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The Complete Data Analysis and Visualization in Python 2023
Rating: 3.3 out of 5(3 ratings)
16 students

The Complete Data Analysis and Visualization in Python 2023

Learn Python libraries: NumPy, Pandas, Matplotlib and Seaborn for data analysis and visualization
Last updated 9/2023
English

What you'll 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

Course content

5 sections39 lectures3h 34m total length
  • Introduction1:45
  • Installation of Anaconda1:49
  • Creating NumPy Array6:19
  • NumPy_Linspace_Random5:54
  • NumPy Array Attributes and Methods8:46
  • NumPy Array Selection Methods6:41
  • NumPy_Indexing_Selection_2D_Array6:24
  • Pandas_Series_Creating_Dataframe5:39
  • Pandas_Selection5:32
  • Pandas_Conditional_Selection5:03
  • Pandas_Handling_Missing_Data6:28
  • Pandas_Groupby_Method5:51
  • Pandas_Value_Counts_Other_Methods4:29
  • Pandas_Exercise_12:27
  • Pandas_Exercise_1_Answer4:24
  • Pandas_Exercise_2_16:25
  • Pandas_Exercise_2_24:26

Requirements

  • No programming experience needed. You will learn everything you need to know.

Description

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
  • Learning Pandas from scratch
  • Preprocessing of data
  • Learning Seaborn