Dataiter currently includes the following classes.

DataFrame is a class for tabular data similar to R's data.frame or pandas.DataFrame. It is under the hood a dictionary of NumPy arrays and thus capable of fast vectorized operations. You can consider this to be a light-weight alternative to Pandas with a simple and consistent API. Performance-wise Dataiter relies on NumPy and Numba and is likely to be at best comparable to Pandas.

ListOfDicts is a class useful for manipulating data from JSON APIs. It provides functionality similar to libraries such as Underscore.js, with manipulation functions that iterate over the data and return a shallow modified copy of the original. attd.AttributeDict is used to provide convenient access to dictionary keys.

GeoJSON is a simple wrapper class that allows reading a GeoJSON file into a DataFrame and writing a data frame to a GeoJSON file. Any operations on the data are thus done with methods provided by the data frame class. Geometry is read as-is into the "geometry" column, but no special geometric operations are currently supported.

# Latest stable version
pip install -U dataiter

# Latest development version
pip install -U git+https://github.com/otsaloma/dataiter

# Numba (optional)
pip install -U numba

Dataiter optionally uses Numba to speed up certain operations. If you have Numba installed and importing it succeeds, Dataiter will use it automatically. It's currently not a hard dependency, so you need to install it separately.

https://dataiter.readthedocs.io/

If you're familiar with either dplyr (R) or Pandas (Python), the comparison table in the documentation will give you a quick overview of the differences and similarities.

https://dataiter.readthedocs.io/en/latest/comparison.html