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@ananya868
Created July 27, 2021 08:18
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "065aeaee",
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd \n",
"import numpy as np"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "700eefc2",
"metadata": {},
"outputs": [],
"source": [
"df = pd.DataFrame()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "3c79dbd4",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Empty DataFrame\n",
"Columns: []\n",
"Index: []\n"
]
}
],
"source": [
"print(df)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "e94040c0",
"metadata": {},
"outputs": [],
"source": [
"df1 = pd.DataFrame([[1,2,3,4],[5,6,7,8],[2,7,8,45],[3,6,8,9],[42,65,8,6]])"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "453f2d1e",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>0</th>\n",
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" <th>2</th>\n",
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" <th>0</th>\n",
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" <td>5</td>\n",
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" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2</td>\n",
" <td>7</td>\n",
" <td>8</td>\n",
" <td>45</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" 0 1 2 3\n",
"0 1 2 3 4\n",
"1 5 6 7 8\n",
"2 2 7 8 45"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df1.head(3)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "2f7107ad",
"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",
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" <th>2</th>\n",
" <td>2</td>\n",
" <td>7</td>\n",
" <td>8</td>\n",
" <td>45</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>3</td>\n",
" <td>6</td>\n",
" <td>8</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>42</td>\n",
" <td>65</td>\n",
" <td>8</td>\n",
" <td>6</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" 0 1 2 3\n",
"1 5 6 7 8\n",
"2 2 7 8 45\n",
"3 3 6 8 9\n",
"4 42 65 8 6"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df1.tail(4)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7666d6ea",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"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": "3.9.1"
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"nbformat_minor": 5
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