def to_quantile(df, n_quantiles=5, axis=1):
"""
Convert cross-section values to the quantile number they belong.
Small values get small quantile numbers.
Parameters
----------
df : DataFrame
index date, column symbols
n_quantiles : int
The number of quantile to be divided to.
axis : int
Axis to apply quantilize.
Returns
-------
res : DataFrame
index date, column symbols
"""
# TODO: unnecesssary warnings
# import warnings
# warnings.filterwarnings(action='ignore', category=RuntimeWarning, module='py_exp')
res_arr = numeric.quantilize_without_nan(df.values, n_quantiles=n_quantiles, axis=axis)
res = pd.DataFrame(index=df.index, columns=df.columns, data=res_arr)
return res
def ts_quantile(self, df, window=3, n_quantiles=5):
roll = df.rolling(window=window)
func = lambda arr: numeric.quantilize_without_nan(
arr, n_quantiles=n_quantiles, axis=0)[-1]
res = roll.apply(func)
return res
def to_quantile(self, df, n_quantiles=5, axis=1, mask=None):
"""
Convert cross-section values to the quantile number they belong.
Small values get small quantile numbers.
Parameters
----------
df : DataFrame
index date, column symbols
n_quantiles : int
The number of quantile to be divided to.
axis : int
Axis to apply quantilize.
Returns
-------
res : DataFrame
index date, column symbols
"""
df = self._align_univariate(df)
df = self._mask_non_index_member(df)
df = self._mask_df(df, mask)
# TODO: unnecesssary warnings
# import warnings
# warnings.filterwarnings(action='ignore', category=RuntimeWarning, module='py_exp')
res_arr = numeric.quantilize_without_nan(df.values, n_quantiles=n_quantiles, axis=axis)
res = pd.DataFrame(index=df.index, columns=df.columns, data=res_arr)
return res
def cond_quantile(self, df, cond, n_quantiles):
cond = cond.fillna(0.0).astype(bool)
df, cond = self._align_bivariate(df, cond)
df = self._mask_non_index_member(df)
res_arr = numeric.quantilize_without_nan(df[cond].values, n_quantiles=n_quantiles, axis=1)
res = pd.DataFrame(index=df.index, columns=df.columns, data=res_arr)
return res
def ts_quantile(self, df, window=3, n_quantiles=5):
roll = df.rolling(window=window)
func = lambda arr: numeric.quantilize_without_nan(arr, n_quantiles=n_quantiles, axis=0)[-1]
res = roll.apply(func)
return res
