parameters-of-the-pd-read-csv-function.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "7328e2d9",
   "metadata": {
    "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19",
    "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5",
    "execution": {
     "iopub.execute_input": "2023-06-02T06:15:39.982230Z",
     "iopub.status.busy": "2023-06-02T06:15:39.981516Z",
     "iopub.status.idle": "2023-06-02T06:15:40.008532Z",
     "shell.execute_reply": "2023-06-02T06:15:40.007326Z"
    },
    "papermill": {
     "duration": 0.038135,
     "end_time": "2023-06-02T06:15:40.011011",
     "exception": false,
     "start_time": "2023-06-02T06:15:39.972876",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/kaggle/input/character-encoding-examples/file_guide.csv\n",
      "/kaggle/input/character-encoding-examples/olaf_Windows-1251.txt\n",
      "/kaggle/input/character-encoding-examples/shisei_UTF-8.txt\n",
      "/kaggle/input/character-encoding-examples/die_ISO-8859-1.txt\n",
      "/kaggle/input/character-encoding-examples/harpers_ASCII.txt\n",
      "/kaggle/input/character-encoding-examples/yan_BIG-5.txt\n",
      "/kaggle/input/character-encoding-examples/portugal_ISO-8859-1.txt\n",
      "/kaggle/input/world-air-quality-index-by-city-and-coordinates/AQI and Lat Long of Countries.csv\n",
      "/kaggle/input/test-csv/test.csv\n"
     ]
    }
   ],
   "source": [
    "# This Python 3 environment comes with many helpful analytics libraries installed\n",
    "# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n",
    "# For example, here's several helpful packages to load\n",
    "\n",
    "import numpy as np # linear algebra\n",
    "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
    "\n",
    "# Input data files are available in the read-only \"../input/\" directory\n",
    "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n",
    "\n",
    "import os\n",
    "for dirname, _, filenames in os.walk('/kaggle/input'):\n",
    "    for filename in filenames:\n",
    "        print(os.path.join(dirname, filename))\n",
    "\n",
    "# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n",
    "# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f79f4d15",
   "metadata": {
    "papermill": {
     "duration": 0.005956,
     "end_time": "2023-06-02T06:15:40.023388",
     "exception": false,
     "start_time": "2023-06-02T06:15:40.017432",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# <h1 style=\"font-size: 42px; font-family: 'Roboto Mono', monospace; font-weight: normal; background-color: #a2d2ff; color: #4361ee; text-align: center; border-radius: 150px 150px;\"><b>Parameters of the `pd.read_csv()` Function<b></h1>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a431d12f",
   "metadata": {
    "papermill": {
     "duration": 0.006496,
     "end_time": "2023-06-02T06:15:40.036722",
     "exception": false,
     "start_time": "2023-06-02T06:15:40.030226",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "<div style=\"border-radius:10px; border:#DEB887 solid; padding: 15px; background-color: #f6f5f5; font-size:100%; text-align:left\">\n",
    "<!-- <h3 align=\"left\"><font color='#DEB887'>Conclusion</font></h3> -->\n",
    "\n",
    "Understanding the various parameters of the `pd.read_csv()` function is essential for harnessing its full potential and effectively handling different data scenarios. In this notebook, we will explore the key parameters of the `pd.read_csv()` function and discuss how they can be utilized to customize data loading, handle different file formats, and address common data challenges."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7579686e",
   "metadata": {
    "papermill": {
     "duration": 0.005963,
     "end_time": "2023-06-02T06:15:40.049006",
     "exception": false,
     "start_time": "2023-06-02T06:15:40.043043",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# <a name=\"1\"></a><h1 style=\"font-size: 36px; font-family: 'Roboto Mono', monospace; font-weight: normal; background-color: #edf2fb; color:#ffa62b; text-align: center; border-radius: 50px 50px;\"><b>1. Header parameter</b></h1>\n",
    "\n",
    "\n",
    "<div style=\"border-radius:10px; border:#e7c6ff solid; padding: 15px; background-color: #f6f5f5; font-size:100%; text-align:left\">\n",
    "    \n",
    "- Specifies the row(s) to use as the column names. \n",
    "- By default, the first row of the file is used as the header. \n",
    "- Using this parameter, you can specify a different row as the header "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "60d7357a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-02T06:15:40.064613Z",
     "iopub.status.busy": "2023-06-02T06:15:40.064217Z",
     "iopub.status.idle": "2023-06-02T06:15:40.115184Z",
     "shell.execute_reply": "2023-06-02T06:15:40.114041Z"
    },
    "papermill": {
     "duration": 0.061035,
     "end_time": "2023-06-02T06:15:40.117721",
     "exception": false,
     "start_time": "2023-06-02T06:15:40.056686",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Unnamed: 1</th>\n",
       "      <th>Unnamed: 2</th>\n",
       "      <th>Unnamed: 3</th>\n",
       "      <th>Unnamed: 4</th>\n",
       "      <th>Unnamed: 5</th>\n",
       "      <th>Unnamed: 6</th>\n",
       "      <th>Unnamed: 7</th>\n",
       "      <th>Unnamed: 8</th>\n",
       "      <th>Unnamed: 9</th>\n",
       "      <th>Unnamed: 10</th>\n",
       "      <th>Unnamed: 11</th>\n",
       "      <th>Unnamed: 12</th>\n",
       "      <th>Unnamed: 13</th>\n",
       "      <th>Unnamed: 14</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>enrollee_id</td>\n",
       "      <td>city</td>\n",
       "      <td>city_development_index</td>\n",
       "      <td>gender</td>\n",
       "      <td>relevent_experience</td>\n",
       "      <td>enrolled_university</td>\n",
       "      <td>education_level</td>\n",
       "      <td>major_discipline</td>\n",
       "      <td>experience</td>\n",
       "      <td>company_size</td>\n",
       "      <td>company_type</td>\n",
       "      <td>last_new_job</td>\n",
       "      <td>training_hours</td>\n",
       "      <td>target</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>29725</td>\n",
       "      <td>city_40</td>\n",
       "      <td>0.776</td>\n",
       "      <td>Male</td>\n",
       "      <td>No relevent experience</td>\n",
       "      <td>no_enrollment</td>\n",
       "      <td>Graduate</td>\n",
       "      <td>STEM</td>\n",
       "      <td>15</td>\n",
       "      <td>50-99</td>\n",
       "      <td>Pvt Ltd</td>\n",
       "      <td>&gt;4</td>\n",
       "      <td>47</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>11561</td>\n",
       "      <td>city_21</td>\n",
       "      <td>0.624</td>\n",
       "      <td>NaN</td>\n",
       "      <td>No relevent experience</td>\n",
       "      <td>Full time course</td>\n",
       "      <td>Graduate</td>\n",
       "      <td>STEM</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>never</td>\n",
       "      <td>83</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>33241</td>\n",
       "      <td>city_115</td>\n",
       "      <td>0.789</td>\n",
       "      <td>NaN</td>\n",
       "      <td>No relevent experience</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Graduate</td>\n",
       "      <td>Business Degree</td>\n",
       "      <td>&lt;1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Pvt Ltd</td>\n",
       "      <td>never</td>\n",
       "      <td>52</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>666</td>\n",
       "      <td>city_162</td>\n",
       "      <td>0.767</td>\n",
       "      <td>Male</td>\n",
       "      <td>Has relevent experience</td>\n",
       "      <td>no_enrollment</td>\n",
       "      <td>Masters</td>\n",
       "      <td>STEM</td>\n",
       "      <td>&gt;20</td>\n",
       "      <td>50-99</td>\n",
       "      <td>Funded Startup</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0   Unnamed: 1 Unnamed: 2              Unnamed: 3 Unnamed: 4  \\\n",
       "0           0  enrollee_id       city  city_development_index     gender   \n",
       "1           1        29725    city_40                   0.776       Male   \n",
       "2           2        11561    city_21                   0.624        NaN   \n",
       "3           3        33241   city_115                   0.789        NaN   \n",
       "4           4          666   city_162                   0.767       Male   \n",
       "\n",
       "                Unnamed: 5           Unnamed: 6       Unnamed: 7  \\\n",
       "0      relevent_experience  enrolled_university  education_level   \n",
       "1   No relevent experience        no_enrollment         Graduate   \n",
       "2   No relevent experience     Full time course         Graduate   \n",
       "3   No relevent experience                  NaN         Graduate   \n",
       "4  Has relevent experience        no_enrollment          Masters   \n",
       "\n",
       "         Unnamed: 8  Unnamed: 9   Unnamed: 10     Unnamed: 11   Unnamed: 12  \\\n",
       "0  major_discipline  experience  company_size    company_type  last_new_job   \n",
       "1              STEM          15         50-99         Pvt Ltd            >4   \n",
       "2              STEM           5           NaN             NaN         never   \n",
       "3   Business Degree          <1           NaN         Pvt Ltd         never   \n",
       "4              STEM         >20         50-99  Funded Startup             4   \n",
       "\n",
       "      Unnamed: 13 Unnamed: 14  \n",
       "0  training_hours      target  \n",
       "1              47           0  \n",
       "2              83           0  \n",
       "3              52           1  \n",
       "4               8           0  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('/kaggle/input/test-csv/test.csv')\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5c1bd511",
   "metadata": {
    "papermill": {
     "duration": 0.006408,
     "end_time": "2023-06-02T06:15:40.131152",
     "exception": false,
     "start_time": "2023-06-02T06:15:40.124744",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "here the row 1 is the names of the column, so to make it as the column name, we can pass in `header=1`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e4ac32b1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-02T06:15:40.146356Z",
     "iopub.status.busy": "2023-06-02T06:15:40.145965Z",
     "iopub.status.idle": "2023-06-02T06:15:40.167109Z",
     "shell.execute_reply": "2023-06-02T06:15:40.166258Z"
    },
    "papermill": {
     "duration": 0.031589,
     "end_time": "2023-06-02T06:15:40.169398",
     "exception": false,
     "start_time": "2023-06-02T06:15:40.137809",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>enrollee_id</th>\n",
       "      <th>city</th>\n",
       "      <th>city_development_index</th>\n",
       "      <th>gender</th>\n",
       "      <th>relevent_experience</th>\n",
       "      <th>enrolled_university</th>\n",
       "      <th>education_level</th>\n",
       "      <th>major_discipline</th>\n",
       "      <th>experience</th>\n",
       "      <th>company_size</th>\n",
       "      <th>company_type</th>\n",
       "      <th>last_new_job</th>\n",
       "      <th>training_hours</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>29725</td>\n",
       "      <td>city_40</td>\n",
       "      <td>0.776</td>\n",
       "      <td>Male</td>\n",
       "      <td>No relevent experience</td>\n",
       "      <td>no_enrollment</td>\n",
       "      <td>Graduate</td>\n",
       "      <td>STEM</td>\n",
       "      <td>15</td>\n",
       "      <td>50-99</td>\n",
       "      <td>Pvt Ltd</td>\n",
       "      <td>&gt;4</td>\n",
       "      <td>47</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>11561</td>\n",
       "      <td>city_21</td>\n",
       "      <td>0.624</td>\n",
       "      <td>NaN</td>\n",
       "      <td>No relevent experience</td>\n",
       "      <td>Full time course</td>\n",
       "      <td>Graduate</td>\n",
       "      <td>STEM</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>never</td>\n",
       "      <td>83</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>33241</td>\n",
       "      <td>city_115</td>\n",
       "      <td>0.789</td>\n",
       "      <td>NaN</td>\n",
       "      <td>No relevent experience</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Graduate</td>\n",
       "      <td>Business Degree</td>\n",
       "      <td>&lt;1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Pvt Ltd</td>\n",
       "      <td>never</td>\n",
       "      <td>52</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>666</td>\n",
       "      <td>city_162</td>\n",
       "      <td>0.767</td>\n",
       "      <td>Male</td>\n",
       "      <td>Has relevent experience</td>\n",
       "      <td>no_enrollment</td>\n",
       "      <td>Masters</td>\n",
       "      <td>STEM</td>\n",
       "      <td>&gt;20</td>\n",
       "      <td>50-99</td>\n",
       "      <td>Funded Startup</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   0  enrollee_id      city  city_development_index gender  \\\n",
       "0  1        29725   city_40                   0.776   Male   \n",
       "1  2        11561   city_21                   0.624    NaN   \n",
       "2  3        33241  city_115                   0.789    NaN   \n",
       "3  4          666  city_162                   0.767   Male   \n",
       "\n",
       "       relevent_experience enrolled_university education_level  \\\n",
       "0   No relevent experience       no_enrollment        Graduate   \n",
       "1   No relevent experience    Full time course        Graduate   \n",
       "2   No relevent experience                 NaN        Graduate   \n",
       "3  Has relevent experience       no_enrollment         Masters   \n",
       "\n",
       "  major_discipline experience company_size    company_type last_new_job  \\\n",
       "0             STEM         15        50-99         Pvt Ltd           >4   \n",
       "1             STEM          5          NaN             NaN        never   \n",
       "2  Business Degree         <1          NaN         Pvt Ltd        never   \n",
       "3             STEM        >20        50-99  Funded Startup            4   \n",
       "\n",
       "   training_hours  target  \n",
       "0              47       0  \n",
       "1              83       0  \n",
       "2              52       1  \n",
       "3               8       0  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_csv('/kaggle/input/test-csv/test.csv', header=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f23b21b0",
   "metadata": {
    "papermill": {
     "duration": 0.006531,
     "end_time": "2023-06-02T06:15:40.182870",
     "exception": false,
     "start_time": "2023-06-02T06:15:40.176339",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# <a name=\"1\"></a><h1 style=\"font-size: 36px; font-family: 'Roboto Mono', monospace; font-weight: normal; background-color: #edf2fb; color:#ffa62b; text-align: center; border-radius: 50px 50px;\"><b>2. usecols parameter</b></h1>\n",
    "\n",
    "<div style=\"border-radius:10px; border:#e7c6ff solid; padding: 15px; background-color: #f6f5f5; font-size:100%; text-align:left\">\n",
    "    \n",
    "- Selects specific columns to read from the file. \n",
    "- Instead of reading all columns, you can provide a list of column names or column indices to include only those columns in the resulting DataFrame."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "4f8f1ff4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-02T06:15:40.198652Z",
     "iopub.status.busy": "2023-06-02T06:15:40.197942Z",
     "iopub.status.idle": "2023-06-02T06:15:40.273713Z",
     "shell.execute_reply": "2023-06-02T06:15:40.272605Z"
    },
    "papermill": {
     "duration": 0.08663,
     "end_time": "2023-06-02T06:15:40.276287",
     "exception": false,
     "start_time": "2023-06-02T06:15:40.189657",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>City</th>\n",
       "      <th>AQI Value</th>\n",
       "      <th>AQI Category</th>\n",
       "      <th>CO AQI Value</th>\n",
       "      <th>CO AQI Category</th>\n",
       "      <th>Ozone AQI Value</th>\n",
       "      <th>Ozone AQI Category</th>\n",
       "      <th>NO2 AQI Value</th>\n",
       "      <th>NO2 AQI Category</th>\n",
       "      <th>PM2.5 AQI Value</th>\n",
       "      <th>PM2.5 AQI Category</th>\n",
       "      <th>lat</th>\n",
       "      <th>lng</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Russian Federation</td>\n",
       "      <td>Praskoveya</td>\n",
       "      <td>51</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>36</td>\n",
       "      <td>Good</td>\n",
       "      <td>0</td>\n",
       "      <td>Good</td>\n",
       "      <td>51</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>44.7444</td>\n",
       "      <td>44.2031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>Presidente Dutra</td>\n",
       "      <td>41</td>\n",
       "      <td>Good</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>5</td>\n",
       "      <td>Good</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>41</td>\n",
       "      <td>Good</td>\n",
       "      <td>-5.2900</td>\n",
       "      <td>-44.4900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>Presidente Dutra</td>\n",
       "      <td>41</td>\n",
       "      <td>Good</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>5</td>\n",
       "      <td>Good</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>41</td>\n",
       "      <td>Good</td>\n",
       "      <td>-11.2958</td>\n",
       "      <td>-41.9869</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Italy</td>\n",
       "      <td>Priolo Gargallo</td>\n",
       "      <td>66</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>39</td>\n",
       "      <td>Good</td>\n",
       "      <td>2</td>\n",
       "      <td>Good</td>\n",
       "      <td>66</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>37.1667</td>\n",
       "      <td>15.1833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Poland</td>\n",
       "      <td>Przasnysz</td>\n",
       "      <td>34</td>\n",
       "      <td>Good</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>34</td>\n",
       "      <td>Good</td>\n",
       "      <td>0</td>\n",
       "      <td>Good</td>\n",
       "      <td>20</td>\n",
       "      <td>Good</td>\n",
       "      <td>53.0167</td>\n",
       "      <td>20.8833</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Country              City  AQI Value AQI Category  CO AQI Value  \\\n",
       "0  Russian Federation        Praskoveya         51     Moderate             1   \n",
       "1              Brazil  Presidente Dutra         41         Good             1   \n",
       "2              Brazil  Presidente Dutra         41         Good             1   \n",
       "3               Italy   Priolo Gargallo         66     Moderate             1   \n",
       "4              Poland         Przasnysz         34         Good             1   \n",
       "\n",
       "  CO AQI Category  Ozone AQI Value Ozone AQI Category  NO2 AQI Value  \\\n",
       "0            Good               36               Good              0   \n",
       "1            Good                5               Good              1   \n",
       "2            Good                5               Good              1   \n",
       "3            Good               39               Good              2   \n",
       "4            Good               34               Good              0   \n",
       "\n",
       "  NO2 AQI Category  PM2.5 AQI Value PM2.5 AQI Category      lat      lng  \n",
       "0             Good               51           Moderate  44.7444  44.2031  \n",
       "1             Good               41               Good  -5.2900 -44.4900  \n",
       "2             Good               41               Good -11.2958 -41.9869  \n",
       "3             Good               66           Moderate  37.1667  15.1833  \n",
       "4             Good               20               Good  53.0167  20.8833  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1 = pd.read_csv('/kaggle/input/world-air-quality-index-by-city-and-coordinates/AQI and Lat Long of Countries.csv')\n",
    "df1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f0f09de7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-02T06:15:40.292983Z",
     "iopub.status.busy": "2023-06-02T06:15:40.291999Z",
     "iopub.status.idle": "2023-06-02T06:15:40.341709Z",
     "shell.execute_reply": "2023-06-02T06:15:40.340619Z"
    },
    "papermill": {
     "duration": 0.06115,
     "end_time": "2023-06-02T06:15:40.344673",
     "exception": false,
     "start_time": "2023-06-02T06:15:40.283523",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>City</th>\n",
       "      <th>AQI Value</th>\n",
       "      <th>lat</th>\n",
       "      <th>lng</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Russian Federation</td>\n",
       "      <td>Praskoveya</td>\n",
       "      <td>51</td>\n",
       "      <td>44.7444</td>\n",
       "      <td>44.2031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>Presidente Dutra</td>\n",
       "      <td>41</td>\n",
       "      <td>-5.2900</td>\n",
       "      <td>-44.4900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>Presidente Dutra</td>\n",
       "      <td>41</td>\n",
       "      <td>-11.2958</td>\n",
       "      <td>-41.9869</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Italy</td>\n",
       "      <td>Priolo Gargallo</td>\n",
       "      <td>66</td>\n",
       "      <td>37.1667</td>\n",
       "      <td>15.1833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Poland</td>\n",
       "      <td>Przasnysz</td>\n",
       "      <td>34</td>\n",
       "      <td>53.0167</td>\n",
       "      <td>20.8833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16690</th>\n",
       "      <td>United States of America</td>\n",
       "      <td>Highland Springs</td>\n",
       "      <td>54</td>\n",
       "      <td>37.5516</td>\n",
       "      <td>-77.3285</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16691</th>\n",
       "      <td>Slovakia</td>\n",
       "      <td>Martin</td>\n",
       "      <td>71</td>\n",
       "      <td>49.0650</td>\n",
       "      <td>18.9219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16692</th>\n",
       "      <td>Slovakia</td>\n",
       "      <td>Martin</td>\n",
       "      <td>71</td>\n",
       "      <td>36.3385</td>\n",
       "      <td>-88.8513</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16693</th>\n",
       "      <td>France</td>\n",
       "      <td>Sceaux</td>\n",
       "      <td>50</td>\n",
       "      <td>48.7786</td>\n",
       "      <td>2.2906</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16694</th>\n",
       "      <td>United States of America</td>\n",
       "      <td>Westerville</td>\n",
       "      <td>71</td>\n",
       "      <td>40.1241</td>\n",
       "      <td>-82.9210</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>16695 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                        Country              City  AQI Value      lat      lng\n",
       "0            Russian Federation        Praskoveya         51  44.7444  44.2031\n",
       "1                        Brazil  Presidente Dutra         41  -5.2900 -44.4900\n",
       "2                        Brazil  Presidente Dutra         41 -11.2958 -41.9869\n",
       "3                         Italy   Priolo Gargallo         66  37.1667  15.1833\n",
       "4                        Poland         Przasnysz         34  53.0167  20.8833\n",
       "...                         ...               ...        ...      ...      ...\n",
       "16690  United States of America  Highland Springs         54  37.5516 -77.3285\n",
       "16691                  Slovakia            Martin         71  49.0650  18.9219\n",
       "16692                  Slovakia            Martin         71  36.3385 -88.8513\n",
       "16693                    France            Sceaux         50  48.7786   2.2906\n",
       "16694  United States of America       Westerville         71  40.1241 -82.9210\n",
       "\n",
       "[16695 rows x 5 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_csv('/kaggle/input/world-air-quality-index-by-city-and-coordinates/AQI and Lat Long of Countries.csv',\n",
    "            usecols=['Country', 'City', 'AQI Value', 'lat', 'lng'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "67017905",
   "metadata": {
    "papermill": {
     "duration": 0.007114,
     "end_time": "2023-06-02T06:15:40.359282",
     "exception": false,
     "start_time": "2023-06-02T06:15:40.352168",
     "status": "completed"
    },
    "tags": []
   },
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "36242ba7",
   "metadata": {
    "papermill": {
     "duration": 0.007442,
     "end_time": "2023-06-02T06:15:40.374006",
     "exception": false,
     "start_time": "2023-06-02T06:15:40.366564",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# <a name=\"1\"></a><h1 style=\"font-size: 36px; font-family: 'Roboto Mono', monospace; font-weight: normal; background-color: #edf2fb; color:#ffa62b; text-align: center; border-radius: 50px 50px;\"><b>3. squeeze parameter</b></h1>\n",
    "<div style=\"border-radius:10px; border:#e7c6ff solid; padding: 15px; background-color: #f6f5f5; font-size:100%; text-align:left\">\n",
    "    \n",
    "- used to import just one column as **a series** out of all columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "15d78673",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-02T06:15:40.390705Z",
     "iopub.status.busy": "2023-06-02T06:15:40.390054Z",
     "iopub.status.idle": "2023-06-02T06:15:40.420373Z",
     "shell.execute_reply": "2023-06-02T06:15:40.418975Z"
    },
    "papermill": {
     "duration": 0.041419,
     "end_time": "2023-06-02T06:15:40.422829",
     "exception": false,
     "start_time": "2023-06-02T06:15:40.381410",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_20/4034721425.py:1: FutureWarning: The squeeze argument has been deprecated and will be removed in a future version. Append .squeeze(\"columns\") to the call to squeeze.\n",
      "\n",
      "\n",
      "  series_squeeze = pd.read_csv('/kaggle/input/world-air-quality-index-by-city-and-coordinates/AQI and Lat Long of Countries.csv',\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0              Russian Federation\n",
       "1                          Brazil\n",
       "2                          Brazil\n",
       "3                           Italy\n",
       "4                          Poland\n",
       "                   ...           \n",
       "16690    United States of America\n",
       "16691                    Slovakia\n",
       "16692                    Slovakia\n",
       "16693                      France\n",
       "16694    United States of America\n",
       "Name: Country, Length: 16695, dtype: object"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "series_squeeze = pd.read_csv('/kaggle/input/world-air-quality-index-by-city-and-coordinates/AQI and Lat Long of Countries.csv', \n",
    "            usecols=['Country'], squeeze=True)\n",
    "\n",
    "series_squeeze"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "4304dc92",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-02T06:15:40.439789Z",
     "iopub.status.busy": "2023-06-02T06:15:40.439418Z",
     "iopub.status.idle": "2023-06-02T06:15:40.445899Z",
     "shell.execute_reply": "2023-06-02T06:15:40.444825Z"
    },
    "papermill": {
     "duration": 0.017496,
     "end_time": "2023-06-02T06:15:40.447945",
     "exception": false,
     "start_time": "2023-06-02T06:15:40.430449",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.series.Series"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(series_squeeze)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8ce797ab",
   "metadata": {
    "papermill": {
     "duration": 0.007246,
     "end_time": "2023-06-02T06:15:40.462894",
     "exception": false,
     "start_time": "2023-06-02T06:15:40.455648",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# <a name=\"1\"></a><h1 style=\"font-size: 36px; font-family: 'Roboto Mono', monospace; font-weight: normal; background-color: #edf2fb; color:#ffa62b; text-align: center; border-radius: 50px 50px;\"><b>4. skiprow parameter</b></h1>\n",
    "<div style=\"border-radius:10px; border:#e7c6ff solid; padding: 15px; background-color: #f6f5f5; font-size:100%; text-align:left\">\n",
    "    \n",
    "- used to skip certain rows\n",
    "- the row number to be skipped has to be passed as a list\n",
    "- can also use lambda functions and other complex logic to skip the rows accordingly"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "de82668b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-02T06:15:40.480441Z",
     "iopub.status.busy": "2023-06-02T06:15:40.479270Z",
     "iopub.status.idle": "2023-06-02T06:15:40.547975Z",
     "shell.execute_reply": "2023-06-02T06:15:40.546894Z"
    },
    "papermill": {
     "duration": 0.079975,
     "end_time": "2023-06-02T06:15:40.550419",
     "exception": false,
     "start_time": "2023-06-02T06:15:40.470444",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>City</th>\n",
       "      <th>AQI Value</th>\n",
       "      <th>AQI Category</th>\n",
       "      <th>CO AQI Value</th>\n",
       "      <th>CO AQI Category</th>\n",
       "      <th>Ozone AQI Value</th>\n",
       "      <th>Ozone AQI Category</th>\n",
       "      <th>NO2 AQI Value</th>\n",
       "      <th>NO2 AQI Category</th>\n",
       "      <th>PM2.5 AQI Value</th>\n",
       "      <th>PM2.5 AQI Category</th>\n",
       "      <th>lat</th>\n",
       "      <th>lng</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>Presidente Dutra</td>\n",
       "      <td>41</td>\n",
       "      <td>Good</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>5</td>\n",
       "      <td>Good</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>41</td>\n",
       "      <td>Good</td>\n",
       "      <td>-5.2900</td>\n",
       "      <td>-44.4900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>Presidente Dutra</td>\n",
       "      <td>41</td>\n",
       "      <td>Good</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>5</td>\n",
       "      <td>Good</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>41</td>\n",
       "      <td>Good</td>\n",
       "      <td>-11.2958</td>\n",
       "      <td>-41.9869</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Italy</td>\n",
       "      <td>Priolo Gargallo</td>\n",
       "      <td>66</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>39</td>\n",
       "      <td>Good</td>\n",
       "      <td>2</td>\n",
       "      <td>Good</td>\n",
       "      <td>66</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>37.1667</td>\n",
       "      <td>15.1833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>United States of America</td>\n",
       "      <td>Punta Gorda</td>\n",
       "      <td>54</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>14</td>\n",
       "      <td>Good</td>\n",
       "      <td>11</td>\n",
       "      <td>Good</td>\n",
       "      <td>54</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>16.1005</td>\n",
       "      <td>-88.8074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>United States of America</td>\n",
       "      <td>Punta Gorda</td>\n",
       "      <td>54</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>14</td>\n",
       "      <td>Good</td>\n",
       "      <td>11</td>\n",
       "      <td>Good</td>\n",
       "      <td>54</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>26.8941</td>\n",
       "      <td>-82.0513</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16687</th>\n",
       "      <td>United States of America</td>\n",
       "      <td>Highland Springs</td>\n",
       "      <td>54</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>34</td>\n",
       "      <td>Good</td>\n",
       "      <td>5</td>\n",
       "      <td>Good</td>\n",
       "      <td>54</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>37.5516</td>\n",
       "      <td>-77.3285</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16688</th>\n",
       "      <td>Slovakia</td>\n",
       "      <td>Martin</td>\n",
       "      <td>71</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>39</td>\n",
       "      <td>Good</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>71</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>49.0650</td>\n",
       "      <td>18.9219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16689</th>\n",
       "      <td>Slovakia</td>\n",
       "      <td>Martin</td>\n",
       "      <td>71</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>39</td>\n",
       "      <td>Good</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>71</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>36.3385</td>\n",
       "      <td>-88.8513</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16690</th>\n",
       "      <td>France</td>\n",
       "      <td>Sceaux</td>\n",
       "      <td>50</td>\n",
       "      <td>Good</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>20</td>\n",
       "      <td>Good</td>\n",
       "      <td>5</td>\n",
       "      <td>Good</td>\n",
       "      <td>50</td>\n",
       "      <td>Good</td>\n",
       "      <td>48.7786</td>\n",
       "      <td>2.2906</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16691</th>\n",
       "      <td>United States of America</td>\n",
       "      <td>Westerville</td>\n",
       "      <td>71</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>44</td>\n",
       "      <td>Good</td>\n",
       "      <td>2</td>\n",
       "      <td>Good</td>\n",
       "      <td>71</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>40.1241</td>\n",
       "      <td>-82.9210</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>16692 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                        Country              City  AQI Value AQI Category  \\\n",
       "0                        Brazil  Presidente Dutra         41         Good   \n",
       "1                        Brazil  Presidente Dutra         41         Good   \n",
       "2                         Italy   Priolo Gargallo         66     Moderate   \n",
       "3      United States of America       Punta Gorda         54     Moderate   \n",
       "4      United States of America       Punta Gorda         54     Moderate   \n",
       "...                         ...               ...        ...          ...   \n",
       "16687  United States of America  Highland Springs         54     Moderate   \n",
       "16688                  Slovakia            Martin         71     Moderate   \n",
       "16689                  Slovakia            Martin         71     Moderate   \n",
       "16690                    France            Sceaux         50         Good   \n",
       "16691  United States of America       Westerville         71     Moderate   \n",
       "\n",
       "       CO AQI Value CO AQI Category  Ozone AQI Value Ozone AQI Category  \\\n",
       "0                 1            Good                5               Good   \n",
       "1                 1            Good                5               Good   \n",
       "2                 1            Good               39               Good   \n",
       "3                 1            Good               14               Good   \n",
       "4                 1            Good               14               Good   \n",
       "...             ...             ...              ...                ...   \n",
       "16687             1            Good               34               Good   \n",
       "16688             1            Good               39               Good   \n",
       "16689             1            Good               39               Good   \n",
       "16690             1            Good               20               Good   \n",
       "16691             1            Good               44               Good   \n",
       "\n",
       "       NO2 AQI Value NO2 AQI Category  PM2.5 AQI Value PM2.5 AQI Category  \\\n",
       "0                  1             Good               41               Good   \n",
       "1                  1             Good               41               Good   \n",
       "2                  2             Good               66           Moderate   \n",
       "3                 11             Good               54           Moderate   \n",
       "4                 11             Good               54           Moderate   \n",
       "...              ...              ...              ...                ...   \n",
       "16687              5             Good               54           Moderate   \n",
       "16688              1             Good               71           Moderate   \n",
       "16689              1             Good               71           Moderate   \n",
       "16690              5             Good               50               Good   \n",
       "16691              2             Good               71           Moderate   \n",
       "\n",
       "           lat      lng  \n",
       "0      -5.2900 -44.4900  \n",
       "1     -11.2958 -41.9869  \n",
       "2      37.1667  15.1833  \n",
       "3      16.1005 -88.8074  \n",
       "4      26.8941 -82.0513  \n",
       "...        ...      ...  \n",
       "16687  37.5516 -77.3285  \n",
       "16688  49.0650  18.9219  \n",
       "16689  36.3385 -88.8513  \n",
       "16690  48.7786   2.2906  \n",
       "16691  40.1241 -82.9210  \n",
       "\n",
       "[16692 rows x 14 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_csv('/kaggle/input/world-air-quality-index-by-city-and-coordinates/AQI and Lat Long of Countries.csv',\n",
    "            skiprows=[1,5,10])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "8a4f318b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-02T06:15:40.568972Z",
     "iopub.status.busy": "2023-06-02T06:15:40.568186Z",
     "iopub.status.idle": "2023-06-02T06:15:40.622877Z",
     "shell.execute_reply": "2023-06-02T06:15:40.621815Z"
    },
    "papermill": {
     "duration": 0.066566,
     "end_time": "2023-06-02T06:15:40.625236",
     "exception": false,
     "start_time": "2023-06-02T06:15:40.558670",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Russian Federation</th>\n",
       "      <th>Praskoveya</th>\n",
       "      <th>51</th>\n",
       "      <th>Moderate</th>\n",
       "      <th>1</th>\n",
       "      <th>Good</th>\n",
       "      <th>36</th>\n",
       "      <th>Good.1</th>\n",
       "      <th>0</th>\n",
       "      <th>Good.2</th>\n",
       "      <th>51.1</th>\n",
       "      <th>Moderate.1</th>\n",
       "      <th>44.7444</th>\n",
       "      <th>44.2031</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>Presidente Dutra</td>\n",
       "      <td>41</td>\n",
       "      <td>Good</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>5</td>\n",
       "      <td>Good</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>41</td>\n",
       "      <td>Good</td>\n",
       "      <td>-11.2958</td>\n",
       "      <td>-41.9869</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Poland</td>\n",
       "      <td>Przasnysz</td>\n",
       "      <td>34</td>\n",
       "      <td>Good</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>34</td>\n",
       "      <td>Good</td>\n",
       "      <td>0</td>\n",
       "      <td>Good</td>\n",
       "      <td>20</td>\n",
       "      <td>Good</td>\n",
       "      <td>53.0167</td>\n",
       "      <td>20.8833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>United States of America</td>\n",
       "      <td>Punta Gorda</td>\n",
       "      <td>54</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>14</td>\n",
       "      <td>Good</td>\n",
       "      <td>11</td>\n",
       "      <td>Good</td>\n",
       "      <td>54</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>26.8941</td>\n",
       "      <td>-82.0513</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Russian Federation</td>\n",
       "      <td>Pyatigorsk</td>\n",
       "      <td>54</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>41</td>\n",
       "      <td>Good</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>54</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>44.0500</td>\n",
       "      <td>43.0667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Netherlands</td>\n",
       "      <td>Raalte</td>\n",
       "      <td>41</td>\n",
       "      <td>Good</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>24</td>\n",
       "      <td>Good</td>\n",
       "      <td>6</td>\n",
       "      <td>Good</td>\n",
       "      <td>41</td>\n",
       "      <td>Good</td>\n",
       "      <td>52.3833</td>\n",
       "      <td>6.2667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8342</th>\n",
       "      <td>China</td>\n",
       "      <td>Wangqing</td>\n",
       "      <td>101</td>\n",
       "      <td>Unhealthy for Sensitive Groups</td>\n",
       "      <td>3</td>\n",
       "      <td>Good</td>\n",
       "      <td>35</td>\n",
       "      <td>Good</td>\n",
       "      <td>2</td>\n",
       "      <td>Good</td>\n",
       "      <td>101</td>\n",
       "      <td>Unhealthy for Sensitive Groups</td>\n",
       "      <td>43.3126</td>\n",
       "      <td>129.7572</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8343</th>\n",
       "      <td>United Kingdom of Great Britain and Northern I...</td>\n",
       "      <td>Urmston</td>\n",
       "      <td>33</td>\n",
       "      <td>Good</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>30</td>\n",
       "      <td>Good</td>\n",
       "      <td>3</td>\n",
       "      <td>Good</td>\n",
       "      <td>33</td>\n",
       "      <td>Good</td>\n",
       "      <td>53.4487</td>\n",
       "      <td>-2.3747</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8344</th>\n",
       "      <td>United States of America</td>\n",
       "      <td>Highland Springs</td>\n",
       "      <td>54</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>34</td>\n",
       "      <td>Good</td>\n",
       "      <td>5</td>\n",
       "      <td>Good</td>\n",
       "      <td>54</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>37.5516</td>\n",
       "      <td>-77.3285</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8345</th>\n",
       "      <td>Slovakia</td>\n",
       "      <td>Martin</td>\n",
       "      <td>71</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>39</td>\n",
       "      <td>Good</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>71</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>36.3385</td>\n",
       "      <td>-88.8513</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8346</th>\n",
       "      <td>United States of America</td>\n",
       "      <td>Westerville</td>\n",
       "      <td>71</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>44</td>\n",
       "      <td>Good</td>\n",
       "      <td>2</td>\n",
       "      <td>Good</td>\n",
       "      <td>71</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>40.1241</td>\n",
       "      <td>-82.9210</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8347 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     Russian Federation        Praskoveya  \\\n",
       "0                                                Brazil  Presidente Dutra   \n",
       "1                                                Poland         Przasnysz   \n",
       "2                              United States of America       Punta Gorda   \n",
       "3                                    Russian Federation        Pyatigorsk   \n",
       "4                                           Netherlands            Raalte   \n",
       "...                                                 ...               ...   \n",
       "8342                                              China          Wangqing   \n",
       "8343  United Kingdom of Great Britain and Northern I...           Urmston   \n",
       "8344                           United States of America  Highland Springs   \n",
       "8345                                           Slovakia            Martin   \n",
       "8346                           United States of America       Westerville   \n",
       "\n",
       "       51                        Moderate  1  Good  36 Good.1   0 Good.2  \\\n",
       "0      41                            Good  1  Good   5   Good   1   Good   \n",
       "1      34                            Good  1  Good  34   Good   0   Good   \n",
       "2      54                        Moderate  1  Good  14   Good  11   Good   \n",
       "3      54                        Moderate  1  Good  41   Good   1   Good   \n",
       "4      41                            Good  1  Good  24   Good   6   Good   \n",
       "...   ...                             ... ..   ...  ..    ...  ..    ...   \n",
       "8342  101  Unhealthy for Sensitive Groups  3  Good  35   Good   2   Good   \n",
       "8343   33                            Good  1  Good  30   Good   3   Good   \n",
       "8344   54                        Moderate  1  Good  34   Good   5   Good   \n",
       "8345   71                        Moderate  1  Good  39   Good   1   Good   \n",
       "8346   71                        Moderate  1  Good  44   Good   2   Good   \n",
       "\n",
       "      51.1                      Moderate.1  44.7444   44.2031  \n",
       "0       41                            Good -11.2958  -41.9869  \n",
       "1       20                            Good  53.0167   20.8833  \n",
       "2       54                        Moderate  26.8941  -82.0513  \n",
       "3       54                        Moderate  44.0500   43.0667  \n",
       "4       41                            Good  52.3833    6.2667  \n",
       "...    ...                             ...      ...       ...  \n",
       "8342   101  Unhealthy for Sensitive Groups  43.3126  129.7572  \n",
       "8343    33                            Good  53.4487   -2.3747  \n",
       "8344    54                        Moderate  37.5516  -77.3285  \n",
       "8345    71                        Moderate  36.3385  -88.8513  \n",
       "8346    71                        Moderate  40.1241  -82.9210  \n",
       "\n",
       "[8347 rows x 14 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_csv('/kaggle/input/world-air-quality-index-by-city-and-coordinates/AQI and Lat Long of Countries.csv',\n",
    "            skiprows=(lambda x: x%2==0))\n",
    "\n",
    "#skipped all the even indexed rows; you can use the 'names' parameter and specify the header "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "de4b658e",
   "metadata": {
    "papermill": {
     "duration": 0.008209,
     "end_time": "2023-06-02T06:15:40.642101",
     "exception": false,
     "start_time": "2023-06-02T06:15:40.633892",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# <a name=\"1\"></a><h1 style=\"font-size: 36px; font-family: 'Roboto Mono', monospace; font-weight: normal; background-color: #edf2fb; color:#ffa62b; text-align: center; border-radius: 50px 50px;\"><b>5. nrows parameter</b></h1>\n",
    "<div style=\"border-radius:10px; border:#e7c6ff solid; padding: 15px; background-color: #f6f5f5; font-size:100%; text-align:left\">\n",
    "    \n",
    "- used to just import `n` rows\n",
    "- can be useful when working with large datasets and you want to load only a subset of the data for initial exploration."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "03384745",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-02T06:15:40.660808Z",
     "iopub.status.busy": "2023-06-02T06:15:40.660441Z",
     "iopub.status.idle": "2023-06-02T06:15:40.691335Z",
     "shell.execute_reply": "2023-06-02T06:15:40.690242Z"
    },
    "papermill": {
     "duration": 0.043104,
     "end_time": "2023-06-02T06:15:40.693657",
     "exception": false,
     "start_time": "2023-06-02T06:15:40.650553",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>City</th>\n",
       "      <th>AQI Value</th>\n",
       "      <th>AQI Category</th>\n",
       "      <th>CO AQI Value</th>\n",
       "      <th>CO AQI Category</th>\n",
       "      <th>Ozone AQI Value</th>\n",
       "      <th>Ozone AQI Category</th>\n",
       "      <th>NO2 AQI Value</th>\n",
       "      <th>NO2 AQI Category</th>\n",
       "      <th>PM2.5 AQI Value</th>\n",
       "      <th>PM2.5 AQI Category</th>\n",
       "      <th>lat</th>\n",
       "      <th>lng</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Russian Federation</td>\n",
       "      <td>Praskoveya</td>\n",
       "      <td>51</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>36</td>\n",
       "      <td>Good</td>\n",
       "      <td>0</td>\n",
       "      <td>Good</td>\n",
       "      <td>51</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>44.7444</td>\n",
       "      <td>44.2031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>Presidente Dutra</td>\n",
       "      <td>41</td>\n",
       "      <td>Good</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>5</td>\n",
       "      <td>Good</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>41</td>\n",
       "      <td>Good</td>\n",
       "      <td>-5.2900</td>\n",
       "      <td>-44.4900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>Presidente Dutra</td>\n",
       "      <td>41</td>\n",
       "      <td>Good</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>5</td>\n",
       "      <td>Good</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>41</td>\n",
       "      <td>Good</td>\n",
       "      <td>-11.2958</td>\n",
       "      <td>-41.9869</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Italy</td>\n",
       "      <td>Priolo Gargallo</td>\n",
       "      <td>66</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>39</td>\n",
       "      <td>Good</td>\n",
       "      <td>2</td>\n",
       "      <td>Good</td>\n",
       "      <td>66</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>37.1667</td>\n",
       "      <td>15.1833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Poland</td>\n",
       "      <td>Przasnysz</td>\n",
       "      <td>34</td>\n",
       "      <td>Good</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>34</td>\n",
       "      <td>Good</td>\n",
       "      <td>0</td>\n",
       "      <td>Good</td>\n",
       "      <td>20</td>\n",
       "      <td>Good</td>\n",
       "      <td>53.0167</td>\n",
       "      <td>20.8833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>Itagi</td>\n",
       "      <td>25</td>\n",
       "      <td>Good</td>\n",
       "      <td>0</td>\n",
       "      <td>Good</td>\n",
       "      <td>9</td>\n",
       "      <td>Good</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>25</td>\n",
       "      <td>Good</td>\n",
       "      <td>-14.1628</td>\n",
       "      <td>-40.0058</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>Nigeria</td>\n",
       "      <td>Iseyin</td>\n",
       "      <td>90</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>3</td>\n",
       "      <td>Good</td>\n",
       "      <td>18</td>\n",
       "      <td>Good</td>\n",
       "      <td>2</td>\n",
       "      <td>Good</td>\n",
       "      <td>90</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>7.9667</td>\n",
       "      <td>3.6000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>Mexico</td>\n",
       "      <td>Isla</td>\n",
       "      <td>81</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>2</td>\n",
       "      <td>Good</td>\n",
       "      <td>26</td>\n",
       "      <td>Good</td>\n",
       "      <td>3</td>\n",
       "      <td>Good</td>\n",
       "      <td>81</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>18.0292</td>\n",
       "      <td>-95.5264</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>Itaitinga</td>\n",
       "      <td>29</td>\n",
       "      <td>Good</td>\n",
       "      <td>0</td>\n",
       "      <td>Good</td>\n",
       "      <td>20</td>\n",
       "      <td>Good</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>29</td>\n",
       "      <td>Good</td>\n",
       "      <td>-3.9689</td>\n",
       "      <td>-38.5278</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>Itapemirim</td>\n",
       "      <td>44</td>\n",
       "      <td>Good</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>16</td>\n",
       "      <td>Good</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>44</td>\n",
       "      <td>Good</td>\n",
       "      <td>-21.0108</td>\n",
       "      <td>-40.8339</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               Country              City  AQI Value AQI Category  \\\n",
       "0   Russian Federation        Praskoveya         51     Moderate   \n",
       "1               Brazil  Presidente Dutra         41         Good   \n",
       "2               Brazil  Presidente Dutra         41         Good   \n",
       "3                Italy   Priolo Gargallo         66     Moderate   \n",
       "4               Poland         Przasnysz         34         Good   \n",
       "..                 ...               ...        ...          ...   \n",
       "95              Brazil             Itagi         25         Good   \n",
       "96             Nigeria            Iseyin         90     Moderate   \n",
       "97              Mexico              Isla         81     Moderate   \n",
       "98              Brazil         Itaitinga         29         Good   \n",
       "99              Brazil        Itapemirim         44         Good   \n",
       "\n",
       "    CO AQI Value CO AQI Category  Ozone AQI Value Ozone AQI Category  \\\n",
       "0              1            Good               36               Good   \n",
       "1              1            Good                5               Good   \n",
       "2              1            Good                5               Good   \n",
       "3              1            Good               39               Good   \n",
       "4              1            Good               34               Good   \n",
       "..           ...             ...              ...                ...   \n",
       "95             0            Good                9               Good   \n",
       "96             3            Good               18               Good   \n",
       "97             2            Good               26               Good   \n",
       "98             0            Good               20               Good   \n",
       "99             1            Good               16               Good   \n",
       "\n",
       "    NO2 AQI Value NO2 AQI Category  PM2.5 AQI Value PM2.5 AQI Category  \\\n",
       "0               0             Good               51           Moderate   \n",
       "1               1             Good               41               Good   \n",
       "2               1             Good               41               Good   \n",
       "3               2             Good               66           Moderate   \n",
       "4               0             Good               20               Good   \n",
       "..            ...              ...              ...                ...   \n",
       "95              1             Good               25               Good   \n",
       "96              2             Good               90           Moderate   \n",
       "97              3             Good               81           Moderate   \n",
       "98              1             Good               29               Good   \n",
       "99              1             Good               44               Good   \n",
       "\n",
       "        lat      lng  \n",
       "0   44.7444  44.2031  \n",
       "1   -5.2900 -44.4900  \n",
       "2  -11.2958 -41.9869  \n",
       "3   37.1667  15.1833  \n",
       "4   53.0167  20.8833  \n",
       "..      ...      ...  \n",
       "95 -14.1628 -40.0058  \n",
       "96   7.9667   3.6000  \n",
       "97  18.0292 -95.5264  \n",
       "98  -3.9689 -38.5278  \n",
       "99 -21.0108 -40.8339  \n",
       "\n",
       "[100 rows x 14 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_csv('/kaggle/input/world-air-quality-index-by-city-and-coordinates/AQI and Lat Long of Countries.csv', nrows=100)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f38b8499",
   "metadata": {
    "papermill": {
     "duration": 0.008984,
     "end_time": "2023-06-02T06:15:40.711736",
     "exception": false,
     "start_time": "2023-06-02T06:15:40.702752",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# <a name=\"1\"></a><h1 style=\"font-size: 36px; font-family: 'Roboto Mono', monospace; font-weight: normal; background-color: #edf2fb; color:#ffa62b; text-align: center; border-radius: 50px 50px;\"><b>6. encoding parameter & error_bad_lines parameter</b></h1>\n",
    "<div style=\"border-radius:10px; border:#e7c6ff solid; padding: 15px; background-color: #f6f5f5; font-size:100%; text-align:left\">\n",
    "    \n",
    "\n",
    "### encoding parameter\n",
    "- sometimes it so happens that some datasets have a different encoding than utf-8\n",
    "- in this cases, we use the encoding parameter to pass the encoding format in which the dataset is encoded in, so that pandas can parse it properly\n",
    "- if you do not know the encoding format, you can open the dataset on any text editor and change its encoding format to utf-8\n",
    "\n",
    "### error_bad_lines parameter\n",
    "- sometimes it so happens that there mighe be more values in the rows than the total columns in the dataset\n",
    "- in such cases, pandas throws an error\n",
    "- to avoid such rows, we can set the `error_bad_lines parameter` to `False`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "9c4ff8b4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-02T06:15:40.731931Z",
     "iopub.status.busy": "2023-06-02T06:15:40.731513Z",
     "iopub.status.idle": "2023-06-02T06:15:40.754062Z",
     "shell.execute_reply": "2023-06-02T06:15:40.752867Z"
    },
    "papermill": {
     "duration": 0.035079,
     "end_time": "2023-06-02T06:15:40.756154",
     "exception": false,
     "start_time": "2023-06-02T06:15:40.721075",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_20/468972137.py:1: FutureWarning: The error_bad_lines argument has been deprecated and will be removed in a future version. Use on_bad_lines in the future.\n",
      "\n",
      "\n",
      "  pd.read_csv('/kaggle/input/character-encoding-examples/yan_BIG-5.txt', encoding='Big5', error_bad_lines=False)\n",
      "Skipping line 16: expected 2 fields, saw 3\n",
      "Skipping line 22: expected 2 fields, saw 3\n",
      "Skipping line 30: expected 2 fields, saw 3\n",
      "Skipping line 47: expected 2 fields, saw 3\n",
      "Skipping line 48: expected 2 fields, saw 3\n",
      "Skipping line 50: expected 2 fields, saw 3\n",
      "Skipping line 57: expected 2 fields, saw 3\n",
      "Skipping line 59: expected 2 fields, saw 3\n",
      "Skipping line 60: expected 2 fields, saw 3\n",
      "Skipping line 68: expected 2 fields, saw 3\n",
      "Skipping line 75: expected 2 fields, saw 3\n",
      "Skipping line 86: expected 2 fields, saw 3\n",
      "Skipping line 89: expected 2 fields, saw 4\n",
      "Skipping line 92: expected 2 fields, saw 4\n",
      "Skipping line 105: expected 2 fields, saw 5\n",
      "Skipping line 110: expected 2 fields, saw 4\n",
      "Skipping line 121: expected 2 fields, saw 3\n",
      "Skipping line 125: expected 2 fields, saw 3\n",
      "Skipping line 147: expected 2 fields, saw 3\n",
      "\n"
     ]
    },
    {
     "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>The Project Gutenberg EBook of Yan shi jia xun</th>\n",
       "      <th>by Yan Zhitui</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>#4 in our series by Yan Zhitui</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Copyright laws are changing all over the world...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>copyright laws for your country before downloa...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>this or any other Project Gutenberg eBook.</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>This header should be the first thing seen whe...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>Michael S. Hart.  Project Gutenberg is a Trade...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>used in any sales of Project Gutenberg eBooks ...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>they hardware or software or any other related...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>express permission.]</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>*END THE SMALL PRINT! FOR PUBLIC DOMAIN EBOOKS...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>119 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        The Project Gutenberg EBook of Yan shi jia xun  by Yan Zhitui\n",
       "0                       #4 in our series by Yan Zhitui            NaN\n",
       "1    Copyright laws are changing all over the world...            NaN\n",
       "2    copyright laws for your country before downloa...            NaN\n",
       "3           this or any other Project Gutenberg eBook.            NaN\n",
       "4    This header should be the first thing seen whe...            NaN\n",
       "..                                                 ...            ...\n",
       "114  Michael S. Hart.  Project Gutenberg is a Trade...            NaN\n",
       "115  used in any sales of Project Gutenberg eBooks ...            NaN\n",
       "116  they hardware or software or any other related...            NaN\n",
       "117                               express permission.]            NaN\n",
       "118  *END THE SMALL PRINT! FOR PUBLIC DOMAIN EBOOKS...            NaN\n",
       "\n",
       "[119 rows x 2 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_csv('/kaggle/input/character-encoding-examples/yan_BIG-5.txt', encoding='Big5', error_bad_lines=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "233f1f1f",
   "metadata": {
    "papermill": {
     "duration": 0.008913,
     "end_time": "2023-06-02T06:15:40.774642",
     "exception": false,
     "start_time": "2023-06-02T06:15:40.765729",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# <a name=\"1\"></a><h1 style=\"font-size: 36px; font-family: 'Roboto Mono', monospace; font-weight: normal; background-color: #edf2fb; color:#ffa62b; text-align: center; border-radius: 50px 50px;\"><b>7. converters parameter</b></h1>\n",
    "<div style=\"border-radius:10px; border:#e7c6ff solid; padding: 15px; background-color: #f6f5f5; font-size:100%; text-align:left\">\n",
    "    \n",
    "- Applies custom functions to specific columns during parsing\n",
    "- sometimes we might want to do some convertions to the data right before we import it, in such cases, `convertors` parameter can be used\n",
    "<br>\n",
    "\n",
    "**Example**\n",
    "- suppose we want to convert 'Russian Federation' to 'Russia' and 'Brazil' to 'BR', we can use the converters parameter while reading the file and perform the operation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "de797431",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-02T06:15:40.795535Z",
     "iopub.status.busy": "2023-06-02T06:15:40.795091Z",
     "iopub.status.idle": "2023-06-02T06:15:40.800691Z",
     "shell.execute_reply": "2023-06-02T06:15:40.799388Z"
    },
    "papermill": {
     "duration": 0.018484,
     "end_time": "2023-06-02T06:15:40.802888",
     "exception": false,
     "start_time": "2023-06-02T06:15:40.784404",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def rename(name):\n",
    "    if name == \"Russian Federation\":\n",
    "        return \"Russia\"\n",
    "    elif name == 'Brazil':\n",
    "        return 'BR'\n",
    "    else:\n",
    "        return name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "35335650",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-02T06:15:40.823027Z",
     "iopub.status.busy": "2023-06-02T06:15:40.822603Z",
     "iopub.status.idle": "2023-06-02T06:15:40.888647Z",
     "shell.execute_reply": "2023-06-02T06:15:40.887841Z"
    },
    "papermill": {
     "duration": 0.078551,
     "end_time": "2023-06-02T06:15:40.890764",
     "exception": false,
     "start_time": "2023-06-02T06:15:40.812213",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>City</th>\n",
       "      <th>AQI Value</th>\n",
       "      <th>AQI Category</th>\n",
       "      <th>CO AQI Value</th>\n",
       "      <th>CO AQI Category</th>\n",
       "      <th>Ozone AQI Value</th>\n",
       "      <th>Ozone AQI Category</th>\n",
       "      <th>NO2 AQI Value</th>\n",
       "      <th>NO2 AQI Category</th>\n",
       "      <th>PM2.5 AQI Value</th>\n",
       "      <th>PM2.5 AQI Category</th>\n",
       "      <th>lat</th>\n",
       "      <th>lng</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Russia</td>\n",
       "      <td>Praskoveya</td>\n",
       "      <td>51</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>36</td>\n",
       "      <td>Good</td>\n",
       "      <td>0</td>\n",
       "      <td>Good</td>\n",
       "      <td>51</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>44.7444</td>\n",
       "      <td>44.2031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>BR</td>\n",
       "      <td>Presidente Dutra</td>\n",
       "      <td>41</td>\n",
       "      <td>Good</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>5</td>\n",
       "      <td>Good</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>41</td>\n",
       "      <td>Good</td>\n",
       "      <td>-5.2900</td>\n",
       "      <td>-44.4900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>BR</td>\n",
       "      <td>Presidente Dutra</td>\n",
       "      <td>41</td>\n",
       "      <td>Good</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>5</td>\n",
       "      <td>Good</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>41</td>\n",
       "      <td>Good</td>\n",
       "      <td>-11.2958</td>\n",
       "      <td>-41.9869</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Italy</td>\n",
       "      <td>Priolo Gargallo</td>\n",
       "      <td>66</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>39</td>\n",
       "      <td>Good</td>\n",
       "      <td>2</td>\n",
       "      <td>Good</td>\n",
       "      <td>66</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>37.1667</td>\n",
       "      <td>15.1833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Poland</td>\n",
       "      <td>Przasnysz</td>\n",
       "      <td>34</td>\n",
       "      <td>Good</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>34</td>\n",
       "      <td>Good</td>\n",
       "      <td>0</td>\n",
       "      <td>Good</td>\n",
       "      <td>20</td>\n",
       "      <td>Good</td>\n",
       "      <td>53.0167</td>\n",
       "      <td>20.8833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16690</th>\n",
       "      <td>United States of America</td>\n",
       "      <td>Highland Springs</td>\n",
       "      <td>54</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>34</td>\n",
       "      <td>Good</td>\n",
       "      <td>5</td>\n",
       "      <td>Good</td>\n",
       "      <td>54</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>37.5516</td>\n",
       "      <td>-77.3285</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16691</th>\n",
       "      <td>Slovakia</td>\n",
       "      <td>Martin</td>\n",
       "      <td>71</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>39</td>\n",
       "      <td>Good</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>71</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>49.0650</td>\n",
       "      <td>18.9219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16692</th>\n",
       "      <td>Slovakia</td>\n",
       "      <td>Martin</td>\n",
       "      <td>71</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>39</td>\n",
       "      <td>Good</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>71</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>36.3385</td>\n",
       "      <td>-88.8513</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16693</th>\n",
       "      <td>France</td>\n",
       "      <td>Sceaux</td>\n",
       "      <td>50</td>\n",
       "      <td>Good</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>20</td>\n",
       "      <td>Good</td>\n",
       "      <td>5</td>\n",
       "      <td>Good</td>\n",
       "      <td>50</td>\n",
       "      <td>Good</td>\n",
       "      <td>48.7786</td>\n",
       "      <td>2.2906</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16694</th>\n",
       "      <td>United States of America</td>\n",
       "      <td>Westerville</td>\n",
       "      <td>71</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>1</td>\n",
       "      <td>Good</td>\n",
       "      <td>44</td>\n",
       "      <td>Good</td>\n",
       "      <td>2</td>\n",
       "      <td>Good</td>\n",
       "      <td>71</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>40.1241</td>\n",
       "      <td>-82.9210</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>16695 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                        Country              City  AQI Value AQI Category  \\\n",
       "0                        Russia        Praskoveya         51     Moderate   \n",
       "1                            BR  Presidente Dutra         41         Good   \n",
       "2                            BR  Presidente Dutra         41         Good   \n",
       "3                         Italy   Priolo Gargallo         66     Moderate   \n",
       "4                        Poland         Przasnysz         34         Good   \n",
       "...                         ...               ...        ...          ...   \n",
       "16690  United States of America  Highland Springs         54     Moderate   \n",
       "16691                  Slovakia            Martin         71     Moderate   \n",
       "16692                  Slovakia            Martin         71     Moderate   \n",
       "16693                    France            Sceaux         50         Good   \n",
       "16694  United States of America       Westerville         71     Moderate   \n",
       "\n",
       "       CO AQI Value CO AQI Category  Ozone AQI Value Ozone AQI Category  \\\n",
       "0                 1            Good               36               Good   \n",
       "1                 1            Good                5               Good   \n",
       "2                 1            Good                5               Good   \n",
       "3                 1            Good               39               Good   \n",
       "4                 1            Good               34               Good   \n",
       "...             ...             ...              ...                ...   \n",
       "16690             1            Good               34               Good   \n",
       "16691             1            Good               39               Good   \n",
       "16692             1            Good               39               Good   \n",
       "16693             1            Good               20               Good   \n",
       "16694             1            Good               44               Good   \n",
       "\n",
       "       NO2 AQI Value NO2 AQI Category  PM2.5 AQI Value PM2.5 AQI Category  \\\n",
       "0                  0             Good               51           Moderate   \n",
       "1                  1             Good               41               Good   \n",
       "2                  1             Good               41               Good   \n",
       "3                  2             Good               66           Moderate   \n",
       "4                  0             Good               20               Good   \n",
       "...              ...              ...              ...                ...   \n",
       "16690              5             Good               54           Moderate   \n",
       "16691              1             Good               71           Moderate   \n",
       "16692              1             Good               71           Moderate   \n",
       "16693              5             Good               50               Good   \n",
       "16694              2             Good               71           Moderate   \n",
       "\n",
       "           lat      lng  \n",
       "0      44.7444  44.2031  \n",
       "1      -5.2900 -44.4900  \n",
       "2     -11.2958 -41.9869  \n",
       "3      37.1667  15.1833  \n",
       "4      53.0167  20.8833  \n",
       "...        ...      ...  \n",
       "16690  37.5516 -77.3285  \n",
       "16691  49.0650  18.9219  \n",
       "16692  36.3385 -88.8513  \n",
       "16693  48.7786   2.2906  \n",
       "16694  40.1241 -82.9210  \n",
       "\n",
       "[16695 rows x 14 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_csv('/kaggle/input/world-air-quality-index-by-city-and-coordinates/AQI and Lat Long of Countries.csv', \n",
    "            converters={'Country':rename})\n",
    "\n",
    "# as you can see Russia and Brazil have been renamed"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0c0846f9",
   "metadata": {
    "papermill": {
     "duration": 0.009661,
     "end_time": "2023-06-02T06:15:40.910048",
     "exception": false,
     "start_time": "2023-06-02T06:15:40.900387",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# <a name=\"1\"></a><h1 style=\"font-size: 36px; font-family: 'Roboto Mono', monospace; font-weight: normal; background-color: #edf2fb; color:#ffa62b; text-align: center; border-radius: 50px 50px;\"><b>8. chunksize parameter</b></h1>\n",
    "<div style=\"border-radius:10px; border:#e7c6ff solid; padding: 15px; background-color: #f6f5f5; font-size:100%; text-align:left\">\n",
    "    \n",
    "- Enables reading the file in smaller chunks or chunks of specified size\n",
    "- Instead of loading the entire file into memory at once, this parameter allows you to process the data in manageable portions.\n",
    "- By setting the chunksize, you can iterate over the file and perform operations on each chunk individually, which is particularly useful for working with large datasets that cannot fit into memory entirely."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "df55619d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-02T06:15:40.931494Z",
     "iopub.status.busy": "2023-06-02T06:15:40.930461Z",
     "iopub.status.idle": "2023-06-02T06:15:40.940940Z",
     "shell.execute_reply": "2023-06-02T06:15:40.940153Z"
    },
    "papermill": {
     "duration": 0.02337,
     "end_time": "2023-06-02T06:15:40.943008",
     "exception": false,
     "start_time": "2023-06-02T06:15:40.919638",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "dfs = pd.read_csv('/kaggle/input/world-air-quality-index-by-city-and-coordinates/AQI and Lat Long of Countries.csv',chunksize=5000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "1b77897e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-06-02T06:15:40.966082Z",
     "iopub.status.busy": "2023-06-02T06:15:40.965342Z",
     "iopub.status.idle": "2023-06-02T06:15:41.025068Z",
     "shell.execute_reply": "2023-06-02T06:15:41.023673Z"
    },
    "papermill": {
     "duration": 0.07516,
     "end_time": "2023-06-02T06:15:41.027881",
     "exception": false,
     "start_time": "2023-06-02T06:15:40.952721",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(5000, 14)\n",
      "(5000, 14)\n",
      "(5000, 14)\n",
      "(1695, 14)\n"
     ]
    }
   ],
   "source": [
    "for chunks in dfs:\n",
    "    print(chunks.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7b352566",
   "metadata": {
    "papermill": {
     "duration": 0.01199,
     "end_time": "2023-06-02T06:15:41.052465",
     "exception": false,
     "start_time": "2023-06-02T06:15:41.040475",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "**Now you can apply all the normal pandas operations inside the `for` loop, and it would get applied on each chunk**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8bb332c1",
   "metadata": {
    "_kg_hide-input": false,
    "papermill": {
     "duration": 0.009418,
     "end_time": "2023-06-02T06:15:41.073053",
     "exception": false,
     "start_time": "2023-06-02T06:15:41.063635",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "<div style=\"border-radius:10px; border:#fb8500 solid; padding: 15px; background-color: #f6f5f5; font-size:100%; text-align:left\">\n",
    "<h3 align=\"left\"><font color='#DEB887'>Conclusion</font></h3>\n",
    "\n",
    "* That's a wrap! Thank you so much for reading the notebook. <br>\n",
    "* There are some more parameters in the `read_csv()` function that haven't been covered here. I suggest you check the [docs](https://pandas.pydata.org/docs/reference/api/pandas.read_csv.html) if you want to read more about the parameters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a2b9ab0a",
   "metadata": {
    "papermill": {
     "duration": 0.009466,
     "end_time": "2023-06-02T06:15:41.092146",
     "exception": false,
     "start_time": "2023-06-02T06:15:41.082680",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.10"
  },
  "papermill": {
   "default_parameters": {},
   "duration": 12.64975,
   "end_time": "2023-06-02T06:15:41.923721",
   "environment_variables": {},
   "exception": null,
   "input_path": "__notebook__.ipynb",
   "output_path": "__notebook__.ipynb",
   "parameters": {},
   "start_time": "2023-06-02T06:15:29.273971",
   "version": "2.4.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}