How to color a graph from a specific date?

Question

Let's take this sample data and this graph :

import pandas as pd
import numpy as np
from datetime import date, timedelta
from matplotlib import pyplot as plt

# Creating sample data

DataX = []

sdate = date(2020, 6, 30) # start date
edate = date(2020, 7, 30) # end date

delta = edate - sdate # as timedelta

for i in range(delta.days + 1):
    day = sdate + timedelta(days=i)
    DataX.append(day)

N = list(range(len(DataX)))

DataY1 = np.exp(N)
DataY2 = np.sin(N)


# create figure and axis objects with subplots()
fig,ax = plt.subplots(figsize=(20,8))
# make a plot
ax.plot(DataX, DataY1, color="red", marker="o")
# set x-axis label
ax.set_xlabel("date",fontsize=14)
# set y-axis label
ax.set_ylabel("Y1",color="red",fontsize=14)
# twin object for two different y-axis on the sample plot
ax2=ax.twinx()
# make a plot with different y-axis using second axis object
ax2.plot(DataX, DataY2,color="blue",marker="o")
ax2.set_ylabel("Y2",color="blue",fontsize=14)
plt.axvline(x=date.today(),color='k', linestyle='--')
plt.title("title")
#plt.savefig("stck_color_predict")
plt.show()

I would like to color the part of the graph where values are predicted (right of the black line). I assume I have to use the fill_between function but I can't reach my goal. How please could I do ?

Expected output (manually done with PowerPoint) :

Answer 1

Try using matplotlib.pyplot.axvspan(xmin, xmax, ymin=0, ymax=1, hold=None, **kwargs) to add a vertical span (rectangle) across the axes, as follow:

import pandas as pd
import numpy as np
from datetime import date, timedelta
from matplotlib import pyplot as plt

# Creating sample data

DataX = []

sdate = date(2020, 6, 30)  # start date
edate = date(2020, 7, 30)  # end date

delta = edate - sdate  # as timedelta

for i in range(delta.days + 1):
    day = sdate + timedelta(days=i)
    DataX.append(day)

N = list(range(len(DataX)))

DataY1 = np.exp(N)
DataY2 = np.sin(N)


# create figure and axis objects with subplots()
fig, ax = plt.subplots(figsize=(20, 8))
# make a plot
ax.plot(DataX, DataY1, color="red", marker="o")
# set x-axis label
ax.set_xlabel("date", fontsize=14)
# set y-axis label
ax.set_ylabel("Y1", color="red", fontsize=14)
# twin object for two different y-axis on the sample plot
ax2 = ax.twinx()
# make a plot with different y-axis using second axis object
ax2.plot(DataX, DataY2, color="blue", marker="o")
ax2.set_ylabel("Y2", color="blue", fontsize=14)
plt.axvline(x=date.today(), color='k', linestyle='--')
plt.title("title")

plt.axvspan(date.today(), edate, facecolor='b', alpha=0.5)

# plt.savefig("stck_color_predict")
plt.show()

Output: