Master the concepts in Data Analysis with Python Course - Numpy, Pandas, Data Visualization created by freeCodeCamp.org. The total lesson runtime is 56:23 minutes providing step-by-step visual instructions. Follow along to build your skills without any subscription or sign-up required.
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Course Description & Lesson Notes
Official Video Description:
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. There are no prerequisites for this course.
Learn more and register for a certificate of accomplishment here: http://zerotopandas.com
‼️ Some of the data files used in this course are now in a new location. Some of the data you can find in this repo: https://github.com/the-stranger-web/jovian_Data_Analyst/tree/main
💻 Code References
• First steps with Python: https://jovian.ai/aakashns/first-steps-with-python
• Variables and data types: https://jovian.ai/aakashns/python-variables-and-data-types
• Conditional statements and loops: https://jovian.ai/aakashns/python-branching-and-loops
• Functions and scope: https://jovian.ai/aakashns/python-functions-and-scope
• Working with OS & files: https://jovian.ai/aakashns/python-os-and-filesystem
• Numerical computing with Numpy: https://jovian.ai/aakashns/python-numerical-computing-with-numpy
• 100 Numpy exercises: https://jovian.ai/aakashns/100-numpy-exercises
• Analyzing tabular data with Pandas: https://jovian.ai/aakashns/python-pandas-data-analysis
• Matplotlib & Seaborn tutorial: https://jovian.ai/aakashns/python-matplotlib-data-visualization
• Data visualization cheat sheet: https://jovian.ai/aakashns/dataviz-cheatsheet
• EDA on StackOverflow Developer Survey: https://jovian.ai/aakashns/python-eda-stackoverflow-survey
• Opendatasets python package: https://github.com/JovianML/opendatasets
• EDA starter notebook: https://jovian.ai/aakashns/zerotopandas-course-project-starter
❤️ Try interactive Python courses in your browser: https://scrimba.com/freeCodeCamp-Python (Made possible by a grant from Scrimba)
⭐️ Course Contents ⭐️
0:00:00 Introduction
Lecture 1
0:01:42 Python Programming Fundamentals
0:02:40 Course Curriculum
0:05:24 Notebook - First Steps with Python and Jupyter
0:08:30 Performing Arithmetic Operations with Python
0:11:34 Solving Multi-step problems using variables
0:20:17 Combining conditions with Logical operators
0:22:22 Adding text using Markdown
0:23:50 Saving and Uploading to Jovian
0:26:38 Variables and Datatypes in Python
0:31:28 Built-in Data types in Python
1:07:19 Further Reading
Lecture 2
1:08:46 Branching Loops and Functions
1:09:02 Notebook - Branching using conditional statements and loops in Python
1:09:24 Branching with if, else, elif
1:15:25 Non Boolean conditions
1:19:00 Iteration with while loops
1:28:57 Iteration with for loops
1:36:27 Functions and scope in Python
1:36:53 Creating and using functions
1:42:24 Writing great functions in Python
1:45:38 Local variables and scope
2:08:19 Documentation functions using Docstrings
2:11:40 Exercise - Data Analysis for Vacation Planning
Lecture 3
2:17:17 Numercial Computing with Numpy
2:18:00 Notebook - Numerical Computing with Numpy
2:26:09 From Python Lists to Numpy Arrays
2:29:09 Operating on Numpy Arrays
2:34:33 Multidimensional Numpy Arrays
3:03:41 Array Indexing and Slicing
3:17:49 Exercises and Further Reading
3:20:50 Assignment 2 - Numpy Array Operations
3:29:16 100 Numpy Exercises
3:31:25 Reading from and Writing to Files using Python
Lecture 4
4:02:59 Analysing Tabular Data with Pandas
4:03:58 Notebook - Analyzing Tabular Data with Pandas
4:16:33 Retrieving Data from a Data Frame
4:32:00 Analyzing Data from Data Frames
4:36:27 Querying and Sorting Rows
5:01:45 Grouping and Aggregation
5:11:26 Merging Data from Multiple Sources
5:26:00 Basic Plotting with Pandas
5:38:27 Assignment 3 - Pandas Practice
Lecture 5
5:52:48 Visualization with Matplotlib and Seaborn
5:54:04 Notebook - Data Visualization with Matplotlib and Seaborn
6:06:43 Line Charts
6:11:27 Improving Default Styles with Seaborn
6:16:51 Scatter Plots
6:28:14 Histogram
6:38:47 Bar Chart
6:50:00 Heatmap
6:57:08 Displaying Images with Matplotlib
7:03:37 Plotting multiple charts in a grid
7:15:42 References and further reading
7:20:17 Course Project - Exploratory Data Analysis
Lecture 6
7:49:56 Exploratory Data Analysis - A Case Study
7:50:55 Notebook - Exploratory Data Analysis - A case Study
8:04:36 Data Preparation and Cleaning
8:19:37 Exploratory Analysis and Visualization
8:54:02 Asking and Answering Questions
9:22:57 Inferences and Conclusions
9:25:00 References and Future Work
9:29:41 Setting up and running Locally
9:34:21 Project Guidelines
9:45:00 Course Recap
9:48:01 What to do next?
9:49:10 Certificate of Accomplishment
9:50:11 What to do after this course?
9:52:16 Jovian Platform
Correction:
3:11:27 The URL for the CSV file is changed. Instead, use https://raw.githubusercontent.com/the-stranger-web/jovian_Data_Analyst/refs/heads/main/italy-covid-daywise.csv
✏️ This course is taught by Aakash N S, co-founder, and CEO of Jovian.
Jovian's YouTube channel: https://youtube.com/jovianml
🌐 Web & Search Guide Notes (DuckDuckGo, Yahoo & Bing):
Learn how to understand Data Analysis With Python Course - Numpy, Pandas, Data Visualization with this step-by-step video tutorial guide. In this video, you will learn essential skills for Data Analysis With Python Course - Numpy, Pandas, Data Visualization.
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🎓 Lesson Overview & Learning Outcomes:
Welcome to the step-by-step video guide for Data Analysis with Python Course - Numpy, Pandas, Data Visualization taught by freeCodeCamp.org. This tutorial provides a comprehensive walkthrough designed to take you from foundational principles to practical implementation.
💡 Key Topics Covered in This Course:
- Core Fundamentals & Setup: Understanding the workspace, essential tools, and initial setup for Data Analysis with Python Course - Numpy, Pandas, Data Visualization.
- Step-by-Step Practical Demonstration: Hands-on implementation guided by freeCodeCamp.org with real-world examples.
- Best Practices & Key Shortcuts: Time-saving workflows, keyboard shortcuts, and industry-standard recommendations.
- Troubleshooting & Common Pitfalls: How to avoid common beginner errors and optimize your workflow for peak efficiency.
📋 Recommended Prerequisites & Study Notes:
No prior advanced experience is required. Follow along with the video player above on any desktop computer, tablet, or mobile device. Pause and rewind at key steps to practice along with the instructor.
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