Learning Objectives

• Reading a data file
• Writing a data file

Reading Data Files

• It is always good to be able to create a dataframe by hand. But, generally, we don't make our data by hand. We work on the data that already exists.
• Data exists in several formats. The most basic of these is the CSV file. CSV stands for comma-separated-values.

What is a CSV file?

• CSV files are normally created by programs that handle large amounts of data. They are a convenient way to export data from spreadsheets and databases and import or use it in other programs.
• CSV (Comma Separated Values) is a simple file format that stores tabular data, such as a spreadsheet or database.
• A CSV file stores tabular data (numbers and text) in plain text.
• Each line of the file is a data record.
• Each record consists of one or more fields, separated by commas.
• The use of the comma as a field separator is the source of the name for this file format.

How does CSV look like?

Working with CSV files in Python

• For working with CSV files in Python, there is an inbuilt module named csv.
• However, a common method for working with CSV files is using Pandas. It makes importing and analyzing data much easier.
• One crucial feature of Pandas is its ability to write and read Excel, CSV, and many other types of files.

Pandas read_csv

• Functions like the Pandas read_csv() method enable you to work with files effectively.
• The read_csv() function reads the CSV file into a DataFrame object.
• A CSV file is similar to a two-dimensional table, and the DataFrame object represents a two-dimensional tabular view.
• The most basic way to read a CSV file in Pandas:

• Now, let's understand how to provide the filename

• One can do many other things through this function only to change the returned object completely.
• For instance, one can read a CSV file not only locally but from a URL through read_csv or choose what columns are to be imported so that we don't have to edit the array later.
• These modifications can be done by the various arguments it takes.
• We don't need to memorize all the arguments, though. Let's look at a few important ones below.

Pandas to_csv with example

• The easiest way to write DataFrames to CSV files is using the Pandas to_csv function.
• Syntax:

• If you want to export without the index, add index=False

• Example:

Comprehensive Tutorial

• Must Read
  A comprehensive tutorial on Pandas for beginners:
  https://www.learndatasci.com/tutorials/python-pandas-tutorial-complete-introduction-for-beginners/

Slide Download Link

You can download the slides for this topic from here.