globalw.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "globalw.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1cWjxIYaqrz9"
      },
      "source": [
        "# Topical Plots: Global Warming\n",
        "## What chart will get the message across best"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "v0SuqkooUbqM",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "4750101c-9496-43a3-fdab-1059e74b33f6"
      },
      "source": [
        "import pandas as pd\n",
        "gw = pd.read_csv('https://data.giss.nasa.gov/gistemp/graphs/graph_data/Global_Mean_Estimates_based_on_Land_and_Ocean_Data/graph.txt',skiprows=(0,1,2,4), delimiter=' ', skipinitialspace=True)\n",
        "gw.columns"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['Year', 'No_Smoothing', 'Lowess(5)'], dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 1
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mXN-5C4nhW57"
      },
      "source": [
        "import matplotlib\n",
        "matplotlib.style.use('seaborn')"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fJefPwq7KiLG",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "outputId": "6e66b2d9-16f8-414c-e3b4-116936608811"
      },
      "source": [
        "gw=gw.rename(columns={'No_Smoothing':'Temp','Lowess(5)':\"Smoothed\"})\n",
        "gw"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Year</th>\n",
              "      <th>Temp</th>\n",
              "      <th>Smoothed</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1880</td>\n",
              "      <td>-0.16</td>\n",
              "      <td>-0.09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1881</td>\n",
              "      <td>-0.08</td>\n",
              "      <td>-0.12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1882</td>\n",
              "      <td>-0.10</td>\n",
              "      <td>-0.16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1883</td>\n",
              "      <td>-0.17</td>\n",
              "      <td>-0.20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1884</td>\n",
              "      <td>-0.28</td>\n",
              "      <td>-0.23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>136</th>\n",
              "      <td>2016</td>\n",
              "      <td>1.01</td>\n",
              "      <td>0.87</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>137</th>\n",
              "      <td>2017</td>\n",
              "      <td>0.92</td>\n",
              "      <td>0.91</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>138</th>\n",
              "      <td>2018</td>\n",
              "      <td>0.85</td>\n",
              "      <td>0.94</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>139</th>\n",
              "      <td>2019</td>\n",
              "      <td>0.98</td>\n",
              "      <td>0.98</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>140</th>\n",
              "      <td>2020</td>\n",
              "      <td>1.02</td>\n",
              "      <td>1.01</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>141 rows × 3 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     Year  Temp  Smoothed\n",
              "0    1880 -0.16     -0.09\n",
              "1    1881 -0.08     -0.12\n",
              "2    1882 -0.10     -0.16\n",
              "3    1883 -0.17     -0.20\n",
              "4    1884 -0.28     -0.23\n",
              "..    ...   ...       ...\n",
              "136  2016  1.01      0.87\n",
              "137  2017  0.92      0.91\n",
              "138  2018  0.85      0.94\n",
              "139  2019  0.98      0.98\n",
              "140  2020  1.02      1.01\n",
              "\n",
              "[141 rows x 3 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QA5hzZ5qKlAc",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 323
        },
        "outputId": "1601efcf-2bef-48ca-9b53-145afab162e0"
      },
      "source": [
        "gw.plot(x='Year',figsize=(20,5))"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f74443148d0>"
            ]
          },
          "metadata": {},
          "execution_count": 4
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x360 with 1 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 350
        },
        "id": "oI6dQoiKpVZd",
        "outputId": "5b2580c1-2d38-4285-94d4-bb1f3f95e6d6"
      },
      "source": [
        "ax=gw.plot(x='Year',y='Smoothed')\n",
        "gw.plot.scatter(x='Year',y='Temp',c='Temp', colormap='inferno',figsize=(20,5),ax=ax)"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f7444281190>"
            ]
          },
          "metadata": {},
          "execution_count": 5
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x360 with 2 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oO6PmZTnbkij"
      },
      "source": [
        "import seaborn as sns"
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UcRFAVB2ck6m",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "outputId": "42f05de1-a77e-4d6a-e53c-8fb3b06ef5a3"
      },
      "source": [
        "gw2=gw.drop(columns='Temp')\n",
        "gw3=gw.drop(columns='Smoothed')\n",
        "gw2\n"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Year</th>\n",
              "      <th>Smoothed</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1880</td>\n",
              "      <td>-0.09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1881</td>\n",
              "      <td>-0.12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1882</td>\n",
              "      <td>-0.16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1883</td>\n",
              "      <td>-0.20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1884</td>\n",
              "      <td>-0.23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>136</th>\n",
              "      <td>2016</td>\n",
              "      <td>0.87</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>137</th>\n",
              "      <td>2017</td>\n",
              "      <td>0.91</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>138</th>\n",
              "      <td>2018</td>\n",
              "      <td>0.94</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>139</th>\n",
              "      <td>2019</td>\n",
              "      <td>0.98</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>140</th>\n",
              "      <td>2020</td>\n",
              "      <td>1.01</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>141 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     Year  Smoothed\n",
              "0    1880     -0.09\n",
              "1    1881     -0.12\n",
              "2    1882     -0.16\n",
              "3    1883     -0.20\n",
              "4    1884     -0.23\n",
              "..    ...       ...\n",
              "136  2016      0.87\n",
              "137  2017      0.91\n",
              "138  2018      0.94\n",
              "139  2019      0.98\n",
              "140  2020      1.01\n",
              "\n",
              "[141 rows x 2 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 801
        },
        "id": "hVLs4WJ4bzVI",
        "outputId": "53a7da75-62d1-4e0d-8d01-6435368c1449"
      },
      "source": [
        "gw2=gw2.set_index('Year')\n",
        "sns.set(rc={'figure.figsize':(20,5)})\n",
        "sns.heatmap(gw2.T)\n",
        "gw2"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Smoothed</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Year</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1880</th>\n",
              "      <td>-0.09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1881</th>\n",
              "      <td>-0.12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1882</th>\n",
              "      <td>-0.16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1883</th>\n",
              "      <td>-0.20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1884</th>\n",
              "      <td>-0.23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016</th>\n",
              "      <td>0.87</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017</th>\n",
              "      <td>0.91</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018</th>\n",
              "      <td>0.94</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019</th>\n",
              "      <td>0.98</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020</th>\n",
              "      <td>1.01</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>141 rows × 1 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "      Smoothed\n",
              "Year          \n",
              "1880     -0.09\n",
              "1881     -0.12\n",
              "1882     -0.16\n",
              "1883     -0.20\n",
              "1884     -0.23\n",
              "...        ...\n",
              "2016      0.87\n",
              "2017      0.91\n",
              "2018      0.94\n",
              "2019      0.98\n",
              "2020      1.01\n",
              "\n",
              "[141 rows x 1 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 8
        },
        {
          "output_type": "display_data",
          "data": {
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\n",
            "text/plain": [
              "<Figure size 1440x360 with 2 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 799
        },
        "id": "zpGy1L69hZQF",
        "outputId": "3c4189fd-395a-46b9-a144-9c531afa39e1"
      },
      "source": [
        "gw3=gw3.set_index('Year')\n",
        "sns.set(rc={'figure.figsize':(20,5)})\n",
        "sns.heatmap(gw3.T)\n",
        "gw3"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Temp</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Year</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1880</th>\n",
              "      <td>-0.16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1881</th>\n",
              "      <td>-0.08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1882</th>\n",
              "      <td>-0.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1883</th>\n",
              "      <td>-0.17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1884</th>\n",
              "      <td>-0.28</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016</th>\n",
              "      <td>1.01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017</th>\n",
              "      <td>0.92</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018</th>\n",
              "      <td>0.85</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019</th>\n",
              "      <td>0.98</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020</th>\n",
              "      <td>1.02</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>141 rows × 1 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "      Temp\n",
              "Year      \n",
              "1880 -0.16\n",
              "1881 -0.08\n",
              "1882 -0.10\n",
              "1883 -0.17\n",
              "1884 -0.28\n",
              "...    ...\n",
              "2016  1.01\n",
              "2017  0.92\n",
              "2018  0.85\n",
              "2019  0.98\n",
              "2020  1.02\n",
              "\n",
              "[141 rows x 1 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 9
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x360 with 2 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mAf2cIn2rPVs"
      },
      "source": [
        ""
      ],
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 394
        },
        "id": "-rWebcQrRRbE",
        "outputId": "894b040c-ae38-404f-97a3-bb801ec99cad"
      },
      "source": [
        "url='https://raw.githubusercontent.com/alanjones2/dataviz/master/tempbydecade.csv'\n",
        "gwdec = pd.read_csv(url, delimiter=' ', skipinitialspace=True)\n",
        "gwdec=gwdec.set_index('Year')\n",
        "gwdec"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>1880</th>\n",
              "      <th>1890</th>\n",
              "      <th>1900</th>\n",
              "      <th>1910</th>\n",
              "      <th>1920</th>\n",
              "      <th>1930</th>\n",
              "      <th>1940</th>\n",
              "      <th>1950</th>\n",
              "      <th>1960</th>\n",
              "      <th>1970</th>\n",
              "      <th>1980</th>\n",
              "      <th>1990</th>\n",
              "      <th>2000</th>\n",
              "      <th>2010</th>\n",
              "      <th>2020</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Year</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>-0.16</td>\n",
              "      <td>-0.35</td>\n",
              "      <td>-0.08</td>\n",
              "      <td>-0.43</td>\n",
              "      <td>-0.28</td>\n",
              "      <td>-0.16</td>\n",
              "      <td>0.13</td>\n",
              "      <td>-0.17</td>\n",
              "      <td>-0.03</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.26</td>\n",
              "      <td>0.45</td>\n",
              "      <td>0.39</td>\n",
              "      <td>0.72</td>\n",
              "      <td>1.02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>-0.08</td>\n",
              "      <td>-0.22</td>\n",
              "      <td>-0.16</td>\n",
              "      <td>-0.44</td>\n",
              "      <td>-0.19</td>\n",
              "      <td>-0.09</td>\n",
              "      <td>0.19</td>\n",
              "      <td>-0.07</td>\n",
              "      <td>0.06</td>\n",
              "      <td>-0.08</td>\n",
              "      <td>0.32</td>\n",
              "      <td>0.40</td>\n",
              "      <td>0.54</td>\n",
              "      <td>0.61</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>-0.10</td>\n",
              "      <td>-0.27</td>\n",
              "      <td>-0.28</td>\n",
              "      <td>-0.36</td>\n",
              "      <td>-0.29</td>\n",
              "      <td>-0.16</td>\n",
              "      <td>0.07</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.14</td>\n",
              "      <td>0.22</td>\n",
              "      <td>0.63</td>\n",
              "      <td>0.65</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>-0.17</td>\n",
              "      <td>-0.31</td>\n",
              "      <td>-0.37</td>\n",
              "      <td>-0.34</td>\n",
              "      <td>-0.27</td>\n",
              "      <td>-0.28</td>\n",
              "      <td>0.09</td>\n",
              "      <td>0.08</td>\n",
              "      <td>0.05</td>\n",
              "      <td>0.16</td>\n",
              "      <td>0.31</td>\n",
              "      <td>0.23</td>\n",
              "      <td>0.62</td>\n",
              "      <td>0.68</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>-0.28</td>\n",
              "      <td>-0.30</td>\n",
              "      <td>-0.47</td>\n",
              "      <td>-0.15</td>\n",
              "      <td>-0.27</td>\n",
              "      <td>-0.12</td>\n",
              "      <td>0.20</td>\n",
              "      <td>-0.13</td>\n",
              "      <td>-0.20</td>\n",
              "      <td>-0.07</td>\n",
              "      <td>0.16</td>\n",
              "      <td>0.32</td>\n",
              "      <td>0.53</td>\n",
              "      <td>0.74</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>-0.33</td>\n",
              "      <td>-0.23</td>\n",
              "      <td>-0.27</td>\n",
              "      <td>-0.14</td>\n",
              "      <td>-0.22</td>\n",
              "      <td>-0.20</td>\n",
              "      <td>0.09</td>\n",
              "      <td>-0.14</td>\n",
              "      <td>-0.11</td>\n",
              "      <td>-0.01</td>\n",
              "      <td>0.12</td>\n",
              "      <td>0.45</td>\n",
              "      <td>0.68</td>\n",
              "      <td>0.89</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>-0.31</td>\n",
              "      <td>-0.11</td>\n",
              "      <td>-0.23</td>\n",
              "      <td>-0.36</td>\n",
              "      <td>-0.11</td>\n",
              "      <td>-0.15</td>\n",
              "      <td>-0.07</td>\n",
              "      <td>-0.19</td>\n",
              "      <td>-0.06</td>\n",
              "      <td>-0.10</td>\n",
              "      <td>0.18</td>\n",
              "      <td>0.33</td>\n",
              "      <td>0.64</td>\n",
              "      <td>1.01</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>-0.36</td>\n",
              "      <td>-0.11</td>\n",
              "      <td>-0.39</td>\n",
              "      <td>-0.46</td>\n",
              "      <td>-0.22</td>\n",
              "      <td>-0.03</td>\n",
              "      <td>-0.03</td>\n",
              "      <td>0.05</td>\n",
              "      <td>-0.02</td>\n",
              "      <td>0.18</td>\n",
              "      <td>0.32</td>\n",
              "      <td>0.46</td>\n",
              "      <td>0.66</td>\n",
              "      <td>0.92</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>-0.17</td>\n",
              "      <td>-0.27</td>\n",
              "      <td>-0.43</td>\n",
              "      <td>-0.30</td>\n",
              "      <td>-0.20</td>\n",
              "      <td>0.00</td>\n",
              "      <td>-0.11</td>\n",
              "      <td>0.06</td>\n",
              "      <td>-0.08</td>\n",
              "      <td>0.07</td>\n",
              "      <td>0.39</td>\n",
              "      <td>0.61</td>\n",
              "      <td>0.54</td>\n",
              "      <td>0.85</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>-0.11</td>\n",
              "      <td>-0.18</td>\n",
              "      <td>-0.48</td>\n",
              "      <td>-0.28</td>\n",
              "      <td>-0.36</td>\n",
              "      <td>-0.01</td>\n",
              "      <td>-0.11</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.05</td>\n",
              "      <td>0.16</td>\n",
              "      <td>0.27</td>\n",
              "      <td>0.38</td>\n",
              "      <td>0.66</td>\n",
              "      <td>0.98</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      1880  1890  1900  1910  1920  1930  ...  1970  1980  1990  2000  2010  2020\n",
              "Year                                      ...                                    \n",
              "0    -0.16 -0.35 -0.08 -0.43 -0.28 -0.16  ...  0.03  0.26  0.45  0.39  0.72  1.02\n",
              "1    -0.08 -0.22 -0.16 -0.44 -0.19 -0.09  ... -0.08  0.32  0.40  0.54  0.61   NaN\n",
              "2    -0.10 -0.27 -0.28 -0.36 -0.29 -0.16  ...  0.01  0.14  0.22  0.63  0.65   NaN\n",
              "3    -0.17 -0.31 -0.37 -0.34 -0.27 -0.28  ...  0.16  0.31  0.23  0.62  0.68   NaN\n",
              "4    -0.28 -0.30 -0.47 -0.15 -0.27 -0.12  ... -0.07  0.16  0.32  0.53  0.74   NaN\n",
              "5    -0.33 -0.23 -0.27 -0.14 -0.22 -0.20  ... -0.01  0.12  0.45  0.68  0.89   NaN\n",
              "6    -0.31 -0.11 -0.23 -0.36 -0.11 -0.15  ... -0.10  0.18  0.33  0.64  1.01   NaN\n",
              "7    -0.36 -0.11 -0.39 -0.46 -0.22 -0.03  ...  0.18  0.32  0.46  0.66  0.92   NaN\n",
              "8    -0.17 -0.27 -0.43 -0.30 -0.20  0.00  ...  0.07  0.39  0.61  0.54  0.85   NaN\n",
              "9    -0.11 -0.18 -0.48 -0.28 -0.36 -0.01  ...  0.16  0.27  0.38  0.66  0.98   NaN\n",
              "\n",
              "[10 rows x 15 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 342
        },
        "id": "O4XA_VswlgD0",
        "outputId": "f73fb166-5d3c-46cb-9593-74dd48116bf4"
      },
      "source": [
        "sns.set(rc={'figure.figsize':(20,5)})\n",
        "sns.heatmap(gwdec)"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f742c814310>"
            ]
          },
          "metadata": {},
          "execution_count": 11
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 1440x360 with 2 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "M1SmjE_SiBtU",
        "outputId": "77e26937-bbce-40eb-cf5a-02bed4de1efa"
      },
      "source": [
        "gw4=gw3.sort_values('Temp',ascending=False)\n",
        "sns.set(rc={'figure.figsize':(5,30)})\n",
        "sns.heatmap(gw4)\n",
        "gw4[:20]"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Temp</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Year</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2020</th>\n",
              "      <td>1.02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016</th>\n",
              "      <td>1.01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019</th>\n",
              "      <td>0.98</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017</th>\n",
              "      <td>0.92</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015</th>\n",
              "      <td>0.89</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018</th>\n",
              "      <td>0.85</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2014</th>\n",
              "      <td>0.74</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2010</th>\n",
              "      <td>0.72</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2005</th>\n",
              "      <td>0.68</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2013</th>\n",
              "      <td>0.68</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2007</th>\n",
              "      <td>0.66</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2009</th>\n",
              "      <td>0.66</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2012</th>\n",
              "      <td>0.65</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006</th>\n",
              "      <td>0.64</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2002</th>\n",
              "      <td>0.63</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2003</th>\n",
              "      <td>0.62</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2011</th>\n",
              "      <td>0.61</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1998</th>\n",
              "      <td>0.61</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2008</th>\n",
              "      <td>0.54</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2001</th>\n",
              "      <td>0.54</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      Temp\n",
              "Year      \n",
              "2020  1.02\n",
              "2016  1.01\n",
              "2019  0.98\n",
              "2017  0.92\n",
              "2015  0.89\n",
              "2018  0.85\n",
              "2014  0.74\n",
              "2010  0.72\n",
              "2005  0.68\n",
              "2013  0.68\n",
              "2007  0.66\n",
              "2009  0.66\n",
              "2012  0.65\n",
              "2006  0.64\n",
              "2002  0.63\n",
              "2003  0.62\n",
              "2011  0.61\n",
              "1998  0.61\n",
              "2008  0.54\n",
              "2001  0.54"
            ]
          },
          "metadata": {},
          "execution_count": 12
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 360x2160 with 2 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 345
        },
        "id": "h1sM_kC6mf63",
        "outputId": "ed41daf6-e44e-4f0c-8ee8-212777c7ac13"
      },
      "source": [
        "gw4=gw3.sort_values('Temp',ascending=False)\n",
        "sns.set(rc={'figure.figsize':(5,5)})\n",
        "sns.heatmap(gw4[:20])"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f742c597cd0>"
            ]
          },
          "metadata": {},
          "execution_count": 13
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 360x360 with 2 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 349
        },
        "id": "47_SuxS5rH2l",
        "outputId": "443c16e9-f59c-4e0b-8997-49d865381c01"
      },
      "source": [
        "sns.heatmap(gw4)"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f742c4bf550>"
            ]
          },
          "metadata": {},
          "execution_count": 14
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 360x360 with 2 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    }
  ]
}