In Pandas, there are parameters to perform left, right, inner or outer merge and join on two DataFrames or Series. However there’s no possibility as of now to perform a cross join to merge or join two methods using how="cross" parameter.
Cross Join :
Example 1:
The above example is proven as follows
# importing pandas moduleimport pandas as pd # Define a dictionary with column Adata1 = {'A': [1, 2]} # Define another dictionary with column Bdata2 = {'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'] = 1df1['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 |
DataFrame 1: 
DataFrame 2 : 
Output : 
Example 2:
Cross join on two DataFrames for user and product.
# importing pandas moduleimport pandas as pd # Define a dictionary containing user IDdata1 = {'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'] = 1df1['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 |
DataFrame 1: 
DataFrame 2 : 
Output : 
Example 3:
# importing pandas moduleimport pandas as pd # Define a dictionary with two columnsdata1 = {'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'] = 1df1['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 |
DataFrame 1: 
DataFrame 2 : 
Output : 
