Let’s discuss how to drop one or multiple columns in Pandas Dataframe. To Delete a column from a Pandas DataFrame or Drop one or more than one column from a DataFrame can be achieved in multiple ways.
Create a simple Dataframe with dictionary of lists, say column names are A, B, C, D, E. In this article, we will cover 6 different methods to delete some columns from Pandas DataFrame.
Python3
# Import pandas packageimport pandas as pd# create a dictionary with five fields eachdata = { 'A': ['A1', 'A2', 'A3', 'A4', 'A5'], 'B': ['B1', 'B2', 'B3', 'B4', 'B5'], 'C': ['C1', 'C2', 'C3', 'C4', 'C5'], 'D': ['D1', 'D2', 'D3', 'D4', 'D5'], 'E': ['E1', 'E2', 'E3', 'E4', 'E5']}# Convert the dictionary into DataFramedf = pd.DataFrame(data)df |
Output:
Drop Columns from a Dataframe using drop() method
Example 1: Remove specific single columns.
Python3
# Import pandas packageimport pandas as pd# create a dictionary with five fields eachdata = { 'A': ['A1', 'A2', 'A3', 'A4', 'A5'], 'B': ['B1', 'B2', 'B3', 'B4', 'B5'], 'C': ['C1', 'C2', 'C3', 'C4', 'C5'], 'D': ['D1', 'D2', 'D3', 'D4', 'D5'], 'E': ['E1', 'E2', 'E3', 'E4', 'E5']}# Convert the dictionary into DataFramedf = pd.DataFrame(data)# Remove column name 'A'df.drop(['A'], axis=1) |
Output:
Example 2: Remove specific multiple columns.
Python3
# Import pandas packageimport pandas as pd# create a dictionary with five fields eachdata = { 'A': ['A1', 'A2', 'A3', 'A4', 'A5'], 'B': ['B1', 'B2', 'B3', 'B4', 'B5'], 'C': ['C1', 'C2', 'C3', 'C4', 'C5'], 'D': ['D1', 'D2', 'D3', 'D4', 'D5'], 'E': ['E1', 'E2', 'E3', 'E4', 'E5']}# Convert the dictionary into DataFramedf = pd.DataFrame(data)# Remove two columns name is 'C' and 'D'df.drop(['C', 'D'], axis=1)# df.drop(columns =['C', 'D']) |
Output:
Example 3: Remove columns based on column index.
Python3
# Import pandas packageimport pandas as pd# create a dictionary with five fields eachdata = { 'A': ['A1', 'A2', 'A3', 'A4', 'A5'], 'B': ['B1', 'B2', 'B3', 'B4', 'B5'], 'C': ['C1', 'C2', 'C3', 'C4', 'C5'], 'D': ['D1', 'D2', 'D3', 'D4', 'D5'], 'E': ['E1', 'E2', 'E3', 'E4', 'E5']}# Convert the dictionary into DataFramedf = pd.DataFrame(data)# Remove three columns as index basedf.drop(df.columns[[0, 4, 2]], axis=1, inplace=True)df |
Output:
Drop Columns from a Dataframe using iloc[] and drop() method.
Remove all columns between a specific column to another column.
Python3
# Import pandas packageimport pandas as pd# create a dictionary with five fields eachdata = { 'A': ['A1', 'A2', 'A3', 'A4', 'A5'], 'B': ['B1', 'B2', 'B3', 'B4', 'B5'], 'C': ['C1', 'C2', 'C3', 'C4', 'C5'], 'D': ['D1', 'D2', 'D3', 'D4', 'D5'], 'E': ['E1', 'E2', 'E3', 'E4', 'E5']}# Convert the dictionary into DataFramedf = pd.DataFrame(data)# Remove all columns between column index 1 to 3df.drop(df.iloc[:, 1:3], inplace=True, axis=1)df |
Output:
Method 3: Drop Columns from a Dataframe using ix() and drop() method.
Remove all columns between a specific column name to another column’s name.
Python3
# Import pandas packageimport pandas as pd# create a dictionary with five fields eachdata = { 'A': ['A1', 'A2', 'A3', 'A4', 'A5'], 'B': ['B1', 'B2', 'B3', 'B4', 'B5'], 'C': ['C1', 'C2', 'C3', 'C4', 'C5'], 'D': ['D1', 'D2', 'D3', 'D4', 'D5'], 'E': ['E1', 'E2', 'E3', 'E4', 'E5']}# Convert the dictionary into DataFramedf = pd.DataFrame(data)# Remove all columns between column name 'B' to 'D'df.drop(df.ix[:, 'B':'D'].columns, axis=1) |
Output:
Method 4: Drop Columns from a Dataframe using loc[] and drop() method.
Remove all columns between a specific column name to another column’s name.
Python3
# Import pandas packageimport pandas as pd# create a dictionary with five fields eachdata = { 'A': ['A1', 'A2', 'A3', 'A4', 'A5'], 'B': ['B1', 'B2', 'B3', 'B4', 'B5'], 'C': ['C1', 'C2', 'C3', 'C4', 'C5'], 'D': ['D1', 'D2', 'D3', 'D4', 'D5'], 'E': ['E1', 'E2', 'E3', 'E4', 'E5']}# Convert the dictionary into DataFramedf = pd.DataFrame(data)# Remove all columns between column name 'B' to 'D'df.drop(df.loc[:, 'B':'D'].columns, axis=1) |
Output:
Note: Different loc() and iloc() is iloc() exclude last column range element.
Method 5: Drop Columns from a Dataframe in an iterative way.
Remove all columns between a specific column name to another column’s name.
Python3
# Import pandas packageimport pandas as pd# create a dictionary with five fields eachdata = { 'A': ['A1', 'A2', 'A3', 'A4', 'A5'], 'B': ['B1', 'B2', 'B3', 'B4', 'B5'], 'C': ['C1', 'C2', 'C3', 'C4', 'C5'], 'D': ['D1', 'D2', 'D3', 'D4', 'D5'], 'E': ['E1', 'E2', 'E3', 'E4', 'E5']}# Convert the dictionary into DataFramedf = pd.DataFrame(data)for col in df.columns: if 'A' in col: del df[col]df |
Output:
Method 6: Python dataframe.pop() method
Python3
# Import pandas packageimport pandas as pd# create a dictionary with five fields eachdata = { 'A': ['A1', 'A2', 'A3', 'A4', 'A5'], 'B': ['B1', 'B2', 'B3', 'B4', 'B5'], 'C': ['C1', 'C2', 'C3', 'C4', 'C5'], 'D': ['D1', 'D2', 'D3', 'D4', 'D5'], 'E': ['E1', 'E2', 'E3', 'E4', 'E5']}# Convert the dictionary into DataFramedf = pd.DataFrame(data)df.pop('B')df |
Output:
A C D E
0 A1 C1 D1 E1
1 A2 C2 D2 E2
2 A3 C3 D3 E3
3 A4 C4 D4 E4
4 A5 C5 D5 E5
