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What you will learn

 

Learn how to read different types of file formats using Pandas.

 

Learn about different data analysis functions in Pandas such as Melt, merge, pivot, cross tabulation etc.

 

Learn about handling missing values using Pandas.

 

Learn and excel handling Series and DataFrames using Pandas.

 

Learn about Pandas Arrays.

 

Learn handling Time data using Pandas.

 

Learn about Multi Indexing using Pandas.

 

Learn about Indexing in Pandas.

 

Learn about Rolling and Expanded Window Functions in Pandas.

 

Learn about Pandas Styling.

 

Learn about Andrew Curves, Autocorrelation plot, bootstrap plot, Lag plot, parallel coordinates.

 

Hands on Real-World Projects

 

Reading Tables from HTML Files using Pandas

 

Gain a deep and hands-on understanding of pandas

Description

Welcome to Pandas Masterclass: Advanced Data Analysis and Visualisation with Pandas.

Pandas is a fast, flexible, easy-to-use open source data analysis and data manipulation library built on top of the python programming language.

It offers data structures and many operations for manipulating data.

Pandas allow many data manipulation operations such as merging, reshaping, cleaning, and data wrangling features.

Pandas library is widely used for data science/data analysis and machine learning tasks.

 


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If you want to master the data analysis library-pandas then this course is perfect for you.

You will gain complete knowledge on Pandas library.

From reading datasets to analyzing them using the different manipulation functions.

Everything is included in this course.

 

In this course, you will cover the following topics:-

  • Reading different file formats

  • General functions of pandas

  • Handling Series

  • Handling Dataframe

  • Introduction to Arrays in Pandas

  • Handling time data

  • Styling data frame

  • Window functions

  • Visualization and plotting

  • Index Objects in Pandas

     

This course is made by keeping in mind the requirements of data analysts and data scientists while working on any project.

After completing this course you will be able to work on any data analysis project efficiently using pandas.

This is a great test for people who are learning the Python language and data science and are looking for new challenges.

Instructor Support – Quick Instructor Support for any queries.

I’m looking forward to see you in the course!

 

You will definitely love this course.

You will have access to all the resources used in this course.

Enroll now and become a pandas pro!!!

 

English
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Content

Introduction to Pandas

Introduction to Pandas
Different Types of Files or Sources of Datasets in Real World
Handling Flat Files using Pandas
Handling Excel Files using Pandas
Handling JSON Files using Pandas
Q and A
Reading Tables from HTML Files using Pandas
Reading Data from SQL Databases using Pandas
Handling SAS and SPSS Files using Pandas
Quiz on Reading Files using Pandas

General Functions in Pandas

Introduction to Melt Function in Pandas
Introduction to Pivoting in Pandas
Introduction to Cross Tabulation using Pandas
Introduction to Binning using Pandas
Introduction to Merge and Concat Operations in Pandas
Finding Missing Values using Pandas
Conversion of Data Types using Pandas
Evaluating Complex Equations using Pandas
Quiz on General Functions in Pandas

Handling Series using Pandas

Attributes in Series
Indexing and Iteration in Series
Binary Operations in Series
Groupby and Window Functions in Series
Descriptive Statistics in Series
Reindexing in Series
Handling Missing Data in Series
Reshaping and Sorting in Series
DateTime properties in Series
Quiz on Handling Series using Pandas

Handling DataFrames using Pandas

DataFrame Attributes
Indexing and Iteration in DataFrames
Binary Operations in DataFrames
Groupby and Window in DataFrames
Descriptive Statistics in DataFrames
Reindexing in DataFrames
Handling Missing values in DataFrames
Reshaping, Sorting and Transposing DataFrames
Join Operations in DataFrames
Handling Time Series Data
Plotting DataFrames
Serialization in DataFrames
Quiz on Handling DataFrames using Pandas

Introduction to Arrays in Pandas

Introduction to Pandas Arrays
Handling Date Time Data
Handling Time Delta Data
Handling Time Span Data
Handling Time Interval data
Handling Categorical Data
Handling Sparse Data
Handling Text and Boolean Data
Quiz on Introduction to Arrays in Pandas

Index Objects in Pandas

Introduction to Indexing in Pandas
Numerical Indexing using Pandas
Categorical Indexing using Pandas
Interval Indexing using Pandas
Multi Indexing using Pandas
Date Time Indexing using Pandas
Time Delta Indexing using Pandas
Period Indexing using Pandas
Date Offsets in Pandas
Quiz on Index Objects in Pandas

Window Functions in Pandas

Introduction to Window Functions
Introduction to Rolling Window Functions
Introduction to Expanded Window Functions
Quiz on Window Functions in Pandas

Styling DataFrames in Pandas

Introduction to Styling DataFrames using Pandas
Applications of Pandas Styling
Built-in Styles in Pandas
Real World Examples
Quiz on Styling DataFrames in Pandas

Visualisations and Plotting in Pandas

Introduction to Pandas Visualisation using Pandas
Introduction to Andrews Curves
Introduction to Autocorrelation Plot
Introduction to Bootstrap Plot
Introduction to Lag Plot for Time Series
Introduction to Parallel Coordinates
Introduction to Scatter Matrix
Quiz on Visualisations and Plotting in Pandas

Outro Section

Conclusion
How to Get Your Certificate of Completion

Bonus Section

Bonus Lecture