Python: Pandas Merge Indicator (Left, Right and Both) Example

When you merge two or more DataFrames in pandas, and you want to have an indicator column to tell the information on the source of each row, then you can make use of the parameter indicator=True along with the pandas.merge() function.

Example: Pandas: Merge Indicator (Left, Right, and Both)

import pandas as pd

data_city_NYC = {
    'City': ['NYC', 'NYC', 'NYC', 'NYC'],
    'Date': ['2023-07-01', '2023-07-02', '2023-07-03', '2023-07-04'],
    'Temp_NYC': [25, 30, 27, 0]
}

data_city_Chicago = {
    'City': ['Chicago', 'Chicago', 'Chicago', 'Chicago'],
    'Date': ['2023-07-01', '2023-07-02', '2023-07-03', '2023-07-06'],
    'Temp_Chicago': [28, 32, 29, 0]
}

df_city_NYC = pd.DataFrame(data_city_NYC).set_index('Date')
df_city_Chicago = pd.DataFrame(data_city_Chicago).set_index('Date')

print("DataFrame: NYC City")
print(df_city_NYC)
print("\nDataFrame: Chicago City")
print(df_city_Chicago)

# Merge both DataFrames on the common column 'Date' and add an indicator
merged_cities_both_df = pd.merge(df_city_NYC, df_city_Chicago, on='Date', how='outer', suffixes=('_NYC', '_Chicago'), indicator=True)

# Merge left DataFrames on the common column 'Date' and add an indicator
merged_cities_left_df = pd.merge(df_city_NYC, df_city_Chicago, on='Date', how='left', suffixes=('_NYC', '_Chicago'), indicator=True)

# Merge right DataFrames on the common column 'Date' and add an indicator
merged_cities_right_df = pd.merge(df_city_NYC, df_city_Chicago, on='Date', how='right', suffixes=('_NYC', '_Chicago'), indicator=True)

print("\nMerged DataFrame Data (Merge Both):")
print(merged_cities_both_df)

print("\nMerged DataFrame Data (Merge Left):")
print(merged_cities_left_df)

print("\nMerged DataFrame Data (Merge Right):")
print(merged_cities_right_df)

DataFrame: NYC City
           City  Temp_NYC
Date                     
2023-07-01  NYC        25
2023-07-02  NYC        30
2023-07-03  NYC        27
2023-07-04  NYC         0

DataFrame: Chicago City
               City  Temp_Chicago
Date                             
2023-07-01  Chicago            28
2023-07-02  Chicago            32
2023-07-03  Chicago            29
2023-07-06  Chicago             0

Merged DataFrame Data (Merge Both):
           City_NYC  Temp_NYC City_Chicago  Temp_Chicago      _merge
Date                                                                
2023-07-01      NYC      25.0      Chicago          28.0        both
2023-07-02      NYC      30.0      Chicago          32.0        both
2023-07-03      NYC      27.0      Chicago          29.0        both
2023-07-04      NYC       0.0          NaN           NaN   left_only
2023-07-06      NaN       NaN      Chicago           0.0  right_only

Merged DataFrame Data (Merge Left):
           City_NYC  Temp_NYC City_Chicago  Temp_Chicago     _merge
Date                                                               
2023-07-01      NYC        25      Chicago          28.0       both
2023-07-02      NYC        30      Chicago          32.0       both
2023-07-03      NYC        27      Chicago          29.0       both
2023-07-04      NYC         0          NaN           NaN  left_only

Merged DataFrame Data (Merge Right):
           City_NYC  Temp_NYC City_Chicago  Temp_Chicago      _merge
Date                                                                
2023-07-01      NYC      25.0      Chicago            28        both
2023-07-02      NYC      30.0      Chicago            32        both
2023-07-03      NYC      27.0      Chicago            29        both
2023-07-06      NaN       NaN      Chicago             0  right_only

Merge Indicator Values