Master the powerful pandas library to analyze, manipulate and visualize data. More than 10 datasets & bonuses included!
InstructorAndy Bek
Free
The curriculum employs a structured pattern of skill challenges followed by detailed solutions to reinforce technical tasks across multiple sections.
Instruction extends beyond basic manipulation to include technical deep dives into memory storage, binary operations, and callables.
Editorial course preview
These 4 complementary views highlight concrete, legible examples from the course presentation.
This slide recaps selection terminology by mapping specific pandas .loc syntax examples to their corresponding operations, such as slicing, boolean masking, and fancy indexing.
This notebook interface displays a skill challenge requiring students to analyze a games dataset by creating visualizations like pie plots and bar charts.
This diagram illustrates how the fillna function operates along different axes in a pandas DataFrame, visualizing forward and backward fill directions.
This infographic illustrates vectorization by showing how data passes through a processor to complete operations in fewer cycles using SIMD technology.
Content relies on older pandas versions, which may result in encountering deprecated or removed methods in modern environments. While a recent update label is present, one signal from 2025 suggests these issues persist, meaning the update may not have addressed them.
Evidence indicates that technical queries in the Q&A section may remain unanswered, suggesting a lack of ongoing support. A signal from late 2025 notes this pattern, and while an update label exists, it does not prove a correction has been made.
The curriculum aligns with the goal of mastering pandas through a structured progression.