fill_between doesn't reach the specified position in X

I was using matplot fill_between, to paint an area in a gaussian curve but one of the areas doesn't reach the specified position, I have no idea why this happens, here is my code, I included some plt.annote arrows to show clearly that the fill_between function doesnt reach the specified position:
This is the line that has the problem:
ax.fill_between(x,0,y,where=(x<=especificacion),color='red',alpha=0.4)

And here's the important part of the code:

from scipy.stats import norm
fig,ax=plt.subplots(figsize=(10,8))
mean=29.02
std=4.01
especificacion=23.52

def gaussian_curve(x,mu,sigma):
  return norm.pdf(x,loc=mu,scale=sigma)

#GraficarcadacurvadeGaussyagregarunaleyenda
x=np.linspace(mean-(3*std),mean+(3*std))
y=gaussian_curve(x,mean,std)
ax.plot(x,y,color='blue')
fcr2=mean-(std*1.2812)
ax.set_xlim([mean-(3*std),mean+(3*std)])
ax.fill_between(x,0,y,where=(x<=fcr2),hatch='///',color='blue',alpha=0.2)
ax.fill_between(x,0,y,where=(x<=especificacion),color='red',alpha=0.4)

valor_y=norm.pdf(especificacion,loc=mean,scale=std)

plt.annotate(f'fcr:{especificacion}',xy=(especificacion,valor_y),xytext=(especificacion,valor_y+0.02),
arrowprops=dict(facecolor='black'))
plt.annotate(f'fc10:{round(fcr2,2)}',xy=(round(fcr2,2),0),xytext=(round(fcr2,2),0.01),
arrowprops=dict(facecolor='black'))

1. I have tried adding decimals to the position like this:
   ax.fill_between(x,0,y,where=(x<=especificacion+0.3),color='red',alpha=0.4)
   but it doesn't work

2. Changing the order in which the areas get painted but it just won't reach the position.

3. Adding a limits on the X axis

You can specify the number of points to generate with np.linspace. From the numpy documentation

> num
int, optional
Number of samples to generate. Default is 50. Must be non-negative

By increasing the number of samples to generate, the gap between each point decreases. You aren't guaranteed to have it be an exact match, but it will be a lot closer to your target value. In the example below, I set num to 200.

from scipy.stats import norm
import numpy as np
import matplotlib.pyplot as plt
fig,ax=plt.subplots(figsize=(10,8))
mean = 29.02
std = 4.01
especificacion = 23.52

def gaussian_curve(x,mu,sigma):
  return norm.pdf(x,loc=mu,scale=sigma)

#GraficarcadacurvadeGaussyagregarunaleyenda
x = np.linspace(mean-(3*std), mean+(3*std), num=200)
y = gaussian_curve(x,mean,std)
ax.plot(x,y,color='blue')
fcr2 = mean-(std*1.2812)
ax.set_xlim([mean-(3*std),mean+(3*std)])
ax.fill_between(x,0,y,where=(x<=fcr2),hatch='///',color='blue',alpha=0.2)
ax.fill_between(x,0,y,where=(x<=especificacion),color='red',alpha=0.4)

valor_y = norm.pdf(especificacion,loc=mean,scale=std)

plt.annotate(f'fcr:{especificacion}',xy=(especificacion,valor_y),xytext=(especificacion,valor_y+0.02),
arrowprops=dict(facecolor='black'))
plt.annotate(f'fc10:{round(fcr2,2)}',xy=(round(fcr2,2),0),xytext=(round(fcr2,2),0.01),
arrowprops=dict(facecolor='black'))

Alternatively, if you require an exact match to your target number, you can add a dummy variable to the numpy array, sort it, then plot your y values.

x = np.append(np.linspace(mean-(3*std),mean+(3*std)), [especificacion])
x = np.sort(x)
y = gaussian_curve(x,mean,std)
(rest of code the same)