global-temp.ipynb

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        "<a href=\"https://colab.research.google.com/github/QuarkNet-HEP/coding-camp/blob/main/global-temp.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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      "cell_type": "markdown",
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        "id": "NF8PU7MWToHq"
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      "source": [
        "# Global Surface Temperature\n",
        "This activity analyzes historical data on global temperature changes from [NASA's GISS Surface Temperature Analysis (GISTEMP)](http://data.giss.nasa.gov/gistemp/).\n",
        "\n",
        "To get started,\n",
        "- You won't hurt anything by experimenting. If you break it, close the tab and open the activity again to start over.\n",
        "- Is this your first time? Need a refresher? Try the 5-minute [Intro to Coding activity](https://colab.research.google.com/github/adamlamee/CODINGinK12/blob/master/notebooks/intro.ipynb) and come back here. \n",
        "\n",
        "When you're ready, run each code cell until you get down to **Part One**."
      ]
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    {
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      "source": [
        "# import the software packages needed\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "%matplotlib inline\n",
        "import matplotlib as mpl\n",
        "import matplotlib.pyplot as plt"
      ]
    },
    {
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      "source": [
        "# Only land temperature averages\n",
        "data1 = pd.read_csv('http://github.com/adamlamee/CODINGinK12/raw/master/data/LAND.csv', header=1).replace(to_replace=\"***\", value=np.NaN)\n",
        "data_LAND_AVG = data1.apply(lambda x: pd.to_numeric(x, errors='ignore'))\n",
        "\n",
        "# Combined land and ocean temperature averages (LOTI: Land Ocean Temperature Index)\n",
        "data2 = pd.read_csv('http://github.com/adamlamee/CODINGinK12/raw/master/data/LOTI.csv', header=1).replace(to_replace=\"***\", value=np.NaN)\n",
        "data_LAND_OCEAN_AVG = data2.apply(lambda x: pd.to_numeric(x, errors='ignore'))"
      ]
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    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "m_0oezVPToHx"
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      "source": [
        "# The .head(n) command displays the first n rows of the file.\n",
        "data_LAND_AVG.head(5)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ylaYDV2gToHy"
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      "outputs": [],
      "source": [
        "# The .shape command displays the (number of rows , number of columns) in a file.\n",
        "data_LAND_AVG.shape"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "f1OzbxAiToHy"
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      "source": [
        "## Part One\n",
        "Let's get acquainted with this data set. Look at the cells above to find the answers to the following questions:\n",
        "- In the table above, what do you think each of the column headings represent?\n",
        "- How many years are included in this data set?\n",
        "\n",
        "When you're ready, scroll down to **Part Two**."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "jp7I-BWtToHy"
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      "outputs": [],
      "source": [
        "x = data_LAND_AVG['Year']\n",
        "y = data_LAND_AVG['JanDec']\n",
        "\n",
        "# plt.plot() makes a line graph\n",
        "fig = plt.figure(figsize=(10, 5))\n",
        "plt.plot(x, y)\n",
        "plt.axhline(0, color='gray')   # try chaning the color. It only knows some color names, though.\n",
        "plt.title('Title me!')\n",
        "plt.xlabel('I need a label')\n",
        "plt.ylabel('I probably need one, too');"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3F2xfCERToHy"
      },
      "source": [
        "## Part Two  \n",
        "The code above generates a graph of average land temperature readings each year, in percent temperature change from past 5-year average.  \n",
        "- The title and axis labels on the graph could use some work. Try editing the code above the graph, then run the code again to see the changes.  \n",
        "- Which years had higher temperatures than the previous 5-year average? When was it cooler than the past 5-year average?  \n",
        "\n",
        "When you're ready, scroll down to Part Three."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "VwHTZw_JToHy"
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      "outputs": [],
      "source": [
        "# Wow, this needs a title and axis labels!\n",
        "fig = plt.figure(figsize=(10, 5))\n",
        "plt.plot(data_LAND_AVG['Year'], data_LAND_AVG['JanDec'], label=\"Land average\")\n",
        "plt.plot(data_LAND_OCEAN_AVG['Year'], data_LAND_OCEAN_AVG['JanDec'], label=\"Land + Ocean average\")\n",
        "plt.axhline(0, color='gray')\n",
        "plt.title('Title me!')\n",
        "plt.xlabel('I need a label')\n",
        "plt.ylabel('I probably need one, too')\n",
        "plt.legend()\n",
        "plt.show()"
      ]
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    {
      "cell_type": "markdown",
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      "source": [
        "## Part Three\n",
        "NASA also measured ocean temperatures. The graph above also shows *combined average temperature for ocean and land* for the same time range.\n",
        "- What differences can you see between the two data sets?  \n",
        "- When is the combined land and ocean average warmer than just the land temperature? When is it cooler?\n",
        "- Which is more likely to show a smaller temperature change, land or land+ocean? Why is that?  \n",
        "- Describe the overall trend of the data.  \n",
        "\n",
        "---  \n",
        "## Saving Your Work  \n",
        "This is running on a Google server on a distant planet and deletes what you've done when you close this tab. To save your work for later use or analysis you have a few options:  \n",
        "- File > \"Save a copy in Drive\" will save it to you Google Drive in a folder called \"Collaboratory\". You can run it later from there.  \n",
        "- File > \"Download .ipynb\" to save to your computer (and run with Jupyter software later)  \n",
        "- File > Print to ... um ... print.  \n",
        "- To save an image of a graph or chart, right-click on it and select Save Image as ...  \n",
        "\n",
        "## Credits\n",
        "The data came from [NASA's GISS Surface Temperature Analysis (GISTEMP)](http://data.giss.nasa.gov/gistemp/) ([original file](http://data.giss.nasa.gov/gistemp/tabledata_v3/GLB.Ts+dSST.csv) pulled 3/28/2017). This notebook was designed by [Adam LaMee](https://adamlamee.github.io/). Thanks to the great folks at [Binder](https://mybinder.org/) and [Google Colaboratory](https://colab.research.google.com/notebooks/intro.ipynb) for making this notebook interactive without you needing to download it or install [Jupyter](https://jupyter.org/) on your own device. Find more activities and license info at [CODINGinK12.org](http://www.codingink12.org).  \n",
        "- GISTEMP Team, 2017: GISS Surface Temperature Analysis (GISTEMP). NASA Goddard Institute for Space Studies. Dataset accessed 20YY-MM-DD at [https://data.giss.nasa.gov/gistemp/](https://data.giss.nasa.gov/gistemp/).\n",
        "- Hansen, J., R. Ruedy, M. Sato, and K. Lo, 2010: [Global surface temperature change](https://pubs.giss.nasa.gov/abs/ha00510u.html), Rev. Geophys., 48, RG4004, doi:10.1029/2010RG000345."
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