Exploratory Data Analysis in Python, Numpy & Pandas for Data Visualization

Exploratory Data Analysis in Python, Numpy & Pandas for Data Visualization - Introduction

Learn the basics of Python, Numpy, Pandas, Data Visualization, and Exploratory Data Analysis in this course for beginners. This was originally presented as a live course. By the end of the course, you will be able to build an end-to-end real-world course project and earn a verified certificate of accomplishment.

Data Analysis with Python and Numpy - Free Course | Credit: Freecodecamp

Exploratory Data Analysis in Python, Numpy & Pandas for Data Visualization - Prerequisite

There are no prerequisites for this course. 

Exploratory Data Analysis in Python, Numpy & Pandas for Data Visualization - Curriculum 

This full course video includes 6 lectures (all in this video): 

1. Introduction to Programming with Python
2. Next Steps with Python
3. Numerical Computing with Numpy
4. Analyzing Tabular Data with Pandas
5. Visualization with Matplotlib and Seaborn
6. Exploratory Data Analysis - A Case Study 💻 Code References 
7. First steps with Python: https://jovian.ai/aakashns/first-steps-with-python
8. Variables and data types: https://jovian.ai/aakashns/python-variables-and-data-types
9. Conditional statements and loops: https://jovian.ai/aakashns/python-branching-and-loops
10. Functions and scope: https://jovian.ai/aakashns/python-functions-and-scope
11. Working with OS & files: https://jovian.ai/aakashns/python-os-and-filesystem
12. Numerical computing with Numpy: https://jovian.ai/aakashns/python-numerical-computing-with-numpy
13. 100 Numpy exercises: https://jovian.ai/aakashns/100-numpy-exercises
14. Analyzing tabular data with Pandas: https://jovian.ai/aakashns/python-pandas-data-analysis
15. Matplotlib & Seaborn tutorial: https://jovian.ai/aakashns/python-matplotlib-data-visualization
16. Data visualization cheat sheet: https://jovian.ai/aakashns/dataviz-cheatsheet
17. EDA on StackOverflow Developer Survey: https://jovian.ai/aakashns/python-eda-stackoverflow-survey
18. Opendatasets python package: https://github.com/JovianML/opendatasets
19. EDA starter notebook: https://jovian.ai/aakashns/zerotopandas-course-project-starter

Watch Full Course Exploratory Data Analysis in Python, Numpy & Pandas for Data Visualization

Click Here to watch on Youtube: Data Analysis with Python Course - Numpy, Pandas, Data Visualization

Exploratory Data Analysis in Python, Numpy & Pandas for Data Visualization Course Content

Lecture 1

1. Python Programming Fundamentals
2. Course Curriculum
3. Notebook - First Steps with Python and Jupyter
4. Performing Arithmetic Operations with Python
5. Solving Multi-step problems using variables
6. Combining conditions with Logical operators
7. Adding text using Markdown
8. Saving and Uploading to Jovian
9. Variables and Datatypes in Python
10. Built-in Data types in Python
11. Further Reading

Lecture 2

1. Branching Loops and Functions
2. Notebook - Branching using conditional statements and loops in Python
3. Branching with if, else, else-if
4. Non Boolean conditions
5. Iteration with while loops
6. Iteration with for loops
7. Functions and scope in Python
8. Creating and using functions
9. Writing great functions in Python
10. Local variables and scope
11. Documentation functions using Docstrings
12. Exercise - Data Analysis for Vacation Planning

Lecture 3

1. Numercial Computing with Numpy
2. Notebook - Numerical Computing with Numpy
3. From Python Lists to Numpy Arrays
4. Operating on Numpy Arrays
5. Multidimensional Numpy Arrays
6. Array Indexing and Slicing
7. Exercises and Further Reading
8. Assignment 2 - Numpy Array Operations
9. 100 Numpy Exercises
10. Reading from and Writing to Files using Python

Lecture 4

1. Analysing Tabular Data with Pandas
2. Notebook - Analyzing Tabular Data with Pandas
3. Retrieving Data from a Data Frame
4. Analyzing Data from Data Frames
5. Querying and Sorting Rows
6. Grouping and Aggregation
7. Merging Data from Multiple Sources
8. Basic Plotting with Pandas
9. Assignment 3 - Pandas Practice

Lecture 5

1. Visualization with Matplotlib and Seaborn
2. Notebook - Data Visualization with Matplotlib and Seaborn
3. Line Charts
4. Improving Default Styles with Seaborn
5. Scatter Plots
6. Histogram
7. Bar Chart
8. Heatmap
9. Displaying Images with Matplotlib
10. Plotting multiple charts in a grid
11. References and further reading
12. Course Project - Exploratory Data Analysis

Lecture 6

1. Exploratory Data Analysis - A Case Study
2. Notebook - Exploratory Data Analysis - A case Study
3. Data Preparation and Cleaning
4. Exploratory Analysis and Visualization
5. Asking and Answering Questions
6. Inferences and Conclusions
7. References and Future Work
8. Setting up and running Locally
9. Project Guidelines
10. Course Recap
11. What to do next?
12. Certificate of Accomplishment
13. What to do after this course?

Exploratory Data Analysis in Python, Numpy & Pandas for Data Visualization

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