A1PythonBeginnerAbout 120 min to complete
Introduction to Python for Data Analysis
Data analysis is the process of turning raw records into decisions. That sentence is doing a lot of work, so let us unpack it with a concrete scene.
Notebook
About 120 minutes to complete
Enrol to read the notebook and download it to run.
What this module covers
Data analysis is the process of turning raw records into decisions. That sentence is doing a lot of work, so let us unpack it with a concrete scene.
By the end of it
- Explain what data analysis is and describe the five stages of the data analysis workflow
- Justify why Python is the dominant language for data work, and state when a spreadsheet or SQL is the better tool
- Identify the core libraries of the Python data stack (NumPy, pandas, Matplotlib, Seaborn, SciPy, scikit-learn) and what each one is responsible for
- Write and execute your first Python statements: comments, print(), variables, and arithmetic
- Recognise Python's four fundamental data types (int, float, str, bool) and inspect them with type()
- Load a real tabular dataset into a pandas DataFrame and inspect it with .head(), .info(), and .describe()
- Produce a first grouped summary and two publication-quality charts
- Apply professional coding conventions (PEP 8 naming, comments, reproducible cells) from your very first line of code