Add x and y labels to a pandas plot

Suppose I have the following code that plots something very simple using pandas:

    import pandas as pd
    values = [[1, 2], [2, 5]]
    df2 = pd.DataFrame(values, columns=['Type A', 'Type B'], 
                       index=['Index 1', 'Index 2'])
    df2.plot(lw=2, colormap='jet', marker='.', markersize=10, 
             title='Video streaming dropout by category')

Output

How do I easily set x and y-labels while preserving my ability to use specific colormaps? I noticed that the plot() wrapper for pandas DataFrames doesn't take any parameters specific for that.

The df.plot() function returns a matplotlib.axes.AxesSubplot object. You can set the labels on that object.

    In [4]: ax = df2.plot(lw=2, colormap='jet', marker='.', markersize=10, title='Video streaming dropout by category')

    In [6]: ax.set_xlabel("x label")
    Out[6]: <matplotlib.text.Text at 0x10e0af2d0>

    In [7]: ax.set_ylabel("y label")
    Out[7]: <matplotlib.text.Text at 0x10e0ba1d0>

enter image description here

Or, more succinctly: ax.set(xlabel="x label", ylabel="y label").

Alternatively, the index x-axis label is automatically set to the Index name, if it has one. so df2.index.name = 'x label' would work too.

From: stackoverflow.com/q/21487329