python主要应用于哪些方面_Python的起源

python主要应用于哪些方面_Python的起源plotnineLatestReleaseLicenseDOIBuildStatusCoverageDocumentationplotnineisanimplementationofagrammarofgraphics

plotnine

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License

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Documentation

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plotnine is an implementation of a grammar of graphics in Python,

it is based on ggplot2. The grammar allows users to compose plots

by explicitly mapping data to the visual objects that make up the

plot.

Plotting with a grammar is powerful, it makes custom (and otherwise

complex) plots easy to think about and then create, while the

simple plots remain simple.

To find out about all building blocks that you can use to create a

plot, check out the documentation. Since plotnine has an API

similar to ggplot2, where we lack in coverage the

ggplot2 documentation may be of some help.

Example

from plotnine import *

from plotnine.data import mtcars

Building a complex plot piece by piece.

Scatter plot

(ggplot(mtcars, aes(‘wt’, ‘mpg’))

+ geom_point())

readme-image-1.png

Scatter plot colored according some variable

(ggplot(mtcars, aes(‘wt’, ‘mpg’, color=’factor(gear)’))

+ geom_point())

readme-image-2.png

Scatter plot colored according some variable and

smoothed with a linear model with confidence intervals.

(ggplot(mtcars, aes(‘wt’, ‘mpg’, color=’factor(gear)’))

+ geom_point()

+ stat_smooth(method=’lm’))

readme-image-3.png

Scatter plot colored according some variable,

smoothed with a linear model with confidence intervals and

plotted on separate panels.

(ggplot(mtcars, aes(‘wt’, ‘mpg’, color=’factor(gear)’))

+ geom_point()

+ stat_smooth(method=’lm’)

+ facet_wrap(‘~gear’))

readme-image-4.png

Make it playful

(ggplot(mtcars, aes(‘wt’, ‘mpg’, color=’factor(gear)’))

+ geom_point()

+ stat_smooth(method=’lm’)

+ facet_wrap(‘~gear’)

+ theme_xkcd())

readme-image-5.png

Installation

Official release

# Using pip

$ pip install plotnine # 1. should be sufficient for most

$ pip install ‘plotnine[all]’ # 2. includes extra/optional packages

# Or using conda

$ conda install -c conda-forge plotnine

Development version

$ pip install git+https://github.com/has2k1/plotnine.git

Contributing

Our documentation could use some examples, but we are looking for something

a little bit special. We have two criteria:

Simple looking plots that otherwise require a trick or two.

Plots that are part of a data analytic narrative. That is, they provide

some form of clarity showing off the geom, stat, … at their

differential best.

If you come up with something that meets those criteria, we would love to

see it. See plotnine-examples.

If you discover a bug checkout the issues if it has not been reported,

yet please file an issue.

And if you can fix a bug, your contribution is welcome.

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