Advanced pandas—Going Beyond the Basics

Explore advanced pandas techniques for reshaping, manipulating, and handling data. Use unique features and extended libraries to optimize workflows and improve data analysis efficiency.

Intermediate

94 Lessons

16h

Certificate of Completion

Explore advanced pandas techniques for reshaping, manipulating, and handling data. Use unique features and extended libraries to optimize workflows and improve data analysis efficiency.

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Explanations

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This course includes

584 Playgrounds

10 Quizzes

This course includes

584 Playgrounds

10 Quizzes

Course Overview

Pandas is an easy-to-use and performant Python library for data manipulation and analysis. It is an important toolkit in a world where the volume of data created and captured is growing exponentially. In this course, you’ll discover an in-depth exploration of the pandas library. The course covers advanced techniques to reshape data, manipulate data, and handle various data types. You will also learn how to use less conventional pandas features to streamline workflows, while also leveraging extended pandas...Show More

TAKEAWAY SKILLS

Python

Data Manipulation

Data Plotting

Data Extraction

Data Statistics

Data Science

Analysis Tools

Python 3

Data Collection

Data Cleaning

Data Visualisation

Data Analysis

Data Types

Python Programming

Polars

Time Series Analysis

Data Storytelling

What You'll Learn

Understanding of pandas’ extensive capabilities in reading data from different sources

Working knowledge of how to effectively handle different types of data in pandas

Hands-on experience using data reshaping and manipulation techniques in pandas

Ability to leverage extended pandas libraries for advanced capabilities in handling and analyzing data

Familiarity with less conventional yet useful features of pandas

Knowledge of efficiency boosting techniques

What You'll Learn

Understanding of pandas’ extensive capabilities in reading data from different sources

Course Content

Before We Begin

Get familiar with advanced pandas for data manipulation, transformation, and visualization skills.

Course Introduction

Reading Data into pandas

Get started with reading diverse data formats into pandas for efficient analysis.

Importance of Data Ingestion

Read Data from the Web

Read Data from HTML Files Read Data from XML Files Read Data from Statistical Software Files Read Data from SQL Databases Read Data from Binary Files (Feather, HDF5, ORC, Parquet)Quiz

Combining Data

Examine methods for combining and merging pandas DataFrames to enhance data manipulation.

Importance of Combining Data Concatenate Merging—Types of Joins Merge 2—Implementation Merging—Scenarios Combine and Update Quiz

Reshaping and Manipulating Data

Enhance your skills in reshaping and manipulating data for effective analysis in pandas.

Importance of Reshaping and Manipulating Data GroupBy—The groupby() method GroupBy—Aggregate GroupBy—Transform and Filter GroupBy—Further Useful Features Pivot—Long and Wide Formats Pivot—The pivot() method Unpivot Stack and Unstack Further Reshaping Capabilities Advanced Indexing 1 Advanced Indexing 2 Quiz

Encoding Data Types

Take a closer look at inspecting, converting, and encoding data types in pandas.

Inspect Data Types Convert and Encode Data Types

Handling Numerical Data

10 Lessons

Focus on advanced arithmetic, comparison, filtering, and statistical methods using pandas.

Handling Categorical Data

6 Lessons

Master handling and transforming categorical data for efficient and meaningful analysis using pandas.

Handling Text Data

7 Lessons

Learn how to use pandas methods for transforming and managing complex text data efficiently.

Handling Time Series Data

17 Lessons

Unpack the core of advanced pandas techniques for time series analysis, manipulation, and resampling.

10.

Handling Sparse Data Structures

2 Lessons

Break apart the techniques for handling and optimizing sparse data structures using pandas.

11.

Handling Missing Data

4 Lessons

Grasp the fundamentals of representing, detecting, and managing missing data in pandas.

Data Analysis and Visualization with sidetable and Bokeh

Project

12.

Leveraging Further Features of pandas

6 Lessons

Solve problems in advanced pandas features like function chaining, assertions, styling, settings, and efficiency.

13.

Utilizing Extended Libraries

5 Lessons

Follow the process of leveraging advanced libraries to enhance data analysis with pandas.

14.

Wrap Up

1 Lesson

Build on essential pandas skills for advanced data handling and real-world applications.

15.

Appendix

5 Lessons

Learn how to use setups, prerequisites, and updates for advanced pandas functionalities.

Time Series Analysis and Visualization Using Python and Plotly

Project

Course Author

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