831 lines
8.3 MiB
Plaintext
831 lines
8.3 MiB
Plaintext
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{
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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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"# Statystyki Koronawirusa\n",
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"\n",
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"Autor: Filip Paluszak\n",
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"\n",
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"Projekt ma na celu wizualizacje statystyk nt. koronawirusa w Polsce. \n",
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"Dane pobrane są z https://www.gov.pl/web/koronawirus/wykaz-zarazen-koronawirusem-sars-cov-2\n",
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"\n",
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"Ponieważ strona rzadowa zmieniała się kilka razy w ciągu paru miesięcy, dane nie były scrapowane, ale pobrane statycznie"
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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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"## Instalacja\n",
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"\n",
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"1) Instalacja geopandas https://www.hatarilabs.com/ih-en/how-to-install-python-geopandas-on-anaconda-in-windows-tutorial\n",
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"\n",
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"2) pip install -r requirements.txt"
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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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"## Ladowanie Danych"
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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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"### Dane statystyczne\n",
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"\n",
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"Dane załadowane są z plików csv. Niestety kodowania plików są różne (mimo że pochodzą z jednego źródła), więc trzeba obsługiwać błędy kodowania"
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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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"import os\n",
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"\n",
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"from pprint import pprint\n",
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"import matplotlib.pyplot as plt\n",
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"import pandas as pd\n",
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"import numpy as np\n",
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"import geopandas as gpd"
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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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"source": [
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"# Wczytujemy dane ze wszystkich plikow\n",
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"def read_data(data_dir):\n",
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" df_list = []\n",
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" for path, _, filenames in os.walk(data_dir):\n",
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" for f in filter(lambda x: x.endswith('.csv'), filenames):\n",
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" filepath = os.path.join(path, f)\n",
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" for enc in [\"utf-8\", \"cp1250\"]:\n",
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" try:\n",
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" df_list.append(pd.read_csv(os.path.join(path, f), encoding=enc, delimiter=';'))\n",
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" break\n",
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" except Exception as e:\n",
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" pass\n",
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" else:\n",
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" print(f'Nie udało się wczytać {filepath}')\n",
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" return pd.concat(df_list)\n",
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" "
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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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"df = read_data('data')\n",
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"# Usuwamy statystyki dla całego kraju\n",
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"df = df[df['wojewodztwo'] != 'Cały kraj']\n",
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"\n",
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"# Usuwamy wiersze bez daty\n",
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"df = df.dropna(subset=['stan_rekordu_na'])"
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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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"name": "stdout",
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"output_type": "stream",
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"text": [
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"['2020-11-23' '2020-11-24' '2020-11-25' '2020-11-26' '2020-11-27'\n",
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" '2020-11-28' '2020-11-29' '2020-11-30' '2020-12-01' '2020-12-02'\n",
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" '2020-12-03' '2020-12-04' '2020-12-05' '2020-12-06' '2020-12-07'\n",
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" '2020-12-08' '2020-12-09' '2020-12-10' '2020-12-11' '2020-12-12'\n",
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" '2020-12-13' '2020-12-14' '2020-12-15' '2020-12-16' '2020-12-17'\n",
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" '2020-12-18' '2020-12-19' '2020-12-20' '2020-12-21' '2020-12-22'\n",
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" '2021-01-27' '2021-01-28' '2021-01-29' '2021-01-30' '2021-01-31'\n",
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" '2021-02-01' '2021-02-02' '2021-02-03' '2021-02-04' '2021-02-05'\n",
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" '2021-02-06' '2021-02-07' '2021-02-08' '2021-02-09' '2021-02-10'\n",
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" '2021-02-11' '2021-02-12' '2021-02-13' '2021-02-14' '2021-02-15'\n",
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" '2021-02-16']\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"51"
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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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"# Możliwe daty\n",
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"available_dates = df['stan_rekordu_na'].unique()\n",
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"print(available_dates)\n",
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"len(available_dates)"
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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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"name": "stdout",
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"output_type": "stream",
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"text": [
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"['wojewodztwo',\n",
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" 'powiat_miasto',\n",
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" 'liczba_przypadkow',\n",
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" 'liczba_na_10_tys_mieszkancow',\n",
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" 'zgony',\n",
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" 'zgony_w_wyniku_covid_bez_chorob_wspolistniejacych',\n",
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" 'zgony_w_wyniku_covid_i_chorob_wspolistniejacych',\n",
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" 'liczba_zlecen_poz',\n",
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" 'liczba_osob_objetych_kwarantanna',\n",
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" 'liczba_wykonanych_testow',\n",
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" 'liczba_testow_z_wynikiem_pozytywnym',\n",
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" 'liczba_testow_z_wynikiem_negatywnym',\n",
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" 'liczba_pozostalych_testow',\n",
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" 'teryt',\n",
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" 'stan_rekordu_na',\n",
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" 'liczba_ozdrowiencow']\n"
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]
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}
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],
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"source": [
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"# Mozliwe kolumny\n",
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"pprint(list(df.columns))"
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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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"### Mapa z powiatami\n",
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"Do wizualizacji posłużyłem się mapą powiatów\n",
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"https://maten.pl/post/poland-map/"
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]
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},
|
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|
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{
|
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|
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"cell_type": "code",
|
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|
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"execution_count": 6,
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"metadata": {},
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"outputs": [],
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"source": [
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"try:\n",
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" pl_powiaty = gpd.read_file('dane_geo\\Powiaty.shp')\n",
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"except ValueError as e:\n",
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" print(e)"
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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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"data": {
|
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"text/plain": [
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|
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"(13.621739949250054, 24.646927985750057, 48.710328010550036, 55.12813517445003)"
|
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|
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]
|
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|
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},
|
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|
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"execution_count": 7,
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|
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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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|
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{
|
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|
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"data": {
|
||
|
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"image/png": "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|
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"text/plain": [
|
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"<Figure size 1008x1008 with 1 Axes>"
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]
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},
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"metadata": {
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"needs_background": "light"
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},
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"output_type": "display_data"
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|
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}
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|
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],
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"source": [
|
||
|
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"# Przykladowa pusta mapa z zaznaczonymi powiatami\n",
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||
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"fig, ax = plt.subplots(1, figsize=(14, 14))\n",
|
||
|
|
"pl_powiaty.plot(ax=ax, linewidth=0.5, edgecolor='0.4', color='0.8')\n",
|
||
|
|
"ax.axis('off')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"## Łączenie danych\n",
|
||
|
|
"Aby wyświetlić dane na mapie, potrzebujemy połączyć dane na temat koronawirusa z mapą.\n",
|
||
|
|
"Będziemy łączyć po kodzie terytorialnym. Niestety formaty w danych nt koronawirusa i mapy się różnią, więc trzeba je uwspólnić"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 8,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"# Usuwamy pierwszą literke z kodu terytorialnego z danych csv\n",
|
||
|
|
"df['JPT_KOD_JE'] = df.apply(lambda x: x.teryt[1:], axis=1)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 9,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"pl_powiaty_merged = pl_powiaty.merge(df, left_on='JPT_KOD_JE', right_on='JPT_KOD_JE')\n",
|
||
|
|
"pl_powiaty_merged.fillna(0, inplace=True)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 10,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"(19380, 46)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 10,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"pl_powiaty_merged.shape"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"## Wizualizacje\n",
|
||
|
|
"\n",
|
||
|
|
"Pomocnicze funkcje do wizualizacji map i wykresow"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 11,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"# Pojedyncza mapa\n",
|
||
|
|
"def map_vis(df, column, date):\n",
|
||
|
|
" if date not in available_dates:\n",
|
||
|
|
" raise Exception(f'Zly zakres daty {date_1}')\n",
|
||
|
|
" \n",
|
||
|
|
" fig, ax = plt.subplots(1, figsize=(15, 15))\n",
|
||
|
|
"\n",
|
||
|
|
" df_1 = df[df['stan_rekordu_na'] == date]\n",
|
||
|
|
" df_1.plot(ax=ax, linewidth=0.5, edgecolor='0.4', column=column, cmap='Greens', scheme='quantiles', legend=True)\n",
|
||
|
|
" \n",
|
||
|
|
" ax.set_title(f'{column} w dniu {date}')\n",
|
||
|
|
" ax.axis('off')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 12,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"# Porownanie dwoch map wzgledem daty\n",
|
||
|
|
"def map_vis_cmp_date(df, column, date_1, date_2):\n",
|
||
|
|
" if date_1 not in available_dates:\n",
|
||
|
|
" raise Exception(f'Zly zakres daty {date_1}')\n",
|
||
|
|
" if date_2 not in available_dates:\n",
|
||
|
|
" raise Exception(f'Zly zakres daty {date_2}')\n",
|
||
|
|
" \n",
|
||
|
|
" \n",
|
||
|
|
" fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(20, 20))\n",
|
||
|
|
" \n",
|
||
|
|
" df_1 = df[df['stan_rekordu_na'] == date_1]\n",
|
||
|
|
" df_2 = df[df['stan_rekordu_na'] == date_2]\n",
|
||
|
|
" \n",
|
||
|
|
" df_1.plot(ax=ax1, linewidth=0.5, edgecolor='0.4', column=column, cmap='Greens', scheme='quantiles', legend=True)\n",
|
||
|
|
" df_2.plot(ax=ax2, linewidth=0.5, edgecolor='0.4', column=column, cmap='Greens', scheme='quantiles', legend=True)\n",
|
||
|
|
" \n",
|
||
|
|
" ax1.set_title(f'{column} w dniu {date_1}')\n",
|
||
|
|
" ax2.set_title(f'{column} w dniu {date_2}')\n",
|
||
|
|
" \n",
|
||
|
|
" ax1.axis('off')\n",
|
||
|
|
" ax2.axis('off')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 13,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"# Porownanie dwoch map wzgledem kolumn\n",
|
||
|
|
"def map_vis_cmp_columns(df, column_1, column_2, date):\n",
|
||
|
|
" if date not in available_dates:\n",
|
||
|
|
" raise Exception(f'Zly zakres daty {date}')\n",
|
||
|
|
" \n",
|
||
|
|
" fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(20, 20))\n",
|
||
|
|
" \n",
|
||
|
|
" df = df[df['stan_rekordu_na'] == date]\n",
|
||
|
|
" \n",
|
||
|
|
" df.plot(ax=ax1, linewidth=0.5, edgecolor='0.4', column=column_1, cmap='Greens', scheme='quantiles', legend=True)\n",
|
||
|
|
" df.plot(ax=ax2, linewidth=0.5, edgecolor='0.4', column=column_2, cmap='Greens', scheme='quantiles', legend=True)\n",
|
||
|
|
" \n",
|
||
|
|
" ax1.set_title(f'{column_1} w dniu {date}')\n",
|
||
|
|
" ax2.set_title(f'{column_2} w dniu {date}')\n",
|
||
|
|
" \n",
|
||
|
|
" ax1.axis('off')\n",
|
||
|
|
" ax2.axis('off')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 14,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"def bar_plot_wojewodztwa(df, column, date):\n",
|
||
|
|
" fig, ax = plt.subplots(figsize=(8, 3), dpi=144)\n",
|
||
|
|
" colors = plt.cm.Dark2(range(6))\n",
|
||
|
|
" \n",
|
||
|
|
" df2 = df[df['stan_rekordu_na'] == date].copy()\n",
|
||
|
|
" df2 = df2.groupby(['wojewodztwo', 'stan_rekordu_na'], as_index=False)[column].agg(sum).reindex()\n",
|
||
|
|
" df2.sort_values(column, inplace=True)\n",
|
||
|
|
" \n",
|
||
|
|
" y = df2.wojewodztwo\n",
|
||
|
|
" width = df2[column]\n",
|
||
|
|
" \n",
|
||
|
|
" ax.barh(y=y, width=width, color=colors);"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 15,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"def wojewodztwo_line_plot(df, column):\n",
|
||
|
|
" fig, ax = plt.subplots(figsize=(25, 10), dpi=144)\n",
|
||
|
|
"\n",
|
||
|
|
" df = df.groupby(['wojewodztwo', 'stan_rekordu_na'], as_index=False)[column].agg(sum).reindex()\n",
|
||
|
|
" for wojewodztwo, df_w in df.groupby(['wojewodztwo']):\n",
|
||
|
|
" x = df_w['stan_rekordu_na']\n",
|
||
|
|
" y = df_w[column]\n",
|
||
|
|
" ax.plot(x, y, label=wojewodztwo)\n",
|
||
|
|
"\n",
|
||
|
|
" ax.legend(bbox_to_anchor=(1.1, 1.05))\n",
|
||
|
|
" fig.autofmt_xdate()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"# Analiza"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"# Liczba Przypadkow"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 16,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 1440x1440 with 2 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"map_vis_cmp_columns(pl_powiaty_merged, 'liczba_przypadkow', 'liczba_na_10_tys_mieszkancow', '2021-02-13')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 17,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 1440x1440 with 2 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"map_vis_cmp_date(pl_powiaty_merged, 'liczba_na_10_tys_mieszkancow', '2020-12-15', '2021-02-16')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 18,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 1152x432 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"bar_plot_wojewodztwa(pl_powiaty_merged, 'liczba_przypadkow', '2021-02-16')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 19,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 1152x432 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"bar_plot_wojewodztwa(pl_powiaty_merged, 'liczba_na_10_tys_mieszkancow', '2021-02-16')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 20,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 3600x1440 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"wojewodztwo_line_plot(pl_powiaty_merged, 'liczba_przypadkow')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 21,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 3600x1440 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"wojewodztwo_line_plot(pl_powiaty_merged, 'liczba_na_10_tys_mieszkancow')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"## Ozdrowiency\n",
|
||
|
|
"\n",
|
||
|
|
"Ponizej pokazujemy statystyki na temat rozkladu ozdrowienców"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 22,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "iVBORw0KGgoAAAANSUhEUgAAA1MAAAM0CAYAAABeSXh+AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8vihELAAAACXBIWXMAAAsTAAALEwEAmpwYAAEAAElEQVR4nOzdd3xcxbk38N+ctn1Xq7bqkm3ZkiX3ijHYmN47Tuj9LgGSEEi75c3Nzb1JLqSHG4JCCC0kgRACBDChG2MMNi5ylbtl9bLavnv6vH+sZGRbklVWlgTz5eMP2t1z5sy2s/OcmXmGUErBMAzDMAzDMAzDDA031hVgGIZhGIZhGIaZiFgwxTAMwzAMwzAMMwwsmGIYhmEYhmEYhhkGFkwxDMMwDMMwDMMMAwumGIZhGIZhGIZhhoEFUwzDMAzDMAzDMMPAgimGYUaMEHKIEHJ299//Rgj5/QjKuoUQ8mH6aseMBCFkByHkjFEq+/uEkD+ORtkTDSGkjBBCCSHCILYtIYTECCH8yagbwzAM0z8WTDEMk1aU0h9RSu8Y63qcDISQ3xFCdhNCTELILX08/g1CSCshJEwI+QMhxDKIMo8EpuMBpbSaUvr+WNeD+Qyl9DCl1EkpNYa6LyHkFELIW4SQLkJIByHkr4SQ/F6PE0LIg4SQQPe/hwghpPuxXELInwkhzd2f6bWEkMW99s0nhLzS/TglhJQNoj7XEULqCSFxQshLhJDMXo+tJIR8RAhJEELeH0RZDxFCGgghke4y//2Yx+cQQjZ2l7eREDJnUC8awzDMAFgwxTAMM3y1AO4GsOnYBwgh5wH4LoCzAJQBmAzgv05m5RimD14Av0PqM1kKIArgiV6P/wuAywHMBjALwMUA/N2POQFsADAfQCaApwC8Rghxdj9uAngDwFWDqQghpBpADYAbAfgAJAA80muTLgC/BPC/g3xujwOopJS6AZwK4DpCyJXdx5IAvAzgj0i9Bk8BeLn7foZhmGFjwRTDMGl17NAtQshp3VeXQ91XjW8hhBR0D1Pq+ZcghNCjiyEPd1/9riOEnNXrgVsJIbsIIVFCyAFCiB8nQAg5gxDSSAh5gBDSTghpIYTc2uvxiwghm7uvaDcQQr4/mOdKKf0NpfQdAHIfD98M4HFK6Q5KaRDAfwO45QT1fAZACYB/dL8u3yaEvEYI+eox220lhFze3Yvwi+7nFO6+f8YJjvEkIeQRQsiq7mOsJYTkEUJ+SQgJdr/ec3tt33sIJ0cI+S4hZH93r8XzPT0JhBArIeSP3feHCCEbCCE+QsiSY95rmRByqI96id29Hn8jhEgDvc+DeD9thJCfdfdOhAkhHxJCbN2PXUpSQxdDhJD3CSHTu++/lRDyj15l7COEPN/rdkNfPRmEkKcIIQ90/11IUj0yd3ffLiepHiDSx348IeSnhJBOQsgBABcd8/j7hJD/7n5/ooSQNwkh2d2PHTUkkBzTm0kGGD5JKV1FKf0rpTRCKU0A+D8AS3ttcjOAn1FKGymlTQB+hu7PLaX0AKX055TSFkqpQSn9HQAJQEX3422U0keQCrgG43oA/6CUfkApjQH4fwCuJIS4ust7m1L6PIDmwRRGKd1NKY33ussEUN799xkABAC/pJQqlNJfAyAAzhxkXRmGYfrEgimGYUYNIaQEwCoADwPIATAHwBZKaXP3MCUnpdQJ4O8A/tJr18UADgDIBvCfAF4knw3/aUfqarkbwK0AfkEImTeI6uQB8AAoBHA7gN8QQrzdj8UB3AQgA6lG7VcIIZcP5zn3Uo1Uz1WPWgA+QkhWfztQSm8EcBjAJd2vzUNIXUG/oWcbQsjs7ufwOoBzASwDMK277l8CEBhE3VYC+A+kXl8FwDqketeyAbwA4Of97Pc1pHotlgMoABAE8Jvux25G6vUtBpAF4C4ASUrpul7vsxfAxwD+3LvQ7kDnpe66rKSUqjjx+zzQ+/lTpHpPTkWqB+XbAExCyLTuY9+H1OfxdaQCVwnAagCndweM+QBEdAcZhJDJSPXKbO3jNVmNVEMd3a/Lge7/A6n3Zg2llPax353dz28ugAUAru5jm+u6n3suUkHLN/vYZqSWAdjR63Zfn9vqvnbsDi4lAPuGeeyjjkUp3Q9ARerzPCzdwX4MQCMAB4A/9TrW1mPei63o57kxDMMMFgumGIYZTdcDeJtS+mdKqUYpDVBKt/TegBDyHQCVAG7rdXc7UleQNUrpcwB2o/vKPaX0NUrpfpqyGsCbAE4fRF00AD/oLvN1ADF8dkX9fUrpNkqpSSndilSDe/kAZQ2GE0C41+2ev11DLOdlAFMJIVO7b98I4LnugEPrLq8SAKGU7qKUtgyizL9TSjdSSmWkAlmZUvp09xyc55Bq4PfFD+Dfu3stFADfB3B1dw+JhlQQVd7da7GRUho5Zv9fIxW49p7L4kZqaNh+ALf2zAMaxPvc5/tJCOGQ+ix9nVLa1F2Xj7rr+yUAr1FK36KUakgFXTYAp1JKDyA15G0OUu/9PwE0EUIqu2+voZSafbwmR4IwpAKTh/BZT8/y7sf7shKpz3gDpbQLwI/72OYJSukeSmkSwPPddUsbQsgsAN8D8K1ed/f1uXUe27tGCHEDeAbAf1FKe28/FMceq+d4Q/2OHEEp/d/u/ed116+n/LQfi2EYBmDBFMMwo6sYqUZynwghFwD4OoDLuxuMPZqOuYJcj1RPCAghFxBCPu4ePhUCcCFSPSonEqCU6r1uJ5BqYIEQspgQ8h5JTcgPI9WrMpgyBxJDKlDo0fN3dCiFdAcBzwO4obvBfi1SjURQSt9FapjWbwC0kVRCDHe/hX2mrdffyT5uO9G3UgB/7x4iFwKwC4CB1HyXZ5AKQP5CUgkIHiKEiD07dg/TOwPAdccEJacgNTfnf3u/54N4n/t7P7MBWNH3564Aqc8SAKC7Hg1I9W4Bn/UyLev++32kAqJ+g6Lu3pQYUoHO6QBeBdBMCKkYaL/uujT0ul3fxzatfTy/tCCElCPVa/x1SumaXg/19bmNHfPe2AD8A8DHlNK+gsC+jnd6r6GePT1hxx6r53gn/I4QQh7tVd6/9X6sOwDfjNRnuWee4rCPxTAMMxAWTDEMM5oaAEzp64HuxuZTSA3rajjm4cJjroSXINVAtQD4G1I9Cj5KaQZSQ7WOm5MyRH8C8AqAYkqpB8CjaShzB1KT+HvMBtBGKT3RMLy+hoQ9hVQv31kAEpTSdUc2pvTXlNL5SA1XmoajexnSrQHABZTSjF7/rN09QBql9L8opVVIDa+7GKmhkyCEnI7UnLHL+ujFeBOpXpl3CCG+7u1H8j53IjWHra/PXTNSASG6j0OQCvibuu/qCaZO7/57NU4QTPXa72oAEk3NM1qN1HP3AtjSzz4t3cfuUTJA+ScSB2DvdTtvoI0JIaUA3gbw35TSZ455uK/P7Y5e+1qQGpLZhM8SU5wQpXRNr6G9PUPrjjpW93BKC4A9gyjvrl7l/aifzQR89jnYAWDWMeeVWTh6iCPDMMyQsWCKYZjR9CyAs0kqxbFACMkiqfTEbqSGr/0HpbSvNaVyAXyNpJISXANgOlKNaQmpxlYHAL27Z+vcNNTTBaCLUioTQhYhNVflhEgqUYIVqUa+SFJJGHrOq08DuJ0QUtU9l+c/ADw5iGLbkMr8d0R38GQilQzgSOOXELKwu1dNRKpBLSPVUzRaHgXww+7GOAghOYSQy7r/XkEImUlSax9FkBqGZxBCipEaOngTpbTPRnL33LA/IRVQZWME73N3b9MfAPycpBKd8CSVBMOCVA/fRYSQs7pfsweQmqf1UffuqwGsAGCjlDYCWAPgfKSGL24e4LCrAdwL4IPu2+8D+CqAD2n/6cufR+ozXtT9+fjuYJ5fP7YA+HL396W/+VcAUkkyALwL4DeU0kf72ORpAPeTVDKNAqReoye79xWRmlOXROr9PG7YY/f3oWcJAEv37f48C+CS7l4rB4AfAHiRUhrtLovv3l8AwHV/v8S+Cuqe6+YnhHhJyiIA9wB4p3uT95H6bnyNEGIhhNzbff+7A9SPYRjmhFgwxTDMqKGUHkZqeNYDSKU53oL
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 1080x1080 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"map_vis(pl_powiaty_merged, 'liczba_na_10_tys_mieszkancow', '2021-01-30')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 23,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 1080x1080 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"map_vis(pl_powiaty_merged, 'liczba_na_10_tys_mieszkancow', '2021-02-16')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 24,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "iVBORw0KGgoAAAANSUhEUgAABGoAAAH9CAYAAABC7JpaAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8vihELAAAACXBIWXMAAAsTAAALEwEAmpwYAAEAAElEQVR4nOzdd5yU1b0/8M952vTZMtvbLG3pIB1FOiqKCIIVbIhmFDUmxsSrN8Xk3l9uoldTTMhdNbaEmCgSiA1URARBelc6u2yv08tTz++P3cWFLcwuu8tizvv18iU785QzM7vzfJ/vOed7CKUUDMMwDMMwDMMwDMMwzMXHXewGMAzDMAzDMAzDMAzDMA1YooZhGIZhGIZhGIZhGKaXYIkahmEYhmEYhmEYhmGYXoIlahiGYRiGYRiGYRiGYXoJlqhhGIZhGIZhGIZhGIbpJViihmEYhmEYhmEYhmEYppdgiRqGYRiGYRiGYRiGYZhegiVqmA4hhBQRQmY1/vspQsjLF3Csewghm7uudV2HEPI0IeSv3XyOyYSQI915jt6sI58/IWQxIeSj7m4TwzAMw/RWLAbr0nOwGIzFYAzTq7FEDdNplNJfUkrvu9jtuFRRSjdRSgde7HZcCiilKyilV3dmX0LI3YSQXYSQACGklBDyDCFEaPZ8MiHkn4SQMCGkmBCyqNlzEwkhHxNC6gkhNYSQtwkhmc2en04I2UAI8RNCiuJoCyGE/JoQUtf43zOEENLs+f8ihBwghGiEkKfjON6GxnYFCCH7CCHzznl+UeNrChNCVhNCks//jjEMwzC9HYvBLgyLweL37xCDEULSCCFvEkLKG4/3BSFkwnmO127MRghJJYT8jRDiI4R4CSEr4nvXGKYBS9QwTAc1v8AwlwQrgO8BSAEwAcBMAI83e/6PABQA6QAWA/gTIWRo43NJAF4EkA/ADSAI4NVm+4YBvALgh3G25TsA5gMYCWAEgOsBeJo9fxzAjwC8H+fxHgWQSSl1Nh77r01BTONrKARwZ+NriwBYHudxGYZhGKbXYTHYJedSicHsAHYAGAMgGcDrAN4nhNjbOd75YrZVACob254G4H/jbCfDAGCJGuYCnDs0lRByJSFkS2PmuKRxWGUWISTU7L8IIYSefRjyQmP2+jAhZGazJ5YQQr4mhAQJIScJIR7EgRByPyHkeGMG/l+EkKzGx390TltUQshrjc/1IYRsbDzXx2i4oDQdL58QQgkhSwkhpwF8SgjhCCE/bsz+VxNC3iCEJDRu/zoh5AeN/85u3HdZ48/9G9tFCCHTCCGlzc6TRQh5p7HX4BQh5LvnvNdvNZ4nSAg5RAgZ2+z5XELIqsZ96wghf2h8/ILb2cr7W0wIGdP47zsa9xvS+PN9hJDVbXwursbPI0AI2Q6g3znPU0LIA4SQY409D39sOj9pNkS32efRvEfmM0JIqz2LlNI/NfacKZTSMgArAExq3M8GYCGAn1BKQ5TSzQD+hYbkBiilH1JK36aUBiilEQB/aNq38fntlNK/ADjZ2rlbcTeA5yilpY1teQ7APc2O9zql9EM0BCPnRSndTynVmn4EIALIbfx5MYB3KaWfU0pDAH4CYAEhxBFnWxmGYZheisVgLAZjMVjXxWCU0pOU0ucppRWUUp1S+iIACUCbo67ai9kIIVejIR77IaXUTylVKaV74mwnwwBgiRqmixBC8gB8COAFAKkALgOwl1JaTim1N/0H4J8A/t5s1wlo+IJNAfAzAKvIN9MzqtGQ7XYCWALgN4SQ0edpxwwA/wPgFgCZAIqbzkcpfaZZOwYDqAHwVuOufwOwq7Ed/4WGL/NzTW3c7xo0fLHfA2A6gL5oyMT/oXG7jQCmNdvnZOP/AWAKgE2U0uaBEgghHIB3AewDkI2GHofvEUKuabbZDY2vJRENF7KmQIAH8F7ja81v3L/pPe7Sdray35RW9tvYyj5AQ69JDA2fy72N/53regDj0NDbcQsa3uuuNgXAocZ/FwDQKaVHmz2/D8DQFnu13LczhjYeP55zxYUQ8h4hJAZgG4DPAOxs7VyU0hNo6LUquJDzMQzDML0Li8FYDNbsZxaDtS3uGIwQchkaEjXHO3muiQCOAHi9MXm3gxAy9Xw7MUxzLFHDdJXFAD6hlL7ZmDWuo5Tubb4BIeQJAINw9sWhGsBvG/f5Bxq+1OYAAKX0fUrpCdpgI4CPAEyOox2vUEp3U0plAE8CuJwQkt+sHRYAqwH8jlL6QWOAMw4NGX2ZUvo5Gi7Y53qaUhqmlEYbz/N8YwY+1Hie2xp7GDYCmNx44Z8C4Bl80wMwFa1fRMcBSKWU/qKx1+EkgJcA3NZsm82U0g8opTqAv6DhQgoA4wFkoSFrH6aUxhp7JZrej65sJxofb7rYTEZDUNb0c6v7NQYyCwH8tLGNB9EwrPRcv6KU+iilpwFsQEOw2WUIIUsAjMU3w0/tAPznbOYH0GLUCSFkBICfIv4htq0593x+APbWes3iRSm9Hg3tvQ7AOkqp0ca5ms7HRtQwDMN8u7AYjMVgbe7HYrAz4orBCCFONHzGP6eUntu+eOUAuBoN72MGGkbvrCGEpLS7F8M0wxI1TFfJBXCirScJIdeioZ7G/MaLbJOyc3oMitFwwQMh5FpCyJeNwz99aLgRPd8XXFbjMQAAjRfGOjT0cDT5M4AjlNJfN9vHSykNn9OOc5W0dZ7GfwsA0htHLoTQcIGbjIaelnJCyEC0ffF1A8giDUOWfY2v9yk0zNltUtns3xEA5saLfS6AYvrNFJjmurqdwDfBRQYAHsA/AExqDMQSAOxtZZ/UxvM2fw9be4/PfY3tzQ3uEELIfAC/AnAtpbS28eEQGnoLm3PinGGshJD+aOitfJRSuinO8z1Fvhni/X9tnM8JINRGr9m5xzvU7HhnBcuNQfaHAK4hhNzQkdfGMAzDXPJYDMZisHywGKz5Pp2KwRoTie8C+JJS+j/NHm8zBmtDFEARpfTPjTHa39Hw/k86z34McwZL1DBdpQTnzHdt0njReR3ALZTSknOezj4nk52HhguVCcA7aMi6p1NKEwF8AOB8Iw/K0XDBbTq3DYALQFnjz/+BhvmmS5vtUwEgqXHb5u04V/Ng5qzzNG6vAahq/HkjgJsASLRhHuxGAHehoTDa3laOXQLgFKU0sdl/Dkrpde2/3DP75pHWC+x1dTtBKT2Ohgv4dwF8TikNouHi/h009DgZrexW03je3GaPtfYex6MpmLM2eyyjvR0IIbPR0Ds2l1J6oNlTRwEIhJABzR4biWZDawkhbgCfAPgv2jAXOi60YUWOpiHnDzQ+fAjf9MK1ONd5jje02fHaClQEfPN3eNa5CCF9AZjQ8JoZhmGYbw8Wg7EYjMVgzXQmBmv8vV+Nht/Xs2oyxRmDNbcfZ//OMkyHsUQN01VWAJhFCLmFECKQhqJllzUOH1wD4MfNhoI2lwbgu4QQkRByMxrmH3+AhnmhJjReXBp7g+JZGvBvAJY0ntsE4JcAtlFKixqP8V2c06NEKS1GQ12PnxNCJELIlQDmnuc8bwL4PmkogGdvPM8/mvWobATwMIDPG3/+DMAjaLiI6q0cbzuAACHkCUKIhRDCE0KGEULGxfGat6Mh0PkVIcRGCDETQpoy9l3dziZN+zX1+Hx2zs9naTzWKgBPE0KspKHwXWtz0M+LUlqDhovoHY3v071oI0AFzsyZXwFgIaV0+znHCje26xeN790kAPPQMOQVhJBsAJ8C+COl9P9wDtJQKNCMhiK+pPG9l9pp/hsAHiMNhQOzAPwAwGvNjic2Ho9DQ/BiJg1Dllt7XYMaezwtjfvdgbPnp68AMJcQMrkxAP4FgFWNQR3DMAzz7cFiMBaDsRjsAmIwQogIYCUaRsLc1UbC69zztxez/RMNCci7G9+nm9AwsuyL8x2XYZqwRA3TJRrns16Hhi+9ejT0BIwEMBoNvSfPk2bV/pvtug3AAAC1AP4fgJtow9zqIBou6G8B8AJYhIbibedrx3o0rG7zDhounP3wzRzjW9Ew/PNr0nI45CI0FNWrR0NBvTfOc6pX0HAh+RzAKTQUaHuk2fMb0TD
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 1440x1440 with 2 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"map_vis_cmp_date(pl_powiaty_merged, 'liczba_ozdrowiencow', '2021-01-30', '2021-02-16')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 25,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 1152x432 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"bar_plot_wojewodztwa(pl_powiaty_merged, 'liczba_ozdrowiencow', '2021-02-16')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 26,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 3600x1440 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"wojewodztwo_line_plot(pl_powiaty_merged, 'liczba_ozdrowiencow')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"## Zgony"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 27,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"name": "stderr",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"C:\\Users\\Filip\\anaconda3\\lib\\site-packages\\mapclassify\\classifiers.py:234: UserWarning: Warning: Not enough unique values in array to form k classes\n",
|
||
|
|
" Warn(\n",
|
||
|
|
"C:\\Users\\Filip\\anaconda3\\lib\\site-packages\\mapclassify\\classifiers.py:237: UserWarning: Warning: setting k to 3\n",
|
||
|
|
" Warn(\"Warning: setting k to %d\" % k_q, UserWarning)\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 1080x1080 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"map_vis(pl_powiaty_merged, 'zgony', '2021-02-16')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 28,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"name": "stderr",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"C:\\Users\\Filip\\anaconda3\\lib\\site-packages\\mapclassify\\classifiers.py:234: UserWarning: Warning: Not enough unique values in array to form k classes\n",
|
||
|
|
" Warn(\n",
|
||
|
|
"C:\\Users\\Filip\\anaconda3\\lib\\site-packages\\mapclassify\\classifiers.py:237: UserWarning: Warning: setting k to 2\n",
|
||
|
|
" Warn(\"Warning: setting k to %d\" % k_q, UserWarning)\n",
|
||
|
|
"C:\\Users\\Filip\\anaconda3\\lib\\site-packages\\mapclassify\\classifiers.py:234: UserWarning: Warning: Not enough unique values in array to form k classes\n",
|
||
|
|
" Warn(\n",
|
||
|
|
"C:\\Users\\Filip\\anaconda3\\lib\\site-packages\\mapclassify\\classifiers.py:237: UserWarning: Warning: setting k to 3\n",
|
||
|
|
" Warn(\"Warning: setting k to %d\" % k_q, UserWarning)\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 1440x1440 with 2 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"map_vis_cmp_columns(\n",
|
||
|
|
" pl_powiaty_merged, \n",
|
||
|
|
" 'zgony_w_wyniku_covid_bez_chorob_wspolistniejacych', \n",
|
||
|
|
" 'zgony_w_wyniku_covid_i_chorob_wspolistniejacych', \n",
|
||
|
|
" '2021-02-16')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 29,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 1152x432 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"bar_plot_wojewodztwa(pl_powiaty_merged, 'zgony', '2021-02-16')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 30,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 3600x1440 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"wojewodztwo_line_plot(pl_powiaty_merged, 'zgony')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"# Podsumowanie"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"Projekt przedstawia wizualizacje danych statystycznych na temat korona wirusa w Polsce.\n",
|
||
|
|
"\n",
|
||
|
|
"Uzyte w projekcie mapy pozwalaja na lepsze zwizualizowanie obszarow dotknietych epidemia"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"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": "3.8.5"
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"nbformat": 4,
|
||
|
|
"nbformat_minor": 4
|
||
|
|
}
|