pandas

#Задания 1
import pandas as pd


name_magazine = ("eqwdfszx", "bgfdvscz", "bvvtgf", "sbtygfdfvsd", "asdf")
number_of_copies = [8000, 14000, 20000, 9000, 16000]
price = [1100, 1000, 1200, 500, 1300]

magazine_dict = {k: v for k, v in zip(name_magazine, {k: v for k, v in zip(number_of_copies, price)}.items())}

df = pd.DataFrame.from_dict(magazine_dict, orient='index', columns=['number_of_copies', 'price'])

print(df)

# search
print(f"\nbvvtgf price: {df.get('price').get('bvvtgf')}\n")

# агрегація
print(f"Count: \n{df.count()}\n")

print(f"Mean: \n\t{df[['price']].mean()}")
print(f"\t{df[['number_of_copies']].mean()}\n")

print(f"Min: \n\t{df[['price']].min()}")
print(f"\t{df[['number_of_copies']].min()}\n")

print(f"Max: \n\t{df[['price']].max()}")
print(f"\t{df[['number_of_copies']].max()}\n")

# групування
print(f"{df.groupby('price').mean()}")



#Задания 2
import calendar
import pandas as pd
import matplotlib.pyplot as plt


fixed_df = pd.read_csv('comptagevelo2009.csv', parse_dates=['Date'], encoding='latin1', dayfirst=True, index_col='Date')

Berri1 = pd.DataFrame(fixed_df['Berri1'])
Berri1['month'] = Berri1.index.month

Berri1_sum = Berri1.groupby(['month']).sum()
Berri1_sum.index = ['January', 'February', 'March', 'April', 'May', 'June',
                    'July', 'August', 'September', 'October', 'November', 'December']

print(f"The most popular month on the track Berri1: {Berri1_sum['Berri1'].idxmax()}")

print(f"The most popular day of the week on the track Berri1: {calendar.day_name[Berri1['Berri1'].idxmax().weekday()]}")

input("Press Enter to show diagrams.. ")

plt.style.use('ggplot')
plt.rcParams['figure.figsize'] = (15, 5)

Berri1['Berri1'].plot(figsize=(15, 10))

Berri1_sum.plot(kind='bar')

plt.show()