Daily historical return deciles

[ishikabansal77]

by_sym = prices.groupby(level='symbol').close
for t in T:
prices[f'r{t:02}'] = by_sym.pct_change(t)
by_sym = prices.groupby(level='symbol').close
for t in T:
prices[f'r{t:02}'] = by_sym.pct_change(t)
for t in T:
prices[f'r{t:02}dec'] = (prices[f'r{t:02}']
.groupby(level='date')
.apply(lambda x: pd.qcut(x,
q=10,
labels=False,
duplicates='drop')))

IndexError Traceback (most recent call last)
Cell In[45], line 2
1 for t in T:
----> 2 prices[f'r{t:02}dec'] = (prices[f'r{t:02}']
3 .groupby(level='date')
4 .apply(lambda x: pd.qcut(x,
5 q=10,
6 labels=False,
7 duplicates='drop')))

File ~\anaconda3\envs\baclass\lib\site-packages\pandas\core\groupby\generic.py:216, in SeriesGroupBy.apply(self, func, *args, **kwargs)
210 @appender(
211 _apply_docs["template"].format(
212 input="series", examples=_apply_docs["series_examples"]
213 )
214 )
215 def apply(self, func, *args, **kwargs) -> Series:
--> 216 return super().apply(func, *args, **kwargs)

File ~\anaconda3\envs\baclass\lib\site-packages\pandas\core\groupby\groupby.py:1353, in GroupBy.apply(self, func, *args, **kwargs)
1351 with option_context("mode.chained_assignment", None):
1352 try:
-> 1353 result = self._python_apply_general(f, self._selected_obj)
1354 except TypeError:
1355 # gh-20949
1356 # try again, with .apply acting as a filtering
(...)
1360 # fails on some columns, e.g. a numeric operation
1361 # on a string grouper column
1363 return self._python_apply_general(f, self._obj_with_exclusions)

File ~\anaconda3\envs\baclass\lib\site-packages\pandas\core\groupby\groupby.py:1402, in GroupBy._python_apply_general(self, f, data, not_indexed_same, is_transform, is_agg)
1367 @Final
1368 def _python_apply_general(
1369 self,
(...)
1374 is_agg: bool = False,
1375 ) -> NDFrameT:
1376 """
1377 Apply function f in python space
1378
(...)
1400 data after applying f
1401 """
-> 1402 values, mutated = self.grouper.apply(f, data, self.axis)
1403 if not_indexed_same is None:
1404 not_indexed_same = mutated

File ~\anaconda3\envs\baclass\lib\site-packages\pandas\core\groupby\ops.py:767, in BaseGrouper.apply(self, f, data, axis)
765 # group might be modified
766 group_axes = group.axes
--> 767 res = f(group)
768 if not mutated and not _is_indexed_like(res, group_axes, axis):
769 mutated = True

Cell In[45], line 4, in (x)
1 for t in T:
2 prices[f'r{t:02}dec'] = (prices[f'r{t:02}']
3 .groupby(level='date')
----> 4 .apply(lambda x: pd.qcut(x,
5 q=10,
6 labels=False,
7 duplicates='drop')))

File ~\anaconda3\envs\baclass\lib\site-packages\pandas\core\reshape\tile.py:377, in qcut(x, q, labels, retbins, precision, duplicates)
375 x_np = np.asarray(x)
376 x_np = x_np[~np.isnan(x_np)]
--> 377 bins = np.quantile(x_np, quantiles)
379 fac, bins = _bins_to_cuts(
380 x,
381 bins,
(...)
386 duplicates=duplicates,
387 )
389 return _postprocess_for_cut(fac, bins, retbins, dtype, original)

File <array_function internals>:180, in quantile(*args, **kwargs)

File ~\anaconda3\envs\baclass\lib\site-packages\numpy\lib\function_base.py:4371, in quantile(a, q, axis, out, overwrite_input, method, keepdims, interpolation)
4369 if not _quantile_is_valid(q):
4370 raise ValueError("Quantiles must be in the range [0, 1]")
-> 4371 return _quantile_unchecked(
4372 a, q, axis, out, overwrite_input, method, keepdims)

File ~\anaconda3\envs\baclass\lib\site-packages\numpy\lib\function_base.py:4383, in _quantile_unchecked(a, q, axis, out, overwrite_input, method, keepdims)
4375 def _quantile_unchecked(a,
4376 q,
4377 axis=None,
(...)
4380 method="linear",
4381 keepdims=False):
4382 """Assumes that q is in [0, 1], and is an ndarray"""
-> 4383 r, k = _ureduce(a,
4384 func=_quantile_ureduce_func,
4385 q=q,
4386 axis=axis,
4387 out=out,
4388 overwrite_input=overwrite_input,
4389 method=method)
4390 if keepdims:
4391 return r.reshape(q.shape + k)

File ~\anaconda3\envs\baclass\lib\site-packages\numpy\lib\function_base.py:3702, in _ureduce(a, func, **kwargs)
3699 else:
3700 keepdim = (1,) * a.ndim
-> 3702 r = func(a, **kwargs)
3703 return r, keepdim

File ~\anaconda3\envs\baclass\lib\site-packages\numpy\lib\function_base.py:4552, in _quantile_ureduce_func(a, q, axis, out, overwrite_input, method)
4550 else:
4551 arr = a.copy()
-> 4552 result = _quantile(arr,
4553 quantiles=q,
4554 axis=axis,
4555 method=method,
4556 out=out)
4557 return result

File ~\anaconda3\envs\baclass\lib\site-packages\numpy\lib\function_base.py:4658, in _quantile(arr, quantiles, axis, method, out)
4650 arr.partition(
4651 np.unique(np.concatenate(([0, -1],
4652 previous_indexes.ravel(),
4653 next_indexes.ravel(),
4654 ))),
4655 axis=DATA_AXIS)
4656 if np.issubdtype(arr.dtype, np.inexact):
4657 slices_having_nans = np.isnan(
-> 4658 take(arr, indices=-1, axis=DATA_AXIS)
4659 )
4660 else:
4661 slices_having_nans = None

File <array_function internals>:180, in take(*args, **kwargs)

File ~\anaconda3\envs\baclass\lib\site-packages\numpy\core\fromnumeric.py:190, in take(a, indices, axis, out, mode)
93 @array_function_dispatch(_take_dispatcher)
94 def take(a, indices, axis=None, out=None, mode='raise'):
95 """
96 Take elements from an array along an axis.
97
(...)
188 [5, 7]])
189 """
--> 190 return _wrapfunc(a, 'take', indices, axis=axis, out=out, mode=mode)

File ~\anaconda3\envs\baclass\lib\site-packages\numpy\core\fromnumeric.py:57, in _wrapfunc(obj, method, *args, **kwds)
54 return _wrapit(obj, method, *args, **kwds)
56 try:
---> 57 return bound(*args, **kwds)
58 except TypeError:
59 # A TypeError occurs if the object does have such a method in its
60 # class, but its signature is not identical to that of NumPy's. This
(...)
64 # Call _wrapit from within the except clause to ensure a potential
65 # exception has a traceback chain.
66 return _wrapit(obj, method, *args, **kwds)

IndexError: cannot do a non-empty take from an empty axes.
4. See error

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[ishikabansal77]

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