Example Notebook is out of date

[nehagupta891]

sales_q_denton = disaggregate_series( sales_a.resample("Y").last(), target_freq="Q", method="denton", agg_func="sum" )

I have downloaded your notebook and tried many different things but your lines for the actual calculation don't seem to work. I get this error: NotImplementedError: Only annual, quarterly and monthly frequencies are supported, found

What's going wrong?

[jessegrabowski]

Hi,

Pandas 2.2.0 deprecated the frequencies "Y" and "Q". You now have to explicitly ask for "YS" or "YE" (and "QS" or "QE").

I re-ran and push the example notebook to reflect the changes. Let me know if you still have problems.

[nehagupta891]

Hi,

Pandas 2.2.0 deprecated the frequencies "Y" and "Q". You now have to explicitly ask for "YS" or "YE" (and "QS" or "QE").

I re-ran and push the example notebook to reflect the changes. Let me know if you still have problems.

Thanks for the quick answer. I now get the following problem when I run your code:

ValueError: Invalid frequency AS-JAN

[jessegrabowski]

Make sure you have updated ts_disagg to version 1.1. You should be using YS, not AS, as AS has been depreciated.

[nehagupta891]

Hi, I have checked and updated it to version 1.1. I also have used YS (haven't changed anything from your notebook), I get this error:

ValueError Traceback (most recent call last) ----> 1 sales_q_denton = disaggregate_series( 2 sales_a.resample("YS").last(), target_freq="QS", method="denton", agg_func="sum" 3 )

323     target_idx = np.flatnonzero(low_freq_df.columns == target_column)[0]
324 

--> 325 df, C_mask, time_conversion_factor = prepare_input_dataframes( 326 low_freq_df, high_freq_df, target_freq, method 327 )

231         )
232 

--> 233 df, C_mask = align_and_merge_dfs(df1_out, df2_out) 234 if no_high_freq_data: 235 C_mask = None

259 
260 def align_and_merge_dfs(low_freq_df, high_freq_df):

--> 261 C_mask = handle_endpoint_differences(low_freq_df, high_freq_df) 262 df = pd.merge(low_freq_df, high_freq_df, left_index=True, right_index=True, how="outer") 263

245 
246     # these are stored as adverbs (e.g. yearly), so remove the -ly suffix

--> 247 attr = get_frequency_name(low_freq)[:-2] 248 249 low_freq_idx = getattr(low_freq_df.index, attr)

 67         return "monthly"
 68 

---> 69 raise ValueError(f"Invalid frequency {freq}") 70 71

ValueError: Invalid frequency AS-JAN

[jessegrabowski]

What version of pandas are you using

[nehagupta891]

Issue is solved, I needed to update pandas

[jessegrabowski]

Awesome, thanks!

I'll update the requirements to prevent usage with pandas<2.2.0