Best course data science using pandas, Top 10 pandas course

Best course data science using pandas, Top 10 pandas course, available at $19.99, with 27 lectures, and has 2 subscribers.

You will learn about What python pandas library and its usage in storing data required for data analytics Python pandas data structures: Series, DataFrame and Panel How to create Series, DataFrame and Panel types of data structures How to access data from Series, DataFrame and Panel data structures What types of operations can be performed on pandas data structures This course is ideal for individuals who are This course is for python programmer. or Also, this course is for data analysts. It is particularly useful for This course is for python programmer. or Also, this course is for data analysts.

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Summary

Title: Best course data science using pandas, Top 10 pandas course

Price: $19.99

Number of Lectures: 27

Number of Published Lectures: 27

Number of Curriculum Items: 27

Number of Published Curriculum Objects: 27

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

What python pandas library and its usage in storing data required for data analytics
Python pandas data structures: Series, DataFrame and Panel
How to create Series, DataFrame and Panel types of data structures
How to access data from Series, DataFrame and Panel data structures
What types of operations can be performed on pandas data structures

Who Should Attend

This course is for python programmer.
Also, this course is for data analysts.

Target Audiences

This course is for python programmer.
Also, this course is for data analysts.

Pandas is an open-source Python Library providing high-performance data manipulation and analysis tool using its powerful data structures. Python with Pandas is used in a wide range of fields including academic and commercial domains including finance, economics, Statistics, analytics, etc.

This is a ultimate guide to python pandas for data science user. In this course user will learn python pandas library. User will learn pandas series, dataframe and panel data structures. Also, they will learn how to create these data structures, store data, access data. The functionality and operations on pandas data structures are also explained in detail. python pandas and its data structures are usefull to store the required for data analytics. The detail content of the course is as follows,

1.Python Pandas – Introduction

2. Python Pandas – Environment Setup

3. Introduction to Data Structures

4. Python Pandas – Series

5. Python Pandas – DataFrame

6. Python Pandas – Basic Functionality

7.Python Pandas – Descriptive Statistics

8.Python Pandas – Function Application

9.Python Pandas – Reindexing

10.Python Pandas – Iteration

11.Python Pandas – Sorting

12.Python Pandas – Working with Text Data

13.Python Pandas – Options and Customization

14.Python Pandas – Indexing and Selecting Data

15.Python Pandas – Statistical Functions

16.Python Pandas – Window Functions

17.Python Pandas – Aggregations

18.Python Pandas – Missing Data

19. Python Pandas – GroupBy

20.Python Pandas – Merging/Joining

21.Python Pandas – Concatenation

22.Python Pandas – Date Functionality

23.Python Pandas – Timedelta

24.Python Pandas – Categorical Data

25.Python Pandas – Visualization

26.Python Pandas – IO Tools

27.Python Pandas – Comparison with SQL

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction to pandas

Lecture 2: Pandas installation

Chapter 2: Types of pandas data structures

Lecture 1: Pandas data structures

Lecture 2: Pandas series

Lecture 3: Pandas DataFrame

Chapter 3: Functionality of pandas

Lecture 1: Basic functionality

Lecture 2: Descriptive statistics

Lecture 3: Function application

Chapter 4: Indexing and reindexing

Lecture 1: Reindexing

Lecture 2: Iteration

Chapter 5: Working with data in pandas

Lecture 1: Sorting data in pandas

Lecture 2: Operations on text data

Lecture 3: Options and customizations

Chapter 6: Advanced indexing

Lecture 1: Indexing and selecting data

Chapter 7: Functions on pandas

Lecture 1: Statistical functions

Lecture 2: Window functions

Lecture 3: Aggregation functions

Chapter 8: Handling missing data

Lecture 1: Missing data

Chapter 9: Groupby function

Lecture 1: Groupby

Chapter 10: Database operations

Lecture 1: Merging or joining

Lecture 2: Concatenation

Chapter 11: Date data handling

Lecture 1: Date functionality

Lecture 2: Timedelta

Chapter 12: Categorical data handling

Lecture 1: Categorical data

Chapter 13: Data visualization and IO operations

Lecture 1: Data visualization

Lecture 2: IO tools

Lecture 3: Comparison with SQL

Instructors

Dr Karveer B Manwade
Professor

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Frequently Asked Questions

How long do I have access to the course materials?

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

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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