Data Analysis with Python Course - Numpy, Pandas, Data Visualization

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