CODEWITHSUNDEEP
pythonpandasstatsmodels
helloB
helloB

Reputation: 3582

seasonal_decompose raises error: TypeError: PeriodIndex given. Check the `freq` attribute instead of using infer_freq

I'm trying to run a basic seasonal_decompose on the oft-used airline passengers data set, which begins with these rows:

Month
1949-02    4.770685
1949-03    4.882802
1949-04    4.859812
1949-05    4.795791
1949-06    4.905275
1949-07    4.997212
1949-08    4.997212
1949-09    4.912655
1949-10    4.779123
1949-11    4.644391
1949-12    4.770685
1950-01    4.744932
1950-02    4.836282
1950-03    4.948760
1950-04    4.905275
1950-05    4.828314
1950-06    5.003946
1950-07    5.135798
1950-08    5.135798
Freq: M, Name: Passengers, dtype: float64

My index type is:

pandas.tseries.period.PeriodIndex

I try to run some very simple code:

from statsmodels.tsa.seasonal import seasonal_decompose
log_passengers.interpolate(inplace = True)
decomposition = seasonal_decompose(log_passengers)

Here is the full output of the error:

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-113-bf122d457673> in <module>()
      1 from statsmodels.tsa.seasonal import seasonal_decompose
      2 log_passengers.interpolate(inplace = True)
----> 3 decomposition = seasonal_decompose(log_passengers)

/Users/ann/anaconda/lib/python3.5/site-packages/statsmodels/tsa/seasonal.py in seasonal_decompose(x, model, filt, freq)
     56     statsmodels.tsa.filters.convolution_filter
     57     """
---> 58     _pandas_wrapper, pfreq = _maybe_get_pandas_wrapper_freq(x)
     59     x = np.asanyarray(x).squeeze()
     60     nobs = len(x)

/Users/ann/anaconda/lib/python3.5/site-packages/statsmodels/tsa/filters/_utils.py in _maybe_get_pandas_wrapper_freq(X, trim)
     44         index = X.index
     45         func = _get_pandas_wrapper(X, trim)
---> 46         freq = index.inferred_freq
     47         return func, freq
     48     else:

pandas/src/properties.pyx in pandas.lib.cache_readonly.__get__ (pandas/lib.c:44097)()

/Users/ann/anaconda/lib/python3.5/site-packages/pandas/tseries/base.py in inferred_freq(self)
    233         """
    234         try:
--> 235             return frequencies.infer_freq(self)
    236         except ValueError:
    237             return None

/Users/ann/anaconda/lib/python3.5/site-packages/pandas/tseries/frequencies.py in infer_freq(index, warn)
    854 
    855     if com.is_period_arraylike(index):
--> 856         raise TypeError("PeriodIndex given. Check the `freq` attribute "
    857                         "instead of using infer_freq.")
    858     elif isinstance(index, pd.TimedeltaIndex):

TypeError: PeriodIndex given. Check the `freq` attribute instead of using infer_freq.

Here's what I've tried:

I see some talk of this on various Github issues (https://github.com/pydata/pandas/issues/6771) , but none of what's discussed seems to help. Any suggestions on how to troubleshoot this or what I'm doing wrong in this simple seasona_decompose?

Upvotes: 5

Views: 11245

Answers (1)

lsalamon
lsalamon

Reputation: 858

seasonal_decompose does not accept PeriodIndex, a workaround would be converting the index to DatetimeIndex using to_timestamp method:

from statsmodels.tsa.seasonal import seasonal_decompose
log_passengers.interpolate(inplace = True)
log_passengers.index=log_passengers.index.to_timestamp()
decomposition = seasonal_decompose(log_passengers)

Upvotes: 4

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