Python | Панды Series.describe ()

Опубликовано: 27 Марта, 2022

Серия Pandas - это одномерный массив ndarray с метками осей. Этикетки не обязательно должны быть уникальными, но должны быть хешируемого типа. Объект поддерживает индексирование как на основе целых чисел, так и на основе меток и предоставляет множество методов для выполнения операций, связанных с индексом.

Pandas Series.describe() function generate a descriptive statistics that summarize the central tendency, dispersion and shape of a dataset’s distribution for the given series object. All the calculations are performed by excluding NaN values.

Syntax: Series.describe(percentiles=None, include=None, exclude=None)
Parameter :
percentiles : The percentiles to include in the output.
include : A white list of data types to include in the result. Ignored for Series.
exclude : A black list of data types to omit from the result. Ignored for Series
Returns : Summary statistics of the Series

Example #1: Use Series.describe() function to find the summary statistics of the given series object.

# importing pandas as pd
import pandas as pd
  
# Creating the Series
sr = pd.Series([80, 25, 3, 25, 24, 6])
  
# Create the Index
index_ = ["Coca Cola", "Sprite", "Coke", "Fanta", "Dew", "ThumbsUp"]
  
# set the index
sr.index = index_
  
# Print the series
print(sr)

Выход :

Now we will use Series.describe() function to find the summary statistics of the underlying data in the given series object.

# find summary statistics of the underlying 
# data in the given series object.
result = sr.describe()
  
# Print the result
print(result)

Output :

As we can see in the output, the Series.describe() function has successfully returned the summary statistics of the given series object.

Example #2 : Use Series.describe() function to find the summary statistics of the underlying data in the given series object. The given series object contains some missing values.

# importing pandas as pd
import pandas as pd
  
# Creating the Series
sr = pd.Series([100, None, None, 18, 65, None, 32, 10, 5, 24, None])
  
# Create the Index
index_ = pd.date_range("2010-10-09", periods = 11, freq ="M")
  
# set the index
sr.index = index_
  
# Print the series
print(sr)

Выход :

Now we will use Series.describe() function to find the summary statistics of the underlying data in the given series object.

# find summary statistics of the underlying 
# data in the given series object.
result = sr.describe()
  
# Print the result
print(result)

Выход :

As we can see in the output, the Series.describe() function has successfully returned the summary statistics of the given series object. NaN values has been ignored while calculating these statistical values.

Внимание компьютерщик! Укрепите свои основы с помощью базового курса программирования Python и изучите основы.

Для начала подготовьтесь к собеседованию. Расширьте свои концепции структур данных с помощью курса Python DS. А чтобы начать свое путешествие по машинному обучению, присоединяйтесь к курсу Машинное обучение - базовый уровень.

Python

Python | Панды Series.describe ()

РЕКОМЕНДУЕМЫЕ СТАТЬИ