Scatter plots in Pandas/Pyplot: How to plot by category

Question

I am trying to make a simple scatter plot in pyplot using a Pandas DataFrame object, but want an efficient way of plotting two variables but have the symbols dictated by a t

Answer 1

From matplotlib 3.1 onwards you can use .legend_elements(). An example is shown in Automated legend creation. The advantage is that a single scatter call can be used.

In this case:

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

df = pd.DataFrame(np.random.normal(10,1,30).reshape(10,3), 
                  index = pd.date_range('2010-01-01', freq = 'M', periods = 10), 
                  columns = ('one', 'two', 'three'))
df['key1'] = (4,4,4,6,6,6,8,8,8,8)


fig, ax = plt.subplots()
sc = ax.scatter(df['one'], df['two'], marker = 'o', c = df['key1'], alpha = 0.8)
ax.legend(*sc.legend_elements())
plt.show()

In case the keys were not directly given as numbers, it would look as

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

df = pd.DataFrame(np.random.normal(10,1,30).reshape(10,3), 
                  index = pd.date_range('2010-01-01', freq = 'M', periods = 10), 
                  columns = ('one', 'two', 'three'))
df['key1'] = list("AAABBBCCCC")

labels, index = np.unique(df["key1"], return_inverse=True)

fig, ax = plt.subplots()
sc = ax.scatter(df['one'], df['two'], marker = 'o', c = index, alpha = 0.8)
ax.legend(sc.legend_elements()[0], labels)
plt.show()