Complete Data Analysis and Visualization in Python

Complete Data Analysis and Visualization in Python - Printable Version

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Complete Data Analysis and Visualization in Python - BaDshaH - 09-19-2023

[Image: d79969c31438cebc62486323baf09caa.jpg]

Published 9/2023
Created by Gulmira Iskendirova
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 39 Lectures ( 3h 34m ) | Size: 2.14 GB

Learn Python libraries: NumPy, Pandas, Matplotlib and Seaborn for data analysis and visualization

[b]What you'll learn[/b]
Data analysis and visualization skill using Python and its different libraries: NumPy, Pandas, Matplotlib, Seaborn
Different formatting methods for charts
Data processing
Statistical methods for visualization

[b]Requirements[/b]
No programming experience needed. You will learn everything you need to know.

[b]Description[/b]
In this course, you will learn Python libraries from scratch. So, if you don't have coding experience, that is very fine.NumPy and Pandas are necessary libraries to do data analysis and preprocessing. In these course, most important concepts will be covered and after completing Pandas lectures, you will do Data Analysis exercise using Pandas for test score dataset. This is important step and aims to polish up your data preprocessing skill.Then, we will learn Matplotlib which is fundamental package for data visualization. In these lectures, we will learn all necessary concepts for data visualization.After, we will dive into Seaborn, statistical package with beautiful charts. First we will explore most important and used charts using Seaborn's built-in dataset - tips. After completing these lectures, we will dive into full data analysis and visualization exercise using complex datasets.Our first full data analysis exercise will be done using Netflix dataset where you will see how to do complex data preprocessing and applying Matplotlib functions to draw charts on progression and history.For second data analysis, dataset about diamond was used where you will explore Seaborn's full possibility.After completing this course, you will learn not only how to do everything correct statistically, but also common mistakes people often do during their analysis work.

Who this course is for
Everyone interested in data analytics and data science
Business Professional interested in data visualization
Data analysis in Python
Data visualization in Python

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