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        "description": "Python Classes for Data Manipulation\n====================================\n\n[![Test](https://github.com/otsaloma/dataiter/workflows/Test/badge.svg)](https://github.com/otsaloma/dataiter/actions)\n[![Documentation Status](https://readthedocs.org/projects/dataiter/badge/?version=latest)](https://dataiter.readthedocs.io/en/latest/?badge=latest)\n[![PyPI](https://img.shields.io/pypi/v/dataiter.svg)](https://pypi.org/project/dataiter/)\n[![Downloads](https://pepy.tech/badge/dataiter/month)](https://pepy.tech/project/dataiter)\n\nDataiter currently includes the following classes.\n\n**`DataFrame`** is a class for tabular data similar to R's `data.frame`\nor `pandas.DataFrame`. It is under the hood a dictionary of NumPy arrays\nand thus capable of fast vectorized operations. You can consider this to\nbe a light-weight alternative to Pandas with a simple and consistent\nAPI. Performance-wise Dataiter relies on NumPy and Numba and is likely\nto be at best comparable to Pandas.\n\n**`ListOfDicts`** is a class useful for manipulating data from JSON\nAPIs. It provides functionality similar to libraries such as\nUnderscore.js, with manipulation functions that iterate over the data\nand return a shallow modified copy of the original. `attd.AttributeDict`\nis used to provide convenient access to dictionary keys.\n\n**`GeoJSON`** is a simple wrapper class that allows reading a GeoJSON\nfile into a `DataFrame` and writing a data frame to a GeoJSON file. Any\noperations on the data are thus done with methods provided by the data\nframe class. Geometry is read as-is into the \"geometry\" column, but no\nspecial geometric operations are currently supported.\n\n## Installation\n\n```bash\n# Latest stable version\npip install -U dataiter\n\n# Latest development version\npip install -U git+https://github.com/otsaloma/dataiter#egg=dataiter\n\n# Numba (optional)\npip install -U numba\n```\n\nDataiter optionally uses **Numba** to speed up certain operations. If\nyou have Numba installed and importing it succeeds, Dataiter will use it\nautomatically. It's currently not a hard dependency, so you need to\ninstall it separately.\n\n## Documentation\n\nhttps://dataiter.readthedocs.io/\n\nIf you're familiar with either dplyr (R) or Pandas (Python), the\ncomparison table in the documentation will give you a quick overview of\nthe differences and similarities.\n\nhttps://dataiter.readthedocs.io/en/latest/comparison.html\n\n\n",
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