Matplotlib, horizontal bar chart (barh) is upside-down

I believe the simplest solution for this problem is to reverse the pandas dataframe before plotting. For example:

df = df.iloc[::-1]
df.plot.barh(stacked=True);

In my opinion that is a bug in the pandas barh function. At least users should be able to pass an argument like reverse_order = True etc.

I believe the joint wrong order of groups and subgroups boils down to a single feature: that the y axis increases upwards, as in a usual plot. Try reversing the y axis of your axes as in this pandas-less example:

import numpy as np
import matplotlib.pyplot as plt

x=range(5)
y=np.random.randn(5)

#plot1: bar
plt.figure()
plt.bar(x,y)

#plot2: barh, wrong order
plt.figure()
plt.barh(x,y)

#plot3: barh with correct order: top-down y axis
plt.figure()
plt.barh(x,y)
plt.gca().invert_yaxis()

Specifically for pandas, pandas.DataFrame.plot and its various plotting submethods return a matplotlib axes object, so you can invert its y axis directly:

ax = df.plot.barh()  # or df.plot(), or similar
ax.invert_yaxis()

I will consider this to be a bug, i.e., the y position of the bars are not assigned correctly. The patch is however relatively simple:

This is only one right order of bars, and that is called..., the right order. Anything that is not the right order, is thus a buggy order. :p

In [63]:

print df
      Total_beef_cattle  Total_dairy_cattle  Total_sheep  Total_deer  \
1994           0.000000            0.000000     0.000000    0.000000   
2002         -11.025827           34.444950   -20.002034   33.858009   
2003          -8.344764           32.882482   -20.041908   37.229441   
2004         -11.895128           34.207998   -20.609926   42.707754   
2005         -12.366101           32.506699   -19.379727   38.499840   

      Total_pigs  Total_horses  
1994    0.000000      0.000000  
2002  -19.100637     11.811093  
2003  -10.766476     18.504488  
2004   -8.072078     13.376472  
2005  -19.230733   -100.000000  
In [64]:

ax = df.plot(kind='barh', sort_columns=True)

#Get the actual bars
bars = [item for item in ax.get_children() if isinstance(item, matplotlib.patches.Rectangle)]
bars = bars[:df.size]

#Reset the y positions for each bar
bars_y = [plt.getp(item, 'y') for item in bars]
for B, Y in zip(bars, np.flipud(np.array(bars_y).reshape(df.shape[::-1])).ravel()):
    B.set_y(Y)