ヒストグラム(python plotnine)
from plotnine import *
from palmerpenguins import load_penguins
import math
penguins = load_penguins()
penguins
species island bill_length_mm ... body_mass_g sex year
0 Adelie Torgersen 39.1 ... 3750.0 male 2007
1 Adelie Torgersen 39.5 ... 3800.0 female 2007
2 Adelie Torgersen 40.3 ... 3250.0 female 2007
3 Adelie Torgersen NaN ... NaN NaN 2007
4 Adelie Torgersen 36.7 ... 3450.0 female 2007
.. ... ... ... ... ... ... ...
339 Chinstrap Dream 55.8 ... 4000.0 male 2009
340 Chinstrap Dream 43.5 ... 3400.0 female 2009
341 Chinstrap Dream 49.6 ... 3775.0 male 2009
342 Chinstrap Dream 50.8 ... 4100.0 male 2009
343 Chinstrap Dream 50.2 ... 3775.0 female 2009
[344 rows x 8 columns]
penguins_adelie=penguins.dropna(subset="bill_length_mm").loc[penguins["species"]=="Adelie"]
penguins_adelie
species island bill_length_mm ... body_mass_g sex year
0 Adelie Torgersen 39.1 ... 3750.0 male 2007
1 Adelie Torgersen 39.5 ... 3800.0 female 2007
2 Adelie Torgersen 40.3 ... 3250.0 female 2007
4 Adelie Torgersen 36.7 ... 3450.0 female 2007
5 Adelie Torgersen 39.3 ... 3650.0 male 2007
.. ... ... ... ... ... ... ...
147 Adelie Dream 36.6 ... 3475.0 female 2009
148 Adelie Dream 36.0 ... 3450.0 female 2009
149 Adelie Dream 37.8 ... 3750.0 male 2009
150 Adelie Dream 36.0 ... 3700.0 female 2009
151 Adelie Dream 41.5 ... 4000.0 male 2009
[151 rows x 8 columns]
g=(
ggplot(penguins_adelie,aes(x="bill_length_mm"))
+geom_histogram(binwidth=2.5)
)
g.save("histogram.png",width=100,height=100*2/(1+math.sqrt(5)),units="mm")
shiny for pythonにするときはこちら
https://github.com/Nobukuni-Hyakutake/statistics/blob/4c0aae8a08947b15ebcf071ef4036014a212248b/basic-app-plot2/app.py
ヒストグラム(R ggplot)
library(tidyverse)
library(palmerpenguins)
penguins_adelie<-penguins |>
filter(species=="Adelie",!is.na(bill_length_mm))
penguins_adelie
# A tibble: 151 × 8
species island bill_length_mm bill_depth_mm flipper_length_mm body_mass_g
<fct> <fct> <dbl> <dbl> <int> <int>
1 Adelie Torgersen 39.1 18.7 181 3750
2 Adelie Torgersen 39.5 17.4 186 3800
3 Adelie Torgersen 40.3 18 195 3250
4 Adelie Torgersen 36.7 19.3 193 3450
5 Adelie Torgersen 39.3 20.6 190 3650
6 Adelie Torgersen 38.9 17.8 181 3625
7 Adelie Torgersen 39.2 19.6 195 4675
8 Adelie Torgersen 34.1 18.1 193 3475
9 Adelie Torgersen 42 20.2 190 4250
10 Adelie Torgersen 37.8 17.1 186 3300
# ℹ 141 more rows
# ℹ 2 more variables: sex <fct>, year <int>
ggplot(penguins_adelie,aes(bill_length_mm))+
geom_histogram(binwidth = 2.5)
Python version
import platform
"Python version "+platform.python_version()
