[version='>=7.3.0'] -> _openmp_mutex\n",
            "libuuid -> libgcc-ng[version='>=7.5.0'] -> _openmp_mutex\n",
            "zstd -> libgcc-ng[version='>=7.3.0'] -> _openmp_mutex\n",
            "libxcb -> libgcc-ng[version='>=7.5.0'] -> _openmp_mutex\n",
            "libxml2 -> libgcc-ng[version='>=9.3.0'] -> _openmp_mutex\n",
            "xz==5.2.4=h14c3975_4 -> libgcc-ng[version='>=7.2.0'] -> _openmp_mutex\n",
            "pandas -> libgcc-ng[version='>=7.5.0'] -> _openmp_mutex\n",
            "libpng -> libgcc-ng[version='>=7.3.0'] -> _openmp_mutex\n",
            "conda-package-handling==1.6.0=py37h7b6447c_0 -> libgcc-ng[version='>=7.3.0'] -> _openmp_mutex\n",
            "yaml==0.1.7=had09818_2 -> libgcc-ng[version='>=7.2.0'] -> _openmp_mutex\n",
            "pillow -> libgcc-ng[version='>=7.5.0'] -> _openmp_mutex\n",
            "pixman -> libgcc-ng[version='>=7.5.0'] -> _openmp_mutex\n",
            "lcms2 -> libgcc-ng[version='>=7.3.0'] -> _openmp_mutex\n",
            "pcre -> libgcc-ng[version='>=7.5.0'] -> _openmp_mutex\n",
            "libwebp-base -> libgcc-ng[version='>=7.5.0'] -> _openmp_mutex\n",
            "rdkit -> libgcc-ng[version='>=7.3.0'] -> _openmp_mutex\n",
            "bottleneck -> libgcc-ng[version='>=7.5.0'] -> _openmp_mutex\n",
            "fontconfig -> libgcc-ng[version='>=7.3.0'] -> _openmp_mutex\n",
            "lz4-c -> libgcc-ng[version='>=7.5.0'] -> _openmp_mutex\n",
            "_openmp_mutex\n",
            "numexpr -> libgcc-ng[version='>=7.5.0'] -> _openmp_mutex\n",
            "openssl==1.1.1d=h7b6447c_4 -> libgcc-ng[version='>=7.3.0'] -> _openmp_mutex\n",
            "numpy -> libgcc-ng[version='>=7.5.0'] -> _openmp_mutex\n",
            "cryptography==2.8=py37h1ba5d50_0 -> libgcc-ng[version='>=7.3.0'] -> _openmp_mutex\n",
            "mkl_random -> libgcc-ng[version='>=7.5.0'] -> _openmp_mutex\n",
            "libffi==3.2.1=hd88cf55_4 -> libgcc-ng[version='>=7.2.0'] -> _openmp_mutex\n",
            "zlib==1.2.11=h7b6447c_3 -> libgcc-ng[version='>=7.3.0'] -> _openmp_mutex\n",
            "sqlite==3.31.1=h7b6447c_0 -> libgcc-ng[version='>=7.3.0'] -> _openmp_mutex\n",
            "bzip2 -> libgcc-ng[version='>=7.3.0'] -> _openmp_mutex\n",
            "glib -> libgcc-ng[version='>=7.5.0'] -> _openmp_mutex\n",
            "py-boost -> libgcc-ng[version='>=7.3.0'] -> _openmp_mutex\n",
            "mkl-service -> libgcc-ng[version='>=7.5.0'] -> _openmp_mutex\n",
            "libedit==3.1.20181209=hc058e9b_0 -> libgcc-ng[version='>=7.3.0'] -> _openmp_mutex\n",
            "ncurses==6.2=he6710b0_0 -> libgcc-ng[version='>=7.3.0'] -> _openmp_mutex\n",
            "libwebp -> libgcc-ng[version='>=7.5.0'] -> _openmp_mutex\n",
            "cairo -> libgcc-ng[version='>=7.3.0'] -> _openmp_mutex\n",
            "cffi==1.14.0=py37h2e261b9_0 -> libgcc-ng[version='>=7.3.0'] -> _openmp_mutex\n",
            "freetype -> libgcc-ng[version='>=7.5.0'] -> _openmp_mutex\n",
            "pycosat==0.6.3=py37h7b6447c_0 -> libgcc-ng[version='>=7.3.0'] -> _openmp_mutex\n",
            "python==3.7.6=h0371630_2 -> libgcc-ng[version='>=7.3.0'] -> _openmp_mutex\n",
            "tk==8.6.8=hbc83047_0 -> libgcc-ng[version='>=7.3.0'] -> _openmp_mutex\n",
            "icu -> libgcc-ng[version='>=7.3.0'] -> _openmp_mutex\n",
            "giflib -> libgcc-ng[version='>=7.3.0'] -> _openmp_mutex\n",
            "libboost -> libgcc-ng[version='>=7.3.0'] -> _openmp_mutex\n",
            "ruamel_yaml==0.15.87=py37h7b6447c_0 -> libgcc-ng[version='>=7.3.0'] -> _openmp_mutex\n",
            "readline==7.0=h7b6447c_5 -> libgcc-ng[version='>=7.3.0'] -> _openmp_mutex\n",
            "jpeg -> libgcc-ng[version='>=7.5.0'] -> _openmp_mutex\n",
            "\n",
            "Package zlib conflicts for:\n",
            "bottleneck -> python[version='>=3.7,<3.8.0a0'] -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "zstd -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "py-boost -> libboost[version='>=1.73.0,<1.73.1.0a0',build=h3ff78a5_11] -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "tk==8.6.8=hbc83047_0 -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "python==3.7.6=h0371630_2 -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "numexpr -> python[version='>=3.7,<3.8.0a0'] -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "mkl_fft -> python[version='>=3.7,<3.8.0a0'] -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "pycparser==2.19=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "cairo -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "packaging -> python[version='>=3.6'] -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "pytz -> python -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "idna==2.8=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "lcms2 -> libtiff[version='>=4.1.0,<5.0a0'] -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "zlib==1.2.11=h7b6447c_3\n",
            "libtiff -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "pyopenssl==19.1.0=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "requests==2.22.0=py37_1 -> python[version='>=3.7,<3.8.0a0'] -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "wheel==0.34.2=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "libboost -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "pysocks==1.7.1=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "cffi==1.14.0=py37h2e261b9_0 -> python[version='>=3.7,<3.8.0a0'] -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "pycosat==0.6.3=py37h7b6447c_0 -> python[version='>=3.7,<3.8.0a0'] -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "six==1.14.0=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "pandas -> python[version='>=3.7,<3.8.0a0'] -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "conda==4.8.2=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "ruamel_yaml==0.15.87=py37h7b6447c_0 -> python[version='>=3.7,<3.8.0a0'] -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "libwebp -> libpng[version='>=1.6.37,<1.7.0a0'] -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "fontconfig -> freetype[version='>=2.10.4,<3.0a0'] -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "pip==20.0.2=py37_1 -> python[version='>=3.7,<3.8.0a0'] -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "libxml2 -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "glib -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "libpng -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "pyparsing -> python[version='>=3.6'] -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "numpy -> python[version='>=3.7,<3.8.0a0'] -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "python-dateutil -> python -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "mkl-service -> python[version='>=3.7,<3.8.0a0'] -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "numpy-base -> python[version='>=3.7,<3.8.0a0'] -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "chardet==3.0.4=py37_1003 -> python[version='>=3.7,<3.8.0a0'] -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "setuptools==45.2.0=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "certifi==2019.11.28=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "freetype -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "pillow -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "urllib3==1.25.8=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "tqdm==4.42.1=py_0 -> python -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "conda-package-handling==1.6.0=py37h7b6447c_0 -> python[version='>=3.7,<3.8.0a0'] -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "cryptography==2.8=py37h1ba5d50_0 -> python[version='>=3.7,<3.8.0a0'] -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "rdkit -> cairo[version='>=1.14.12,<2.0a0'] -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "mkl_random -> python[version='>=3.7,<3.8.0a0'] -> zlib[version='>=1.2.11,<1.3.0a0']\n",
            "\n",
            "Package ncurses conflicts for:\n",
            "cryptography==2.8=py37h1ba5d50_0 -> python[version='>=3.7,<3.8.0a0'] -> ncurses[version='>=6.1,<7.0a0']\n",
            "packaging -> python[version='>=3.6'] -> ncurses[version='>=6.1,<7.0a0']\n",
            "mkl_random -> python[version='>=3.7,<3.8.0a0'] -> ncurses[version='>=6.1,<7.0a0']\n",
            "pip==20.0.2=py37_1 -> python[version='>=3.7,<3.8.0a0'] -> ncurses[version='>=6.1,<7.0a0']\n",
            "pandas -> python[version='>=3.7,<3.8.0a0'] -> ncurses[version='>=6.1,<7.0a0']\n",
            "pycparser==2.19=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> ncurses[version='>=6.1,<7.0a0']\n",
            "pyopenssl==19.1.0=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> ncurses[version='>=6.1,<7.0a0']\n",
            "pycosat==0.6.3=py37h7b6447c_0 -> python[version='>=3.7,<3.8.0a0'] -> ncurses[version='>=6.1,<7.0a0']\n",
            "idna==2.8=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> ncurses[version='>=6.1,<7.0a0']\n",
            "rdkit -> python[version='>=3.7,<3.8.0a0'] -> ncurses[version='>=6.1,<7.0a0']\n",
            "pillow -> python[version='>=3.7,<3.8.0a0'] -> ncurses[version='>=6.1,<7.0a0']\n",
            "numpy-base -> python[version='>=3.7,<3.8.0a0'] -> ncurses[version='>=6.1,<7.0a0']\n",
            "ncurses==6.2=he6710b0_0\n",
            "six==1.14.0=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> ncurses[version='>=6.1,<7.0a0']\n",
            "mkl_fft -> python[version='>=3.7,<3.8.0a0'] -> ncurses[version='>=6.1,<7.0a0']\n",
            "conda==4.8.2=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> ncurses[version='>=6.1,<7.0a0']\n",
            "setuptools==45.2.0=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> ncurses[version='>=6.1,<7.0a0']\n",
            "ruamel_yaml==0.15.87=py37h7b6447c_0 -> python[version='>=3.7,<3.8.0a0'] -> ncurses[version='>=6.1,<7.0a0']\n",
            "readline==7.0=h7b6447c_5 -> ncurses[version='>=6.1,<7.0a0']\n",
            "py-boost -> python[version='>=3.7,<3.8.0a0'] -> ncurses[version='>=6.1,<7.0a0']\n",
            "urllib3==1.25.8=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> ncurses[version='>=6.1,<7.0a0']\n",
            "certifi==2019.11.28=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> ncurses[version='>=6.1,<7.0a0']\n",
            "chardet==3.0.4=py37_1003 -> python[version='>=3.7,<3.8.0a0'] -> ncurses[version='>=6.1,<7.0a0']\n",
            "pyparsing -> python[version='>=3.6'] -> ncurses[version='>=6.1,<7.0a0']\n",
            "conda-package-handling==1.6.0=py37h7b6447c_0 -> python[version='>=3.7,<3.8.0a0'] -> ncurses[version='>=6.1,<7.0a0']\n",
            "pysocks==1.7.1=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> ncurses[version='>=6.1,<7.0a0']\n",
            "libedit==3.1.20181209=hc058e9b_0 -> ncurses[version='>=6.1,<7.0a0']\n",
            "tqdm==4.42.1=py_0 -> python -> ncurses[version='>=6.1,<7.0a0']\n",
            "bottleneck -> python[version='>=3.7,<3.8.0a0'] -> ncurses[version='>=6.1,<7.0a0']\n",
            "requests==2.22.0=py37_1 -> python[version='>=3.7,<3.8.0a0'] -> ncurses[version='>=6.1,<7.0a0']\n",
            "cffi==1.14.0=py37h2e261b9_0 -> python[version='>=3.7,<3.8.0a0'] -> ncurses[version='>=6.1,<7.0a0']\n",
            "wheel==0.34.2=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> ncurses[version='>=6.1,<7.0a0']\n",
            "numexpr -> python[version='>=3.7,<3.8.0a0'] -> ncurses[version='>=6.1,<7.0a0']\n",
            "mkl-service -> python[version='>=3.7,<3.8.0a0'] -> ncurses[version='>=6.1,<7.0a0']\n",
            "python==3.7.6=h0371630_2 -> ncurses[version='>=6.1,<7.0a0']\n",
            "pytz -> python -> ncurses[version='>=6.1,<7.0a0']\n",
            "numpy -> python[version='>=3.7,<3.8.0a0'] -> ncurses[version='>=6.1,<7.0a0']\n",
            "sqlite==3.31.1=h7b6447c_0 -> libedit[version='>=3.1.20181209,<3.2.0a0'] -> ncurses[version='>=6.1,<7.0a0']\n",
            "python-dateutil -> python -> ncurses[version='>=6.1,<7.0a0']\n",
            "\n",
            "Package python conflicts for:\n",
            "mkl_fft -> python[version='>=3.7,<3.8.0a0']\n",
            "cffi==1.14.0=py37h2e261b9_0 -> python[version='>=3.7,<3.8.0a0']\n",
            "pytz -> python\n",
            "pandas -> python[version='>=3.7,<3.8.0a0']\n",
            "tqdm==4.42.1=py_0 -> python\n",
            "pillow -> python[version='>=3.7,<3.8.0a0']\n",
            "pysocks==1.7.1=py37_0 -> python[version='>=3.7,<3.8.0a0']\n",
            "conda-package-handling==1.6.0=py37h7b6447c_0 -> tqdm -> python\n",
            "pip==20.0.2=py37_1 -> python[version='>=3.7,<3.8.0a0']\n",
            "python-dateutil -> six[version='>=1.5'] -> python[version='>=3.7,<3.8.0a0']\n",
            "python-dateutil -> python\n",
            "conda==4.8.2=py37_0 -> python[version='>=3.7,<3.8.0a0']\n",
            "numpy-base -> python[version='>=3.7,<3.8.0a0']\n",
            "mkl-service -> python[version='>=3.7,<3.8.0a0']\n",
            "pyparsing -> python[version='>=3.6']\n",
            "pyopenssl==19.1.0=py37_0 -> python[version='>=3.7,<3.8.0a0']\n",
            "pycosat==0.6.3=py37h7b6447c_0 -> python[version='>=3.7,<3.8.0a0']\n",
            "numpy -> python[version='>=3.7,<3.8.0a0']\n",
            "chardet==3.0.4=py37_1003 -> python[version='>=3.7,<3.8.0a0']\n",
            "wheel==0.34.2=py37_0 -> python[version='>=3.7,<3.8.0a0']\n",
            "pandas -> python-dateutil[version='>=2.7.3'] -> python\n",
            "packaging -> python[version='>=3.6']\n",
            "py-boost -> python[version='>=3.7,<3.8.0a0']\n",
            "conda-package-handling==1.6.0=py37h7b6447c_0 -> python[version='>=3.7,<3.8.0a0']\n",
            "certifi==2019.11.28=py37_0 -> python[version='>=3.7,<3.8.0a0']\n",
            "bottleneck -> python[version='>=3.7,<3.8.0a0']\n",
            "idna==2.8=py37_0 -> python[version='>=3.7,<3.8.0a0']\n",
            "numexpr -> packaging -> python[version='>=3.6']\n",
            "ruamel_yaml==0.15.87=py37h7b6447c_0 -> python[version='>=3.7,<3.8.0a0']\n",
            "mkl_random -> python[version='>=3.7,<3.8.0a0']\n",
            "python==3.7.6=h0371630_2\n",
            "requests==2.22.0=py37_1 -> python[version='>=3.7,<3.8.0a0']\n",
            "cryptography==2.8=py37h1ba5d50_0 -> python[version='>=3.7,<3.8.0a0']\n",
            "rdkit -> python[version='>=3.7,<3.8.0a0']\n",
            "pycparser==2.19=py37_0 -> python[version='>=3.7,<3.8.0a0']\n",
            "numexpr -> python[version='>=3.7,<3.8.0a0']\n",
            "setuptools==45.2.0=py37_0 -> python[version='>=3.7,<3.8.0a0']\n",
            "six==1.14.0=py37_0 -> python[version='>=3.7,<3.8.0a0']\n",
            "urllib3==1.25.8=py37_0 -> python[version='>=3.7,<3.8.0a0']\n",
            "\n",
            "Package pixman conflicts for:\n",
            "rdkit -> cairo[version='>=1.14.12,<2.0a0'] -> pixman[version='>=0.40.0,<1.0a0']\n",
            "pixman\n",
            "cairo -> pixman[version='>=0.40.0,<1.0a0']\n",
            "\n",
            "Package libedit conflicts for:\n",
            "python==3.7.6=h0371630_2 -> sqlite[version='>=3.30.1,<4.0a0'] -> libedit[version='>=3.1.20181209,<3.2.0a0']\n",
            "sqlite==3.31.1=h7b6447c_0 -> libedit[version='>=3.1.20181209,<3.2.0a0']\n",
            "libedit==3.1.20181209=hc058e9b_0\n",
            "\n",
            "Package icu conflicts for:\n",
            "rdkit -> libboost[version='>=1.73.0,<1.74.0a0'] -> icu[version='>=58.2,<59.0a0']\n",
            "fontconfig -> libxml2[version='>=2.9.10,<2.10.0a0'] -> icu[version='>=58.2,<59.0a0']\n",
            "icu\n",
            "py-boost -> libboost[version='>=1.73.0,<1.73.1.0a0',build=h3ff78a5_11] -> icu[version='>=58.2,<59.0a0']\n",
            "libboost -> icu[version='>=58.2,<59.0a0']\n",
            "libxml2 -> icu[version='>=58.2,<59.0a0']\n",
            "\n",
            "Package certifi conflicts for:\n",
            "wheel==0.34.2=py37_0 -> setuptools -> certifi[version='>=2016.9.26']\n",
            "urllib3==1.25.8=py37_0 -> certifi\n",
            "certifi==2019.11.28=py37_0\n",
            "setuptools==45.2.0=py37_0 -> certifi[version='>=2016.9.26']\n",
            "requests==2.22.0=py37_1 -> urllib3[version='>=1.21.1,<1.26,!=1.25.0,!=1.25.1'] -> certifi\n",
            "pip==20.0.2=py37_1 -> setuptools -> certifi[version='>=2016.9.26']\n",
            "requests==2.22.0=py37_1 -> certifi[version='>=2017.4.17']\n",
            "conda==4.8.2=py37_0 -> requests[version='>=2.18.4,<3'] -> certifi[version='>=2016.9.26|>=2017.4.17']\n",
            "\n",
            "Package libpng conflicts for:\n",
            "fontconfig -> freetype[version='>=2.10.4,<3.0a0'] -> libpng[version='>=1.6.37,<1.7.0a0']\n",
            "freetype -> libpng[version='>=1.6.37,<1.7.0a0']\n",
            "pillow -> freetype[version='>=2.10.4,<3.0a0'] -> libpng[version='>=1.6.37,<1.7.0a0']\n",
            "cairo -> libpng[version='>=1.6.37,<1.7.0a0']\n",
            "rdkit -> cairo[version='>=1.14.12,<2.0a0'] -> libpng[version='>=1.6.37,<1.7.0a0']\n",
            "libwebp -> libpng[version='>=1.6.37,<1.7.0a0']\n",
            "libpng\n",
            "\n",
            "Package mkl conflicts for:\n",
            "bottleneck -> numpy[version='>=1.16.6,<2.0a0'] -> mkl[version='>=2021.4.0,<2022.0a0']\n",
            "pandas -> numexpr[version='>=2.7.0'] -> mkl[version='>=2021.4.0,<2022.0a0']\n",
            "mkl\n",
            "numpy -> mkl-service[version='>=2.3.0,<3.0a0'] -> mkl[version='>=2021.2.0,<2022.0a0|>=2021.3.0,<2022.0a0']\n",
            "mkl_fft -> mkl-service[version='>=2.3.0,<3.0a0'] -> mkl[version='>=2021.2.0,<2022.0a0|>=2021.4.0,<2022.0a0']\n",
            "numexpr -> mkl-service[version='>=2.3.0,<3.0a0'] -> mkl[version='>=2021.2.0,<2022.0a0']\n",
            "rdkit -> numpy[version='>=1.12'] -> mkl[version='>=2021.4.0,<2022.0a0']\n",
            "numpy -> mkl[version='>=2021.4.0,<2022.0a0']\n",
            "mkl_random -> mkl[version='>=2021.2.0,<2022.0a0']\n",
            "mkl-service -> mkl[version='>=2021.2.0,<2022.0a0']\n",
            "numpy-base -> mkl[version='>=2021.4.0,<2022.0a0']\n",
            "mkl_random -> numpy[version='>=1.16,<2.0a0'] -> mkl[version='>=2021.4.0,<2022.0a0']\n",
            "mkl_fft -> mkl[version='>=2021.3.0,<2022.0a0']\n",
            "numexpr -> mkl[version='>=2021.4.0,<2022.0a0']\n",
            "numpy-base -> mkl-service[version='>=2.3.0,<3.0a0'] -> mkl[version='>=2021.2.0,<2022.0a0']\n",
            "\n",
            "Package glib conflicts for:\n",
            "rdkit -> cairo[version='>=1.14.12,<2.0a0'] -> glib[version='>=2.67.4,<3.0a0']\n",
            "cairo -> glib[version='>=2.67.4,<3.0a0']\n",
            "glib\n",
            "\n",
            "Package libffi conflicts for:\n",
            "pysocks==1.7.1=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> libffi[version='>=3.2.1,<4.0a0']\n",
            "numpy-base -> python[version='>=3.7,<3.8.0a0'] -> libffi[version='>=3.2.1,<4.0a0']\n",
            "requests==2.22.0=py37_1 -> python[version='>=3.7,<3.8.0a0'] -> libffi[version='>=3.2.1,<4.0a0']\n",
            "cryptography==2.8=py37h1ba5d50_0 -> cffi[version='>=1.8'] -> libffi[version='>=3.2.1,<4.0a0']\n",
            "wheel==0.34.2=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> libffi[version='>=3.2.1,<4.0a0']\n",
            "pytz -> python -> libffi[version='>=3.2.1,<4.0a0']\n",
            "python==3.7.6=h0371630_2 -> libffi[version='>=3.2.1,<4.0a0']\n",
            "numpy -> python[version='>=3.7,<3.8.0a0'] -> libffi[version='>=3.2.1,<4.0a0']\n",
            "chardet==3.0.4=py37_1003 -> python[version='>=3.7,<3.8.0a0'] -> libffi[version='>=3.2.1,<4.0a0']\n",
            "pyopenssl==19.1.0=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> libffi[version='>=3.2.1,<4.0a0']\n",
            "rdkit -> python[version='>=3.7,<3.8.0a0'] -> libffi[version='>=3.2.1,<4.0a0']\n",
            "pyparsing -> python[version='>=3.6'] -> libffi[version='>=3.2.1,<4.0a0']\n",
            "pycparser==2.19=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> libffi[version='>=3.2.1,<4.0a0']\n",
            "pip==20.0.2=py37_1 -> python[version='>=3.7,<3.8.0a0'] -> libffi[version='>=3.2.1,<4.0a0']\n",
            "pycosat==0.6.3=py37h7b6447c_0 -> python[version='>=3.7,<3.8.0a0'] -> libffi[version='>=3.2.1,<4.0a0']\n",
            "six==1.14.0=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> libffi[version='>=3.2.1,<4.0a0']\n",
            "pandas -> python[version='>=3.7,<3.8.0a0'] -> libffi[version='>=3.2.1,<4.0a0']\n",
            "numexpr -> python[version='>=3.7,<3.8.0a0'] -> libffi[version='>=3.2.1,<4.0a0']\n",
            "mkl-service -> python[version='>=3.7,<3.8.0a0'] -> libffi[version='>=3.2.1,<4.0a0']\n",
            "conda==4.8.2=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> libffi[version='>=3.2.1,<4.0a0']\n",
            "python-dateutil -> python -> libffi[version='>=3.2.1,<4.0a0']\n",
            "idna==2.8=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> libffi[version='>=3.2.1,<4.0a0']\n",
            "mkl_random -> python[version='>=3.7,<3.8.0a0'] -> libffi[version='>=3.2.1,<4.0a0']\n",
            "cffi==1.14.0=py37h2e261b9_0 -> libffi[version='>=3.2.1,<4.0a0']\n",
            "cairo -> glib[version='>=2.67.4,<3.0a0'] -> libffi[version='>=3.3|>=3.3,<3.4.0a0']\n",
            "tqdm==4.42.1=py_0 -> python -> libffi[version='>=3.2.1,<4.0a0']\n",
            "certifi==2019.11.28=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> libffi[version='>=3.2.1,<4.0a0']\n",
            "urllib3==1.25.8=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> libffi[version='>=3.2.1,<4.0a0']\n",
            "mkl_fft -> python[version='>=3.7,<3.8.0a0'] -> libffi[version='>=3.2.1,<4.0a0']\n",
            "py-boost -> python[version='>=3.7,<3.8.0a0'] -> libffi[version='>=3.2.1,<4.0a0']\n",
            "ruamel_yaml==0.15.87=py37h7b6447c_0 -> python[version='>=3.7,<3.8.0a0'] -> libffi[version='>=3.2.1,<4.0a0']\n",
            "setuptools==45.2.0=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> libffi[version='>=3.2.1,<4.0a0']\n",
            "glib -> libffi[version='>=3.3|>=3.3,<3.4.0a0']\n",
            "pillow -> python[version='>=3.7,<3.8.0a0'] -> libffi[version='>=3.2.1,<4.0a0']\n",
            "bottleneck -> python[version='>=3.7,<3.8.0a0'] -> libffi[version='>=3.2.1,<4.0a0']\n",
            "conda-package-handling==1.6.0=py37h7b6447c_0 -> python[version='>=3.7,<3.8.0a0'] -> libffi[version='>=3.2.1,<4.0a0']\n",
            "packaging -> python[version='>=3.6'] -> libffi[version='>=3.2.1,<4.0a0']\n",
            "libffi==3.2.1=hd88cf55_4\n",
            "\n",
            "Package lz4-c conflicts for:\n",
            "lz4-c\n",
            "zstd -> lz4-c[version='>=1.9.3,<1.10.0a0']\n",
            "libboost -> zstd[version='>=1.4.5,<1.5.0a0'] -> lz4-c[version='>=1.9.3,<1.10.0a0']\n",
            "libtiff -> zstd[version='>=1.4.5,<1.5.0a0'] -> lz4-c[version='>=1.9.3,<1.10.0a0']\n",
            "\n",
            "Package _libgcc_mutex conflicts for:\n",
            "bzip2 -> libgcc-ng[version='>=7.3.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "libxcb -> libgcc-ng[version='>=7.5.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "pycosat==0.6.3=py37h7b6447c_0 -> libgcc-ng[version='>=7.3.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "icu -> libgcc-ng[version='>=7.3.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "numpy-base -> libgcc-ng[version='>=7.5.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "giflib -> libgcc-ng[version='>=7.3.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "zstd -> libgcc-ng[version='>=7.3.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "libpng -> libgcc-ng[version='>=7.3.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "mkl_random -> libgcc-ng[version='>=7.5.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "sqlite==3.31.1=h7b6447c_0 -> libgcc-ng[version='>=7.3.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "ruamel_yaml==0.15.87=py37h7b6447c_0 -> libgcc-ng[version='>=7.3.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "_openmp_mutex -> _libgcc_mutex==0.1=main\n",
            "lcms2 -> libgcc-ng[version='>=7.3.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "xz==5.2.4=h14c3975_4 -> libgcc-ng[version='>=7.2.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "mkl_fft -> libgcc-ng[version='>=7.5.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "libgomp -> _libgcc_mutex==0.1=main\n",
            "jpeg -> libgcc-ng[version='>=7.5.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "libuuid -> libgcc-ng[version='>=7.5.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "lz4-c -> libgcc-ng[version='>=7.5.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "readline==7.0=h7b6447c_5 -> libgcc-ng[version='>=7.3.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "openssl==1.1.1d=h7b6447c_4 -> libgcc-ng[version='>=7.3.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "libwebp-base -> libgcc-ng[version='>=7.5.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "python==3.7.6=h0371630_2 -> libgcc-ng[version='>=7.3.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "zlib==1.2.11=h7b6447c_3 -> libgcc-ng[version='>=7.3.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "libtiff -> libgcc-ng[version='>=7.3.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "rdkit -> libgcc-ng[version='>=7.3.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "libboost -> libgcc-ng[version='>=7.3.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "numpy -> libgcc-ng[version='>=7.5.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "cffi==1.14.0=py37h2e261b9_0 -> libgcc-ng[version='>=7.3.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "mkl-service -> libgcc-ng[version='>=7.5.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "numexpr -> libgcc-ng[version='>=7.5.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "pixman -> libgcc-ng[version='>=7.5.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "conda-package-handling==1.6.0=py37h7b6447c_0 -> libgcc-ng[version='>=7.3.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "libwebp -> libgcc-ng[version='>=7.5.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "cairo -> libgcc-ng[version='>=7.3.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "pandas -> libgcc-ng[version='>=7.5.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "bottleneck -> libgcc-ng[version='>=7.5.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "py-boost -> libgcc-ng[version='>=7.3.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "libgcc-ng==9.1.0=hdf63c60_0 -> _libgcc_mutex=[build=main]\n",
            "yaml==0.1.7=had09818_2 -> libgcc-ng[version='>=7.2.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "libxml2 -> libgcc-ng[version='>=9.3.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "freetype -> libgcc-ng[version='>=7.5.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "ncurses==6.2=he6710b0_0 -> libgcc-ng[version='>=7.3.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "pillow -> libgcc-ng[version='>=7.5.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "tk==8.6.8=hbc83047_0 -> libgcc-ng[version='>=7.3.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "_libgcc_mutex==0.1=main\n",
            "pcre -> libgcc-ng[version='>=7.5.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "libedit==3.1.20181209=hc058e9b_0 -> libgcc-ng[version='>=7.3.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "fontconfig -> libgcc-ng[version='>=7.3.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "cryptography==2.8=py37h1ba5d50_0 -> libgcc-ng[version='>=7.3.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "libffi==3.2.1=hd88cf55_4 -> libgcc-ng[version='>=7.2.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "glib -> libgcc-ng[version='>=7.5.0'] -> _libgcc_mutex[version='*|0.1',build=main]\n",
            "\n",
            "Package ld_impl_linux-64 conflicts for:\n",
            "setuptools==45.2.0=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> ld_impl_linux-64\n",
            "mkl_fft -> python[version='>=3.7,<3.8.0a0'] -> ld_impl_linux-64\n",
            "idna==2.8=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> ld_impl_linux-64\n",
            "ld_impl_linux-64==2.33.1=h53a641e_7\n",
            "conda==4.8.2=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> ld_impl_linux-64\n",
            "numpy-base -> python[version='>=3.7,<3.8.0a0'] -> ld_impl_linux-64\n",
            "rdkit -> python[version='>=3.7,<3.8.0a0'] -> ld_impl_linux-64\n",
            "tqdm==4.42.1=py_0 -> python -> ld_impl_linux-64\n",
            "chardet==3.0.4=py37_1003 -> python[version='>=3.7,<3.8.0a0'] -> ld_impl_linux-64\n",
            "packaging -> python[version='>=3.6'] -> ld_impl_linux-64\n",
            "mkl-service -> python[version='>=3.7,<3.8.0a0'] -> ld_impl_linux-64\n",
            "cryptography==2.8=py37h1ba5d50_0 -> python[version='>=3.7,<3.8.0a0'] -> ld_impl_linux-64\n",
            "six==1.14.0=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> ld_impl_linux-64\n",
            "urllib3==1.25.8=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> ld_impl_linux-64\n",
            "conda-package-handling==1.6.0=py37h7b6447c_0 -> python[version='>=3.7,<3.8.0a0'] -> ld_impl_linux-64\n",
            "bottleneck -> python[version='>=3.7,<3.8.0a0'] -> ld_impl_linux-64\n",
            "certifi==2019.11.28=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> ld_impl_linux-64\n",
            "pytz -> python -> ld_impl_linux-64\n",
            "pyopenssl==19.1.0=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> ld_impl_linux-64\n",
            "pandas -> python[version='>=3.7,<3.8.0a0'] -> ld_impl_linux-64\n",
            "pysocks==1.7.1=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> ld_impl_linux-64\n",
            "python-dateutil -> python -> ld_impl_linux-64\n",
            "py-boost -> python[version='>=3.7,<3.8.0a0'] -> ld_impl_linux-64\n",
            "pycosat==0.6.3=py37h7b6447c_0 -> python[version='>=3.7,<3.8.0a0'] -> ld_impl_linux-64\n",
            "ruamel_yaml==0.15.87=py37h7b6447c_0 -> python[version='>=3.7,<3.8.0a0'] -> ld_impl_linux-64\n",
            "requests==2.22.0=py37_1 -> python[version='>=3.7,<3.8.0a0'] -> ld_impl_linux-64\n",
            "cffi==1.14.0=py37h2e261b9_0 -> python[version='>=3.7,<3.8.0a0'] -> ld_impl_linux-64\n",
            "pip==20.0.2=py37_1 -> python[version='>=3.7,<3.8.0a0'] -> ld_impl_linux-64\n",
            "mkl_random -> python[version='>=3.7,<3.8.0a0'] -> ld_impl_linux-64\n",
            "python==3.7.6=h0371630_2 -> ld_impl_linux-64\n",
            "numpy -> python[version='>=3.7,<3.8.0a0'] -> ld_impl_linux-64\n",
            "pycparser==2.19=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> ld_impl_linux-64\n",
            "pillow -> python[version='>=3.7,<3.8.0a0'] -> ld_impl_linux-64\n",
            "numexpr -> python[version='>=3.7,<3.8.0a0'] -> ld_impl_linux-64\n",
            "pyparsing -> python[version='>=3.6'] -> ld_impl_linux-64\n",
            "wheel==0.34.2=py37_0 -> python[version='>=3.7,<3.8.0a0'] -> ld_impl_linux-64\n",
            "\n",
            "Package mkl_random conflicts for:\n",
            "pandas -> numpy[version='>=1.19.2,<2.0a0'] -> mkl_random\n",
            "mkl_fft -> numpy[version='>=1.16,<2.0a0'] -> mkl_random\n",
            "rdkit -> numpy[version='>=1.12'] -> mkl_random\n",
            "mkl_random\n",
            "numexpr -> numpy[version='>=1.16.6,<2.0a0'] -> mkl_random\n",
            "bottleneck -> numpy[version='>=1.16.6,<2.0a0'] -> mkl_random\n",
            "numpy -> mkl_random\n",
            "\n",
            "Package conda-package-handling conflicts for:\n",
            "conda==4.8.2=py37_0 -> conda-package-handling[version='>=1.3.0']\n",
            "conda-package-handling==1.6.0=py37h7b6447c_0\n",
            "\n",
            "Package six conflicts for:\n",
            "six==1.14.0=py37_0\n",
            "mkl_random -> mkl-service[version='>=2.3.0,<3.0a0'] -> six\n",
            "cryptography==2.8=py37h1ba5d50_0 -> six[version='>=1.4.1']\n",
            "python-dateutil -> six[version='>=1.5']\n",
            "pandas -> python-dateutil[version='>=2.7.3'] -> six[version='>=1.5']\n",
            "pyopenssl==19.1.0=py37_0 -> cryptography[version='>=2.8'] -> six[version='>=1.4.1']\n",
            "urllib3==1.25.8=py37_0 -> cryptography[version='>=1.3.4'] -> six[version='>=1.4.1|>=1.5.2']\n",
            "conda-package-handling==1.6.0=py37h7b6447c_0 -> six\n",
            "mkl_fft -> mkl-service[version='>=2.3.0,<3.0a0'] -> six\n",
            "pyopenssl==19.1.0=py37_0 -> six[version='>=1.5.2']\n",
            "numpy-base -> mkl-service[version='>=2.3.0,<3.0a0'] -> six\n",
            "mkl-service -> six\n",
            "numpy -> mkl-service[version='>=2.3.0,<3.0a0'] -> six\n",
            "numexpr -> mkl-service[version='>=2.3.0,<3.0a0'] -> six\n",
            "conda==4.8.2=py37_0 -> conda-package-handling[version='>=1.3.0'] -> six[version='>=1.5.2']\n",
            "\n",
            "Package zstd conflicts for:\n",
            "rdkit -> libboost[version='>=1.73.0,<1.74.0a0'] -> zstd[version='>=1.4.5,<1.5.0a0']\n",
            "lcms2 -> libtiff[version='>=4.1.0,<5.0a0'] -> zstd[version='>=1.4.5,<1.5.0a0']\n",
            "libboost -> zstd[version='>=1.4.5,<1.5.0a0']\n",
            "pillow -> libtiff[version='>=4.1.0,<5.0a0'] -> zstd[version='>=1.4.5,<1.5.0a0']\n",
            "zstd\n",
            "libtiff -> zstd[version='>=1.4.5,<1.5.0a0']\n",
            "libwebp -> libtiff[version='>=4.1.0,<5.0a0'] -> zstd[version='>=1.4.5,<1.5.0a0']\n",
            "py-boost -> libboost[version='>=1.73.0,<1.73.1.0a0',build=h3ff78a5_11] -> zstd[version='>=1.4.5,<1.5.0a0']\n",
            "\n",
            "Package giflib conflicts for:\n",
            "pillow -> libwebp[version='>=0.3.0'] -> giflib[version='>=5.2.1,<5.3.0a0']\n",
            "libwebp -> giflib[version='>=5.2.1,<5.3.0a0']\n",
            "giflib\n",
            "\n",
            "Package libboost conflicts for:\n",
            "rdkit -> libboost[version='>=1.73.0,<1.74.0a0']\n",
            "libboost\n",
            "py-boost -> libboost[version='>=1.73.0,<1.73.1.0a0',build=h3ff78a5_11]\n",
            "rdkit -> py-boost -> libboost[version='>=1.73.0,<1.73.1.0a0',build=h3ff78a5_11]\n",
            "\n",
            "Package yaml conflicts for:\n",
            "yaml==0.1.7=had09818_2\n",
            "ruamel_yaml==0.15.87=py37h7b6447c_0 -> yaml[version='>=0.1.7,<0.2.0a0']\n",
            "conda==4.8.2=py37_0 -> ruamel_yaml[version='>=0.11.14,<0.16'] -> yaml[version='>=0.1.7,<0.2.0a0']\n",
            "\n",
            "Package pillow conflicts for:\n",
            "rdkit -> pillow\n",
            "pillow\n",
            "\n",
            "Package freetype conflicts for:\n",
            "freetype\n",
            "cairo -> freetype[version='>=2.10.4,<3.0a0']\n",
            "rdkit -> cairo[version='>=1.14.12,<2.0a0'] -> freetype[version='>=2.10.4,<3.0a0']\n",
            "pillow -> freetype[version='>=2.10.4,<3.0a0']\n",
            "rdkit -> freetype[version='>=2.10.3,<3.0a0']\n",
            "fontconfig -> freetype[version='>=2.10.4,<3.0a0']\n",
            "\n",
            "Package python-dateutil conflicts for:\n",
            "pandas -> python-dateutil[version='>=2.7.3']\n",
            "python-dateutil\n",
            "rdkit -> pandas -> python-dateutil[version='>=2.7.3']\n",
            "\n",
            "Package pytz conflicts for:\n",
            "pandas -> pytz[version='>=2017.3']\n",
            "pytz\n",
            "rdkit -> pandas -> pytz[version='>=2017.3']\n",
            "\n",
            "Package pyopenssl conflicts for:\n",
            "requests==2.22.0=py37_1 -> urllib3[version='>=1.21.1,<1.26,!=1.25.0,!=1.25.1'] -> pyopenssl[version='>=0.14']\n",
            "conda==4.8.2=py37_0 -> pyopenssl[version='>=16.2.0']\n",
            "urllib3==1.25.8=py37_0 -> pyopenssl[version='>=0.14']\n",
            "pyopenssl==19.1.0=py37_0\n",
            "\n",
            "Package libwebp-base conflicts for:\n",
            "pillow -> libtiff[version='>=4.1.0,<5.0a0'] -> libwebp-base\n",
            "libwebp-base\n",
            "libtiff -> libwebp-base\n",
            "lcms2 -> libtiff[version='>=4.1.0,<5.0a0'] -> libwebp-base\n",
            "libwebp -> libwebp-base\n",
            "\n",
            "Package packaging conflicts for:\n",
            "pandas -> numexpr[version='>=2.7.0'] -> packaging\n",
            "packaging\n",
            "numexpr -> packaging\n",
            "\n",
            "Package libtiff conflicts for:\n",
            "libtiff\n",
            "lcms2 -> libtiff[version='>=4.1.0,<5.0a0']\n",
            "rdkit -> pillow -> libtiff[version='>=4.1.0,<5.0a0']\n",
            "pillow -> libtiff[version='>=4.1.0,<5.0a0']\n",
            "libwebp -> libtiff[version='>=4.1.0,<5.0a0']\n",
            "\n",
            "Package asn1crypto conflicts for:\n",
            "cryptography==2.8=py37h1ba5d50_0 -> asn1crypto[version='>=0.21.0']\n",
            "asn1crypto==1.3.0=py37_0\n",
            "pyopenssl==19.1.0=py37_0 -> cryptography[version='>=2.8'] -> asn1crypto[version='>=0.21.0']\n",
            "urllib3==1.25.8=py37_0 -> cryptography[version='>=1.3.4'] -> asn1crypto[version='>=0.21.0']\n",
            "\n",
            "Package pandas conflicts for:\n",
            "pandas\n",
            "rdkit -> pandas\n",
            "\n",
            "Package pycparser conflicts for:\n",
            "cryptography==2.8=py37h1ba5d50_0 -> cffi[version='>=1.8'] -> pycparser\n",
            "cffi==1.14.0=py37h2e261b9_0 -> pycparser\n",
            "pycparser==2.19=py37_0\n",
            "\n",
            "Package tqdm conflicts for:\n",
            "tqdm==4.42.1=py_0\n",
            "conda-package-handling==1.6.0=py37h7b6447c_0 -> tqdm\n",
            "conda==4.8.2=py37_0 -> conda-package-handling[version='>=1.3.0'] -> tqdm\n",
            "\n",
            "Package libxcb conflicts for:\n",
            "libxcb\n",
            "rdkit -> cairo[version='>=1.14.12,<2.0a0'] -> libxcb[version='>=1.14,<2.0a0']\n",
            "cairo -> libxcb[version='>=1.14,<2.0a0']\n",
            "\n",
            "Package cffi conflicts for:\n",
            "cffi==1.14.0=py37h2e261b9_0\n",
            "urllib3==1.25.8=py37_0 -> cryptography[version='>=1.3.4'] -> cffi[version='>=1.8']\n",
            "pyopenssl==19.1.0=py37_0 -> cryptography[version='>=2.8'] -> cffi[version='>=1.8']\n",
            "cryptography==2.8=py37h1ba5d50_0 -> cffi[version='>=1.8']\n",
            "\n",
            "Package bottleneck conflicts for:\n",
            "bottleneck\n",
            "pandas -> bottleneck[version='>=1.2.1']\n",
            "rdkit -> pandas -> bottleneck[version='>=1.2.1']\n",
            "\n",
            "Package mkl-service conflicts for:\n",
            "pandas -> numexpr[version='>=2.7.0'] -> mkl-service[version='>=2.3.0,<3.0a0']\n",
            "mkl-service\n",
            "mkl_fft -> mkl-service[version='>=2.3.0,<3.0a0']\n",
            "bottleneck -> numpy[version='>=1.16.6,<2.0a0'] -> mkl-service[version='>=2.3.0,<3.0a0']\n",
            "numpy-base -> mkl-service[version='>=2.3.0,<3.0a0']\n",
            "mkl_random -> mkl-service[version='>=2.3.0,<3.0a0']\n",
            "rdkit -> numpy[version='>=1.12'] -> mkl-service[version='>=2.3.0,<3.0a0']\n",
            "numpy -> mkl-service[version='>=2.3.0,<3.0a0']\n",
            "numexpr -> mkl-service[version='>=2.3.0,<3.0a0']\n",
            "\n",
            "Package setuptools conflicts for:\n",
            "conda==4.8.2=py37_0 -> setuptools[version='>=31.0.1']\n",
            "setuptools==45.2.0=py37_0\n",
            "wheel==0.34.2=py37_0 -> setuptools\n",
            "pip==20.0.2=py37_1 -> setuptools\n",
            "\n",
            "Package intel-openmp conflicts for:\n",
            "numpy -> mkl[version='>=2021.4.0,<2022.0a0'] -> intel-openmp=2021\n",
            "intel-openmp\n",
            "mkl-service -> mkl[version='>=2021.2.0,<2022.0a0'] -> intel-openmp=2021\n",
            "numexpr -> mkl[version='>=2021.4.0,<2022.0a0'] -> intel-openmp=2021\n",
            "mkl_fft -> mkl[version='>=2021.3.0,<2022.0a0'] -> intel-openmp=2021\n",
            "mkl_random -> mkl[version='>=2021.2.0,<2022.0a0'] -> intel-openmp=2021\n",
            "numpy-base -> mkl[version='>=2021.4.0,<2022.0a0'] -> intel-openmp=2021\n",
            "mkl -> intel-openmp=2021\n",
            "\n",
            "Package jpeg conflicts for:\n",
            "lcms2 -> jpeg[version='>=9b,<10a']\n",
            "libwebp -> libtiff[version='>=4.1.0,<5.0a0'] -> jpeg[version='>=9b,<10a']\n",
            "pillow -> jpeg\n",
            "rdkit -> pillow -> jpeg\n",
            "jpeg\n",
            "pillow -> lcms2[version='>=2.12,<3.0a0'] -> jpeg[version='>=9b,<10a|>=9d,<10a']\n",
            "libwebp -> jpeg[version='>=9d,<10a']\n",
            "libtiff -> jpeg[version='>=9b,<10a']\n",
            "\n",
            "Package idna conflicts for:\n",
            "urllib3==1.25.8=py37_0 -> idna[version='>=2.0.0']\n",
            "requests==2.22.0=py37_1 -> urllib3[version='>=1.21.1,<1.26,!=1.25.0,!=1.25.1'] -> idna[version='>=2.0.0']\n",
            "urllib3==1.25.8=py37_0 -> cryptography[version='>=1.3.4'] -> idna[version='>=2.1']\n",
            "pyopenssl==19.1.0=py37_0 -> cryptography[version='>=2.8'] -> idna[version='>=2.1']\n",
            "cryptography==2.8=py37h1ba5d50_0 -> idna[version='>=2.1']\n",
            "idna==2.8=py37_0\n",
            "conda==4.8.2=py37_0 -> requests[version='>=2.18.4,<3'] -> idna[version='>=2.5,<2.9']\n",
            "requests==2.22.0=py37_1 -> idna[version='>=2.5,<2.9']\n",
            "\n",
            "Package ruamel_yaml conflicts for:\n",
            "ruamel_yaml==0.15.87=py37h7b6447c_0\n",
            "conda==4.8.2=py37_0 -> ruamel_yaml[version='>=0.11.14,<0.16']\n",
            "\n",
            "Package requests conflicts for:\n",
            "conda==4.8.2=py37_0 -> requests[version='>=2.18.4,<3']\n",
            "requests==2.22.0=py37_1\n",
            "\n",
            "Package pcre conflicts for:\n",
            "pcre\n",
            "cairo -> glib[version='>=2.67.4,<3.0a0'] -> pcre[version='>=8.45,<9.0a0']\n",
            "glib -> pcre[version='>=8.45,<9.0a0']\n",
            "\n",
            "Package ca-certificates conflicts for:\n",
            "python==3.7.6=h0371630_2 -> openssl[version='>=1.1.1d,<1.1.2a'] -> ca-certificates\n",
            "cryptography==2.8=py37h1ba5d50_0 -> openssl[version='>=1.1.1d,<1.1.2a'] -> ca-certificates\n",
            "ca-certificates==2020.1.1=0\n",
            "openssl==1.1.1d=h7b6447c_4 -> ca-certificates\n",
            "\n",
            "Package chardet conflicts for:\n",
            "chardet==3.0.4=py37_1003\n",
            "conda==4.8.2=py37_0 -> requests[version='>=2.18.4,<3'] -> chardet[version='>=3.0.2,<3.1.0']\n",
            "requests==2.22.0=py37_1 -> chardet[version='>=3.0.2,<3.1.0']\n",
            "\n",
            "Package py-boost conflicts for:\n",
            "py-boost\n",
            "rdkit -> py-boost\n",
            "\n",
            "Package libuuid conflicts for:\n",
            "fontconfig -> libuuid[version='>=1.0.3,<2.0a0']\n",
            "cairo -> fontconfig[version='>=2.13.1,<3.0a0'] -> libuuid[version='>=1.0.3,<2.0a0']\n",
            "libuuid\n",
            "\n",
            "Package fontconfig conflicts for:\n",
            "rdkit -> cairo[version='>=1.14.12,<2.0a0'] -> fontconfig[version='>=2.13.1,<3.0a0']\n",
            "fontconfig\n",
            "cairo -> fontconfig[version='>=2.13.1,<3.0a0']\n",
            "\n",
            "Package pysocks conflicts for:\n",
            "requests==2.22.0=py37_1 -> urllib3[version='>=1.21.1,<1.26,!=1.25.0,!=1.25.1'] -> pysocks[version='>=1.5.6,<2.0,!=1.5.7']\n",
            "pysocks==1.7.1=py37_0\n",
            "urllib3==1.25.8=py37_0 -> pysocks[version='>=1.5.6,<2.0,!=1.5.7']\n",
            "\n",
            "Package wheel conflicts for:\n",
            "pip==20.0.2=py37_1 -> wheel\n",
            "wheel==0.34.2=py37_0\n",
            "\n",
            "Package urllib3 conflicts for:\n",
            "urllib3==1.25.8=py37_0\n",
            "requests==2.22.0=py37_1 -> urllib3[version='>=1.21.1,<1.26,!=1.25.0,!=1.25.1']\n",
            "conda==4.8.2=py37_0 -> requests[version='>=2.18.4,<3'] -> urllib3[version='>=1.21.1,<1.26,!=1.25.0,!=1.25.1']\n",
            "\n",
            "Package lcms2 conflicts for:\n",
            "rdkit -> pillow -> lcms2[version='>=2.12,<3.0a0']\n",
            "lcms2\n",
            "pillow -> lcms2[version='>=2.12,<3.0a0']\n",
            "\n",
            "Package cryptography conflicts for:\n",
            "requests==2.22.0=py37_1 -> urllib3[version='>=1.21.1,<1.26,!=1.25.0,!=1.25.1'] -> cryptography[version='>=1.3.4']\n",
            "conda==4.8.2=py37_0 -> pyopenssl[version='>=16.2.0'] -> cryptography[version='>=2.8']\n",
            "pyopenssl==19.1.0=py37_0 -> cryptography[version='>=2.8']\n",
            "cryptography==2.8=py37h1ba5d50_0\n",
            "urllib3==1.25.8=py37_0 -> pyopenssl[version='>=0.14'] -> cryptography[version='>=2.8']\n",
            "urllib3==1.25.8=py37_0 -> cryptography[version='>=1.3.4']\n",
            "\n",
            "Package libwebp conflicts for:\n",
            "pillow -> libwebp[version='>=0.3.0|>=1.2.0,<1.3.0a0']\n",
            "rdkit -> pillow -> libwebp[version='>=0.3.0|>=1.2.0,<1.3.0a0']\n",
            "libwebp\n",
            "\n",
            "Package libgomp conflicts for:\n",
            "_openmp_mutex -> libgomp[version='>=7.5.0']\n",
            "libgomp\n",
            "\n",
            "Package numexpr conflicts for:\n",
            "pandas -> numexpr[version='>=2.7.0']\n",
            "numexpr\n",
            "rdkit -> pandas -> numexpr[version='>=2.7.0']\n",
            "\n",
            "Package pyparsing conflicts for:\n",
            "packaging -> pyparsing[version='>=2.0.2,!=3.0.5']\n",
            "pyparsing\n",
            "numexpr -> packaging -> pyparsing[version='>=2.0.2,!=3.0.5']\n",
            "\n",
            "Package cairo conflicts for:\n",
            "cairo\n",
            "rdkit -> cairo[version='>=1.14.12,<2.0a0']\n",
            "\n",
            "Package libxml2 conflicts for:\n",
            "cairo -> fontconfig[version='>=2.13.1,<3.0a0'] -> libxml2[version='>=2.9.10,<2.10.0a0']\n",
            "libxml2\n",
            "fontconfig -> libxml2[version='>=2.9.10,<2.10.0a0']\n",
            "\n",
            "Package pycosat conflicts for:\n",
            "conda==4.8.2=py37_0 -> pycosat[version='>=0.6.3']\n",
            "pycosat==0.6.3=py37h7b6447c_0\n",
            "\n",
            "Collecting package metadata (current_repodata.json): - \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\bdone\n",
            "Solving environment: \\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\bdone\n",
            "\n",
            "# All requested packages already installed.\n",
            "\n"
          ]
        }
      ],
      "source": [
        "! wget https://repo.anaconda.com/miniconda/Miniconda3-py37_4.8.2-Linux-x86_64.sh\n",
        "! chmod +x Miniconda3-py37_4.8.2-Linux-x86_64.sh\n",
        "! bash ./Miniconda3-py37_4.8.2-Linux-x86_64.sh -b -f -p /usr/local\n",
        "! conda install -c rdkit rdkit -y\n",
        "import sys\n",
        "sys.path.append('/usr/local/lib/python3.7/site-packages/')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QmxXXFa4wTNG"
      },
      "source": [
        "## **Load data**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "Fpu5C7HlwV9s"
      },
      "outputs": [],
      "source": [
        "import pandas as pd"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "id": "GCcE8J5XwjtB"
      },
      "outputs": [],
      "source": [
        "df = pd.read_csv(\"https://raw.githubusercontent.com/stawiskm/QSAR_Modelbuilding_amesTest/main/data/QSAR_ames_raw-data.csv\")"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def cleanSMILES(row):\n",
        "    cpd = str(row.canonical_smiles).split('.')\n",
        "    cpd_longest = max(cpd, key = len)\n",
        "    return cpd_longest"
      ],
      "metadata": {
        "id": "N-VHNDe4QRLn"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "id": "7AMm19NW0bJR"
      },
      "outputs": [],
      "source": [
        "df['smiles'] = df.apply(cleanSMILES ,axis=1)"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df = df.drop(\"canonical_smiles\",axis=1)"
      ],
      "metadata": {
        "id": "zcW-JgyfSGKl"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YzN_S4Quro5S"
      },
      "source": [
        "## **Calculate Lipinski descriptors**\n",
        "Christopher Lipinski, a scientist at Pfizer, came up with a set of rule-of-thumb for evaluating the **druglikeness** of compounds. Such druglikeness is based on the Absorption, Distribution, Metabolism and Excretion (ADME) that is also known as the pharmacokinetic profile. Lipinski analyzed all orally active FDA-approved drugs in the formulation of what is to be known as the **Rule-of-Five** or **Lipinski's Rule**.\n",
        "\n",
        "The Lipinski's Rule stated the following:\n",
        "* Molecular weight < 500 Dalton\n",
        "* Octanol-water partition coefficient (LogP) < 5\n",
        "* Hydrogen bond donors < 5\n",
        "* Hydrogen bond acceptors < 10 "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9qn_eQcnxY7C"
      },
      "source": [
        "### **Import libraries**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "id": "CgBjIdT-rnRU"
      },
      "outputs": [],
      "source": [
        "import numpy as np\n",
        "from rdkit import Chem\n",
        "from rdkit.Chem import Descriptors, Lipinski"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JsgTV-ByxdMa"
      },
      "source": [
        "### **Calculate descriptors**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "id": "bCXEY7a9ugO_"
      },
      "outputs": [],
      "source": [
        "# Inspired by: https://codeocean.com/explore/capsules?query=tag:data-curation\n",
        "\n",
        "def lipinski(row):\n",
        "\n",
        "    elem = row.smiles\n",
        "    mol=Chem.MolFromSmiles(elem)           \n",
        "       \n",
        "    desc_MolWt = Descriptors.MolWt(mol)\n",
        "    desc_MolLogP = Descriptors.MolLogP(mol)\n",
        "    desc_NumHDonors = Lipinski.NumHDonors(mol)\n",
        "    desc_NumHAcceptors = Lipinski.NumHAcceptors(mol)\n",
        "           \n",
        "    row = [desc_MolWt,\n",
        "           desc_MolLogP,\n",
        "           desc_NumHDonors,\n",
        "           desc_NumHAcceptors]   \n",
        "           \n",
        "    return row"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "id": "ThFIFw8IukMY"
      },
      "outputs": [],
      "source": [
        "df[[\"MW\",\"LogP\",\"NumHDonors\",\"NumHAcceptors\"]]   = df.apply(lipinski,axis=1, result_type ='expand')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "id": "QRm3uxBxPeSP"
      },
      "outputs": [],
      "source": [
        "df_final = df.rename(columns={\"activity_comment\": \"class\",\"smiles\":\"canonical_smiles\"})"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TTB-xkOcgwRX"
      },
      "source": [
        "Let's write this to CSV file."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "id": "sbZfHUSOgykw"
      },
      "outputs": [],
      "source": [
        "df_final.to_csv('QSAR_ames_lipinskydata.csv',index=False)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "p9vA4-hQQ8sA"
      },
      "source": [
        "---"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "x0vqbQWfxsZu"
      },
      "source": [
        "## **Exploratory Data Analysis (Chemical Space Analysis) via Lipinski descriptors**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "18heJagiyHoF"
      },
      "source": [
        "### **Import library**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "id": "0Egq_rNsxtIj"
      },
      "outputs": [],
      "source": [
        "import seaborn as sns\n",
        "sns.set(style='ticks')\n",
        "import matplotlib.pyplot as plt"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NiarmFbOdG3H"
      },
      "source": [
        "### **Frequency plot of the 2 bioactivity classes**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 367
        },
        "id": "w2Ia0iycdMO2",
        "outputId": "4b9462f0-66c3-42d1-a822-e4a5f7810fdb"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 396x396 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "plt.figure(figsize=(5.5, 5.5))\n",
        "\n",
        "sns.countplot(x='class', data=df_final, edgecolor='black')\n",
        "\n",
        "plt.xlabel('Bioactivity class', fontsize=14, fontweight='bold')\n",
        "plt.ylabel('Frequency', fontsize=14, fontweight='bold')\n",
        "\n",
        "plt.savefig('plot_bioactivity_class.pdf')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wB68NKVG0j68"
      },
      "source": [
        "### **Scatter plot of MW versus LogP**\n",
        "\n",
        "It can be seen that the 2 bioactivity classes are spanning similar chemical spaces as evident by the scatter plot of MW vs LogP."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 367
        },
        "id": "F79BNwjF0nub",
        "outputId": "11ecbe9e-c3d1-41ea-9bd8-aef457fcdeab"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 396x396 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "plt.figure(figsize=(5.5, 5.5))\n",
        "\n",
        "sns.scatterplot(x='MW', y='LogP', data=df_final, hue='class', edgecolor='black', alpha=0.7)\n",
        "\n",
        "plt.xlabel('MW', fontsize=14, fontweight='bold')\n",
        "plt.ylabel('LogP', fontsize=14, fontweight='bold')\n",
        "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0)\n",
        "plt.savefig('plot_MW_vs_LogP.pdf')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "oLAfyRwHyJfX"
      },
      "source": [
        "### **Box plots**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PsOqKyysCZCv"
      },
      "source": [
        "**Statistical analysis | Mann-Whitney U Test**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {
        "id": "LPdV1vDnWBsh"
      },
      "outputs": [],
      "source": [
        "def mannwhitney(descriptor, verbose=False):\n",
        "  # https://machinelearningmastery.com/nonparametric-statistical-significance-tests-in-python/\n",
        "  from numpy.random import seed\n",
        "  from numpy.random import randn\n",
        "  from scipy.stats import mannwhitneyu\n",
        "\n",
        "# seed the random number generator\n",
        "  seed(1)\n",
        "\n",
        "# actives and inactives\n",
        "  selection = [descriptor, 'class']\n",
        "  df = df_final[selection]\n",
        "  active = df[df['class'] == 'Toxic']\n",
        "  active = active[descriptor]\n",
        "\n",
        "  selection = [descriptor, 'class']\n",
        "  df = df_final[selection]\n",
        "  inactive = df[df['class'] == 'Non-toxic']\n",
        "  inactive = inactive[descriptor]\n",
        "\n",
        "# compare samples\n",
        "  stat, p = mannwhitneyu(active, inactive)\n",
        "  #print('Statistics=%.3f, p=%.3f' % (stat, p))\n",
        "\n",
        "# interpret\n",
        "  alpha = 0.05\n",
        "  if p > alpha:\n",
        "    interpretation = 'Same distribution (fail to reject H0)'\n",
        "  else:\n",
        "    interpretation = 'Different distribution (reject H0)'\n",
        "  \n",
        "  results = pd.DataFrame({'Descriptor':descriptor,\n",
        "                          'Statistics':stat,\n",
        "                          'p':p,\n",
        "                          'alpha':alpha,\n",
        "                          'Interpretation':interpretation}, index=[0])\n",
        "  filename = 'mannwhitneyu_' + descriptor + '.csv'\n",
        "  results.to_csv(filename)\n",
        "\n",
        "  return results"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "o2UlCwPmyTBq"
      },
      "source": [
        "#### **MW**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 370
        },
        "id": "ZNlEEsDEx3m6",
        "outputId": "cb55f787-2687-4f7a-8297-4563efced440"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 396x396 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "plt.figure(figsize=(5.5, 5.5))\n",
        "\n",
        "sns.boxplot(x = 'class', y = 'MW', data = df_final)\n",
        "\n",
        "plt.xlabel('Bioactivity class', fontsize=14, fontweight='bold')\n",
        "plt.ylabel('MW', fontsize=14, fontweight='bold')\n",
        "\n",
        "plt.savefig('plot_MW.pdf')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 81
        },
        "id": "wRl2FvgHYqaG",
        "outputId": "dbee0efb-a623-4473-d1ce-463e41e3f5b0"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  Descriptor  Statistics         p  alpha                      Interpretation\n",
              "0         MW     25065.0  0.002389   0.05  Different distribution (reject H0)"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-6e530282-6704-425b-bb59-56acbecbd701\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Descriptor</th>\n",
              "      <th>Statistics</th>\n",
              "      <th>p</th>\n",
              "      <th>alpha</th>\n",
              "      <th>Interpretation</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>MW</td>\n",
              "      <td>25065.0</td>\n",
              "      <td>0.002389</td>\n",
              "      <td>0.05</td>\n",
              "      <td>Different distribution (reject H0)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-6e530282-6704-425b-bb59-56acbecbd701')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
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              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
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              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-6e530282-6704-425b-bb59-56acbecbd701 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-6e530282-6704-425b-bb59-56acbecbd701');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ],
      "source": [
        "mannwhitney('MW')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "z5hyBhGqyc6J"
      },
      "source": [
        "#### **LogP**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 367
        },
        "id": "liEtkpI4yX9t",
        "outputId": "8f67b6dd-3c72-4014-b4ce-e410358ea812"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 396x396 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "plt.figure(figsize=(5.5, 5.5))\n",
        "\n",
        "sns.boxplot(x = 'class', y = 'LogP', data = df_final)\n",
        "\n",
        "plt.xlabel('Bioactivity class', fontsize=14, fontweight='bold')\n",
        "plt.ylabel('LogP', fontsize=14, fontweight='bold')\n",
        "\n",
        "plt.savefig('plot_LogP.pdf')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2KgV5v_oFLXh"
      },
      "source": [
        "**Statistical analysis | Mann-Whitney U Test**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 81
        },
        "id": "B61UsGMIFLuE",
        "outputId": "985b6869-6140-4364-841c-220d2c28a60a"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  Descriptor  Statistics         p  alpha                      Interpretation\n",
              "0       LogP     25450.5  0.004534   0.05  Different distribution (reject H0)"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-e306cccf-aaa8-486f-8789-32a1d8ceba02\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Descriptor</th>\n",
              "      <th>Statistics</th>\n",
              "      <th>p</th>\n",
              "      <th>alpha</th>\n",
              "      <th>Interpretation</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>LogP</td>\n",
              "      <td>25450.5</td>\n",
              "      <td>0.004534</td>\n",
              "      <td>0.05</td>\n",
              "      <td>Different distribution (reject H0)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e306cccf-aaa8-486f-8789-32a1d8ceba02')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-e306cccf-aaa8-486f-8789-32a1d8ceba02 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-e306cccf-aaa8-486f-8789-32a1d8ceba02');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ],
      "source": [
        "mannwhitney('LogP')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4db7LZLRym2k"
      },
      "source": [
        "#### **NumHDonors**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 367
        },
        "id": "iru1JPM1yg5A",
        "outputId": "29c00cfb-17f7-467a-a496-d413a6422113"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 396x396 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "plt.figure(figsize=(5.5, 5.5))\n",
        "\n",
        "sns.boxplot(x = 'class', y = 'NumHDonors', data = df_final)\n",
        "\n",
        "plt.xlabel('Bioactivity class', fontsize=14, fontweight='bold')\n",
        "plt.ylabel('NumHDonors', fontsize=14, fontweight='bold')\n",
        "\n",
        "plt.savefig('plot_NumHDonors.pdf')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vM5vZWanFe3c"
      },
      "source": [
        "**Statistical analysis | Mann-Whitney U Test**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 21,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 81
        },
        "id": "mS-rOqq7Fd1E",
        "outputId": "81527a95-8d15-4c6b-a03c-5b3b83899c12"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   Descriptor  Statistics         p  alpha                      Interpretation\n",
              "0  NumHDonors     26673.0  0.021797   0.05  Different distribution (reject H0)"
            ],
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              "      <th>Descriptor</th>\n",
              "      <th>Statistics</th>\n",
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              "      <th>Interpretation</th>\n",
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              "      <th>0</th>\n",
              "      <td>NumHDonors</td>\n",
              "      <td>26673.0</td>\n",
              "      <td>0.021797</td>\n",
              "      <td>0.05</td>\n",
              "      <td>Different distribution (reject H0)</td>\n",
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              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-e883a4b0-678f-4e14-87db-13885898633e button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-e883a4b0-678f-4e14-87db-13885898633e');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ],
      "source": [
        "mannwhitney('NumHDonors')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yOYQ3QiSyu7-"
      },
      "source": [
        "#### **NumHAcceptors**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 22,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 367
        },
        "id": "yCw6tgNCyxHf",
        "outputId": "4da473bf-f06a-4764-c112-4e80aebbb190"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 396x396 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "plt.figure(figsize=(5.5, 5.5))\n",
        "\n",
        "sns.boxplot(x = 'class', y = 'NumHAcceptors', data = df_final)\n",
        "\n",
        "plt.xlabel('Bioactivity class', fontsize=14, fontweight='bold')\n",
        "plt.ylabel('NumHAcceptors', fontsize=14, fontweight='bold')\n",
        "\n",
        "plt.savefig('plot_NumHAcceptors.pdf')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 23,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 81
        },
        "id": "NEQoDZctFtGG",
        "outputId": "b518d2ef-bbb4-49af-a005-be23dd5adea9"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      Descriptor  Statistics         p  alpha  \\\n",
              "0  NumHAcceptors     27203.0  0.048219   0.05   \n",
              "\n",
              "                       Interpretation  \n",
              "0  Different distribution (reject H0)  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-7ed7a109-47a6-4e8f-9175-0fc5a841622a\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Descriptor</th>\n",
              "      <th>Statistics</th>\n",
              "      <th>p</th>\n",
              "      <th>alpha</th>\n",
              "      <th>Interpretation</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>NumHAcceptors</td>\n",
              "      <td>27203.0</td>\n",
              "      <td>0.048219</td>\n",
              "      <td>0.05</td>\n",
              "      <td>Different distribution (reject H0)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-7ed7a109-47a6-4e8f-9175-0fc5a841622a')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-7ed7a109-47a6-4e8f-9175-0fc5a841622a button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-7ed7a109-47a6-4e8f-9175-0fc5a841622a');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ],
      "source": [
        "mannwhitney('NumHAcceptors')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "U-rK8l0wWnKK"
      },
      "source": [
        "## **Zip files**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 24,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GW1ZSsfJWqbM",
        "outputId": "ff15e291-b19a-411b-eaf3-d93c7af85fd9"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "updating: plot_MW.pdf (deflated 40%)\n",
            "updating: mannwhitneyu_MW.csv (deflated 9%)\n",
            "updating: plot_bioactivity_class.pdf (deflated 39%)\n",
            "updating: mannwhitneyu_NumHDonors.csv (deflated 10%)\n",
            "updating: plot_NumHDonors.pdf (deflated 38%)\n",
            "updating: plot_MW_vs_LogP.pdf (deflated 21%)\n",
            "updating: mannwhitneyu_LogP.csv (deflated 10%)\n",
            "updating: mannwhitneyu_NumHAcceptors.csv (deflated 10%)\n",
            "updating: plot_LogP.pdf (deflated 39%)\n",
            "updating: plot_NumHAcceptors.pdf (deflated 38%)\n",
            "updating: QSAR_ames_lipinskydata.csv (deflated 75%)\n"
          ]
        }
      ],
      "source": [
        "! zip -r results.zip . -i *.csv *.pdf"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 25,
      "metadata": {
        "id": "LMWOG2UIXEg-",
        "outputId": "ac08666d-185f-49d2-9cee-2d58baaddc5a",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "cp: cannot stat 'ames-test_bioactivity_data.csv': No such file or directory\n"
          ]
        }
      ],
      "source": [
        "! cp ames-test_bioactivity_data.csv \"/content/gdrive/My Drive/Colab Notebooks/data\""
      ]
    }
  ],
  "metadata": {
    "colab": {
      "collapsed_sections": [],
      "name": "AMES_Test-Part-2-Exploratory-Data-Analysis.ipynb",
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python",
      "version": "3.9.7"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}