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I have something like the following dataframe where each record is a point along a line. Fields include distance from the line's beginning and point elevation. 

>>> import pandas as pd >>> import matplotlib.pyplot as plt >>> >>> df=pd.DataFrame() >>> df['Distance']=[5,100,200,300,350,370,400] >>> df['Elevation']=[0,5,10,5,10,15,20] >>> df Distance Elevation 0 5 0 1 100 5 2 200 10 3 300 5 4 350 10 5 370 15 6 400 20 >>>

I want to create a plot that shows the elevation profile. Both distance and elevation are scaled in feet and I want it so increments of x and y have the same length (so the plot more realistically shows the elevation profile).

>>> plt.plot(df['Distance'],df['Elevation']) [<matplotlib.lines.Line2D object at 0x0A1C7EB0>] >>> plt.axis('equal') (0.0, 400.0, 0.0, 20.0) >>> plt.show() >>>

enter image description here

Now that scaling is correct (a foot is represented by the same distance in both the x and y axis) how can I set the y limits so that they better suit the data (from -5 to 25 for example)?

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If you use the OO approach, then you can use ax.set_ylim(-5,25):

import pandas as pd import matplotlib.pyplot as plt df=pd.DataFrame() df['Distance']=[5,100,200,300,350,370,400] df['Elevation']=[0,5,10,5,10,15,20] fig = plt.figure() ax = fig.add_subplot(111, aspect='equal') ax.plot(df['Distance'],df['Elevation']) ax.set_ylim(-5,25)

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thank you that's great. what does "the OO approach" stand for?
object-orientated. I.e. making a figure and axes, and then calling ax.plot, ax.set_ylim, fig.savefig etc. rather than plt.plot, plt.ylim, etc.

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