Learn the core Pandas workflow through nine guided Beginner labs and 45 verified coding steps. Starting with imports and a simple Series, you will progress to building DataFrame objects, reading CSV data, selecting and filtering rows, sorting tables, cleaning common issues, calculating statistics, and grouping records.
Each lab focuses on a small dataset and a clear operation. You edit a Python script, run it from the terminal, inspect the output, and complete a check before moving on. This structure develops dependable table-handling habits without requiring you to design an analysis project from scratch.
What You Will Learn
- Import Pandas and create, access, and inspect
SeriesandDataFrameobjects - Build DataFrames from dictionaries with chosen columns and index labels
- Read CSV files while handling comments, headers, and custom missing-value markers
- Select columns and rows with brackets,
loc,iloc, and label-based slices - Filter records with Boolean conditions, combined expressions,
isin, andnotnull - Sort by one or more columns, control sort direction, and manage indexes afterward
- Clean data by dropping or filling missing values, removing duplicates, renaming columns, and converting types
- Calculate descriptive statistics and summarize groups with
groupbyandagg
Who This Course Is For
This course is for Python beginners taking their first structured steps with Pandas and for learners who want guided practice before attempting open-ended data analysis. It suits those who prefer short explanations, small datasets, and a check after every coding step.
Prerequisites: You should know basic Python syntax, including variables, lists, dictionaries, and running a script. No previous Pandas experience is required.
Learning environment: All nine labs use an Ubuntu 22.04 WebIDE with starter .py files, a terminal, sample in-memory tables, and two local CSV files where needed. Each of the 45 steps has a task check; no local setup or external data account is required.
Frequently Asked Questions
How is this different from the 100 Pandas Exercises course?
This course teaches through nine guided labs with explanations and step checks. The 100-exercise course is a single self-directed Notebook with worked answers and a broader advanced range, making this course the better starting point for new Pandas users.
Will I work in Jupyter Notebook?
No. You edit ordinary Python files in a browser-based WebIDE and run them from a terminal. This gives you practice with a script-based Pandas workflow.
What topics are outside the course scope?
The curriculum does not cover joins or merges, pivot tables, time series, Excel files, or plotting. It deliberately concentrates on foundational DataFrame selection, cleaning, statistics, and grouping.
Do the labs use external or large real-world datasets?
No. The labs use compact tables defined in starter scripts and small local CSV files for students and missing-value examples. No download, cloud account, or external service is involved.
