siuba.dply.forcats¶
fct_reorder¶
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siuba.dply.forcats.fct_reorder(fct, x, func=<function median>, desc=False) → pandas.core.arrays.categorical.Categorical¶ -
siuba.dply.forcats.fct_reorder(__data: siuba.siu.Symbolic, *args, **kwargs) -
siuba.dply.forcats.fct_reorder(__data: siuba.siu.Call, *args, **kwargs) Return copy of fct, with categories reordered according to values in x.
- Parameters
fct – a pandas.Categorical, or array(-like) used to create one.
x – values used to reorder categorical. Must be same length as fct.
func – function run over all values within a level of the categorical.
desc – whether to sort in descending order.
Examples
>>> fct_reorder(['a', 'a', 'b'], [4, 3, 2]) ['a', 'a', 'b'] Categories (2, object): ['b', 'a']
>>> fct_reorder(['a', 'a', 'b'], [4, 3, 2], desc = True) ['a', 'a', 'b'] Categories (2, object): ['a', 'b']
>>> fct_reorder(['x', 'x', 'y'], [4, 0, 2], np.max) ['x', 'x', 'y'] Categories (2, object): ['y', 'x']
fct_recode¶
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siuba.dply.forcats.fct_recode(fct, recat=None, **kwargs) → pandas.core.arrays.categorical.Categorical¶ -
siuba.dply.forcats.fct_recode(__data: siuba.siu.Symbolic, *args, **kwargs) -
siuba.dply.forcats.fct_recode(__data: siuba.siu.Call, *args, **kwargs) Return copy of fct with renamed categories.
- Parameters
fct – a pandas.Categorical, or array(-like) used to create one.
**kwargs – arguments of form new_name = old_name.
Examples
>>> cat = ['a', 'b', 'c'] >>> fct_recode(cat, z = 'c') ['a', 'b', 'z'] Categories (3, object): ['a', 'b', 'z']
# >>> fct_recode(cat, x = ‘a’, x = ‘b’) # >>> fct_recode(cat, x = [‘a’, ‘b’])
fct_collapse¶
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siuba.dply.forcats.fct_collapse(fct, recat, group_other=None) → pandas.core.arrays.categorical.Categorical¶ -
siuba.dply.forcats.fct_collapse(__data: siuba.siu.Symbolic, *args, **kwargs) -
siuba.dply.forcats.fct_collapse(__data: siuba.siu.Call, *args, **kwargs) Return copy of fct with categories renamed. Optionally group all others.
- Parameters
fct – a pandas.Categorical, or array(-like) used to create one.
recat – dictionary of form {new_cat_name: old_cat_name}. old_cat_name may be a list of existing categories, to be given the same name.
group_other – an optional string, specifying what all other categories should be named.
Notes
Resulting levels index is ordered according to the earliest level replaced. If we rename the first and last levels to “c”, then “c” is the first level.
Examples
>>> fct_collapse(['a', 'b', 'c'], {'x': 'a'}) ['x', 'b', 'c'] Categories (3, object): ['x', 'b', 'c']
>>> fct_collapse(['a', 'b', 'c'], {'x': 'a'}, group_other = 'others') ['x', 'others', 'others'] Categories (2, object): ['x', 'others']
>>> fct_collapse(['a', 'b', 'c'], {'ab': ['a', 'b']}) ['ab', 'ab', 'c'] Categories (2, object): ['ab', 'c']
>>> fct_collapse(['a', 'b', None], {'a': ['b']}) ['a', 'a', NaN] Categories (1, object): ['a']
fct_lump¶
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siuba.dply.forcats.fct_lump(fct, n=None, prop=None, w=None, other_level='Other', ties=None) → pandas.core.arrays.categorical.Categorical¶ -
siuba.dply.forcats.fct_lump(__data: siuba.siu.Symbolic, *args, **kwargs) -
siuba.dply.forcats.fct_lump(__data: siuba.siu.Call, *args, **kwargs) - Parameters
fct – a pandas.Categorical, or array(-like) used to create one.
n – number of categories to keep.
prop – (not implemented) keep categories that occur prop proportion of the time.
w – array of weights corresponding to each value in fct.
other_level – name for all lumped together levels.
ties – (not implemented) method to use in the case of ties.
Notes
Currently, one of n and prop must be specified.
Examples
>>> fct_lump(['a', 'a', 'b', 'c'], n = 1) ['a', 'a', 'Other', 'Other'] Categories (2, object): ['a', 'Other']
# TODO: implement prop arg >>> fct_lump([‘a’, ‘a’, ‘b’, ‘b’, ‘c’, ‘d’], prop = .2) [‘a’, ‘a’, ‘b’, ‘b’, ‘Other’, ‘Other’] Categories (3, object): [‘a’, ‘b’, ‘Other’]
fct_rev¶
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siuba.dply.forcats.fct_rev(fct) → pandas.core.arrays.categorical.Categorical¶ -
siuba.dply.forcats.fct_rev(__data: siuba.siu.Symbolic, *args, **kwargs) -
siuba.dply.forcats.fct_rev(__data: siuba.siu.Call, *args, **kwargs) Return a copy of fct with category level order reversed.next
- Parameters
fct – a pandas.Categorical, or array(-like) used to create one.
