Data Analysis with Python (pandas, polars, DuckDB)
Data Analysis with Python (pandas, polars, DuckDB) practice
18 exercises and 65 quizzes from the lessons of this track. Sample tests run in your browser; what you pass is kept in this browser only.
The data-analysis workflow and your toolkit
- Compute both definitions of a busy day
- Quiz: What data analysis is: from question to decision
- Report what differs from the lock file
- Quiz: Set up your analysis environment and lock file
- Quiz: NumPy essentials for analysts
- Count hidden gaps and repeated keys in a CSV file
- Quiz: A first look at any dataset: shape, types, surprises
pandas foundations
Loading data: CSV, Excel, JSON, Parquet and databases
Cleaning: missing values, duplicates, types and text
- Turn raw weight cells into numbers or missing values
- Quiz: Missing data: find it, understand it, decide
- Keep the latest complete record per contact
- Quiz: Duplicates, keys and the latest record
- Parse amounts and day-first dates from text
- Quiz: Converting types: numbers, dates and Indian formats
- Clean a district column against an official list
- Quiz: Cleaning text: whitespace, case, Unicode, spelling
- Flag outliers with IQR fences and robust z-scores
- Quiz: Outliers, impossible values and rule checks
Summaries, group-by and pivot tables
Combining data: concat and joins
Reshaping: tidy data, melt, pivot and MultiIndex
Dates and time series
- Count daily users and the busiest hour in IST
- Quiz: Dates, times and time zones (IST and UTC)
- Label financial-year quarters and total the revenue
- Quiz: Resampling, frequencies and Indian financial years
- A 7-day average per store that needs 4 observations
- Quiz: Rolling, expanding and weighted windows
- Month-on-month and year-on-year growth for whole months
- Quiz: Growth rates, lags and seasonality
Text extraction and categorical data
Visualising data with matplotlib
Statistics an analyst uses every week
polars: expressions, lazy queries and speed
DuckDB: SQL on DataFrames and files
Performance and scale
Data-quality checks you can automate
Reporting and communicating results
Analyst interviews and take-home assignments
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