In Python, how to delete a column in a Pandas Dataframe?
In Python, there are several ways to drop a column in a Pandas Dataframe. Let consider the following dataframe as an example:
import pandas as pd
df = pd.DataFrame([[1, 2, 3], [4, 5, 6]], columns = ["col1", "col2", "col3"])
Option 1: use pandas.dataframe.drop.
df = df.drop("col2", axis=1)
Option 2: use pandas.dataframe.drop without having to reassign df thanks to the inplace=True option.
df.drop("col2", axis=1, inplace=True)
Option 3: use del.
del df["col2"]
In Python, there are several ways to drop a column in a Pandas Dataframe. Let consider the following dataframe as an example:
import pandas as pd
df = pd.DataFrame([[1, 2, 3], [4, 5, 6]], columns = ["col1", "col2", "col3"])
Option 1: use pandas.dataframe.drop.
df = df.drop("col2", axis=1)
Option 2: use pandas.dataframe.drop without having to reassign df thanks to the inplace=True option.
df.drop("col2", axis=1, inplace=True)
Option 3: use del.
del df["col2"]
In Python, there are several ways to drop a column in a Pandas Dataframe. Let consider the following dataframe as an example:
import pandas as pd
df = pd.DataFrame([[1, 2, 3], [4, 5, 6]], columns = ["col1", "col2", "col3"])
Option 1: use pandas.dataframe.drop.
df = df.drop("col2", axis=1)
Option 2: use pandas.dataframe.drop without having to reassign df thanks to the inplace=True option.
df.drop("col2", axis=1, inplace=True)
Option 3: use del.
del df["col2"]
In Python, there are several ways to drop a column in a Pandas Dataframe. Let consider the following dataframe as an example:
import pandas as pd
df = pd.DataFrame([[1, 2, 3], [4, 5, 6]], columns = ["col1", "col2", "col3"])
Option 1: use pandas.dataframe.drop.
df = df.drop("col2", axis=1)
Option 2: use pandas.dataframe.drop without having to reassign df thanks to the inplace=True option.
df.drop("col2", axis=1, inplace=True)
Option 3: use del.
del df["col2"]
| # | ID | Query | URL | Count |
|---|---|---|---|---|
| 0 | 13184 | en | https://en.ans.wiki/335/in-python-how-to-delete-a-column-in-a-pandas-dataframe | 5 |