Climate Funds.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# CLIMATE-FUNDS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import numpy as np\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Fund</th>\n",
       "      <th>FundType</th>\n",
       "      <th>Fund focus</th>\n",
       "      <th>Pledge (USD mn)</th>\n",
       "      <th>Deposit (USD mn)</th>\n",
       "      <th>Approval (USD mn)</th>\n",
       "      <th>Disbursement (USD mn)</th>\n",
       "      <th>Number of projects approved</th>\n",
       "      <th>Date reported</th>\n",
       "      <th>Date collected</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Adaptation for Smallholder Agriculture Program...</td>\n",
       "      <td>Multilateral</td>\n",
       "      <td>Adaptation</td>\n",
       "      <td>381.670000</td>\n",
       "      <td>330.000000</td>\n",
       "      <td>307.000000</td>\n",
       "      <td>60.079449</td>\n",
       "      <td>42</td>\n",
       "      <td>2018-11-28</td>\n",
       "      <td>2018-11-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Adaptation Fund (AF)</td>\n",
       "      <td>Multilateral</td>\n",
       "      <td>Adaptation</td>\n",
       "      <td>755.459372</td>\n",
       "      <td>755.458642</td>\n",
       "      <td>531.573964</td>\n",
       "      <td>305.620000</td>\n",
       "      <td>163</td>\n",
       "      <td>2018-09-30</td>\n",
       "      <td>2018-11-19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Amazon Fund</td>\n",
       "      <td>Multi Donor National</td>\n",
       "      <td>Mitigation - REDD</td>\n",
       "      <td>1748.370000</td>\n",
       "      <td>1217.950000</td>\n",
       "      <td>717.127198</td>\n",
       "      <td>437.396602</td>\n",
       "      <td>102</td>\n",
       "      <td>2018-11-15</td>\n",
       "      <td>2018-11-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BioCarbon Fund Initiative for Sustainable Fore...</td>\n",
       "      <td>Multilateral</td>\n",
       "      <td>Mitigation - REDD</td>\n",
       "      <td>351.934000</td>\n",
       "      <td>190.636000</td>\n",
       "      <td>81.285000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5</td>\n",
       "      <td>2018-11-21</td>\n",
       "      <td>2018-11-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Clean Technology Fund (CTF)</td>\n",
       "      <td>Multilateral</td>\n",
       "      <td>Mitigation - General</td>\n",
       "      <td>5461.910000</td>\n",
       "      <td>5462.630000</td>\n",
       "      <td>4989.400000</td>\n",
       "      <td>1531.260000</td>\n",
       "      <td>109</td>\n",
       "      <td>2018-10-02</td>\n",
       "      <td>2018-11-26</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                Fund              FundType  \\\n",
       "0  Adaptation for Smallholder Agriculture Program...          Multilateral   \n",
       "1                               Adaptation Fund (AF)          Multilateral   \n",
       "2                                        Amazon Fund  Multi Donor National   \n",
       "3  BioCarbon Fund Initiative for Sustainable Fore...          Multilateral   \n",
       "4                        Clean Technology Fund (CTF)          Multilateral   \n",
       "\n",
       "             Fund focus  Pledge (USD mn)  Deposit (USD mn)  Approval (USD mn)  \\\n",
       "0            Adaptation       381.670000        330.000000         307.000000   \n",
       "1            Adaptation       755.459372        755.458642         531.573964   \n",
       "2     Mitigation - REDD      1748.370000       1217.950000         717.127198   \n",
       "3     Mitigation - REDD       351.934000        190.636000          81.285000   \n",
       "4  Mitigation - General      5461.910000       5462.630000        4989.400000   \n",
       "\n",
       "   Disbursement (USD mn)  Number of projects approved Date reported   \\\n",
       "0              60.079449                           42     2018-11-28   \n",
       "1             305.620000                          163     2018-09-30   \n",
       "2             437.396602                          102     2018-11-15   \n",
       "3               0.000000                            5     2018-11-21   \n",
       "4            1531.260000                          109     2018-10-02   \n",
       "\n",
       "  Date collected  \n",
       "0     2018-11-29  \n",
       "1     2018-11-19  \n",
       "2     2018-11-30  \n",
       "3     2018-11-01  \n",
       "4     2018-11-26  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df=pd.read_excel(\"data.xlsx\")\n",
    "df.rename(columns={'Fund Type':'FundType',},inplace=True)\n",
    "df.head()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Determine the funds pledged and donated by the countries."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\ANKITA SAHA\\anaconda\\lib\\site-packages\\pandas\\core\\frame.py:4133: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  errors=errors,\n"
     ]
    },
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Fund</th>\n",
       "      <th>Pledge (USD mn)</th>\n",
       "      <th>Donated</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Adaptation for Smallholder Agriculture Program...</td>\n",
       "      <td>381.670000</td>\n",
       "      <td>60.079449</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Adaptation Fund (AF)</td>\n",
       "      <td>755.459372</td>\n",
       "      <td>305.620000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Amazon Fund</td>\n",
       "      <td>1748.370000</td>\n",
       "      <td>437.396602</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BioCarbon Fund Initiative for Sustainable Fore...</td>\n",
       "      <td>351.934000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Clean Technology Fund (CTF)</td>\n",
       "      <td>5461.910000</td>\n",
       "      <td>1531.260000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Congo Basin Forest Fund (CBFF)</td>\n",
       "      <td>186.021000</td>\n",
       "      <td>62.547000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Forest Carbon Partnership Facility - Readiness...</td>\n",
       "      <td>430.030000</td>\n",
       "      <td>447.127546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Forest Carbon Partnership Facility - Carbon Fu...</td>\n",
       "      <td>889.510000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Forest Investment Program (FIP)</td>\n",
       "      <td>735.740000</td>\n",
       "      <td>168.070000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Global Environment Facility (GEF4)</td>\n",
       "      <td>1082.981565</td>\n",
       "      <td>961.260355</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Global Environment Facility (GEF5)</td>\n",
       "      <td>1152.405166</td>\n",
       "      <td>500.749846</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Global Environment Facility (GEF6)</td>\n",
       "      <td>1117.156598</td>\n",
       "      <td>208.065952</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Global Climate Change Alliance (GCCA)</td>\n",
       "      <td>1332.907135</td>\n",
       "      <td>172.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Global Energy Efficiency and Renewable Energy ...</td>\n",
       "      <td>281.500000</td>\n",
       "      <td>89.070000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Green Climate Fund (GCF)</td>\n",
       "      <td>10302.300000</td>\n",
       "      <td>391.766080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Indonesia Climate Change Trust Fund (ICCTF)</td>\n",
       "      <td>26.170800</td>\n",
       "      <td>7.687613</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Least Developed Countries Fund (LDCF)</td>\n",
       "      <td>1371.719394</td>\n",
       "      <td>531.862897</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>MDG Achievement Fund</td>\n",
       "      <td>89.500000</td>\n",
       "      <td>82.520000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Partnership for Market Readiness</td>\n",
       "      <td>129.600000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Pilot Program for Climate Resilience (PPCR)</td>\n",
       "      <td>1154.660000</td>\n",
       "      <td>390.230000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Scaling Up Renewable Energy Program (SREP)</td>\n",
       "      <td>744.540000</td>\n",
       "      <td>55.210000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Special Climate Change Fund (SCCF)</td>\n",
       "      <td>371.060000</td>\n",
       "      <td>186.787778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>UN-REDD Programme</td>\n",
       "      <td>319.550000</td>\n",
       "      <td>289.477500</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                 Fund  Pledge (USD mn)  \\\n",
       "0   Adaptation for Smallholder Agriculture Program...       381.670000   \n",
       "1                                Adaptation Fund (AF)       755.459372   \n",
       "2                                         Amazon Fund      1748.370000   \n",
       "3   BioCarbon Fund Initiative for Sustainable Fore...       351.934000   \n",
       "4                         Clean Technology Fund (CTF)      5461.910000   \n",
       "5                      Congo Basin Forest Fund (CBFF)       186.021000   \n",
       "6   Forest Carbon Partnership Facility - Readiness...       430.030000   \n",
       "7   Forest Carbon Partnership Facility - Carbon Fu...       889.510000   \n",
       "8                     Forest Investment Program (FIP)       735.740000   \n",
       "9                  Global Environment Facility (GEF4)      1082.981565   \n",
       "10                 Global Environment Facility (GEF5)      1152.405166   \n",
       "11                 Global Environment Facility (GEF6)      1117.156598   \n",
       "12              Global Climate Change Alliance (GCCA)      1332.907135   \n",
       "13  Global Energy Efficiency and Renewable Energy ...       281.500000   \n",
       "14                           Green Climate Fund (GCF)     10302.300000   \n",
       "15        Indonesia Climate Change Trust Fund (ICCTF)        26.170800   \n",
       "16              Least Developed Countries Fund (LDCF)      1371.719394   \n",
       "17                               MDG Achievement Fund        89.500000   \n",
       "18                   Partnership for Market Readiness       129.600000   \n",
       "19        Pilot Program for Climate Resilience (PPCR)      1154.660000   \n",
       "20         Scaling Up Renewable Energy Program (SREP)       744.540000   \n",
       "21                 Special Climate Change Fund (SCCF)       371.060000   \n",
       "22                                  UN-REDD Programme       319.550000   \n",
       "\n",
       "        Donated  \n",
       "0     60.079449  \n",
       "1    305.620000  \n",
       "2    437.396602  \n",
       "3      0.000000  \n",
       "4   1531.260000  \n",
       "5     62.547000  \n",
       "6    447.127546  \n",
       "7      0.000000  \n",
       "8    168.070000  \n",
       "9    961.260355  \n",
       "10   500.749846  \n",
       "11   208.065952  \n",
       "12   172.750000  \n",
       "13    89.070000  \n",
       "14   391.766080  \n",
       "15     7.687613  \n",
       "16   531.862897  \n",
       "17    82.520000  \n",
       "18     0.000000  \n",
       "19   390.230000  \n",
       "20    55.210000  \n",
       "21   186.787778  \n",
       "22   289.477500  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1=df[['Fund','Pledge (USD mn)','Disbursement (USD mn)']]\n",
    "df1.rename(columns={'Disbursement (USD mn)':'Donated'},inplace=True)\n",
    "df1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Compare who gave more, and who gave less funds."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Graph showing the maximum and minimum donation')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1800x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X=list(df1.Fund)\n",
    "Y=list(df1.Donated)\n",
    "\n",
    "fig,ax=plt.subplots(figsize=(25,5))\n",
    "plt.xticks(rotation=90)\n",
    "ax.bar(X,Y,color='red')\n",
    "plt.xlabel(\"Fund\",fontsize=25)\n",
    "plt.ylabel(\"Amount donated:\",fontsize=15)\n",
    "plt.title(\"Graph showing the maximum and minimum donation\",fontsize=25)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1mIt is evident from the above graph that:\n",
      "\n",
      "\u001b[1m1.The Fund who gave the MAXIMUM donation(in USD mn) is:\n",
      "\n",
      "\n",
      "                          Fund  Donated\n",
      "4  Clean Technology Fund (CTF)  1531.26\n",
      "\n",
      "\n",
      "\u001b[1m1.The Fund who gave the MINIMUM donation(in USD mn) is:\n",
      "\n",
      "\n",
      "                                                 Fund  Donated\n",
      "3   BioCarbon Fund Initiative for Sustainable Fore...      0.0\n",
      "7   Forest Carbon Partnership Facility - Carbon Fu...      0.0\n",
      "18                   Partnership for Market Readiness      0.0\n"
     ]
    }
   ],
   "source": [
    "df2=df1[['Fund','Donated']]\n",
    "print(\"\\033[1m\"+\"It is evident from the above graph that:\\n\")\n",
    "print(\"\\033[1m\"+\"1.The Fund who gave the MAXIMUM donation(in USD mn) is:\\n\\n\")\n",
    "print(df2[df2.Donated==df2.Donated.max()])\n",
    "print(\"\\n\")\n",
    "print(\"\\033[1m\"+\"1.The Fund who gave the MINIMUM donation(in USD mn) is:\\n\\n\")\n",
    "print(df2[df2.Donated==df2.Donated.min()])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Type of funds given."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1mThe different types of funds are: \n",
      "Multilateral\n",
      "Multi Donor National\n",
      "Multi Donor Regional\n"
     ]
    }
   ],
   "source": [
    "print(\"\\033[1m\"+\"The different types of funds are: \")\n",
    "a=list(df.FundType.unique())\n",
    "print(*a,sep='\\n')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Overall analysis "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This data presents cumulative data on the pledges, deposits and the project approvals made by multilateral climate change funds tracked by Climate Funds Update.From the above graphit is evident that the maximum donation is made by Clean Technology Fund (CTF) and the least fundis given by:\n",
    "1.BioCarbon Fund Initiative for Sustainable Forest Landscapes (BioCarbon Fund ISFL)\n",
    "2. Partnership for Market Readiness\n",
    "3.Forest Carbon Partnership Facility - Carbon Fund (FCPF-CF)\n",
    "These companies had practically no donation yet they had a lot of money pledged for the projects."
   ]
  }
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