极客教程如何按组大小对分组的Pandas数据框进行排序
在这篇文章中，我们将讨论如何在Pandas中根据组的大小对分组数据进行排序。
用到的方法
在这里，我们将通过列表将输入作为一个字典数据结构。
- groupby(): groupby()是用来根据列值对数据进行分组。
- size(): 这是用来获取数据框的大小。
- sort_values()): 该函数按照所传递的Column的升序或降序对数据框进行排序。
这个任务很简单，对于一个给定的数据框架，首先我们需要根据要求对任何一列进行分组，然后根据它们的大小来排列分组后的值。这里的大小是指一个值在一列中出现的次数或其频率。
示例 1:
# 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)
Python
输出:
示例 2:
# 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)
Python
输出:
我们还可以对多列进行分组。语法保持不变，但我们需要把多列放在一个列表中，并在groupby()中传递该列表
语法:
dataframe.groupby([column1,column2,.column n]).size().sort_values(ascending=True)
Python
示例 3:
# 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)
Python
输出:
