Download notebook (.ipynb)

stat_summary_bin()#

import pandas as pd

from lets_plot import *

LetsPlot.setup_html()

df = pd.read_csv("https://raw.githubusercontent.com/JetBrains/lets-plot-docs/master/data/iris.csv")
print(df.shape)
df.head()

(150, 5)
sepal_length sepal_width petal_length petal_width species
0 5.1 3.5 1.4 0.2 setosa
1 4.9 3.0 1.4 0.2 setosa
2 4.7 3.2 1.3 0.2 setosa
3 4.6 3.1 1.5 0.2 setosa
4 5.0 3.6 1.4 0.2 setosa

1. The geom Parameter#

ggplot(df, aes("petal_length", "sepal_length")) + \
    stat_summary_bin(geom='crossbar', width=1, binwidth=.5) + \
    geom_point(shape=21)

2. fun, fun_min, fun_max Parameters#

ggplot(df, aes("petal_length", "sepal_length")) + \
    stat_summary_bin(geom='crossbar', width=1, binwidth=.5, \
                     fun='mq', fun_min='lq', fun_max='uq') + \
    geom_point(shape=21)

3. The quantiles Parameter#

ggplot(df, aes("petal_length", "sepal_length")) + \
    stat_summary_bin(geom='crossbar', width=1, binwidth=.5, \
                     fun='mq', fun_min='lq', fun_max='uq', \
                     quantiles=[.05, .5, .95]) + \
    geom_point(shape=21)

4. center and boundary Parameters#

def get_plot(center=None, boundary=None):
    return ggplot(df, aes("petal_length", "sepal_length")) + \
        stat_summary_bin(geom='crossbar', width=1, binwidth=.5, \
                         center=center, boundary=boundary) + \
        geom_point(shape=21) + \
        ggtitle("center={0}, boundary={1}".format(center, boundary))

gggrid([
    get_plot(),
    get_plot(center=1),
    get_plot(boundary=1),
], ncol=2)