Data Science Tutorial

Data science is the skill of collecting data, cleaning it, exploring it and using it to answer questions and make predictions.

Shops want to know which products sell best. Hospitals want to spot patients at risk. Banks want to catch fraud. All of them need people who can work with data, and Python is the most popular language for the job.

This tutorial uses Python and the pandas library. You should know basic Python first: variables, lists, dictionaries, loops and functions.

What You Will Learn

• What data science is and the steps of a data project
• pandas Series and DataFrames
• Loading CSV files and exploring a dataset
• Cleaning data: missing values, duplicates and wrong types
• Filtering, sorting and grouping to answer questions
• Making charts with matplotlib
• Basic statistics and your first machine learning model with scikit-learn

A First Example

This code finds the students who scored more than 75:

import pandas as pd

df = pd.DataFrame({
    "student": ["Ali", "Ayesha", "Bilal", "Sana", "Hamza"],
    "marks": [72, 85, 90, 64, 78],
})
print(df[df["marks"] > 75])

  student  marks
1  Ayesha     85
2   Bilal     90
4   Hamza     78

Exercises and Quiz

Lessons end with a short exercise, and the last lesson has a quiz on the whole tutorial.

What to Learn Next

If you are new to spreadsheets and data, the Excel tutorial is a gentle start. To store data in databases, learn SQL, and to deploy data projects in the cloud, see AWS.