In this article, we will discuss different ways to delete the last column of a pandas dataframe in python.
Table of Contents
- Use iloc to drop last column of pandas dataframe.
- Use drop() to remove last column of pandas dataframe.
- Use del keyword to drop last column of pandas dataframe.
- Use pop() to drop last column of pandas dataframe.
Use iloc to drop last column of pandas dataframe
In Pandas, the Dataframe provides an attribute iloc, to select a part of dataframe using the position based indexing. This selected portion can be a few columns or rows . We can use this attribute to select all the columns except the last one and then assign back the selected columns to the original variable. It will give an effect that we have deleted the last column from the dataframe. For example,
# Drop last column of a dataframe df = df.iloc[: , :-1]
We selected a portion of dataframe, that included all rows, but it selected only n-1 columns i.e. from first to last -1. Then assigned this back to the same variable. So, basically it removed the last column of dataframe.
How did it work?
The syntax of dataframe.iloc[] is like,
df.iloc[row_start:row_end , col_start, col_end]
Arguments:
- row_start: The row index/position from where it should start selection. Default is 0.
- row_end: The row index/position from where it should end the selection i.e. select till row_end-1. Default is till the last row of the dataframe.
- col_start: The column index/position from where it should start selection. Default is 0.
- col_end: The column index/position from where it should end the selection i.e. select till end-1. Default is till the last column of the dataframe.
It returns a portion of dataframe that includes rows from row_start to row_end-1 and columns from col_start to col_end-1.
To delete the last column from dataframe, just selected the columns from position 0 till one before the last column. As we can use the negative indexing, so to select all columns except last one use –> (:-1) i.e. from column at position 0 till -2 i.e. one position less than the last column (-1). To select all the rows use default values i.e. (:) i.e.
# Drop last column of a dataframe df = df.iloc[: , :-1]
Checkout complete example to delete the last column of dataframe,
import pandas as pd
# List of Tuples
empoyees = [('Jack', 34, 'Sydney', 5) ,
('Riti', 31, 'Delhi' , 7) ,
('Aadi', 16, 'London', 11) ,
('Mark', 41, 'Delhi' , 12)]
# Create a DataFrame object
df = pd.DataFrame( empoyees,
columns=['Name', 'Age', 'City', 'Experience'])
print("Contents of the Dataframe : ")
print(df)
# Drop last column of a dataframe
df = df.iloc[: , :-1]
print("Modified Dataframe : ")
print(df)
Output:
Contents of the Dataframe : Name Age City Experience 0 Jack 34 Sydney 5 1 Riti 31 Delhi 7 2 Aadi 16 London 11 3 Mark 41 Delhi 12 Modified Dataframe : Name Age City 0 Jack 34 Sydney 1 Riti 31 Delhi 2 Aadi 16 London 3 Mark 41 Delhi
Use drop() to remove last column of pandas dataframe
In pandas, the dataframe’s drop() function accepts a sequence of column names that it needs to delete from the dataframe. To make sure that it removes the columns only, use argument axis=1 and to make changes in place i.e. in calling dataframe object, pass argument inplace=True.
Checkout complete example to delete the last column of dataframe is as follows,
import pandas as pd
# List of Tuples
empoyees = [('Jack', 34, 'Sydney', 5) ,
('Riti', 31, 'Delhi' , 7) ,
('Aadi', 16, 'London', 11) ,
('Mark', 41, 'Delhi' , 12)]
# Create a DataFrame object
df = pd.DataFrame( empoyees,
columns=['Name', 'Age', 'City', 'Experience'])
print("Contents of the Dataframe : ")
print(df)
# Drop last column
df.drop(columns=df.columns[-1],
axis=1,
inplace=True)
print("Modified Dataframe : ")
print(df)
Output:
Contents of the Dataframe : Name Age City Experience 0 Jack 34 Sydney 5 1 Riti 31 Delhi 7 2 Aadi 16 London 11 3 Mark 41 Delhi 12 Modified Dataframe : Name Age City 0 Jack 34 Sydney 1 Riti 31 Delhi 2 Aadi 16 London 3 Mark 41 Delhi
We fetched the column names of dataframe as a sequence and then selected the last column name using negative indexing i.e. at position -1. Then passed that name as the argument in drop() function, therefore it deleted the last column of dataframe.
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Use del keyword to drop last column of pandas dataframe
Fetch the name of last column of dataframe i.e. at position -1, from the dataframe.columns sequence. Then select that column by passing column name in subscript operator i.e. df[df.columns[-1]]. Then call del keyword on selected column,
del df[df.columns[-1]]
It will delete the last column of dataframe.
Checkout complete example to remove the last column of dataframe is as follows,
import pandas as pd
# List of Tuples
empoyees = [('Jack', 34, 'Sydney', 5) ,
('Riti', 31, 'Delhi' , 7) ,
('Aadi', 16, 'London', 11) ,
('Mark', 41, 'Delhi' , 12)]
# Create a DataFrame object
df = pd.DataFrame( empoyees,
columns=['Name', 'Age', 'City', 'Experience'])
print("Contents of the Dataframe : ")
print(df)
# Delete last column
del df[df.columns[-1]]
print("Modified Dataframe : ")
print(df)
Output:
Name Age City Experience 0 Jack 34 Sydney 5 1 Riti 31 Delhi 7 2 Aadi 16 London 11 3 Mark 41 Delhi 12 Modified Dataframe : Name Age City 0 Jack 34 Sydney 1 Riti 31 Delhi 2 Aadi 16 London 3 Mark 41 Delhi
It deleted the last column of dataframe in place.
Use pop() to drop last column of pandas dataframe
In Pandas, dataframe provides a function pop(column_name). It expects a column name as an argument and deletes that column from the calling dataframe object. It also returns the deleted column as a series. Let’s use this to delete last column of dataframe,
import pandas as pd
# List of Tuples
empoyees = [('Jack', 34, 'Sydney', 5) ,
('Riti', 31, 'Delhi' , 7) ,
('Aadi', 16, 'London', 11) ,
('Mark', 41, 'Delhi' , 12)]
# Create a DataFrame object
df = pd.DataFrame( empoyees,
columns=['Name', 'Age', 'City', 'Experience'])
print("Contents of the Dataframe : ")
print(df)
# Drop last column
df.pop(df.columns[-1])
print("Modified Dataframe : ")
print(df)
Output:
Contents of the Dataframe : Name Age City Experience 0 Jack 34 Sydney 5 1 Riti 31 Delhi 7 2 Aadi 16 London 11 3 Mark 41 Delhi 12 Modified Dataframe : Name Age City 0 Jack 34 Sydney 1 Riti 31 Delhi 2 Aadi 16 London 3 Mark 41 Delhi
We passed the column name of last column to the pop() function. It removed the last column of dataframe in place and also returned the deleted column as a series.
Summary:
We learned about different ways to delete last column of a dataframe.
Thanks for reading.