New to Python
Begin with variables, lists, and dictionaries. Build your first table one step at a time.
Start from the beginningFree course · Practical reference · Real Python
Understand your data.
Explain your code.
Learn pandas from Python dictionaries to complete data analysis. Predict a result, run the code, change something, and explain what happened.
30 modules120 worked examples & tasks8 independent assessment tasks6 data file formats
Choose your starting point
Coming from spreadsheets
Start with tables and familiar operations, then explore indexes, grouping, and files.
Start with DataFramesAlready using Python
Explore pandas behavior: labels, selection, missing data, joins, and grouped calculations.
Start with SeriesSolving a problem today
Find a short example, a common mistake, and a link to the full explanation.
Open the referenceMake understanding visible
Each lesson includes a small example, three questions, a change to make, a hint, a worked solution, and a code check. Follow the guided path or switch a lesson to Quick reference.
Written explanations matter. A successful code check shows that the programmed requirements passed; use the independent assessment and its rubric to examine understanding on unfamiliar data.
The complete learning path
Move in order or use a module's prerequisites to choose where to begin.
00 · Foundation
A short Python bridge
Read the small amount of Python needed to begin the pandas lessons.
4 learning cells · questions, practice & solutions01 · FoundationStart with a dictionary
Read, access, and change named values in a Python dictionary.
4 learning cells · questions, practice & solutions02 · FoundationFrom one student to many
Represent several records with lists and dictionaries before building a table.
4 learning cells · questions, practice & solutions03 · FoundationMeet the pandas Series
Create a labeled column and explain positions, labels, and arithmetic.
4 learning cells · questions, practice & solutions04 · FoundationBuild and inspect a DataFrame
Turn Python data into a table and inspect its structure before analysis.
4 learning cells · questions, practice & solutions05 · FoundationSelect exactly what you need
Choose rows, columns, and individual cells using labels and positions.
4 learning cells · questions, practice & solutions06 · CoreFilter with conditions
Build Boolean masks and combine conditions to answer precise questions.
4 learning cells · questions, practice & solutions07 · CoreSorting and index decisions
Order records deliberately and control which labels identify rows.
4 learning cells · questions, practice & solutions08 · CoreCreate and update columns
Calculate new fields, tidy column names, and change selected values safely.
4 learning cells · questions, practice & solutions09 · CoreData types and safe conversion
Choose a useful data type and identify values that cannot be converted.
4 learning cells · questions, practice & solutions10 · CoreMissing values and honest cleaning
Find missing entries and choose a treatment that fits the question.
4 learning cells · questions, practice & solutions11 · CoreDuplicates and data quality
Find repeated records and validate IDs, ranges, and allowed labels.
4 learning cells · questions, practice & solutions12 · CoreClean and search text
Standardize labels and extract useful pieces from text columns.
4 learning cells · questions, practice & solutions13 · CoreDates, times, and durations
Parse dates explicitly and use calendar-aware operations.
4 learning cells · questions, practice & solutions14 · CoreMap, apply, and vectorize
Choose an appropriate way to transform values and create categories.
4 learning cells · questions, practice & solutions15 · CoreStatistics you can explain
Summarize center, spread, completeness, and association with clear interpretations.
4 learning cells · questions, practice & solutions16 · CoreGroup, summarize, and compare
Distinguish group summaries, row-aligned transformations, and group filters.
4 learning cells · questions, practice & solutions17 · CoreMerge related tables
Connect tables by a key and audit which records matched.
4 learning cells · questions, practice & solutions18 · CoreConcatenate and align
Combine rows or columns while respecting index labels.
4 learning cells · questions, practice & solutions19 · CoreReshape tables
Move between long and wide layouts and choose when to aggregate.
4 learning cells · questions, practice & solutions20 · CoreRead and write files
Move data between pandas and common local file formats.
4 learning cells · questions, practice & solutions21 · ExtensionWork with time series
Distinguish calendar dates, observed records, windows, and changes over time.
4 learning cells · questions, practice & solutions22 · ExtensionExplore richer structures
Use multiple index levels, list-valued columns, and categorical encodings.
4 learning cells · questions, practice & solutions23 · ExtensionWork efficiently and reproducibly
Read less data, combine chunk summaries correctly, and make repeatable samples.
4 learning cells · questions, practice & solutions24 · CorePlot and interpret
Select a plot that answers a clear question and label its units.
4 learning cells · questions, practice & solutions25 · ApplyDebugging clinic
Find the reason a pandas result is wrong, then repair it.
4 learning cells · questions, practice & solutions26 · ApplyEnd-to-end classroom project
Clean, audit, summarize, visualize, and export a small dataset with an explanation of every choice.
4 learning cells · questions, practice & solutions27 · ExtensionImport CSV and text with confidence
Choose explicit parsing rules, preserve identifiers, and verify imported records.
4 learning cells · questions, practice & solutions28 · ExtensionWork across Excel and JSON formats
Read worksheets and JSON structures without changing the underlying observations.
4 learning cells · questions, practice & solutions29 · ApplyAnalyze a real public dataset
Produce a traceable descriptive analysis with justified exclusions and visible denominators.
4 learning cells · questions, practice & solutions