python - Pandas Plots: Separate color for weekends, pretty printing times on x axis -

i created plot looks like

i have few issues:

1. how can show weekends. ways had thought grab indices corresponding weekends , draw transparent bars between xlims. rectangle drawn same. best if done plainly in pandas.
2. the date formatting not pretty

following code used generate plot

ax4=df4.plot(kind='bar',stacked=true,title='mains 1 breakdown'); ax4.set_ylabel('power (w)'); idx_weekend=df4.index[df4.index.dayofweek>=5] ax.bar(idx_weekend.to_datetime(),[1800 x in range(10)]) 

the ax.bar highlighting weekends, not produce visible output. (problem 1) problem 2 tried use major formatter , locators, code follows:

ax4=df4.plot(kind='bar',stacked=true,title='mains 1 breakdown'); ax4.set_ylabel('power (w)'); formatter=matplotlib.dates.dateformatter('%d-%b'); locator=matplotlib.dates.daylocator(interval=1); ax4.xaxis.set_major_formatter(formatter); ax4.xaxis.set_major_locator(locator); 

the output produced follows:

it may helpful know dataframe looks like

in [122]:df4  out[122]: <class 'pandas.core.frame.dataframe'> datetimeindex: 36 entries, 2011-04-19 00:00:00 2011-05-24 00:00:00 data columns: (0 6 am) dawn          19  non-null values (12 6 pm) dusk         19  non-null values (6 12 noon) morning    19  non-null values (6pm 12 noon) night    20  non-null values dtypes: float64(4) 

i tried lot , these hacks work. await more pythonic , consistent solutions. solution labeling problems:

def correct_labels(ax):     labels = [item.get_text() item in ax.get_xticklabels()]     days=[label.split(" ")[0] label in labels]     months=["jan","feb","mar","apr","may","jun","jul","aug","sep","oct","nov","dec"]     final_labels=[]     in range(len(days)):         a=days[i].split("-")         final_labels.append(a[2]+"\n"+months[int(a[1])-1])     ax.set_xticklabels(final_labels) 

also while plotting make following change

ax=df.plot(kind='bar',rot=0) 

this makes labels @ 0 rotation.

for finding weekends , highlighting them, wrote following 2 functions:

def find_weekend_indices(datetime_array):     indices=[]     in range(len(datetime_array)):         if datetime_array[i].weekday()>=5:             indices.append(i)     return indices  def highlight_weekend(weekend_indices,ax):     i=0     while i<len(weekend_indices):          ax.axvspan(weekend_indices[i], weekend_indices[i]+2, facecolor='green', edgecolor='none', alpha=.2)          i+=2 

now, plot looks more useful , covers these use cases.