I have two questions that I put in one help request. so I hope it will not make this overcrowded.

I spend quite some time figuring this out but not successful so far. I am trying to plot only points from a series of data that are close to each other so not the transitions (see below plot). Probably I need an if condition that says if x(2)-x(1)<0.005 plot and if not do not plot. Later I want to do a linear regression on these points (thats why I want to exclude transitions). Can you please help me how to do the plotting with this condition and do linear regression.
enter image description here
This is my code:

# which value you want to use or plot reading from log data
desired_field1= "x y Box"
desired_value1 = "x1 [um]"
desired_field2= "x y Box"
desired_value2 =  "x3 [um]"
desired_field3= "LM Position"
desired_value3 =  "Z [um]"


# extracting desired data from logging
data=pd.read_excel(r"test2.xlsx", sheet_name='Sheet1')
data = data[(data['_time'] < '2024-05-21T09:49:37.6089875Z') & (data['_time'] > '2024-05-21T09:43:31.7141954Z')] #selecting desired time interval
data_measurement1 = data.loc[data['_measurement'] == desired_field1]
data_field1 = data_measurement1.loc[data['_field'] == desired_value1]
data_measurement2 = data.loc[data['_measurement'] == desired_field2]
data_field2 = data_measurement2.loc[data['_field'] == desired_value2]
data_measurement3 = data.loc[data['_measurement'] == desired_field3]
data_field3 = data_measurement3.loc[data['_field'] == desired_value3]
values1 = list(data_field1['_value']) #values we are interested in
values2 = list(data_field2['_value'])
values3 = list(data_field3['_value'])
#....

mean_xs = [(g + h) / 2 for g, h in zip(values1, values2)]
LM_mean = [50-x for x in mean_xs]

#start plotting
data_field1['_time'] = pd.to_datetime(data_field1['_time'].str.split().str[-1])
data_field2['_time'] = pd.to_datetime(data_field2['_time'].str.split().str[-1])
data_field3['_time'] = pd.to_datetime(data_field3['_time'].str.split().str[-1])
plt.plot(data_field1['_time'], values1, '-', label = desired_value1)
plt.plot(data_field2['_time'], values2, '-', label = desired_value2 )
plt.plot(data_field3['_time'], values3, '-', label = desired_value3)


plt.xlabel('time [D hh:mm]')
plt.ylabel(' x [um] MCS')
plt.legend(loc='best')
plt.gca().yaxis.grid(True)

plt.figure()
plt.plot(LM_mean, values3, 'o')

I have tried searching for this but was not successful