Reputation: 248
I'm trying to use fill_between
with a pandas Series values but it's not working. The 'DAY'
field is string date format like '%Y-%m-%d'
.
df_tmp
like:
MEDIA_B2W MEDIA_CONC UPPER_BOUND LOWER_BOUND DAY
2017.48 2512.55 2811.0 1924.0 2017-01-01
1999.38 2512.55 2811.0 1924.0 2017-01-02
1930.89 2512.55 2811.0 1924.0 2017-01-03
df_tmp[['UPPER_BOUND','LOWER_BOUND','MEDIA_CONC','MEDIA_B2W','DAY']].plot(
x='DAY',ax=ax[0],grid=True,style=['r-','b-','y--','g-o'])
ax[0].fill_between(df_tmp.index,df_tmp['UPPER_BOUND'], df_tmp['LOWER_BOUND'],
facecolor='green', alpha=0.2, interpolate=True)
I would like to color between the upper and lower bound. This is the current plot
Just the lines appear in the plot.
Upvotes: 0
Views: 471
Reputation: 21264
This workaround uses df
indices for x ticks, and then swaps for the time series.
df = df[['UPPER_BOUND','LOWER_BOUND','MEDIA_CONC','MEDIA_B2W','DAY']]
ax = df.plot(x=df.index, grid=True, style=['r-','b-','y--','g-o'])
ax.fill_between(df.index, df.LOWER_BOUND, df.UPPER_BOUND,
facecolor='green', alpha=0.2, interpolate=True)
# replace index values with dates
ax.set_xticks(df.index)
ax.set_xticklabels(df.DAY)
# cosmetic adjustments
pad = 700
ax.set_ylim([df.LOWER_BOUND.min()-pad, df.UPPER_BOUND.max()+pad])
Alternately, you can set DAY
as df.index
:
df.DAY = pd.to_datetime(df.DAY)
df = df.set_index('DAY')
ax = df.plot(grid=True, style=['r-','b-','y--','g-o'])
ax.fill_between(df.index, df.LOWER_BOUND, df.UPPER_BOUND,
facecolor='green', alpha=0.2, interpolate=True)
# cosmetic adjustments
pad = 700
_=ax.set_ylim([df.LOWER_BOUND.min()-pad, df.UPPER_BOUND.max()+pad])
Upvotes: 1