Easy and fast way of creating scatter plots.
Project description
scatterd
- Easy and fast manner of creating scatter plots.
Contents
Installation
- Install scatterd from PyPI (recommended). scatterd is compatible with Python 3.6+ and runs on Linux, MacOS X and Windows.
- It is distributed under the MIT license.
Requirements
pip install numpy matplotlib colourmap
Quick Start
pip install scatterd
- Alternatively, install scatterd from the GitHub source:
git clone https://github.com/erdogant/scatterd.git
cd scatterd
python setup.py install
Import scatterd package
from scatterd import scatterd
Example:
# Import some example data
from sklearn import datasets
iris = datasets.load_iris()
X = iris.data[:, :2] # we only take the first two features.
y = iris.target
# Make simple scatterplot
scatterd(X[:,0], X[:,1])
# Color based on labels
scatterd(X[:,0], X[:,1], label=y, s=100)
# Set labels
scatterd(X[:,0], X[:,1], label=y, s=100, norm=True, cmap='Set2', xlabel='xlabel', ylabel='ylabel', title='Title')
# Change sizes
s=np.random.randint(10,200,len(y))
scatterd(X[:,0], X[:,1], label=y, s=s, cmap='Set2', xlabel='xlabel', ylabel='ylabel', title='Title', fontsize=25, figsize=(15,10))
# Change figure size
scatterd(X[:,0], X[:,1], figsize=(25,15))
Citation
Please cite scatterd in your publications if this is useful for your research. Here is an example BibTeX entry:
@misc{erdogant2019scatterd,
title={scatterd},
author={Erdogan Taskesen},
year={2019},
howpublished={\url{https://github.com/erdogant/scatterd}},
}
Maintainers
- Erdogan Taskesen, github: erdogant
Contribute
- Contributions are welcome.
Licence
See LICENSE for details.
Donation
- This package is created and maintained in my free time. If this package is usefull, you can show your gratitude :) Thanks!
Project details
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