Plotting in matplotlib and fixing the x axis

I am trying to create a plot in Python using matplotlib. I write first the following code:

import pandas as pd
import matplotlib.pyplot as plt

df = pd.read_csv(r'Plot_Example.csv',sep=';')
df = df.set_index("Date")

fig, ax = plt.subplots() 
fig.set_size_inches(18.5, 18.5)
ax.plot(df["Yt"], label="Yt",color='blue') 
ax.plot(df["X1t"], label="X1t",color='red') 
ax.plot(df["X2t"],
label="X2t",color='yellow') 
ax.legend() fig.savefig('test3png.png',dpi=100)

For some more information:

df.info()

<class 'pandas.core.frame.DataFrame'> Index: 96 entries, 1/1/1949 to
1/12/1956 Data columns (total 3 columns):  #   Column  Non-Null Count 
Dtype
---  ------  --------------  -----  0   Yt      96 non-null     int64  1   X1t     96 non-null     int64  2   X2t     96 non-null     int64
dtypes: int64(3) memory usage: 2.6+ KB

All good, I get the following graph:

The problem is that I cannot see the date values in the horizontal axis. Is there a way to format the axis?

I have tried the following:

import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.dates import YearLocator, DateFormatter

df = pd.read_csv(r'Plot_Example.csv',sep=';')
df["Date"] = pd.to_datetime(df["Date"])
df = df.set_index("Date")

fig, ax = plt.subplots() 
fig.set_size_inches(18.5, 18.5)
ax.plot(df["Yt"], label="Yt",color='blue') 
ax.plot(df["X1t"],
label="X1t",color='red') 
ax.plot(df["X2t"], label="X2t", color='yellow') 
years = mdates.YearLocator() 
yearsFmt = mdates.DateFormatter('\n%Y') ?
ax.xaxis.set_major_locator(years)
ax.xaxis.set_major_formatter(yearsFmt) 
ax.legend()
fig.savefig('test3png.png', dpi=100)

I get nice formatting of the x-axis, but I get erroneous results in the plotting of the time series on the y-axis.

How can I format the x-axis from the original image or fix the time-series plotting in the second image?

You can keep only every n-th date on your x-axis (in the code below I chose n=10). Additionally, you can rotate the labels to avoid overlap:

tick_spacing = 10
plt.xticks(
    ax.get_xticks()[::tick_spacing],
    ax.get_xticklabels()[::tick_spacing],
    rotation=45,
    ha='right'
)