chartly 0.0.2

A Python package for chartly multiple plots.

chartly Package

chartly is a simple plotting tool designed to help users create scientific plots with ease. Whether you want to test a distribution for normality or to plot contours onto a map of the globe, chartly can help you achieve your scientific plot with minimal effort. Chartly also allows users to plot multiple overlays and subplots onto the same figure.

Project Status

Here's the current status of our workflows:

Workflow	Status
Testing Suite
Deployment Suite
Sphinx Documentation
Guard Main Branch
Code Quality Checker

Components

The chartly's codebase structure is as shown below:

.
├── chartly/
│   ├── base.py
│   ├── chartly.py
│   ├── charts.py
│   └── utilities.py
│   └── tests/
│   │   ├── __init__.py
│   │   └── test_chartly.py
├── docs/
│   ├── __init__.py
│   ├── source/
|   │   ├── conf.py
|   │   ├── index.rst
|   │   ├── Plot.rst
|   │   └── Multiplots.rst
├── requirements/
│   ├── testing.txt
│   ├── staging.txt
│   └── production.txt
├── LICENSE
├── MANIFEST.in
├── README.md
├── requirements.txt
├── setup.py
└── VERSION

Installation

To install chartly, run this command in your command line:

pip install chartly

Example

Here is an example on how to use chartly to plot.

import chartly
import numpy as np

# 1. Define Some Data
data = np.random.randn(100)

# 2. Define the main figure labels
super_axes_labels = {"super_title": "Simple Example", "super_xlabel": "X", "super_ylabel": "Y"}

# 3. Create a chart instance
plot = chartly.Chart(super_axes_labels)

# 4. Customize the plot and the axes
axes_labels = {"linelabel": "Example Line Label"}
customs = {"linestyle": "dashdot", "color": "mediumslateblue"}

# 5. Plot the data
payload = {"plot": "line_plot", "data": data, "axes_labels": axes_labels, "customs": customs}
plot.new_subplot(payload)

# 6. Render the main figure
plot()