Ahilyanagar Learning

Python for Data Analysis: NumPy, Pandas and Matplotlib

Analyse real data with Python in 6 guided hours: NumPy arrays, Pandas tables, cleaning messy data, grouping and statistics, and charts with Matplotlib, ending with a complete student-performance project.

Instructor
Vidya Pawar, Director, StudyThis
Level
Beginner
Language
English
Lessons
13, 6 hr

What you’ll learn

  • Set up Google Colab and use the Python needed for data work
  • Calculate with NumPy arrays: statistics, filtering, rows and columns
  • Build and explore tables with Pandas DataFrames
  • Clean real data: missing values, duplicates and wrong types
  • Analyse CSV and Excel files with filtering, sorting and groupby
  • Draw line, bar, scatter and histogram charts with Matplotlib
  • Choose the right chart and write honest conclusions
  • Complete a full data analysis project

About this course

Every college, shop and company collects data. This course teaches you to turn that data into answers with Python, the most widely used language for data work, using its three essential libraries: NumPy, Pandas and Matplotlib.

You work in Google Colab, free in your web browser, with nothing to install. Every hour tells you exactly what to type and what output to expect, and every program, table and chart in the notes was really run, so what you see is real output.

You will create and calculate with NumPy arrays; build and explore Pandas DataFrames; filter, sort and clean real data with missing values and duplicates; read and save CSV and Excel files; summarise data with groupby; and draw line, bar, scatter and histogram charts. The course ends with a complete Student Performance Analysis of a 62-student dataset, from loading to written conclusions.

Each hour ends with a practice task and a quiz. Pass the final quiz to earn a certificate that anyone can verify online by scanning its QR code. Basic programming knowledge (for example our C or Python courses) helps, and the Python you need is revised in Hour 1.

Course content

Hour 1: Introduction to Data Analysis and NumPy 2 lessons
  1. Notes Notes: Introduction to Data Analysis and NumPy Preview 40 min
  2. Reading Practice: Colab, Python and first arrays 20 min
  3. Quiz Unit quiz: pass it to open the next unit
Hour 2: NumPy Arrays and Operations 2 lessons
  1. Notes Notes: NumPy Arrays and Operations 40 min
  2. Reading Practice: Calculating with NumPy 20 min
  3. Quiz Unit quiz: pass it to open the next unit
Hour 3: Pandas Series and DataFrames 2 lessons
  1. Notes Notes: Pandas Series and DataFrames 40 min
  2. Reading Practice: Your first DataFrames 20 min
  3. Quiz Unit quiz: pass it to open the next unit
Hour 4: Data Filtering and Cleaning 2 lessons
  1. Notes Notes: Data Filtering and Cleaning 40 min
  2. Reading Practice: Filtering and cleaning 20 min
  3. Quiz Unit quiz: pass it to open the next unit
Hour 5: Data Analysis with CSV and Excel Files 3 lessons
  1. Reading Datasets for this course
  2. Notes Notes: Data Analysis with CSV and Excel Files 40 min
  3. Reading Practice: Analysing a real file 20 min
  4. Quiz Unit quiz: pass it to open the next unit
Hour 6: Data Visualization and Final Project 2 lessons
  1. Notes Notes: Data Visualization and Final Project 40 min
  2. Reading Final project: Analyse a dataset yourself 20 min
  3. Quiz Unit quiz: pass it to open the next unit