Learning Python for Data Analysis and Visualization (Version 1)

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Learning Python for Data Analysis and Visualization (Version 1)

Instructor Miss Hijab Aqsa
Category Programming
Last Update 19 Feb, 2025

Course Curriculam

Intro to course and Python

Installation and Overwiew of Setup
iPython/Jupyter Notebook Overview

IDE Setup

Using NumPy and Pandas

Working with data: Part 1

Working with data: Part 2

Working with data: Part 3

Data Visualization

Macine Learning

Example Projects

Free

Free access this course

Course Information

Instructor: Miss Hijab Aqsa
Lesson: 25
Quizze: 0

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✅ Basic Computer Skills – Familiarity with using a computer, installing software, and file management.
✅ No Prior Python Knowledge Required – The course starts from the basics, making it beginner-friendly.
✅ Basic Math Skills – A fundamental understanding of mathematics and statistics will be helpful but not mandatory.
✅ A Laptop or PC – Preferably with at least 4GB RAM for smooth performance.
✅ Python & Jupyter Notebook Installation – Instructions will be provided on how to install Python and Jupyter Notebook for hands-on practice.

Shopping cart

Learning Python for Data Analysis and Visualization (Version 1)

Learning Python for Data Analysis and Visualization (Version 1)

Course Curriculam

Intro to course and Python

Installation and Overwiew of Setup

iPython/Jupyter Notebook Overview

IDE Setup

Using NumPy and Pandas

Creating and Using Arrays

Universal Array Function

Series, DataFrames, Index objects, Reindex

Drop Entry, Selecting Entries, Data Alignment, Rank and Sort

Summary Statistics, Missing Data, Index Hierarchy

Working with data: Part 1

Reading and Writing Text Files

JSON with Python

HTML with Python

Microsoft Excel files with Python

Working with data: Part 2

Merge – Merge on Index

Concatenate – Combining DataFrames – Reshaping – Pivoting

Duplicates in DataFrames – Mapping – Replace – Rename Index

Binning – Outliers – Permutation

Working with data: Part 3

GroupBy on DataFrames

GroupBy on Dict and Series

Aggregation

Splitting Applying and Combining and Cross Tabulation

Data Visualization

Installing Seaborn

Histograms – Combining Plot Styles – Box and Violin Plots – Regression Plots

Heatmaps and Clustered Matrices

Macine Learning

Introduction to Machine Learning with SciKit Learn

Linear Regression – Logistic Regression

Multi Class Classification

Example Projects

Quick Links

Shopping cart

Learning Python for Data Analysis and Visualization (Version 1)

Learning Python for Data Analysis and Visualization (Version 1)

Course Curriculam

Intro to course and Python

Installation and Overwiew of Setup

iPython/Jupyter Notebook Overview

IDE Setup

Using NumPy and Pandas

Creating and Using Arrays

Universal Array Function

Series, DataFrames, Index objects, Reindex

Drop Entry, Selecting Entries, Data Alignment, Rank and Sort

Summary Statistics, Missing Data, Index Hierarchy

Working with data: Part 1

Reading and Writing Text Files

JSON with Python

HTML with Python

Microsoft Excel files with Python

Working with data: Part 2

Merge – Merge on Index

Concatenate – Combining DataFrames – Reshaping – Pivoting

Duplicates in DataFrames – Mapping – Replace – Rename Index

Binning – Outliers – Permutation

Working with data: Part 3

GroupBy on DataFrames

GroupBy on Dict and Series

Aggregation

Splitting Applying and Combining and Cross Tabulation

Data Visualization

Installing Seaborn

Histograms – Combining Plot Styles – Box and Violin Plots – Regression Plots

Heatmaps and Clustered Matrices

Macine Learning

Introduction to Machine Learning with SciKit Learn

Linear Regression – Logistic Regression

Multi Class Classification

Example Projects

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