ulist

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Documentation <https://rust-data-science.github.io/ulist/>__ | Source Code <https://github.com/tushushu/ulist>__

What

| Ulist is an ultra fast list/array data structure written in Rust with
  Python bindings. It aims to be the fundamental package for processing
  and computing 1-D list/array in Python.
| It provides:

-  an efficient, flexible and expressive 1-D list/array object;
-  broadcasting methods;
-  a SQL-like and method-chaining programming experience;

Performance

| Ulist is extremly fast, and even compared with libraries like Numpy. It is

• more efficient on the string and boolean array,
• same level efficient on the integer array,
• and a bit slower on the floating array.

Faster than Numpy is not the target of writing this repo, because they are just two different libraries. Ulist is more focused on general domain rather than just data science/machine learning/AI, for example the Linear Algebra Computation is not provided. But if you are curious about the performance, please see the benchmarking results <https://github.com/tushushu/ulist/blob/main/benchmark.rst>__.

Requirements

-  Python: 3.7+
-  OS: Linux, MacOS and Windows

Installation

Run pip install ulist

Examples

Count the number of items in bins.
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

Given an array ``arr``, count the number of items in bins [0, 3), [3, 6), [6, 9) and [9, +inf). The ``result`` is a Python dictionary with bin names as keys and numbers as values.

.. code:: python

   >>> import ulist as ul

   >>> arr = ul.arange(12)
   >>> arr
   UltraFastList([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11])

   >>> result = arr.case(default='[9, +inf)')\
   ...             .when(lambda x: x < 3, then='[0, 3)')\
   ...             .when(lambda x: x < 6, then='[3, 6)')\
   ...             .when(lambda x: x < 9, then='[6, 9)')\
   ...             .end()\
   ...             .counter()
   >>> result
   {'[3, 6)': 3, '[9, +inf)': 3, '[6, 9)': 3, '[0, 3)': 3}

Dot product.
^^^^^^^^^^^^

Given two 1-D arrays and calculate the dot product result of those arrays.

.. code:: python

   >>> import ulist as ul

   >>> arr = ul.from_seq(range(1, 4), dtype='float')
   >>> arr
   UltraFastList([1.0, 2.0, 3.0])

   >>> result = arr.mul(arr).sum()
   >>> result
   14.0

Rate of adults.
^^^^^^^^^^^^^^^

Given the ages of people as ``arr``, and suppose the adults are equal or above 18. Clean the data by removing abnormal values and then calculate the rate of adults.

.. code:: python

   >>> import ulist as ul

   >>> arr = ul.from_seq([-1, 10, 15, 20, 30, 50, 70, 80, 100, 200], dtype='int')
   >>> result = arr.where(lambda x: (x >= 0) & (x < 120))\
   ...             .apply(lambda x: x >= 18)\
   ...             .mean()
   >>> result
   0.75

Contribute

All contributions are welcome. See Developer Guide <https://github.com/tushushu/ulist/blob/main/develop.rst>__

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