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Comma Separated Variables (CSV)

We know how to create DataFrame but most of the time we will be working with already existing datasets and CSV is one of the most common formats for bid datasets.
CSV (comma-separated values) is a text-only spreadsheet format.
The first row of CSV contains the heading and other rows contain values, whereas each column heading and each variable is separated by a comma.
```
column1,column2,column3
value1,value2,value3
```

Loading CSV Data

You can load the data of CSV File into a DataFrame in Pandas using:
```
pd.read_csv('file.csv')
```
Here the read_csv() method is called and 'file.csv' is the name of the CSV file and is passed as an argument.
You can also save the data to a CSV file from a DataFrame using:
```
df.to_csv('csv-file.csv')
```
Here, the to_csv() method is used and 'df' is our DataFrame object and 'csv-file.csv' is the file where we are saving the data of the dataframe.

Example:

Here, we have a small CSV file, which contains a dataset of the top 5 cleanest cities in India and its columns contain City, Population (in Millions), and its Rank.

import pandas as pd

df = pd.read_csv('sample.csv')
print(df)

Output:

City	Population	Rank
Indore	32.0	1
Surat	77.0	2
Vijayawada	21.0	3
Navi Mumbai	11.0	4
Pune	7.4	5

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Pandas Tutorials | Projects | Interview Questions Tutorial

Pandas Tutorials | Projects | Interview Questions Tutorial

Introduction to Pandas

Cleaning Data with Pandas

Tables in Pandas

Interview Questions in Pandas

Loading Data from CSV

Comma Separated Variables (CSV)

Loading CSV Data

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