- import numpy as np
- import pandas as pd
- import matplotlib.pyplot as plt
- minwlatach = []
- maxwlatach = []
- sprzedawcmin = []
- sprzedawcmax = []
- df = pd.read_csv('zamowienia.csv')
- print(df)
- print(df['Datazamowienia'])
- df['year'] = pd.DatetimeIndex(df['Datazamowienia']).year
- print(df)
- lata = [2003,2004,2005]
- for i in lata:
- ramka = df[((df.year == i) & (df.Utarg > 1000))]
- minwart = ramka.agg({'Utarg':['min']})
- minwlatach.append(int(minwart['Utarg'][0]))
- maxwart = ramka.agg({'Utarg':['max']})
- maxwlatach.append(int(maxwart['Utarg'][0]))
- for i in range(0,3):
- x = 2003 + i;
- nazwa = df[((df.year == x) & (df.Utarg == int(minwlatach[i])))]
- nazwa1 = df[((df.year == x) & (df.Utarg == int(maxwlatach[i])))]
- sprzedawcmin.append(df.loc[[0], ['Sprzedawca']])
- sprzedawcmax.append(df.loc[[1], ['Sprzedawca']])
- print(minwlatach)
- print(maxwlatach)
- print("---------------------")
- print(sprzedawcmin)
- print(sprzedawcmax)
- tabela = pd.DataFrame()
- tabela.loc[:,"Utarg"] = minwlatach + maxwlatach
- tabela.plot.bar()
- plt.title("Wykres")
- plt.text(0, 8000, ' minimalne w latach', style='italic',bbox={'facecolor':'red', 'alpha':0.2, 'pad':10})
- plt.text(0, 5000, '2003', style='italic',bbox={'facecolor':'red', 'alpha':0.2, 'pad':10}, rotation=90)
- plt.text(1, 5000, '2004', style='italic',bbox={'facecolor':'red', 'alpha':0.2, 'pad':10}, rotation=90)
- plt.text(2, 5000, '2005', style='italic',bbox={'facecolor':'red', 'alpha':0.2, 'pad':10}, rotation=90)
- plt.text(3, 19000, ' maksymalne w latach', style='italic',bbox={'facecolor':'red', 'alpha':0.2, 'pad':10})
- plt.text(3, 17000, '2003', style='italic',bbox={'facecolor':'red', 'alpha':0.2, 'pad':10}, rotation=90)
- plt.text(4, 17000, '2004', style='italic',bbox={'facecolor':'red', 'alpha':0.2, 'pad':10}, rotation=90)
- plt.text(5, 17000, '2005', style='italic',bbox={'facecolor':'red', 'alpha':0.2, 'pad':10}, rotation=90)
- plt.xticks(np.arange(6), sprzedawcmin + sprzedawcmax)
- plt.show()