Comments (1)
To maybe add a common use case. Here the goal is to add the biological domain to the favorite animal of certain people:
import pandas as pd
# Create the first DataFrame with person names and favorite animals
df1_data = {
'Person': ['John', 'Emma', 'Alex','Darleen'],
'Animal': ['Dog', 'Spider', 'Snake','Cat']
}
df1 = pd.DataFrame(df1_data)
# Create the second DataFrame with mapping of animals to biological class
df2_data = {
'Animal': ['Dog', 'Snake', 'Cat'],
'Biological_Class': ['Mammal', 'Reptile', 'Mammal']
}
df2 = pd.DataFrame(df2_data)
# Merge the DataFrames on the 'Animal' column
merged_df = pd.merge(
df1,
df2,
on='Animal',
validate='m:1'
)
The merged_df
will lack the favorite animal of Emma, as 'Spider' has no class defined in df2
. With the proposed feature validate
could be set to m:1+left_total
. This would raise an error as not all keys from the left df1
are contained in the right df2
.
from pandas.
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from pandas.