Matplotlib Scatterplot with Legend

Matplotlib scatter plot legend

2D scatter plot

Using the scatter method of the matplotlib.pyplot module should work (at least with matplotlib 1.2.1 with Python 2.7.5), as in the example code below. Also, if you are using scatter plots, use scatterpoints=1 rather than numpoints=1 in the legend call to have only one point for each legend entry.

In the code below I've used random values rather than plotting the same range over and over, making all the plots visible (i.e. not overlapping each other).

import matplotlib.pyplot as plt
from numpy.random import random

colors = ['b', 'c', 'y', 'm', 'r']

lo = plt.scatter(random(10), random(10), marker='x', color=colors[0])
ll = plt.scatter(random(10), random(10), marker='o', color=colors[0])
l  = plt.scatter(random(10), random(10), marker='o', color=colors[1])
a  = plt.scatter(random(10), random(10), marker='o', color=colors[2])
h  = plt.scatter(random(10), random(10), marker='o', color=colors[3])
hh = plt.scatter(random(10), random(10), marker='o', color=colors[4])
ho = plt.scatter(random(10), random(10), marker='x', color=colors[4])

plt.legend((lo, ll, l, a, h, hh, ho),
           ('Low Outlier', 'LoLo', 'Lo', 'Average', 'Hi', 'HiHi', 'High Outlier'),
           scatterpoints=1,
           loc='lower left',
           ncol=3,
           fontsize=8)

plt.show()

3D scatter plot

To plot a scatter in 3D, use the plot method, as the legend does not support Patch3DCollection as is returned by the scatter method of an Axes3D instance. To specify the markerstyle you can include this as a positional argument in the method call, as seen in the example below. Optionally one can include argument to both the linestyle and marker parameters.

import matplotlib.pyplot as plt
from numpy.random import random
from mpl_toolkits.mplot3d import Axes3D

colors=['b', 'c', 'y', 'm', 'r']

ax = plt.subplot(111, projection='3d')

ax.plot(random(10), random(10), random(10), 'x', color=colors[0], label='Low Outlier')
ax.plot(random(10), random(10), random(10), 'o', color=colors[0], label='LoLo')
ax.plot(random(10), random(10), random(10), 'o', color=colors[1], label='Lo')
ax.plot(random(10), random(10), random(10), 'o', color=colors[2], label='Average')
ax.plot(random(10), random(10), random(10), 'o', color=colors[3], label='Hi')
ax.plot(random(10), random(10), random(10), 'o', color=colors[4], label='HiHi')
ax.plot(random(10), random(10), random(10), 'x', color=colors[4], label='High Outlier')

plt.legend(loc='upper left', numpoints=1, ncol=3, fontsize=8, bbox_to_anchor=(0, 0))

plt.show()

How do I add a legend to a scatter plot on matplotlib (the points are colour coded according to an array of 0s and 1s)?

To do what you need, you will need to assign the view - 0 or 1 to a color, so that the right color is mapped. This can be done using map. The handle for the legend will need to have the custom text added, so that the blue and red colors are assigned and show with the correct labels. I have used random numbers as data to plot the graph required, keeping as much of your code as is.

Code

import pandas as pd
import numpy as np
import random
import matplotlib.pyplot as plt
from matplotlib.lines import Line2D

size = []
price = []
view = []

for i in range(0,100):
    size.append(round(random.random(),3))
    price.append(round(random.random(),3))
    view.append(int(random.random()*10 % 2))
df = pd.DataFrame({'size':size, 'price':price, 'view':view})
colors = {0:'red', 1:'blue'}
plt.scatter(x=df['size'], y=df['price'], c=df['view'].map(colors))
plt.xlabel("Size", fontsize = 25, c = "green")
plt.ylabel("Price", fontsize = 25, c = "green")
markersize=8) for k, v in colors.items()]
custom = [Line2D([], [], marker='.', color='red', linestyle='None'),
          Line2D([], [], marker='.', color='blue', linestyle='None')]

plt.legend(handles = custom, labels=['No View', 'View'], bbox_to_anchor= (1.05, 0.5), loc= "lower left")
plt.show()

Output graph

Matplotlib scatterplot legend

as the full code is not available, I am just creating dummy data with 4 entries to demonstrate how to create scatter plot with the 3 colors you are talking about. This will create the legend based on what you enter in map.

import matplotlib.pyplot as plt 
data = {'x1': [1, 3, 6, 9], #Your X values
        'x2':[15, 11, 5, 8], #Your Y values 
        'y': [0,1,2,1]}  #The colors you want for each circle
X=pd.DataFrame(data)

map = {0: 'red', 1:'green', 2:"blue"}
fig, ax = plt.subplots()
for g in X.y.unique():  #For each group R/G/B
    ix = np.where(X.y == g)
    ax.scatter(X.x1[ix[0]], X.x2[ix[0]], c = map[g], label = map[g], s = 50) #Draw with said color
ax.legend()
plt.show()

Output graph

Matplotlib scatter plot legend display problem

You need to replace the plt.legend(scatteer..) line by this.... Documentation on legend_element is available here.

plt.legend(scatter.legend_elements(prop='colors', num=len(colorlist))[0], u, loc=2)

Output Plot

matplotlib: scatter plot with legend as string of class

You need to change the value of the legend's label in every iteration of the for loop, one possibility being the use of zip

for item, animal in zip(counter.items(), ['cat', 'dog']):
    row_ix = np.where(y == item[0])[0]
    plt.scatter(X[row_ix, 0], X[row_ix, 1], label=animal)
plt.legend()
plt.show()

Matplotlib scatter plot with legend

First, I have a feeling you meant to use apostrophes, not backticks when declaring colours.

For a legend you need some shapes as well as the classes. For example, the following creates a list of rectangles called recs for each colour in class_colours.

import matplotlib.patches as mpatches

classes = ['A','B','C']
class_colours = ['r','b','g']
recs = []
for i in range(0,len(class_colours)):
    recs.append(mpatches.Rectangle((0,0),1,1,fc=class_colours[i]))
plt.legend(recs,classes,loc=4)

There is a second way of creating a legend, in which you specify the "Label" for a set of points using a separate scatter command for each set. An example of this is given below.

classes = ['A','A','B','C','C','C']
colours = ['r','r','b','g','g','g']
for (i,cla) in enumerate(set(classes)):
    xc = [p for (j,p) in enumerate(x) if classes[j]==cla]
    yc = [p for (j,p) in enumerate(y) if classes[j]==cla]
    cols = [c for (j,c) in enumerate(colours) if classes[j]==cla]
    plt.scatter(xc,yc,c=cols,label=cla)
plt.legend(loc=4)

The first method is the one I've personally used, the second I just found looking at the matplotlib documentation. Since the legends were covering datapoints I moved them, and the locations for legends can be found here. If there's another way to make a legend, I wasn't able to find it after a few quick searches in the docs.

How to display legend for matplotlib scatterplot color

Try this:

import matplotlib.pyplot as plt

x = [1, 2, 3, 4, 5]
y = [1, 2, 3, 4, 5]
z = [3, 8.5, 2.1, 1.8, 9]

fig1, ax1 = plt.subplots()
scat = ax1.scatter(x, y, linewidths=1, alpha = .7, edgecolor= 'k', s=200, c=z)
ax1.legend(*scat.legend_elements(), title="Colors")

plt.show()

I tested this code in Python 3.10.4 with Matplotlib 3.5.2.

I figured out this solution from the matplotlib documentation page, which has some other examples like this: https://matplotlib.org/3.1.0/gallery/lines_bars_and_markers/scatter_with_legend.html

Matplotlib - Adding legend to scatter plot

Here is a solution. This code is based on the Matplotlib's tutorial on scatter plot with legends. Looping of the dataset grouped by gender allows to generate a color per gender (and corresponding legend). The size is then indicated from the output of the scatter function, using legend_elements for the sizes.

This is what I obtain with the dataset used in your example:

Here is the code:

import matplotlib.pyplot as plt
import seaborn as sns

# Read and group by gender
tips = sns.load_dataset("tips")
grouped = tips.groupby("sex")

# Show per group
fig, ax = plt.subplots(1)
for i, (name, group) in enumerate(grouped):
    sc = ax.scatter(
        group["total_bill"],
        group["tip"],
        s=group["size"] * 20,
        alpha=0.5,
        label=name,
    )

# Add legends (one for gender, other for size)
ax.add_artist(ax.legend(title='Gender'))
ax.legend(*sc.legend_elements("sizes", num=6), loc="lower left", title="Size")
ax.set_title("Scatter with legend")

plt.show()

plt.legend only adds first element to scatter plot

You can do that by replacing the plt.legend(classes) in your code by this line... I hope this is what you are looking for. I am using matplotlib 3.3.4.

plt.legend(handles=scatter.legend_elements()[0], labels=classes)

Output plot

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