Colour fill on plot based on conditions with python

Question

I have plotted a graph with dataset df, where Timestamp is the index:

df:

      Timestamp     Temperature     
2020-02-06 08:23:04 18.5    
2020-02-06 08:23:05 18.5    
2020-02-06 08:23:06 18.5    
2020-02-06 08:23:07 18.5    
2020-02-06 08:23:08 18.5    
... ... ...
2020-02-06 20:14:36 21.0    

and code

df.plot( y='Temperature', figsize=(16, 10),) 
plt.axhline(y=40, color='r', linestyle='-')
plt.axhline(y=25, color='b', linestyle='-')
plt.show()

The graph looks like this:

I would like to fill in colour for area where temperature is between 25°C and 40°C(inside the triangle). Can I do this by tweaking my code? If not, what's a good way of doing this? Thanks!

Note: The data is not continuous, but has been forward filled to have constant interval of 1 second. Also, temperature at the peak is above 40°C and the corresponding vertical section in Timestamp should not be coloured.

Answer 1

I can suggest this approach using fill_between using the where argument:

Timestamp = pd.date_range('2020-02-06 08:23:04', periods=1000, freq='s')
df = pd.DataFrame({'Timestamp': Timestamp,
                   'Temperature': 30+15*np.cos(np.linspace(0,10,Timestamp.size))})

df['top_lim'] = 40.
df['bottom_lim'] = 25.

plt.plot_date(df['Timestamp'], df['Temperature'], '-')
plt.plot_date(df['Timestamp'], df['top_lim'], '-', color='r')
plt.plot_date(df['Timestamp'], df['bottom_lim'], '-', color='blue')

plt.fill_between(df['Timestamp'], df['bottom_lim'], df['Temperature'],
                where=(df['Temperature'] >= df['bottom_lim'])&(df['Temperature'] <= df['top_lim']),
                facecolor='orange', alpha=0.3)

########### EDIT ################

# plt.fill_between(df['Timestamp'], df['bottom_lim'], df['top_lim'],
#                 where=(df['Temperature'] >= df['top_lim']),
#                 facecolor='orange', alpha=0.3)


mask = (df['Temperature'] <= df['top_lim'])&(df['Temperature'] >= df['bottom_lim'])
plt.scatter(df['Timestamp'][mask], df['Temperature'][mask], marker='.', color='black')
cumulated_time = df['Timestamp'][mask].diff().sum()
plt.title(f'Cumulated time in range = {cumulated_time}')
plt.show()