A strip plot is very simple to understand. It is basically a scatter plot that differentiates different categories. So, all the data that corresponds to each category is shown as a scatter plot, and all the observations and collected data that are visualized are shown, side-by-side on a single graph.
Strip plots are considered a good alternative to a box plot or a violin plot.
seaborn.stripplot(
x=None,
y=None,
hue=None,
data=None,
color=None
)
x: Data for x-axis. There is no specified type for x; so, it is important to define it if someone is looking for data to be interpreted as long-form.
y: Data for y-axis. There is no specified type for y. It is important to define it if someone is looking for data to be interpreted as long-form.
hue: Another one of the inputs for plotting any type of long-form data. This parameter is used to determine the column that will be used for color encoding.
data: Dataset to be used for plotting. The format of data can include:
x, y, and hue variables to easily identify how data should be plotted from DataFrame.color: Refers to the individual colors of all elements for a gradient palette.
The function returns the corresponding plot.
Let’s draw a few scatter plots, with Iris dataset, that compare all three species types with their respective sepal_width, sepal_length , and petal_length.
# import librariesimport seaborn as snsimport matplotlib.pyplot as plt# load the iris datasetdf = sns.load_dataset('iris')# use sns for striplot# the column of sepcies is used as x.# the column of sepal_width is used as y.# the data is the iris dataframe.sns.stripplot(x=df["species"], y=df["sepal_width"], data=df)plt.show()
One can always add a title, xlabel, or ylabel using the matplotlib functions of
plt.xlabel,plt.ylabel, andplt.title.
import seaborn as snsimport matplotlib.pyplot as pltdf = sns.load_dataset('iris')sns.stripplot(x=df["species"], y=df["sepal_length"], data=df)plt.xlabel("species")plt.ylabel("sepal length")plt.show()
import seaborn as snsimport matplotlib.pyplot as pltdf = sns.load_dataset('iris')sns.stripplot(x=df["species"], y=df["petal_length"], data=df)plt.show()
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