{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Основы программирования в Python\n", "\n", "*Алла Тамбовцева, НИУ ВШЭ*\n", "\n", "\n", "## Библиотека pandas. Продолжение." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Группировка и агрегирование: методы `.groupby()` и `.agg()`" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Часто случается, что данные необходимо сгруппировать по какому-то признаку ‒ по значениям определенной переменной. На входе имеется таблица (датафрейм), а на выходе хочется получить несколько таблиц: отдельная таблица для каждого значения. Давайте рассмотрим такой пример. У нас есть база данных с результатами выборов, и нам нужно сгруппировать данные по регионам. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Для начала импортируем библиотеку pandas и загрузим файл с данными." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import pandas as pd" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Для разнообразия загрузим файл по ссылке с Github (база большая, загрузится не моментально):" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "df = pd.read_csv(\"https://raw.githubusercontent.com/allatambov/R-programming-3/master/lectures/lect7-12-01/47130-8314.csv\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "В таблице сохранены результаты выборов президента России 2012 года. " ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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linkuikkom1kom2kom3kom4kom5123...181920212223абвг
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" ], "text/plain": [ " link uik \\\n", "0 http://www.adygei.vybory.izbirkom.ru/region/ad... 1 \n", "1 http://www.adygei.vybory.izbirkom.ru/region/ad... 2 \n", "2 http://www.adygei.vybory.izbirkom.ru/region/ad... 3 \n", "3 http://www.adygei.vybory.izbirkom.ru/region/ad... 4 \n", "4 http://www.adygei.vybory.izbirkom.ru/region/ad... 5 \n", "\n", " kom1 kom2 kom3 kom4 kom5 1 2 \\\n", "0 Республика Адыгея (Адыгея) Адыгейская УИК №1 NaN NaN 2383.0 2147.0 \n", "1 Республика Адыгея (Адыгея) Адыгейская УИК №2 NaN NaN 2865.0 2586.0 \n", "2 Республика Адыгея (Адыгея) Адыгейская УИК №3 NaN NaN 2821.0 2558.0 \n", "3 Республика Адыгея (Адыгея) Адыгейская УИК №4 NaN NaN 2069.0 1868.0 \n", "4 Республика Адыгея (Адыгея) Адыгейская УИК №5 NaN NaN 777.0 705.0 \n", "\n", " 3 ... 18 19 20 21 22 23 а б в г \n", "0 0.0 ... 0.0 24.0 382.0 28.0 71.0 1066.0 NaN NaN NaN NaN \n", "1 0.0 ... 0.0 51.0 453.0 49.0 104.0 1174.0 NaN NaN NaN NaN \n", "2 0.0 ... 0.0 36.0 481.0 24.0 107.0 1025.0 NaN NaN NaN NaN \n", "3 0.0 ... 0.0 0.0 414.0 0.0 48.0 784.0 NaN NaN NaN NaN \n", "4 0.0 ... 0.0 19.0 138.0 4.0 7.0 286.0 NaN NaN NaN NaN \n", "\n", "[5 rows x 34 columns]" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.head()" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "RangeIndex: 90003 entries, 0 to 90002\n", "Data columns (total 34 columns):\n", "link 90003 non-null object\n", "uik 90003 non-null int64\n", "kom1 90003 non-null object\n", "kom2 90003 non-null object\n", "kom3 89618 non-null object\n", "kom4 0 non-null float64\n", "kom5 0 non-null float64\n", "1 89994 non-null float64\n", "2 89994 non-null float64\n", "3 89994 non-null float64\n", "4 89994 non-null float64\n", "5 89994 non-null float64\n", "6 89994 non-null float64\n", "7 89994 non-null float64\n", "8 89994 non-null float64\n", "9 89994 non-null float64\n", "10 89994 non-null float64\n", "11 89994 non-null float64\n", "12 89994 non-null float64\n", "13 89994 non-null float64\n", "14 89994 non-null float64\n", "15 89994 non-null float64\n", "16 89994 non-null float64\n", "17 89994 non-null float64\n", "18 89994 non-null float64\n", "19 89994 non-null float64\n", "20 89994 non-null float64\n", "21 89994 non-null float64\n", "22 89994 non-null float64\n", "23 89994 non-null float64\n", "а 0 non-null float64\n", "б 0 non-null float64\n", "в 0 non-null float64\n", "г 0 non-null float64\n", "dtypes: float64(29), int64(1), object(4)\n", "memory usage: 23.3+ MB\n" ] } ], "source": [ "df.info()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Таблица достаточно большая, поэтому давайте выберем те столбцы, которые понадобятся нам для работы. Какие именно? Столбцы в этой базе имеют порядковый номер строки в таблице на [сайте]() Центральной избирательной комиссии.\n", "\n", "Выберем столбцы, которые соответствуют уровням комиссий, а также следующим показателям: общее число зарегистрированных избирателей, число недействительных бюллетеней, число действительных бюллетеней, число голосов за Жириновского, Зюганова, Миронова, Прохорова и Путина." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "d = df[[\"kom1\", \"kom2\", \"kom3\", \"1\", \"9\", \"10\", \"19\", \"20\", \"21\", \"22\", \"23\"]]" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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kom1kom2kom319101920212223
0Республика Адыгея (Адыгея)АдыгейскаяУИК №12383.019.01571.024.0382.028.071.01066.0
1Республика Адыгея (Адыгея)АдыгейскаяУИК №22865.029.01831.051.0453.049.0104.01174.0
2Республика Адыгея (Адыгея)АдыгейскаяУИК №32821.031.01673.036.0481.024.0107.01025.0
3Республика Адыгея (Адыгея)АдыгейскаяУИК №42069.00.01246.00.0414.00.048.0784.0
4Республика Адыгея (Адыгея)АдыгейскаяУИК №5777.08.0454.019.0138.04.07.0286.0
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" ], "text/plain": [ " kom1 kom2 kom3 1 9 10 19 \\\n", "0 Республика Адыгея (Адыгея) Адыгейская УИК №1 2383.0 19.0 1571.0 24.0 \n", "1 Республика Адыгея (Адыгея) Адыгейская УИК №2 2865.0 29.0 1831.0 51.0 \n", "2 Республика Адыгея (Адыгея) Адыгейская УИК №3 2821.0 31.0 1673.0 36.0 \n", "3 Республика Адыгея (Адыгея) Адыгейская УИК №4 2069.0 0.0 1246.0 0.0 \n", "4 Республика Адыгея (Адыгея) Адыгейская УИК №5 777.0 8.0 454.0 19.0 \n", "\n", " 20 21 22 23 \n", "0 382.0 28.0 71.0 1066.0 \n", "1 453.0 49.0 104.0 1174.0 \n", "2 481.0 24.0 107.0 1025.0 \n", "3 414.0 0.0 48.0 784.0 \n", "4 138.0 4.0 7.0 286.0 " ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "d.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Теперь присвоим столбцам более информативные названия:" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "d.columns = [\"region\", \"tik\", \"uik\", \"total\", \"invalid\", \"valid\", \"Zh\", \"Zu\", \"Mi\", \"Pr\", \"Pu\"]" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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regiontikuiktotalinvalidvalidZhZuMiPrPu
0Республика Адыгея (Адыгея)АдыгейскаяУИК №12383.019.01571.024.0382.028.071.01066.0
1Республика Адыгея (Адыгея)АдыгейскаяУИК №22865.029.01831.051.0453.049.0104.01174.0
2Республика Адыгея (Адыгея)АдыгейскаяУИК №32821.031.01673.036.0481.024.0107.01025.0
3Республика Адыгея (Адыгея)АдыгейскаяУИК №42069.00.01246.00.0414.00.048.0784.0
4Республика Адыгея (Адыгея)АдыгейскаяУИК №5777.08.0454.019.0138.04.07.0286.0
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" ], "text/plain": [ " region tik uik total invalid valid \\\n", "0 Республика Адыгея (Адыгея) Адыгейская УИК №1 2383.0 19.0 1571.0 \n", "1 Республика Адыгея (Адыгея) Адыгейская УИК №2 2865.0 29.0 1831.0 \n", "2 Республика Адыгея (Адыгея) Адыгейская УИК №3 2821.0 31.0 1673.0 \n", "3 Республика Адыгея (Адыгея) Адыгейская УИК №4 2069.0 0.0 1246.0 \n", "4 Республика Адыгея (Адыгея) Адыгейская УИК №5 777.0 8.0 454.0 \n", "\n", " Zh Zu Mi Pr Pu \n", "0 24.0 382.0 28.0 71.0 1066.0 \n", "1 51.0 453.0 49.0 104.0 1174.0 \n", "2 36.0 481.0 24.0 107.0 1025.0 \n", "3 0.0 414.0 0.0 48.0 784.0 \n", "4 19.0 138.0 4.0 7.0 286.0 " ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "d.head() # опять посмотрим" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Посмотрим теперь, какие регионы есть в базе. Выбрать столбец *region* в таком случае будет не совсем удачно, поскольку в нем будет много повторяющихся значенийй. Посмотрим только на уникальные:" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array(['Республика Адыгея (Адыгея)', 'Республика Алтай',\n", " 'Республика Башкортостан', 'Республика Бурятия',\n", " 'Республика Дагестан', 'Ðåñïóáëèêà Äàãåñòàí',\n", " 'Республика Ингушетия', 'Кабардино-Балкарская Республика',\n", " 'Республика Калмыкия', 'Карачаево-Черкесская Республика',\n", " 'Республика Карелия', 'Республика Коми', 'Республика Марий Эл',\n", " 'Республика Мордовия', 'Республика Саха (Якутия)',\n", " 'Республика Северная Осетия - Алания', 'Республика Тыва',\n", " 'Удмуртская Республика', 'Республика Хакасия',\n", " 'Чувашская Республика - Чувашия', 'Алтайский край',\n", " 'Забайкальский край', 'Камчатский край', 'Краснодарский край',\n", " 'Красноярский край', 'Пермский край', 'Приморский край',\n", " 'Ставропольский край', 'Хабаровский край', 'Õàáàðîâñêèé êðàé',\n", " 'Амурская область', 'Архангельская область',\n", " 'Астраханская область', 'Белгородская область', 'Брянская область',\n", " 'Владимирская область', 'Волгоградская область',\n", " 'Вологодская область', 'Воронежская область', 'Ивановская область',\n", " 'Иркутская область', 'Калужская область', 'Кемеровская область',\n", " 'Кировская область', 'Костромская область', 'Курганская область',\n", " 'Курская область', 'Ленинградская область', 'Липецкая область',\n", " 'Магаданская область', 'Московская область', 'Мурманская область',\n", " 'Ìóðìàíñêàÿ îáëàñòü', 'Нижегородская область',\n", " 'Новгородская область', 'Новосибирская область', 'Омская область',\n", " 'Оренбургская область', 'Орловская область', 'Пензенская область',\n", " 'Псковская область', 'Ростовская область', 'Рязанская область',\n", " 'Самарская область', 'Саратовская область', 'Сахалинская область',\n", " 'Свердловская область', 'Смоленская область', 'Тамбовская область',\n", " 'Тверская область', 'Томская область', 'Тульская область',\n", " 'Тюменская область', 'Ульяновская область', 'Челябинская область',\n", " 'Город Москва', 'Город Санкт-Петербург', 'Ãîðîä Ñàíêò-Ïåòåðáóðã',\n", " 'Еврейская автономная область', 'Ненецкий автономный округ',\n", " 'Чукотский автономный округ', 'Ямало-Ненецкий автономный округ',\n", " 'Город Байконур (Республика Казахстан)',\n", " 'Территория за пределами РФ'], dtype=object)" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "d.region.unique() # метод unique - уникальные значения" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Видно, что в этом массиве встречаются какие-то крокозябры (названия со странной кодировкой). Давайте уберем эти строки из базы." ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "# отфильтруем с помощью условий\n", "d = d[(d.region != 'Ðåñïóáëèêà Äàãåñòàí') & \n", " (d.region != 'Õàáàðîâñêèé êðàé') & \n", " (d.region != 'Ìóðìàíñêàÿ îáëàñòü') & (d.region != 'Ãîðîä Ñàíêò-Ïåòåðáóðã')]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Сгруппируем данные по регионам и посчитаем для каждого региона явку в процентах и процент голосов за каждого кандидата. Группировка осуществляется с помощью метода `.groupby()`." ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "d.groupby('region') # пока ничего не увидели" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Что выдает метод `.groupby()`? На самом деле он делает следующее: создает список, состоящий из кортежей. Каждый кортеж ‒ это пара *название группы*-*соответствующий ей фрагмент датафрейма*." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# посмотрим на все сразу\n", "for g in d.groupby('region'):\n", " print(g)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "В таком виде метод `.groupby()` дает нам немного. Мы же хотим не просто получать отдельные таблицы, а агрегировать данные по регионам ‒ суммировать все показатели (число избирателей, бюллетеней, голосов) по каждому региону. Тут на помощь придет метод `.agg()`, который выполняет агрегирование по группам." ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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totalinvalidvalidZhZuMiPrPu
region
Алтайский край1961328.012004.01163426.097961.0261665.045883.083778.0674139.0
Амурская область662320.04708.0394996.039717.067433.013594.023070.0251182.0
Архангельская область988678.05522.0569492.051169.091648.033223.060108.0333344.0
Астраханская область769608.05107.0427496.021918.067662.018595.021873.0297448.0
Белгородская область1210590.010209.0889764.059561.0211079.035601.049807.0533716.0
Брянская область1045083.06922.0692926.042974.0146340.023453.032141.0448018.0
Владимирская область1202174.08484.0629526.053615.0132400.041895.060315.0341301.0
Волгоградская область2003455.012696.01265720.087657.0240998.055325.071142.0810598.0
Вологодская область987574.06596.0601999.049492.093417.040306.057064.0361720.0
Воронежская область1918524.013073.01291271.081081.0292379.047974.069813.0800024.0
Город Байконур (Республика Казахстан)15116.0185.010422.0586.01288.0317.0722.07509.0
Город Москва7309869.087698.04159740.0267418.0814573.0214703.0868736.01994310.0
Город Санкт-Петербург3849426.033331.02355236.0110979.0311937.0157768.0370799.01403753.0
Еврейская автономная область135703.01208.078205.06632.014796.02763.05102.048912.0
Забайкальский край831712.05271.0493136.049612.071636.015015.029466.0327407.0
Ивановская область866474.05338.0513901.037650.095005.023060.037016.0321170.0
Иркутская область1915179.012186.01060537.088419.0242097.041152.094008.0594861.0
Кабардино-Балкарская Республика528147.0418.0385368.011888.053261.011753.08937.0299529.0
Калужская область798196.06327.0500606.037634.0101459.021427.040911.0299175.0
Камчатский край256522.01951.0154696.016504.025009.05430.014015.093738.0
Карачаево-Черкесская Республика319473.0631.0290989.02851.016937.02162.02629.0266410.0
Кемеровская область2076673.016002.01626578.0112067.0133705.037450.075519.01267837.0
Кировская область1125794.07864.0682321.054531.0127982.036005.063993.0399810.0
Костромская область567472.03076.0345513.028204.090714.016094.026517.0183984.0
Краснодарский край3803307.032893.02659197.0176119.0496909.088976.0181844.01715349.0
Красноярский край2192321.016279.01287567.0112222.0235058.046123.0109827.0784337.0
Курганская область751903.04314.0478077.041340.083955.019280.027725.0305777.0
Курская область947765.06350.0600367.049744.0122775.023101.038002.0366745.0
Ленинградская область1281947.010664.0800093.054857.0114951.047518.080874.0501893.0
Липецкая область954695.07751.0618784.044697.0132408.024722.034778.0382179.0
...........................
Республика Калмыкия214497.01242.0131760.03374.023295.03562.08029.093500.0
Республика Карелия558774.03839.0305600.026579.050957.018886.037798.0171380.0
Республика Коми750661.06970.0518810.040314.070135.022738.043759.0341864.0
Республика Марий Эл537932.03984.0377164.024895.084200.015175.024282.0228612.0
Республика Мордовия649355.03796.0577911.013635.042060.06448.09353.0506415.0
Республика Саха (Якутия)614351.03978.0453719.020010.065871.020193.029712.0317933.0
Республика Северная Осетия - Алания512245.03995.0409435.013063.087017.012864.06848.0289643.0
Республика Тыва159341.0860.0146720.02574.06370.02023.02925.0132828.0
Республика Хакасия382578.02819.0244660.020991.050872.08878.019400.0144519.0
Ростовская область3315673.021742.02091438.0132418.0423884.076633.0134461.01324042.0
Рязанская область967998.06508.0614459.047068.0132981.025562.037903.0370945.0
Самарская область2562916.020828.01536839.0117828.0320128.061361.0125423.0912099.0
Саратовская область1991376.012400.01310761.066985.0206818.043267.059006.0934685.0
Сахалинская область398893.02846.0225504.020016.045730.08856.022337.0128565.0
Свердловская область3527808.025560.02048423.0107819.0251690.0113353.0237780.01337781.0
Смоленская область816276.05843.0476106.038246.0111182.020930.032516.0273232.0
Ставропольский край1983954.012448.01183292.083543.0215600.037551.075724.0770874.0
Тамбовская область884888.05570.0614521.028179.0107797.013973.019594.0444978.0
Тверская область1137087.07076.0660420.049384.0131591.032835.059302.0387308.0
Территория за пределами РФ459661.05838.0436093.012006.031785.08674.059942.0323686.0
Томская область787075.05194.0453117.035139.086403.016966.053028.0261581.0
Тульская область1249121.08862.0858707.050218.0147019.029601.043917.0587952.0
Тюменская область1056505.06915.0829264.059083.095398.020455.043047.0611281.0
Удмуртская Республика1218251.09048.0775357.049160.0116277.026803.067362.0515755.0
Ульяновская область1048667.06926.0659233.046384.0160089.027783.037437.0387540.0
Хабаровский край1056125.08733.0645264.068500.0115436.031944.062145.0367239.0
Челябинская область2757879.025366.01704033.097869.0254542.088177.0138907.01124538.0
Чувашская Республика - Чувашия954572.010465.0692492.039707.0144676.031201.038838.0438070.0
Чукотский автономный округ35968.0428.028909.02106.02651.0633.02209.021310.0
Ямало-Ненецкий автономный округ358834.02669.0332293.017456.018738.04979.07807.0283313.0
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80 rows × 8 columns

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" ], "text/plain": [ " total invalid valid \\\n", "region \n", "Алтайский край 1961328.0 12004.0 1163426.0 \n", "Амурская область 662320.0 4708.0 394996.0 \n", "Архангельская область 988678.0 5522.0 569492.0 \n", "Астраханская область 769608.0 5107.0 427496.0 \n", "Белгородская область 1210590.0 10209.0 889764.0 \n", "Брянская область 1045083.0 6922.0 692926.0 \n", "Владимирская область 1202174.0 8484.0 629526.0 \n", "Волгоградская область 2003455.0 12696.0 1265720.0 \n", "Вологодская область 987574.0 6596.0 601999.0 \n", "Воронежская область 1918524.0 13073.0 1291271.0 \n", "Город Байконур (Республика Казахстан) 15116.0 185.0 10422.0 \n", "Город Москва 7309869.0 87698.0 4159740.0 \n", "Город Санкт-Петербург 3849426.0 33331.0 2355236.0 \n", "Еврейская автономная область 135703.0 1208.0 78205.0 \n", "Забайкальский край 831712.0 5271.0 493136.0 \n", "Ивановская область 866474.0 5338.0 513901.0 \n", "Иркутская область 1915179.0 12186.0 1060537.0 \n", "Кабардино-Балкарская Республика 528147.0 418.0 385368.0 \n", "Калужская область 798196.0 6327.0 500606.0 \n", "Камчатский край 256522.0 1951.0 154696.0 \n", "Карачаево-Черкесская Республика 319473.0 631.0 290989.0 \n", "Кемеровская область 2076673.0 16002.0 1626578.0 \n", "Кировская область 1125794.0 7864.0 682321.0 \n", "Костромская область 567472.0 3076.0 345513.0 \n", "Краснодарский край 3803307.0 32893.0 2659197.0 \n", "Красноярский край 2192321.0 16279.0 1287567.0 \n", "Курганская область 751903.0 4314.0 478077.0 \n", "Курская область 947765.0 6350.0 600367.0 \n", "Ленинградская область 1281947.0 10664.0 800093.0 \n", "Липецкая область 954695.0 7751.0 618784.0 \n", "... ... ... ... \n", "Республика Калмыкия 214497.0 1242.0 131760.0 \n", "Республика Карелия 558774.0 3839.0 305600.0 \n", "Республика Коми 750661.0 6970.0 518810.0 \n", "Республика Марий Эл 537932.0 3984.0 377164.0 \n", "Республика Мордовия 649355.0 3796.0 577911.0 \n", "Республика Саха (Якутия) 614351.0 3978.0 453719.0 \n", "Республика Северная Осетия - Алания 512245.0 3995.0 409435.0 \n", "Республика Тыва 159341.0 860.0 146720.0 \n", "Республика Хакасия 382578.0 2819.0 244660.0 \n", "Ростовская область 3315673.0 21742.0 2091438.0 \n", "Рязанская область 967998.0 6508.0 614459.0 \n", "Самарская область 2562916.0 20828.0 1536839.0 \n", "Саратовская область 1991376.0 12400.0 1310761.0 \n", "Сахалинская область 398893.0 2846.0 225504.0 \n", "Свердловская область 3527808.0 25560.0 2048423.0 \n", "Смоленская область 816276.0 5843.0 476106.0 \n", "Ставропольский край 1983954.0 12448.0 1183292.0 \n", "Тамбовская область 884888.0 5570.0 614521.0 \n", "Тверская область 1137087.0 7076.0 660420.0 \n", "Территория за пределами РФ 459661.0 5838.0 436093.0 \n", "Томская область 787075.0 5194.0 453117.0 \n", "Тульская область 1249121.0 8862.0 858707.0 \n", "Тюменская область 1056505.0 6915.0 829264.0 \n", "Удмуртская Республика 1218251.0 9048.0 775357.0 \n", "Ульяновская область 1048667.0 6926.0 659233.0 \n", "Хабаровский край 1056125.0 8733.0 645264.0 \n", "Челябинская область 2757879.0 25366.0 1704033.0 \n", "Чувашская Республика - Чувашия 954572.0 10465.0 692492.0 \n", "Чукотский автономный округ 35968.0 428.0 28909.0 \n", "Ямало-Ненецкий автономный округ 358834.0 2669.0 332293.0 \n", "\n", " Zh Zu Mi Pr \\\n", "region \n", "Алтайский край 97961.0 261665.0 45883.0 83778.0 \n", "Амурская область 39717.0 67433.0 13594.0 23070.0 \n", "Архангельская область 51169.0 91648.0 33223.0 60108.0 \n", "Астраханская область 21918.0 67662.0 18595.0 21873.0 \n", "Белгородская область 59561.0 211079.0 35601.0 49807.0 \n", "Брянская область 42974.0 146340.0 23453.0 32141.0 \n", "Владимирская область 53615.0 132400.0 41895.0 60315.0 \n", "Волгоградская область 87657.0 240998.0 55325.0 71142.0 \n", "Вологодская область 49492.0 93417.0 40306.0 57064.0 \n", "Воронежская область 81081.0 292379.0 47974.0 69813.0 \n", "Город Байконур (Республика Казахстан) 586.0 1288.0 317.0 722.0 \n", "Город Москва 267418.0 814573.0 214703.0 868736.0 \n", "Город Санкт-Петербург 110979.0 311937.0 157768.0 370799.0 \n", "Еврейская автономная область 6632.0 14796.0 2763.0 5102.0 \n", "Забайкальский край 49612.0 71636.0 15015.0 29466.0 \n", "Ивановская область 37650.0 95005.0 23060.0 37016.0 \n", "Иркутская область 88419.0 242097.0 41152.0 94008.0 \n", "Кабардино-Балкарская Республика 11888.0 53261.0 11753.0 8937.0 \n", "Калужская область 37634.0 101459.0 21427.0 40911.0 \n", "Камчатский край 16504.0 25009.0 5430.0 14015.0 \n", "Карачаево-Черкесская Республика 2851.0 16937.0 2162.0 2629.0 \n", "Кемеровская область 112067.0 133705.0 37450.0 75519.0 \n", "Кировская область 54531.0 127982.0 36005.0 63993.0 \n", "Костромская область 28204.0 90714.0 16094.0 26517.0 \n", "Краснодарский край 176119.0 496909.0 88976.0 181844.0 \n", "Красноярский край 112222.0 235058.0 46123.0 109827.0 \n", "Курганская область 41340.0 83955.0 19280.0 27725.0 \n", "Курская область 49744.0 122775.0 23101.0 38002.0 \n", "Ленинградская область 54857.0 114951.0 47518.0 80874.0 \n", "Липецкая область 44697.0 132408.0 24722.0 34778.0 \n", "... ... ... ... ... \n", "Республика Калмыкия 3374.0 23295.0 3562.0 8029.0 \n", "Республика Карелия 26579.0 50957.0 18886.0 37798.0 \n", "Республика Коми 40314.0 70135.0 22738.0 43759.0 \n", "Республика Марий Эл 24895.0 84200.0 15175.0 24282.0 \n", "Республика Мордовия 13635.0 42060.0 6448.0 9353.0 \n", "Республика Саха (Якутия) 20010.0 65871.0 20193.0 29712.0 \n", "Республика Северная Осетия - Алания 13063.0 87017.0 12864.0 6848.0 \n", "Республика Тыва 2574.0 6370.0 2023.0 2925.0 \n", "Республика Хакасия 20991.0 50872.0 8878.0 19400.0 \n", "Ростовская область 132418.0 423884.0 76633.0 134461.0 \n", "Рязанская область 47068.0 132981.0 25562.0 37903.0 \n", "Самарская область 117828.0 320128.0 61361.0 125423.0 \n", "Саратовская область 66985.0 206818.0 43267.0 59006.0 \n", "Сахалинская область 20016.0 45730.0 8856.0 22337.0 \n", "Свердловская область 107819.0 251690.0 113353.0 237780.0 \n", "Смоленская область 38246.0 111182.0 20930.0 32516.0 \n", "Ставропольский край 83543.0 215600.0 37551.0 75724.0 \n", "Тамбовская область 28179.0 107797.0 13973.0 19594.0 \n", "Тверская область 49384.0 131591.0 32835.0 59302.0 \n", "Территория за пределами РФ 12006.0 31785.0 8674.0 59942.0 \n", "Томская область 35139.0 86403.0 16966.0 53028.0 \n", "Тульская область 50218.0 147019.0 29601.0 43917.0 \n", "Тюменская область 59083.0 95398.0 20455.0 43047.0 \n", "Удмуртская Республика 49160.0 116277.0 26803.0 67362.0 \n", "Ульяновская область 46384.0 160089.0 27783.0 37437.0 \n", "Хабаровский край 68500.0 115436.0 31944.0 62145.0 \n", "Челябинская область 97869.0 254542.0 88177.0 138907.0 \n", "Чувашская Республика - Чувашия 39707.0 144676.0 31201.0 38838.0 \n", "Чукотский автономный округ 2106.0 2651.0 633.0 2209.0 \n", "Ямало-Ненецкий автономный округ 17456.0 18738.0 4979.0 7807.0 \n", "\n", " Pu \n", "region \n", "Алтайский край 674139.0 \n", "Амурская область 251182.0 \n", "Архангельская область 333344.0 \n", "Астраханская область 297448.0 \n", "Белгородская область 533716.0 \n", "Брянская область 448018.0 \n", "Владимирская область 341301.0 \n", "Волгоградская область 810598.0 \n", "Вологодская область 361720.0 \n", "Воронежская область 800024.0 \n", "Город Байконур (Республика Казахстан) 7509.0 \n", "Город Москва 1994310.0 \n", "Город Санкт-Петербург 1403753.0 \n", "Еврейская автономная область 48912.0 \n", "Забайкальский край 327407.0 \n", "Ивановская область 321170.0 \n", "Иркутская область 594861.0 \n", "Кабардино-Балкарская Республика 299529.0 \n", "Калужская область 299175.0 \n", "Камчатский край 93738.0 \n", "Карачаево-Черкесская Республика 266410.0 \n", "Кемеровская область 1267837.0 \n", "Кировская область 399810.0 \n", "Костромская область 183984.0 \n", "Краснодарский край 1715349.0 \n", "Красноярский край 784337.0 \n", "Курганская область 305777.0 \n", "Курская область 366745.0 \n", "Ленинградская область 501893.0 \n", "Липецкая область 382179.0 \n", "... ... \n", "Республика Калмыкия 93500.0 \n", "Республика Карелия 171380.0 \n", "Республика Коми 341864.0 \n", "Республика Марий Эл 228612.0 \n", "Республика Мордовия 506415.0 \n", "Республика Саха (Якутия) 317933.0 \n", "Республика Северная Осетия - Алания 289643.0 \n", "Республика Тыва 132828.0 \n", "Республика Хакасия 144519.0 \n", "Ростовская область 1324042.0 \n", "Рязанская область 370945.0 \n", "Самарская область 912099.0 \n", "Саратовская область 934685.0 \n", "Сахалинская область 128565.0 \n", "Свердловская область 1337781.0 \n", "Смоленская область 273232.0 \n", "Ставропольский край 770874.0 \n", "Тамбовская область 444978.0 \n", "Тверская область 387308.0 \n", "Территория за пределами РФ 323686.0 \n", "Томская область 261581.0 \n", "Тульская область 587952.0 \n", "Тюменская область 611281.0 \n", "Удмуртская Республика 515755.0 \n", "Ульяновская область 387540.0 \n", "Хабаровский край 367239.0 \n", "Челябинская область 1124538.0 \n", "Чувашская Республика - Чувашия 438070.0 \n", "Чукотский автономный округ 21310.0 \n", "Ямало-Ненецкий автономный округ 283313.0 \n", "\n", "[80 rows x 8 columns]" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "d.groupby('region').agg('sum')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Сначала в `.groupby()` мы указали переменную, по которой нужно выполнить группировку, затем в `.agg()` мы указали функцию, которую нужно выполнить. В нашем случае это 'sum', поскольку нам нужно просто сложить все показатели в пределах одного региона. Применять можно и другие функции, например, считать среднее:" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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totalinvalidvalidZhZuMiPrPu
region
Алтайский край1053.3447916.446831624.82599452.610634140.52900124.64178344.993555362.051020
Амурская область845.8748406.012771504.46487950.72413886.12132817.36143029.463602320.794381
Архангельская область1004.7540655.611789578.75203352.00101693.13821133.76321161.085366338.764228
Астраханская область1313.3242328.715017729.51535837.402730115.46416431.73208237.325939507.590444
Белгородская область968.4720008.167200711.81120047.648800168.86320028.48080039.845600426.972800
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" ], "text/plain": [ " total invalid valid Zh \\\n", "region \n", "Алтайский край 1053.344791 6.446831 624.825994 52.610634 \n", "Амурская область 845.874840 6.012771 504.464879 50.724138 \n", "Архангельская область 1004.754065 5.611789 578.752033 52.001016 \n", "Астраханская область 1313.324232 8.715017 729.515358 37.402730 \n", "Белгородская область 968.472000 8.167200 711.811200 47.648800 \n", "\n", " Zu Mi Pr Pu \n", "region \n", "Алтайский край 140.529001 24.641783 44.993555 362.051020 \n", "Амурская область 86.121328 17.361430 29.463602 320.794381 \n", "Архангельская область 93.138211 33.763211 61.085366 338.764228 \n", "Астраханская область 115.464164 31.732082 37.325939 507.590444 \n", "Белгородская область 168.863200 28.480800 39.845600 426.972800 " ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "d.groupby('region').agg('mean').head() # mean - среднее" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Или сразу несколько статистик. которые можно указать в `.agg()` в виде списка." ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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totalinvalidvalidZhZuMiPrPu
meanmedianmeanmedianmeanmedianmeanmedianmeanmedianmeanmedianmeanmedianmeanmedian
region
Алтайский край1053.344791823.06.4468314.0624.825994495.052.61063441.0140.529001109.524.64178315.044.99355522.0362.051020305.5
Амурская область845.874840523.06.0127714.0504.464879326.050.72413831.086.12132852.017.3614309.029.46360212.0320.794381224.0
Архангельская область1004.754065581.55.6117892.0578.752033332.552.00101629.093.13821144.033.76321119.061.08536620.5338.764228230.5
Астраханская область1313.3242321283.58.7150176.0729.515358692.537.40273031.0115.464164100.531.73208222.037.32593922.0507.590444480.0
Белгородская область968.472000802.08.1672006.0711.811200633.047.64880041.0168.863200140.528.48080021.039.84560022.0426.972800397.0
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" ], "text/plain": [ " total invalid valid \\\n", " mean median mean median mean \n", "region \n", "Алтайский край 1053.344791 823.0 6.446831 4.0 624.825994 \n", "Амурская область 845.874840 523.0 6.012771 4.0 504.464879 \n", "Архангельская область 1004.754065 581.5 5.611789 2.0 578.752033 \n", "Астраханская область 1313.324232 1283.5 8.715017 6.0 729.515358 \n", "Белгородская область 968.472000 802.0 8.167200 6.0 711.811200 \n", "\n", " Zh Zu Mi \\\n", " median mean median mean median mean \n", "region \n", "Алтайский край 495.0 52.610634 41.0 140.529001 109.5 24.641783 \n", "Амурская область 326.0 50.724138 31.0 86.121328 52.0 17.361430 \n", "Архангельская область 332.5 52.001016 29.0 93.138211 44.0 33.763211 \n", "Астраханская область 692.5 37.402730 31.0 115.464164 100.5 31.732082 \n", "Белгородская область 633.0 47.648800 41.0 168.863200 140.5 28.480800 \n", "\n", " Pr Pu \n", " median mean median mean median \n", "region \n", "Алтайский край 15.0 44.993555 22.0 362.051020 305.5 \n", "Амурская область 9.0 29.463602 12.0 320.794381 224.0 \n", "Архангельская область 19.0 61.085366 20.5 338.764228 230.5 \n", "Астраханская область 22.0 37.325939 22.0 507.590444 480.0 \n", "Белгородская область 21.0 39.845600 22.0 426.972800 397.0 " ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "d.groupby('region').agg(['mean', 'median']).head() # среднее и медиана" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Кроме того, внутри `.agg()` можно указывать свои функции. Например, нас интересует разница между максимальным и минимальным значением. Сначала напишем функцию `my_diff`, которая будет определять такую разность:" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [], "source": [ "def my_diff(x):\n", " return max(x) - min(x)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Проверим, как она работает:" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "4" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "my_diff([4, 6, 8]) # все верно, 8 - 4 = 4" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Теперь используем эту функцию внутри `.agg()`:" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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totalinvalidvalidZhZuMiPrPu
region
Алтайский край3030.072.02389.0379.0573.0131.0351.01639.0
Амурская область2942.0130.01773.0267.0404.092.0197.01201.0
Архангельская область2953.076.01951.0232.0407.0153.0369.01205.0
Астраханская область2936.0223.01862.0209.0411.0157.0234.01367.0
Белгородская область2998.071.02118.0234.0612.0108.0335.01268.0
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" ], "text/plain": [ " total invalid valid Zh Zu Mi Pr \\\n", "region \n", "Алтайский край 3030.0 72.0 2389.0 379.0 573.0 131.0 351.0 \n", "Амурская область 2942.0 130.0 1773.0 267.0 404.0 92.0 197.0 \n", "Архангельская область 2953.0 76.0 1951.0 232.0 407.0 153.0 369.0 \n", "Астраханская область 2936.0 223.0 1862.0 209.0 411.0 157.0 234.0 \n", "Белгородская область 2998.0 71.0 2118.0 234.0 612.0 108.0 335.0 \n", "\n", " Pu \n", "region \n", "Алтайский край 1639.0 \n", "Амурская область 1201.0 \n", "Архангельская область 1205.0 \n", "Астраханская область 1367.0 \n", "Белгородская область 1268.0 " ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "d.groupby('region').agg(my_diff).head() # везде смотрим на первые 5 строк" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Возможностей на самом деле у метода `.agg()` много, но давайте более продвинутые вещи оставим на потом (будет выложен отдельный конспект с дополнительными материалами).\n", "\n", "Все, что мы пока сделали, очень интересно, но есть проблема: все данные пока даны в абсолютных значениях, не в процентах. Это неудобно. Давайте сгруппируем данные по региону и добавим в базу с агрегированными данными новые столбцы: явка в процентах и проценты голосов за каждого кандидата.\n", "\n", "Для этого необходимо вспомнить, как считается явка и проценты голосов. Явка считается так: суммируем число действительных и недействительных бюллетеней. Чтобы получить явку в процентах, делим явку на общее число зарегистрированных избирателей и домножаем на 100, чтобы перевести долю в проценты. Проценты голосов за кандидатов считаем от явки, берем число голосов за кандидата, делим на явку и домножаем на 100. Проделаем это поэтапно. \n", "\n", "Сначала сохраним результат агрегирования в переменную `regs` и добавим новый столбец для явки в абсолютных значениях (в голосах)." ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [], "source": [ "regs = d.groupby('region').agg('sum')\n", "\n", "regs[\"turnout\"] = regs.invalid + regs.valid # новый столбец - сумма двух старых" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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totalinvalidvalidZhZuMiPrPuturnout
region
Алтайский край1961328.012004.01163426.097961.0261665.045883.083778.0674139.01175430.0
Амурская область662320.04708.0394996.039717.067433.013594.023070.0251182.0399704.0
Архангельская область988678.05522.0569492.051169.091648.033223.060108.0333344.0575014.0
\n", "
" ], "text/plain": [ " total invalid valid Zh Zu \\\n", "region \n", "Алтайский край 1961328.0 12004.0 1163426.0 97961.0 261665.0 \n", "Амурская область 662320.0 4708.0 394996.0 39717.0 67433.0 \n", "Архангельская область 988678.0 5522.0 569492.0 51169.0 91648.0 \n", "\n", " Mi Pr Pu turnout \n", "region \n", "Алтайский край 45883.0 83778.0 674139.0 1175430.0 \n", "Амурская область 13594.0 23070.0 251182.0 399704.0 \n", "Архангельская область 33223.0 60108.0 333344.0 575014.0 " ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "regs.head(3)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Теперь добавим столбец с явкой в процентах:" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [], "source": [ "regs[\"turnout_perc\"] = regs.turnout / regs.total * 100" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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totalinvalidvalidZhZuMiPrPuturnoutturnout_perc
region
Алтайский край1961328.012004.01163426.097961.0261665.045883.083778.0674139.01175430.059.930313
Амурская область662320.04708.0394996.039717.067433.013594.023070.0251182.0399704.060.349076
Архангельская область988678.05522.0569492.051169.091648.033223.060108.0333344.0575014.058.159886
\n", "
" ], "text/plain": [ " total invalid valid Zh Zu \\\n", "region \n", "Алтайский край 1961328.0 12004.0 1163426.0 97961.0 261665.0 \n", "Амурская область 662320.0 4708.0 394996.0 39717.0 67433.0 \n", "Архангельская область 988678.0 5522.0 569492.0 51169.0 91648.0 \n", "\n", " Mi Pr Pu turnout turnout_perc \n", "region \n", "Алтайский край 45883.0 83778.0 674139.0 1175430.0 59.930313 \n", "Амурская область 13594.0 23070.0 251182.0 399704.0 60.349076 \n", "Архангельская область 33223.0 60108.0 333344.0 575014.0 58.159886 " ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "regs.head(3)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Осталось проделать аналогичные операции для голосов за разных кандидатов. Но повторять одно и то же пять раз не хочется (а что бы мы делали, если бы кандидатов было больше?). Давайте напишем функцию, которая будет принимать на вход столбец, делить все его значения на значения из столбца *turnout* и переводить все в проценты." ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [], "source": [ "def to_perc(x):\n", " return x / regs.turnout * 100" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "А теперь выберем из базы данных столбцы с голосами за кандидатов и применим к ним нашу функцию." ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [], "source": [ "perc = regs[['Zh' ,'Zu', 'Mi', 'Pr', 'Pu']].apply(to_perc, axis = 0) # axis = 0 - по столбцам, не по строкам " ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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ZhZuMiPrPu
region
Алтайский край8.33405622.2612153.9035087.12743457.352543
Амурская область9.93660316.8707343.4010175.77177162.842003
Архангельская область8.89874015.9383955.77777210.45331157.971458
\n", "
" ], "text/plain": [ " Zh Zu Mi Pr Pu\n", "region \n", "Алтайский край 8.334056 22.261215 3.903508 7.127434 57.352543\n", "Амурская область 9.936603 16.870734 3.401017 5.771771 62.842003\n", "Архангельская область 8.898740 15.938395 5.777772 10.453311 57.971458" ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "perc.head(3)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Нужно переименовать столбцы в базе `perc`. Давайте сделаем это по-умному: возьмем названия столбцов в `perc` и приклеим к ним часть с `_perc`, чтобы названия столбцов с показателями в процентах отличались от показателей в абсолютных числах." ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['Zh', 'Zu', 'Mi', 'Pr', 'Pu']" ] }, "execution_count": 28, "metadata": {}, "output_type": "execute_result" } ], "source": [ "old_cols = list(perc.columns)\n", "old_cols" ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['Zh_perc', 'Zu_perc', 'Mi_perc', 'Pr_perc', 'Pu_perc']" ] }, "execution_count": 29, "metadata": {}, "output_type": "execute_result" } ], "source": [ "new_cols = [x + \"_perc\" for x in old_cols]\n", "new_cols" ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [], "source": [ "perc.columns = new_cols" ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Zh_percZu_percMi_percPr_percPu_perc
region
Алтайский край8.33405622.2612153.9035087.12743457.352543
Амурская область9.93660316.8707343.4010175.77177162.842003
Архангельская область8.89874015.9383955.77777210.45331157.971458
\n", "
" ], "text/plain": [ " Zh_perc Zu_perc Mi_perc Pr_perc Pu_perc\n", "region \n", "Алтайский край 8.334056 22.261215 3.903508 7.127434 57.352543\n", "Амурская область 9.936603 16.870734 3.401017 5.771771 62.842003\n", "Архангельская область 8.898740 15.938395 5.777772 10.453311 57.971458" ] }, "execution_count": 31, "metadata": {}, "output_type": "execute_result" } ], "source": [ "perc.head(3)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Ура! Последний аккорд: соединим нашу таблицу `regs` с таблицей `perc`, чтобы все показатели были в одном месте. Способов объединять датафреймы много, но давайте обсудим их в следующий раз. А пока просто склеим две таблицы по столбцам с помощью метода `.concat()`." ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [], "source": [ "final = pd.concat([regs, perc], axis = 1) # axis = 1 - по столбцам" ] }, { "cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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totalinvalidvalidZhZuMiPrPuturnoutturnout_percZh_percZu_percMi_percPr_percPu_perc
region
Алтайский край1961328.012004.01163426.097961.0261665.045883.083778.0674139.01175430.059.9303138.33405622.2612153.9035087.12743457.352543
Амурская область662320.04708.0394996.039717.067433.013594.023070.0251182.0399704.060.3490769.93660316.8707343.4010175.77177162.842003
Архангельская область988678.05522.0569492.051169.091648.033223.060108.0333344.0575014.058.1598868.89874015.9383955.77777210.45331157.971458
Астраханская область769608.05107.0427496.021918.067662.018595.021873.0297448.0432603.056.2108245.06653915.6406684.2983985.05613768.757729
Белгородская область1210590.010209.0889764.059561.0211079.035601.049807.0533716.0899973.074.3416856.61808723.4539263.9557855.53427759.303557
\n", "
" ], "text/plain": [ " total invalid valid Zh Zu \\\n", "region \n", "Алтайский край 1961328.0 12004.0 1163426.0 97961.0 261665.0 \n", "Амурская область 662320.0 4708.0 394996.0 39717.0 67433.0 \n", "Архангельская область 988678.0 5522.0 569492.0 51169.0 91648.0 \n", "Астраханская область 769608.0 5107.0 427496.0 21918.0 67662.0 \n", "Белгородская область 1210590.0 10209.0 889764.0 59561.0 211079.0 \n", "\n", " Mi Pr Pu turnout turnout_perc \\\n", "region \n", "Алтайский край 45883.0 83778.0 674139.0 1175430.0 59.930313 \n", "Амурская область 13594.0 23070.0 251182.0 399704.0 60.349076 \n", "Архангельская область 33223.0 60108.0 333344.0 575014.0 58.159886 \n", "Астраханская область 18595.0 21873.0 297448.0 432603.0 56.210824 \n", "Белгородская область 35601.0 49807.0 533716.0 899973.0 74.341685 \n", "\n", " Zh_perc Zu_perc Mi_perc Pr_perc Pu_perc \n", "region \n", "Алтайский край 8.334056 22.261215 3.903508 7.127434 57.352543 \n", "Амурская область 9.936603 16.870734 3.401017 5.771771 62.842003 \n", "Архангельская область 8.898740 15.938395 5.777772 10.453311 57.971458 \n", "Астраханская область 5.066539 15.640668 4.298398 5.056137 68.757729 \n", "Белгородская область 6.618087 23.453926 3.955785 5.534277 59.303557 " ] }, "execution_count": 33, "metadata": {}, "output_type": "execute_result" } ], "source": [ "final.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Приличную базу мы получили, можно перейти к чему-то более содержательному." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Еще немного про визуализацию данных" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "В прошлый раз мы познакомились с тем, как строить графики для переменных в базе данных. Мы уже обсудили два типа графиков для количественных данных: гистограмму и ящик с усами. Давайте посмотрим на диаграммы рассеяния ‒ графики, которые позволяют увидеть совместное распределение пары количественных показателей. " ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [], "source": [ "import matplotlib # загружаем библиотеку для графиков" ] }, { "cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [], "source": [ "% matplotlib inline " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "А теперь сама диаграмма рассеяния (*scatterplot*) для показателей *явка в процентах* и *процент за Зюганова*:" ] }, { "cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 37, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "final.plot.scatter('turnout_perc', 'Zu_perc')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Можем привести график в порядок. Добавить заголовок и подписи к осям, плюс, изменить цвет точек. Для этого основной график сохраним в переменную `ax`, а затем применим к ней методы, которые отвечают за добавление заголовка и названиям осей *x* и *y*. " ] }, { "cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 38, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ax = final.plot.scatter('turnout_perc', 'Zu_perc', color = \"magenta\") # цвет magenta\n", "ax.set_title('Scatterplot') # заголовок для объекта ax\n", "ax.set_xlabel('turnout rate (%)') # подпись для оси x\n", "ax.set_ylabel('votes for Zuganov (%)') # подпись для оси y" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "По графику видно, что, в целом, чем выше явка, тем ниже процент голосов за Зюганова. Углубляться в разные настройки графиков и в статистику не будем, но познакомимся с примером графика средствами библиотеки pandas. Построим матрицу диаграмм рассеяния (*scatterplot matrix*), сетку с диаграммами рассеяния для всех пар показателей.\n", "\n", "Логично будет строить такой график для переменных в базе `perc`, поскольку правильнее смотреть на связи между показателями в процентах." ] }, { "cell_type": "code", "execution_count": 39, "metadata": {}, "outputs": [], "source": [ "from pandas.plotting import scatter_matrix # импортируем функцию" ] }, { "cell_type": "code", "execution_count": 40, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[,\n", " ,\n", " ,\n", " ,\n", " ],\n", " [,\n", " ,\n", " ,\n", " ,\n", " ],\n", " [,\n", " ,\n", " ,\n", " ,\n", " ],\n", " [,\n", " ,\n", " ,\n", " ,\n", " ],\n", " [,\n", " ,\n", " ,\n", " ,\n", " ]],\n", " dtype=object)" ] }, "execution_count": 40, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "scatter_matrix(perc, diagonal='hist', figsize=(10, 10)) # строим график" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Аргумент `diagonal` отвечает за тип графика, который будет находиться на диагонали (в нашем случае гистограмма ‒ `'hist'`), а аргумент `figsize` ‒ за размер графика (по горизонтали и по вертикали). На диагоналях также можно построить сглаженные графики плотности распределения показателей:" ] }, { "cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[,\n", " ,\n", " ,\n", " ,\n", " ],\n", " [,\n", " ,\n", " ,\n", " ,\n", " ],\n", " [,\n", " ,\n", " ,\n", " ,\n", " ],\n", " [,\n", " ,\n", " ,\n", " ,\n", " ],\n", " [,\n", " ,\n", " ,\n", " ,\n", " ]],\n", " dtype=object)" ] }, "execution_count": 41, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "scatter_matrix(perc, diagonal='kde', figsize=(10, 10)) # kde - от kernel density estimation" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "На этом пока всё." ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "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": "3.5.2" } }, "nbformat": 4, "nbformat_minor": 2 }