I plotted a series of subplots of a Dataframe's columns, and I cannot find a way to add data labels and a mean line to the plots.

my code now looks something like this (I'm simplifying the data here):

categorized = pd.DataFrame(data={"food":[50, 60, 23, 80], 
                                 "books":[10, 18, 3, 12], 
                                 "cloths":[30, 50, 23, 80]},
                           index=["jan", "feb", "mar", "apr"])
a = categorized.plot(kind='bar', subplots=True, legend=False, figsize=(25, 105), sharex=False, layout=(4, 1))
plt.subplots_adjust(hspace=0.55)

I found two ways to handle this but I can't use any of them:

1. to use matplotlib, which has the option of mean and data labels - but I didn't see an option for multiple subplots (one per column)
2. pandas' above example - with subplots - but I couldn't find how to add data labels and mean line

Is there another way that combines the benefits of both options? Thanks!

CodePudding user response：

I'm not sure what you're trying to do as far as subplots, data labels, and the mean line go, but here is a script that produces a result similar to the result of the pandas command. In particular, it produces a plot with the three bar graphs as subplots, stacked on top of each other. Unlike the pandas command, the bars here are a bit wider and the colors are the same.

categorized = pd.DataFrame(data={"food":[50, 60, 23, 80], 
                                 "books":[10, 18, 3, 12], 
                                 "cloths":[30, 50, 23, 80]},
                           index=["jan", "feb", "mar", "apr"])
fig,axs = plt.subplots(3,sharex = False, figsize=(10, 42))

for k,c in enumerate(categorized.columns):
    axs[k].bar(categorized.index,categorized.loc[:,c])
    axs[k].set_title(c)

Result:

Pandas result for comparison: