We’ll be using palmerpenguins for the dataset, and plotnine to visualize the palmer penguin’s bill_length_mm column as a histogram.
from palmerpenguins import load_penguins
penguins = load_penguins()
penguins.head()| species | island | bill_length_mm | bill_depth_mm | flipper_length_mm | body_mass_g | sex | year | |
|---|---|---|---|---|---|---|---|---|
| 0 | Adelie | Torgersen | 39.1 | 18.7 | 181.0 | 3750.0 | male | 2007 |
| 1 | Adelie | Torgersen | 39.5 | 17.4 | 186.0 | 3800.0 | female | 2007 |
| 2 | Adelie | Torgersen | 40.3 | 18.0 | 195.0 | 3250.0 | female | 2007 |
| 3 | Adelie | Torgersen | NaN | NaN | NaN | NaN | NaN | 2007 |
| 4 | Adelie | Torgersen | 36.7 | 19.3 | 193.0 | 3450.0 | female | 2007 |
We’ll be creating a base histogram using plotnine as follows:
from plotnine import aes, geom_histogram, ggplot, theme_minimal
g = ggplot(penguins, aes(x="bill_length_mm")) + geom_histogram()
g
Now we want to highlight part of the histogram. We do this by adding another data and aesthetic layer to our plotnine figure.
species = "Adelie" # selected species
selected = penguins.loc[penguins.species == species] # selected data
selected| species | island | bill_length_mm | bill_depth_mm | flipper_length_mm | body_mass_g | sex | year | |
|---|---|---|---|---|---|---|---|---|
| 0 | Adelie | Torgersen | 39.1 | 18.7 | 181.0 | 3750.0 | male | 2007 |
| 1 | Adelie | Torgersen | 39.5 | 17.4 | 186.0 | 3800.0 | female | 2007 |
| 2 | Adelie | Torgersen | 40.3 | 18.0 | 195.0 | 3250.0 | female | 2007 |
| 3 | Adelie | Torgersen | NaN | NaN | NaN | NaN | NaN | 2007 |
| 4 | Adelie | Torgersen | 36.7 | 19.3 | 193.0 | 3450.0 | female | 2007 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 147 | Adelie | Dream | 36.6 | 18.4 | 184.0 | 3475.0 | female | 2009 |
| 148 | Adelie | Dream | 36.0 | 17.8 | 195.0 | 3450.0 | female | 2009 |
| 149 | Adelie | Dream | 37.8 | 18.1 | 193.0 | 3750.0 | male | 2009 |
| 150 | Adelie | Dream | 36.0 | 17.1 | 187.0 | 3700.0 | female | 2009 |
| 151 | Adelie | Dream | 41.5 | 18.5 | 201.0 | 4000.0 | male | 2009 |
152 rows × 8 columns
Now that we have the new data, we can add the new selected dataframe to our original figure, g
g + geom_histogram(data=selected, fill="#447099")
The 2 different bill_length_mm are plotted as independent histograms, so the auto binning is causing the bars to not line up. Let’s re-create our plot and also set a uniform bin width by setting binwidth=1.
(
ggplot(aes(x="bill_length_mm"))
+ geom_histogram(penguins, fill="#C2C2C4", binwidth=1)
+ geom_histogram(selected, fill="#447099", binwidth=1)
)