text: Calculate KS statistic for models
  Project description
  Title
  summary
  pyks
  The goal of
  pyks is to help do calculation KS statistic for a model.
  The R version rawKS is hosted
  from GitHub.
  Installation
  You can install the released version of
  pyks from Anaconda
  Cloud with:
  conda install -c jiaxiangbu pyks
  or the released version of
  pyks from Python Package
  Index with:
  pip install pyks
  or the development version from GitHub with:
  pip install git+
  Citations
  If you use pyks, I would be very grateful if you can add a citation in your published work. By citing pyks, beyond acknowledging the work, you contribute to make it more visible and guarantee its growing and sustainability. For citation, please use the BibTex or the citation content.
  @misc{jiaxiang_li_2019_3351276, author = {Jiaxiang Li}, title = {JiaxiangBU/pyks: pyks 1.1.3}, month = jul, year = 2019, doi = {10.5281/zenodo.3351276}, url = {} }
  Jiaxiang Li. (2019, July 25). JiaxiangBU/pyks: pyks 1.1.3 (Version v1.1.3). Zenodo.
  Disclaimers
  Code of Conduct
  Please note that the
  pyks project is released with a Contributor Code
  of Conduct.
  By contributing to this project, you agree to abide by its terms.
  License
  MIT \u00a9 Jiaxiang Li
  Examples
  import pandas as pd import numpy as np
  df1 = pd.read_csv('refs/two_class_example.csv')
  from pyKS.ks import perf
  perf(df1).chart()
  0.727689153693382
  The function `plot` is depreciated, use `perf.plot()` <Figure size 432x288 with 0 Axes>
  perf(df1).table()
  The function `summary` is depreciated, use `perf.table()`
  </style></style>
  .dataframe tbody tr th { vertical-align: top; } .dataframe thead th { text-align: right; }
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