semvec/pypi-packages huggingface dataset:
kubernetes-explorer 1.0.1
Kubernetes Explorer lets you create a graph of the objects and dependencies inside your Kubernetes cluster.
Requires Python: >=3.6

# Kubernetes Explorer

Kubernetes Explorer lets you have an overview of the applications deployed on your Kubernetes cluster.  
It helps you create a Graphviz file showing the objects and dependencies inside your cluster.

## Creator

Jonathan Donzallaz

## Deployment

```bash
python setup.py sdist bdist_wheel
python -m twine upload dist/*
```
confplot 0.1.1
Plot a pretty confusion matrix (like Matlab) in python using seaborn and matplotlib
Requires Python: >=3.6

# ConfPlot: Plot Confusion Matrix in Python

[![PyPI version](https://badge.fury.io/py/confplot.svg)](https://badge.fury.io/py/confplot)
![CI](https://github.com/fcakyon/confplot/workflows/CI/badge.svg)

Plot a pretty confusion matrix (like Matlab) in python using seaborn and matplotlib

This module lets you plot a pretty looking confusion matrix from a np matrix or from a prediction results and actual labels.

Sample plots:

<img src="screenshots/conf_matrix_plot1.png" width="450"> <img src="screenshots/conf_matrix_plot2.png" width="450">

## Getting started

### Installation

```console
pip install confplot
```

### Usage

#### Plot confusion matrix from matrix

```python
# import package
import confplot

# assume you have a confusion matrix array like this
array = np.array(
    [[13,  0,  1,  0,  2,  0],
     [ 0, 50,  2,  0, 10,  0],
     [ 0, 13, 16,  0,  0,  3],
     [ 0,  0,  0, 13,  1,  0],
     [ 0, 40,  0,  1, 15,  0],
     [ 0,  0,  0,  0,  0, 20]]
)

# convert it to a pandas dataframe
df_cm = DataFrame(array, index=range(1, 7), columns=range(1, 7))

# create and save confusion matrix plot as "cm_plot.png"
confplot.plot_confusion_matrix_from_matrix(df_cm, outfile="cm_plot.png")
```

#### Plot confusion matrix from data
```python
# import package
import confplot

# assume you have 1D y_true (actual values) and y_pred (predictions) arrays
y_true = ...
y_pred = ...

# arange targetclass names if you want
columns = ["ahududu", "ananas", "armut", "avokado", "ayva"]

# create and save confusion matrix plot as "cm_plot.png"
confplot.plot_confusion_matrix_from_data(
    y_true,
    y_pred,
    columns,
    outfile="cm_plot.png"
)
```