Data Analysis Crash Course

Once you’re comfortable with the lessons from our basics course, you’re all set to learn how to apply these skills to data analysis. The articles below introduce the first concepts on data analysis in Python and should set you up to read further into the topic. Concepts within the articles are explained with topics around football and will give you the knowledge to get started with Python data analysis using the NumPy and Pandas modules.

Data Analysis Part One: NumPy

  1. Arrays in NumPy
  2. Indexing NumPy Arrays

Data Analysis Part Two: Pandas

  1. Series
  2. DataFrames
  3. Dealing with Missing Data
  4. Grouping Data
  5. Joining Data
  6. Filtering Data on Conditions
  7. Describing Datasets
  8. Pandas Operations

Extra Credit:

  1. Building Interactive Analysis Tools with Streamlit

Now that we are getting comfortable with manipulating and analysing data in Python, you’re going to want to shout about your insights. Take a look through our data visualisation tutorials to learn how we can communicate with our data in Python!

Recommendations, topic requests or conversation is welcome! Get in touch on Twitter!