semvec/pypi-packages huggingface dataset:
wizad 0.1.0
A simple visualization library for univariate and bivariate analysis
Requires Python: >=3.7

This is a simple package to help you do univariate and bivariate analysis on numerc and categorical features. The visuals are generated using matplotlib and seaborn. The package is still in development and more features will be added soon. The usp is that in a single figure with subplots all the visuals are presented in a compact manner with a simple function call and passing the dataframe and a list of numeric or categorical features.
musicTour 1.6.0
Get all the artists and/or all styles of the world
Requires Python: >=3.7

# Description

MusicTour generates a JSON or returns all the styles and/or artists in the world.

It is based on the website https://everynoise.com/

# Quick start

```python
import musicTour
musicTour.getAll() # Generates a JSON with all styles and artists in the world
```

# Warning

Generating all the styles and/or artists can take several dozens of minutes.

# Parameters

The function musicTour.getAll() can take 3 arguments.
By default, they are all set to True.

# musicTour.getAll(styles, artists, output)

All three arguments are booleans.

To generate a JSON, you have to set the third argument to True.

Examples:

```python
musicTour.getAll(True, True, True) # generates a JSON of all styles and artists.

musicTour.getAll(False, True, True) # generates a JSON of all artists.

musicTour.getAll(True, False, True) # generates a JSON of all styles.
```

When you just want to return the value in a variable, you can set the third argument to False:

Examples:

```python
allArtistsStyles = musicTour.getAll(True, True, False)
print(allArtistsStyles) # Prints all styles and artists

musicTour.getAll(False, True, False)# returns all artists.

musicTour.getAll(True, False, False)# returns all styles.
```