There is a new API that makes this even simpler.

plt.gca().invert_xaxis()

and/or

plt.gca().invert_yaxis()

DisplacedAussie s answer is correct, but usually a shorter method is just to reverse the single axis in question:

plt.scatter(x_arr, y_arr)
ax = plt.gca()
ax.set_ylim(ax.get_ylim()[::-1])

where the gca() function returns the current Axes instance and the [::-1] reverses the list.

You could also use function exposed by the axes object of the scatter plot

scatter = plt.scatter(x, y)
ax = scatter.axes
ax.invert_xaxis()
ax.invert_yaxis()

Use matplotlib.pyplot.axis()

axis([xmin, xmax, ymin, ymax])

So you could add something like this at the end:

plt.axis([min(x_arr), max(x_arr), max(y_arr), 0])

Although you might want padding at each end so that the extreme points don t sit on the border.

If you re in ipython in pylab mode, then

plt.gca().invert_yaxis()
show()

the show() is required to make it update the current figure.

Another similar method to those described above is to use plt.ylim for example:

plt.ylim(max(y_array), min(y_array))

This method works for me when I m attempting to compound multiple datasets on Y1 and/or Y2

using ylim() might be the best approach for your purpose:

xValues = list(range(10))
quads = [x** 2 for x in xValues]
plt.ylim(max(quads), 0)
plt.plot(xValues, quads)

will result:

Alternatively, you can use the matplotlib.pyplot.axis() function, which allows you inverting any of the plot axis

ax = matplotlib.pyplot.axis()
matplotlib.pyplot.axis((ax[0],ax[1],ax[3],ax[2]))

Or if you prefer to only reverse the X-axis, then

matplotlib.pyplot.axis((ax[1],ax[0],ax[2],ax[3]))

Indeed, you can invert both axis:

matplotlib.pyplot.axis((ax[1],ax[0],ax[3],ax[2]))

If using matplotlib you can try: matplotlib.pyplot.xlim(l, r) matplotlib.pyplot.ylim(b, t)

These two lines set the limits of the x and y axes respectively. For the x axis, the first argument l sets the left most value, and the second argument r sets the right most value. For the y axis, the first argument b sets the bottom most value, and the second argument t sets the top most value.

if you are doing this in a subplot, here is the solution i found

fig, ax = plt.subplots(1,2, sharex = True)
for i in range(2):
    ax[i].plot(xdata, ydata)
axs = plt.gca()
axs.invert_xaxis()

While using sharex, last two lines needs to be outside the for loop