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authorPriyansh <[email protected]>2021-11-15 23:34:43 -0500
committerPriyansh <[email protected]>2021-11-15 23:34:43 -0500
commit79a37b0e8cfb3a0c8956ef8093d34256432ea8e0 (patch)
tree7ee21a0f1831c537ef4fc92c54a5072885d25132
parent5542b6c21307ff77cab8fef4218012ec9c5d328b (diff)
downloadtemp_pred_arima-79a37b0e8cfb3a0c8956ef8093d34256432ea8e0.tar.xz
temp_pred_arima-79a37b0e8cfb3a0c8956ef8093d34256432ea8e0.zip
Sandeep added database files
Diffstat
-rw-r--r--.DS_Storebin0 -> 6148 bytes
-rw-r--r--.gitattributes2
-rw-r--r--database_files/GlobalLandTemperaturesByCity.csv3
-rw-r--r--database_files/dbcreation.ipynb5430
-rw-r--r--database_files/pythonproject.db3
5 files changed, 5438 insertions, 0 deletions
diff --git a/.DS_Store b/.DS_Store
new file mode 100644
index 0000000..6daa72f
--- /dev/null
+++ b/.DS_Store
Binary files differ
diff --git a/.gitattributes b/.gitattributes
new file mode 100644
index 0000000..81a7c83
--- /dev/null
+++ b/.gitattributes
@@ -0,0 +1,2 @@
+*.db filter=lfs diff=lfs merge=lfs -text
+*.csv filter=lfs diff=lfs merge=lfs -text
diff --git a/database_files/GlobalLandTemperaturesByCity.csv b/database_files/GlobalLandTemperaturesByCity.csv
new file mode 100644
index 0000000..b980b00
--- /dev/null
+++ b/database_files/GlobalLandTemperaturesByCity.csv
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9be86b51487f10e811a0ab43a75946739dfe7bea2342ddcd1f6bc48d51b8c493
+size 532830464
diff --git a/database_files/dbcreation.ipynb b/database_files/dbcreation.ipynb
new file mode 100644
index 0000000..194115b
--- /dev/null
+++ b/database_files/dbcreation.ipynb
@@ -0,0 +1,5430 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "50043e80",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from IPython.display import display, HTML\n",
+ "import pandas as pd\n",
+ "import sqlite3\n",
+ "from sqlite3 import Error\n",
+ "\n",
+ "def create_connection(db_file, delete_db=False):\n",
+ " import os\n",
+ " if delete_db and os.path.exists(db_file):\n",
+ " os.remove(db_file)\n",
+ "\n",
+ " conn = None\n",
+ " try:\n",
+ " conn = sqlite3.connect(db_file)\n",
+ " conn.execute(\"PRAGMA foreign_keys = 1\")\n",
+ " except Error as e:\n",
+ " print(e)\n",
+ "\n",
+ " return conn\n",
+ "\n",
+ "\n",
+ "def create_table(conn, create_table_sql):\n",
+ " try:\n",
+ " c = conn.cursor()\n",
+ " c.execute(create_table_sql)\n",
+ " except Error as e:\n",
+ " print(e)\n",
+ " \n",
+ "def execute_sql_statement(sql_statement, conn):\n",
+ " cur = conn.cursor()\n",
+ " cur.execute(sql_statement)\n",
+ "\n",
+ " rows = cur.fetchall()\n",
+ "\n",
+ " return rows"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "a0dfa189",
+ "metadata": {},
+ "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>dt</th>\n",
+ " <th>AverageTemperature</th>\n",
+ " <th>AverageTemperatureUncertainty</th>\n",
+ " <th>City</th>\n",
+ " <th>Country</th>\n",
+ " <th>Latitude</th>\n",
+ " <th>Longitude</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>2474</th>\n",
+ " <td>1950-01-01</td>\n",
+ " <td>-0.712</td>\n",
+ " <td>0.280</td>\n",
+ " <td>Århus</td>\n",
+ " <td>Denmark</td>\n",
+ " <td>57.05N</td>\n",
+ " <td>10.33E</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2475</th>\n",
+ " <td>1950-02-01</td>\n",
+ " <td>1.423</td>\n",
+ " <td>0.218</td>\n",
+ " <td>Århus</td>\n",
+ " <td>Denmark</td>\n",
+ " <td>57.05N</td>\n",
+ " <td>10.33E</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2476</th>\n",
+ " <td>1950-03-01</td>\n",
+ " <td>4.166</td>\n",
+ " <td>0.266</td>\n",
+ " <td>Århus</td>\n",
+ " <td>Denmark</td>\n",
+ " <td>57.05N</td>\n",
+ " <td>10.33E</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2477</th>\n",
+ " <td>1950-04-01</td>\n",
+ " <td>6.743</td>\n",
+ " <td>0.310</td>\n",
+ " <td>Århus</td>\n",
+ " <td>Denmark</td>\n",
+ " <td>57.05N</td>\n",
+ " <td>10.33E</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2478</th>\n",
+ " <td>1950-05-01</td>\n",
+ " <td>12.714</td>\n",
+ " <td>0.246</td>\n",
+ " <td>Århus</td>\n",
+ " <td>Denmark</td>\n",
+ " <td>57.05N</td>\n",
+ " <td>10.33E</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",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>8599207</th>\n",
+ " <td>2013-05-01</td>\n",
+ " <td>11.464</td>\n",
+ " <td>0.236</td>\n",
+ " <td>Zwolle</td>\n",
+ " <td>Netherlands</td>\n",
+ " <td>52.24N</td>\n",
+ " <td>5.26E</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>8599208</th>\n",
+ " <td>2013-06-01</td>\n",
+ " <td>15.043</td>\n",
+ " <td>0.261</td>\n",
+ " <td>Zwolle</td>\n",
+ " <td>Netherlands</td>\n",
+ " <td>52.24N</td>\n",
+ " <td>5.26E</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>8599209</th>\n",
+ " <td>2013-07-01</td>\n",
+ " <td>18.775</td>\n",
+ " <td>0.193</td>\n",
+ " <td>Zwolle</td>\n",
+ " <td>Netherlands</td>\n",
+ " <td>52.24N</td>\n",
+ " <td>5.26E</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>8599210</th>\n",
+ " <td>2013-08-01</td>\n",
+ " <td>18.025</td>\n",
+ " <td>0.298</td>\n",
+ " <td>Zwolle</td>\n",
+ " <td>Netherlands</td>\n",
+ " <td>52.24N</td>\n",
+ " <td>5.26E</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>8599211</th>\n",
+ " <td>2013-09-01</td>\n",
+ " <td>NaN</td>\n",
+ " <td>NaN</td>\n",
+ " <td>Zwolle</td>\n",
+ " <td>Netherlands</td>\n",
+ " <td>52.24N</td>\n",
+ " <td>5.26E</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "<p>2685150 rows × 7 columns</p>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " dt AverageTemperature AverageTemperatureUncertainty \\\n",
+ "2474 1950-01-01 -0.712 0.280 \n",
+ "2475 1950-02-01 1.423 0.218 \n",
+ "2476 1950-03-01 4.166 0.266 \n",
+ "2477 1950-04-01 6.743 0.310 \n",
+ "2478 1950-05-01 12.714 0.246 \n",
+ "... ... ... ... \n",
+ "8599207 2013-05-01 11.464 0.236 \n",
+ "8599208 2013-06-01 15.043 0.261 \n",
+ "8599209 2013-07-01 18.775 0.193 \n",
+ "8599210 2013-08-01 18.025 0.298 \n",
+ "8599211 2013-09-01 NaN NaN \n",
+ "\n",
+ " City Country Latitude Longitude \n",
+ "2474 Århus Denmark 57.05N 10.33E \n",
+ "2475 Århus Denmark 57.05N 10.33E \n",
+ "2476 Århus Denmark 57.05N 10.33E \n",
+ "2477 Århus Denmark 57.05N 10.33E \n",
+ "2478 Århus Denmark 57.05N 10.33E \n",
+ "... ... ... ... ... \n",
+ "8599207 Zwolle Netherlands 52.24N 5.26E \n",
+ "8599208 Zwolle Netherlands 52.24N 5.26E \n",
+ "8599209 Zwolle Netherlands 52.24N 5.26E \n",
+ "8599210 Zwolle Netherlands 52.24N 5.26E \n",
+ "8599211 Zwolle Netherlands 52.24N 5.26E \n",
+ "\n",
+ "[2685150 rows x 7 columns]"
+ ]
+ },
+ "execution_count": 2,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "import pandas as pd\n",
+ "df=pd.read_csv(\"GlobalLandTemperaturesByCity.csv\")\n",
+ "data=df[df.dt>\"1949-12-31\"]\n",
+ "data\n",
+ " "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 92,
+ "id": "77341f9c",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
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+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ('Çorlu', '40.99N', '27.69E'),\n",
+ " ...]"
+ ]
+ },
+ "execution_count": 92,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "data_for_loc_table=data[['City','Latitude','Longitude']]\n",
+ "data_for_loc_table=data_for_loc_table.to_records(index=False)\n",
+ "result_data_for_loc_table=list(data_for_loc_table)\n",
+ "result_data_for_loc_table"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "e635279c",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "records=data.to_records(index=False)\n",
+ "result=list(records)\n",
+ "req_resut=[]\n",
+ "#j=0\n",
+ "for i in result:\n",
+ " # j=j+1\n",
+ " req_resut.append((i[4],))\n",
+ " #if j==10:\n",
+ " # break\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "id": "74c13a5f",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[('Belgium',),\n",
+ " ('Mali',),\n",
+ " ('Bolivia',),\n",
+ " ('Madagascar',),\n",
+ " ('Nepal',),\n",
+ " ('Italy',),\n",
+ " ('Czech Republic',),\n",
+ " ('Lebanon',),\n",
+ " ('Laos',),\n",
+ " ('Japan',),\n",
+ " ('Cambodia',),\n",
+ " ('Eritrea',),\n",
+ " ('Bulgaria',),\n",
+ " ('Suriname',),\n",
+ " ('Reunion',),\n",
+ " ('Guatemala',),\n",
+ " ('Bosnia And Herzegovina',),\n",
+ " ('Romania',),\n",
+ " ('Macedonia',),\n",
+ " ('Ethiopia',),\n",
+ " ('Colombia',),\n",
+ " ('Ukraine',),\n",
+ " ('Uruguay',),\n",
+ " ('Israel',),\n",
+ " ('Pakistan',),\n",
+ " ('Central African Republic',),\n",
+ " ('Indonesia',),\n",
+ " ('Slovenia',),\n",
+ " ('Ireland',),\n",
+ " ('Canada',),\n",
+ " ('Belarus',),\n",
+ " ('Oman',),\n",
+ " ('Swaziland',),\n",
+ " ('Bangladesh',),\n",
+ " ('Mexico',),\n",
+ " ('Tanzania',),\n",
+ " ('Rwanda',),\n",
+ " ('Niger',),\n",
+ " ('Angola',),\n",
+ " ('Guyana',),\n",
+ " ('Peru',),\n",
+ " ('Ecuador',),\n",
+ " ('Serbia',),\n",
+ " ('Turkey',),\n",
+ " ('Guinea',),\n",
+ " ('Sweden',),\n",
+ " ('Germany',),\n",
+ " ('Papua New Guinea',),\n",
+ " ('Morocco',),\n",
+ " ('Georgia',),\n",
+ " ('Nicaragua',),\n",
+ " ('Australia',),\n",
+ " ('Gabon',),\n",
+ " ('Nigeria',),\n",
+ " ('Finland',),\n",
+ " ('Panama',),\n",
+ " ('Taiwan',),\n",
+ " ('Norway',),\n",
+ " ('Burundi',),\n",
+ " ('Algeria',),\n",
+ " ('Botswana',),\n",
+ " ('Yemen',),\n",
+ " ('Dominican Republic',),\n",
+ " ('Syria',),\n",
+ " ('Spain',),\n",
+ " ('Costa Rica',),\n",
+ " ('Libya',),\n",
+ " ('Iceland',),\n",
+ " ('Lithuania',),\n",
+ " ('Armenia',),\n",
+ " ('Austria',),\n",
+ " ('Zimbabwe',),\n",
+ " ('Portugal',),\n",
+ " ('Argentina',),\n",
+ " ('Equatorial Guinea',),\n",
+ " ('Hong Kong',),\n",
+ " ('Senegal',),\n",
+ " ('Zambia',),\n",
+ " ('Philippines',),\n",
+ " ('Croatia',),\n",
+ " ('Kenya',),\n",
+ " ('Haiti',),\n",
+ " ('South Korea',),\n",
+ " ('Cuba',),\n",
+ " ('Latvia',),\n",
+ " ('Slovakia',),\n",
+ " ('Togo',),\n",
+ " ('Malawi',),\n",
+ " ('Cyprus',),\n",
+ " ('Somalia',),\n",
+ " ('Iran',),\n",
+ " ('Burkina Faso',),\n",
+ " ('Tajikistan',),\n",
+ " ('Guinea Bissau',),\n",
+ " ('Puerto Rico',),\n",
+ " ('Gambia',),\n",
+ " ('Chad',),\n",
+ " ('Kazakhstan',),\n",
+ " ('Venezuela',),\n",
+ " ('New Zealand',),\n",
+ " ('Vietnam',),\n",
+ " ('Hungary',),\n",
+ " (\"Côte D'Ivoire\",),\n",
+ " ('Switzerland',),\n",
+ " ('Sri Lanka',),\n",
+ " ('United Arab Emirates',),\n",
+ " ('Ghana',),\n",
+ " ('Uzbekistan',),\n",
+ " ('Turkmenistan',),\n",
+ " ('Djibouti',),\n",
+ " ('Namibia',),\n",
+ " ('Sudan',),\n",
+ " ('Azerbaijan',),\n",
+ " ('Poland',),\n",
+ " ('Montenegro',),\n",
+ " ('Mauritania',),\n",
+ " ('Greece',),\n",
+ " ('Mauritius',),\n",
+ " ('Burma',),\n",
+ " ('Liberia',),\n",
+ " ('Tunisia',),\n",
+ " ('Bahamas',),\n",
+ " ('Estonia',),\n",
+ " ('Congo',),\n",
+ " ('Uganda',),\n",
+ " ('India',),\n",
+ " ('Qatar',),\n",
+ " ('Chile',),\n",
+ " ('Russia',),\n",
+ " ('Bahrain',),\n",
+ " ('Mozambique',),\n",
+ " ('Congo (Democratic Republic Of The)',),\n",
+ " ('Mongolia',),\n",
+ " ('Singapore',),\n",
+ " ('Thailand',),\n",
+ " ('Moldova',),\n",
+ " ('Afghanistan',),\n",
+ " ('China',),\n",
+ " ('United States',),\n",
+ " ('Benin',),\n",
+ " ('Honduras',),\n",
+ " ('Jamaica',),\n",
+ " ('Egypt',),\n",
+ " ('Cameroon',),\n",
+ " ('South Africa',),\n",
+ " ('Paraguay',),\n",
+ " ('United Kingdom',),\n",
+ " ('Albania',),\n",
+ " ('Netherlands',),\n",
+ " ('Saudi Arabia',),\n",
+ " ('Denmark',),\n",
+ " ('Brazil',),\n",
+ " ('Sierra Leone',),\n",
+ " ('El Salvador',),\n",
+ " ('Malaysia',),\n",
+ " ('Iraq',),\n",
+ " ('Jordan',),\n",
+ " ('Lesotho',),\n",
+ " ('France',)]"
+ ]
+ },
+ "execution_count": 4,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "req_resut=list((set(req_resut)))\n",
+ "req_resut"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 12,
+ "id": "0551a70c",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[('Århus', 'Denmark'), ('Århus', 'Denmark'), ('Århus', 'Denmark'), ('Århus', 'Denmark'), ('Århus', 'Denmark'), ('Århus', 'Denmark'), ('Århus', 'Denmark'), ('Århus', 'Denmark'), ('Århus', 'Denmark'), ('Århus', 'Denmark')]\n"
+ ]
+ }
+ ],
+ "source": [
+ "#req_result_2=[]\n",
+ "#j=0\n",
+ "#for i in result:\n",
+ "# j=j+1\n",
+ " \n",
+ "# req_result_2.append((i[3],i[4]))\n",
+ "# if j==10:\n",
+ " # break\n",
+ "#print(req_result_2)\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "id": "21eca337",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "conn = create_connection('pythonproject.db')\n",
+ "cur=conn.cursor()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "id": "0422c509",
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "NameError",
+ "evalue": "name 'req_result_2' is not defined",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
+ "\u001b[0;32m<ipython-input-8-efb28f5a0e81>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreq_result_2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mreq_result_2\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mreq_result_3\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m3\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreq_result_3\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m3\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0mreq_result_2\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0;34m'a'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;31mNameError\u001b[0m: name 'req_result_2' is not defined"
+ ]
+ }
+ ],
+ "source": [
+ "for i in range(len(req_result_2)-2):\n",
+ " if (req_result_2[i][1]) != (req_result_3[i][3]):\n",
+ " print(req_result_3[i][3]+req_result_2[i][1]+'a')\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 48,
+ "id": "af74cdef",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "<sqlite3.Cursor at 0x7fe940c30c70>"
+ ]
+ },
+ "execution_count": 48,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "execute_sql_statement(\"DROP TABLE IF EXISTS City_Table\",conn)\n",
+ "execute_sql_statement(\"DROP TABLE IF EXISTS Country_Table\",conn)\n",
+ "#execute_sql_statement(\"DROP TABLE IF EXISTS City_Table\",conn)\n",
+ "#execute_sql_statement(\"DROP TABLE IF EXISTS Temperature_Table\",conn)\n",
+ "create_table(conn,'''CREATE TABLE Country_Table (PK INTEGER PRIMARY KEY, Country_Name VARCHAR)''')\n",
+ "#create_table(conn,'''CREATE TABLE City_Table (PK INTEGER PRIMARY KEY, City_Name VARCHAR , Country_Name VARCHAR,\n",
+ "#FOREIGN KEY(Country_Name) REFERENCES Country_Table(Country_Name))''')\n",
+ "#create_table(conn,'''CREATE TABLE Temperature_Table (PK INTEGER PRIMARY KEY, DATE VARCHAR , Avg_Temp VARCHAR , City_Name VARCHAR , Country_Name VARCHAR,\n",
+ "#FOREIGN KEY(City_Name) REFERENCES City_Table(City_Name),FOREIGN KEY(Country_Name) REFERENCES Country_Table(Country_Name))''')\n",
+ "# for i in result:\n",
+ "# a,b,c=i[4],i[5],i[6]\n",
+ " #print(type(a),type(b),type(c))\n",
+ " #print(a,b,c)\n",
+ " #print(\"\"\"INSERT INTO Country_Table ('Country_Name','LAT','LONG') Values ('\"\"\"+i[4]+\"'\"+\",'\"+i[5]+\"','\"+i[6]+\"')\")\n",
+ " #print(a,b,c)\n",
+ " #print(f'''INSERT INTO Country_Table ('Country_Name','LAT','LONG') Values ('{i[4]}','{i[5]}','{i[6]}')''')\n",
+ "cur.executemany(\"INSERT INTO Country_Table ('Country_Name') Values (?)\",req_resut)\n",
+ "#cur.executemany(\"INSERT INTO City_Table ('City_Name','Country_Name') Values (?,?)\",req_result_2)\n",
+ "#cur.executemany(\"INSERT INTO Temperature_Table ('DATE','Avg_Temp','City_Name','Country_Name') Values (?,?,?,?)\",req_result_3)\n",
+ "\n",
+ "\n",
+ " \n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "052b15c6",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 49,
+ "id": "59930452",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "abc=execute_sql_statement(\"Select * from Country_Table\", conn)\n",
+ "abc1={}\n",
+ "for i in abc:\n",
+ " abc1[i[1]]=i[0]\n",
+ "#abc1\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 50,
+ "id": "52c77691",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "req_result_2=[]\n",
+ "#j=0\n",
+ "for i in result:\n",
+ " \n",
+ " #j=j+1\n",
+ " req_result_2.append((i[3],abc1[i[4]]))\n",
+ " # if j==10:\n",
+ " #break\n",
+ "#print(req_result_2)\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 51,
+ "id": "f5b64360",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "create_table(conn,'''CREATE TABLE City_Table (City_Id INTEGER PRIMARY KEY, City_Name VARCHAR , Country_ID INTEGER,\n",
+ "FOREIGN KEY(Country_ID) REFERENCES Country_Table(PK))''')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 52,
+ "id": "1206d273",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "city=[]\n",
+ "for i in result:\n",
+ " # j=j+1\n",
+ " city.append((i[3],abc1[i[4]]))\n",
+ "city_country_unique=list((set(city)))\n",
+ "\n",
+ "#for i in city_country_unique:\n",
+ " # i[1]=abc1[i[1]]\n",
+ "#city_country_unique "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 54,
+ "id": "cfca5230",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "<sqlite3.Cursor at 0x7fe940c30c70>"
+ ]
+ },
+ "execution_count": 54,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "cur.executemany(\"INSERT INTO City_Table ('City_Name','Country_ID') Values (?,?)\",city_country_unique)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 71,
+ "id": "d9f71f49",
+ "metadata": {},
+ "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>City_Id</th>\n",
+ " <th>City_Name</th>\n",
+ " <th>Country_ID</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>0</th>\n",
+ " <td>1</td>\n",
+ " <td>Braila</td>\n",
+ " <td>18</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1</th>\n",
+ " <td>2</td>\n",
+ " <td>Rabat</td>\n",
+ " <td>49</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2</th>\n",
+ " <td>3</td>\n",
+ " <td>Asmara</td>\n",
+ " <td>12</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3</th>\n",
+ " <td>4</td>\n",
+ " <td>Caxias</td>\n",
+ " <td>152</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4</th>\n",
+ " <td>5</td>\n",
+ " <td>Ezhou</td>\n",
+ " <td>138</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>...</th>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3485</th>\n",
+ " <td>3486</td>\n",
+ " <td>Chakwal</td>\n",
+ " <td>25</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3486</th>\n",
+ " <td>3487</td>\n",
+ " <td>Port Louis</td>\n",
+ " <td>118</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3487</th>\n",
+ " <td>3488</td>\n",
+ " <td>Oakland</td>\n",
+ " <td>139</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3488</th>\n",
+ " <td>3489</td>\n",
+ " <td>Basti</td>\n",
+ " <td>126</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3489</th>\n",
+ " <td>3490</td>\n",
+ " <td>Colorado Springs</td>\n",
+ " <td>139</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "<p>3490 rows × 3 columns</p>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " City_Id City_Name Country_ID\n",
+ "0 1 Braila 18\n",
+ "1 2 Rabat 49\n",
+ "2 3 Asmara 12\n",
+ "3 4 Caxias 152\n",
+ "4 5 Ezhou 138\n",
+ "... ... ... ...\n",
+ "3485 3486 Chakwal 25\n",
+ "3486 3487 Port Louis 118\n",
+ "3487 3488 Oakland 139\n",
+ "3488 3489 Basti 126\n",
+ "3489 3490 Colorado Springs 139\n",
+ "\n",
+ "[3490 rows x 3 columns]"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#df=execute_sql_statement(\"Select * from City_Table\", conn)\n",
+ "df=pd.read_sql_query(\"Select * from City_Table\", conn)\n",
+ "display(df)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 56,
+ "id": "9dd4ef62",
+ "metadata": {},
+ "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>PK</th>\n",
+ " <th>Country_Name</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>0</th>\n",
+ " <td>1</td>\n",
+ " <td>Belgium</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1</th>\n",
+ " <td>2</td>\n",
+ " <td>Mali</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2</th>\n",
+ " <td>3</td>\n",
+ " <td>Bolivia</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3</th>\n",
+ " <td>4</td>\n",
+ " <td>Madagascar</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4</th>\n",
+ " <td>5</td>\n",
+ " <td>Nepal</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>...</th>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>154</th>\n",
+ " <td>155</td>\n",
+ " <td>Malaysia</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>155</th>\n",
+ " <td>156</td>\n",
+ " <td>Iraq</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>156</th>\n",
+ " <td>157</td>\n",
+ " <td>Jordan</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>157</th>\n",
+ " <td>158</td>\n",
+ " <td>Lesotho</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>158</th>\n",
+ " <td>159</td>\n",
+ " <td>France</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "<p>159 rows × 2 columns</p>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " PK Country_Name\n",
+ "0 1 Belgium\n",
+ "1 2 Mali\n",
+ "2 3 Bolivia\n",
+ "3 4 Madagascar\n",
+ "4 5 Nepal\n",
+ ".. ... ...\n",
+ "154 155 Malaysia\n",
+ "155 156 Iraq\n",
+ "156 157 Jordan\n",
+ "157 158 Lesotho\n",
+ "158 159 France\n",
+ "\n",
+ "[159 rows x 2 columns]"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "df1=pd.read_sql_query(\"Select * from Country_Table\", conn)\n",
+ "display(df1)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 58,
+ "id": "4c2a9868",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[(18, 'Haora', 126, 126, 'India'),\n",
+ " (20, 'Bhadreswar', 126, 126, 'India'),\n",
+ " (33, 'Khandwa', 126, 126, 'India'),\n",
+ " (36, 'Godhra', 126, 126, 'India'),\n",
+ " (48, 'Orai', 126, 126, 'India'),\n",
+ " (50, 'Thanesar', 126, 126, 'India'),\n",
+ " (73, 'Bahadurgarh', 126, 126, 'India'),\n",
+ " (94, 'Hoshiarpur', 126, 126, 'India'),\n",
+ " (96, 'Kanpur', 126, 126, 'India'),\n",
+ " (138, 'Chhatarpur', 126, 126, 'India')]"
+ ]
+ },
+ "execution_count": 58,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "execute_sql_statement(\"select * from City_Table join Country_Table on Country_Table.PK = City_Table.Country_ID AND Country_Table.Country_Name='India' LIMIT 10\",conn)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 62,
+ "id": "3932f5a5",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "{'Braila': 1,\n",
+ " 'Rabat': 2,\n",
+ " 'Asmara': 3,\n",
+ " 'Caxias': 4,\n",
+ " 'Ezhou': 5,\n",
+ " 'Teresina': 6,\n",
+ " 'Tirana': 7,\n",
+ " 'Jiayuguan': 8,\n",
+ " 'Atibaia': 9,\n",
+ " 'Mwene Ditu': 10,\n",
+ " 'Regina': 11,\n",
+ " 'Santa Luzia': 12,\n",
+ " 'Ica': 13,\n",
+ " 'Philadelphia': 14,\n",
+ " 'Bila Tserkva': 15,\n",
+ " 'Khimki': 16,\n",
+ " 'Lapu Lapu': 17,\n",
+ " 'Haora': 18,\n",
+ " 'Thaton': 19,\n",
+ " 'Bhadreswar': 20,\n",
+ " 'Wenzhou': 21,\n",
+ " 'San Nicolas': 22,\n",
+ " 'Yelets': 23,\n",
+ " 'Jimeta': 24,\n",
+ " 'Moriguchi': 25,\n",
+ " 'Kryvyy Rih': 26,\n",
+ " 'Omaha': 27,\n",
+ " 'Nawabshah': 28,\n",
+ " 'Adiwerna': 29,\n",
+ " 'Coacalco': 30,\n",
+ " 'Mytishchi': 31,\n",
+ " 'Mishima': 32,\n",
+ " 'Khandwa': 33,\n",
+ " 'Kirovohrad': 34,\n",
+ " 'Tychy': 35,\n",
+ " 'Godhra': 36,\n",
+ " 'Passo Fundo': 37,\n",
+ " 'Cartago': 38,\n",
+ " 'Orléans': 39,\n",
+ " 'Lille': 40,\n",
+ " 'Salihorsk': 41,\n",
+ " 'Olathe': 42,\n",
+ " 'Pomona': 43,\n",
+ " 'Aksu': 44,\n",
+ " 'Usak': 45,\n",
+ " 'Uitenhage': 46,\n",
+ " 'Leiyang': 47,\n",
+ " 'Orai': 48,\n",
+ " 'Yokkaichi': 49,\n",
+ " 'Thanesar': 50,\n",
+ " 'Anchorage': 51,\n",
+ " 'Douala': 52,\n",
+ " 'Abidjan': 53,\n",
+ " 'Temirtau': 54,\n",
+ " 'Yibin': 55,\n",
+ " 'Edéa': 56,\n",
+ " 'Beian': 57,\n",
+ " 'Arvada': 58,\n",
+ " 'Ogaki': 59,\n",
+ " 'Vilnius': 60,\n",
+ " 'Hangzhou': 61,\n",
+ " 'Potsdam': 62,\n",
+ " 'Bratsk': 63,\n",
+ " 'Jhelum': 64,\n",
+ " 'Budapest': 65,\n",
+ " 'Los Teques': 66,\n",
+ " 'Brikama': 67,\n",
+ " 'Kediri': 68,\n",
+ " 'Huangcun': 69,\n",
+ " 'Trelew': 70,\n",
+ " 'Colchester': 71,\n",
+ " 'Gorontalo': 72,\n",
+ " 'Bahadurgarh': 73,\n",
+ " 'Jiangyou': 74,\n",
+ " 'Puebla': 75,\n",
+ " 'Chimbote': 76,\n",
+ " 'Yantai': 77,\n",
+ " 'Valencia': 2864,\n",
+ " 'Spring Valley': 79,\n",
+ " 'Tongchuan': 80,\n",
+ " 'Gandajika': 81,\n",
+ " 'Funtua': 82,\n",
+ " 'Green Bay': 83,\n",
+ " 'Hargeysa': 84,\n",
+ " 'Jaffna': 85,\n",
+ " 'Florence': 86,\n",
+ " 'Tianmen': 87,\n",
+ " 'Apodaca': 88,\n",
+ " 'Ungaran': 89,\n",
+ " 'Sagamihara': 90,\n",
+ " 'The Hague': 91,\n",
+ " 'Petapa': 92,\n",
+ " 'Bahawalpur': 93,\n",
+ " 'Hoshiarpur': 94,\n",
+ " 'Zaoyang': 95,\n",
+ " 'Kanpur': 96,\n",
+ " 'Takaoka': 97,\n",
+ " 'Guarujá': 98,\n",
+ " 'Port Moresby': 99,\n",
+ " 'Downey': 100,\n",
+ " 'Fengshan': 101,\n",
+ " 'Riga': 102,\n",
+ " 'Nice': 103,\n",
+ " 'Iwaki': 104,\n",
+ " 'Vitória Da Conquista': 105,\n",
+ " 'Salinas': 106,\n",
+ " 'Wloclawek': 107,\n",
+ " 'Mazyr': 108,\n",
+ " 'Wellington': 109,\n",
+ " 'Benha': 110,\n",
+ " 'Wichita': 111,\n",
+ " 'Sunnyvale': 112,\n",
+ " 'Huaibei': 113,\n",
+ " 'Chaozhou': 114,\n",
+ " 'Longyan': 115,\n",
+ " 'Shaoxing': 116,\n",
+ " 'Touliu': 117,\n",
+ " 'Vancouver': 469,\n",
+ " 'Linshui': 119,\n",
+ " 'Malang': 120,\n",
+ " 'Magnitogorsk': 121,\n",
+ " 'Petropavlovsk Kamchatskiy': 122,\n",
+ " 'Ibadan': 123,\n",
+ " 'Petare': 124,\n",
+ " 'Magé': 125,\n",
+ " 'Maringá': 126,\n",
+ " 'Tarhunah': 127,\n",
+ " 'Celaya': 128,\n",
+ " 'Huancayo': 129,\n",
+ " 'Yevpatoriya': 130,\n",
+ " 'Kariya': 131,\n",
+ " 'Sakura': 132,\n",
+ " 'Lvov': 133,\n",
+ " 'Varna': 134,\n",
+ " 'Yerevan': 135,\n",
+ " 'Poá': 136,\n",
+ " 'Juliaca': 137,\n",
+ " 'Chhatarpur': 138,\n",
+ " 'Ivanovo': 139,\n",
+ " 'Jerusalem': 140,\n",
+ " 'Malambo': 141,\n",
+ " 'Nandurbar': 142,\n",
+ " 'Amroha': 143,\n",
+ " 'Belgorod': 144,\n",
+ " 'Rangpur': 145,\n",
+ " 'Nis': 146,\n",
+ " 'Tokyo': 147,\n",
+ " 'Guantánamo': 148,\n",
+ " 'Kure': 149,\n",
+ " 'Tacloban': 150,\n",
+ " 'Stockton': 151,\n",
+ " 'Gojra': 152,\n",
+ " 'Naucalpan': 153,\n",
+ " 'Moradabad': 154,\n",
+ " 'Neyveli': 155,\n",
+ " 'Clermont Ferrand': 156,\n",
+ " 'Bandung': 157,\n",
+ " 'Maanshan': 158,\n",
+ " 'Tianjin': 159,\n",
+ " 'Garza García': 160,\n",
+ " 'Baia Mare': 161,\n",
+ " 'Tanshui': 162,\n",
+ " 'Chita': 163,\n",
+ " 'Tengzhou': 164,\n",
+ " 'Vanadzor': 165,\n",
+ " 'Vizianagaram': 166,\n",
+ " 'Udon Thani': 167,\n",
+ " 'Beni Suef': 168,\n",
+ " 'Turhal': 169,\n",
+ " 'Ludwigshafen': 170,\n",
+ " 'Evansville': 171,\n",
+ " 'Blitar': 172,\n",
+ " 'Hyderabad': 1474,\n",
+ " 'Namangan': 174,\n",
+ " 'Xinzhou': 175,\n",
+ " 'Colombo': 885,\n",
+ " 'Badalona': 177,\n",
+ " 'Louga': 178,\n",
+ " 'Gloucester': 179,\n",
+ " 'Mariara': 180,\n",
+ " 'Visakhapatnam': 181,\n",
+ " 'Madhyamgram': 182,\n",
+ " 'Tripoli': 183,\n",
+ " 'Luque': 184,\n",
+ " 'Daloa': 185,\n",
+ " 'Goiânia': 186,\n",
+ " 'Araraquara': 187,\n",
+ " 'Bissau': 188,\n",
+ " 'Misato': 189,\n",
+ " 'Itapevi': 190,\n",
+ " 'Miandoab': 191,\n",
+ " 'Torreón': 192,\n",
+ " 'Middlesbrough': 193,\n",
+ " 'Lengshuijiang': 194,\n",
+ " 'Irbil': 195,\n",
+ " 'Ashdod': 196,\n",
+ " 'Kolomna': 197,\n",
+ " 'Houma': 198,\n",
+ " 'Yenangyaung': 199,\n",
+ " 'Abu Dhabi': 200,\n",
+ " 'Pontianak': 201,\n",
+ " 'Bialystok': 202,\n",
+ " 'Antofagasta': 203,\n",
+ " 'Goma': 204,\n",
+ " 'Ongole': 205,\n",
+ " 'Tumkur': 206,\n",
+ " 'Jalpaiguri': 207,\n",
+ " 'Gudivada': 208,\n",
+ " 'Sudbury': 209,\n",
+ " 'Mahbubnagar': 210,\n",
+ " 'Shreveport': 211,\n",
+ " 'La Rioja': 212,\n",
+ " 'Newcastle': 2044,\n",
+ " 'Warsaw': 214,\n",
+ " 'Kiel': 215,\n",
+ " 'Morvi': 216,\n",
+ " 'Kurume': 217,\n",
+ " 'Teófilo Otoni': 218,\n",
+ " 'Derby': 219,\n",
+ " 'Idlib': 220,\n",
+ " 'Kakinada': 221,\n",
+ " 'Jhansi': 222,\n",
+ " 'Komaki': 223,\n",
+ " 'Badlapur': 224,\n",
+ " 'Santa Maria': 225,\n",
+ " 'Leghorn': 226,\n",
+ " 'Jinchengjiang': 227,\n",
+ " 'Buffalo': 228,\n",
+ " 'Kassel': 229,\n",
+ " 'Katumba': 230,\n",
+ " 'San Juan': 706,\n",
+ " 'Palwal': 232,\n",
+ " 'Bielsko Biala': 233,\n",
+ " 'Brasília': 234,\n",
+ " 'Lusaka': 235,\n",
+ " 'Ingraj Bazar': 236,\n",
+ " 'Bilbao': 237,\n",
+ " 'Brescia': 238,\n",
+ " 'Almetyevsk': 239,\n",
+ " 'Chiclayo': 240,\n",
+ " 'Norman': 241,\n",
+ " 'Gorgan': 242,\n",
+ " 'Ratlam': 243,\n",
+ " 'Mataró': 244,\n",
+ " 'Selam': 245,\n",
+ " 'Mawlamyine': 246,\n",
+ " 'Gravataí': 247,\n",
+ " 'Roseville': 248,\n",
+ " 'Suining': 249,\n",
+ " 'Maragheh': 250,\n",
+ " 'Lembang': 251,\n",
+ " 'Guayaquil': 252,\n",
+ " 'Bello': 253,\n",
+ " 'Siirt': 254,\n",
+ " 'Algeciras': 255,\n",
+ " 'Fuzhou': 256,\n",
+ " 'Derbent': 257,\n",
+ " 'Haicheng': 258,\n",
+ " 'Barueri': 259,\n",
+ " 'Banjarmasin': 260,\n",
+ " 'Rajpur': 261,\n",
+ " 'São Caetano Do Sul': 262,\n",
+ " 'Cilegon': 263,\n",
+ " 'Pretoria': 264,\n",
+ " 'Bulawayo': 265,\n",
+ " 'Montería': 266,\n",
+ " 'Sambalpur': 267,\n",
+ " 'Nanyang': 268,\n",
+ " 'Graz': 269,\n",
+ " 'Meiktila': 270,\n",
+ " 'Bournemouth': 271,\n",
+ " 'Cikampek': 272,\n",
+ " 'Lleida': 273,\n",
+ " 'Pondicherry': 274,\n",
+ " 'Kashihara': 275,\n",
+ " 'Ibirité': 276,\n",
+ " 'Wroclaw': 277,\n",
+ " 'Jersey City': 278,\n",
+ " 'Kuantan': 279,\n",
+ " 'San Miguelito': 280,\n",
+ " 'Lira': 281,\n",
+ " 'Bologna': 282,\n",
+ " 'Carmen': 283,\n",
+ " 'Jolo': 284,\n",
+ " 'Zenica': 285,\n",
+ " 'Bridgeport': 286,\n",
+ " 'Thanjavur': 287,\n",
+ " 'Ibagué': 288,\n",
+ " 'Midrand': 289,\n",
+ " 'Cibinong': 290,\n",
+ " 'Nancy': 291,\n",
+ " 'Castanhal': 292,\n",
+ " 'Maracanaú': 293,\n",
+ " 'Oulu': 294,\n",
+ " 'Xichang': 295,\n",
+ " 'Maturín': 296,\n",
+ " 'Guaymas': 297,\n",
+ " 'Bombay': 298,\n",
+ " 'Imabari': 299,\n",
+ " 'Ningbo': 300,\n",
+ " 'Jiroft': 301,\n",
+ " 'Anyang': 302,\n",
+ " 'Morena': 303,\n",
+ " 'Vidisha': 304,\n",
+ " 'Jingdezhen': 305,\n",
+ " 'Esenyurt': 306,\n",
+ " 'Cairns': 307,\n",
+ " 'Jaú': 308,\n",
+ " 'Tapachula': 309,\n",
+ " 'Cimahi': 310,\n",
+ " 'Queimados': 311,\n",
+ " 'Itajaí': 312,\n",
+ " 'Volgodonsk': 313,\n",
+ " 'Mandi Bahauddin': 314,\n",
+ " 'Embu': 315,\n",
+ " 'Parana': 316,\n",
+ " 'Beaumont': 317,\n",
+ " 'Çorlu': 318,\n",
+ " 'Djougou': 319,\n",
+ " 'Santa Fe': 320,\n",
+ " 'Overland Park': 321,\n",
+ " 'Cincinnati': 322,\n",
+ " 'Danshui': 323,\n",
+ " 'Arlington': 324,\n",
+ " 'Cianjur': 325,\n",
+ " 'Jequié': 326,\n",
+ " 'Pyay': 327,\n",
+ " 'Chalco': 328,\n",
+ " 'Ürümqi': 329,\n",
+ " 'Fuxin': 330,\n",
+ " 'Mandsaur': 331,\n",
+ " 'Malatya': 332,\n",
+ " 'Campeche': 333,\n",
+ " 'Carúpano': 334,\n",
+ " 'Baharampur': 335,\n",
+ " 'Punta Arenas': 336,\n",
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+ " 'Nehe': 338,\n",
+ " 'Nuevo Laredo': 339,\n",
+ " 'Guntur': 340,\n",
+ " 'Khuzdar': 341,\n",
+ " 'San Diego': 342,\n",
+ " 'Guna': 343,\n",
+ " 'Yatsushiro': 344,\n",
+ " 'Perm': 345,\n",
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+ " 'Garut': 347,\n",
+ " 'Shahreza': 348,\n",
+ " 'Yuci': 349,\n",
+ " 'Anbu': 350,\n",
+ " 'Ranghulu': 351,\n",
+ " 'Puqi': 352,\n",
+ " 'Hamilton': 3150,\n",
+ " 'Ocumare Del Tuy': 354,\n",
+ " 'Ciputat': 355,\n",
+ " 'Potosí': 356,\n",
+ " 'Rostov Na Donu': 357,\n",
+ " 'Satkhira': 358,\n",
+ " 'Taunggyi': 359,\n",
+ " 'Teluknaga': 360,\n",
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+ " 'Uruguaiana': 362,\n",
+ " 'Alexandria': 1256,\n",
+ " 'Lincoln': 364,\n",
+ " 'Ambattur': 365,\n",
+ " 'Novi Sad': 366,\n",
+ " 'Calgary': 367,\n",
+ " 'Nacala': 368,\n",
+ " 'Thanyaburi': 369,\n",
+ " 'Port Said': 370,\n",
+ " 'Amadora': 371,\n",
+ " 'Cicalengka': 372,\n",
+ " 'Walsall': 373,\n",
+ " 'Hardoi': 374,\n",
+ " 'Barakpur': 375,\n",
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+ " 'Awassa': 377,\n",
+ " 'Komsomolsk Na Amure': 378,\n",
+ " 'Orizaba': 379,\n",
+ " 'Cienfuegos': 380,\n",
+ " 'Joetsu': 381,\n",
+ " 'Joinville': 382,\n",
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+ " 'Helsinki': 390,\n",
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+ " 'Syktyvkar': 392,\n",
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+ " 'Montgomery': 400,\n",
+ " 'Huixquilucan': 401,\n",
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+ " 'Hrodna': 404,\n",
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+ " 'Bragança Paulista': 407,\n",
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+ " 'San Francisco De Macorís': 415,\n",
+ " 'Tieli': 416,\n",
+ " 'Mossoró': 417,\n",
+ " 'Cisarua': 418,\n",
+ " 'Gudalur': 419,\n",
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+ " 'Shantipur': 422,\n",
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+ " 'Pingxiang': 426,\n",
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+ " 'Cajamarca': 431,\n",
+ " 'Ciudad Valles': 432,\n",
+ " 'Amarillo': 433,\n",
+ " 'Pietermaritzburg': 434,\n",
+ " 'Ahmadpur East': 435,\n",
+ " 'Lafayette': 436,\n",
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+ " 'Paris': 438,\n",
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+ " 'Viransehir': 440,\n",
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+ " 'Fort Lauderdale': 444,\n",
+ " 'Perugia': 445,\n",
+ " 'Kirkuk': 446,\n",
+ " 'Southend On Sea': 447,\n",
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+ " 'Bandundu': 449,\n",
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+ " 'Timon': 451,\n",
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+ " 'Tilburg': 471,\n",
+ " 'Lucena': 472,\n",
+ " 'Duque De Caxias': 473,\n",
+ " 'Pimpri': 474,\n",
+ " 'East Los Angeles': 475,\n",
+ " 'Dortmund': 476,\n",
+ " 'Szeged': 477,\n",
+ " 'Bukan': 478,\n",
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+ " 'Bochum': 484,\n",
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+ " 'Numazu': 490,\n",
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+ " 'Lubumbashi': 498,\n",
+ " 'Kimberley': 499,\n",
+ " 'Delmas': 500,\n",
+ " 'Nevinnomyssk': 501,\n",
+ " 'Punto Fijo': 502,\n",
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+ " 'Eslamshahr': 504,\n",
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+ " 'Gardez': 547,\n",
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+ " 'Quetzaltenango': 549,\n",
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+ " 'Melbourne': 556,\n",
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+ " 'Mutare': 558,\n",
+ " 'Kota Kinabalu': 559,\n",
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+ " 'León': 2726,\n",
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+ " 'Bytom': 820,\n",
+ " 'Aalborg': 821,\n",
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+ " 'Shiraz': 851,\n",
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+ " 'Fayetteville': 853,\n",
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+ " 'Sandakan': 856,\n",
+ " 'Astrakhan': 857,\n",
+ " 'Kalemie': 858,\n",
+ " 'Newcastle Upon Tyne': 859,\n",
+ " 'Ngaoundéré': 860,\n",
+ " 'Guatemala City': 861,\n",
+ " 'Isesaki': 862,\n",
+ " 'Agra': 863,\n",
+ " 'Toamasina': 864,\n",
+ " 'Ichihara': 865,\n",
+ " 'Clearwater': 866,\n",
+ " 'Tubruq': 867,\n",
+ " 'Xiazhen': 868,\n",
+ " 'Sholapur': 869,\n",
+ " 'Fuenlabrada': 870,\n",
+ " 'Kisangani': 871,\n",
+ " 'Cagua': 872,\n",
+ " 'Bénin': 873,\n",
+ " 'Seremban': 874,\n",
+ " 'Mingshui': 875,\n",
+ " 'Tambaram': 876,\n",
+ " 'Verona': 877,\n",
+ " 'Wazirabad': 878,\n",
+ " 'Boa Vista': 879,\n",
+ " 'New Orleans': 880,\n",
+ " 'Saveh': 881,\n",
+ " 'Matola': 882,\n",
+ " 'Linxia': 883,\n",
+ " 'Fort Worth': 884,\n",
+ " 'Lasa': 886,\n",
+ " 'Kitwe': 887,\n",
+ " 'Qazvin': 888,\n",
+ " 'Thái Nguyên': 889,\n",
+ " 'Firozpur': 890,\n",
+ " 'Calamba': 891,\n",
+ " 'Jiazi': 892,\n",
+ " 'La Ceiba': 893,\n",
+ " 'Adelaide': 894,\n",
+ " 'Myingyan': 895,\n",
+ " 'Xiantao': 896,\n",
+ " 'Manzanillo': 3217,\n",
+ " 'Babol': 898,\n",
+ " 'Sadiqabad': 899,\n",
+ " 'Bhind': 900,\n",
+ " 'Caxias Do Sul': 901,\n",
+ " 'Kano': 902,\n",
+ " 'Skopje': 903,\n",
+ " 'Huambo': 904,\n",
+ " 'Montevideo': 905,\n",
+ " 'Yanan': 906,\n",
+ " 'Gainesville': 907,\n",
+ " 'Chigasaki': 908,\n",
+ " 'Dundee': 909,\n",
+ " 'Acapulco': 910,\n",
+ " 'Ayer Itam': 911,\n",
+ " 'Gent': 912,\n",
+ " 'Knoxville': 913,\n",
+ " 'Medellín': 914,\n",
+ " 'Silchar': 915,\n",
+ " 'Basildon': 916,\n",
+ " 'Ejido': 917,\n",
+ " 'Kirov': 918,\n",
+ " 'Cordoba': 919,\n",
+ " 'Tarragona': 920,\n",
+ " 'Itagüí': 921,\n",
+ " 'Zhuzhou': 922,\n",
+ " 'Rohtak': 923,\n",
+ " 'Moshi': 924,\n",
+ " 'Volzhskiy': 925,\n",
+ " 'Mirpur Khas': 926,\n",
+ " 'Pilibhit': 927,\n",
+ " 'Southampton': 928,\n",
+ " 'Ratisbon': 929,\n",
+ " 'Bohicon': 930,\n",
+ " 'Fujimi': 931,\n",
+ " 'Vryheid': 932,\n",
+ " 'Provo': 933,\n",
+ " 'Dadu': 934,\n",
+ " 'Nakhodka': 935,\n",
+ " 'Kursk': 936,\n",
+ " 'Zhukovskiy': 937,\n",
+ " 'Port Saint Lucie': 938,\n",
+ " 'Foggia': 939,\n",
+ " 'Naperville': 940,\n",
+ " 'Chitungwiza': 941,\n",
+ " 'Jiutepec': 942,\n",
+ " 'Soweto': 943,\n",
+ " 'Richmond': 944,\n",
+ " 'Valledupar': 945,\n",
+ " 'Seversk': 946,\n",
+ " 'Coventry': 947,\n",
+ " 'Mandalay': 948,\n",
+ " 'Binjai': 949,\n",
+ " 'Peoria': 950,\n",
+ " 'Mataram': 951,\n",
+ " 'Ramnicu Valcea': 952,\n",
+ " 'Reims': 953,\n",
+ " 'Tebingtinggi': 954,\n",
+ " 'Ecatepec': 955,\n",
+ " 'Ipatinga': 956,\n",
+ " 'Barquisimeto': 957,\n",
+ " 'Saarbrücken': 958,\n",
+ " 'Porbandar': 959,\n",
+ " 'Humen': 960,\n",
+ " 'Srikakulam': 961,\n",
+ " 'Changzhou': 962,\n",
+ " 'Kuala Lumpur': 963,\n",
+ " 'Sosnowiec': 964,\n",
+ " 'Orekhovo Zuevo': 965,\n",
+ " 'Adoni': 966,\n",
+ " 'San Luis': 967,\n",
+ " 'Butuan': 968,\n",
+ " 'Kohat': 969,\n",
+ " 'Zhaotong': 970,\n",
+ " 'Independence': 971,\n",
+ " 'Nezahualcóyotl': 972,\n",
+ " 'Banja Luka': 973,\n",
+ " 'Sultanpur': 974,\n",
+ " 'Almere': 975,\n",
+ " 'Mokolo': 976,\n",
+ " 'Maisuru': 977,\n",
+ " 'Pucallpa': 978,\n",
+ " 'Toyota': 979,\n",
+ " 'Formosa': 980,\n",
+ " 'Ulhasnagar': 981,\n",
+ " 'Mixco': 982,\n",
+ " 'Mannheim': 983,\n",
+ " 'Maykop': 984,\n",
+ " 'Oberhausen': 985,\n",
+ " 'Brazzaville': 986,\n",
+ " 'Canberra': 987,\n",
+ " 'Mercedes': 988,\n",
+ " 'Sitapur': 989,\n",
+ " 'Innsbruck': 990,\n",
+ " 'Stoke On Trent': 991,\n",
+ " 'Afyonkarahisar': 992,\n",
+ " 'Rengasdengklok': 993,\n",
+ " 'Bid': 994,\n",
+ " 'Nouakchott': 995,\n",
+ " 'Santo André': 996,\n",
+ " 'Kigoma': 997,\n",
+ " 'Rome': 998,\n",
+ " 'Sanmenxia': 999,\n",
+ " 'Sunggal': 1000,\n",
+ " 'Santa Teresa': 1001,\n",
+ " 'Breda': 1002,\n",
+ " 'Focsani': 1003,\n",
+ " ...}"
+ ]
+ },
+ "execution_count": 62,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "city_table_values=execute_sql_statement(\"select * from City_Table \",conn)\n",
+ "city_ids={}\n",
+ "for i in city_table_values:\n",
+ " city_ids[i[1]]=i[0]\n",
+ "city_ids\n",
+ " "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "3d6298b4",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 59,
+ "id": "fcd18ad9",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "create_table(conn,'''CREATE TABLE Temperature (PK INTEGER PRIMARY KEY , Date VARCHAR, Avg_Temperature VARCHAR, City_ID INTEGER,\n",
+ "FOREIGN KEY(City_ID) REFERENCES City_Table(City_Id))''')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 66,
+ "id": "e1a0d17e",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
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+ " ('1950-07-01', 16.699, 2889),\n",
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+ " ('1969-07-01', 21.038, 318),\n",
+ " ...]"
+ ]
+ },
+ "execution_count": 66,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "temp_table_values=[]\n",
+ "j=1\n",
+ "for i in result:\n",
+ " j=j+1\n",
+ " temp_table_values.append((i[0],i[1],city_ids[i[3]]))\n",
+ "#temp_table_values"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 67,
+ "id": "fb218911",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "<sqlite3.Cursor at 0x7fe940c30c70>"
+ ]
+ },
+ "execution_count": 67,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "cur.executemany(\"INSERT INTO Temperature ('Date','Avg_Temperature','City_ID') Values (?,?,?)\",temp_table_values)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 75,
+ "id": "8e34f625",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
+ " }\n",
+ "\n",
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+ " 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>PK</th>\n",
+ " <th>Date</th>\n",
+ " <th>Avg_Temperature</th>\n",
+ " <th>City_ID</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>0</th>\n",
+ " <td>1</td>\n",
+ " <td>1950-01-01</td>\n",
+ " <td>-0.712</td>\n",
+ " <td>2889</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1</th>\n",
+ " <td>2</td>\n",
+ " <td>1950-02-01</td>\n",
+ " <td>1.423</td>\n",
+ " <td>2889</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2</th>\n",
+ " <td>3</td>\n",
+ " <td>1950-03-01</td>\n",
+ " <td>4.166</td>\n",
+ " <td>2889</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3</th>\n",
+ " <td>4</td>\n",
+ " <td>1950-04-01</td>\n",
+ " <td>6.743</td>\n",
+ " <td>2889</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4</th>\n",
+ " <td>5</td>\n",
+ " <td>1950-05-01</td>\n",
+ " <td>12.714</td>\n",
+ " <td>2889</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>...</th>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2685145</th>\n",
+ " <td>2685146</td>\n",
+ " <td>2013-05-01</td>\n",
+ " <td>11.464</td>\n",
+ " <td>1714</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2685146</th>\n",
+ " <td>2685147</td>\n",
+ " <td>2013-06-01</td>\n",
+ " <td>15.043</td>\n",
+ " <td>1714</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2685147</th>\n",
+ " <td>2685148</td>\n",
+ " <td>2013-07-01</td>\n",
+ " <td>18.775</td>\n",
+ " <td>1714</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2685148</th>\n",
+ " <td>2685149</td>\n",
+ " <td>2013-08-01</td>\n",
+ " <td>18.025</td>\n",
+ " <td>1714</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2685149</th>\n",
+ " <td>2685150</td>\n",
+ " <td>2013-09-01</td>\n",
+ " <td>None</td>\n",
+ " <td>1714</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "<p>2685150 rows × 4 columns</p>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " PK Date Avg_Temperature City_ID\n",
+ "0 1 1950-01-01 -0.712 2889\n",
+ "1 2 1950-02-01 1.423 2889\n",
+ "2 3 1950-03-01 4.166 2889\n",
+ "3 4 1950-04-01 6.743 2889\n",
+ "4 5 1950-05-01 12.714 2889\n",
+ "... ... ... ... ...\n",
+ "2685145 2685146 2013-05-01 11.464 1714\n",
+ "2685146 2685147 2013-06-01 15.043 1714\n",
+ "2685147 2685148 2013-07-01 18.775 1714\n",
+ "2685148 2685149 2013-08-01 18.025 1714\n",
+ "2685149 2685150 2013-09-01 None 1714\n",
+ "\n",
+ "[2685150 rows x 4 columns]"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "df1=pd.read_sql_query(\"Select * from Temperature\", conn)\n",
+ "display(df1)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 76,
+ "id": "f08f8148",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "create_table(conn,'''CREATE TABLE Loc_Table (ID INTEGER PRIMARY KEY , City_ID INTEGER, LAT FLOAT,LONG FLOAT,\n",
+ "FOREIGN KEY(City_ID) REFERENCES City_Table(City_ID))''')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 98,
+ "id": "ee98ee19",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
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+ " (318, 40.99, 27.69),\n",
+ " (318, 40.99, 27.69),\n",
+ " (318, 40.99, 27.69),\n",
+ " (318, 40.99, 27.69),\n",
+ " (318, 40.99, 27.69),\n",
+ " (318, 40.99, 27.69),\n",
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+ " (318, 40.99, 27.69),\n",
+ " (318, 40.99, 27.69),\n",
+ " ...]"
+ ]
+ },
+ "execution_count": 98,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "#Lat= North is positive, South is negative\n",
+ "#Long= West is negative, East is positive\n",
+ "data_to_check_loc=result_data_for_loc_table\n",
+ "data_to_input_loc_table=[]\n",
+ "j=0\n",
+ "for i in data_to_check_loc:\n",
+ " t=[0,0,0]\n",
+ " if i[1][-1]=='N':\n",
+ " t[1]=(float(i[1][:-1]))\n",
+ " if i[1][-1]=='S':\n",
+ " t[1]=float(i[1][:-1])*(-1)\n",
+ " if i[2][-1]=='E':\n",
+ " t[2]=float(i[2][:-1]) \n",
+ " if i[2][-1]=='W':\n",
+ " t[2]=float(i[2][:-1])*(-1)\n",
+ " t[0]=i[0]\n",
+ " tuple1=(city_ids[t[0]],t[1],t[2])\n",
+ " data_to_input_loc_table.append(tuple1)\n",
+ "data_to_input_loc_table"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 99,
+ "id": "cc0fba0c",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "<sqlite3.Cursor at 0x7fe940c30c70>"
+ ]
+ },
+ "execution_count": 99,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "cur.executemany(\"INSERT INTO Loc_Table ('City_ID','LAT','LONG') Values (?,?,?)\",data_to_input_loc_table)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 102,
+ "id": "aead2755",
+ "metadata": {},
+ "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>ID</th>\n",
+ " <th>City_ID</th>\n",
+ " <th>LAT</th>\n",
+ " <th>LONG</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>0</th>\n",
+ " <td>1</td>\n",
+ " <td>2889</td>\n",
+ " <td>57.05</td>\n",
+ " <td>10.33</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1</th>\n",
+ " <td>2</td>\n",
+ " <td>2889</td>\n",
+ " <td>57.05</td>\n",
+ " <td>10.33</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2</th>\n",
+ " <td>3</td>\n",
+ " <td>2889</td>\n",
+ " <td>57.05</td>\n",
+ " <td>10.33</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3</th>\n",
+ " <td>4</td>\n",
+ " <td>2889</td>\n",
+ " <td>57.05</td>\n",
+ " <td>10.33</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4</th>\n",
+ " <td>5</td>\n",
+ " <td>2889</td>\n",
+ " <td>57.05</td>\n",
+ " <td>10.33</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>...</th>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " <td>...</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2685145</th>\n",
+ " <td>2685146</td>\n",
+ " <td>1714</td>\n",
+ " <td>52.24</td>\n",
+ " <td>5.26</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2685146</th>\n",
+ " <td>2685147</td>\n",
+ " <td>1714</td>\n",
+ " <td>52.24</td>\n",
+ " <td>5.26</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2685147</th>\n",
+ " <td>2685148</td>\n",
+ " <td>1714</td>\n",
+ " <td>52.24</td>\n",
+ " <td>5.26</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2685148</th>\n",
+ " <td>2685149</td>\n",
+ " <td>1714</td>\n",
+ " <td>52.24</td>\n",
+ " <td>5.26</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2685149</th>\n",
+ " <td>2685150</td>\n",
+ " <td>1714</td>\n",
+ " <td>52.24</td>\n",
+ " <td>5.26</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "<p>2685150 rows × 4 columns</p>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " ID City_ID LAT LONG\n",
+ "0 1 2889 57.05 10.33\n",
+ "1 2 2889 57.05 10.33\n",
+ "2 3 2889 57.05 10.33\n",
+ "3 4 2889 57.05 10.33\n",
+ "4 5 2889 57.05 10.33\n",
+ "... ... ... ... ...\n",
+ "2685145 2685146 1714 52.24 5.26\n",
+ "2685146 2685147 1714 52.24 5.26\n",
+ "2685147 2685148 1714 52.24 5.26\n",
+ "2685148 2685149 1714 52.24 5.26\n",
+ "2685149 2685150 1714 52.24 5.26\n",
+ "\n",
+ "[2685150 rows x 4 columns]"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "df1=pd.read_sql_query(\"Select * from Loc_Table \", conn)\n",
+ "display(df1)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "f67e8d5b",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "df1=pd.read_sql_query(\"select * from Loc_Table join Temperature on Loc_Table.City_ID=Temperature.City_ID join city_table on city_table.city_id=Temperature.City_ID join country_table on country_table.pk=city_table.country_id group by Date LIMIT 10\", conn)\n",
+ "display(df1)\n",
+ "#(\"select * from Loc_Table join Temperature on Loc_Table.City_ID=Temperature.City_ID join city_table on city_table.city_id=Temperature.City_ID join country_table on country_table.pk=city_table.country_id LIMIT 10\",conn)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "3fd0999a",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "city_index=execute_sql_statement(\"Select * from \"Select * from City_Table\"\", conn)\n",
+ "city_indexes={}\n",
+ "for i in abc:\n",
+ " abc1[i[1]]=i[0]"
+ ]
+ }
+ ],
+ "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": "3.8.8"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/database_files/pythonproject.db b/database_files/pythonproject.db
new file mode 100644
index 0000000..c72c425
--- /dev/null
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+size 155222016
generated by cgit v1.2.3 (git 2.25.1) at 2026-06-06 05:57:33 +0000