Fixed AQI Downloader Python Notebook

Exceptions were being thrown when AQI_data and AQI_data_csv Folder did not preexist so code has been added to Add these Folders if not existing.
Created CSV Merging Code to create merged.csv in AQI_data_csv Folder.
Added Tirumala (Tirupati) to City Mapping
Added Sri Vijaya Puram (Previously Port Blair) to City to State Mapping (Andaman And Nicobar)

Notebook Also uses Data updated as of 27-02-2025 23:15

Note: Need to Add xarray to requirements.txt
It is an Optional dependency of Pandas but was used in the Last Cell.

aqi_downloader.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -20,7 +20,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -34,7 +34,9 @@
     "    file_exists, file_path, file_name = check_exists(date)\n",
     "    if file_exists:\n",
     "        return file_path\n",
-    "    \n",
+    "\n",
+    "    os.makedirs(\"AQI_data\", exist_ok=True)\n",
+    "\n",
     "    url = f\"https://cpcb.nic.in//upload/Downloads/{file_name}\"\n",
     "    response = requests.get(url)\n",
     "    if response.status_code == 200:\n",
@@ -48,7 +50,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -59,19 +61,19 @@
       "               '2016-01-05', '2016-01-06', '2016-01-07', '2016-01-08',\n",
       "               '2016-01-09', '2016-01-10',\n",
       "               ...\n",
-      "               '2024-11-02', '2024-11-03', '2024-11-04', '2024-11-05',\n",
-      "               '2024-11-06', '2024-11-07', '2024-11-08', '2024-11-09',\n",
-      "               '2024-11-10', '2024-11-11'],\n",
-      "              dtype='datetime64[ns]', length=3238, freq='D')\n"
+      "               '2025-02-17', '2025-02-18', '2025-02-19', '2025-02-20',\n",
+      "               '2025-02-21', '2025-02-22', '2025-02-23', '2025-02-24',\n",
+      "               '2025-02-25', '2025-02-26'],\n",
+      "              dtype='datetime64[ns]', length=3345, freq='D')\n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       "(None, 3238)"
+       "(None, 3345)"
       ]
      },
-     "execution_count": 15,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -84,7 +86,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -92,8 +94,9 @@
      "output_type": "stream",
      "text": [
       "Failed to download https://cpcb.nic.in//upload/Downloads/AQI_Bulletin_20160606.pdf with status code 404\n",
+      "Failed to download https://cpcb.nic.in//upload/Downloads/AQI_Bulletin_20170618.pdf with status code 404\n",
       "Failed to download https://cpcb.nic.in//upload/Downloads/AQI_Bulletin_20171014.pdf with status code 404\n",
-      "Failed to download https://cpcb.nic.in//upload/Downloads/AQI_Bulletin_20170618.pdf with status code 404\n"
+      "Failed to download https://cpcb.nic.in//upload/Downloads/AQI_Bulletin_20250101.pdf with status code 404\n"
      ]
     }
    ],
@@ -104,23 +107,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "3238\n"
+      "3345\n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       "3235"
+       "3341"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -133,35 +136,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "6b1ea587cbcb48f6838b51ebc5b2dfc3",
+       "model_id": "438a2a0c07fb4367b18a4deff93364e9",
        "version_major": 2,
        "version_minor": 0
       },
       "text/plain": [
-       "  0%|          | 0/3238 [00:00<?, ?it/s]"
+       "  0%|          | 0/3345 [00:00<?, ?it/s]"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "File AQI_Bulletin_20160606.pdf does not exist\n",
-      "No tables found in AQI_data/AQI_Bulletin_20160704.pdf\n",
-      "No tables found in AQI_data/AQI_Bulletin_20160721.pdf\n",
-      "No tables found in AQI_data/AQI_Bulletin_20160723.pdf\n",
-      "No tables found in AQI_data/AQI_Bulletin_20160722.pdf\n",
-      "File AQI_Bulletin_20170618.pdf does not exist\n",
-      "File AQI_Bulletin_20171014.pdf does not exist\n"
-     ]
     }
    ],
    "source": [
@@ -309,6 +299,11 @@
     "        raise ValueError(\"Table pattern not recognized\")\n",
     "\n",
     "def process_file(date):\n",
+    "    folders = [\"AQI_data\", \"AQI_data_csv\"]\n",
+    "\n",
+    "    for folder in folders:\n",
+    "        if not os.path.exists(folder):\n",
+    "            os.makedirs(folder)\n",
     "    file_exists, file_path, file_name = check_exists(date)\n",
     "    if not file_exists:\n",
     "        print(f\"File {file_name} does not exist\")\n",
@@ -364,6 +359,49 @@
     "_ = Parallel(48)(delayed(process_file)(file_path) for file_path in tqdm(dates))"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Creating Merged DataFrame"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Merged CSV saved as AQI_data_csv/merged.csv\n"
+     ]
+    }
+   ],
+   "source": [
+    "import os\n",
+    "import pandas as pd\n",
+    "\n",
+    "def merge_csv_files(folder_path, output_file):\n",
+    "    csv_files = [f for f in os.listdir(folder_path) if f.endswith('.csv')]\n",
+    "    \n",
+    "    if not csv_files:\n",
+    "        print(\"No CSV files found in the folder.\")\n",
+    "        return\n",
+    "\n",
+    "    df_list = [pd.read_csv(os.path.join(folder_path, file)) for file in csv_files]\n",
+    "    merged_df = pd.concat(df_list, ignore_index=True)\n",
+    "\n",
+    "    merged_df.to_csv(output_file, index=False)\n",
+    "    print(f\"Merged CSV saved as {output_file}\")\n",
+    "\n",
+    "# Example usage\n",
+    "folder_path = \"AQI_data_csv\"\n",
+    "output_file = \"AQI_data_csv/merged.csv\"\n",
+    "merge_csv_files(folder_path, output_file)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -373,16 +411,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "372342"
+       "397732"
       ]
      },
-     "execution_count": 19,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -394,14 +432,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "['Agartala', 'Agra', 'Ahmedabad', 'Ahmednagar', 'Aizawl', 'Ajmer', 'Akola', 'Alwar', 'Ambala', 'Amravati', 'Amritsar', 'Anantapur', 'Angul', 'Ankleshwar', 'Araria', 'Ariyalur', 'Arrah', 'Asansol', 'Aurangabad (Bihar)', 'Aurangabad(Maharashtra)', 'Baddi', 'Badlapur', 'Bagalkot', 'Baghpat', 'Bahadurgarh', 'Balasore', 'Ballabgarh', 'Banswara', 'Baran', 'Barbil', 'Bareilly', 'Baripada', 'Barmer', 'Barrackpore', 'Bathinda', 'Begusarai', 'Belapur', 'Belgaum', 'Bengaluru', 'Bettiah', 'Bhagalpur', 'Bharatpur', 'Bhilai', 'Bhilwara', 'Bhiwadi', 'Bhiwandi', 'Bhiwani', 'Bhopal', 'Bhubaneswar', 'Bidar', 'Bihar Sharif', 'Bikaner', 'Bilaspur', 'Bileipada', 'Boisar', 'Brajrajnagar', 'Bulandshahr', 'Bundi', 'Buxar', 'Byasanagar', 'Byrnihat', 'Chamarajanagar', 'Chandigarh', 'Chandrapur', 'Charkhi Dadri', 'Chengalpattu', 'Chennai', 'Chhal', 'Chhapra', 'Chikkaballapur', 'Chikkamagaluru', 'Chittoor', 'Chittorgarh', 'Churu', 'Coimbtore', 'Cuddalore', 'Cuttack', 'Damoh', 'Darbhanga', 'Dausa', 'Davanagere', 'Dehradun', 'Delhi', 'Dewas', 'Dhanbad', 'Dharuhera', 'Dharwad', 'Dholpur', 'Dhule', 'Dindigul', 'Dungarpur', 'Durgapur', 'Eloor', 'Ernakulam', 'Faridabad', 'Fatehabad', 'Firozabad', 'Gadag', 'Gandhinagar', 'Gangtok', 'Gaya', 'Ghaziabad', 'Gorakhpur', 'Greater_Noida', 'Gummidipoondi', 'Gurugram', 'Guwahati', 'Gwalior', 'Hajipur', 'Haldia', 'Hanumangarh', 'Hapur', 'Hassan', 'Haveri', 'Hisar', 'Hosur', 'Howrah', 'Hubballi', 'Hyderabad', 'Imphal', 'Indore', 'Jabalpur', 'Jaipur', 'Jaisalmer', 'Jalandhar', 'Jalgaon', 'Jalna', 'Jalore', 'Jhalawar', 'Jhansi', 'Jharsuguda', 'Jhunjhunu', 'Jind', 'Jodhpur', 'Jorapokhar', 'Kadapa', 'Kaithal', 'Kalaburgi', 'Kalyan', 'Kanchipuram', 'Kannur', 'Kanpur', 'Karauli', 'Karnal', 'Karur', 'Karwar', 'Kashipur', 'Katihar', 'Katni', 'Keonjhar', 'Khanna', 'Khurja', 'Kishanganj', 'Kochi', 'Kohima', 'Kolar', 'Kolhapur', 'Kolkata', 'Kollam', 'Koppal', 'Korba', 'Kota', 'Kozhikode', 'Kunjemura', 'Kurushketra', 'Latur', 'Loni_Ghaziabad', 'Lucknow', 'Ludhiana', 'Madurai', 'Mahad', 'Maihar', 'Malegaon', 'Mandi Gobindgarh', 'Mandideep', 'Mandikhera', 'Manesar', 'Mangalore', 'Manguraha', 'Medikeri', 'Meerut', 'Milupara', 'Mira-Bhayandar', 'Moradabad', 'Motihari', 'Mumbai', 'Munger', 'Muzaffarnagar', 'Muzaffarpur', 'Mysuru', 'NOIDA', 'Nagaon', 'Nagapattinam', 'Nagaur', 'Nagpur', 'Naharlagun', 'Nalbari', 'Nanded', 'Nandesari', 'Narnaul', 'Nashik', 'Navi Mumbai', 'Nayagarh', 'Noida', 'Ooty', 'Pali', 'Palkalaiperur', 'Palwal', 'Panchkula', 'Panipat', 'Parbhani', 'Pathardih', 'Patiala', 'Patna', 'Pimpri-Chinchwad', 'Pithampur', 'Pratapgarh', 'Prayagraj', 'Puducherry', 'Pudukottai', 'Pune', 'Purnia', 'Raichur', 'Raipur', 'Rairangpur', 'Rajamahendravaram', 'Rajgir', 'Rajsamand', 'Ramanagara', 'Ramanathapuram', 'Ranipet', 'Ratlam', 'Rishikesh', 'Rohtak', 'Rourkela', 'Rupnagar', 'Sagar', 'Saharsa', 'Salem', 'Samastipur', 'Sangli', 'Sasaram', 'Satna', 'Sawai Madhopur', 'Shillong', 'Shivamogga', 'Sikar', 'Silchar', 'Siliguri', 'Singrauli', 'Sirohi', 'Sirsa', 'Sivasagar', 'Siwan', 'Solapur', 'Sonipat', 'Sri Ganganagar', 'Srinagar', 'Suakati', 'Surat', 'Talcher', 'Tensa', 'Thane', 'Thanjavur', 'Thiruvananthapuram', 'Thoothukudi', 'Thrissur', 'Tiruchirappalli', 'Tirunelveli', 'Tirupati', 'Tirupur', 'Tonk', 'Tumidih', 'Udaipur', 'Udupi', 'Ujjain', 'Ulhasnagar', 'Vapi', 'Varanasi', 'Vatva', 'Vellore', 'Vijayapura', 'Vijayawada', 'Virar', 'Virudhunagar', 'Visakhapatnam', 'Vrindavan', 'Yadgir', 'Yamunanagar']\n"
+      "['Agartala', 'Agra', 'Ahmedabad', 'Ahmednagar', 'Aizawl', 'Ajmer', 'Akola', 'Alwar', 'Ambala', 'Amravati', 'Amritsar', 'Anantapur', 'Angul', 'Ankleshwar', 'Araria', 'Ariyalur', 'Arrah', 'Asansol', 'Aurangabad (Bihar)', 'Aurangabad(Maharashtra)', 'Baddi', 'Badlapur', 'Bagalkot', 'Baghpat', 'Bahadurgarh', 'Balasore', 'Ballabgarh', 'Banswara', 'Baran', 'Barbil', 'Bareilly', 'Baripada', 'Barmer', 'Barrackpore', 'Bathinda', 'Begusarai', 'Belapur', 'Belgaum', 'Bengaluru', 'Bettiah', 'Bhagalpur', 'Bharatpur', 'Bhilai', 'Bhilwara', 'Bhiwadi', 'Bhiwandi', 'Bhiwani', 'Bhopal', 'Bhubaneswar', 'Bidar', 'Bihar Sharif', 'Bikaner', 'Bilaspur', 'Bileipada', 'Boisar', 'Brajrajnagar', 'Bulandshahr', 'Bundi', 'Buxar', 'Byasanagar', 'Byrnihat', 'Chamarajanagar', 'Chandigarh', 'Chandrapur', 'Charkhi Dadri', 'Chengalpattu', 'Chennai', 'Chhal', 'Chhapra', 'Chikkaballapur', 'Chikkamagaluru', 'Chittoor', 'Chittorgarh', 'Churu', 'Coimbtore', 'Cuddalore', 'Cuttack', 'Damoh', 'Darbhanga', 'Dausa', 'Davanagere', 'Dehradun', 'Delhi', 'Dewas', 'Dhanbad', 'Dharuhera', 'Dharwad', 'Dholpur', 'Dhule', 'Dindigul', 'Dungarpur', 'Durgapur', 'Eloor', 'Ernakulam', 'Faridabad', 'Fatehabad', 'Firozabad', 'Gadag', 'Gandhinagar', 'Gangtok', 'Gaya', 'Ghaziabad', 'Gorakhpur', 'Greater_Noida', 'Gummidipoondi', 'Gurugram', 'Guwahati', 'Gwalior', 'Hajipur', 'Haldia', 'Hanumangarh', 'Hapur', 'Hassan', 'Haveri', 'Hisar', 'Hosur', 'Howrah', 'Hubballi', 'Hyderabad', 'Imphal', 'Indore', 'Jabalpur', 'Jaipur', 'Jaisalmer', 'Jalandhar', 'Jalgaon', 'Jalna', 'Jalore', 'Jhalawar', 'Jhansi', 'Jharsuguda', 'Jhunjhunu', 'Jind', 'Jodhpur', 'Jorapokhar', 'Kadapa', 'Kaithal', 'Kalaburgi', 'Kalyan', 'Kanchipuram', 'Kannur', 'Kanpur', 'Karauli', 'Karnal', 'Karur', 'Karwar', 'Kashipur', 'Katihar', 'Katni', 'Keonjhar', 'Khanna', 'Khurja', 'Kishanganj', 'Kochi', 'Kohima', 'Kolar', 'Kolhapur', 'Kolkata', 'Kollam', 'Koppal', 'Korba', 'Kota', 'Kozhikode', 'Kunjemura', 'Kurushketra', 'Latur', 'Loni_Ghaziabad', 'Lucknow', 'Ludhiana', 'Madurai', 'Mahad', 'Maihar', 'Malegaon', 'Mandi Gobindgarh', 'Mandideep', 'Mandikhera', 'Manesar', 'Mangalore', 'Manguraha', 'Medikeri', 'Meerut', 'Milupara', 'Mira-Bhayandar', 'Moradabad', 'Motihari', 'Mumbai', 'Munger', 'Muzaffarnagar', 'Muzaffarpur', 'Mysuru', 'NOIDA', 'Nagaon', 'Nagapattinam', 'Nagaur', 'Nagpur', 'Naharlagun', 'Nalbari', 'Nanded', 'Nandesari', 'Narnaul', 'Nashik', 'Navi Mumbai', 'Nayagarh', 'Noida', 'Ooty', 'Pali', 'Palkalaiperur', 'Palwal', 'Panchkula', 'Panipat', 'Parbhani', 'Pathardih', 'Patiala', 'Patna', 'Pimpri-Chinchwad', 'Pithampur', 'Pratapgarh', 'Prayagraj', 'Puducherry', 'Pudukottai', 'Pune', 'Purnia', 'Raichur', 'Raipur', 'Rairangpur', 'Rajamahendravaram', 'Rajgir', 'Rajsamand', 'Ramanagara', 'Ramanathapuram', 'Ranipet', 'Ratlam', 'Rishikesh', 'Rohtak', 'Rourkela', 'Rupnagar', 'Sagar', 'Saharsa', 'Salem', 'Samastipur', 'Sangli', 'Sasaram', 'Satna', 'Sawai Madhopur', 'Shillong', 'Shivamogga', 'Sikar', 'Silchar', 'Siliguri', 'Singrauli', 'Sirohi', 'Sirsa', 'Sivasagar', 'Siwan', 'Solapur', 'Sonipat', 'Sri Ganganagar', 'Sri Vijaya Puram', 'Srinagar', 'Suakati', 'Surat', 'Talcher', 'Tensa', 'Thane', 'Thanjavur', 'Thiruvananthapuram', 'Thoothukudi', 'Thrissur', 'Tiruchirappalli', 'Tirunelveli', 'Tirupati', 'Tirupur', 'Tonk', 'Tumidih', 'Udaipur', 'Udupi', 'Ujjain', 'Ulhasnagar', 'Vapi', 'Varanasi', 'Vatva', 'Vellore', 'Vijayapura', 'Vijayawada', 'Virar', 'Virudhunagar', 'Visakhapatnam', 'Vrindavan', 'Yadgir', 'Yamunanagar']\n"
      ]
     }
    ],
@@ -420,6 +458,7 @@
     "    \"Manglore\": \"Mangalore\",\n",
     "    \"Pimpri Chinchwad\": \"Pimpri-Chinchwad\",\n",
     "    \"Tumakuru\": \"Tumidih\",\n",
+    "    \"Tirumala\": \"Tirupati\",\n",
     "    \"Tiruppur\": \"Tirupur\",\n",
     "    \"Yamuna Nagar\": \"Yamunanagar\",\n",
     "    \"vellore\": \"Vellore\"  # duplicate, can map to itself or be handled separately\n",
@@ -438,48 +477,49 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
        "State\n",
-       "Andhra Pradesh       10881\n",
-       "Arunachal Pradesh      557\n",
-       "Assam                 4582\n",
-       "Bihar                26391\n",
-       "Chandigarh            1874\n",
-       "Chhattisgarh          4674\n",
-       "Delhi                 3224\n",
-       "Gujarat              11558\n",
-       "Haryana              49090\n",
-       "Himachal Pradesh       916\n",
-       "Jammu and Kashmir      822\n",
-       "Jharkhand             1872\n",
-       "Karnataka            33054\n",
-       "Kerala               11121\n",
-       "Madhya Pradesh       29800\n",
-       "Maharashtra          35954\n",
-       "Manipur                724\n",
-       "Meghalaya             1839\n",
-       "Mizoram               1433\n",
-       "Nagaland              1305\n",
-       "Odisha               10816\n",
-       "Puducherry            1330\n",
-       "Punjab               18876\n",
-       "Rajasthan            34231\n",
-       "Sikkim                 772\n",
-       "Tamil Nadu           12170\n",
-       "Telangana             3216\n",
-       "Tripura               1349\n",
-       "Uttar Pradesh        39710\n",
-       "Uttarakhand           1866\n",
-       "West Bengal          14674\n",
+       "Andaman and Nicobar        6\n",
+       "Andhra Pradesh         11546\n",
+       "Arunachal Pradesh        614\n",
+       "Assam                   5099\n",
+       "Bihar                  28633\n",
+       "Chandigarh              1980\n",
+       "Chhattisgarh            5357\n",
+       "Delhi                   3330\n",
+       "Gujarat                12195\n",
+       "Haryana                50177\n",
+       "Himachal Pradesh        1022\n",
+       "Jammu and Kashmir        822\n",
+       "Jharkhand               2076\n",
+       "Karnataka              35248\n",
+       "Kerala                 11549\n",
+       "Madhya Pradesh         31326\n",
+       "Maharashtra            39193\n",
+       "Manipur                  790\n",
+       "Meghalaya               1956\n",
+       "Mizoram                 1535\n",
+       "Nagaland                1398\n",
+       "Odisha                 12363\n",
+       "Puducherry              1433\n",
+       "Punjab                 19676\n",
+       "Rajasthan              37729\n",
+       "Sikkim                   812\n",
+       "Tamil Nadu             14080\n",
+       "Telangana               3322\n",
+       "Tripura                 1442\n",
+       "Uttar Pradesh          41800\n",
+       "Uttarakhand             2156\n",
+       "West Bengal            15406\n",
        "Name: count, dtype: int64"
       ]
      },
-     "execution_count": 21,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -593,6 +633,7 @@
     "    'Solapur': 'Maharashtra',\n",
     "    'Sonipat': 'Haryana',\n",
     "    'Sri Ganganagar': 'Rajasthan',\n",
+    "    'Sri Vijaya Puram': 'Andaman and Nicobar',\n",
     "    'Srinagar': 'Jammu and Kashmir',\n",
     "    'Suakati': 'Odisha',\n",
     "    'Surat': 'Gujarat',\n",
@@ -631,7 +672,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -694,12 +735,12 @@
        "0       Agra  417          PM\\n2.5        Severe   \n",
        "1  Bengaluru   95  PM , PM\\n2.5 10  Satisfactory   \n",
        "\n",
-       "   Based on number of monitoring stations       Date          State  \n",
-       "0                                       1 2016-01-01  Uttar Pradesh  \n",
-       "1                                       5 2016-01-01      Karnataka  "
+       "  Based on number of monitoring stations       Date          State  \n",
+       "0                                      1 2016-01-01  Uttar Pradesh  \n",
+       "1                                      5 2016-01-01      Karnataka  "
       ]
      },
-     "execution_count": 34,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -712,16 +753,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "370681"
+       "396071"
       ]
      },
-     "execution_count": 37,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -732,15 +773,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "370681\n",
-      "369967\n"
+      "396071\n",
+      "395213\n"
      ]
     }
    ],
@@ -753,7 +794,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -763,7 +804,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "zeel_py310",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
@@ -777,7 +818,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.15"
+   "version": "3.12.4"
   }
  },
  "nbformat": 4,