{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# About Dataset\n",
    "\n",
    "Context\n",
    "\n",
    "Methane is responsible for around 30% of the rise in global temperatures since the Industrial Revolution, and rapid and sustained reductions in methane emissions are key to limiting near-term global warming and improving air quality. The energy sector – including oil, natural gas, coal and bioenergy – accounts for nearly 40% of methane emissions from human activity.\n",
    "\n",
    "Content\n",
    "The following dataset has information about methane gas emissions globally. Details about the columns are as follows:\n",
    "\n",
    "region -\n",
    "country - Country of Emission.\n",
    "emissions - Methane Emissions in kt.\n",
    "type - Sector from which emissions occur.\n",
    "Segment- Sub-sector from which emissions occur.\n",
    "reason - The reason for the emission.\n",
    "ba\n",
    "seYear - Base year for the tracking of emissions.\n",
    "notes - The source of data\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-12T16:58:09.717145Z",
     "iopub.status.busy": "2023-04-12T16:58:09.716781Z",
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     "shell.execute_reply": "2023-04-12T16:58:13.477037Z",
     "shell.execute_reply.started": "2023-04-12T16:58:09.717110Z"
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import plotly.express as px\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-12T16:58:13.483139Z",
     "iopub.status.busy": "2023-04-12T16:58:13.482412Z",
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     "shell.execute_reply": "2023-04-12T16:58:13.526378Z",
     "shell.execute_reply.started": "2023-04-12T16:58:13.483059Z"
    }
   },
   "outputs": [],
   "source": [
    "df=pd.read_csv(\"data/Methane_final.csv\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-12T16:58:13.529325Z",
     "iopub.status.busy": "2023-04-12T16:58:13.528892Z",
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     "shell.execute_reply": "2023-04-12T16:58:13.559005Z",
     "shell.execute_reply.started": "2023-04-12T16:58:13.529284Z"
    }
   },
   "outputs": [],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-12T16:58:13.563328Z",
     "iopub.status.busy": "2023-04-12T16:58:13.562761Z",
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     "shell.execute_reply": "2023-04-12T16:58:13.568955Z",
     "shell.execute_reply.started": "2023-04-12T16:58:13.563289Z"
    }
   },
   "outputs": [],
   "source": [
    "df.columns\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-12T16:58:13.573802Z",
     "iopub.status.busy": "2023-04-12T16:58:13.573427Z",
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     "shell.execute_reply": "2023-04-12T16:58:13.587379Z",
     "shell.execute_reply.started": "2023-04-12T16:58:13.573767Z"
    }
   },
   "outputs": [],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-12T16:58:13.591898Z",
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     "shell.execute_reply.started": "2023-04-12T16:58:13.591857Z"
    }
   },
   "outputs": [],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-12T16:58:13.629190Z",
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     "shell.execute_reply.started": "2023-04-12T16:58:13.629152Z"
    },
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-12T16:58:13.652901Z",
     "iopub.status.busy": "2023-04-12T16:58:13.652305Z",
     "iopub.status.idle": "2023-04-12T16:58:13.660320Z",
     "shell.execute_reply": "2023-04-12T16:58:13.658308Z",
     "shell.execute_reply.started": "2023-04-12T16:58:13.652867Z"
    }
   },
   "outputs": [],
   "source": [
    "df.type.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-12T16:58:13.662741Z",
     "iopub.status.busy": "2023-04-12T16:58:13.661829Z",
     "iopub.status.idle": "2023-04-12T16:58:13.674253Z",
     "shell.execute_reply": "2023-04-12T16:58:13.672844Z",
     "shell.execute_reply.started": "2023-04-12T16:58:13.662688Z"
    }
   },
   "outputs": [],
   "source": [
    "df.reason.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-12T16:58:13.680101Z",
     "iopub.status.busy": "2023-04-12T16:58:13.679076Z",
     "iopub.status.idle": "2023-04-12T16:58:13.688523Z",
     "shell.execute_reply": "2023-04-12T16:58:13.687012Z",
     "shell.execute_reply.started": "2023-04-12T16:58:13.680056Z"
    }
   },
   "outputs": [],
   "source": [
    "df.region.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-12T16:58:13.690937Z",
     "iopub.status.busy": "2023-04-12T16:58:13.690187Z",
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     "shell.execute_reply": "2023-04-12T16:58:13.702147Z",
     "shell.execute_reply.started": "2023-04-12T16:58:13.690892Z"
    }
   },
   "outputs": [],
   "source": [
    "df.reason=df.reason.astype('category')\n",
    "df.type=df.type.astype('category')\n",
    "df.region=df.region.astype('category')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-12T16:58:13.705427Z",
     "iopub.status.busy": "2023-04-12T16:58:13.704813Z",
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     "shell.execute_reply": "2023-04-12T16:58:13.729908Z",
     "shell.execute_reply.started": "2023-04-12T16:58:13.705385Z"
    }
   },
   "outputs": [],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-12T16:58:13.733193Z",
     "iopub.status.busy": "2023-04-12T16:58:13.732800Z",
     "iopub.status.idle": "2023-04-12T16:58:13.741125Z",
     "shell.execute_reply": "2023-04-12T16:58:13.739619Z",
     "shell.execute_reply.started": "2023-04-12T16:58:13.733152Z"
    }
   },
   "outputs": [],
   "source": [
    "df.drop(columns=['Unnamed: 0'],inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-12T16:58:13.743153Z",
     "iopub.status.busy": "2023-04-12T16:58:13.742728Z",
     "iopub.status.idle": "2023-04-12T16:58:13.762842Z",
     "shell.execute_reply": "2023-04-12T16:58:13.761949Z",
     "shell.execute_reply.started": "2023-04-12T16:58:13.743111Z"
    }
   },
   "outputs": [],
   "source": [
    "df.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-12T16:58:13.765226Z",
     "iopub.status.busy": "2023-04-12T16:58:13.764548Z",
     "iopub.status.idle": "2023-04-12T16:58:13.772765Z",
     "shell.execute_reply": "2023-04-12T16:58:13.771954Z",
     "shell.execute_reply.started": "2023-04-12T16:58:13.765187Z"
    }
   },
   "outputs": [],
   "source": [
    "df.emissions=df.emissions.apply(lambda x:round(x,2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-12T16:58:13.774881Z",
     "iopub.status.busy": "2023-04-12T16:58:13.774188Z",
     "iopub.status.idle": "2023-04-12T16:58:13.787058Z",
     "shell.execute_reply": "2023-04-12T16:58:13.786106Z",
     "shell.execute_reply.started": "2023-04-12T16:58:13.774840Z"
    }
   },
   "outputs": [],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-12T16:58:13.789464Z",
     "iopub.status.busy": "2023-04-12T16:58:13.788757Z",
     "iopub.status.idle": "2023-04-12T16:58:13.806040Z",
     "shell.execute_reply": "2023-04-12T16:58:13.804671Z",
     "shell.execute_reply.started": "2023-04-12T16:58:13.789403Z"
    }
   },
   "outputs": [],
   "source": [
    "df.duplicated().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-12T16:58:13.808188Z",
     "iopub.status.busy": "2023-04-12T16:58:13.807474Z",
     "iopub.status.idle": "2023-04-12T16:58:13.827909Z",
     "shell.execute_reply": "2023-04-12T16:58:13.826783Z",
     "shell.execute_reply.started": "2023-04-12T16:58:13.808144Z"
    }
   },
   "outputs": [],
   "source": [
    "df.describe().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-12T16:58:13.830033Z",
     "iopub.status.busy": "2023-04-12T16:58:13.829427Z",
     "iopub.status.idle": "2023-04-12T16:58:13.840782Z",
     "shell.execute_reply": "2023-04-12T16:58:13.839534Z",
     "shell.execute_reply.started": "2023-04-12T16:58:13.829998Z"
    }
   },
   "outputs": [],
   "source": [
    "df.baseYear.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-12T16:58:13.842986Z",
     "iopub.status.busy": "2023-04-12T16:58:13.842250Z",
     "iopub.status.idle": "2023-04-12T16:58:13.862485Z",
     "shell.execute_reply": "2023-04-12T16:58:13.861467Z",
     "shell.execute_reply.started": "2023-04-12T16:58:13.842939Z"
    }
   },
   "outputs": [],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-12T16:58:13.863938Z",
     "iopub.status.busy": "2023-04-12T16:58:13.863611Z",
     "iopub.status.idle": "2023-04-12T16:58:13.874576Z",
     "shell.execute_reply": "2023-04-12T16:58:13.872683Z",
     "shell.execute_reply.started": "2023-04-12T16:58:13.863912Z"
    }
   },
   "outputs": [],
   "source": [
    "df.baseYear=df.baseYear.replace(\"2019-2021\",2020)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-12T16:58:13.879267Z",
     "iopub.status.busy": "2023-04-12T16:58:13.876077Z",
     "iopub.status.idle": "2023-04-12T16:58:13.888744Z",
     "shell.execute_reply": "2023-04-12T16:58:13.887719Z",
     "shell.execute_reply.started": "2023-04-12T16:58:13.879223Z"
    }
   },
   "outputs": [],
   "source": [
    "df.baseYear.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-12T16:58:13.890705Z",
     "iopub.status.busy": "2023-04-12T16:58:13.890306Z",
     "iopub.status.idle": "2023-04-12T16:58:13.898952Z",
     "shell.execute_reply": "2023-04-12T16:58:13.897787Z",
     "shell.execute_reply.started": "2023-04-12T16:58:13.890670Z"
    }
   },
   "outputs": [],
   "source": [
    "#df['baseYear']= pd.to_datetime(df['baseYear'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-12T16:58:13.901003Z",
     "iopub.status.busy": "2023-04-12T16:58:13.900335Z",
     "iopub.status.idle": "2023-04-12T16:58:13.915303Z",
     "shell.execute_reply": "2023-04-12T16:58:13.914319Z",
     "shell.execute_reply.started": "2023-04-12T16:58:13.900965Z"
    }
   },
   "outputs": [],
   "source": [
    "df1=df[(df[\"region\"]!='World') & (df['segment']!='Total')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-12T16:58:13.917577Z",
     "iopub.status.busy": "2023-04-12T16:58:13.916931Z",
     "iopub.status.idle": "2023-04-12T16:58:13.931241Z",
     "shell.execute_reply": "2023-04-12T16:58:13.930377Z",
     "shell.execute_reply.started": "2023-04-12T16:58:13.917535Z"
    }
   },
   "outputs": [],
   "source": [
    "max_emission_countries=df1.groupby(['region','country'])['emissions'].sum().reset_index()\n",
    "max_emission_countries.sort_values(by='emissions',ascending=False,inplace=True,ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-12T16:58:13.933371Z",
     "iopub.status.busy": "2023-04-12T16:58:13.932709Z",
     "iopub.status.idle": "2023-04-12T16:58:13.937916Z",
     "shell.execute_reply": "2023-04-12T16:58:13.936837Z",
     "shell.execute_reply.started": "2023-04-12T16:58:13.933332Z"
    }
   },
   "outputs": [],
   "source": [
    "df2=max_emission_countries.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-12T16:58:13.939822Z",
     "iopub.status.busy": "2023-04-12T16:58:13.939202Z",
     "iopub.status.idle": "2023-04-12T16:58:15.767431Z",
     "shell.execute_reply": "2023-04-12T16:58:15.766162Z",
     "shell.execute_reply.started": "2023-04-12T16:58:13.939785Z"
    }
   },
   "outputs": [],
   "source": [
    "fig = px.pie(df2, names='country', values='emissions', hole=0.6, title='Emission per country',\n",
    "                      color_discrete_sequence=px.colors.qualitative.T10)\n",
    "fig.update_layout(title_text='Emission per country', title_x=0.5,height = 900)\n",
    "fig.update_traces(textposition='inside',textinfo='label+percent')\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-12T16:58:15.772903Z",
     "iopub.status.busy": "2023-04-12T16:58:15.772577Z",
     "iopub.status.idle": "2023-04-12T16:58:15.825918Z",
     "shell.execute_reply": "2023-04-12T16:58:15.824355Z",
     "shell.execute_reply.started": "2023-04-12T16:58:15.772874Z"
    }
   },
   "outputs": [],
   "source": [
    "#which year have maximum emission\n",
    "\n",
    "emission_per_year=df.groupby('baseYear').emissions.sum()\n",
    "fig = px.pie(emission_per_year, names=emission_per_year.index, values=emission_per_year.values, title='Emission per country',\n",
    "                      color_discrete_sequence=px.colors.qualitative.T10)\n",
    "fig.update_layout(title_text='Emission per year', title_x=0.5,height = 500)\n",
    "fig.update_traces(textposition='inside',textinfo='label+percent')\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-12T16:58:15.827790Z",
     "iopub.status.busy": "2023-04-12T16:58:15.827387Z",
     "iopub.status.idle": "2023-04-12T16:58:15.880977Z",
     "shell.execute_reply": "2023-04-12T16:58:15.879554Z",
     "shell.execute_reply.started": "2023-04-12T16:58:15.827753Z"
    }
   },
   "outputs": [],
   "source": [
    "fig = px.pie(df1, names='region', values='emissions', hole=0.6, title='Emission per country',\n",
    "                      color_discrete_sequence=px.colors.qualitative.T10)\n",
    "fig.update_layout(title_text='Emission per country', title_x=0.5,height = 900)\n",
    "fig.update_traces(textposition='inside',textinfo='label+percent')\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-12T16:58:15.882728Z",
     "iopub.status.busy": "2023-04-12T16:58:15.882355Z",
     "iopub.status.idle": "2023-04-12T16:58:16.043505Z",
     "shell.execute_reply": "2023-04-12T16:58:16.041643Z",
     "shell.execute_reply.started": "2023-04-12T16:58:15.882696Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-7-71a6516fd873>:1: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  df6=df.groupby('region').get_group('Asia Pacific').sort_values(by='%percent emission')\n"
     ]
    },
    {
     "ename": "KeyError",
     "evalue": "'%percent emission'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-7-71a6516fd873>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdf6\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgroupby\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'region'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_group\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Asia Pacific'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msort_values\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mby\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'%percent emission'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36msort_values\u001b[0;34m(self, by, axis, ascending, inplace, kind, na_position, ignore_index, key)\u001b[0m\n\u001b[1;32m   6942\u001b[0m             \u001b[0;31m# len(by) == 1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   6943\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 6944\u001b[0;31m             \u001b[0mk\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_label_or_level_values\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mby\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   6945\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   6946\u001b[0m             \u001b[0;31m# need to rewrap column in Series to apply key function\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36m_get_label_or_level_values\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m   1842\u001b[0m             \u001b[0mvalues\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0maxes\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_level_values\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_values\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1843\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1844\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1845\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1846\u001b[0m         \u001b[0;31m# Check for duplicates\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyError\u001b[0m: '%percent emission'"
     ]
    }
   ],
   "source": [
    "df6=df.groupby('region').get_group('Asia Pacific').sort_values(by='%percent emission')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.status.busy": "2023-04-12T16:58:16.044320Z",
     "iopub.status.idle": "2023-04-12T16:58:16.044712Z",
     "shell.execute_reply": "2023-04-12T16:58:16.044551Z",
     "shell.execute_reply.started": "2023-04-12T16:58:16.044529Z"
    }
   },
   "outputs": [],
   "source": [
    "fig = px.pie(df6, names='country', values='emissions', hole=0.6, title='Emission per country',\n",
    "                      color_discrete_sequence=px.colors.qualitative.T10)\n",
    "fig.update_layout(title_text='Emission per country', title_x=0.5,height = 900)\n",
    "fig.update_traces(textposition='inside',textinfo='label+percent')\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.status.busy": "2023-04-12T16:58:16.049381Z",
     "iopub.status.idle": "2023-04-12T16:58:16.050653Z",
     "shell.execute_reply": "2023-04-12T16:58:16.050176Z",
     "shell.execute_reply.started": "2023-04-12T16:58:16.050137Z"
    }
   },
   "outputs": [],
   "source": [
    "df3=df.groupby(\"segment\").emissions.sum().reset_index().sort_values(by='emissions', ascending=False,ignore_index=True)\n",
    "df3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.status.busy": "2023-04-12T16:58:16.051940Z",
     "iopub.status.idle": "2023-04-12T16:58:16.052480Z",
     "shell.execute_reply": "2023-04-12T16:58:16.052224Z",
     "shell.execute_reply.started": "2023-04-12T16:58:16.052195Z"
    }
   },
   "outputs": [],
   "source": [
    "#segment occurance having emission\n",
    "\n",
    "sns.countplot(data=df,y='segment',order=df.segment.value_counts().index[0:10])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.status.busy": "2023-04-12T16:58:16.054775Z",
     "iopub.status.idle": "2023-04-12T16:58:16.055289Z",
     "shell.execute_reply": "2023-04-12T16:58:16.055059Z",
     "shell.execute_reply.started": "2023-04-12T16:58:16.055032Z"
    }
   },
   "outputs": [],
   "source": [
    "df[\"%percent emission\"]= ((df[\"emissions\"]/df[\"emissions\"].sum())*100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.status.busy": "2023-04-12T16:58:16.057017Z",
     "iopub.status.idle": "2023-04-12T16:58:16.057553Z",
     "shell.execute_reply": "2023-04-12T16:58:16.057294Z",
     "shell.execute_reply.started": "2023-04-12T16:58:16.057268Z"
    }
   },
   "outputs": [],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.status.busy": "2023-04-12T16:58:16.060757Z",
     "iopub.status.idle": "2023-04-12T16:58:16.061301Z",
     "shell.execute_reply": "2023-04-12T16:58:16.061077Z",
     "shell.execute_reply.started": "2023-04-12T16:58:16.061046Z"
    }
   },
   "outputs": [],
   "source": [
    "df3=df[df['country']=='World']\n",
    "df3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.status.busy": "2023-04-12T16:58:16.063276Z",
     "iopub.status.idle": "2023-04-12T16:58:16.064227Z",
     "shell.execute_reply": "2023-04-12T16:58:16.063828Z",
     "shell.execute_reply.started": "2023-04-12T16:58:16.063759Z"
    }
   },
   "outputs": [],
   "source": [
    "df4=df.loc[np.where((temp2['segment']=='Total'))]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.status.busy": "2023-04-12T16:58:16.065727Z",
     "iopub.status.idle": "2023-04-12T16:58:16.066248Z",
     "shell.execute_reply": "2023-04-12T16:58:16.066013Z",
     "shell.execute_reply.started": "2023-04-12T16:58:16.065988Z"
    }
   },
   "outputs": [],
   "source": [
    "df4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.status.busy": "2023-04-12T16:58:16.067714Z",
     "iopub.status.idle": "2023-04-12T16:58:16.068160Z",
     "shell.execute_reply": "2023-04-12T16:58:16.067963Z",
     "shell.execute_reply.started": "2023-04-12T16:58:16.067940Z"
    }
   },
   "outputs": [],
   "source": [
    "'''percent of emission in different type'''\n",
    "\n",
    "sns.barplot(data=df3, x='type',y='%percent emission')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-12T16:59:33.236579Z",
     "iopub.status.busy": "2023-04-12T16:59:33.236167Z",
     "iopub.status.idle": "2023-04-12T16:59:33.251999Z",
     "shell.execute_reply": "2023-04-12T16:59:33.250390Z",
     "shell.execute_reply.started": "2023-04-12T16:59:33.236541Z"
    }
   },
   "outputs": [],
   "source": [
    "df.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-12T17:24:33.032934Z",
     "iopub.status.busy": "2023-04-12T17:24:33.032539Z",
     "iopub.status.idle": "2023-04-12T17:24:33.040529Z",
     "shell.execute_reply": "2023-04-12T17:24:33.038821Z",
     "shell.execute_reply.started": "2023-04-12T17:24:33.032901Z"
    }
   },
   "outputs": [],
   "source": [
    "## Segment vs Emissions\n",
    "\n",
    "seg_ment=df[~(df['segment']=='Total')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-12T17:30:51.442636Z",
     "iopub.status.busy": "2023-04-12T17:30:51.441947Z",
     "iopub.status.idle": "2023-04-12T17:30:51.456353Z",
     "shell.execute_reply": "2023-04-12T17:30:51.455265Z",
     "shell.execute_reply.started": "2023-04-12T17:30:51.442599Z"
    }
   },
   "outputs": [],
   "source": [
    "seg=seg_ment.groupby('segment').emissions.sum().reset_index().sort_values(by='emissions',ascending=False,ignore_index=True)[0:10]\n",
    "seg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-12T17:34:34.503946Z",
     "iopub.status.busy": "2023-04-12T17:34:34.502729Z",
     "iopub.status.idle": "2023-04-12T17:34:34.597289Z",
     "shell.execute_reply": "2023-04-12T17:34:34.596324Z",
     "shell.execute_reply.started": "2023-04-12T17:34:34.503885Z"
    }
   },
   "outputs": [],
   "source": [
    "fig=px.bar(seg,x='segment',y='emissions',color='segment')\n",
    "fig.update_layout(title_text='Segment vs Emissions', title_x=0.5)\n",
    "#fig.update_traces(textposition='inside',textinfo='label+percent')\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-12T17:36:31.713171Z",
     "iopub.status.busy": "2023-04-12T17:36:31.712776Z",
     "iopub.status.idle": "2023-04-12T17:36:31.729242Z",
     "shell.execute_reply": "2023-04-12T17:36:31.727764Z",
     "shell.execute_reply.started": "2023-04-12T17:36:31.713135Z"
    }
   },
   "outputs": [],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-12T17:53:36.314912Z",
     "iopub.status.busy": "2023-04-12T17:53:36.314533Z",
     "iopub.status.idle": "2023-04-12T17:53:36.322277Z",
     "shell.execute_reply": "2023-04-12T17:53:36.321201Z",
     "shell.execute_reply.started": "2023-04-12T17:53:36.314881Z"
    }
   },
   "outputs": [],
   "source": [
    "##Emission vs Type analysis\n",
    "typ=df.groupby('type').emissions.sum().reset_index()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-12T17:54:34.735945Z",
     "iopub.status.busy": "2023-04-12T17:54:34.734572Z",
     "iopub.status.idle": "2023-04-12T17:54:34.783349Z",
     "shell.execute_reply": "2023-04-12T17:54:34.781882Z",
     "shell.execute_reply.started": "2023-04-12T17:54:34.735873Z"
    }
   },
   "outputs": [],
   "source": [
    "fig=px.pie(typ,values='emissions',names='type')\n",
    "fig.update_traces(textposition='inside',textinfo='label+percent')\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-12T18:03:53.189333Z",
     "iopub.status.busy": "2023-04-12T18:03:53.188322Z",
     "iopub.status.idle": "2023-04-12T18:03:53.202707Z",
     "shell.execute_reply": "2023-04-12T18:03:53.201174Z",
     "shell.execute_reply.started": "2023-04-12T18:03:53.189295Z"
    }
   },
   "outputs": [],
   "source": [
    "##segment and Reason vs Emissions\n",
    "\n",
    "sre=df.groupby(['segment','reason']).emissions.sum().reset_index()\n",
    "se=sre[~(sre['segment']=='Total')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-12T18:11:57.420456Z",
     "iopub.status.busy": "2023-04-12T18:11:57.419326Z",
     "iopub.status.idle": "2023-04-12T18:11:57.489845Z",
     "shell.execute_reply": "2023-04-12T18:11:57.488895Z",
     "shell.execute_reply.started": "2023-04-12T18:11:57.420385Z"
    }
   },
   "outputs": [],
   "source": [
    "px.bar(se,x='emissions',y='segment',color='reason')"
   ]
  }
 ],
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