semvec/pypi-packages huggingface dataset:
gnpp 0.1.0
Simple tool for generate new project python
License: MIT

# Generate New Project Python (GNPP)
Simple tool for generate :
- name_project folder
- name_project.py
- LICENSE
- README.md
- setup.py

# Install
```
$ pip install gnpp
```

# Usage
## CLI
```
$ gnpp -h

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██║   ██║██║╚██╗██║██╔═══╝ ██╔═══╝
╚██████╔╝██║ ╚████║██║     ██║
 ╚═════╝ ╚═╝  ╚═══╝╚═╝     ╚═╝
=== Generate New Project Python ===
Simple tool for generate :
name_project folder, name_project.py, LICENSE, README.md, setup.py


Options:
  -h, --help          Display this message
  -p, --project-name  Project name
  -l, --license       License project (apache ,gnu, mit, unlicense)
  -a, --author        Author project
  -d, --description   Description project
  -e, --email         Email project
  -u, --url           Url project
```

```
default:
-p, --project-name  = new_project
-l, --license       = unlicense
-a, --author        = author
-d, --description   = new_project
-e, --email         = new_project@email.com
-u, --url           = https://pypi.org/project/new_project
```

## Combination with shell function
### Example function:
```
new-project() {
  if [ "$1" != "" ] && [ "$2" != "" ] && [ "$3" != "" ] && [ "$4" != "" ]
    then
      gnpp -p "$1" -l "$2" -a "nestero" -e "nes@email.com" -d "$3" -u "$4"
    else
      echo "new-project <project name> <license> <description> <url project>"
  fi
}
```

```
$ new-project "tes projeck" "mit" "ini deskripsi" "www.www.com"
Project tes_projeck has been created :
* README.md
* LICENSE
* setup.py
* tes_projeck
```
bornly 0.3.0
Seaborn-like API for some plotly plots
License: MIT
Requires Python: >=3.7.0

<h1 align="center">
Bornly
</h1>

<p align="center">
<img width="458" alt="Screenshot 2021-12-11 at 19 42 47" src="https://user-images.githubusercontent.com/33491632/145689600-9c31dd60-d0c6-430c-b350-7d24d7eef7fc.png">
</p>

<p align="center">
Seaborn-like API for interactive plotly visualisations
</p>

## Installation

Note: the `$` is not part of the command:

```console
$ pip install -U bornly
```

## Examples

### Lineplot

```python
import bornly as bns

fmri = bns.load_dataset("fmri")
ax = bns.lineplot(data=fmri, x="timepoint", y="signal", hue="event")
ax.figure
```

![lineplot](img/lineplot.png)

### Barplot

```python
import bornly as bns

tips = bns.load_dataset("tips")
ax = bns.barplot(x="day", y="total_bill", data=tips, hue="time")
ax.figure
```

![barplot](img/barplot.png)

### Scatterplot

```python
import bornly as bns

diamonds = bns.load_dataset("diamonds")
ax = bns.scatterplot(
    x="carat",
    y="price",
    hue="clarity",
    size="depth",
    palette="ch:r=-.2,d=.3_r",
    sizes=(1, 8),
    data=diamonds,
)
ax.figure
```

![scatterplot](img/scatterplot.png)

### Kdeplot

```python
import bornly as bns

iris = bns.load_dataset("iris")
ax = bns.kdeplot(data=iris)
ax.figure
```

![kdeplot](img/kdeplot.png)

```python
from string import ascii_letters
import numpy as np
import pandas as pd
import bornly as bns
import matplotlib.pyplot as plt

# Generate a large random dataset
rs = np.random.RandomState(33)
d = pd.DataFrame(data=rs.normal(size=(100, 26)), columns=list(ascii_letters[26:]))
# Compute the correlation matrix
corr = d.corr()
# Generate a mask for the upper triangle
mask = np.triu(np.ones_like(corr, dtype=bool))
# Generate a custom diverging colormap
cmap = bns.diverging_palette(230, 20, as_cmap=True)
# Draw the heatmap with the mask and correct aspect ratio
ax = bns.heatmap(corr, mask=mask, cmap=cmap, vmax=0.3, center=0)
ax.figure
```

![heatmap](img/heatmap.png)

### Pairplot

```python
import bornly as bns

penguins = bns.load_dataset("penguins")
bns.pairplot(penguins, hue="species")
```

![pairplot](img/pairplot.png)

### Histplot

```python
import bornly as bns

penguins = bns.load_dataset("penguins")
ax = bns.histplot(data=penguins, x="flipper_length_mm", hue="species")
ax.figure
```

![histplot](img/histplot.png)