How to Make Histogram with Plotly

Let’s build a histogram!

Import Data

import pandas as pd
from plotly import express as px

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

The Basic Information of Data

We should always check waht are the variables in our data, and the total number of observations

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

penguins.shape

(344, 17)

Data cleanning

penguins = pd.read_csv(url)
penguins = penguins.dropna(subset = ["Body Mass (g)", "Sex"])
penguins["Species"] = penguins["Species"].str.split().str.get(0)
penguins = penguins[penguins["Sex"] != "."]

cols = ["Species", "Island", "Sex", "Culmen Length (mm)", "Culmen Depth (mm)", "Flipper Length (mm)", "Body Mass (g)"]
penguins = penguins[cols]
penguins.head()

	Species	Island	Sex	Culmen Length (mm)	Culmen Depth (mm)	Flipper Length (mm)	Body Mass (g)
0	Adelie	Torgersen	MALE	39.1	18.7	181.0	3750.0
1	Adelie	Torgersen	FEMALE	39.5	17.4	186.0	3800.0
2	Adelie	Torgersen	FEMALE	40.3	18.0	195.0	3250.0
4	Adelie	Torgersen	FEMALE	36.7	19.3	193.0	3450.0
5	Adelie	Torgersen	MALE	39.3	20.6	190.0	3650.0

We have total 344 obseravtions, and 17 variables in this data set.

More About the Data

For example, I am interested in how many observations of different species of penguins, we could use groupby () to achieve it.

penguins.groupby("Species").count()

	Island	Sex	Culmen Length (mm)	Culmen Depth (mm)	Flipper Length (mm)	Body Mass (g)
Species
Adelie	146	146	146	146	146	146
Chinstrap	68	68	68	68	68	68
Gentoo	119	119	119	119	119	119

Make a histgram plot by use plotly

A histogram is the most commonly used graph to show frequency distributions. To plot a simple histogram, we need a data frame, and a variable you want to observe.

fig = px.histogram(data_frame = penguins, 
                   x = "Culmen Length (mm)", 
                   )

# show the plot
fig.show()

The plot looks too simple, let’s add more components:

the **color** argument takes a name of a column in data_frame and uses it to assign a color to the plot. Here, we want to assign different colors with respect to different species of penguins. Using this argument will also create a legend.
the color of bars looks too bright, then we could use **opacity** argument which takes value from 0 to 1 to adjust the transparency

fig = px.histogram(data_frame = penguins, 
                   x = "Culmen Length (mm)", 
                   color = "Species",
                   opacity = 0.5
                   )

# show the plot
fig.show()

Now, our plot looks a little better than the first version, but it may look too wide compared to its height. So by using width and height arguments, we could adjust the ratio of the plot. Also, using nbins can set the bins we want to show in the plot

fig = px.histogram(data_frame = penguins, 
                   x = "Culmen Length (mm)", 
                   color = "Species",
                   opacity = 0.5,
                   nbins = 30, 
                   width = 900,
                   height = 450,
                   barmode='stack'
                   )

# show the plot
fig.show()

Finally, add a title to the plot

fig = px.histogram(data_frame = penguins, 
                   x = "Culmen Length (mm)", 
                   color = "Species",
                   opacity = 0.5,
                   nbins = 30, 
                   width = 900,
                   height = 450,
                   barmode='stack'
                   )

# set title and its alignment
fig.update_layout(title_text="Histogram of Penguins' Culmen Length", title_x=0.5, title_y=0.92)
# show the plot
fig.show()

Written on April 4, 2022