The Complete Data Analysis and Visualization in Python 2023

The Complete Data Analysis and Visualization in Python 2023, available at $19.99, has an average rating of 5, with 39 lectures, based on 2 reviews, and has 10 subscribers.

You will learn about Python's different libraries: NumPy, Pandas, Matplotlib, Seaborn scatter plot, bar plot, lmplot, lineplot, displot, boxplot, violinplot, pie chart and many others Data preprocessing using Pandas Jupyter Notebook Seaborn Reviewing basic statistics Exploratory Data Analysis Data Analysis on Netflix dataset, Diamond dataset, Test Score dataset This course is ideal for individuals who are Everyone interested in data analytics and data science or Business Professional interested in data visualization or Data analysis in Python or Data visualization in Python or Learning Pandas from scratch or Preprocessing of data or Learning Seaborn It is particularly useful for Everyone interested in data analytics and data science or Business Professional interested in data visualization or Data analysis in Python or Data visualization in Python or Learning Pandas from scratch or Preprocessing of data or Learning Seaborn.

Enroll now: The Complete Data Analysis and Visualization in Python 2023

Summary

Title: The Complete Data Analysis and Visualization in Python 2023

Price: $19.99

Average Rating: 5

Number of Lectures: 39

Number of Published Lectures: 39

Number of Curriculum Items: 39

Number of Published Curriculum Objects: 39

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

Python's different libraries: NumPy, Pandas, Matplotlib, Seaborn
scatter plot, bar plot, lmplot, lineplot, displot, boxplot, violinplot, pie chart and many others
Data preprocessing using Pandas
Jupyter Notebook
Seaborn
Reviewing basic statistics
Exploratory Data Analysis
Data Analysis on Netflix dataset, Diamond dataset, Test Score dataset

Who Should Attend

Everyone interested in data analytics and data science
Business Professional interested in data visualization
Data analysis in Python
Data visualization in Python
Learning Pandas from scratch
Preprocessing of data
Learning Seaborn

Target Audiences

Everyone interested in data analytics and data science
Business Professional interested in data visualization
Data analysis in Python
Data visualization in Python
Learning Pandas from scratch
Preprocessing of data
Learning Seaborn

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.

Course Curriculum

Chapter 1: NumPy and Pandas

Lecture 1: Introduction

Lecture 2: Installation of Anaconda

Lecture 3: Creating NumPy Array

Lecture 4: NumPy_Linspace_Random

Lecture 5: NumPy Array Attributes and Methods

Lecture 6: NumPy Array Selection Methods

Lecture 7: NumPy_Indexing_Selection_2D_Array

Lecture 8: Pandas_Series_Creating_Dataframe

Lecture 9: Pandas_Selection

Lecture 10: Pandas_Conditional_Selection

Lecture 11: Pandas_Handling_Missing_Data

Lecture 12: Pandas_Groupby_Method

Lecture 13: Pandas_Value_Counts_Other_Methods

Lecture 14: Pandas_Exercise_1

Lecture 15: Pandas_Exercise_1_Answer

Lecture 16: Pandas_Exercise_2_1

Lecture 17: Pandas_Exercise_2_2

Chapter 2: Matplotlib

Lecture 1: Matplotlib_Lecture_1

Lecture 2: Matplotlib_Lecture_2

Lecture 3: Matplotlib_Lecture_3

Lecture 4: Matplotlib_Lecture_4

Chapter 3: Seaborn

Lecture 1: Seaborn_Lecture_1

Lecture 2: Seaborn_Lecture_2

Lecture 3: Seaborn_Lecture_3

Lecture 4: Seaborn_Lecture_4

Lecture 5: Seaborn_Lecture_5

Lecture 6: Seaborn_Lecture_6

Lecture 7: Seaborn_Lecture_7

Lecture 8: Seaborn_Lecture_8

Lecture 9: Seaborn_Lecture_9

Chapter 4: Data_Analysis_Visualization_1

Lecture 1: Data_Analysis_Netflix_Dataset_1

Lecture 2: Data_Analysis_Netflix_Dataset_2

Lecture 3: Data_Analysis_Netflix_Dataset_3

Chapter 5: Data_Analysis_Visualization_2

Lecture 1: Data_Analysis_Diamond_Dataset_1

Lecture 2: Data_Analysis_Diamond_Dataset_2

Lecture 3: Data_Analysis_Diamond_Dataset_3

Lecture 4: Data_Analysis_Diamond_Dataset_5

Lecture 5: Data_Analysis_Diamond_Dataset_6

Lecture 6: Data_Analysis_Diamond_Dataset_4

Instructors

Gulmira Iskendirova
Instructor at Udemy

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5 stars: 2 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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