如何按组大小对分组熊猫数据帧进行排序？
在本文中，我们将讨论如何根据熊猫的群体大小对分组数据进行排序。
使用的功能
在这里，我们将输入作为字典数据结构通过列表传递。
- group by():group by()用于根据列值对数据进行分组。
- size(): 这个用来获取数据帧的大小。
- 【sort_values():此函数按传递列的升序或降序对数据框进行排序。
任务很简单，对于给定的数据帧，首先我们需要根据需求按任意列分组，然后根据列的大小排列分组后的值。这里的大小是指一个值在一列中出现的次数或出现的频率。
*例 1:*
蟒蛇 3
# importing pandas module for dataframe
import pandas as pd
# creating a dataframe with student
# name and subject
dataframe1 = pd.DataFrame({'student_name': ['bobby', 'ojaswi', 'gnanesh',
'rohith', 'karthik', 'sudheer',
'vani'],
'subjects': ['dbms', 'python', 'dbms', 'oops',
'oops', 'oops', 'dbms']})
# display dataframe
print(dataframe1)
# group the data on subjects column based on
# size and sort in descending order
a = dataframe1.groupby('subjects').size().sort_values(ascending=False)
# group the data on subjects column based on
# size and sort in ascending order
b = dataframe1.groupby('subjects').size().sort_values(ascending=True)
print(a, b)
*输出:*
*例 2:*
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# importing pandas module for dataframe
import pandas as pd
# creating a dataframe with student name
# , subject and address
dataframe1 = pd.DataFrame({'student_name': ['bobby', 'ojaswi', 'gnanesh',
'rohith', 'karthik', 'sudheer',
'vani'],
'subjects': ['dbms', 'python', 'dbms', 'oops',
'oops', 'oops', 'dbms'],
'address': ['ponnur', 'ponnur', 'hyd', 'tenali',
'tenali', 'hyd', 'patna']})
# display dataframe
print(dataframe1)
# group the data on address column based
# on size and sort in descending order
a = dataframe1.groupby('address').size().sort_values(ascending=False)
# group the data on address column based
# on size and sort in ascending order
b = dataframe1.groupby('address').size().sort_values(ascending=True)
print(a, b)
输出:
我们还可以对多个列进行分组。语法保持不变，但是我们需要在列表中传递多个列，并在 groupby()中传递列表
*语法:*
dataframe.groupby([column1，column2，。列 n])。大小()。排序值(升序=真)
*例 3:*
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# importing pandas module for dataframe
import pandas as pd
# creating a dataframe with student
# name , subject and address
dataframe1 = pd.DataFrame({'student_name': ['bobby', 'ojaswi', 'gnanesh',
'rohith', 'karthik', 'sudheer',
'vani'],
'subjects': ['dbms', 'python', 'dbms', 'oops',
'oops', 'oops', 'dbms'],
'address': ['ponnur', 'ponnur', 'hyd', 'tenali',
'tenali', 'hyd', 'patna']})
# display dataframe
print(dataframe1)
# group the data on address and subjects
# column based on size and sort in descending
# order
a = dataframe1.groupby(['address', 'subjects']
).size().sort_values(ascending=False)
# group the data on address and subjects
# column based on size and sort in ascending
# order
b = dataframe1.groupby(['address', 'subjects']
).size().sort_values(ascending=True)
print(a, b)
*输出:*
