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‎Notebooks/01_SQLite.ipynb

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"cur = conn.cursor()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### Querying the sqlite_master table for table names"
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]
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},
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{
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"cell_type": "code",
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"cell_type": "code",
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},
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"cell_type": "code",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"<sqlite3.Cursor at 0x7fe55c78aa40>"
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"<sqlite3.Cursor at 0x7fe1fa654180>"
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]
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},
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"execution_count": 11,
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"execution_count": 9,
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"metadata": {},
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"output_type": "execute_result"
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},
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"cell_type": "code",
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"metadata": {},
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{
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" print(row)"
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{
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"cell_type": "code",
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"execution_count": 11,
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"metadata": {},
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"outputs": [],
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"source": [
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"conn.commit()\n",
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"conn.close()"
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]
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},
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"cell_type": "markdown",
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"metadata": {},
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},
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"cell_type": "code",
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"execution_count": 12,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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" date trans symbol qty price\n",
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"0 2006-01-05 BUY RHAT 100.0 35.14\n"
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" date trans symbol qty price\n",
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"0 2006-01-05 BUY RHAT 100.0 35.14\n",
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"1 2006-03-28 BUY IBM 1000.0 45.00\n",
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"2 2006-04-06 SELL IBM 500.0 53.00\n",
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"3 2006-04-05 BUY MSFT 1000.0 72.00\n"
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]
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}
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],
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},
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"cell_type": "code",
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"metadata": {},
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"outputs": [],
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"source": [
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"source": [
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"### Accessing existing [Database](https://www.sqlitetutorial.net/sqlite-sample-database/):\n",
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"\n",
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"![Chinook Schema](../SampleDBs/sqlite-sample-database-color.jpg)"
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"![Chinook Schema](../Figs/sqlite-sample-database-color.jpg) \n",
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"[Source](https://www.sqlitetutorial.net/) "
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"! wget https://cdn.sqlitetutorial.net/wp-content/uploads/2018/03/chinook.zip\n",
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"! unzip chinook.zip\n",
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"! mv chinook.zip ../SampleDBs/chinook.sqlite\n",
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"! rm chinook.zip"
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"#### Retrieving original database"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"! wget https://cdn.sqlitetutorial.net/wp-content/uploads/2018/03/chinook.zip \n",
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"! unzip chinook.zip ../SampleDBs/chinook.sqlite \n",
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"! rm chinook.zip "
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]
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},
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"cell_type": "code",
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},
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"execution_count": 15,
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" print(c)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### Querying the sqlite_master table to examine the table structure"
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]
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},
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" print(c)"
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### Same with Pandas"
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]
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},
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>Name</th>\n",
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" <th>Title</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>A Cor Do Som</td>\n",
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" <td>None</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td>AC/DC</td>\n",
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" <td>For Those About To Rock We Salute You</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td>AC/DC</td>\n",
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" <td>Let There Be Rock</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td>Aaron Copland &amp; London Symphony Orchestra</td>\n",
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" <td>A Copland Celebration, Vol. I</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>4</th>\n",
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" <td>Aaron Goldberg</td>\n",
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" <td>Worlds</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" Name \\\n",
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"0 A Cor Do Som \n",
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"1 AC/DC \n",
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"2 AC/DC \n",
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"3 Aaron Copland & London Symphony Orchestra \n",
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"4 Aaron Goldberg \n",
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"\n",
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" Title \n",
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"0 None \n",
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"1 For Those About To Rock We Salute You \n",
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"2 Let There Be Rock \n",
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"3 A Copland Celebration, Vol. I \n",
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"4 Worlds "
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]
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},
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"execution_count": 31,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"#https://www.sqlitetutorial.net/"
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"df = pd.read_sql_query(query, conn)\n",
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"df.head()"
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.6"
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"version": "3.9.5"
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}
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"nbformat": 4,

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