Generic selectors
Exact matches only
Search in title
Search in content
wb_sunny

How to update the value of a row in a Python Dataframe?

Update The Values Of A Particular Row In A Python Dataframe

Hello, readers! In this article, we will be focusing on different ways to update the value of a row in a Python Dataframe in detail.

So, let us get started!


First, where do rows and columns reside?

In Python programming language, we come across this module called Pandas which offers us a data structure called a data frame.

A data frame stores data in it in the form of rows and columns. Thus, it can be considered as a matrix and is useful while analyzing the data.

Let us created a dataframe right away!

import pandas as pd 
info= {"Num":[12,14,13,12,14,13,15], "NAME":['John','Camili','Rheana','Joseph','Amanti','Alexa','Siri']}

data = pd.DataFrame(info)
print("Original Data frame:\n")
print(data)

Here, we have created a data frame using pandas.DataFrame() function

Output:

Original Data frame:
 
   Num   NAME
0   12    John
1   14  Camili
2   13  Rheana
3   12  Joseph
4   14  Amanti
5   13   Alexa
6   15    Siri

We will be using the above created data frame in the entire article for reference with respect to examples.


1. Using Python at() method to update the value of a row

Python at() method enables us to update the value of one row at a time with respect to a column.

Syntax:

dataframe.at[index,'column-name']='new value'

Example:

In this example, we have provided the at() function with index 6 of the data frame and column ‘NAME’. Thus, the value of the column ‘NAME’ at row index 6 gets updated.

data.at[6,'NAME']='Safa'

Output:

Num    NAME
0   12    John
1   14  Camili
2   13  Rheana
3   12  Joseph
4   14  Amanti
5   13   Alexa
6   15    Safa

2. Python loc() function to change the value of a row/column

Python loc() method can also be used to update the value of a row with respect to columns by providing the labels of the columns and the index of the rows.

Syntax:

dataframe.loc[row index,['column-names']] = value

Example:

data.loc[0:2,['Num','NAME']] = [100,'Python']

Here, we have updated the value of the rows from index 0 to 2 with respect to columns ‘Num’ and ‘NAME’, respectively.

Output:

Num    NAME
0  100  Python
1  100  Python
2  100  Python
3   12  Joseph
4   14  Amanti
5   13   Alexa
6   15    Siri

3. Python replace() method to update values in a dataframe

Using Python replace() method, we can update or change the value of any string within a data frame. We need not provide the index or label values to it.

Syntax:

dataframe.replace("old string", "new string")

Example:

data.replace("Siri", 
           "Code", 
           inplace=True)

As seen above, we have replaced the word “Siri” with “Code” within the dataframe.

Output:

 Num    NAME
0   12    John
1   14  Camili
2   13  Rheana
3   12  Joseph
4   14  Amanti
5   13   Alexa
6   15    Code

4. Using iloc() method to update the value of a row

With the Python iloc() method, it is possible to change or update the value of a row/column by providing the index values of the same.

Syntax:

dataframe.iloc[index] = value

Example:

data.iloc[[0,1,3,6],[0]] = 100

In this example, we have updated the value of the rows 0, 1, 3 and 6 with respect to the first column i.e. ‘Num’ to 100.

We can even provide the function with slicing of rows to change the values of multiple rows consequently using iloc() function.

Output:

Num    NAME
0  100    John
1  100  Camili
2   13  Rheana
3  100  Joseph
4   14  Amanti
5   13   Alexa
6  100    Siri

Conclusion

By this, we have come to the end of this topic. Feel free to comment below, in case you come across any question.

For more such posts related to Python, stay tuned and till then, Happy Learning!! 🙂