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Easy and fast way of creating scatter plots.

Project description

scatterd

Python PyPI Version License Downloads Donate

  • 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

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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