Intersection of two pandas dataframes based on column entries

Intersection of two pandas dataframes based on column entries

You can find the intersection of two pandas DataFrames based on specific column entries using the merge() function. This operation will return rows that have the same values in the specified column(s) in both DataFrames. Here's how you can do it:

import pandas as pd

# Sample data
data1 = {'ID': [1, 2, 3, 4],
         'Value': ['A', 'B', 'C', 'D']}

data2 = {'ID': [3, 4, 5, 6],
         'Value': ['C', 'D', 'E', 'F']}

df1 = pd.DataFrame(data1)
df2 = pd.DataFrame(data2)

# Merge DataFrames based on 'Value' column
intersection = df1.merge(df2, on='Value', how='inner')

print(intersection)

In this example, the merge() function is used to find the intersection of df1 and df2 based on the 'Value' column. The on parameter specifies the column on which the merge should be performed, and the how parameter is set to 'inner' to get only the rows that have the same 'Value' in both DataFrames.

The output will be:

   ID_x Value  ID_y
0     3     C     3
1     4     D     4

The resulting DataFrame shows the intersection of rows based on the 'Value' column.

Remember that the column names in the result DataFrame might include suffixes (_x and _y) to distinguish between the same column names in the original DataFrames. You can handle these suffixes if needed, or rename the columns as necessary.

Examples

  1. "Pandas intersection of dataframes based on column values"

    Description: This query aims to find common rows between two pandas DataFrames based on specific column entries.

    import pandas as pd

# Sample DataFrames
df1 = pd.DataFrame({'A': [1, 2, 3, 4], 'B': ['a', 'b', 'c', 'd']})
df2 = pd.DataFrame({'A': [3, 4, 5, 6], 'B': ['c', 'd', 'e', 'f']})

intersection = pd.merge(df1, df2, on=['A', 'B'], how='inner')
print(intersection)

  2. "Pandas find common rows in dataframes by column values"

    Description: This query is about finding rows that have common values in specific columns across two pandas DataFrames.

    import pandas as pd

# Sample DataFrames
df1 = pd.DataFrame({'A': [1, 2, 3, 4], 'B': ['a', 'b', 'c', 'd']})
df2 = pd.DataFrame({'A': [3, 4, 5, 6], 'B': ['c', 'd', 'e', 'f']})

common_rows = df1[df1.isin(df2).all(axis=1)]
print(common_rows)

  3. "Pandas intersect dataframes based on column entries"

    Description: This query seeks to intersect two pandas DataFrames based on common values in specified columns.

    import pandas as pd

# Sample DataFrames
df1 = pd.DataFrame({'A': [1, 2, 3, 4], 'B': ['a', 'b', 'c', 'd']})
df2 = pd.DataFrame({'A': [3, 4, 5, 6], 'B': ['c', 'd', 'e', 'f']})

intersection = pd.merge(df1, df2, on=['A', 'B'], how='inner')
print(intersection)

  4. "Pandas intersection of dataframes by column values"

    Description: This query focuses on finding the intersection of two pandas DataFrames based on common values in specified columns.

    import pandas as pd

# Sample DataFrames
df1 = pd.DataFrame({'A': [1, 2, 3, 4], 'B': ['a', 'b', 'c', 'd']})
df2 = pd.DataFrame({'A': [3, 4, 5, 6], 'B': ['c', 'd', 'e', 'f']})

intersection = pd.merge(df1, df2, on=['A', 'B'], how='inner')
print(intersection)

  5. "Pandas common rows in dataframes by column entries"

    Description: This query looks for a way to find rows with common values in specific columns across two pandas DataFrames.

    import pandas as pd

# Sample DataFrames
df1 = pd.DataFrame({'A': [1, 2, 3, 4], 'B': ['a', 'b', 'c', 'd']})
df2 = pd.DataFrame({'A': [3, 4, 5, 6], 'B': ['c', 'd', 'e', 'f']})

common_rows = df1[df1.isin(df2).all(axis=1)]
print(common_rows)

  6. "Pandas find common entries in dataframes based on columns"

    Description: This query seeks a method to identify common entries between two pandas DataFrames, focusing on specific columns.

    import pandas as pd

# Sample DataFrames
df1 = pd.DataFrame({'A': [1, 2, 3, 4], 'B': ['a', 'b', 'c', 'd']})
df2 = pd.DataFrame({'A': [3, 4, 5, 6], 'B': ['c', 'd', 'e', 'f']})

common_entries = pd.merge(df1, df2, on=['A', 'B'], how='inner')
print(common_entries)

  7. "Pandas intersection of dataframes by column values without duplicates"

    Description: Users might seek a solution to find the intersection of two pandas DataFrames based on specific columns while avoiding duplicate rows.

    import pandas as pd

# Sample DataFrames
df1 = pd.DataFrame({'A': [1, 2, 3, 4], 'B': ['a', 'b', 'c', 'd']})
df2 = pd.DataFrame({'A': [3, 4, 5, 6], 'B': ['c', 'd', 'e', 'f']})

intersection = pd.merge(df1, df2, on=['A', 'B'], how='inner').drop_duplicates()
print(intersection)

  8. "Pandas intersect dataframes based on column values"

    Description: This query is about finding the intersection of two pandas DataFrames based on common values in specified columns.

    import pandas as pd

# Sample DataFrames
df1 = pd.DataFrame({'A': [1, 2, 3, 4], 'B': ['a', 'b', 'c', 'd']})
df2 = pd.DataFrame({'A': [3, 4, 5, 6], 'B': ['c', 'd', 'e', 'f']})

intersection = pd.merge(df1, df2, on=['A', 'B'], how='inner')
print(intersection)

  9. "Pandas common rows in dataframes by column entries"

    Description: This query is about finding rows with common values in specific columns across two pandas DataFrames.

    import pandas as pd

# Sample DataFrames
df1 = pd.DataFrame({'A': [1, 2, 3, 4], 'B': ['a', 'b', 'c', 'd']})
df2 = pd.DataFrame({'A': [3, 4, 5, 6], 'B': ['c', 'd', 'e', 'f']})

common_rows = df1[df1.isin(df2).all(axis=1)]
print(common_rows)

  10. "Pandas intersection of dataframes by column entries"

    Description: This query seeks to find the intersection of two pandas DataFrames based on common values in specified columns.

    import pandas as pd

# Sample DataFrames
df1 = pd.DataFrame({'A': [1, 2, 3, 4], 'B': ['a', 'b', 'c', 'd']})
df2 = pd.DataFrame({'A': [3, 4, 5, 6], 'B': ['c', 'd', 'e', 'f']})

intersection = pd.merge(df1, df2, on=['A', 'B'], how='inner')
print(intersection)

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