Compare two timeseries for distance

tdist.py

import pandas as pd
import numpy as np
import math
from datetime import datetime, timedelta

df1 = pd.DataFrame()
df1["time"] = pd.date_range('08/12/2021 00:00:01', periods=6, freq="4S")
df1['values'] = [1, 2, 3, 4, 5, 6]

df2 = pd.DataFrame()
df2["time"] = pd.date_range('08/12/2021', periods=4, freq="6S")
df2['values'] = [1, 2, 5, 200]

df = pd.merge(df1, df2, how="outer", left_on="time", right_on="time", sort=True)
print(df)

#df = df.interpolate(method="pad", axis=0)
df.ffill(inplace=True)
df.dropna(inplace=True)
#df.bfill(inplace=True)

df["time_to"] = df["time"].shift(-1)
df["time_to"].ffill(inplace=True)
df["duration"] = df["time_to"] - df["time"]

# Note: we do not have to use abs if d is a real distance
df["d"] = np.abs(np.arctan(df["values_x"] - df["values_y"]) / (math.pi / 2))

min_time = min(df["time"])
max_time = max(df["time_to"])
total = max_time - min_time
total = sum(df["duration"], timedelta())
print(total)

df["wd"] = df["d"] * ((df["time_to"] - df["time"]) / total)
print(df)
t2 = sum(df["wd"])
print(t2)