matplotlib boxplot with split y-axis - python-3.x

Question

I would like to make a box plot with data similar to this
d = {'Education': [1,1,1,1,2,2,2,2,2,3,3,3,3,4,4,4,4],
'Hours absent': [3, 100,5,7,2,128,4,6,7,1,2,118,2,4,136,1,1]}
df = pd.DataFrame(data=d)
df.head()
This works beautifully:
df.boxplot(column=['Hours absent'] , by=['Education'])
plt.ylim(0, 140)
plt.show()
But the outliers are far away, therefore I would like to split the y-axis.
But here the boxplot commands "column" and "by" are not accepted anymore. So instead of splitting the data by education, I only get one merged data point.
This is my code:
dfnew = df[['Hours absent', 'Education']] # In reality I take the different
columns from a much bigger dataset
fig, (ax1, ax2) = plt.subplots(2, 1, sharex=True)
ax1.boxplot(dfnew['Hours absent'])
ax1.set_ylim(40, 140)
ax2.boxplot(dfnew['Hours absent'])
ax2.set_ylim(0, 40)
ax1.spines['bottom'].set_visible(False)
ax2.spines['top'].set_visible(False)
ax1.xaxis.tick_top()
ax1.tick_params(labeltop='off') # don't put tick labels at the top
ax2.xaxis.tick_bottom()
d = .015 # how big to make the diagonal lines in axes coordinates
# arguments to pass to plot, just so we don't keep repeating them
kwargs = dict(transform=ax1.transAxes, color='k', clip_on=False)
ax1.plot((-d, +d), (-d, +d), **kwargs) # top-left diagonal
ax1.plot((1 - d, 1 + d), (-d, +d), **kwargs) # top-right diagonal
kwargs.update(transform=ax2.transAxes) # switch to the bottom axes
ax2.plot((-d, +d), (1 - d, 1 + d), **kwargs) # bottom-left diagonal
ax2.plot((1 - d, 1 + d), (1 - d, 1 + d), **kwargs) # bottom-right diagonal
plt.show()
These are the things I tried (I always changed this both for the first and second subplot) and the errors I got.
ax1.boxplot(dfnew['Hours absent'],dfnew['Education'])
#The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(),
#a.any() or a.all().
ax1.boxplot(column=dfnew['Hours absent'], by=dfnew['Education'])#boxplot()
#got an unexpected keyword argument 'column'
ax1.boxplot(dfnew['Hours absent'], by=dfnew['Education']) #boxplot() got an
#unexpected keyword argument 'by'
I also tried to convert data into array for y axis and list for x axis:
data = df[['Hours absent']].as_matrix()
labels= list(df['Education'])
print(labels)
print(len(data))
print(len(labels))
print(type(data))
print(type(labels))
And I substituted in the plot command like this:
ax1.boxplot(x=data, labels=labels)
ax2.boxplot(x=data, labels=labels)
Now the error is ValueError: Dimensions of labels and X must be compatible.
But they are both 17 long, I don't understand what is going wrong here.

Answer 1

You are overcomplicating this, the code for breaking the Y-axis is independent of the code for plotting the boxplot. Nothing keeps you from using df.boxplot, it will add some labels and titles you do not want but that is easy to fix.
df.boxplot(column='Hours absent', by='Education', ax=ax1)
ax1.set_xlabel('')
ax1.set_ylim(ymin=90)
df.boxplot(column='Hours absent', by='Education', ax=ax2)
ax2.set_title('')
ax2.set_ylim(ymax=50)
fig.subplots_adjust(top=0.87)
Of course you can also use matplotlib's boxplot, as long as you provide the parameters it needs. According to the docstring it will make
a box and whisker plot for each column of x or each vector in
sequence x
Which means you have to do the "by" part yourself.
grouper = df.groupby('Education')['Hours absent']
x = [grouper.get_group(k) for k in grouper.groups]
ax1.boxplot(x)
ax1.set_ylim(ymin=90)
ax2.boxplot(x)
ax2.set_ylim(ymax=50)