yandex_hackathon_result_by_ds_team_4.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "1610fbb5",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-info\" style=\"border-radius: 15px; box-shadow: 4px 4px 4px; border: 1px solid \">\n",
    "<font size=\"5\"><b><center>Yandex Hackathon: Result by Team № 4</center></b></font>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a1bea8dd",
   "metadata": {},
   "source": [
    "**Данный ноутбук посвящён сравнению результатов, полученных с помощью разработанного алгоритма, с рекомендациями старой системы и непосредственным решением сотрудника склада:**\n",
    "\n",
    "\n",
    "**Сравнение будет проходить по двум параметрам:**\n",
    "\n",
    " - **Затраты на упаковку**\n",
    "  - **Занимаемый объем при транспортировке**\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a4d1006d",
   "metadata": {},
   "source": [
    "#  Загрузка библиотек"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "0612c0e8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "98f24682e4274d1e85d35f278f25df1c",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import pickle\n",
    "import os\n",
    "from tqdm import tqdm, notebook\n",
    "\n",
    "from matplotlib.gridspec import GridSpec\n",
    "from matplotlib.patches import Patch\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "import scipy\n",
    "from scipy.sparse import csr_matrix\n",
    "from statistics import mean\n",
    "\n",
    "\n",
    "import joblib\n",
    "import faiss\n",
    "from faiss import read_index\n",
    "\n",
    "import warnings\n",
    "import sys\n",
    "\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "notebook.tqdm().pandas()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4629b7c3",
   "metadata": {},
   "source": [
    "# Подготовка инструментов"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "7584af2c",
   "metadata": {},
   "outputs": [],
   "source": [
    "cwd = os.getcwd()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "dbf9f9cf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/Users/greygreywolf/Documents/yandex_market_hackaton_team_4'"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cwd"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1984e4e7",
   "metadata": {},
   "source": [
    "**Пути к данным, моделям, масштабизаторам**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "c22e5b78",
   "metadata": {},
   "outputs": [],
   "source": [
    "PATH_DATA = cwd + '/initial_data/data.csv'\n",
    "PATH_SKU = cwd + '/initial_data/sku.csv'\n",
    "PATH_SKU_CARGOTYPES = cwd + '/initial_data/sku_cargotypes.csv'\n",
    "PATH_CARTON = cwd + '/initial_data/carton.csv'\n",
    "PATH_CARGOTYPES_INFO = cwd + '/initial_data/cargotype_info.csv'\n",
    "PATH_CARTON_PRICE = cwd + '/initial_data/carton_price.xlsx'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "425e0ae7",
   "metadata": {},
   "outputs": [],
   "source": [
    "PATH_TO_SAVE_SCALER_CLASIFIC = cwd + '/for_docker_images/src/scalers/scaler_rb_for_clusific.bin'\n",
    "PATH_TO_SAVE_SCALER_FOR_CLUSTER = cwd + '/for_docker_images/src/scalers/scaler_rb_for_cluster.bin'\n",
    "PATH_TO_SAVE_TFIDF_VECTORIZER = cwd + '/for_docker_images/src/vectorizers/tfidf_vectorizer.bin'\n",
    "PATH_TO_OHE = cwd + \"/for_docker_images/src/scalers/encoder.bin\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "131f9e43",
   "metadata": {},
   "outputs": [],
   "source": [
    "PATH_TO_SAVE_CLUSTERING_MODEL = cwd + \"/for_docker_images/src/models/clustering_model.pkl\"\n",
    "PATH_TO_SAVE_FAISS = cwd + \"/for_docker_images/src/models/fiass_index_with_drop_columns.index\"\n",
    "PATH_TO_SAVE_COLUMNS_TO_DROP = cwd + \"/for_docker_images/src/models/columns_to_drop\"\n",
    "PATH_TO_COLUMNS_TARGET = cwd + '/for_docker_images/src/models/target.csv'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f334ee7b",
   "metadata": {},
   "source": [
    "**Для преобразования датасета возьмем функции описанные в тетрадке с моделированием.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "6751341e",
   "metadata": {},
   "outputs": [],
   "source": [
    "def forming_df_for_tfidf(df_in):\n",
    "    df = df_in.copy(deep=True)\n",
    "    df['cargotype'] = df['cargotype'].astype('str')\n",
    "    df_for_tfidf = df[['sku', 'cargotype']]\n",
    "    df_for_tfidf['cargotype'] = df_for_tfidf['cargotype'] + ' '\n",
    "    df_for_tfidf = df_for_tfidf.groupby('sku')['cargotype'].agg('sum').reset_index(drop=False)\n",
    "    return df_for_tfidf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "e5d8d455",
   "metadata": {},
   "outputs": [],
   "source": [
    "def sorted_dementions_sku(df):\n",
    "    df['list_demensions'] = df.apply(lambda x: sorted([x['a'], x['b'], x['c']]), axis=1)\n",
    "    df['a'] = df.apply(lambda x: x['list_demensions'][0], axis=1)\n",
    "    df['b'] = df.apply(lambda x: x['list_demensions'][1], axis=1)\n",
    "    df['c'] = df.apply(lambda x: x['list_demensions'][2], axis=1)\n",
    "    df.drop('list_demensions', axis=1, inplace=True)\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "4f65a71c",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_tfidf_dataframe(df, tfidf):\n",
    "    tfidf_matrix = tfidf.transform(df['cargotype'])\n",
    "    dict_for_columns = {i[1]: i[0] for i in tfidf.vocabulary_.items()}\n",
    "    new_df = pd.DataFrame.sparse.from_spmatrix(tfidf_matrix).rename(columns=dict_for_columns)\n",
    "    new_df.insert(0, 'sku', df['sku'])\n",
    "    new_df['no_cargotype'] = (df['cargotype'] == '').astype('int')\n",
    "    return new_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "2c3dda97",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_df_for_cluster(df, tfidf, scaler):\n",
    "    new_df = df.copy(deep=True)\n",
    "    df_cargotype = get_tfidf_dataframe(new_df[['sku', 'cargotype']], tfidf)\n",
    "    new_df = new_df[['sku', 'a', 'b', 'c']]\n",
    "    new_df['volume'] = new_df['a'] * new_df['b'] * new_df['c']\n",
    "    new_df = new_df.merge(df_cargotype.drop_duplicates(), how='left', on='sku')\n",
    "    new_df['no_cargotype'] = (df['cargotype'] == '').astype('int')\n",
    "    new_df['no_size'] = ((new_df['a'].values == 0) &\n",
    "                         (new_df['b'].values == 0) &\n",
    "                         (new_df['c'].values == 0)).astype('int')\n",
    "    new_df[['a', 'b', 'c', 'volume']] = scaler.transform(new_df[['a', 'b', 'c', 'volume']])\n",
    "    new_df.drop(['sku'], axis=1, inplace=True)\n",
    "    return new_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "f3e5914f",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_weight_size_charact(df):\n",
    "    new_df = df.copy(deep=True)\n",
    "    new_df['specific_weight'] = new_df['goods_wght'] / new_df['volume']\n",
    "    new_df['specific_weight'] = new_df['specific_weight'].fillna(0)\n",
    "    new_df.loc[new_df['specific_weight'] == np.inf, 'specific_weight'] = sys.maxsize\n",
    "    new_df = new_df.fillna(0)\n",
    "    return new_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "2e3b93a5",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_df_for_predict(df, tfidf, scaler, column_drop):\n",
    "    new_df = df[['sku', 'a', 'b', 'c', 'cluster']]\n",
    "    new_df['volume'] = new_df['a'] * new_df['b'] * new_df['c']\n",
    "    new_df['no_size'] = ((df['a'].values == 0) &\n",
    "                         (df['b'].values == 0) &\n",
    "                         (df['c'].values == 0)).astype('int')\n",
    "    new_df = sorted_dementions_sku(new_df)\n",
    "    df_tfidf = get_tfidf_dataframe(df[['sku', 'cargotype']], tfidf)\n",
    "    new_df = new_df.merge(df_tfidf, how='left', on='sku')\n",
    "    new_df['goods_wght'] = df['goods_wght']\n",
    "    new_df = get_weight_size_charact(new_df)\n",
    "    new_df[['a', 'b', 'c', 'volume', 'goods_wght', 'specific_weight']] = scaler.transform(\n",
    "        new_df[['a', 'b', 'c', 'volume', 'goods_wght', 'specific_weight']])\n",
    "    columns_for_ohe = ['cluster_' + str(i) for i in encoder.categories_[0]]\n",
    "    new_df[columns_for_ohe] = encoder.transform(new_df['cluster'].values.reshape(-1, 1)).toarray()\n",
    "    new_df.drop('cluster', axis=1, inplace=True)\n",
    "    new_df = new_df.drop(column_drop, axis=1)\n",
    "    new_df = new_df.drop('sku', axis=1)\n",
    "    return new_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "69b1e0d3",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_bool_list_ib_list(list1, list2):\n",
    "    res = False\n",
    "    for carton in list1:\n",
    "            if carton in list2:\n",
    "                res = True\n",
    "    return res"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "4971e8cf",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_fit_predict_list_n(index, x_test, k=20, n=3, one_row=True):\n",
    "    xq_x_test = x_test.values.astype('float32')\n",
    "    dem, ind = index.search(xq_x_test, k)\n",
    "    predicted_list = []\n",
    "    for candidates in ind:\n",
    "        predict = []\n",
    "        for candidate in candidates:\n",
    "            if id_base_dict[candidate] not in predict:\n",
    "                predict.append(id_base_dict[candidate])\n",
    "        predicted_list.append(predict[:n])\n",
    "    if one_row:\n",
    "        return list(np.array(predicted_list).reshape(-1, ))\n",
    "    return predicted_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "39b14a07",
   "metadata": {},
   "outputs": [],
   "source": [
    "LIST_BIG_CARTON = ['STRETCH', 'NONPACK']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "40cb2ddc",
   "metadata": {},
   "source": [
    "**Загрузим масштабизаторы, веторизатор и модели**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "7c76188f",
   "metadata": {},
   "outputs": [],
   "source": [
    "scaler_clasific = joblib.load(PATH_TO_SAVE_SCALER_CLASIFIC)\n",
    "scaler_claster = joblib.load(PATH_TO_SAVE_SCALER_FOR_CLUSTER)\n",
    "tfidf = joblib.load(PATH_TO_SAVE_TFIDF_VECTORIZER)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "f8b24d9d",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(PATH_TO_SAVE_CLUSTERING_MODEL, 'rb') as file:\n",
    "    kmeans = pickle.load(file)\n",
    "\n",
    "with open(PATH_TO_SAVE_COLUMNS_TO_DROP, 'rb') as file:\n",
    "    column_drop = pickle.load(file)\n",
    "    \n",
    "with open(PATH_TO_OHE, 'rb') as file:\n",
    "    encoder = pickle.load(file)\n",
    "    \n",
    "    \n",
    "target = (pd.read_csv(PATH_TO_COLUMNS_TARGET))['target']\n",
    "id_base_dict = dict(target.reset_index(drop=True))\n",
    "ind = read_index(PATH_TO_SAVE_FAISS)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4f4049cd",
   "metadata": {},
   "source": [
    "**Загрузим исходные данные и подготовим их для использования разработанного алгоритма**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "e8573bd1",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_data = pd.read_csv(PATH_DATA, index_col=0)\n",
    "df_sku = pd.read_csv(PATH_SKU, index_col=0)\n",
    "df_sku_cargotypes = pd.read_csv(PATH_SKU_CARGOTYPES, index_col=0)\n",
    "df_carton = pd.read_csv(PATH_CARTON, index_col=0)\n",
    "df_carton_price = pd.read_excel(PATH_CARTON_PRICE, names=['cartontype', 'price'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "f2c5d134",
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sku</th>\n",
       "      <th>cargotype</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>12633828</th>\n",
       "      <td>af49bf330e2cf16e44f0be1bdfe337bd</td>\n",
       "      <td>290</td>\n",
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       "    <tr>\n",
       "      <th>12633829</th>\n",
       "      <td>af49bf330e2cf16e44f0be1bdfe337bd</td>\n",
       "      <td>600</td>\n",
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       "    <tr>\n",
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       "      <td>af49bf330e2cf16e44f0be1bdfe337bd</td>\n",
       "      <td>610</td>\n",
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       "    <tr>\n",
       "      <th>12633831</th>\n",
       "      <td>af49bf330e2cf16e44f0be1bdfe337bd</td>\n",
       "      <td>950</td>\n",
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       "      <th>12633832</th>\n",
       "      <td>af49bf330e2cf16e44f0be1bdfe337bd</td>\n",
       "      <td>970</td>\n",
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       "      <th>12633833</th>\n",
       "      <td>af49bf330e2cf16e44f0be1bdfe337bd</td>\n",
       "      <td>980</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                       sku  cargotype\n",
       "12633828  af49bf330e2cf16e44f0be1bdfe337bd        290\n",
       "12633829  af49bf330e2cf16e44f0be1bdfe337bd        600\n",
       "12633830  af49bf330e2cf16e44f0be1bdfe337bd        610\n",
       "12633831  af49bf330e2cf16e44f0be1bdfe337bd        950\n",
       "12633832  af49bf330e2cf16e44f0be1bdfe337bd        970\n",
       "12633833  af49bf330e2cf16e44f0be1bdfe337bd        980"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sku_cargotypes.query('sku == \"af49bf330e2cf16e44f0be1bdfe337bd\"')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0a7eba03",
   "metadata": {},
   "source": [
    "# Предобработка датасета"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d1c6ff60",
   "metadata": {},
   "source": [
    "**Обработаем датасет с карготипами, что бы учесть наличие несколих карготипов для каждого товара**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "011a7821",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sku</th>\n",
       "      <th>cargotype</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4862bf0e760a593b13f3f2fcf822e533</td>\n",
       "      <td>290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4862bf0e760a593b13f3f2fcf822e533</td>\n",
       "      <td>901</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                sku  cargotype\n",
       "0  4862bf0e760a593b13f3f2fcf822e533        290\n",
       "1  4862bf0e760a593b13f3f2fcf822e533        901"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sku_cargotypes.query('sku == \"4862bf0e760a593b13f3f2fcf822e533\"')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "165bccc2",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_sku_cargotypes = forming_df_for_tfidf(df_sku_cargotypes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "62594cb7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sku</th>\n",
       "      <th>cargotype</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1791785</th>\n",
       "      <td>4862bf0e760a593b13f3f2fcf822e533</td>\n",
       "      <td>290 901</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      sku cargotype\n",
       "1791785  4862bf0e760a593b13f3f2fcf822e533  290 901 "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sku_cargotypes.query('sku == \"4862bf0e760a593b13f3f2fcf822e533\"')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "81ecbdd2",
   "metadata": {},
   "source": [
    "**Удалим лишние признаки**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "278bec02",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_data.drop(['selected_cartontype', 'recommended_cartontype',\n",
    "              'who', 'trackingid', 'whs'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6a128d93",
   "metadata": {},
   "source": [
    "**Присоеденим остальные признаки. Несмотря на то, что разработанный алгоритм работает с любыми размерами из датасета, в нем присутсвуют типы упаковок, которых нет в словаре с ценами. В дальнейшем это может помешать оценить затраченную на упавку стоимость, поэтому удалим такие типы.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "0178bd13",
   "metadata": {},
   "outputs": [],
   "source": [
    "full_df = df_data.merge(df_sku, how='left', on='sku')\n",
    "full_df = full_df.merge(df_sku_cargotypes, how='left', on='sku')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "8bec54a9",
   "metadata": {},
   "outputs": [],
   "source": [
    "full_df = df_data.merge(df_sku, how='left', on='sku')\n",
    "full_df = full_df.merge(df_sku_cargotypes, how='left', on='sku')\n",
    "full_df = full_df[full_df['selected_carton'].isin(df_carton_price.cartontype.unique().tolist())]\n",
    "full_df = full_df[full_df['recommended_carton'].isin(df_carton_price.cartontype.unique().tolist())]\n",
    "full_df.reset_index(drop=True, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "be62790e",
   "metadata": {},
   "source": [
    "**Рассчет стоимость текущего датасета займет значительное время, ограничемся последними 60 строками**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "d7072a1c",
   "metadata": {},
   "outputs": [],
   "source": [
    "trancated_df = full_df[276848:276908].copy(deep=True)\n",
    "trancated_df.reset_index(drop=True, inplace=True)\n",
    "trancated_df.dropna(axis=0, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "12da754b",
   "metadata": {},
   "source": [
    "**Обработаме текущий датасет**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "ac94e2fd",
   "metadata": {},
   "outputs": [],
   "source": [
    "trancated_df.sort_values(by=['orderkey'], inplace=True)\n",
    "trancated_df.reset_index(drop=True, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "b1850b8f",
   "metadata": {},
   "outputs": [],
   "source": [
    "for_analysis = trancated_df.copy(deep=True)\n",
    "trancated_df.drop(['orderkey', 'selected_carton', 'recommended_carton', 'pack_volume', 'box_num', 'sel_calc_cube', 'rec_calc_cube'], axis=1, inplace=True)\n",
    "trancated_df = trancated_df[['sku', 'a', 'b', 'c', 'goods_wght', 'cargotype']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "c7724f23",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_sku_cargot_str = forming_df_for_tfidf(trancated_df)\n",
    "trancated_df = trancated_df.drop(['cargotype'], axis=1).merge(df_sku_cargot_str, how='left', on='sku')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "af953fc5",
   "metadata": {},
   "outputs": [],
   "source": [
    "trancated_df = sorted_dementions_sku(trancated_df)\n",
    "df_for_claster = get_df_for_cluster(trancated_df, tfidf, scaler_claster)\n",
    "trancated_df['cluster'] = kmeans.predict(df_for_claster)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "18ebeddb",
   "metadata": {},
   "source": [
    "# Обработка датасета с помощью текущего алгоритма"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bb7eeefd",
   "metadata": {},
   "source": [
    "**Используем алгоритм для группировки товаров и выбора упаковки для каждого заказа из набора данных**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "ad5449d7",
   "metadata": {},
   "outputs": [],
   "source": [
    "dct_wth_orders = {}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "5077bb54",
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "for order in for_analysis['orderkey'].unique().tolist():\n",
    "    df_for_order_analysis = for_analysis.query('orderkey == @order')\n",
    "    first_index_df = df_for_order_analysis.index[0]\n",
    "    last_index_df = df_for_order_analysis.index[-1]\n",
    "    if first_index_df == last_index_df:\n",
    "        df_for_order_for_alg = trancated_df.loc[[first_index_df]]\n",
    "    elif first_index_df != last_index_df:\n",
    "        df_for_order_for_alg = trancated_df[first_index_df:last_index_df]\n",
    "    list_answer = []\n",
    "    # перебираем кластеры по очереди\n",
    "    for cluster in sorted(df_for_order_for_alg['cluster'].unique()):\n",
    "        df_cluster = df_for_order_for_alg[df_for_order_for_alg['cluster'] == cluster]\n",
    "    # Отсортируем df_cluster по объёму\n",
    "        df_cluster['volume'] = df_cluster['a'] * df_cluster['b'] * df_cluster['c']\n",
    "        df_cluster = df_cluster.sort_values('volume', ascending=False)\n",
    "        df_cluster = df_cluster.drop('volume', axis=1)\n",
    "    # сбросим индексы\n",
    "        df_cluster = df_cluster.reset_index(drop=True)\n",
    "    # Создадим словарь с текущей стопкой sku товаров\n",
    "        list_sku = []\n",
    "        while df_cluster.shape[0] != 0:\n",
    "            dict_sku = {}\n",
    "            index_for_drop = [0]  # для записи индексов товаров, которые упакованы\n",
    "            # делаем текущим айтемом первую строку, добавляем её в текущий список sku\n",
    "            item = df_cluster.iloc[:1]\n",
    "            old_item = item.copy(deep=True)\n",
    "            list_sku.append(item.loc[0]['sku'])\n",
    "            # проводим предобработку sku в формат для предсказания и делаем прогноз\n",
    "            item = get_df_for_predict(item, tfidf, scaler_clasific, column_drop)\n",
    "            predict = get_fit_predict_list_n(ind, item)\n",
    "            # Проверяем не один ли товар в ордере, если один, то предиктим, добавляем в словарь, и выходим из цикла\n",
    "            if df_cluster.shape[0] == 1:\n",
    "                dict_sku[' '.join(map(str, list_sku))] = predict\n",
    "                list_answer.append(dict_sku)\n",
    "                break\n",
    "            # Проверяем не был ли товар крупногабаритным по упаковке, если был, то просто добавляем в словарь и дропаем его из датасета\n",
    "            if get_bool_list_ib_list(LIST_BIG_CARTON, predict):\n",
    "                dict_sku[' '.join(map(str, list_sku))] = predict\n",
    "                list_answer.append(dict_sku)\n",
    "                df_cluster = df_cluster[df_cluster.index != 0]\n",
    "                df_cluster = df_cluster.reset_index(drop=True)\n",
    "                list_sku = []\n",
    "            else:\n",
    "            # если товар не был крупногабаритным, то перебираем все оставшиеся товары, чтобы доукомплектовать коробку\n",
    "                for i in range(1, df_cluster.shape[0]):\n",
    "                # Выбираем наименьший размер текущего айтема и доавляем кнему наименьший размер следующего\n",
    "                    new_item = df_cluster.iloc[i:i + 1]\n",
    "                    new_item_sku = new_item.loc[i]['sku']\n",
    "                    new_item['a'] = old_item['a'].values + new_item['a'].values\n",
    "                    # после этого переопределяем наибольший размер по оставшимся двум измерениям\n",
    "                    new_item['b'] = max(old_item['b'].values, new_item['b'].values)\n",
    "                    new_item['c'] = max(old_item['c'].values, new_item['c'].values)\n",
    "                    # определяем вес объединенного айтема\n",
    "                    new_item['goods_wght'] = old_item['goods_wght'].values + new_item['goods_wght'].values\n",
    "                    # определяем новый карготип товара, для этого объединяем карготипы двух рассматриваемых товаров,\n",
    "                    # разделяем их в список, находим уникальные вхождения при помощи множеств, объединяем обратно в строку\n",
    "                    new_item['cargotype'] = ' '.join(set((old_item.loc[0]['cargotype'] + new_item.loc[i]['cargotype']).split()))\n",
    "                    # проводим предобработку sku в формат для предсказания и делаем прогноз\n",
    "                    item_for_pred = get_df_for_predict(new_item.reset_index(drop=True),\n",
    "                                                       tfidf,\n",
    "                                                       scaler_clasific,\n",
    "                                                       column_drop)\n",
    "                    predict_list = get_fit_predict_list_n(ind, item_for_pred)\n",
    "                    # если новый товар не крупногабаритный, тогда добавляем его в список супер товара\n",
    "                    # и дропаем второй товар из df_cluster\n",
    "                    if not get_bool_list_ib_list(LIST_BIG_CARTON, predict_list):\n",
    "                        list_sku.append(new_item_sku)\n",
    "                        index_for_drop.append(i)\n",
    "                        old_item = new_item.reset_index(drop=True)\n",
    "                            # удаляем объект, обнуляем индексы\n",
    "                df_cluster = df_cluster[~df_cluster.index.isin(index_for_drop)]\n",
    "                df_cluster = df_cluster.reset_index(drop=True)\n",
    "                old_item_for_pred = get_df_for_predict(old_item,\n",
    "                                                       tfidf,\n",
    "                                                       scaler_clasific,\n",
    "                                                       column_drop)\n",
    "                # После обхода добавляем в словарь очередной набор\n",
    "                dict_sku[' '.join(map(str, list_sku))] = get_fit_predict_list_n(ind, old_item_for_pred)\n",
    "                list_answer.append(dict_sku)\n",
    "                list_sku = []\n",
    "    dct_wth_orders[order] = list_answer"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bb2e5a82",
   "metadata": {},
   "source": [
    "# Сравнение результатов"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "216ae554",
   "metadata": {},
   "source": [
    "## Сравнение цен "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a4f4dec5",
   "metadata": {},
   "source": [
    "**Сравним затраты на упаковку рекомендованные разработанным алгоритмом с затратами, основанные на выборе человека и рекомендациях предшествующей системы.**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "894e3292",
   "metadata": {},
   "source": [
    "**Создадим словарь цен упаковок**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "1ded648a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'MYA': 1.10986120605469,\n",
       " 'MYB': 2.29743245442708,\n",
       " 'MYC': 3.61671256510417,\n",
       " 'MYD': 6.91837518601191,\n",
       " 'MYE': 8.06272243923611,\n",
       " 'MYF': 4.08313023663949,\n",
       " 'YMA': 4.39293721516927,\n",
       " 'YMC': 7.77748710436699,\n",
       " 'YME': 23.6702600549768,\n",
       " 'YMF': 10.6614871294071,\n",
       " 'YMG': 17.4663671875,\n",
       " 'YML': 37.6945662313433,\n",
       " 'YMW': 13.8700002034505,\n",
       " 'YMX': 28.48125,\n",
       " 'YMY': 40.9111781529018}"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dict_wth_price = dict(zip(df_carton_price.cartontype, df_carton_price.price))\n",
    "dict_wth_price"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5e422fea",
   "metadata": {},
   "source": [
    "**Далее вычислим затраты на паковку рекмендованную предшествующим алгоритмом, и выбранную упаковщиком**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "a92245d6",
   "metadata": {},
   "outputs": [],
   "source": [
    "for_analysis['selected_price'] = for_analysis['selected_carton'].apply(lambda x: dict_wth_price[x] if x not in LIST_BIG_CARTON else 0)\n",
    "for_analysis['recomended_price'] = for_analysis['recommended_carton'].apply(lambda x: dict_wth_price[x] if x not in LIST_BIG_CARTON else 0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4ca76458",
   "metadata": {},
   "source": [
    "**Рассчитаем затраты по результатам работы нового алгоритма, но перед этим сагрегируем полученные результаты**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "9056fa3f",
   "metadata": {},
   "outputs": [],
   "source": [
    "for_analysis_by_order = for_analysis.groupby('orderkey')['selected_price','recomended_price'].sum().reset_index()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d61c7e4f",
   "metadata": {},
   "source": [
    "**Для рассчета цен по результатм финальном алгоритма будем брать первую из трех предложенных упаковок.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "ff8eeffa",
   "metadata": {},
   "outputs": [],
   "source": [
    "for_analysis_by_order['now_price'] = 0\n",
    "for num_order, sku_and_cartontype in dct_wth_orders.items():\n",
    "    for dct in sku_and_cartontype:\n",
    "        for _ , lst_wth_cartontype in dct.items():\n",
    "            if lst_wth_cartontype[0] in LIST_BIG_CARTON:\n",
    "                for_analysis_by_order.loc[for_analysis_by_order['orderkey'] == num_order, 'now_price'] += 0\n",
    "            elif lst_wth_cartontype[0] not in LIST_BIG_CARTON:  \n",
    "                for_analysis_by_order.loc[for_analysis_by_order['orderkey'] == num_order, 'now_price'] += dict_wth_price[lst_wth_cartontype[0]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "d65ed5c9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<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>orderkey</th>\n",
       "      <th>selected_price</th>\n",
       "      <th>recomended_price</th>\n",
       "      <th>now_price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0e4f34db53e37d6bf171c2e055e2b4e0</td>\n",
       "      <td>7.233425</td>\n",
       "      <td>15.554974</td>\n",
       "      <td>2.297432</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0f7044e79cb62222396cc81e4ce53e10</td>\n",
       "      <td>3.616713</td>\n",
       "      <td>7.777487</td>\n",
       "      <td>2.297432</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>207fca032df1ef3ff517b7460a9be52f</td>\n",
       "      <td>23.332461</td>\n",
       "      <td>23.332461</td>\n",
       "      <td>6.918375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2eb73fa9fd34c6b85a47082d0efe6fca</td>\n",
       "      <td>4.392937</td>\n",
       "      <td>4.392937</td>\n",
       "      <td>2.297432</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3acc4b901256bcd9f333b6978864773b</td>\n",
       "      <td>7.777487</td>\n",
       "      <td>7.777487</td>\n",
       "      <td>1.109861</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>40cb76ed7064202a5b8a5ce9cbfb1de4</td>\n",
       "      <td>13.836750</td>\n",
       "      <td>47.340520</td>\n",
       "      <td>2.297432</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>4207ef10bd059f8b57a5796657d4cccc</td>\n",
       "      <td>40.313612</td>\n",
       "      <td>87.331836</td>\n",
       "      <td>4.594865</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>4b311935811db1e95e60a13f7876f4dc</td>\n",
       "      <td>15.554974</td>\n",
       "      <td>15.554974</td>\n",
       "      <td>2.297432</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>5d71fcf9bc99aa8a1cc3cfb76f4f678b</td>\n",
       "      <td>16.125445</td>\n",
       "      <td>47.340520</td>\n",
       "      <td>2.297432</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>741bdd8e6a671176d33b174552aaafea</td>\n",
       "      <td>6.918375</td>\n",
       "      <td>7.777487</td>\n",
       "      <td>3.616713</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>744d44b955662ba88ce76f65c4ecc6c2</td>\n",
       "      <td>7.777487</td>\n",
       "      <td>7.777487</td>\n",
       "      <td>23.670260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>79280f65326de924b331cace4c6becaa</td>\n",
       "      <td>83.220001</td>\n",
       "      <td>104.798203</td>\n",
       "      <td>13.836750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>968d5b8026ba427e274645bf329a734a</td>\n",
       "      <td>2.297432</td>\n",
       "      <td>2.297432</td>\n",
       "      <td>2.297432</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>9a1a1e90a1f256d40be7afcad3fc95e5</td>\n",
       "      <td>4.392937</td>\n",
       "      <td>4.392937</td>\n",
       "      <td>3.616713</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>b2d5108421ce9c823a083fdaf870b9a2</td>\n",
       "      <td>83.220001</td>\n",
       "      <td>104.798203</td>\n",
       "      <td>13.836750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>bb55964e80fac7350f84cbde59c5876c</td>\n",
       "      <td>27.740000</td>\n",
       "      <td>34.932734</td>\n",
       "      <td>6.918375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>bcdba58921c3a0ffdd5601060fcadd9d</td>\n",
       "      <td>83.220001</td>\n",
       "      <td>104.798203</td>\n",
       "      <td>13.836750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>c702d7560bbd2846fccd7d03af6e3980</td>\n",
       "      <td>35.143498</td>\n",
       "      <td>35.143498</td>\n",
       "      <td>17.571749</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>e10a25df37f434a7f5fd0c64fdcfec72</td>\n",
       "      <td>8.785874</td>\n",
       "      <td>15.554974</td>\n",
       "      <td>2.297432</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>f0e3c38687aa6ba1e61831a14f258035</td>\n",
       "      <td>83.220001</td>\n",
       "      <td>104.798203</td>\n",
       "      <td>13.836750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>f1a5e5ba97b77db86e1d747d0d4dbbfb</td>\n",
       "      <td>2.297432</td>\n",
       "      <td>7.777487</td>\n",
       "      <td>2.297432</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            orderkey  selected_price  recomended_price  \\\n",
       "0   0e4f34db53e37d6bf171c2e055e2b4e0        7.233425         15.554974   \n",
       "1   0f7044e79cb62222396cc81e4ce53e10        3.616713          7.777487   \n",
       "2   207fca032df1ef3ff517b7460a9be52f       23.332461         23.332461   \n",
       "3   2eb73fa9fd34c6b85a47082d0efe6fca        4.392937          4.392937   \n",
       "4   3acc4b901256bcd9f333b6978864773b        7.777487          7.777487   \n",
       "5   40cb76ed7064202a5b8a5ce9cbfb1de4       13.836750         47.340520   \n",
       "6   4207ef10bd059f8b57a5796657d4cccc       40.313612         87.331836   \n",
       "7   4b311935811db1e95e60a13f7876f4dc       15.554974         15.554974   \n",
       "8   5d71fcf9bc99aa8a1cc3cfb76f4f678b       16.125445         47.340520   \n",
       "9   741bdd8e6a671176d33b174552aaafea        6.918375          7.777487   \n",
       "10  744d44b955662ba88ce76f65c4ecc6c2        7.777487          7.777487   \n",
       "11  79280f65326de924b331cace4c6becaa       83.220001        104.798203   \n",
       "12  968d5b8026ba427e274645bf329a734a        2.297432          2.297432   \n",
       "13  9a1a1e90a1f256d40be7afcad3fc95e5        4.392937          4.392937   \n",
       "14  b2d5108421ce9c823a083fdaf870b9a2       83.220001        104.798203   \n",
       "15  bb55964e80fac7350f84cbde59c5876c       27.740000         34.932734   \n",
       "16  bcdba58921c3a0ffdd5601060fcadd9d       83.220001        104.798203   \n",
       "17  c702d7560bbd2846fccd7d03af6e3980       35.143498         35.143498   \n",
       "18  e10a25df37f434a7f5fd0c64fdcfec72        8.785874         15.554974   \n",
       "19  f0e3c38687aa6ba1e61831a14f258035       83.220001        104.798203   \n",
       "20  f1a5e5ba97b77db86e1d747d0d4dbbfb        2.297432          7.777487   \n",
       "\n",
       "    now_price  \n",
       "0    2.297432  \n",
       "1    2.297432  \n",
       "2    6.918375  \n",
       "3    2.297432  \n",
       "4    1.109861  \n",
       "5    2.297432  \n",
       "6    4.594865  \n",
       "7    2.297432  \n",
       "8    2.297432  \n",
       "9    3.616713  \n",
       "10  23.670260  \n",
       "11  13.836750  \n",
       "12   2.297432  \n",
       "13   3.616713  \n",
       "14  13.836750  \n",
       "15   6.918375  \n",
       "16  13.836750  \n",
       "17  17.571749  \n",
       "18   2.297432  \n",
       "19  13.836750  \n",
       "20   2.297432  "
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for_analysis_by_order"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "ae36ac19",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1500x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15, 10))\n",
    "plt.title('Сравнение цен на тип выбранный упаковки по заказам', fontsize=17)\n",
    "sns.set_style('darkgrid')\n",
    "sns.barplot(data=for_analysis_by_order,\n",
    "            x=for_analysis_by_order.orderkey,\n",
    "            y='selected_price',\n",
    "            color='lightgreen',\n",
    "            alpha=0.5,\n",
    "            label = 'Цена выбранная упаковщиком')\n",
    "sns.barplot(data=for_analysis_by_order,\n",
    "            x=for_analysis_by_order.orderkey,\n",
    "            y='recomended_price',\n",
    "            alpha=0.5,\n",
    "            color='lightblue',\n",
    "            label = 'Цена выбранная старым алгоритмом')\n",
    "sns.barplot(data=for_analysis_by_order,\n",
    "            x=for_analysis_by_order.orderkey,\n",
    "            y='now_price',\n",
    "            alpha=0.5,\n",
    "            color='red',\n",
    "            label = 'Цена выбранная новым алгоритмом')\n",
    "plt.ylabel('Цена', fontsize=14)\n",
    "plt.xlabel('Заказы', fontsize=14)\n",
    "plt.xticks(rotation=90)\n",
    "plt.grid(True)\n",
    "plt.legend(edgecolor = 'r',\n",
    "           facecolor = 'oldlace');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "7964fba3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'4d4734cd71d9b24871f37c7df29c2ed9': ['YME', 'MYC', 'NONPACK']}]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dct_wth_orders['744d44b955662ba88ce76f65c4ecc6c2']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bf13c1f5",
   "metadata": {},
   "source": [
    "**Из графика выше можно сделать вывод, что для большинства заказов текущий алгоритм выбирает наименьшую по стоимости упаковку, в том числе немаловажную роль играет группировка товаров. В отдельных случая , как с заказом выше новая цена превышает предыдущую. Так как модель обучалась из соображений не только экономии пространства и стоимости упаковки, но и сохранения надлежащего качества товара во время доставки, первый варинт рекомендации значительно дороже того, что был ранее. Так же стоит обратить внимание на то, что в рекомендациях присутствуют три варианта, среди которых есть \"NONPACK\". В подобных случаях упаковщику следует учитывать качества товара и выбрать подходящий варинат. Так же можно предположить, что количество товаров с такими характеристками в датасете значительно мало, и модель могла недостаточно обучится работе с этим типом.**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fa5e77b6",
   "metadata": {},
   "source": [
    "**В дополнениеследует отметить, что старая рекомендательная система почти всегда предлогала самую дорогую упаковку. Упаковщик выбирал менее затратные варианты.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "fd9a4b71",
   "metadata": {},
   "outputs": [],
   "source": [
    "total_price = for_analysis_by_order[['selected_price','recomended_price','now_price']].agg('sum').reset_index().rename(columns={'index': 'price', 0: 'value'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "f7008de8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<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>price</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>selected_price</td>\n",
       "      <td>560.416847</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>recomended_price</td>\n",
       "      <td>791.250047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>now_price</td>\n",
       "      <td>144.040804</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              price       value\n",
       "0    selected_price  560.416847\n",
       "1  recomended_price  791.250047\n",
       "2         now_price  144.040804"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total_price"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "b2ceae8d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 7))\n",
    "plt.title('Общее сравнение цен на упаковку', fontsize=17)\n",
    "sns.set_style('darkgrid')\n",
    "sns.barplot(data=total_price,\n",
    "            x='price',\n",
    "            y='value',\n",
    "            palette=['lightgreen', 'lightblue', 'red'])\n",
    "plt.ylabel('Значение цены', fontsize=14)\n",
    "plt.xlabel('Тип цены', fontsize=14)\n",
    "plt.grid(True)\n",
    "plt.legend(handles=[Patch(color='lightgreen', alpha=.5, label=f'Общее стоимость упаковок, выбранная упаковщиком'),\n",
    "                    Patch(color='lightblue', alpha=.5, label=f'Общая стоимость упаковок , рекомендованных старым алгоритмом'),\n",
    "                    Patch(color='red', alpha=.5, label=f'Общая стоимость упаковок , рекомендованных новым алгоритмом')],\n",
    "           edgecolor = 'r',\n",
    "           facecolor = 'oldlace', \n",
    "           loc='center',\n",
    "           bbox_to_anchor=(0.5, -0.2));"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4443e4b7",
   "metadata": {},
   "source": [
    "**Общая значение расходов на упаковки, рекомендованные новым алгоритмом, значительно ниже рекомендаций старого алгоритма и выбора упавощика**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "654fc8f1",
   "metadata": {},
   "source": [
    "## Сравнение объема"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b6cbd479",
   "metadata": {},
   "source": [
    "**Теперь сравним объем упакованных товаров**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "5b118e8b",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_carton = df_carton.reset_index()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5b3f7e44",
   "metadata": {},
   "source": [
    "**Вычислим объем для упаковок**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "4ca4c7da",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_carton['volume'] = df_carton['LENGTH'] * df_carton['WIDTH'] * df_carton['HEIGHT']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f31521a9",
   "metadata": {},
   "source": [
    "**Создадим словарь размеров упаковок.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "a157b0a3",
   "metadata": {},
   "outputs": [],
   "source": [
    "dict_wth_volume = dict(zip(df_carton.CARTONTYPE, df_carton.volume))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "8582b523",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'YMA': 3705.0,\n",
       " 'YMC': 9000.0,\n",
       " 'YME': 40050.0,\n",
       " 'YMF': 13125.0,\n",
       " 'YMG': 26820.0,\n",
       " 'YMH': 72240.0,\n",
       " 'YMJ': 69600.0,\n",
       " 'KSD': 0.0,\n",
       " 'YML': 108000.0,\n",
       " 'YMN': 144000.0,\n",
       " 'YMO': 58500.0,\n",
       " 'YMP': 46200.0,\n",
       " 'YMQ': 168000.0,\n",
       " 'YMR': 384000.0,\n",
       " 'YMS': 263599.875,\n",
       " 'NONPACK': 0.0,\n",
       " 'STRETCH': 0.0,\n",
       " 'YMU': 2592.0,\n",
       " 'YMV': 4292.0,\n",
       " 'YMW': 18000.0,\n",
       " 'YMХ': 46800.0,\n",
       " 'MYF': 1500.0,\n",
       " 'YMX': 46800.0,\n",
       " 'YMY': 72800.0,\n",
       " 'MYA': 999.0,\n",
       " 'MYB': 3449.6000000000004,\n",
       " 'MYC': 8436.0,\n",
       " 'MYD': 15579.999999999998,\n",
       " 'MYE': 26277.3}"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dict_wth_volume"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "08a3cf3b",
   "metadata": {},
   "outputs": [],
   "source": [
    "for_analysis['total_volume_of_goods'] = for_analysis['a'] * for_analysis['b'] * for_analysis['c']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "288d3673",
   "metadata": {},
   "outputs": [],
   "source": [
    "for_analysis_by_order = for_analysis.groupby('orderkey')['sel_calc_cube','rec_calc_cube', 'total_volume_of_goods'].sum().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "28e514ea",
   "metadata": {},
   "outputs": [],
   "source": [
    "for_analysis_by_order['now_volume'] = 0\n",
    "for num_order, sku_and_cartontype in dct_wth_orders.items():\n",
    "    for dct in sku_and_cartontype:\n",
    "        for _ , lst_wth_cartontype in dct.items():\n",
    "            if lst_wth_cartontype[0] in LIST_BIG_CARTON:\n",
    "                for_analysis_by_order.loc[for_analysis_by_order['orderkey'] == num_order, 'now_volume'] += 0\n",
    "            elif lst_wth_cartontype[0] not in LIST_BIG_CARTON:  \n",
    "                for_analysis_by_order.loc[for_analysis_by_order['orderkey'] == num_order, 'now_volume'] += dict_wth_volume[lst_wth_cartontype[0]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "d2aca11e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<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>orderkey</th>\n",
       "      <th>sel_calc_cube</th>\n",
       "      <th>rec_calc_cube</th>\n",
       "      <th>total_volume_of_goods</th>\n",
       "      <th>now_volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0e4f34db53e37d6bf171c2e055e2b4e0</td>\n",
       "      <td>9120</td>\n",
       "      <td>17050</td>\n",
       "      <td>4160.000</td>\n",
       "      <td>3449.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0f7044e79cb62222396cc81e4ce53e10</td>\n",
       "      <td>4560</td>\n",
       "      <td>8525</td>\n",
       "      <td>2080.000</td>\n",
       "      <td>3449.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>207fca032df1ef3ff517b7460a9be52f</td>\n",
       "      <td>25575</td>\n",
       "      <td>25575</td>\n",
       "      <td>4186.000</td>\n",
       "      <td>15580.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2eb73fa9fd34c6b85a47082d0efe6fca</td>\n",
       "      <td>3360</td>\n",
       "      <td>3360</td>\n",
       "      <td>577.490</td>\n",
       "      <td>3449.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3acc4b901256bcd9f333b6978864773b</td>\n",
       "      <td>8525</td>\n",
       "      <td>8525</td>\n",
       "      <td>4050.000</td>\n",
       "      <td>999.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>40cb76ed7064202a5b8a5ce9cbfb1de4</td>\n",
       "      <td>15200</td>\n",
       "      <td>86400</td>\n",
       "      <td>31250.000</td>\n",
       "      <td>3449.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>4207ef10bd059f8b57a5796657d4cccc</td>\n",
       "      <td>54180</td>\n",
       "      <td>91350</td>\n",
       "      <td>14684.150</td>\n",
       "      <td>6899.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>4b311935811db1e95e60a13f7876f4dc</td>\n",
       "      <td>17050</td>\n",
       "      <td>17050</td>\n",
       "      <td>1387.490</td>\n",
       "      <td>3449.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>5d71fcf9bc99aa8a1cc3cfb76f4f678b</td>\n",
       "      <td>21672</td>\n",
       "      <td>86400</td>\n",
       "      <td>18424.000</td>\n",
       "      <td>3449.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>741bdd8e6a671176d33b174552aaafea</td>\n",
       "      <td>7600</td>\n",
       "      <td>8525</td>\n",
       "      <td>3724.000</td>\n",
       "      <td>8436.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>744d44b955662ba88ce76f65c4ecc6c2</td>\n",
       "      <td>8525</td>\n",
       "      <td>8525</td>\n",
       "      <td>408.000</td>\n",
       "      <td>40050.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>79280f65326de924b331cace4c6becaa</td>\n",
       "      <td>130872</td>\n",
       "      <td>109620</td>\n",
       "      <td>12512.178</td>\n",
       "      <td>31160.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>968d5b8026ba427e274645bf329a734a</td>\n",
       "      <td>2816</td>\n",
       "      <td>2816</td>\n",
       "      <td>378.000</td>\n",
       "      <td>3449.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>9a1a1e90a1f256d40be7afcad3fc95e5</td>\n",
       "      <td>3360</td>\n",
       "      <td>3360</td>\n",
       "      <td>624.000</td>\n",
       "      <td>8436.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>b2d5108421ce9c823a083fdaf870b9a2</td>\n",
       "      <td>130872</td>\n",
       "      <td>109620</td>\n",
       "      <td>12512.178</td>\n",
       "      <td>31160.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>bb55964e80fac7350f84cbde59c5876c</td>\n",
       "      <td>43624</td>\n",
       "      <td>36540</td>\n",
       "      <td>4170.726</td>\n",
       "      <td>15580.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>bcdba58921c3a0ffdd5601060fcadd9d</td>\n",
       "      <td>130872</td>\n",
       "      <td>109620</td>\n",
       "      <td>12512.178</td>\n",
       "      <td>31160.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>c702d7560bbd2846fccd7d03af6e3980</td>\n",
       "      <td>26880</td>\n",
       "      <td>26880</td>\n",
       "      <td>2152.000</td>\n",
       "      <td>14820.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>e10a25df37f434a7f5fd0c64fdcfec72</td>\n",
       "      <td>6720</td>\n",
       "      <td>17050</td>\n",
       "      <td>1728.000</td>\n",
       "      <td>3449.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>f0e3c38687aa6ba1e61831a14f258035</td>\n",
       "      <td>130872</td>\n",
       "      <td>109620</td>\n",
       "      <td>12512.178</td>\n",
       "      <td>31160.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>f1a5e5ba97b77db86e1d747d0d4dbbfb</td>\n",
       "      <td>2816</td>\n",
       "      <td>8525</td>\n",
       "      <td>680.680</td>\n",
       "      <td>3449.6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            orderkey  sel_calc_cube  rec_calc_cube  \\\n",
       "0   0e4f34db53e37d6bf171c2e055e2b4e0           9120          17050   \n",
       "1   0f7044e79cb62222396cc81e4ce53e10           4560           8525   \n",
       "2   207fca032df1ef3ff517b7460a9be52f          25575          25575   \n",
       "3   2eb73fa9fd34c6b85a47082d0efe6fca           3360           3360   \n",
       "4   3acc4b901256bcd9f333b6978864773b           8525           8525   \n",
       "5   40cb76ed7064202a5b8a5ce9cbfb1de4          15200          86400   \n",
       "6   4207ef10bd059f8b57a5796657d4cccc          54180          91350   \n",
       "7   4b311935811db1e95e60a13f7876f4dc          17050          17050   \n",
       "8   5d71fcf9bc99aa8a1cc3cfb76f4f678b          21672          86400   \n",
       "9   741bdd8e6a671176d33b174552aaafea           7600           8525   \n",
       "10  744d44b955662ba88ce76f65c4ecc6c2           8525           8525   \n",
       "11  79280f65326de924b331cace4c6becaa         130872         109620   \n",
       "12  968d5b8026ba427e274645bf329a734a           2816           2816   \n",
       "13  9a1a1e90a1f256d40be7afcad3fc95e5           3360           3360   \n",
       "14  b2d5108421ce9c823a083fdaf870b9a2         130872         109620   \n",
       "15  bb55964e80fac7350f84cbde59c5876c          43624          36540   \n",
       "16  bcdba58921c3a0ffdd5601060fcadd9d         130872         109620   \n",
       "17  c702d7560bbd2846fccd7d03af6e3980          26880          26880   \n",
       "18  e10a25df37f434a7f5fd0c64fdcfec72           6720          17050   \n",
       "19  f0e3c38687aa6ba1e61831a14f258035         130872         109620   \n",
       "20  f1a5e5ba97b77db86e1d747d0d4dbbfb           2816           8525   \n",
       "\n",
       "    total_volume_of_goods  now_volume  \n",
       "0                4160.000      3449.6  \n",
       "1                2080.000      3449.6  \n",
       "2                4186.000     15580.0  \n",
       "3                 577.490      3449.6  \n",
       "4                4050.000       999.0  \n",
       "5               31250.000      3449.6  \n",
       "6               14684.150      6899.2  \n",
       "7                1387.490      3449.6  \n",
       "8               18424.000      3449.6  \n",
       "9                3724.000      8436.0  \n",
       "10                408.000     40050.0  \n",
       "11              12512.178     31160.0  \n",
       "12                378.000      3449.6  \n",
       "13                624.000      8436.0  \n",
       "14              12512.178     31160.0  \n",
       "15               4170.726     15580.0  \n",
       "16              12512.178     31160.0  \n",
       "17               2152.000     14820.0  \n",
       "18               1728.000      3449.6  \n",
       "19              12512.178     31160.0  \n",
       "20                680.680      3449.6  "
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for_analysis_by_order"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "6a9487cc",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_for_bar = pd.melt(for_analysis_by_order, id_vars=['orderkey'], value_vars=['sel_calc_cube', 'rec_calc_cube',\n",
    "                                                                              'total_volume_of_goods',\n",
    "                                                                              'now_volume'])\n",
    "df_for_bar['variable'] = df_for_bar['variable'].replace({'sel_calc_cube': 'Объем выбранный упаковщиком',\n",
    "                                                         'rec_calc_cube': 'Обьем рекомндованный старым алгоритмом',\n",
    "                                                         'total_volume_of_goods': 'Суммарный объем товаров',\n",
    "                                                         'now_volume': 'Объем рассчитаный новым алгоритмом'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "e3a51ebd",
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 2000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20, 10))\n",
    "sns.barplot(data=df_for_bar,\n",
    "            x=df_for_bar.orderkey,\n",
    "            y=df_for_bar.value,\n",
    "            hue = 'variable',\n",
    "            palette='Set2')\n",
    "plt.ylabel('Объем', fontsize=14)\n",
    "plt.xlabel('Заказы', fontsize=14)\n",
    "plt.xticks(rotation=90)\n",
    "plt.grid(True)\n",
    "plt.legend(edgecolor = 'r',\n",
    "           facecolor = 'oldlace');"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "afcc778b",
   "metadata": {},
   "source": [
    "**Благодаря тщательной компановке товаров новому алгоритму в большинстве случаев удалось рационализировать занимаемое при транспортровке место в равнение с старой рекомендательной ситемой и человеческим фактором. Кроме того, на графике присутсвуют аномалии, а именно 4 случая, где суммарный обьем товаров в заказе превышает объем рекомендованной упаковки. Рассмотрим эти случае подробно.**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0cc159d7",
   "metadata": {},
   "source": [
    "**Выведем отдельно содержимое заказов.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "5ec21ecf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'bd4fcd43314a9b3e28cbf7ae22b3ece4': ['MYA', 'MYB', 'YMG']}]"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dct_wth_orders['3acc4b901256bcd9f333b6978864773b']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "a2ce91f4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'de2a4fb8e7834ab11f2a7bdf48c69482': ['MYB', 'NONPACK', 'MYA']}]"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dct_wth_orders['40cb76ed7064202a5b8a5ce9cbfb1de4']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "afc144d8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'e40f1c96a8de1baaa44fec15d7ae5268 e40f1c96a8de1baaa44fec15d7ae5268': ['MYB',\n",
       "   'YMG',\n",
       "   'MYD']},\n",
       " {'e40f1c96a8de1baaa44fec15d7ae5268 e40f1c96a8de1baaa44fec15d7ae5268': ['MYB',\n",
       "   'YMG',\n",
       "   'MYD']}]"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dct_wth_orders['4207ef10bd059f8b57a5796657d4cccc']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "29bde03f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'8560b5d4a4fe66486c568fab84a34b10': ['MYB', 'MYA', 'YMG']}]"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dct_wth_orders['5d71fcf9bc99aa8a1cc3cfb76f4f678b']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "97cd21fa",
   "metadata": {},
   "source": [
    "**Посмотрим на количество товаров из заказа в общем датасете.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "956fe8a1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Количетсво товаров с sku-bd4fcd43314a9b3e28cbf7ae22b3ece4 в датасете - 6\n",
      "Количетсво товаров с sku-de2a4fb8e7834ab11f2a7bdf48c69482 в датасете - 9\n",
      "Количетсво товаров с sku-e40f1c96a8de1baaa44fec15d7ae5268 в датасете - 69\n",
      "Количетсво товаров с sku-8560b5d4a4fe66486c568fab84a34b10 в датасете - 21\n"
     ]
    }
   ],
   "source": [
    "for sku in ['bd4fcd43314a9b3e28cbf7ae22b3ece4', 'de2a4fb8e7834ab11f2a7bdf48c69482', 'e40f1c96a8de1baaa44fec15d7ae5268', '8560b5d4a4fe66486c568fab84a34b10']:\n",
    "    print(f'Количетсво товаров с sku-{sku} в датасете -', len(df_data.query('sku == @sku')))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "71053ea4",
   "metadata": {},
   "source": [
    "**Учитывая небольшое количество примеров в датасете с этими товарами, можно сделать вывод, что модель недообучилась. В дальнейшем, при большем наборе данных качество модели можно будет значительно улучшить.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "4efbc3ec",
   "metadata": {},
   "outputs": [],
   "source": [
    "total_volume = for_analysis_by_order[['sel_calc_cube','rec_calc_cube','now_volume', 'total_volume_of_goods']].agg('sum').reset_index().rename(columns={'index': 'volume', 0: 'value'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "ae20a014",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<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>volume</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>sel_calc_cube</td>\n",
       "      <td>785071.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>rec_calc_cube</td>\n",
       "      <td>894936.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>now_volume</td>\n",
       "      <td>266486.600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>total_volume_of_goods</td>\n",
       "      <td>144713.248</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  volume       value\n",
       "0          sel_calc_cube  785071.000\n",
       "1          rec_calc_cube  894936.000\n",
       "2             now_volume  266486.600\n",
       "3  total_volume_of_goods  144713.248"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total_volume"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "cf84f9b4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 7))\n",
    "plt.title('Общее сравнение объема упакованных товаров', fontsize=17)\n",
    "sns.set_style('darkgrid')\n",
    "sns.barplot(data=total_volume,\n",
    "            x='volume',\n",
    "            y='value',\n",
    "            palette=['lightgreen', 'lightblue', 'red', 'magenta'])\n",
    "plt.ylabel('Значение объема', fontsize=14)\n",
    "plt.xlabel('Тип объема', fontsize=14)\n",
    "plt.grid(True)\n",
    "plt.legend(handles=[Patch(color='lightgreen', alpha=.5, label=f'Общее объем упакованных товаров от упаковщика'),\n",
    "                    Patch(color='lightblue', alpha=.5, label=f'Общее объем упакованных товаров от старого алгоритма'),\n",
    "                    Patch(color='red', alpha=.5, label=f'Общее объем упакованных товаров от нового алгоритма'),\n",
    "                    Patch(color='magenta', alpha=.5, label=f'Общее объем товаров')],\n",
    "           edgecolor = 'r',\n",
    "           facecolor = 'oldlace', \n",
    "           loc='center',\n",
    "           bbox_to_anchor=(0.5, -0.2));"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9b24b97a",
   "metadata": {},
   "source": [
    "**Новый алгоритм позволит значительно сэкономить место при транспортировке**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bbc25815",
   "metadata": {},
   "source": [
    "# Выводы"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "52a0379d",
   "metadata": {},
   "source": [
    "В результате проделанной работы был разработан алгоритм, позволяющий:\n",
    "\n",
    "    1. Значительно зкономить место при транспортировке за счет компановки товаров в заказе.\n",
    "    2. Снизить затраты на упаковку для товара/группы товаров.\n",
    "    3. Иметь вариативность в выборе из нескольких предложенных для товаров упаковок, в случае если какой либо не   будет на складе."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.16"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}