# Adding a matplotlib legend

## Question:

How can one create a legend for a line graph in `Matplotlib`

‘s `PyPlot`

without creating any extra variables?

Please consider the graphing script below:

```
if __name__ == '__main__':
PyPlot.plot(total_lengths, sort_times_bubble, 'b-',
total_lengths, sort_times_ins, 'r-',
total_lengths, sort_times_merge_r, 'g+',
total_lengths, sort_times_merge_i, 'p-', )
PyPlot.title("Combined Statistics")
PyPlot.xlabel("Length of list (number)")
PyPlot.ylabel("Time taken (seconds)")
PyPlot.show()
```

As you can see, this is a very basic use of `matplotlib`

‘s `PyPlot`

. This ideally generates a graph like the one below:

Nothing special, I know. However, it is unclear what data is being plotted where (I’m trying to plot the data of some sorting algorithms, length against time taken, and I’d like to make sure people know which line is which). Thus, I need a legend, however, taking a look at the following example below(from the official site):

```
ax = subplot(1,1,1)
p1, = ax.plot([1,2,3], label="line 1")
p2, = ax.plot([3,2,1], label="line 2")
p3, = ax.plot([2,3,1], label="line 3")
handles, labels = ax.get_legend_handles_labels()
# reverse the order
ax.legend(handles[::-1], labels[::-1])
# or sort them by labels
import operator
hl = sorted(zip(handles, labels),
key=operator.itemgetter(1))
handles2, labels2 = zip(*hl)
ax.legend(handles2, labels2)
```

You will see that I need to create an extra variable `ax`

. How can I add a legend to my graph *without* having to create this extra variable and retaining the simplicity of my current script?

## Answers:

Add labels to each argument in your plot call corresponding to the series it is graphing, i.e. `label = "series 1"`

Then simply add `Pyplot.legend()`

to the bottom of your script and the legend will display these labels.

Add a `label=`

to each of your `plot()`

calls, and then call `legend(loc='upper left')`

.

Consider this sample (tested with Python 3.8.0):

```
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0, 20, 1000)
y1 = np.sin(x)
y2 = np.cos(x)
plt.plot(x, y1, "-b", label="sine")
plt.plot(x, y2, "-r", label="cosine")
plt.legend(loc="upper left")
plt.ylim(-1.5, 2.0)
plt.show()
```

Slightly modified from this tutorial: http://jakevdp.github.io/mpl_tutorial/tutorial_pages/tut1.html

Here’s an example to help you out …

```
fig = plt.figure(figsize=(10,5))
ax = fig.add_subplot(111)
ax.set_title('ADR vs Rating (CS:GO)')
ax.scatter(x=data[:,0],y=data[:,1],label='Data')
plt.plot(data[:,0], m*data[:,0] + b,color='red',label='Our Fitting
Line')
ax.set_xlabel('ADR')
ax.set_ylabel('Rating')
ax.legend(loc='best')
plt.show()
```

You can access the Axes instance (`ax`

) with `plt.gca()`

. In this case, you can use

```
plt.gca().legend()
```

You can do this either by using the `label=`

keyword in each of your `plt.plot()`

calls or by assigning your labels as a tuple or list within `legend`

, as in this working example:

```
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(-0.75,1,100)
y0 = np.exp(2 + 3*x - 7*x**3)
y1 = 7-4*np.sin(4*x)
plt.plot(x,y0,x,y1)
plt.gca().legend(('y0','y1'))
plt.show()
```

However, if you need to access the Axes instance more that once, I do recommend saving it to the variable `ax`

with

```
ax = plt.gca()
```

and then calling `ax`

instead of `plt.gca()`

.

A simple plot for sine and cosine curves with a legend.

Used `matplotlib.pyplot`

```
import math
import matplotlib.pyplot as plt
x=[]
for i in range(-314,314):
x.append(i/100)
ysin=[math.sin(i) for i in x]
ycos=[math.cos(i) for i in x]
plt.plot(x,ysin,label='sin(x)') #specify label for the corresponding curve
plt.plot(x,ycos,label='cos(x)')
plt.xticks([-3.14,-1.57,0,1.57,3.14],['-$pi$','-$pi$/2',0,'$pi$/2','$pi$'])
plt.legend()
plt.show()
```

You can add a custom legend documentation

```
first = [1, 2, 4, 5, 4]
second = [3, 4, 2, 2, 3]
plt.plot(first, 'g--', second, 'r--')
plt.legend(['First List', 'Second List'], loc='upper left')
plt.show()
```