2809 lines
65 KiB
Plaintext
2809 lines
65 KiB
Plaintext
{
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"cells": [
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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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"## [pandas](https://pandas.pydata.org/)\n",
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"\n",
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"- A pandas egy NumPy-ra épülő adatfeldolgozó és elemző eszköz. Alapötleteit az R nyelvből vette.\n",
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"- Alapvető adattípusa a DataFrame (tábla) és a Series (oszlop). Segítségükkel memóriabeli, oszlopalapú adatbázis kezelés valósítható meg.\n",
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"- https://pandas.pydata.org/docs/user_guide/10min.html."
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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": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"# A pandas modul importálása pd néven.\n",
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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": 2,
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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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"'1.5.3'"
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]
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},
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"execution_count": 2,
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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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"# A pandas verziószáma.\n",
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"pd.__version__"
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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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"# DataFrame létrehozása oszlopokból.\n",
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"# A bemenet egy szótár, ahol a kulcsok az oszlopnevek, az értékek az oszlopok.\n",
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"df1 = pd.DataFrame({'aa': [1, 2, 3], 'bb': ['x', 'y', 'z']})"
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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>aa</th>\n",
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" <th>bb</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>1</td>\n",
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" <td>x</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>2</td>\n",
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" <td>y</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>3</td>\n",
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" <td>z</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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" aa bb\n",
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"0 1 x\n",
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"1 2 y\n",
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"2 3 z"
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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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"df1"
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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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"pandas.core.frame.DataFrame"
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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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"# Az eredmény típusa.\n",
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"type(df1)"
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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": 6,
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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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"Index(['aa', 'bb'], dtype='object')"
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]
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},
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"execution_count": 6,
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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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"# Oszlopnevek.\n",
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"df1.columns"
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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": 7,
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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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"aa\n",
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"bb\n"
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]
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}
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],
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"source": [
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"# Iterálás az oszlopneveken.\n",
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"for c in df1:\n",
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" print(c)"
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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": 8,
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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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"3"
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]
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},
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"execution_count": 8,
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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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"# Sorok száma.\n",
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"len(df1)"
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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": 9,
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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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"(3, 2)"
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]
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},
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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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],
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"source": [
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"# A DataFrame alakja.\n",
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"df1.shape"
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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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"scrolled": true
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},
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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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"<class 'pandas.core.frame.DataFrame'>\n",
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"RangeIndex: 3 entries, 0 to 2\n",
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"Data columns (total 2 columns):\n",
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" # Column Non-Null Count Dtype \n",
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"--- ------ -------------- ----- \n",
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" 0 aa 3 non-null int64 \n",
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" 1 bb 3 non-null object\n",
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"dtypes: int64(1), object(1)\n",
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"memory usage: 180.0+ bytes\n"
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]
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}
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],
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"source": [
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"# Összesítő információ.\n",
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"df1.info()"
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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/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>aa</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>count</th>\n",
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" <td>3.0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>mean</th>\n",
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" <td>2.0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>std</th>\n",
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" <td>1.0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>min</th>\n",
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" <td>1.0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>25%</th>\n",
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" <td>1.5</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>50%</th>\n",
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" <td>2.0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>75%</th>\n",
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" <td>2.5</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>max</th>\n",
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" <td>3.0</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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" aa\n",
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"count 3.0\n",
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"mean 2.0\n",
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"std 1.0\n",
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"min 1.0\n",
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"25% 1.5\n",
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"50% 2.0\n",
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"75% 2.5\n",
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"max 3.0"
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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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"# Alapvető oszlopstatisztikák (a numerikus oszlopokról).\n",
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"df1.describe()"
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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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"source": [
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"# DataFrame létrehozása sorokból.\n",
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"# A bemenet szótárak listája, ahol minden szótár egy sort reprezentál.\n",
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"data = [\n",
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" {'alma': 10, 'körte': 20},\n",
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" {'alma': 30},\n",
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" {'alma': 40, 'körte': 50}\n",
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"]\n",
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"df2 = pd.DataFrame(data)"
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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/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>alma</th>\n",
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" <th>körte</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>10</td>\n",
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" <td>20.0</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>30</td>\n",
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" <td>NaN</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>40</td>\n",
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" <td>50.0</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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" alma körte\n",
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"0 10 20.0\n",
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"1 30 NaN\n",
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"2 40 50.0"
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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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"df2"
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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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"- A pandas a hiányzó adatokat NaN (\"not a number\") értékkel reprezentálja.\n",
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"- Ez hatékony, de vannak veszélyei."
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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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"False"
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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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"import numpy as np\n",
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"np.nan == np.nan"
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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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"RangeIndex(start=0, stop=3, step=1)"
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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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"# Minden DataFrame-hez (és Series-hez) tartozik index.\n",
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"# Alapértelmezés szerint az index 0-tól induló, 1-esével növekedő sorszám.\n",
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"df2.index"
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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": 16,
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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>alma</th>\n",
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" <th>körte</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>x</th>\n",
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" <td>10</td>\n",
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" <td>20.0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>y</th>\n",
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" <td>30</td>\n",
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" <td>NaN</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>z</th>\n",
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" <td>40</td>\n",
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" <td>50.0</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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" alma körte\n",
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"x 10 20.0\n",
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"y 30 NaN\n",
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"z 40 50.0"
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]
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},
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"execution_count": 16,
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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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"# Másfajta indexet is használhatunk.\n",
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"df3 = pd.DataFrame(data, ['x', 'y', 'z'])\n",
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"df3"
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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": 17,
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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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"Index(['x', 'y', 'z'], dtype='object')"
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]
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},
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"execution_count": 17,
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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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"df3.index"
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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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"0 20\n",
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"1 30\n",
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"2 40\n",
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"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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"source": [
|
|
"# Series létrehozása index megadása nélkül.\n",
|
|
"se1 = pd.Series([20, 30, 40])\n",
|
|
"se1"
|
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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": 19,
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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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"pandas.core.series.Series"
|
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]
|
|
},
|
|
"execution_count": 19,
|
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"metadata": {},
|
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"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Az eredmény típusa.\n",
|
|
"type(se1)"
|
|
]
|
|
},
|
|
{
|
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"cell_type": "code",
|
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"execution_count": 20,
|
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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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"dtype('int64')"
|
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]
|
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},
|
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"execution_count": 20,
|
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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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"se1.dtype"
|
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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": 21,
|
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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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"aa 20\n",
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"bb 30\n",
|
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"cc 40\n",
|
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"dtype: int64"
|
|
]
|
|
},
|
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"execution_count": 21,
|
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"metadata": {},
|
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"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Series létrehozása index megadásával.\n",
|
|
"se2 = pd.Series([20, 30, 40], ['aa', 'bb', 'cc'])\n",
|
|
"se2"
|
|
]
|
|
},
|
|
{
|
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"cell_type": "code",
|
|
"execution_count": 22,
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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",
|
|
"</style>\n",
|
|
"<table border=\"1\" class=\"dataframe\">\n",
|
|
" <thead>\n",
|
|
" <tr style=\"text-align: right;\">\n",
|
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" <th></th>\n",
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" <th>aa</th>\n",
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" <th>bb</th>\n",
|
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" </tr>\n",
|
|
" </thead>\n",
|
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" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>0</th>\n",
|
|
" <td>1</td>\n",
|
|
" <td>x</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>2</td>\n",
|
|
" <td>y</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>3</td>\n",
|
|
" <td>z</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"</div>"
|
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],
|
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"text/plain": [
|
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" aa bb\n",
|
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"0 1 x\n",
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"1 2 y\n",
|
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"2 3 z"
|
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]
|
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},
|
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"execution_count": 22,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# DataFrame-ből [] operátorral lehet kiválasztani oszlopot.\n",
|
|
"df1"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 23,
|
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"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
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"text/plain": [
|
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"0 1\n",
|
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"1 2\n",
|
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"2 3\n",
|
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"Name: aa, dtype: int64"
|
|
]
|
|
},
|
|
"execution_count": 23,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"df1['aa']"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 24,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"pandas.core.series.Series"
|
|
]
|
|
},
|
|
"execution_count": 24,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"type(df1['aa'])"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 25,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"0 1\n",
|
|
"1 2\n",
|
|
"2 3\n",
|
|
"Name: aa, dtype: int64"
|
|
]
|
|
},
|
|
"execution_count": 25,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# ...illetve ha az oszlop neve érvényes azonosítónév, akkor . operátorral is.\n",
|
|
"df1.aa"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 26,
|
|
"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>bb</th>\n",
|
|
" <th>aa</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>0</th>\n",
|
|
" <td>x</td>\n",
|
|
" <td>1</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>y</td>\n",
|
|
" <td>2</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>z</td>\n",
|
|
" <td>3</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"</div>"
|
|
],
|
|
"text/plain": [
|
|
" bb aa\n",
|
|
"0 x 1\n",
|
|
"1 y 2\n",
|
|
"2 z 3"
|
|
]
|
|
},
|
|
"execution_count": 26,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Több oszlop kiválasztása.\n",
|
|
"df1[['bb', 'aa']]"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 27,
|
|
"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>bb</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>0</th>\n",
|
|
" <td>x</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>y</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>z</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"</div>"
|
|
],
|
|
"text/plain": [
|
|
" bb\n",
|
|
"0 x\n",
|
|
"1 y\n",
|
|
"2 z"
|
|
]
|
|
},
|
|
"execution_count": 27,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Ha 1 elemű listával indexelünk, akkor az eredmény DataFrame típusú.\n",
|
|
"df1[['bb']]"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 28,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"pandas.core.frame.DataFrame"
|
|
]
|
|
},
|
|
"execution_count": 28,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"type(df1[['bb']])"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"Megjegyzés\n",
|
|
"- Az 1 oszlopos DataFrame nem ugyanaz, mint a Series!"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 29,
|
|
"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>alma</th>\n",
|
|
" <th>körte</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>x</th>\n",
|
|
" <td>10</td>\n",
|
|
" <td>20.0</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>y</th>\n",
|
|
" <td>30</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>z</th>\n",
|
|
" <td>40</td>\n",
|
|
" <td>50.0</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"</div>"
|
|
],
|
|
"text/plain": [
|
|
" alma körte\n",
|
|
"x 10 20.0\n",
|
|
"y 30 NaN\n",
|
|
"z 40 50.0"
|
|
]
|
|
},
|
|
"execution_count": 29,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Sor(ok) kiválasztása DataFrame-ből.\n",
|
|
"df3"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 30,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"alma 10.0\n",
|
|
"körte 20.0\n",
|
|
"Name: x, dtype: float64"
|
|
]
|
|
},
|
|
"execution_count": 30,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Egy sor kiválasztása.\n",
|
|
"df3.loc['x']"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 31,
|
|
"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>alma</th>\n",
|
|
" <th>körte</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>x</th>\n",
|
|
" <td>10</td>\n",
|
|
" <td>20.0</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>z</th>\n",
|
|
" <td>40</td>\n",
|
|
" <td>50.0</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"</div>"
|
|
],
|
|
"text/plain": [
|
|
" alma körte\n",
|
|
"x 10 20.0\n",
|
|
"z 40 50.0"
|
|
]
|
|
},
|
|
"execution_count": 31,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Több sor kiválasztása.\n",
|
|
"df3.loc[['x', 'z']]"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 32,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"alma 10.0\n",
|
|
"körte 20.0\n",
|
|
"Name: x, dtype: float64"
|
|
]
|
|
},
|
|
"execution_count": 32,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# ...pozíció alapján is lehet sort kiválasztani.\n",
|
|
"df3.iloc[0]"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 33,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/html": [
|
|
"<div>\n",
|
|
"<style scoped>\n",
|
|
" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
|
|
" }\n",
|
|
"\n",
|
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" .dataframe tbody tr th {\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>alma</th>\n",
|
|
" <th>körte</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>x</th>\n",
|
|
" <td>10</td>\n",
|
|
" <td>20.0</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>y</th>\n",
|
|
" <td>30</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"</div>"
|
|
],
|
|
"text/plain": [
|
|
" alma körte\n",
|
|
"x 10 20.0\n",
|
|
"y 30 NaN"
|
|
]
|
|
},
|
|
"execution_count": 33,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# ...első néhány elem kiválasztása.\n",
|
|
"df3[:2]"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 34,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"aa 20\n",
|
|
"bb 30\n",
|
|
"cc 40\n",
|
|
"dtype: int64"
|
|
]
|
|
},
|
|
"execution_count": 34,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# A se2 tartalma (mert ezt fogjuk használni az alábbi néhány példában).\n",
|
|
"se2"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 35,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"30"
|
|
]
|
|
},
|
|
"execution_count": 35,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Egy elem kiválasztása Series-ből.\n",
|
|
"se2['bb']"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 36,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"cc 40\n",
|
|
"bb 30\n",
|
|
"dtype: int64"
|
|
]
|
|
},
|
|
"execution_count": 36,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Több elem kiválasztása Series-ből.\n",
|
|
"se2[['cc', 'bb']]"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 37,
|
|
"metadata": {
|
|
"scrolled": true
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"array([20, 30, 40], dtype=int64)"
|
|
]
|
|
},
|
|
"execution_count": 37,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Nyers adattartalom kinyerése Series-ből.\n",
|
|
"se2.values"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 38,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"numpy.ndarray"
|
|
]
|
|
},
|
|
"execution_count": 38,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# ...és annak típusa.\n",
|
|
"type(se2.values)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 39,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"array([[10., 20.],\n",
|
|
" [30., nan],\n",
|
|
" [40., 50.]])"
|
|
]
|
|
},
|
|
"execution_count": 39,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Nyers adattartalom kinyerése DataFrame-ből.\n",
|
|
"df2.values"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"### [Kiválasztás](https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html) (SELECT)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 40,
|
|
"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>tanuló</th>\n",
|
|
" <th>tantárgy</th>\n",
|
|
" <th>osztályzat</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>0</th>\n",
|
|
" <td>Gipsz Jakab</td>\n",
|
|
" <td>Matematika</td>\n",
|
|
" <td>5</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>Gipsz Jakab</td>\n",
|
|
" <td>Testnevelés</td>\n",
|
|
" <td>2</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>Bank Aranka</td>\n",
|
|
" <td>Matematika</td>\n",
|
|
" <td>3</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>3</th>\n",
|
|
" <td>Bank Aranka</td>\n",
|
|
" <td>Matematika</td>\n",
|
|
" <td>5</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>4</th>\n",
|
|
" <td>Bank Aranka</td>\n",
|
|
" <td>Testnevelés</td>\n",
|
|
" <td>4</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>5</th>\n",
|
|
" <td>Rontó Róbert</td>\n",
|
|
" <td>Matematika</td>\n",
|
|
" <td>1</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>6</th>\n",
|
|
" <td>Rontó Róbert</td>\n",
|
|
" <td>Matematika</td>\n",
|
|
" <td>2</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>7</th>\n",
|
|
" <td>Rontó Róbert</td>\n",
|
|
" <td>Testnevelés</td>\n",
|
|
" <td>5</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"</div>"
|
|
],
|
|
"text/plain": [
|
|
" tanuló tantárgy osztályzat\n",
|
|
"0 Gipsz Jakab Matematika 5\n",
|
|
"1 Gipsz Jakab Testnevelés 2\n",
|
|
"2 Bank Aranka Matematika 3\n",
|
|
"3 Bank Aranka Matematika 5\n",
|
|
"4 Bank Aranka Testnevelés 4\n",
|
|
"5 Rontó Róbert Matematika 1\n",
|
|
"6 Rontó Róbert Matematika 2\n",
|
|
"7 Rontó Róbert Testnevelés 5"
|
|
]
|
|
},
|
|
"execution_count": 40,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Hozzunk létre egy példa DataFrame-et!\n",
|
|
"df = pd.DataFrame([\n",
|
|
" {'tanuló': 'Gipsz Jakab', 'tantárgy': 'Matematika', 'osztályzat': 5},\n",
|
|
" {'tanuló': 'Gipsz Jakab', 'tantárgy': 'Testnevelés', 'osztályzat': 2},\n",
|
|
" {'tanuló': 'Bank Aranka', 'tantárgy': 'Matematika', 'osztályzat': 3},\n",
|
|
" {'tanuló': 'Bank Aranka', 'tantárgy': 'Matematika', 'osztályzat': 5},\n",
|
|
" {'tanuló': 'Bank Aranka', 'tantárgy': 'Testnevelés', 'osztályzat': 4},\n",
|
|
" {'tanuló': 'Rontó Róbert', 'tantárgy': 'Matematika', 'osztályzat': 1},\n",
|
|
" {'tanuló': 'Rontó Róbert', 'tantárgy': 'Matematika', 'osztályzat': 2},\n",
|
|
" {'tanuló': 'Rontó Róbert', 'tantárgy': 'Testnevelés', 'osztályzat': 5},\n",
|
|
"])\n",
|
|
"df"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 41,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"0 True\n",
|
|
"1 True\n",
|
|
"2 False\n",
|
|
"3 False\n",
|
|
"4 False\n",
|
|
"5 False\n",
|
|
"6 False\n",
|
|
"7 False\n",
|
|
"Name: tanuló, dtype: bool"
|
|
]
|
|
},
|
|
"execution_count": 41,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Logikai feltétel oszlop.\n",
|
|
"df['tanuló'] == 'Gipsz Jakab'"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 42,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"pandas.core.series.Series"
|
|
]
|
|
},
|
|
"execution_count": 42,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# ...aminek a típusa:\n",
|
|
"type(df['tanuló'] == 'Gipsz Jakab')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 43,
|
|
"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>tanuló</th>\n",
|
|
" <th>tantárgy</th>\n",
|
|
" <th>osztályzat</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>0</th>\n",
|
|
" <td>Gipsz Jakab</td>\n",
|
|
" <td>Matematika</td>\n",
|
|
" <td>5</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>Gipsz Jakab</td>\n",
|
|
" <td>Testnevelés</td>\n",
|
|
" <td>2</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"</div>"
|
|
],
|
|
"text/plain": [
|
|
" tanuló tantárgy osztályzat\n",
|
|
"0 Gipsz Jakab Matematika 5\n",
|
|
"1 Gipsz Jakab Testnevelés 2"
|
|
]
|
|
},
|
|
"execution_count": 43,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Gipsz Jakab összes osztályzata.\n",
|
|
"df[df['tanuló'] == 'Gipsz Jakab']\n",
|
|
"# SQL-ben: SELECT * FROM df WHERE tanuló='Gipsz Jakab'"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"### Műveletek\n",
|
|
"A logikai értékű Series adatok műveletei: & (és), | (vagy), ~ (tagadás)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 44,
|
|
"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>tanuló</th>\n",
|
|
" <th>tantárgy</th>\n",
|
|
" <th>osztályzat</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>Gipsz Jakab</td>\n",
|
|
" <td>Testnevelés</td>\n",
|
|
" <td>2</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>Bank Aranka</td>\n",
|
|
" <td>Matematika</td>\n",
|
|
" <td>3</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>4</th>\n",
|
|
" <td>Bank Aranka</td>\n",
|
|
" <td>Testnevelés</td>\n",
|
|
" <td>4</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>6</th>\n",
|
|
" <td>Rontó Róbert</td>\n",
|
|
" <td>Matematika</td>\n",
|
|
" <td>2</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"</div>"
|
|
],
|
|
"text/plain": [
|
|
" tanuló tantárgy osztályzat\n",
|
|
"1 Gipsz Jakab Testnevelés 2\n",
|
|
"2 Bank Aranka Matematika 3\n",
|
|
"4 Bank Aranka Testnevelés 4\n",
|
|
"6 Rontó Róbert Matematika 2"
|
|
]
|
|
},
|
|
"execution_count": 44,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Az 1-esnél jobb és 5-ösnél rosszabb osztályzatok (az és (&) művelettel).\n",
|
|
"df[(df['osztályzat'] > 1) & (df['osztályzat'] < 5)]"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 45,
|
|
"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>tanuló</th>\n",
|
|
" <th>tantárgy</th>\n",
|
|
" <th>osztályzat</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>Gipsz Jakab</td>\n",
|
|
" <td>Testnevelés</td>\n",
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" <td>2</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>Bank Aranka</td>\n",
|
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" <td>Matematika</td>\n",
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" <td>3</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>Bank Aranka</td>\n",
|
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" <td>Testnevelés</td>\n",
|
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" <td>4</td>\n",
|
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" </tr>\n",
|
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" <tr>\n",
|
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" <th>6</th>\n",
|
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" <td>Rontó Róbert</td>\n",
|
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" <td>Matematika</td>\n",
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" <td>2</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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" tanuló tantárgy osztályzat\n",
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"1 Gipsz Jakab Testnevelés 2\n",
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"2 Bank Aranka Matematika 3\n",
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"4 Bank Aranka Testnevelés 4\n",
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"6 Rontó Róbert Matematika 2"
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]
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},
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"execution_count": 45,
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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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"# ...mint előbb, a vagy (|) művelettel.\n",
|
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"df[(df['osztályzat'] == 2) | (df['osztályzat'] == 3) | (df['osztályzat'] == 4)]"
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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": 46,
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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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" vertical-align: middle;\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>tanuló</th>\n",
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" <th>tantárgy</th>\n",
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" <th>osztályzat</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>1</th>\n",
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" <td>Gipsz Jakab</td>\n",
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" <td>Testnevelés</td>\n",
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" <td>2</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>Bank Aranka</td>\n",
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" <td>Matematika</td>\n",
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" <td>3</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>Bank Aranka</td>\n",
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" <td>Testnevelés</td>\n",
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" <td>4</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>6</th>\n",
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" <td>Rontó Róbert</td>\n",
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" <td>Matematika</td>\n",
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" <td>2</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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" tanuló tantárgy osztályzat\n",
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"1 Gipsz Jakab Testnevelés 2\n",
|
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"2 Bank Aranka Matematika 3\n",
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"4 Bank Aranka Testnevelés 4\n",
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"6 Rontó Róbert Matematika 2"
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]
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},
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"execution_count": 46,
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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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"# ...mint előbb, a tagadás (~) művelettel.\n",
|
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"df[~((df['osztályzat'] == 1) | (df['osztályzat'] == 5))]"
|
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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": 47,
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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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"2.6666666666666665"
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]
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},
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"execution_count": 47,
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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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"# Rontó Róbert osztályzatainak átlaga.\n",
|
|
"df[df['tanuló'] == 'Rontó Róbert']['osztályzat'].mean()"
|
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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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"### [Csoportosítás](https://pandas.pydata.org/pandas-docs/stable/user_guide/groupby.html) (GROUPBY)\n",
|
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"\n",
|
|
"Pandas-ban a csoportosítás folyamata az alábbi lépésekből áll:\n",
|
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"\n",
|
|
"- Az adatok **felosztása (split)** csoportokra, valamilyen feltétel alapján.\n",
|
|
"- Valamely **függvény alkalmazása (apply)** az egyes csoportokra külön-külön.\n",
|
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"- Az eredmények **kombinálása (combine)** egy adatszerkezetbe.\n",
|
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"\n",
|
|
"Ezek közül a felosztás a legegyszerűbb. A felosztás kritériuma általában egy oszlopban (vagy oszlop kombinációban) található érték. A függvényalkalmazás lehet aggregáló jellegű (pl. csoportonkénti elemszám, összeg, átlag, minimum, maximum, első rekord, utolsó rekord) vagy egyéb (pl. csoportonkénti standardizálás, adathiány kitöltés vagy szűrés). A kombinálási lépés az aggregáló típusú függvények esetén automatikusan lefut, egyéb esetekben a programozónak kell kezdeményeznie."
|
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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": 48,
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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",
|
|
" <thead>\n",
|
|
" <tr style=\"text-align: right;\">\n",
|
|
" <th></th>\n",
|
|
" <th>tanuló</th>\n",
|
|
" <th>tantárgy</th>\n",
|
|
" <th>osztályzat</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>0</th>\n",
|
|
" <td>Gipsz Jakab</td>\n",
|
|
" <td>Matematika</td>\n",
|
|
" <td>5</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>Gipsz Jakab</td>\n",
|
|
" <td>Testnevelés</td>\n",
|
|
" <td>2</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>Bank Aranka</td>\n",
|
|
" <td>Matematika</td>\n",
|
|
" <td>3</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>3</th>\n",
|
|
" <td>Bank Aranka</td>\n",
|
|
" <td>Matematika</td>\n",
|
|
" <td>5</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>4</th>\n",
|
|
" <td>Bank Aranka</td>\n",
|
|
" <td>Testnevelés</td>\n",
|
|
" <td>4</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>5</th>\n",
|
|
" <td>Rontó Róbert</td>\n",
|
|
" <td>Matematika</td>\n",
|
|
" <td>1</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>6</th>\n",
|
|
" <td>Rontó Róbert</td>\n",
|
|
" <td>Matematika</td>\n",
|
|
" <td>2</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>7</th>\n",
|
|
" <td>Rontó Róbert</td>\n",
|
|
" <td>Testnevelés</td>\n",
|
|
" <td>5</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"</div>"
|
|
],
|
|
"text/plain": [
|
|
" tanuló tantárgy osztályzat\n",
|
|
"0 Gipsz Jakab Matematika 5\n",
|
|
"1 Gipsz Jakab Testnevelés 2\n",
|
|
"2 Bank Aranka Matematika 3\n",
|
|
"3 Bank Aranka Matematika 5\n",
|
|
"4 Bank Aranka Testnevelés 4\n",
|
|
"5 Rontó Róbert Matematika 1\n",
|
|
"6 Rontó Róbert Matematika 2\n",
|
|
"7 Rontó Róbert Testnevelés 5"
|
|
]
|
|
},
|
|
"execution_count": 48,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Használjuk az előző DataFrame-et!\n",
|
|
"df"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 49,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# Csoportosítás tantárgyak szerint.\n",
|
|
"gb = df.groupby('tantárgy')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 50,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<pandas.core.groupby.generic.DataFrameGroupBy object at 0x000002B18F945750>"
|
|
]
|
|
},
|
|
"execution_count": 50,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Az eredmény típusa.\n",
|
|
"gb"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 51,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"tantárgy\n",
|
|
"Matematika 5\n",
|
|
"Testnevelés 3\n",
|
|
"dtype: int64"
|
|
]
|
|
},
|
|
"execution_count": 51,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Hány rekord tartozik az egyes tantárgyakhoz?\n",
|
|
"gb.size()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 52,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"tantárgy\n",
|
|
"Matematika 5\n",
|
|
"Testnevelés 3\n",
|
|
"dtype: int64"
|
|
]
|
|
},
|
|
"execution_count": 52,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Ugyanez, az átmeneti GroupBy objektum használata nélkül.\n",
|
|
"df.groupby('tantárgy').size()\n",
|
|
"# SQL-ben: SELECT tantárgy, COUNT(*) FROM df GROUP BY tantárgy"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 53,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"tantárgy\n",
|
|
"Matematika 3.200000\n",
|
|
"Testnevelés 3.666667\n",
|
|
"Name: osztályzat, dtype: float64"
|
|
]
|
|
},
|
|
"execution_count": 53,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Tantárgyankénti átlag.\n",
|
|
"df.groupby('tantárgy')['osztályzat'].mean()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 54,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"tantárgy\n",
|
|
"Matematika 3.200000\n",
|
|
"Testnevelés 3.666667\n",
|
|
"Name: osztályzat, dtype: float64"
|
|
]
|
|
},
|
|
"execution_count": 54,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# ...ugyanez csúnyábban:\n",
|
|
"df['osztályzat'].groupby(df['tantárgy']).mean()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 55,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"tanuló tantárgy \n",
|
|
"Bank Aranka Matematika 4.0\n",
|
|
" Testnevelés 4.0\n",
|
|
"Gipsz Jakab Matematika 5.0\n",
|
|
" Testnevelés 2.0\n",
|
|
"Rontó Róbert Matematika 1.5\n",
|
|
" Testnevelés 5.0\n",
|
|
"Name: osztályzat, dtype: float64"
|
|
]
|
|
},
|
|
"execution_count": 55,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Tantárgyankénti átlag minden tanulóhoz.\n",
|
|
"df.groupby(['tanuló', 'tantárgy'])['osztályzat'].mean()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 56,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"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",
|
|
" }\n",
|
|
"\n",
|
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" .dataframe tbody tr th {\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>tanuló</th>\n",
|
|
" <th>tantárgy</th>\n",
|
|
" <th>osztályzat</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>0</th>\n",
|
|
" <td>Bank Aranka</td>\n",
|
|
" <td>Matematika</td>\n",
|
|
" <td>4.0</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>Bank Aranka</td>\n",
|
|
" <td>Testnevelés</td>\n",
|
|
" <td>4.0</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>Gipsz Jakab</td>\n",
|
|
" <td>Matematika</td>\n",
|
|
" <td>5.0</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>3</th>\n",
|
|
" <td>Gipsz Jakab</td>\n",
|
|
" <td>Testnevelés</td>\n",
|
|
" <td>2.0</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>4</th>\n",
|
|
" <td>Rontó Róbert</td>\n",
|
|
" <td>Matematika</td>\n",
|
|
" <td>1.5</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>5</th>\n",
|
|
" <td>Rontó Róbert</td>\n",
|
|
" <td>Testnevelés</td>\n",
|
|
" <td>5.0</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"</div>"
|
|
],
|
|
"text/plain": [
|
|
" tanuló tantárgy osztályzat\n",
|
|
"0 Bank Aranka Matematika 4.0\n",
|
|
"1 Bank Aranka Testnevelés 4.0\n",
|
|
"2 Gipsz Jakab Matematika 5.0\n",
|
|
"3 Gipsz Jakab Testnevelés 2.0\n",
|
|
"4 Rontó Róbert Matematika 1.5\n",
|
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"5 Rontó Róbert Testnevelés 5.0"
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]
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},
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"execution_count": 56,
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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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"# Az index átalakítása két hagyományos oszloppá.\n",
|
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"df.groupby(['tanuló', 'tantárgy'])['osztályzat'].mean().reset_index()"
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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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"### Rendezés, minimum, maximum"
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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": 57,
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"metadata": {},
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"outputs": [
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"data": {
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" <thead>\n",
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" <th></th>\n",
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" <th>a</th>\n",
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" <th>b</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>10</td>\n",
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" <td>20</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>12</td>\n",
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" <td>29</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>8</td>\n",
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" <td>21</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>15</td>\n",
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" <td>19</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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" a b\n",
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"0 10 20\n",
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"1 12 29\n",
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"2 8 21\n",
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"3 15 19"
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]
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},
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"execution_count": 57,
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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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"# Példa tábla a rendezéshez.\n",
|
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"df4 = pd.DataFrame([\n",
|
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" {'a': 10, 'b': 20},\n",
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" {'a': 12, 'b': 29},\n",
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" {'a': 8, 'b': 21},\n",
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" {'a': 15, 'b': 19}\n",
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"])\n",
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"df4"
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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": 58,
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"metadata": {},
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"outputs": [
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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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" .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>a</th>\n",
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" <th>b</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>2</th>\n",
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" <td>8</td>\n",
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" <td>21</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>10</td>\n",
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" <td>20</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>12</td>\n",
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" <td>29</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>15</td>\n",
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" <td>19</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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" a b\n",
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"2 8 21\n",
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"0 10 20\n",
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"1 12 29\n",
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"3 15 19"
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]
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},
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"execution_count": 58,
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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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"# Rendezés 'a' szerint.\n",
|
|
"df4.sort_values('a')"
|
|
]
|
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},
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{
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"cell_type": "code",
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"execution_count": 59,
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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>a</th>\n",
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" <th>b</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>3</th>\n",
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" <td>15</td>\n",
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" <td>19</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>12</td>\n",
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" <td>29</td>\n",
|
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" </tr>\n",
|
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" <tr>\n",
|
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" <th>0</th>\n",
|
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" <td>10</td>\n",
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" <td>20</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>8</td>\n",
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" <td>21</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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" a b\n",
|
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"3 15 19\n",
|
|
"1 12 29\n",
|
|
"0 10 20\n",
|
|
"2 8 21"
|
|
]
|
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},
|
|
"execution_count": 59,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Rendezés csökkenő sorrendbe.\n",
|
|
"df4.sort_values('a', ascending=False)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 60,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
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"1 29\n",
|
|
"2 21\n",
|
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"0 20\n",
|
|
"Name: b, dtype: int64"
|
|
]
|
|
},
|
|
"execution_count": 60,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Egy oszlop elemeinek rendezése (a három legnagyobb elem meghatározásához).\n",
|
|
"df4['b'].sort_values(ascending=False)[:3]"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 61,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"29"
|
|
]
|
|
},
|
|
"execution_count": 61,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# A 'b' oszlop maximuma.\n",
|
|
"df4['b'].max()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 62,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"1"
|
|
]
|
|
},
|
|
"execution_count": 62,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Mely indexnél található a 'b' oszlop maximuma?\n",
|
|
"df4['b'].idxmax()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"### Módosítás"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 63,
|
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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",
|
|
" <thead>\n",
|
|
" <tr style=\"text-align: right;\">\n",
|
|
" <th></th>\n",
|
|
" <th>a</th>\n",
|
|
" <th>b</th>\n",
|
|
" <th>c</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>0</th>\n",
|
|
" <td>10</td>\n",
|
|
" <td>20</td>\n",
|
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" <td>30</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>12</td>\n",
|
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" <td>29</td>\n",
|
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" <td>41</td>\n",
|
|
" </tr>\n",
|
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" <tr>\n",
|
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" <th>2</th>\n",
|
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" <td>8</td>\n",
|
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" <td>21</td>\n",
|
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" <td>29</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>3</th>\n",
|
|
" <td>15</td>\n",
|
|
" <td>19</td>\n",
|
|
" <td>34</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"</div>"
|
|
],
|
|
"text/plain": [
|
|
" a b c\n",
|
|
"0 10 20 30\n",
|
|
"1 12 29 41\n",
|
|
"2 8 21 29\n",
|
|
"3 15 19 34"
|
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]
|
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},
|
|
"execution_count": 63,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Új oszlop felvétele.\n",
|
|
"df4['c'] = df4['a'] + df4['b']\n",
|
|
"df4"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 64,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"41"
|
|
]
|
|
},
|
|
"execution_count": 64,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Egy elem 'elérése'.\n",
|
|
"df4['c'][1]"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 65,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"41"
|
|
]
|
|
},
|
|
"execution_count": 65,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# ...ugyanez másképp:\n",
|
|
"df4.loc[1]['c']"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 66,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
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"41"
|
|
]
|
|
},
|
|
"execution_count": 66,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# ...ugyanez másképp:\n",
|
|
"df4.iloc[1]['c']"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 67,
|
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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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"<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>a</th>\n",
|
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" <th>b</th>\n",
|
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" <th>c</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>10</td>\n",
|
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" <td>20</td>\n",
|
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" <td>30</td>\n",
|
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" </tr>\n",
|
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" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>12</td>\n",
|
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" <td>29</td>\n",
|
|
" <td>100</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>8</td>\n",
|
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" <td>21</td>\n",
|
|
" <td>29</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>3</th>\n",
|
|
" <td>15</td>\n",
|
|
" <td>19</td>\n",
|
|
" <td>34</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
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"</div>"
|
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],
|
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"text/plain": [
|
|
" a b c\n",
|
|
"0 10 20 30\n",
|
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"1 12 29 100\n",
|
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"2 8 21 29\n",
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"3 15 19 34"
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]
|
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},
|
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"execution_count": 67,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Egy elem módosítása.\n",
|
|
"df4['c'][1] = 100\n",
|
|
"df4"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 68,
|
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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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" }\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>a</th>\n",
|
|
" <th>b</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>0</th>\n",
|
|
" <td>10</td>\n",
|
|
" <td>20</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>12</td>\n",
|
|
" <td>29</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>8</td>\n",
|
|
" <td>21</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>3</th>\n",
|
|
" <td>15</td>\n",
|
|
" <td>19</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"</div>"
|
|
],
|
|
"text/plain": [
|
|
" a b\n",
|
|
"0 10 20\n",
|
|
"1 12 29\n",
|
|
"2 8 21\n",
|
|
"3 15 19"
|
|
]
|
|
},
|
|
"execution_count": 68,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Oszlop törlése.\n",
|
|
"del df4['c']\n",
|
|
"df4"
|
|
]
|
|
}
|
|
],
|
|
"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": "3.11.3"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 2
|
|
}
|