Some important imports

In order to work with a panda data frame, we need to import the pandas library. Finally we need libraries that enable visualization in python such as plotly.

import pandas as pd
import plotly.express as px

We are working with Palmer penguins data set which we need to import by using its url.

url = "https://raw.githubusercontent.com/PhilChodrow/PIC16B/master/datasets/palmer_penguins.csv"
penguins = pd.read_csv(url)
penguins.head()

	studyName	Sample Number	Species	Region	Island	Stage	Individual ID	Clutch Completion	Date Egg	Culmen Length (mm)	Culmen Depth (mm)	Flipper Length (mm)	Body Mass (g)	Sex	Delta 15 N (o/oo)	Delta 13 C (o/oo)	Comments
0	PAL0708	1	Adelie Penguin (Pygoscelis adeliae)	Anvers	Torgersen	Adult, 1 Egg Stage	N1A1	Yes	11/11/07	39.1	18.7	181.0	3750.0	MALE	NaN	NaN	Not enough blood for isotopes.
1	PAL0708	2	Adelie Penguin (Pygoscelis adeliae)	Anvers	Torgersen	Adult, 1 Egg Stage	N1A2	Yes	11/11/07	39.5	17.4	186.0	3800.0	FEMALE	8.94956	-24.69454	NaN
2	PAL0708	3	Adelie Penguin (Pygoscelis adeliae)	Anvers	Torgersen	Adult, 1 Egg Stage	N2A1	Yes	11/16/07	40.3	18.0	195.0	3250.0	FEMALE	8.36821	-25.33302	NaN
3	PAL0708	4	Adelie Penguin (Pygoscelis adeliae)	Anvers	Torgersen	Adult, 1 Egg Stage	N2A2	Yes	11/16/07	NaN	NaN	NaN	NaN	NaN	NaN	NaN	Adult not sampled.
4	PAL0708	5	Adelie Penguin (Pygoscelis adeliae)	Anvers	Torgersen	Adult, 1 Egg Stage	N3A1	Yes	11/16/07	36.7	19.3	193.0	3450.0	FEMALE	8.76651	-25.32426	NaN

Data Visualization

We will use the express module form plotly library to create a visualization of culmen length vs culmen depth for each island as we figured out in our project for PIC16A that those features are the best candidates based on their linear coefficients. We need to pass data frame, x and y coordinates to the px.scatter function. x and y coordinates are the names of the columns in our data frame. As we want to predict species based on these features, we color each species with a distinct color by setting the color to “Species” column. We set width and height appropriately to get the most readable visualization. Facet_col creates subplots for each island and title sets the title of the figure.

fig = px.scatter(data_frame = penguins, 
                 x = "Culmen Length (mm)", 
                 y = "Culmen Depth (mm)",
                 color = "Species",
                 width = 1000,
                 height = 300,
                 opacity = 0.5, 
                 facet_col = "Island",
                 title = "Culmen length vs Culmen depth in each island"
)

# reduce whitespace
fig.update_layout(margin={"r":0,"t":50,"l":0,"b":0})
# show the plot

fig.show()