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Update column value of CSV in Python

  • Difficulty Level : Medium
  • Last Updated : 03 Jan, 2021

Prerequisites: Pandas

In this article, we will discuss ways in which the value(s) of a column can be updated. The best and the optimal way to update any column value of a CSV is to use the Pandas Library and the DataFrame functions.

Link for the CSV file in use – Click here

Method 1

Approach

  • Import module
  • Open CSV file and read its data
  • Find column to be updated
  • Update value in the CSV file using to_csv() function

to_csv() method converts the Data Frame into CSV data as the output is returned to the file, it takes the file object or the file name as the parameter and the index=False should be mentioned so that the indices are not written into the CSV file. But this method is very tedious and is not reliable when you want to update similar values that are occurring multiple times. 



Details in the file before updating:

Example:

Python3




# importing the pandas library
import pandas as pd
  
# reading the csv file
df = pd.read_csv("AllDetails.csv")
  
# updating the column value/data
df.loc[5, 'Name'] = 'SHIV CHANDRA'
  
# writing into the file
df.to_csv("AllDetails.csv", index=False)
  
print(df)

Details after updating:

Method 2: 

Approach

  • Import module
  • Open csv file and read its data
  • Find column to be updated
  • Update value in the csv file using replace() function

The replace() method is useful when we have to update the data that is occurring multiple number of time. We simply just have to specify the column name and need to pass the values as a dictionary into the replace() method which is in the form of key and value pair, the key will have the previous data of the column and value will have the data to be updated with. 



 Before updating column data/value:

Example:

Python3




# importing the pandas library
import pandas as pd
  
# reading the csv file
df = pd.read_csv("AllDetails.csv")
  
# updating the column value/data
df['Status'] = df['Status'].replace({'P': 'A'})
  
# writing into the file
df.to_csv("AllDetails.csv", index=False)
  
print(df)

After updating column data/value:

Method 3:

In this method, we are employing csv module which is a dedicated module centrally created for reading, writing and updating csv files. 

Approach:

  • Import module
  • Read data as dictionary
  • Update the required column values storing it as a list of dictionary
  • Inserting it back, row by row
  • Closing the file.

File before update:

Program:

Python3




import csv
  
op = open("AllDetails.csv", "r")
dt = csv.DictReader(op)
print(dt)
up_dt = []
for r in dt:
    print(r)
    row = {'Sno': r['Sno'],
           'Registration Number': r['Registration Number'],
           'Name': r['Name'],
           'RollNo': r['RollNo'],
           'Status': 'P'}
    up_dt.append(row)
print(up_dt)
op.close()
op = open("AllDetails.csv", "w", newline='')
headers = ['Sno', 'Registration Number', 'Name', 'RollNo', 'Status']
data = csv.DictWriter(op, delimiter=',', fieldnames=headers)
data.writerow(dict((heads, heads) for heads in headers))
data.writerows(up_dt)
  
op.close()

Output:

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