Xticks By Pandas Plot, Rename With The String

I have this df: df = pd.DataFrame({'A': [1, 2, 3], 'B': [2, 3, 5], 'C': ['name 1', 'name 2', 'name 3']}) A B C 0 1 2 name 1 1 2 3 name 2 2 3 5 name 3 What is i

Solution 1:

The link you provided is a good resource, but shows the whole thing being done in matplotlib.pyplot and uses .subplots() to get to the axes. While I've done this before, I keep searching for ways to just use the built-into-pandas .plot() function as much as possible. To me it can simplify the code and makes it easier to leverage DataFrame goodness.

There do seem to be a number of things that aren't easy to do fully inside the parameters of df.plot() by itself, though. Luckily it returns an matplotlib.AxesSubplot, which opens up a much larger range of possibilities.

I copied your data above into a DataFrame:

df = pd.read_clipboard(quotechar="'")

It looks sort-of like:

   A B  C
0  1 2 'name 1'
1  2 3 'name 2'
2  3 5 'name 3'

But, of course, much better in non table-crippled html. (Maybe SO will fix this one day).

Then all I had to do was:

ax = df.A.plot(xticks=df.index, rot=90)
ax.set_xticklabels(df.C)

If you are using IPython/Jupyter and %matplotlib inline then both of those need to be in the same cell. I had forgotten that at first and spent quite a bit of time trying to figure what was going wrong.

You can do it all using the ax variable:

 ax = df.A.plot()
 ax.set_xticks(df.index)
 ax.set_xticklabels(df.C, rotation=90)

but, as I mentioned, I haven't found a way to the xticklabels inside the df.plot() function parameters, which would make it possible to do this all in a single line.

The extra step to rotate the xtick labels may be extraneous in this example, but came in handy in the one I was working on when looking for this answer.

And, of course, you can plot both A and B columns together even easier:

 ax = df.plot()
 ax.set_xticks(df.index)
 ax.set_xticklabels(df.C, rotation=90)

Solution 2:

As of matplotlib 3.5.0

Use ax.set_xticks with the new labels param to set ticks and labels simultaneously:

ax = df.plot(y='A')
ax.set_xticks(ticks=df.index, labels=df.C)
#                             ^^^^^^

Or, since df.plot returns an Axes object, we can chain it:

df.plot(y='A').set_xticks(df.index, df.C)

Note that plt.xticks always had a labels param, so this change just unifies the Axes and pyplot APIs.