Python · Advanced level

Advanced level · Module 5 of 6 · 24 guided hours

Data Analysis with pandas

Use pandas to clean, combine, summarise and chart tabular data for reports.

Learning objectives

  • Load and inspect data in DataFrames
  • Clean and transform data
  • Summarise with groupby and chart results

Topics

  • Series and DataFrames
  • reading CSV and Excel
  • cleaning missing and inconsistent values
  • groupby and pivot tables
  • matplotlib charts

Lessons

  1. Lesson 1 Loading and Exploring Data with pandas

    Read CSV and Excel files into DataFrames and understand their structure.

    DataFramedtypeloc/ilocboolean filtering

  2. Lesson 2 Cleaning and Transforming Data

    Fix missing values, inconsistent spellings, wrong types and duplicates.

    NaNfillna/dropnadrop_duplicatesastype and to_datetime

  3. Lesson 3 Combining and Reshaping Datasets

    Merge related datasets and reshape tables to answer questions that one file alone cannot.

    mergejoin keypivot_tablemelt

  4. Lesson 4 Summarising and Charting Results

    Aggregate data with groupby and pivot tables and present findings with clear charts.

    groupby/aggpivot_tablematplotlibchart labelling

Practical activity

Analyse a provided public dataset (for example market prices or school enrolment) and present three evidence-based findings with charts.

Expected outcomes

  • Reproducible data analysis notebooks
  • Clear, honest charts

Assessment

Notebook and findings marked for correctness, documentation of cleaning and chart quality.

Taught live by an instructor — online or in person. Free course lessons are for self-study and do not lead to a certificate — see registration options.