How To Read A CSV File In Pandas | Pandas Tutorial 2 | Big Data Tutorials | Codeing School

In this article, I teach how to read a CSV file in Pandas. Pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.

Reading A CSV File In Python Pandas | Data Science and Big Data Tutorials

Today’s topic: How to read a CSV file in Pandas/Jupyter Notebook

**1^st you need a data set. If you have not any kind of data set, you can download it, Click Here.

Reading a CSV File:

Step 1. Upload the CSV file on your work folder.

Step 2. Click On upload.

Click On upload

Step 3. Choose the CSV file.

Choose the CSV file

Step 4. And Upload the CSV file.

And Upload the CSV file

To Read this CSV file:

import pandas as pd

df1 = pd.read_csv('Indian_states_analysis.csv')

df1

Output

Image 1. Read CSV

Logic: pd.read_csv(), this is syntax for read CSV files. pd.read_csv('Indian_states_analysis.csv'), “Indian_states_analysis.csv” is the name of the CSV file. Write the CSV file name within, ‘’ à mean single inverted comma.

Print top 4 rows:

df1.head(4)

Output:

Print top 4 rows

Print last 3 rows:

df1.tail(3)

Output:

Print last 3 rows

Find Datatype:

print(df1['name_of_city'].dtype)

Output:

object

print(df1['dist_code'].dtype)

Output:

int64

Logic: See the Image no. 1, 'name_of_city', is the 1^st column in our data set. When I write the syntax à print(df1['name_of_city'].dtype), it gave me ‘Object’ as output. Because, when Pandas didn’t understand the data type of the elements, it gives Object as output. Next,

See the Image no. 1, 'dist_code', is the 4^th column in our data set.

When I write the syntax à print(df1['dist_code'].dtype), it give me ‘int64’, because it is an integer value.

Find Data Type

If you have, any quarry please comment below.