Pandas: Bar-Plot with two bars and two y-axis

Using the new pandas release (0.14.0 or later) the below code will work. To create the two axis I have manually created two matplotlib axes objects (ax and ax2) which will serve for both bar plots.

When plotting a Dataframe you can choose the axes object using ax=.... Also in order to prevent the two plots from overlapping I have modified where they align with the position keyword argument, this defaults to 0.5 but that would mean the two bar plots overlapping.

import matplotlib.pyplot as pltimport numpy as npimport pandas as pdfrom io import StringIOs = StringIO("""     amount     priceA     40929   4066443B     93904   9611272C    188349  19360005D    248438  24335536E    205622  18888604F    140173  12580900G     76243   6751731H     36859   3418329I     29304   2758928J     39768   3201269K     30350   2867059""")df = pd.read_csv(s, index_col=0, delimiter=' ', skipinitialspace=True)fig = plt.figure() # Create matplotlib figureax = fig.add_subplot(111) # Create matplotlib axesax2 = ax.twinx() # Create another axes that shares the same x-axis as ax.width = 0.4df.amount.plot(kind='bar', color='red', ax=ax, width=width, position=1)df.price.plot(kind='bar', color='blue', ax=ax2, width=width, position=0)ax.set_ylabel('Amount')ax2.set_ylabel('Price')plt.show()

You just need to write: df.plot( kind= 'bar', secondary_y= 'amount')

import matplotlib.pyplot as pltimport numpy as npimport pandas as pdfrom io import StringIOs = StringIO("""     amount     priceA     40929   4066443B     93904   9611272C    188349  19360005D    248438  24335536E    205622  18888604F    140173  12580900G     76243   6751731H     36859   3418329I     29304   2758928J     39768   3201269K     30350   2867059""")df = pd.read_csv(s, index_col=0, delimiter=' ', skipinitialspace=True)_ = df.plot( kind= 'bar' , secondary_y= 'amount' , rot= 0 )plt.show()

Here is an other method:

• create all the bars in left axes
• move some bars to the right axes by change it's transform attribute

Here is the code:

import pylab as pldf = pd.DataFrame(np.random.rand(10, 2), columns=["left", "right"])df["left"] *= 100ax = df.plot(kind="bar")ax2 = ax.twinx()for r in ax.patches[len(df):]:    r.set_transform(ax2.transData)ax2.set_ylim(0, 2);

here is the output: