A DataFrame is a two-dimensional data structure in which data is aligned in rows and columns. In this Answer, we'll learn how to find the common rows between two DataFrames using the `merge()` function in Python pandas.
df1.merge(df2, how = 'inner' ,indicator=False)
In the syntax above, df1 and df2 are two DataFrames.
We pass inner as a value to the how parameter to get the common rows between two DataFrames. This operation is similar to InnerJoin in SQL.
import pandas as pd#data frame 1classA = pd.DataFrame({"Student": ['John', 'Lexi', 'Augustin', 'Jane', 'Kate'],"Age": [18, 17, 19, 17, 18]})#data frame 2classB = pd.DataFrame({"Student": ['John', 'Lexi', 'Bob', 'karl', 'Kate', 'Jane'],"Age": [18, 17, 16, 19, 18, 20]})#get uncommon rowsprint(classA.merge(classB, how = 'inner' ,indicator=False))
In the above code snippet,
pandas module, which contains methods to create DataFrames and modify them.classA and classB by merging both DataFrames using the merge() method and passing inner as the value to the how parameter.Free Resources