How to infer legend using df.plot()-CodePudding

How to infer and display legend?

import matplotlib.pyplot as plt
import pandas as pd

df = pd.read_csv('iris.csv')
for i, s in enumerate(species := df['species'].drop_duplicates().values):
    df.loc[df['species'] == s, 'c'] = i
df.plot(kind='scatter', x='sepal_length', y='sepal_width', c='c', cmap='viridis')
plt.show()

Which results in:

I tried calling plt.legend(species) expecting the 3 species names to show, but only 1 of the 3 is displayed, why? and is there a way to infer it somehow in the same fashion as c='c'?

CodePudding user response：

df.plot(kind='scatter', x='sepal_length', y='sepal_width', c='c', cmap='viridis', legend = True)

Does adding legend=True work?

CodePudding user response：

you can use seaborn library and make your life easy:

import seaborn as sns
sns.FacetGrid(iris, hue ="class",
          height = 6).map(plt.scatter,
                          'sepallength',
                          'sepalwidth').add_legend()

but if you insist on doing it in your way, I think the easiest way is to separate each category in a for loop as follows:

iris_df=pd.read_csv('iris.csv')
for i in range(0, 3):    
    species_df = iris_df[iris_df['class'] == i]    
    plt.scatter(        
    species_df['sepal_length'],        
    species_df[''],
    color=colours[i],        
    alpha=0.5,        
    label=species[i]   
)

plt.xlabel('sepal length (cm)')
plt.ylabel('sepal width(cm)')
plt.title('Iris dataset: petal length vs sepal length')
plt.legend(loc='lower right')

plt.show()