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In Pandas, you can delete one or more columns from a DataFrame using methods like drop(), del, or pop(). The most flexible and recommended approach is drop() because it supports multiple columns, in-place modification, and error handling.
Example:
import pandas as pd# Sample DataFramedf = pd.DataFrame({'Name': ['Alice', 'Bob', 'Charlie'],'Age': [25, 30, 35],'City': ['NY', 'LA', 'Chicago']})print("Original DataFrame:")print(df)# Remove 'City' column in-placedf.drop(columns=['City'], inplace=True)print("\nAfter deleting 'City' column:")print(df)コピーしました。✕コピーOutput:
Original DataFrame:Name Age City0 Alice 25 NY1 Bob 30 LA2 Charlie 35 ChicagoAfter deleting 'City' column:Name Age0 Alice 251 Bob 302 Charlie 35コピーしました。✕コピーUsing drop()
Syntax:
df.drop(columns=['col1', 'col2'], inplace=True)コピーしました。✕コピーSupports removing multiple columns at once.
Use errors='ignore' to avoid exceptions if a column is missing.
Using del keyword
Syntax:
del df['col_name']コピーしました。✕コピーDeletes a single column directly.
python - Delete a column from a Pandas DataFrame
2012年11月16日 · To remove multiple columns col1, col2, . . . , coln, we have to …
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使用例del df['column_name']How to Delete a column from Pandas DataFrame
2025年7月15日 · Not all attributes (columns) are useful to generate insights, so it's better to delete those columns from the DataFrame. Deleting a column in Pandas …
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