I am using matplotlib to plot some step functions from a dataframe
df['s1'].plot(c='b', drawstyle="steps-post")
df['s2'].plot(c='b', drawstyle="steps-post")
...
The result looks like
I would like to have this only plot the horizontal lines, not the vertical lines connecting the jump points. I could not find a straightforward parameter for plot that would seem to do that. Is there a way to do this?
There is no built-in option to produce a step function without vertical lines as far as I can tell. But you may easily build one yourself. The following uses the fact that np.nan is not plotted and cuts the line. So adding np.nan in between the steps suppresses the vertical line.
import matplotlib.pyplot as plt
import numpy as np
def mystep(x,y, ax=None, where='post', **kwargs):
assert where in ['post', 'pre']
x = np.array(x)
y = np.array(y)
if where=='post': y_slice = y[:-1]
if where=='pre': y_slice = y[1:]
X = np.c_[x[:-1],x[1:],x[1:]]
Y = np.c_[y_slice, y_slice, np.zeros_like(x[:-1])*np.nan]
if not ax: ax=plt.gca()
return ax.plot(X.flatten(), Y.flatten(), **kwargs)
x = [1,3,4,5,8,10,11]
y = [5,4,2,7,6,4,4]
mystep(x,y, color="crimson")
plt.show()
drawstyle='steps-post' keyword argument in plt.plot() for drawing step graphs i.e. the y-value of the flat line at any given x-value is equal to the y-value at the next smallest x-value from the passed x array. For example using the arrays in @ImportanceOfBeingErnest's answer, the y-value at x=1.5 equals the y-value at x=1 (i.e. y=5).
drawstyle='steps-post' is adding vertical lines between the horizontal ones. I had to change one line in the mysteps-function so X could be also a object with datetime: Y = np.c_[y_slice, y_slice, np.zeros(x[:-1].shape)*np.nan]Seems like hlines is the "correct" (built-in) way to do this:
import matplotlib.pyplot as plt
x = [1,3,4,5,8,10,11]
y = [5,4,2,7,6,4]
plt.hlines(y,x[:-1],x[1:])
plt.show()
