не может вывести freq из неконвертируемого типа индекса

Question

Я пытаюсь использовать фильтр сезонных корректировок для набора данных, загружаемого из файла Excel. Один из столбцов - это дата в этом формате

, и я скопировал и вставил некоторый код, который отлично работал в другом проекте

path_to_x13  = "C:\\Program Files\\WinX13\\x13as\\"
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
plt.style.use(['seaborn-paper'])
import statsmodels.api as sm
from statsmodels.tsa.api import VAR 
from statsmodels.tsa.base.datetools import dates_from_str 
import datetime as dt
from rdflib import Graph

#!jt -t grade3 -nfs 11 -fs 11 -tfs 11 -cellw 1200
# We load the panel and do some data cleaning
mexico_pib = pd.read_excel("pib_trimestral_mexico1980_2020.xlsx")
mexico_imss_agregado = pd.read_excel("cubo_imss_asegurados_agregado.xlsx")
mexico_imss_pordel = pd.read_excel("cubo_imss_asegurados_pordel.xlsx")

Далее я * oop по словарю, в котором хранится скорректированная на сезонность продукция

seasonal_employment_agg = {}
seasonal_employment_pordel = {} 
seasonal_pib = {}

seasonal_pib = {}
for var in variables_pib:
    seasonal_pib[f'{var}sa'] = sm.tsa.x13_arima_analysis(endog = 
                            mexico_pib[var].dropna(), 
                            x12path = path_to_x13, prefer_x13 = True,  
                            freq = "Q")  
hp_pib = {}
for var in variables_pib:
    x = seasonal_pib[f'{var}sa'].seasadj
    temp_cycle, temp_trend = sm.tsa.filters.hpfilter(np.log(x).dropna(), lamb = 1600)
    hp_pib[f'{var}sa_c'] = temp_cycle 

, но я получаю следующее сообщение об ошибке

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
C:\ProgramData\Anaconda3\lib\site-packages\statsmodels\tsa\x13.py in pandas_to_series_spec(x)
    295     try:
--> 296         period = _freq_to_period[x.index.freqstr]
    297     except (AttributeError, ValueError):

AttributeError: 'Int64Index' object has no attribute 'freqstr'

During handling of the above exception, another exception occurred:

TypeError                                 Traceback (most recent call last)
<ipython-input-314-4a26a77c7ec9> in <module>
      9                             mexico_pib[var].dropna(),
     10                             x12path = path_to_x13, prefer_x13 = True,
---> 11                             freq = "Q")  
     12 hp_pib = {}
     13 for var in variables_pib:

C:\ProgramData\Anaconda3\lib\site-packages\pandas\util\_decorators.py in wrapper(*args, **kwargs)
    212                 else:
    213                     kwargs[new_arg_name] = new_arg_value
--> 214             return func(*args, **kwargs)
    215 
    216         return cast(F, wrapper)

C:\ProgramData\Anaconda3\lib\site-packages\statsmodels\tsa\x13.py in x13_arima_analysis(endog, maxorder, maxdiff, diff, exog, log, outlier, trading, forecast_periods, retspec, speconly, start, freq, print_stdout, x12path, prefer_x13)
    421                                                         periods=len(endog),
    422                                                         freq=freq))
--> 423     spec_obj = pandas_to_series_spec(endog)
    424     spec = spec_obj.create_spec()
    425     spec += "transform{{function={0}}}\n".format(_log_to_x12[log])

C:\ProgramData\Anaconda3\lib\site-packages\statsmodels\tsa\x13.py in pandas_to_series_spec(x)
    297     except (AttributeError, ValueError):
    298         from pandas.tseries.api import infer_freq
--> 299         period = _freq_to_period[infer_freq(x.index)]
    300     start_date = x.index[0]
    301     if period == 12:

C:\ProgramData\Anaconda3\lib\site-packages\pandas\tseries\frequencies.py in infer_freq(index, warn)
    284         if isinstance(index, (pd.Int64Index, pd.Float64Index)):
    285             raise TypeError(
--> 286                 f"cannot infer freq from a non-convertible index type {type(index)}"
    287             )
    288         index = index.values

TypeError: cannot infer freq from a non-convertible index type <class 'pandas.core.indexes.numeric.Int64Index'>

Спасибо