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How to delete the last row of data of a pandas DataFrame?
Given a Pandas DataFrame, we have to delete the last row of data of it.
By Pranit Sharma Last updated : September 22, 2023
Rows in pandas are the different cell (column) values that are aligned horizontally and also provide uniformity. Each row can have the same or different value. Rows are generally marked with the index number but in pandas, we can also assign index names according to the needs. In pandas, we can create, read, update and delete a column or row value.
An index is the number of rows that ranges from 0 to n-1, so if the index is 0, it represents the first row and the n-1th index represents the last row.
Problem statement
Given a Pandas DataFrame, we have to delete the last row of data of it.
Deleting the last row of data of a pandas DataFrame
To delete the last row of the pandas DataFrame, we will first access the last index of the DataFrame by subtracting 1 from the length of the DataFrame. We will then remove the last index of the DataFrame with the help of pandas.DataFrame.drop() method.
Note
To work with pandas, we need to import pandas package first, below is the syntax:
import pandas as pd
Let us understand with the help of an example,
Python code to delete the last row of data of a pandas DataFrame
# Importing pandas package
import pandas as pd
# Creating a dictionary
dict = {
'Name':[
'Harry','Raman','Parth','Mukesh','Neelam','Megha',
'Deepak','Nitin','Manoj','Rishi','Sandeep','Divyansh',
'Sheetal','Shalini'
],
'Sport_selected':[
'Cricket','Cricket','Cricket','Cricket','Basketball',
'Basketball','Football','Cricket','Tennis','Tennis',
'Chess','Football','Basketball','Chess'
]
}
# Creating a DataFrame
df=pd.DataFrame(dict)
# Display original DataFrame
print("Original DataFrame:\n",df,"\n")
# Accessing the last row
last_row = len(df)
# Deleting the last row
result = df.drop(df.index[last_row-1])
# Display result
print("DataFrame after deleting the last row:\n",result)
Output
The output of the above program is:
Original DataFrame:
Name Sport_selected
0 Harry Cricket
1 Raman Cricket
2 Parth Cricket
3 Mukesh Cricket
4 Neelam Basketball
5 Megha Basketball
6 Deepak Football
7 Nitin Cricket
8 Manoj Tennis
9 Rishi Tennis
10 Sandeep Chess
11 Divyansh Football
12 Sheetal Basketball
13 Shalini Chess
DataFrame after deleting the last row:
Name Sport_selected
0 Harry Cricket
1 Raman Cricket
2 Parth Cricket
3 Mukesh Cricket
4 Neelam Basketball
5 Megha Basketball
6 Deepak Football
7 Nitin Cricket
8 Manoj Tennis
9 Rishi Tennis
10 Sandeep Chess
11 Divyansh Football
12 Sheetal Basketball
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