top of page

Data Scientist Program


Free Online Data Science Training for Complete Beginners.

No prior coding knowledge required!

Reading CSV Files

CSV stands for "Comma Separated Values" is a simple file format which is used commonly for data science.Each line is a data record which hold information consists of one or more fields, separated by commas.

How to Read a CSV ?

There are two ways of reading csv files.

  1. Using csv.reader

  2. Using Pandas

  3. Using readlines()

Using csv.reader

1.Import the CSV library

import csv

2. " .Open()"

.open() will be use to open the file that is" Data.csv"


3. Use csv.reader to read csv file


4. Extract Records

To extract records you need to create a list called rows iterated through csv reader object and append by each row to list.

for row in csvreader:

5. Close the file

Using ".close()" you can close the opened file. For file Data as shown below.


Using Pandas

Pandas is an important library when it comes to data science and used in multiple ways . Here are the steps for using to reading a csv file using pandas.

1. Importing Pandas Library

The first step is to import the library in the code as it is used to work with pandas.

import pandas as pd

2. Load CSV files to Pandas using read_csv()

The pandas are used here to reading csv is done with the help of command read_csv used over a file named "Data.csv"


3. Extract The Fields

.columns is used to extract field names form the file and represent it in the form of headers.


4.Extract Rows

All the rows of data can simply be extracted calling the name of the field

attached to filename.


Using readlines()

.readlines() is used to return all the lines in a file in a common list.Each item of the list row of csv file.Hence the first roe of the readlines() is the header and rest of them are the records.

with open ('Data.csv) as file:
    content= file.readlines()

For more information check out the link.


Recent Posts

See All


bottom of page