Skip to main content

A data analysis and visualization helper module.

Project description

[![Build Status](https://travis-ci.org/fmv1992/data_utilities.svg?branch=master)](https://travis-ci.org/fmv1992/data_utilities)

# Data Utilities

This module provides some helper functions and conveniences for working with
data analysis in python.

It depends on:

* Numpy
* Scipy
* Pandas
* Matplotlib
* Seaborn
* Scikit-learn

# Organization and files

.
├── data_utilities
│   ├── matplotlib_utilities.py
│   ├── pandas_utilities.py
│   └── python_utilities.py
├── readme.md
└── tests
└── test.py

Each of python's significant data modules has its own set of helper functions.

This module does not intend to create its own API or standards. Instead each of
the utilities module should follow the guidelines and APIs provided by the
parent module.

Note: This is a primitive project. Expect backwards incompatible changes as I
figure out the best way to to develop the utilities. Use at your own risk :)

# TODO

* Add test to every function.
- Current coverage: 56%

* Move changelog and todo sections to separate files
(https://github.com/pypa/sampleproject)

* ~~Setup TravisCI, add stickers of TravisCI and coverage of functions with
tests.~~

# Changelog

#### Version 1.2.0

<!---
* `matplolib_utilities`
* A

* `pandas_utilities`
* A

* `python_utilities`
* A
-->

* Other
* Added package to PyPA as "data_utilities" # XXX
* Added a test method to the package:
python3 -c "import data_utilities as du; du.test()"

#### Version 1.1.0

* Improved `histogram_of_dataframe` function: added a textbox with summary
statistics.

* Added a function to scale axes axis (`scale_axes_axis`).

* Added a colorbar argument to `plot_3d`.

* Label containers now return a list of matplotlib Text objects.

* Added a boolean column to `dummy_dataframe`.

* Added a test module for other libraries: `matplotlib_utilities` and
`python_utilities`.

* Cleaned up the code.

#### Version 1.0.0

* Incompatible changes: the two utility functions to create dummy dataframes
now use a keyword argument 'shape' instead of 'n' or 'rows' and 'columns' to
resemble the numpy interface.

#### Version 0.1.1

* Added a convenience function (`statistical_distributions_dataframe`) of
variable size initialized with some common statistical distributions.

* Added a test module which allows parametrized tests via the `TestMetaClass`.

* Added a test module for the `find_components_of_array` function.

#### Version 0.0.1

* First commit.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

data_utilities-1.2.5.tar.gz (19.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

data_utilities-1.2.5-py3-none-any.whl (23.8 kB view details)

Uploaded Python 3

File details

Details for the file data_utilities-1.2.5.tar.gz.

File metadata

File hashes

Hashes for data_utilities-1.2.5.tar.gz
Algorithm Hash digest
SHA256 f1ec431aba88f937c772470e520b80ba5e91199040942fa56249eef0a720c134
MD5 42a2a0735bd25ba8ca69ba62959d4d7a
BLAKE2b-256 c1ba5f064f706f5d99a4b7bb0a2f1d555098d7090cec7a990ed42955b9c2cb11

See more details on using hashes here.

File details

Details for the file data_utilities-1.2.5-py3-none-any.whl.

File metadata

File hashes

Hashes for data_utilities-1.2.5-py3-none-any.whl
Algorithm Hash digest
SHA256 721fb4fa5febd9f0594cec371d768ae75b2e6d11c0f2b5db013111859f6d9d3a
MD5 d24d2454c1631ed3fc8086051e2ea3dc
BLAKE2b-256 9f4deb028547d17de53366585df0c7d704273ae7dfc6253944dd67650ba6efcb

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page