Python Pandas Library Full Tutorial

Python Pandas Library Full Tutorial, available at $34.99, has an average rating of 4.15, with 32 lectures, based on 201 reviews, and has 19260 subscribers.

You will learn about pandas library This course is ideal for individuals who are Beginner in Python or Who wants to learn Pandas Library It is particularly useful for Beginner in Python or Who wants to learn Pandas Library.

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Summary

Title: Python Pandas Library Full Tutorial

Price: $34.99

Average Rating: 4.15

Number of Lectures: 32

Number of Published Lectures: 32

Number of Curriculum Items: 32

Number of Published Curriculum Objects: 32

Original Price: $22.99

Quality Status: approved

Status: Live

What You Will Learn

pandas library

Who Should Attend

Beginner in Python
Who wants to learn Pandas Library

Target Audiences

Beginner in Python
Who wants to learn Pandas Library

pandas is a software library written for the Python programming language for data manipulation and analysis. In particular, it offers data structures and operations for manipulating numerical tables and time series. In this course, you’ll learn a lot about this library. Basic knowledge of Numpy is required, as we will perform some tasks using NumPy.

[Note: In this course, we used Jupyter Notebook to write all the codings. in case if you don’t have Jupyter Notebook or you don’t how to use Jupyter Notebook, you can simply run these codes in any IDE, or even in Python Default IDLE.]

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: Install and Upgrade Pandas and Basics of Jupyter Notebook

Lecture 3: How to create a dataframe and series

Lecture 4: Creating a CSV File

Lecture 5: Read CSV

Lecture 6: Head, Tail & Describe

Lecture 7: Indexing

Chapter 2: Intermediate Level

Lecture 1: Creating DF using Numpy

Lecture 2: Data Type

Lecture 3: Getting Index and Column

Lecture 4: DF to Numpy

Lecture 5: Transpose of DataFrame

Lecture 6: Sorting

Lecture 7: Is Dataframe combination of Series

Lecture 8: loc in Pandas

Lecture 9: What if you mistake a column name

Lecture 10: Deleting Rows or Columns

Lecture 11: Print Certain Amount of Rows and Columns

Lecture 12: Print with Conditions

Lecture 13: Print with Multiple Conditions

Lecture 14: ILOC

Lecture 15: Replace

Lecture 16: Reset Index

Lecture 17: IsNull( )

Lecture 18: DropNA

Lecture 19: Drop Duplicates

Chapter 3: Miscellenious

Lecture 1: Miscellenious

Lecture 2: For Loops

Lecture 3: Adding a New Column

Lecture 4: String Contains and REGEX

Lecture 5: Conditional Changes

Lecture 6: Chunksize

Instructors

Diptam Paul
Computer Science Engineer

Rating Distribution

1 stars: 3 votes
2 stars: 7 votes
3 stars: 52 votes
4 stars: 81 votes
5 stars: 58 votes

Frequently Asked Questions

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You can view and review the lecture materials indefinitely, like an on-demand channel.

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