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abhiramrabhiramr
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Added Books Ipython Notebook
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‎Notebooks/Books2018.ipynb

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"import pandas as pd"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"books = pd.read_csv(\"./data/books_2018.csv\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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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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"436"
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]
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},
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"execution_count": 5,
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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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"len(books)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"metadata": {},
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"outputs": [],
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"source": [
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"df2 = pd.DataFrame({'Title':books.Title.unique()})\n"
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]
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},
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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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{
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"data": {
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"text/plain": [
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"399"
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},
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"execution_count": 11,
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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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"len(df2)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 15,
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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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"Sapiens 4\n",
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"Shoe Dog 3\n",
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"1984 3\n",
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"The Rosie Project 3\n",
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"Ghachar Ghochar 3\n",
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"Ready Player One 3\n",
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"Leila 3\n",
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"A Thousand Splendid Suns 2\n",
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"Three Body Problem 2\n",
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"Children of Time 2\n",
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"Norwegian Wood 2\n",
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"Zero to One 2\n",
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"Neverwhere 2\n",
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"A Suitable Boy 2\n",
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"City of Djinns 2\n",
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"Deep Work 2\n",
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"Norse Mythology 2\n",
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"Sacred Games 2\n",
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"The Shadow Rising 2\n",
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"Man’s Search for Meaning 2\n",
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"Steve Jobs 2\n",
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"The Dresden Files 2\n",
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"Dogs of War 2\n",
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"The Great Indian Novel 2\n",
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"Ender’s Game 2\n",
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"The Game 2\n",
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"2001 A Space Odyssey 2\n",
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"The Martian 2\n",
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"Outliers 2\n",
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"The Audacity of Hope 1\n",
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" ..\n",
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"Selfish Gene - 1\n",
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"Timeline - 1\n",
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"The Taj Trilogy 1\n",
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"Eleanor Oliphant Is Completely Fine 1\n",
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"Midnight’s Children 1\n",
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"Faiz Ahmed Faiz Poems 1\n",
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"Colorless Tsukuru Tazaki and His Years of Pilgrimage 1\n",
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"Guards Guards 1\n",
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"The Dragon Reborn 1\n",
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"The Vegetarian 1\n",
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"Zen and the Art of Motorcycle Maintenance 1\n",
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"The Interpreter of Maladies 1\n",
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"Malgudi Days 1\n",
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"Skin in the game 1\n",
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"The ministry of utmost happiness 1\n",
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"The Illicit Happiness of Others 1\n",
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"WoT 1\n",
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"Sabriel 1\n",
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"Blood Sweat and Pixels 1\n",
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"The Demon hunt of Chottanikkara 1\n",
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"Red Rising 1\n",
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"Blind Willow Sleeping Woman 1\n",
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"Narcopolis 1\n",
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"Edge of Physics 1\n",
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"Thinking Fast 1\n",
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"Sandman 1\n",
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"Aristotle and Dante Discover The Secrets of the Universe 1\n",
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"Time Machine 1\n",
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"Gene 1\n",
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"Artemis 1\n",
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"Name: Title, Length: 399, dtype: int64"
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]
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},
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"execution_count": 15,
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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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"books['Title'].value_counts()\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 18,
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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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"Month\n",
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"1 60\n",
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"2 4\n",
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"4 15\n",
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"5 68\n",
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"6 84\n",
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"7 85\n",
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"8 30\n",
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"11 90\n",
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"Name: Sl No, dtype: int64"
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]
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},
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"execution_count": 18,
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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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"books.groupby(books.Month).count()['Sl No']"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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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": "3.5.2"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

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