Delve into effective data manipulation with pandas. Discover filtering, merging, grouping, and reshaping techniques through hands-on examples, best practices, and performance tips for real-world analysis.

pandas.tar.gz

pandas

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Python

pandas-with-sqlite3

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The course is a comprehensive guide to using pandas for data analysis. It covers a wide range of topics related to data manipulation, including filtering, merging, grouping, pivoting, and reshaping data.

In this course, you’ll learn about the best practices and efficient techniques for working with data. You’ll be provided with numerous examples of real-world data analysis problems and gain hands-on experience with the pandas library to solve them effectively. This course will also cover performance considerations and provide insights on common pitfalls to avoid when using pandas.

The course is suitable for both beginners and experienced users of pandas. It includes detailed explanations of pandas concepts and functions, as well as tips and tricks for optimizing your code. By the time you’re done with this course, you’ll be able to effectively handle data using pandas.

Effective Data Manipulation with pandas

We'll be exploring a dataset from a Siena College Poll in 2018. This data has rankings of United States presidents in various attributes.
We'll pull the raw data and show how to recreate the visualization first. Then we'll demonstrate more features of DataFrames with the presidential data.

## Getting the data

Wikipedia has the data from Siena College. We can scrape the data using the following commands. 

> **Note**: Given that Wikipedia can change at any time, there is no guarantee that this code will work at the time of your taking this course.



We'll be exploring a dataset from a Siena College Poll in 2018. This data has rankings of United States presidents in various attributes.
We'll pull the raw data and show how to recreate the visualization first. Then we'll demonstrate more features of DataFrames with the presidential data.

# Getting the data

Wikipedia has the data from Siena College. We can scrape the data using the following commands. 

> **Note**: Given that Wikipedia can change at any time, there is no guarantee that this code will work at the time of your taking this course.



Explore the similarities between the two data structures before diving into the unique features of DataFrames.

Introduction

Series Deep Dive

DataFrames

Manipulating Data

Wrapping Up

Appendix

Similarities between Series and DataFrame

Getting the data