Практическое занятие №53

Практическое занятие №53 (1И)

Тема: Практика вычисления описательных статистических величин в Python Pandas

Цель работы: формирование теоретических и практических навыков работы на языке программирования Python

Оборудование: компьютер с установленной операционной системой Windows, подключение к сети Интернет

Время работы 2 часа

Ход работы

Задание 1.

# Import package

from pandas import DataFrame

# Create DataFrame

cart = {'Product': ['Mobile', 'AC', 'Mobile', 'Sofa', 'Laptop'],

        'Price': [20000, 28000, 22000, 19000, 45000],

         'Year': [2014, 2015, 2016, 2017, 2018]

        }

df = DataFrame(cart, columns = ['Product', 'Price', 'Year'])

# Original DataFrame

print("Original DataFrame:\n", df)

# Describing descriptive statistics of Price

print("\nDescriptive statistics of Price:\n")

stats = df['Price'].describe()

print(stats)

Задание 2.

# Import package

from pandas import DataFrame

# Create DataFrame

cart = {'Product': ['Mobile', 'AC', 'Mobile', 'Sofa', 'Laptop'],

        'Price': [20000, 28000, 22000, 19000, 45000],

         'Year': [2014, 2015, 2016, 2017, 2018]

        }

df = DataFrame(cart, columns = ['Product', 'Price', 'Year'])

# Original DataFrame

print("Original DataFrame:\n", df)

# Describing descriptive statistics of Year

print("\nDescriptive statistics of year:\n")

stats = df['Year'].describe()

print(stats)

Задание 3.

# Import package

from pandas import DataFrame

# Create DataFrame

cart = {'Product': ['Mobile', 'AC', 'Mobile', 'Sofa', 'Laptop'],

        'Price': [20000, 28000, 22000, 19000, 45000],

         'Year': [2014, 2015, 2016, 2017, 2018]

        }

df = DataFrame(cart, columns = ['Product', 'Price', 'Year'])

# Original DataFrame

print("Original DataFrame:\n", df)

# Describing descriptive statistics of whole dataframe

print("\nDescriptive statistics of whole dataframe:\n")

stats = df.describe(include = 'all')

print(stats)

Задание 4.

from pandas import DataFrame

# Create DataFrame

cart = {'Product': ['Mobile', 'AC', 'Mobile', 'Sofa', 'Laptop'],

        'Price': [20000, 28000, 22000, 19000, 45000],

         'Year': [2014, 2015, 2016, 2017, 2018]

        }

df = DataFrame(cart, columns = ['Product', 'Price', 'Year'])

# Original DataFrame

print("Original DataFrame:\n", df)

# Print Count of Price

print("\nCount of Price:\n")

counts = df['Price'].count()

print(counts)

# Print mean of Price

print("\nMean of Price:\n")

m = df['Price'].mean()

print(m)

# Print maximum value of Price

print("\nMaximum value of Price:\n")

mx = df['Price'].max()

print(m)

# Print standard deviation of Price

print("\nStandard deviation of Price:\n")

sd = df['Price'].std()

print(sd)