Importing and Exporting Data between CSV Files and DataFrames – Class 12 IP Notes

Working with data is an important task in programming. In Class 12 Informatics Practices, we use the Pandas library to handle data. One of the most common formats used to store and exchange data is CSV which stands for Comma Separated Values. Pandas provides simple functions to import data from a CSV file into a DataFrame and export data from a DataFrame back to a CSV file.

What is a CSV File

A CSV file is a plain text file where each line represents a record and values are separated by commas. For example a file named students.csv may look like this:

RollNo,Name,Marks
101,Anita,92
102,Rahul,85
103,Simran,78

Importing CSV File into a DataFrame

To load data from a CSV file into a Pandas DataFrame we use the read_csv function.

import pandas as pd

df = pd.read_csv("students.csv")

print(df)

Explanation:

pd.read_csv(“filename.csv”) reads the CSV file into a DataFrame
By default it assumes comma as the separator

Some useful parameters of read_csv are:

sep → to specify a different separator, for example sep=”;”
header → row number to use as column names, header=None if no header row exists
index_col → to set a column as index
usecols → to load only specific columns

Example:

df = pd.read_csv("students.csv", usecols=["RollNo", "Name"])
print(df)

Exporting DataFrame to CSV File

To save a DataFrame into a CSV file we use the to_csv function.

df.to_csv("output.csv", index=False)

Explanation:

to_csv(“filename.csv”) saves the DataFrame to a CSV file
index=False prevents writing row numbers into the file

Example Program

import pandas as pd

# Import data
df = pd.read_csv("students.csv")
print("Original Data:")
print(df)

# Add new column
df["Grade"] = ["A", "B", "C"]

# Export updated DataFrame
df.to_csv("students_updated.csv", index=False)

print("Updated data saved successfully")

The new file students_updated.csv will look like this:

RollNo,Name,Marks,Grade
101,Anita,92,A
102,Rahul,85,B
103,Simran,78,C

Summary

read_csv is used to import data from a CSV file into a DataFrame
to_csv is used to export a DataFrame to a CSV file
CSV is a simple and widely used file format for storing and exchanging data

Short Revision Table – Importing and Exporting CSV in Pandas

Operation	Function / Parameter	Example Code
Import CSV into DataFrame	`read_csv("filename.csv")`	`df = pd.read_csv("data.csv")`
Specify separator	`sep` parameter	`pd.read_csv("data.csv", sep=";")`
Read file without header	`header=None`	`pd.read_csv("data.csv", header=None)`
Set column as index	`index_col` parameter	`pd.read_csv("data.csv", index_col="RollNo")`
Load only specific columns	`usecols` parameter	`pd.read_csv("data.csv", usecols=["Name","Marks"])`
Export DataFrame to CSV	`to_csv("filename.csv")`	`df.to_csv("output.csv")`
Export without row index	`index=False`	`df.to_csv("output.csv", index=False)`

Practice Questions with Answers

Q1. What is a CSV file Give an example
Ans. A CSV file is a text file in which data is stored in tabular form. Each line represents a record and values are separated by commas.
Example:

RollNo,Name,Marks
101,Anita,92
102,Rahul,85

Q2. Name the function used to import a CSV file into a Pandas DataFrame
Ans. The function used is read_csv()

Q3. Which parameter of read_csv is used to select only specific columns from the file
Ans. The parameter usecols is used to select specific columns.

Q4. Write a short program to read a CSV file named marks.csv and display only the columns RollNo and Marks
Ans.

import pandas as pd
df = pd.read_csv("marks.csv", usecols=["RollNo", "Marks"])
print(df)

Q5. How can you save a DataFrame without row numbers into a CSV file
Ans. Use the parameter index=False with the to_csv function.
Example:

df.to_csv("output.csv", index=False)

Q6. Write a program to read a CSV file students.csv add a new column Grade with values A B and C and then save the updated DataFrame into a new file students_new.csv
Ans.

import pandas as pd

df = pd.read_csv("students.csv")
df["Grade"] = ["A", "B", "C"]
df.to_csv("students_new.csv", index=False)

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