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DOC: Fixed PR06 docstring errors in pandas.interval_range & pandas.util.hash_array #28760

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Merged
merged 4 commits into from
Oct 7, 2019
Merged

DOC: Fixed PR06 docstring errors in pandas.interval_range & pandas.util.hash_array #28760

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1bed140
DOC: Fixed PR06 docstring errors in pandas.interval_range
samyak-jn Oct 2, 2019
0198696
DOC: Fixed PR06 docstring errors in pandas.util.hash_array
samyak-jn Oct 2, 2019
4191976
Corrects hashing.py
samyak-jn Oct 2, 2019
5367b6d
Updates hashing.py
samyak-jn Oct 3, 2019
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2 changes: 1 addition & 1 deletion pandas/core/indexes/interval.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1410,7 +1410,7 @@ def interval_range(
Left bound for generating intervals
end : numeric or datetime-like, default None
Right bound for generating intervals
periods : integer, default None
periods : int, default None
Number of periods to generate
freq : numeric, string, or DateOffset, default None
The length of each interval. Must be consistent with the type of start
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26 changes: 13 additions & 13 deletions pandas/core/util/hashing.py
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Expand Up @@ -62,11 +62,11 @@ def hash_pandas_object(

Parameters
----------
index : boolean, default True
index : bool, default True
include the index in the hash (if Series/DataFrame)
encoding : string, default 'utf8'
encoding for data & key when strings
hash_key : string key to encode, default to _default_hash_key
encoding : str, default 'utf8'
encoding for data & key when str
hash_key : str key to encode, default to _default_hash_key
categorize : bool, default True
Whether to first categorize object arrays before hashing. This is more
efficient when the array contains duplicate values.
Expand Down Expand Up @@ -143,8 +143,8 @@ def hash_tuples(vals, encoding="utf8", hash_key=None):
Parameters
----------
vals : MultiIndex, list-of-tuples, or single tuple
encoding : string, default 'utf8'
hash_key : string key to encode, default to _default_hash_key
encoding : str, default 'utf8'
hash_key : str key to encode, default to _default_hash_key

Returns
-------
Expand Down Expand Up @@ -186,8 +186,8 @@ def hash_tuple(val, encoding="utf8", hash_key=None):
Parameters
----------
val : single tuple
encoding : string, default 'utf8'
hash_key : string key to encode, default to _default_hash_key
encoding : str, default 'utf8'
hash_key : str key to encode, default to _default_hash_key

Returns
-------
Expand All @@ -209,8 +209,8 @@ def _hash_categorical(c, encoding, hash_key):
Parameters
----------
c : Categorical
encoding : string, default 'utf8'
hash_key : string key to encode, default to _default_hash_key
encoding : str, default 'utf8'
hash_key : str key to encode, default to _default_hash_key

Returns
-------
Expand Down Expand Up @@ -246,9 +246,9 @@ def hash_array(vals, encoding="utf8", hash_key=None, categorize=True):
Parameters
----------
vals : ndarray, Categorical
encoding : string, default 'utf8'
encoding for data & key when strings
hash_key : string key to encode, default to _default_hash_key
encoding : str, default 'utf8'
encoding for data & key when str
hash_key : str key to encode, default to _default_hash_key
categorize : bool, default True
Whether to first categorize object arrays before hashing. This is more
efficient when the array contains duplicate values.
Expand Down