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keshavsingh4522keshavsingh4522
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operation on dictionary
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‎Datacamp/IntermediatePython/Dict.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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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"{'a': 45, 'b': 66, 'c': 44}\n"
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]
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}
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],
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"source": [
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"d={'a':45,'b':66,'c':44}\n",
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"print(d)"
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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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"dict_keys(['a', 'b', 'c'])"
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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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"d.keys()"
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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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{
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"data": {
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"text/plain": [
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"dict_values([45, 66, 44])"
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]
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},
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"execution_count": 3,
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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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"d.values()"
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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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"## 2"
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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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"{'a': 45, 'b': 44, 'c': 44}"
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]
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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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"d={'a':45,'b':66,'c':44,'b':44}\n",
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"d"
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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": 12,
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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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"True"
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]
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},
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"execution_count": 12,
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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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"'b' in d"
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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": 13,
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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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"{'a': 45, 'b': 44, 'c': 123}"
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]
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},
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"execution_count": 13,
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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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"d['c']=123\n",
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"d"
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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": 14,
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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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"{'a': 45, 'c': 123}"
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]
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},
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"execution_count": 14,
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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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"del(d['b'])\n",
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"d"
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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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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"{'capital': 'paris', 'population': 66.03}\n",
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"{'spain': {'capital': 'madrid', 'population': 46.77}, 'france': {'capital': 'paris', 'population': 66.03}, 'germany': {'capital': 'berlin', 'population': 80.62}, 'norway': {'capital': 'oslo', 'population': 5.084}, 'italy': {'capital': 'rome', 'population': 59.83}}\n"
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]
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}
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],
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"source": [
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"# Dictionary of dictionaries\n",
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"europe = { 'spain': { 'capital':'madrid', 'population':46.77 },\n",
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" 'france': { 'capital':'paris', 'population':66.03 },\n",
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" 'germany': { 'capital':'berlin', 'population':80.62 },\n",
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" 'norway': { 'capital':'oslo', 'population':5.084 } }\n",
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"# Print out the capital of France\n",
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"print(europe['france'])\n",
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"# Create sub-dictionary data\n",
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"data={'capital':'rome','population':59.83}\n",
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"# Add data to europe under key 'italy'\n",
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"europe['italy']=data\n",
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"# Print europe\n",
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"print(europe)"
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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": 4,
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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>spain</th>\n",
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" <th>france</th>\n",
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" <th>germany</th>\n",
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" <th>norway</th>\n",
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" <th>italy</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>capital</th>\n",
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" <td>madrid</td>\n",
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" <td>paris</td>\n",
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" <td>berlin</td>\n",
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" <td>oslo</td>\n",
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" <td>rome</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>population</th>\n",
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" <td>46.77</td>\n",
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" <td>66.03</td>\n",
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" <td>80.62</td>\n",
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" <td>5.084</td>\n",
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" <td>59.83</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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" spain france germany norway italy\n",
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"capital madrid paris berlin oslo rome\n",
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"population 46.77 66.03 80.62 5.084 59.83"
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]
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},
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"execution_count": 4,
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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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"import pandas as pd\n",
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"d=pd.DataFrame(europe)\n",
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"d"
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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": "3.7.5"
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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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