This is a refactored version of the original code.

Install

pip install babino2020masks

How to use

Gather data

ny = API(api_settings['NYS'][:2], **api_settings['NYS'][2])
df = ny.get_all_data_statewide()

/home/runner/work/babino2020masks/babino2020masks/babino2020masks/core.py:63: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  for o in self.iter_data(): df = df.append(o)
/home/runner/work/babino2020masks/babino2020masks/babino2020masks/core.py:63: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  for o in self.iter_data(): df = df.append(o)
/home/runner/work/babino2020masks/babino2020masks/babino2020masks/core.py:63: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  for o in self.iter_data(): df = df.append(o)
/home/runner/work/babino2020masks/babino2020masks/babino2020masks/core.py:63: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  for o in self.iter_data(): df = df.append(o)
/home/runner/work/babino2020masks/babino2020masks/babino2020masks/core.py:63: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  for o in self.iter_data(): df = df.append(o)
/home/runner/work/babino2020masks/babino2020masks/babino2020masks/core.py:63: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  for o in self.iter_data(): df = df.append(o)
/home/runner/work/babino2020masks/babino2020masks/babino2020masks/core.py:63: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  for o in self.iter_data(): df = df.append(o)
/home/runner/work/babino2020masks/babino2020masks/babino2020masks/core.py:63: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  for o in self.iter_data(): df = df.append(o)
/home/runner/work/babino2020masks/babino2020masks/babino2020masks/core.py:63: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  for o in self.iter_data(): df = df.append(o)
/home/runner/work/babino2020masks/babino2020masks/babino2020masks/core.py:63: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  for o in self.iter_data(): df = df.append(o)
/home/runner/work/babino2020masks/babino2020masks/babino2020masks/core.py:63: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  for o in self.iter_data(): df = df.append(o)
/home/runner/work/babino2020masks/babino2020masks/babino2020masks/core.py:63: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  for o in self.iter_data(): df = df.append(o)
/home/runner/work/babino2020masks/babino2020masks/babino2020masks/core.py:63: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  for o in self.iter_data(): df = df.append(o)
/home/runner/work/babino2020masks/babino2020masks/babino2020masks/core.py:78: FutureWarning: Dropping invalid columns in DataFrameGroupBy.add is deprecated. In a future version, a TypeError will be raised. Before calling .add, select only columns which should be valid for the function.
  df = df.groupby('date').sum()

ax = plot_data_and_fit(df, 'Date', 'Odds', None, None, None, figsize=(10, 7))
ax.set_title(f'{df.tail(1).Date[0]:%B %d, %Y}, Positivity Odds:{df.tail(1).Odds[0]:2.3}');

Fit the model

sdf = df.loc[df.Date<='15-05-2020'].copy()
lics = LassoICSelector(sdf['Odds'], 'bic')
lics.fit_best_alpha()

/opt/hostedtoolcache/Python/3.8.13/x64/lib/python3.8/site-packages/pandas/core/arraylike.py:52: UserWarning: Parsing '15-05-2020' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.
  return self._cmp_method(other, operator.le)
/opt/hostedtoolcache/Python/3.8.13/x64/lib/python3.8/site-packages/sklearn/linear_model/_base.py:133: FutureWarning: The default of 'normalize' will be set to False in version 1.2 and deprecated in version 1.4.
If you wish to scale the data, use Pipeline with a StandardScaler in a preprocessing stage. To reproduce the previous behavior:

from sklearn.pipeline import make_pipeline

model = make_pipeline(StandardScaler(with_mean=False), LassoLars())

If you wish to pass a sample_weight parameter, you need to pass it as a fit parameter to each step of the pipeline as follows:

kwargs = {s[0] + '__sample_weight': sample_weight for s in model.steps}
model.fit(X, y, **kwargs)

Set parameter alpha to: original_alpha * np.sqrt(n_samples). 
  warnings.warn(

Positivity Odds in NYS

sdf['Fit'], sdf['Odds_l'], sdf['Odds_u'] = lics.odds_hat_l_u()
ax = plot_data_and_fit(sdf, 'Date', 'Odds', 'Fit', 'Odds_l', 'Odds_u', figsize=(10, 7))

Instantaneous reproduction number, $R_t$

sdf['R'], sdf['Rl'], sdf['Ru'] = lics.rt()
ax = plot_data_and_fit(sdf, 'Date', None, 'R', 'Rl', 'Ru', figsize=(10, 7), logy=False, palette=[colorblind[1],colorblind[1]])

Counterfactual Scenario without Masks

sdf['Cf. Odds'], sdf['cf_odds_l'], sdf['cf_odds_u'] = lics.counterfactual()

ax = plot_data_and_fit(sdf, 'Date', 'Odds', 'Fit', 'Odds_l', 'Odds_u', figsize=(10, 7))
plot_data_and_fit(sdf, 'Date', None, 'Cf. Odds', 'cf_odds_l', 'cf_odds_u', palette=[colorblind[2],colorblind[2]], ax=ax);

Last updated on 07/26/2022 13:48:33