Milestone Trend Analysis Using Python

Following the example of the implementation on the github repo:
https://github.com/barakb32/PBI-MTA

And the topics:
https://community.powerbi.com/t5/Desktop/Create-Milestone-Trend-Analysis-MTA-in-Power-BI/m-p/191509
https://community.powerbi.com/t5/Developer/Milestone-Trend-Analysis/m-p/1366360

I want to create a milestone trend analysis like the image below:

My dataset is in the following format: 

And my python script: 

# The following code to create a dataframe and remove duplicated rows is always executed and acts as a preamble for your script: 

# dataset = pandas.DataFrame(M Actual Value, M, M Plan Value)
# dataset = dataset.drop_duplicates()

# Paste or type your script code here:
import matplotlib.pyplot as plt, datetime
import matplotlib.dates as mdates

dataset['Span Date']=pandas.to_datetime(dataset['Span Date'])
dataset['M Actual Value']=pandas.to_datetime(dataset['M Actual Value'])

pivot=pandas.pivot_table(dataset, aggfunc='first', index="M Actual Value", values='Span Date', columns='M')

for column in pivot:
    clean=pivot[['45 Line',column]]
    clean=clean[clean[column].notnull()]
    plt.plot_date(clean['45 Line'],clean[column],xdate=True,ydate=True,ls='-', lw=1)    
plt.xticks(rotation=0)

dtFmt = mdates.DateFormatter('%Y-%m') # define the formatting
plt.gca().xaxis.set_major_formatter(dtFmt)
plt.gca().yaxis.set_major_formatter(dtFmt)
plt.show()

The final Output is:

Is there any way to display correct days? I notice years (1600+ etc) that are not in my data.