mplscience
Matplotlib style for scientific publications. This style keeps things pretty simple and aims to make moderate improvements to the base matplotlib style. It also sets things like the PDF font type to make it easier to interact with figures in Adobe Illustrator. Open the tutorial in Colab to see examples. mplscience is compatible with all Matplotlib-based packages, including Seaborn.
Usage
import mplscience
import seaborn as sns
mplscience.available_styles()
mplscience.set_style()
df = sns.load_dataset("anscombe")
sns.scatterplot(x="x", y="y", hue="dataset", data=df)
If you're using Seaborn, you may want to run sns.reset_orig() first to clear Seaborn-specific styling. You can also use the reset_current parameter of mplscience functions to reset any custom styling like this:
mplscience.set_style(reset_current=True)
The style can also be using in a context like this:
import mplscience
with mplscience.style_context():
plt.plot(x, y)
1 maintainer
Metadata
1 maintainer
Release files for mplscience 0.0.5
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| mplscience-0.0.5.tar.gz | 4.2 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| mplscience-0.0.5-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 8.9 kB
Release files / mplscience-0.0.5.tar.gz
| Download URL | mplscience-0.0.5.tar.gz |
|---|---|
| Size | 4.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
a53af8af6571fcd8d07cc27ebd201ac0e717063788c96d9036027638e725133a
|
|
BLAKE2b-256 checksum How to use checksums |
1a4e38e1f55d40b21b5efa424ed8ad7e23f1c5d13eb20e47e1da50828c03debb
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/1.1.4 CPython/3.7.6 Darwin/20.3.0
|
Release files / mplscience-0.0.5-py3-none-any.whl
| Download URL | mplscience-0.0.5-py3-none-any.whl |
|---|---|
| Size | 4.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
d0c71f9ac4ff44002584d288dba1cd3a3cd2f0f163366aa525a12428f2adfb25
|
|
BLAKE2b-256 checksum How to use checksums |
5b9f7da7a72ebf1d203fd6a3aae30a3ad6898d519a2be89a372ca3f765d08f3d
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/1.1.4 CPython/3.7.6 Darwin/20.3.0
|
Security for mplscience 0.0.5
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.
