saezlab/data_tools

Collection of Python functions and classes designed to make data scientists' life easier.

data_tools

Data tools: a collection of Python functions and classes designed to make data scientists' life easier.

Copyright (C) 2020 Nicolàs Palacio-Escat

Contact: nicolas.palacio@bioquant.uni-heidelberg.de

Disclaimer

This package is still under development and will be periodically updated with new features. Contributions are very welcome (fork + pull request). If you find any bug or suggestion for upgrades, please use the issue system.

GNU-GLPv3: This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

A full copy of the GNU General Public License can be found on file LICENSE.md. If not, see http://www.gnu.org/licenses/.

Contents

• databases
  • kegg_link
  • kegg_pathway_mapping
  • op_kinase_substrate
  • up_map
• diffusion
  • build_mat
  • coef_mat_hetero
• iterables
  • bit_or
  • chunk_this
  • find_min
  • in_all
  • similarity
  • subsets
  • unzip_dicts
• models
  • DoseResponse
  • Lasso
  • Linear
  • PowerLaw
• plots
  • cmap_bkgr
  • cmap_bkrd
  • cmap_rdbkgr
  • chordplot
  • cluster_hmap
  • density
  • pca
  • phase_portrait
  • piano_consensus
  • similarity_heatmap
  • similarity_histogram
  • upset_wrap
  • venn
  • volcano
• signal
  • fconvolve
  • gauss_kernel
  • gauss_noise
• spatial
  • equidist_polar
  • get_boundaries
  • neighbour_count
• strings
  • is_numeric
  • join_str_lists

Dependencies

• NumPy
• Matplotlib
• Pandas
• SciPy
• Scikit-learn
• UpSetPlot
• adjustText
• certifi

Installation

Fast way with pip

If you have pip, just type on the terminal:

pip install git+https://github.com/Nic-Nic/data_tools.git

By cloning the git repository

First download/clone data_tools from the GitHub repository. From the terminal:

git clone https://github.com/Nic-Nic/data_tools.git
cd data_tools

Then you can install it by running setup.py as follows:

python setup.py sdist

Or using pip:

pip install .

Testing the module

Along with data_tools, all dependencies will be installed as well as the testing suite. In order to run the tests, type on the terminal:

python -m test_data_tools

NOTE: data_tools.plots module does not have any tests implemented.

Documentation

You can find a detailed description of the modules and functions within this package in the webpage, also available as a PDF.

You can also find the version history in the changelog.