Udemy - Essential Guide to Python Pandas torrent

Essential Guide to Python Pandas
https://DevCourseWeb.com

Last updated 11/2022
Duration: 1h 32m | Video: .MP4, 1280x720 30 fps | Audio: AAC, 48 kHz, 2ch | Size: 598 MB
Genre: eLearning | Language: English

A Python Pandas crash course to teach you all the essentials to get started with data analytics

What you'll learn
Describe the Anatomy and main components of Pandas Data Structures. Understand Pandas Data Types and the correct use case for each type.
Implement several methods to get data into and from Pandas DataFrames. These methods include Python Native Data Structures, Tabular data files, API queries etc
Describe any information within a Pandas DataFrame. This will help you to identify data problems such as having missing values or using incorrect data types
Perform Data manipulation and cleaning. This part includes fixing data types, handling missing values, removing duplicate records, and many more
Merge & Join multiple datasets into Pandas DataFrames
Perform Data Summarization & Aggregation within any DataFrame
Create different types of Data Visualization
Apply all the Pandas knowledge you have learned in this course to a real-world Data Analysis Project to investigate COVID-19 infection, and the consequent lo
Requirements
To take the best out of this course, you will need a minimum working knowledge about Python programming language and are comfortable running data science documents using Jupyter notebook
Description
This Pandas crash course is designed to be a practical guide with real-life examples about the most common data manipulation tasks. The materials are presented with reusable code examples to allow you to quickly apply what you learn to your data analysis projects.
By the end of this course, you should be able to
Describe the Anatomy of Pandas Data Structures. This includes Pandas DataFrames, Series, and Indices.
Implement several methods to get data into and from Pandas DataFrames. These methods include Python Native Data Structures, Tabular data files, API queries and JSON format, web scraping, and more.
Describe any information within a Pandas DataFrame. This will help you to identify data problems such as having missing values or using incorrect data types.
Understand Pandas Data Types and the correct use case for each type.
Perform Data manipulation and cleaning. This part includes fixing data types, handling missing values, removing duplicate records, and many more.
Merge & Join multiple datasets into Pandas DataFrames
Perform Data Summarization & Aggregation within any DataFrame
Create different types of Data Visualization
Update Pandas Styling Settings
Conduct a Data Analysis Project using Pandas library to collect and investigate COVID-19 infection, and the consequent lockdown in different countries.
In addition to the course materials, you will also have free access to the following:- A Jupyter Notebook with all the code examples covered in this course- A free e-book in PDF format

Who this course is for
This course is for aspiring data professionals and Python developers who want to learn how to process data in Pandas.