create a scatter plot from a csv file with categories

Question

I only just stepped into Python and I'm trying to generate a scatter plot with several categories. I am using the Iris Dataset as a basis, here is what I have so far:

import matplotlib.pyplot as plt
import numpy as np

fig,ax = plt.subplots(1)

iris_data = np.genfromtxt(
    "iris.csv", names=True,
    dtype="float", delimiter=",")

x=iris_data["sepal_length"]
y=iris_data["sepal_width"]
g=iris_data["class"]
plt.scatter(x,y)

plt.show()

I don't know how to separate out the classes and plot each one on the same graph.

I am coming from Matlab where all I needed was the "gscatter(x,y,g) creates a scatter plot of x and y, grouped by g" to get the job done, but I am finding out that python needs a little more to get the group by g part done.

Thank you in advance for any help.

Can you be more specific about which part you're struggling with? Have you looked at the matplotlib documentation? — AMC
– AMC, Commented May 7, 2020 at 23:05

mechanical_meat · Accepted Answer · 2020-05-07 23:09:06Z

1

Use seaborn:

import seaborn as sns, matplotlib.pyplot as plt

iris = sns.load_dataset('iris')
sns.scatterplot(x='sepal_length',y='sepal_width',data=iris,hue='species')

plt.show()

Result:

You can do the same in matplotlib as in the example below as long as your data is organized in a pandas DataFrame:

for k,g in iris.groupby('species'):
    plt.scatter(g['sepal_length'],g['sepal_width'],label=k)

edited May 7, 2020 at 23:09

answered May 7, 2020 at 22:39

mechanical_meat

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