在 Pandas 中执行交叉连接的Python程序

在 Pandas 中，有一些参数可以在两个 DataFrame 或 Series 上执行左、右、内或外合并和连接。但是，到目前为止，还不可能使用how="cross"参数执行交叉连接来合并或连接两种方法。

交叉连接：

示例 1：

上面的例子证明如下

# importing pandas module
import pandas as pd 
   
# Define a dictionary with column A
data1 = {'A': [1, 2]} 
     
# Define another dictionary with column B
data2 = {'B': ['a', 'b', 'c']}  
   
# Convert the dictionary into DataFrame  
df = pd.DataFrame(data1, index =[0, 1])
   
# Convert the dictionary into DataFrame  
df1 = pd.DataFrame(data2, index =[2, 3, 4]) 
  
# Now to perform cross join, we will create
# a key column in both the DataFrames to 
# merge on that key.
df['key'] = 1
df1['key'] = 1
  
# to obtain the cross join we will merge 
# on the key and drop it.
result = pd.merge(df, df1, on ='key').drop("key", 1)
  
result

数据框 1：
数据框 2：
输出 ：

示例 2：

交叉连接用户和产品的两个 DataFrame。

# importing pandas module
import pandas as pd 
   
# Define a dictionary containing user ID
data1 = {'Name': ["Rebecca", "Maryam", "Anita"],
        'UserID': [1, 2, 3]} 
     
# Define a dictionary containing product ID 
data2 = {'ProductID': ['P1', 'P2', 'P3', 'P4']} 
   
# Convert the dictionary into DataFrame  
df = pd.DataFrame(data1, index =[0, 1, 2])
   
# Convert the dictionary into DataFrame  
df1 = pd.DataFrame(data2, index =[2, 3, 6, 7]) 
  
# Now to perform cross join, we will create
# a key column in both the DataFrames to 
# merge on that key.
df['key'] = 1
df1['key'] = 1
  
# to obtain the cross join we will merge on 
# the key and drop it.
result = pd.merge(df, df1, on ='key').drop("key", 1)
  
result

数据框 1：
数据框 2：
输出 ：

示例 3：

# importing pandas module
import pandas as pd 
   
# Define a dictionary with two columns
data1 = {'col 1': [0, 1],
        'col 2': [2, 3]} 
     
# Define another dictionary 
data2 = {'col 3': [5, 6],
        'col 4': [7, 8]}  
   
# Convert the dictionary into DataFrame  
df = pd.DataFrame(data1, index =[0, 1])
   
# Convert the dictionary into DataFrame  
df1 = pd.DataFrame(data2, index =[2, 3]) 
  
# Now to perform cross join, we will create
# a key column in both the DataFrames to
# merge on that key.
df['key'] = 1
df1['key'] = 1
  
# to obtain the cross join we will merge on 
# the key and drop it.
result = pd.merge(df, df1, on ='key').drop("key", 1)
  
result

数据框 1：
数据框 2：
输出 ：