Classes for data manipulation
Project description
Python Classes for Data Manipulation
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.
Installation
# 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.
Documentation
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.
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