multiple plot in one figure in Python
This is very simple to do:
import matplotlib.pyplot as plt
plt.plot(<X AXIS VALUES HERE>, <Y AXIS VALUES HERE>, 'line type', label='label here')
plt.plot(<X AXIS VALUES HERE>, <Y AXIS VALUES HERE>, 'line type', label='label here')
plt.legend(loc='best')
plt.show()
You can keep adding plt.plot
as many times as you like. As for line type
, you need to first specify the color. So for blue, it's b
. And for a normal line it's -
. An example would be:
plt.plot(total_lengths, sort_times_heap, 'b-', label="Heap")
Since I don't have a high enough reputation to comment I'll answer liang question on Feb 20 at 10:01 as an answer to the original question.
In order for the for the line labels to show you need to add plt.legend to your code. to build on the previous example above that also includes title, ylabel and xlabel:
import matplotlib.pyplot as plt
plt.plot(<X AXIS VALUES HERE>, <Y AXIS VALUES HERE>, 'line type', label='label here')
plt.plot(<X AXIS VALUES HERE>, <Y AXIS VALUES HERE>, 'line type', label='label here')
plt.title('title')
plt.ylabel('ylabel')
plt.xlabel('xlabel')
plt.legend()
plt.show()
EDIT: I just realised after reading your question again, that i did not answer your question. You want to enter multiple lines in the same plot. However, I'll leave it be, because this served me very well multiple times. I hope you find usefull someday
I found this a while back when learning python
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
fig = plt.figure()
# create figure window
gs = gridspec.GridSpec(a, b)
# Creates grid 'gs' of a rows and b columns
ax = plt.subplot(gs[x, y])
# Adds subplot 'ax' in grid 'gs' at position [x,y]
ax.set_ylabel('Foo') #Add y-axis label 'Foo' to graph 'ax' (xlabel for x-axis)
fig.add_subplot(ax) #add 'ax' to figure
you can make different sizes in one figure as well, use slices in that case:
gs = gridspec.GridSpec(3, 3)
ax1 = plt.subplot(gs[0,:]) # row 0 (top) spans all(3) columns
consult the docs for more help and examples. This little bit i typed up for myself once, and is very much based/copied from the docs as well. Hope it helps... I remember it being a pain in the #$% to get acquainted with the slice notation for the different sized plots in one figure. After that i think it's very simple :)