semvec/pypi-packages huggingface dataset:
spotifyapi-wrapper 2.0.2
A small Spotify API that can help you get the data of the user who issued the token.
License: MIT

# spotiapi
A small library for getting convenient and structured information about the Spotify user (currently only about the user
who created the app key). Last library version - **2.0.2** (`pip install -U spotiapi==2.0.1`).

![MIT](https://img.shields.io/github/license/Julheer/spotiapi.svg)
![Version](https://img.shields.io/pypi/v/spotiapi)

## Requirements

This library requires one additional library: [http3](https://github.com/encode/httpx) (versions **>=0.6.7**). It will
be installed automatically when you download my library from PyPI.

## Installation
To install the library, you will need the Python - `pip` package manager. You can install the library by writing a single command - `pip install -U spotiapi`. You can also specify a specific version. Please [check this](https://pypi.org/project/spotiapi) for more information.

## Examples
Getting information about the user who created the current token:
```python
from asyncio import run
from spotiapi import SpotifyAPIWrapper

spotify = SpotifyAPIWrapper('spotify_api_token')


async def request_data():
    request_self = await spotify.get_self()
    if 'error' in request_self:
        return print(f'Something went wrong... ({request_self["code"]})')

    return print(f'Hello, {request_self["display_name"]}!')

if __name__ == '__main__':
    run(request_data())

```

You can find other examples [here](https://github.com/julheer/spotiapi/blob/main/examples), or on the pages of other users who used this repository and pointed this repository out.

© [Julheer](https://github.com/julheer), 2021. Developed with ❤.
termtitle 0.2.0
A command line program to change macOS terminal title
License: MIT

terminal title change
=====================

End user Installation via Homebrew
----------------------------------

``brew install termtitle``

If it is not accessable, try 

``brew install https://raw.githubusercontent.com/grimmer0125/homebrew-core/termtitle/Formula/termtitle.rb``

End user Installation via pip
-----------------------------

.. image:: https://img.shields.io/pypi/dw/termtitle.svg

Thare are several ways to install, and it depends on your Python environment and preference.

1. default system python + install globally (accessable for each user)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

``sudo pip install termtitle``

2. default system python + install in current user folder
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

``pin install --user termtitle``.

But you need to add Python bin directories to PATH,

- test it first, ``python2.7 -m site &> /dev/null && PATH="$PATH:`python2.7 -m site --user-base`/bin"`` (ref: https://stackoverflow.com/a/48380776/7354486)
- ``termtitle random_title``
- if you see your titles change, then you can permanently change your PATH, ``echo 'export PATH="$PATH:`python2.7 -m site --user-base`/bin"' >>~/.bash_profile``

3. Python3+pip3 (which might be from "brew install python3")
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

``pip3 install termtitle``.

4. non system Python of pyenv
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

``pip install termtitle``.

Usage
---------------------

If you are using zsh and this package does not take effect, you might need to set `DISABLE_AUTO_TITLE="true"` in `~/.zshrc` and restart shell to try again.


- ``termtitle demo_project_root``
- ``termtitle 這是秘密的鋼彈計劃``
- ``termtitle サイボーグ009のメンバー``
- ``termtitle ""`` # reset the title to empty


Dev
---------------------

local test:

- Install: `python setup.py install`
- Uninstall: `pip uninstall termtitle`

publish:

1. change ``version="x.y.z`` in ``setup.py``
2. ``python setup.py check --restructuredtext -s`` do some check before publishing
3. ``python setup.py sdist``
4. Use twine to publish: ``twine upload dist/*``
spotiapi 2.0.1
A small Spotify API that can help you get the data of the user who issued the token.
License: MIT

# spotiapi
A small library for getting convenient and structured information about the Spotify user (currently only about the user
who created the app key). Last library version - **2.0.1** (`pip install -U spotiapi==2.0.1`).

![MIT](https://img.shields.io/github/license/Julheer/spotiapi.svg)
![Version](https://img.shields.io/pypi/v/spotiapi)

## Requirements

This library requires one additional library: [http3](https://github.com/encode/httpx) (versions **>=0.6.7**). It will
be installed automatically when you download my library from PyPI.

## Installation
To install the library, you will need the Python - `pip` package manager. You can install the library by writing a single command - `pip install -U spotiapi`. You can also specify a specific version. Please [check this](https://pypi.org/project/spotiapi) for more information.

## Examples
Getting information about the user who created the current token:
```python
from asyncio import run
from spotiapi import SpotifyAPIWrapper

spotify = SpotifyAPIWrapper('spotify_api_token')


async def request_data():
    request_self = await spotify.get_self()
    if 'error' in request_self:
        return print(f'Something went wrong... ({request_self["code"]})')

    return print(f'Hello, {request_self["display_name"]}!')

if __name__ == '__main__':
    run(request_data())

```

You can find other examples [here](https://github.com/julheer/spotiapi/blob/main/examples), or on the pages of other users who used this repository and pointed this repository out.

© [Julheer](https://github.com/julheer), 2021. Developed with ❤.
sparse-profile 0.1.1
EDA on sparse data for classification problems
License: MIT
Keywords: eda,sparse data,classification

# Sparse profile  - EDA on sparse data
Module to perform EDA tasks for a classification problem with sparse data<br>
Curently takes only numeric values

Sample usage
------------
```python
import pandas as pd
import numpy as np
from sparse_profile import sparse_profile

df = pd.DataFrame({
        'target' : [1, 1, 1, 1, 0, 0 ,0 ,0, 1, 0],
        'col_1' :  [1, 0, 0, 0, 0, 0, 0, 0, 0, 9],
        'col_2' :  [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
    })
sProfile = sparse_profile(df, 'target')
print(sProfile.top_gain)
```
Output maximum gain obtained from each column
```
col_2    0.422810
col_1    0.074882
dtype: float64
```

```python
print(sProfile.report_sparsity)
```
Output percentage of zeros in column

```
col_1  0.8
col_2  0.1
```

Various sparse_profile reports can be accessed as attributes of the sparse_profile class object. List of all available attributes:
* report_sparsity:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; pandas dataframe, Percentage of zeros in each column
* report_distinct:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;pandas dataframe, Count of distinct non zero values in each column
* report_overall:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;pandas dataframe, Overall summary of each column (similar to pandas describe())
* report_non_zero:&nbsp;&nbsp;&nbsp;&nbsp;pandas dataframe, Summary of each column after removing zeros
* gain_df:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;pandas dataframe, Relative information gain at decile cutoffs for each column wrt target column
* auc_df:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;pandas dataframe, AUC of each column wrt target column
* top_gain:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;pandas dataframe, Columns sorted by maximum gain obtained from gain_df