plotnine.geoms.geom_point

class plotnine.geoms.geom_point(*args, **kwargs)[source]

Plot points (Scatter plot)

Usage

geom_point(mapping=None, data=None, stat='identity', position='identity',
           na_rm=False, inherit_aes=True, show_legend=None, **kwargs)

Only the mapping and data can be positional, the rest must be keyword arguments. **kwargs can be aesthetics (or parameters) used by the stat.

Parameters:
mapping : aes, optional

Aesthetic mappings created with aes(). If specified and inherit.aes=True, it is combined with the default mapping for the plot. You must supply mapping if there is no plot mapping.

Aesthetic Default value
x  
y  
alpha 1
color 'black'
fill None
group  
shape 'o'
size 1.5
stroke 0.5

The bold aesthetics are required.

data : dataframe, optional

The data to be displayed in this layer. If None, the data from from the ggplot() call is used. If specified, it overrides the data from the ggplot() call.

stat : str or stat, optional (default: identity)

The statistical transformation to use on the data for this layer. If it is a string, it must be the registered and known to Plotnine.

position : str or position, optional (default: identity)

Position adjustment. If it is a string, it must be registered and known to Plotnine.

na_rm : bool, optional (default: False)

If False, removes missing values with a warning. If True silently removes missing values.

inherit_aes : bool, optional (default: True)

If False, overrides the default aesthetics.

show_legend : bool or dict, optional (default: None)

Whether this layer should be included in the legends. None the default, includes any aesthetics that are mapped. If a bool, False never includes and True always includes. A dict can be used to exclude specific aesthetis of the layer from showing in the legend. e.g show_legend={'color': False}, any other aesthetic are included by default.

Examples

In [1]:
import pandas as pd
import numpy as np

from plotnine import *
from plotnine.data import *

%matplotlib inline
In [2]:
mpg.head()
Out[2]:
manufacturer model displ year cyl trans drv cty hwy fl class
0 audi a4 1.8 1999 4 auto(l5) f 18 29 p compact
1 audi a4 1.8 1999 4 manual(m5) f 21 29 p compact
2 audi a4 2.0 2008 4 manual(m6) f 20 31 p compact
3 audi a4 2.0 2008 4 auto(av) f 21 30 p compact
4 audi a4 2.8 1999 6 auto(l5) f 16 26 p compact

Basic scatter plot

In [3]:
p = ggplot(aes(x='displ', y='cty'), mpg)
p + geom_point()
../_images/geom_point_3_0.png
Out[3]:
<ggplot: (97654321012345679)>

Aesthetic mappings

In [4]:
p + geom_point(aes(color='factor(cyl)'))
../_images/geom_point_5_0.png
Out[4]:
<ggplot: (97654321012345679)>
In [5]:
p + geom_point(aes(shape='factor(cyl)'))
../_images/geom_point_6_0.png
Out[5]:
<ggplot: (97654321012345679)>
In [6]:
p + geom_point(aes(color='hwy'))
../_images/geom_point_7_0.png
Out[6]:
<ggplot: (97654321012345679)>

Modify the color scale

In [7]:
p + geom_point(aes(color='hwy')) + scale_color_gradient(low='blue', high='red')
../_images/geom_point_9_0.png
Out[7]:
<ggplot: (97654321012345679)>
In [8]:
p + geom_point(aes(size='hwy'))
../_images/geom_point_10_0.png
Out[8]:
<ggplot: (97654321012345679)>