Decompose time series in Python with statsmodels

I am trying to decompose a time series. The database is a 2x8638 matrix. Follow the code.

import numpy as np
import pandas as pd
import matplotlib.pylab as plt
%matplotlib inline
from matplotlib.pylab import rcParams
rcParams['figure.figsize'] = 15, 6
from pandas.plotting import register_matplotlib_converters
register_matplotlib_converters()

df1 = pd.read_csv("u_x_ts.csv").set_index("0")
df1.head()

enter image description here

from statsmodels.tsa.seasonal import seasonal_decompose
result = seasonal_decompose(df1, model='multiplicative')
result.plot()
plt.show()

then python returns the error message:

ValueError: Multiplicative seasonality is not appropriate for zero and negative values

I think statsmodels doesn't support such small values, because at the beginning of the series the values ​​are too small. But if anyone knows a way out of this problem I appreciate it.