Metadata-Version: 2.1
Name: pandas-utility
Version: 0.1.3
Summary: Some useful Pandas utility functions
Home-page: https://github.com/mmphego/pandas_utility
Author: pandas_utility
Author-email: mpho112@gmail.com
License: MIT license
Project-URL: Bug Reports, https://github.com/mmphego/pandas_utility/issues
Project-URL: Source, https://github.com/mmphego/pandas_utility
Project-URL: Say Thanks!, https://saythanks.io/to/mmphego
Keywords: pandas_utility
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Requires-Python: >=3.6.0
Description-Content-Type: text/markdown
Requires-Dist: pandas
Requires-Dist: numpy


# Pandas Utility

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Some useful Pandas utility functions.

# Installation

To install Pandas Utility, run this command in your terminal:

```python
    pip install pandas_utility
```

This is the preferred method to install Pandas Utility,
as it will always install the most recent stable release.

If you don't have [pip](https://pip.pypa.io) installed,
this [Python installation guide](http://docs.python-guide.org/en/latest/starting/installation/) can guide you through the process.

## From sources

The sources for Pandas Utility can be downloaded from the [Github repo](https://github.com/mmphego/pandas_utility).

You can either clone the public repository:

```bash
git clone git://github.com/mmphego/pandas_utility
```

Or download the [tarball](https://github.com/mmphego/pandas_utility/tarball/master):

```bash
curl  -OL https://github.com/mmphego/pandas_utility/tarball/master
```

Once you have a copy of the source, you can install it with:

```bash
pip install -U .
```

# Usage

```python
In [1]: from pandas_utility import PandasUtilities as utils
   ...:
   ...: df = utils.create_random_df(3, 5)

In [2]: df
Out[2]:
          0         1         2         3         4
0  0.056019  0.608052  0.434670  0.712330  0.602797
1  0.050986  0.458700  0.899288  0.783495  0.683170
2  0.232940  0.707126  0.639882  0.675283  0.793030

In [3]: df = utils.rename_cols(df, new_names=['col A', 'col B', 'col C', 'col D', 'col E'])

In [4]: df
Out[4]:
      col_A     col_B     col_C     col_D     col_E
0  0.056019  0.608052  0.434670  0.712330  0.602797
1  0.050986  0.458700  0.899288  0.783495  0.683170
2  0.232940  0.707126  0.639882  0.675283  0.793030

```

# Oh, Thanks!

By the way...
Click if you'd like to [saythanks](https://saythanks.io/to/>mmphego)... :) else *Star* it.

✨🍰✨

# Feedback

Feel free to fork it or send me PR to improve it.

# Credits

This package was created with [Cookiecutter](https://github.com/audreyr/cookiecutter) and the [mmphego/cookiecutter-python-package](https://github.com/mmphego/cookiecutter-python-package) project template.


