如何在Pandas中合并不同长度的DataFrames

在这篇文章中，我们将讨论如何在Pandas中合并两个不同长度的数据帧。它可以使用merge()方法来完成。

语法:

DataFrame.merge(parameters)

下面是一些例子，描述了如何使用上述方法合并不同长度的数据帧。

示例 1:

下面是一个合并两个不同长度的学生数据框架的程序。

# importing pandas module
  
import pandas as pd
  
# create a list that contains 
# student id of subject 1
list1 = [7058, 7059, 7075, 7076]
  
# create a list that contains
# student id of subject 2
list2 = [7058, 7059, 7012, 7075, 7076]
  
# create a list that contains 
# student names of subject 1
list11 = ["Sravan", "Jyothika", "Deepika",
          "Kyathi"]
  
# create a list that contains 
# student names of subject 2
list22 = ["Sravan", "Jyothika", "Salma", 
          "Deepika", "Kyathi"]
  
  
# pass list1 and list11 to the
# dataframe1
dataframe1 = pd.DataFrame(
  {"Student ID": list1, "Student Name": list11})
print('First data frame:')
display(dataframe1)
  
# pass list2 and list22 to the
# dataframe1
dataframe2 = pd.DataFrame(
  {"Student ID": list2, "Student Name": list22})
print('Second data frame:')
display(dataframe2)
  
# apply merge function to merge the
# two dataframes
mergedf = dataframe2.merge(dataframe1, how='left')
print('Merged data frame:')
display(mergedf)

输出:

如何在Pandas中合并不同长度的DataFrames？

示例 2:

下面是另一个程序，用于合并一个长度为4的数据框和另一个长度为9的数据框。

# importing pandas module
import pandas as pd
  
# create a list that contains
# student id of subject 1
list1 = [7058, 7059, 7075, 7076]
  
# create a list that contains
# student id of subject 2
list2 = [7058, 7059, 7012, 7075, 7076,
         7034, 7046, 7036, 7015]
  
# create a list that contains
# student names of subject 1
list11 = ["Sravan", "Jyothika", "Deepika",
          "Kyathi"]
  
# create a list that contains
# student names of subject 2
list22 = ["Sravan", "Jyothika", "salma", 
          "Deepika", "Kyathi", "meghana",
          "pranathi", "bhanu", "keshav"]
  
  
# pass list1 and list11 to the
# dataframe1
dataframe1 = pd.DataFrame(
  {"Student ID": list1, "Student Name": list11})
print('First data frame:')
display(dataframe1)
  
# pass list2 and list22 to the 
# dataframe1
dataframe2 = pd.DataFrame(
  {"Student ID": list2, "Student Name": list22})
print('Second data frame:')
display(dataframe2)
  
# apply merge function to merge
# the two dataframes
mergedf = dataframe2.merge(dataframe1, how='inner')
print('Merged data frame:')
display(mergedf)