kaplanmeier 0.1.4

Create survival curves using kaplanmeier, the log-rank test and making plots.

kaplanmeier - Python package to compute the kaplan meier curves, log-rank test, and make the plots.

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Installation

• Install kaplanmeier from PyPI (recommended). kaplanmeier is compatible with Python 3.6+ and runs on Linux, MacOS X and Windows.
• Distributed under the MIT license.

Requirements

• Create environment:

conda create -n env_KM python=3.6
conda activate env_KM
pip install matplotlib numpy pandas seaborn lifelines

Installation

pip install kaplanmeier

Import kaplanmeier package

import kaplanmeier as km

Example:

df = km.example_data()
time_event=df['time']
censoring=df['Died'] 
labx=df['group']

# Compute survival
out=km.fit(time_event, censoring, labx)

Make figure with cii_alpha=0.05 (default)

km.plot(out)

km.plot(out, cmap='Set1', cii_lines=None, cii_alpha=0.05)

km.plot(out, cmap='Set1', cii_lines='line', cii_alpha=0.05)

km.plot(out, cmap=[(1, 0, 1),(0, 1, 1)])

km.plot(out, cmap='Set2')

km.plot(out, cmap='Set2', methodtype='custom')

• df looks like this:

     time  Died  group
0     485     0      1
1     526     1      2
2     588     1      2
3     997     0      1
4     426     1      1
..    ...   ...    ...
175   183     0      1
176  3196     0      1
177   457     1      2
178  2100     1      1
179   376     0      1

[180 rows x 3 columns]

Citation

Please cite kaplanmeier in your publications if this is useful for your research. Here is an example BibTeX entry:

@misc{erdogant2019kaplanmeier,
  title={kaplanmeier},
  author={Erdogan Taskesen},
  year={2019},
  howpublished={\url{https://github.com/erdogant/kaplanmeier}},
}

References

• http://lifelines.readthedocs.io/en/latest/Survival%20analysis%20with%20lifelines.html

Maintainer

• Erdogan Taskesen, github: erdogant
• Contributions are welcome.
• If you wish to buy me a Coffee for this work, it is very appreciated :)