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- import numpy as np
- import pandas as pd
- import matplotlib.pyplot as plt
- def importIMGW(miasto):
- data=pd.read_csv(str(miasto)+'_2018.csv',sep=',',decimal='.',
- parse_dates=[[2,3,4]],usecols=[2,3,4,5,7,9],header=None,
- index_col=0,dtype={5:'float64',7:'float64',9:'float64'})
- data.columns=['tMin','tMax','tMean']
- data.index.names=['Data']
- return data
- gorzow = importIMGW('Gorzow')
- kasprowy = importIMGW('Kasprowy')
- krakow = importIMGW('Krakow')
- suwalki = importIMGW('Suwalki')
- ustka = importIMGW('Ustka')
- # 1
- mean = pd.DataFrame({'Gorzow': gorzow['tMean'], 'Suwalki': suwalki['tMean'], 'Kasprowy': kasprowy['tMean']})
- mean.plot()
- plt.show()
- # 2
- krakow_max = krakow['tMax'].resample('M').mean()
- suwalki_max = suwalki['tMax'].resample('M').mean()
- maks = pd.DataFrame({'Krakow': krakow_max, 'Suwalki': suwalki_max})
- maks = maks.set_index(maks.index.month_name())
- maks.plot.bar()
- plt.show()
- # 3
- kasprowy_summer = kasprowy['tMean']['22-06-2018':'23-09-2018']
- ustka_summer = ustka['tMean']['22-06-2018':'23-09-2018']
- lato = pd.DataFrame({'Kasprowy': kasprowy_summer, 'Ustka': ustka_summer})
- lato.plot.hist()
- plt.show()
- # 4
- tmin = pd.DataFrame({'Gorzow': gorzow['tMin'], 'Kasprowy': kasprowy['tMin'], 'Krakow': krakow['tMin'],\
- 'Suwalki': suwalki['tMin'], 'Ustka': ustka['tMin']})
- correlation = tmin.corr()
- print(correlation)
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