Easy handling of missing data (represented as
NaN) in floating point as well as non-floating point data
Size mutability: columns can be inserted/deleted from DataFrame
Powerful, flexible groupby functionality to perform split-apply-combine operations on data sets, for both aggregating and transforming data
Make it easy to convert Arrays, JSONs, List or Objects, Tensors and differently-indexed data structures into DataFrame objects
Intelligent label-based slicing, fancy indexing, and querying of large data sets
Robust IO tools for loading data from flat-files (CSV and delimited) and JSON data format.
Powerful, flexible and intutive API for plotting DataFrames and Series interactively.
Timeseries-specific functionality: date range generation and date and time properties.
New to danfo? Check out the getting started guides. They contain an introduction to danfo's main concepts and links to additional contents.
The reference guide contains a detailed description of the danfo API. The reference describes how each function works and which parameters can be used.
Want to help improve our documentation and existing functionalities? The contributing guidelines will guide you through the process.