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Python Package for Age-Period-Cohort and extended Chain-Ladder Analysis

License: GNU General Public License v3.0

Python 11.63% Jupyter Notebook 88.37%

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apc's Issues

pandas related errors in forecast and plot_parameters

Hi @JonasHarnau , first, thank you for releasing this package!

I started playing with it a little and encountered a few errors, which seem to be related to pandas version I am using. As both errors below come from pandas, could you maybe share which last version you tested the code with and check if it's working with the newest 0.25.3 version?

The simple code to replicate is as follows:

import apc
model = apc.Model()
model.data_from_df(apc.loss_KN(), data_format="CL", time_adjust=1)
model.fit("gen_log_normal_response", "APC")

and then:

model.forecast()

causes the following `ValueError` (click to unfold)

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-4-87d05bd4ab9b> in <module>
----> 1 model.forecast()

~[...]/venv/lib/python3.6/site-packages/apc/Model.py in forecast(self, quantiles, method, attach_to_self)
   2404                 raise ValueError('Forecasting not supported for this family.')
   2405 
-> 2406         self._get_point_fc()
   2407 
   2408         def _agg(df, lvl):

~[...]/venv/lib/python3.6/site-packages/apc/Model.py in _get_point_fc(self, attach_to_self)
   2294         """Generate point forecasts."""
   2295         fc_design = self._get_fc_design(self.predictor)
-> 2296         fc_linpred = fc_design.dot(self.parameters['coef']).rename(
   2297             'linear_predictor_forecast')
   2298 

~[...]/venv/lib/python3.6/site-packages/pandas/core/frame.py in dot(self, other)
   1076             common = self.columns.union(other.index)
   1077             if len(common) > len(self.columns) or len(common) > len(other.index):
-> 1078                 raise ValueError("matrices are not aligned")
   1079 
   1080             left = self.reindex(columns=common, copy=False)

ValueError: matrices are not aligned

and

model.plot_parameters()

causes the `KeyError: 'index'` (click to unfold)

---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
~[...]/venv/lib/python3.6/site-packages/pandas/core/indexes/base.py in get_loc(self, key, method, tolerance)
   2896             try:
-> 2897                 return self._engine.get_loc(key)
   2898             except KeyError:

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()

pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()

KeyError: 'index'

During handling of the above exception, another exception occurred:

KeyError                                  Traceback (most recent call last)
<ipython-input-5-e4fd0d5dc15b> in <module>
----> 1 model.plot_parameters()

~[...]/venv/lib/python3.6/site-packages/apc/Model.py in plot_parameters(self, plot_style, around_coef, simplify_ranges, figsize)
   2130         predictor = self.predictor
   2131 
-> 2132         parameters_adhoc = self.identify(plot_style, attach_to_self=False)
   2133 
   2134         def get_coefs(x):

~[...]/venv/lib/python3.6/site-packages/apc/Model.py in identify(self, style, attach_to_self)
   2018                 index=column_labels).T
   2019 
-> 2020             A_d_rows.index = A_d_rows.reset_index()['index'].apply(
   2021                 lambda x: 'A_detrend_' + x[2:])
   2022             B_d_rows.index = B_d_rows.reset_index()['index'].apply(

~[...]/venv/lib/python3.6/site-packages/pandas/core/frame.py in __getitem__(self, key)
   2993             if self.columns.nlevels > 1:
   2994                 return self._getitem_multilevel(key)
-> 2995             indexer = self.columns.get_loc(key)
   2996             if is_integer(indexer):
   2997                 indexer = [indexer]

~[...]/venv/lib/python3.6/site-packages/pandas/core/indexes/base.py in get_loc(self, key, method, tolerance)
   2897                 return self._engine.get_loc(key)
   2898             except KeyError:
-> 2899                 return self._engine.get_loc(self._maybe_cast_indexer(key))
   2900         indexer = self.get_indexer([key], method=method, tolerance=tolerance)
   2901         if indexer.ndim > 1 or indexer.size > 1:

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()

pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()

KeyError: 'index'

I am using JupyterLab within Amazon SageMaker, but this should be irrelevant here.

Python and package versions:

Python 3.6.6 :: Anaconda, Inc.

Full `pip freeze` print (click to unfold)

apc==1.0.1
backcall==0.1.0
clear==1.0.1
cycler==0.10.0
decorator==4.4.1
goodlogging==1.0.1
ipdb==0.12.3
ipykernel==5.1.3
ipython==7.11.1
ipython-genutils==0.2.0
jedi==0.15.2
jupyter-client==5.3.4
jupyter-core==4.6.1
kiwisolver==1.1.0
matplotlib==3.1.2
numpy==1.18.1
pandas==0.25.3
parso==0.5.2
patsy==0.5.1
pexpect==4.7.0
pickleshare==0.7.5
prompt-toolkit==3.0.2
ptyprocess==0.6.0
Pygments==2.5.2
pyparsing==2.4.6
python-dateutil==2.8.1
pytz==2019.3
pyzmq==18.1.1
quad-form-ratio==0.1.1
rarfile==2.7
requests==2.6.0
scipy==1.4.1
seaborn==0.9.0
six==1.13.0
statsmodels==0.10.2
tornado==6.0.3
traitlets==4.3.3
wcwidth==0.1.8

Out[6]: dose

I am regenerating the model for the purpose of using it as a base for my own apc analysis.
I can see the response and rate data is separately brought in, but where does the dose data come from? I is not available in neither Out[3] nor Out[4].

ValueError: matrices are not aligned in model.forecast()

I have some wine price data as below:

My goal is to forecast the price in future days.

However, there is value error during forecast:

ValueError: matrices are not aligned in Model.forecast()

apc/apc/Model.py

Line 2268 in 4908cc1

fc_linpred = fc_design.dot(self.parameters['coef']).rename(

Thank you for your work on Python. Recently, I encountered a problem with mismatched matrix shapes when using it. I don't quite understand what kind of operation the ‘dot’ here is supposed to perform, as the two matrices involved in the calculation seem to be unable to match. This problem occurred on Belgian_lung_cancer.

--> fc_linpred = fc_design.dot(self.parameters['coef']).rename(
'linear_predictor_forecast')
if self.family in ('poisson_response', 'od_poisson_response'):
fc_point = np.exp(fc_linpred).rename('point_forecast')
ValueError: matrices are not aligned

Chart to editable format

Hi! Thanks for all your support. I got my paper ready for publication. Just to ask, if it is possible to output the charts not into jpg, but to some kind of editable format. I am not even sure what the editable format would be...
Thanks Janika

janikabachmann/apc

model from df

I am using the same input format as Belgian_lung_cancer.xlsx reading from excel file as data1 and data2.
Then data=[data1, data2] but from model.data_from_df(**data) get an error:
data_from_df() argument after ** must be a mapping, not list

Can you please share steps 1-6 when imported from excel?

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