CODEWITHSUNDEEP
pythonmatplotliblegend
DJV
DJV

Reputation: 873

Matplotlib Legends in For Loop

I'm binning data and plotting it on a map with a legend for each bin, but I get a line in my legend for each time I go through the loop. How can I just get one line in my legend for each binned category?

NOTE: I have separate for loops to ensure that the smaller circles plot on top of the bigger circles.

enter image description here

sigcorrs = np.random.rand(100,1)

m = Basemap(llcrnrlon=35.,llcrnrlat=30.,urcrnrlon=-160.,urcrnrlat=63.,projection='lcc',resolution='c',lat_1=20.,lat_2=40.,lon_0=90.,lat_0=50.)  
m.drawcountries()
m.drawmapboundary(fill_color='lightblue')
m.drawparallels(np.arange(0.,90.,5.),color='gray',dashes=[1,3],labels=[1,0,0,0])
m.drawmeridians(np.arange(0.,360.,15.),color='gray',dashes=[1,3],labels=[0,0,0,1])
m.fillcontinents(color='beige',lake_color='lightblue',zorder=0)
plt.title('Mean Absolute Error')

for a in range(len(clat)):
    if sigcorrs[a] > 0.8:
        X,Y = m(clon[a],clat[a])  
        m.scatter(X,Y,s=300,label='Corr > 0.8')
    else:
        continue

for a in range(len(clat)):
    if sigcorrs[a] > 0.6 and sigcorrs[a] <= 0.8:
        X,Y = m(clon[a],clat[a])  
        m.scatter(X,Y,s=200,label='Corr > 0.6')
    else:
        continue

for a in range(len(clat)):
    if sigcorrs[a] > 0.4 and sigcorrs[a] <= 0.6:
        X,Y = m(clon[a],clat[a])  
        m.scatter(X,Y,s=100,label='Corr > 0.4')
    else:
        continue

for a in range(len(clat)):
    if sigcorrs[a] <= 0.4:
        X,Y = m(clon[a],clat[a])  
        m.scatter(X,Y,s=50,label='Corr < 0.4')
    else:
        continue

plt.legend()
plt.show()

Upvotes: 5

Views: 8188

Answers (2)

hamflow
hamflow

Reputation: 311

Another method is to plot data without labels inside for loop and plot one instance of the last indexed data with labels again outside for loop. For example:

The wrong way:

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.colors

example_y1 = np.random.rand(100,1) * 1.2
example_y2 = np.random.rand(100,1)

x = range(len(example_y1))

for i in range(len(example1)):
    if example_y1[i] > example_y2[i]:
        plt.scatter(x[i],example_y1[i,0], c = 'blue', label='example1')
        plt.scatter(x[i],example_y1[i,0], c = 'green', label='example2')

plt.ylabel('Y')
plt.xlabel('X')
plt.legend(loc='upper left')
plt.show()

enter image description here

The right way:

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.colors

example_y1 = np.random.rand(100,1) * 1.2
example_y2 = np.random.rand(100,1)

x = range(len(example_y1))

for i in range(len(example1)):
    if example_y1[i] > example_y2[i]:
        plt.scatter(x[i],example_y1[i,0], c = 'blue')
        plt.scatter(x[i],example_y1[i,0], c = 'green')
        n = i # last index

plt.scatter(x[n],example_y1[n,0], c = 'blue', label='example1')
plt.scatter(x[n],example_y1[n,0], c = 'green', label='example2')
plt.ylabel('Y')
plt.xlabel('X')
plt.legend(loc='upper left')
plt.show()

enter image description here

Upvotes: 0

thomas
thomas

Reputation: 1813

You can avoid this by setting only one label per category. For example in the first loop:

label_added =False
for a in range(len(clat)):
    if sigcorrs[a] > 0.8:
        X,Y = m(clon[a],clat[a])  
        if not label_added:
            m.scatter(X,Y,s=300,label='Corr > 0.8')
            label_added = True
        else:
            m.scatter(X,Y,s=300)
    else:
        continue

Upvotes: 7

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