Pandas with Python

Analyze data quickly and easily with Python's powerful pandas library

updated on icon Updated on Sep, 2023

language icon Language - English

person icon DATAhill Solutions Srinivas Reddy

architecture icon Development,Data Science and AI ML,Pandas


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Course Description

Why learn Pandas?

If you've spent time in a spreadsheet software like Microsoft Excel, Apple Numbers, or Google Sheets and are eager to take your data analysis skills to the next level, this course is for you!

Data Analysis with Pandas and Python introduces you to the popular Pandas library built on top of the Python programming language.

Pandas is a powerhouse tool that allows you to do anything and everything with colossal data sets -- analyzing, organizing, sorting, filtering, pivoting, aggregating, munging, cleaning, calculating, and more!

I call it "Excel on steroids"!

Over the course of more than 19 hours, I'll take you step-by-step through Pandas, from installation to visualization! We'll cover hundreds of different methods, attributes, features, and functionalities packed away inside this awesome library. We'll dive into tons of different datasets, short and long, broken and pristine, to demonstrate the incredible versatility and efficiency of this package.

Data Analysis with Pandas and Python is bundled with dozens of datasets for you to use. Dive right in and follow along with my lessons to see how easy it is to get started with pandas!

Whether you're a new data analyst or have spent years (*cough* too long *cough*) in Excel, Data Analysis with pandas and Python offers you an incredible introduction to one of the most powerful data toolkits available today!

1. Introduction Series & DataFrame

2. Date Range & Inspecting Data

3. Indexing & Slicing on DataFrame - 1

4. loc & iloc

5. Indexing & Slicing on DataFrame - 2

6. Concatination & Descriptive Statistics

7. Merging DataFrames

8. Working with Text Data

9. Function Application & Loading data in Python

10. Loading Data from CSV, Excel & URL

11. Data Visualization using Pandas

12. What is Data Science

13. What is Machine Learning

Who this course is for:

  • Beginner Python developers curious about Data Science


What will you learn in this course:

  • Perform a multitude of data operations in Python's popular "pandas" library including grouping, pivoting, joining and more!
  • Possess a strong understanding of manipulating 1D, 2D, and 3D data sets
  • Learn hundreds of methods and attributes across numerous pandas objects
  • Resolve common issues in broken or incomplete data sets


What are the prerequisites for this course?

  • Basic / intermediate experience with Microsoft Excel or another spreadsheet software (common functions, vlookups, Pivot Tables etc)
  • Basic experience with the Python programming language
  • Strong knowledge of data types (strings, integers, floating points, booleans) etc
Pandas with Python


Check out the detailed breakdown of what’s inside the course

Pandas with Python
24 Lectures
  • play icon Session 1. Introduction Series & DataFrame 02:02 02:02
  • play icon Introduction Series & DataFrame 41:00 41:00
  • play icon Session 2. Date Range & Inspecting Data 00:50 00:50
  • play icon Date Range & Inspecting Data 29:36 29:36
  • play icon Session 3. Indexing & Slicing on DataFrame - 1 00:44 00:44
  • play icon Indexing & Slicing on DataFrame - 1 30:13 30:13
  • play icon Session 4. loc & iloc 00:45 00:45
  • play icon Loc & iloc 31:18 31:18
  • play icon Session 5. Indexing & Slicing on DataFrame - 2 00:27 00:27
  • play icon Indexing & Slicing on DataFrame - 2 18:24 18:24
  • play icon Session 6. Concatenation & Descriptive Statistics 00:55 00:55
  • play icon Concatenation & Descriptive Statistics 31:54 31:54
  • play icon Session 7. Merging DataFrames 00:54 00:54
  • play icon Merging DataFrames 29:28 29:28
  • play icon Session 8. Working with Text Data 00:43 00:43
  • play icon Working with Text Data 18:40 18:40
  • play icon Session 9. Function Application & Loading data in Python 00:59 00:59
  • play icon Function Application & Loading data in Python 40:33 40:33
  • play icon Session 10. Loading Data from CSV, Excel & URL 00:56 00:56
  • play icon Loading Data from CSV, Excel & URL 21:24 21:24
  • play icon Session 11. Data Visualization using Pandas 00:45 00:45
  • play icon Data Visualization using Pandas 19:33 19:33
  • play icon What is Data Science 32:26 32:26
  • play icon What is Machine Learning 26:33 26:33

Instructor Details

DATAhill Solutions Srinivas Reddy

DATAhill Solutions Srinivas Reddy

Data Scientist

Mr. Srinivas Reddy is Founder & MD of DATAhill Solutions

He is Research Scholar (Ph.D) on Artificial Intelligence & Machine Learning

He Received Masters of Technology in Computer Science & Engineering from JNTU, MICROSOFT Certified Professional, IBM Certified Professional & Certified from IIT Kanpur & IIT Ropar.

Having 10+ Years of Experience in Software & Training.

His Experience includes Managing, Data Processing, Data Cleaning, Predicting and Analyzing of Large volume of Business Data.

Expertise in Data Science, Data Analytics, Machine Learning, Deep Learning, Artificial Intelligence, Python, R, Weka, Data Management & BI Technologies.

Having Patents and Publications in Various Fields such as Artificial Intelligence, Machine Learning and Data Science Technologies.

Professionally, He is Data Science Management Consultant with over 7+ years of Experience in Finance, Retail, Transport and other Industries.

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