Pandas Function For 90% Of Data Science Tasks

The most used Pandas functions with code examples to make learning comfortable

Photo by Christina Morillo: https://www.pexels.com/photo/woman-programming-on-a-notebook-1181359/

Pandas is an open-source Python-based library, extensively used for data manipulation and analysis. It is simple and quick! Which made data scientists fall in love with it.

I used to find Pandas Library overwhelming at the start because I approached it incorrectly. This is why I wrote this article, to make it 100x easier for everyone!

Whether you are experienced with Pandas or Just starting out, this article will provide you with value, I have gone through all the important functions in pandas, with examples!

I have divided this article into sections, on the basis of how often you will use a particular function. First are the essential ones, and then, the functions get powerful in what they do! Save this article, for further reference!

1. Most Essential Functions:

DataFrame(): Creates a DataFrame from various data sources (e.g., arrays, lists, dictionaries).

import pandas as pd

# Create a DataFrame using a dictionary
data = {
    'Name': ['John', 'Emma', 'David', 'Sophia'],
    'Age': [25, 28, 32, 30],
    'City': ['New York', 'London', 'Paris', 'Tokyo']
}

df =…