Best course data science using pandas, Top 10 pandas course

Top 10 best course on data science Best course for data analytics Best top 10 course for data science Python pandas 2022

Data Science
4.5 hours
Apr 2022
last update
regular price

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


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



Introduction to pandas
Pandas installation

Types of pandas data structures

Pandas data structures
Pandas series
Pandas DataFrame

Functionality of pandas

Basic functionality
Descriptive statistics
Function application

Indexing and reindexing


Working with data in pandas

Sorting data in pandas
Operations on text data
Options and customizations

Advanced indexing

Indexing and selecting data

Functions on pandas

Statistical functions
Window functions
Aggregation functions

Handling missing data

Missing data

Groupby function


Database operations

Merging or joining

Date data handling

Date functionality

Categorical data handling

Categorical data

Data visualization and IO operations

Data visualization
IO tools
Comparision with SQL


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