Dataiter Documentation

Dataiter’s DataFrame is a class for tabular data similar to R’s data.frame, implementing all common operations to manipulate data. It is under the hood a dictionary of NumPy arrays and thus capable of fast vectorized operations. You can consider it to be a light-weight alternative to Pandas with a simple and consistent API. Performance-wise Dataiter relies on NumPy and PyArrow and is likely to be at best comparable to Pandas.

Additionally Dataiter includes ListOfDicts, a class for manipulating hierarchical data, such as from JSON APIs or document databases, and GeoJSON, a class for manipulating data from GeoJSON files in a data frame.

Tutorials

• Quick Start
• Comparison
• Aggregation

API Documentation

• dataiter
• dataiter.DataFrame
• dataiter.DataFrameColumn
• dataiter.GeoJSON
• dataiter.ListOfDicts
• dataiter.Vector
• dataiter.dt
• dataiter.dtypes
• dataiter.regex

For Coding Agents

• llms.txt

• llms-full.txt

Without a terminal, as is usually the case for coding agents, print output is wrapped to dataiter.PRINT_MAX_WIDTH columns, which splits wide data frames into several blocks of columns. To get one line per row, you might want to disable wrapping with di.PRINT_MAX_WIDTH = math.inf. To save context, you might also want to print fewer rows, e.g. di.PRINT_MAX_ROWS = 10. See dataiter for other print settings.