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Pandas with Python

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

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

Goals

  • 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

Prerequisites

  • 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
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Curriculum

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

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