def value_counts(values, sort=True, ascending=False):
"""
Compute a histogram of the counts of non-null values
Parameters
----------
values : ndarray (1-d)
sort : boolean, default True
Sort by values
ascending : boolean, default False
Sort in ascending order
Returns
-------
value_counts : Series
"""
from pandas.core.series import Series
from collections import defaultdict
if com.is_integer_dtype(values.dtype):
values = com._ensure_int64(values)
keys, counts = lib.value_count_int64(values)
result = Series(counts, index=keys)
else:
counter = defaultdict(lambda: 0)
values = values[com.notnull(values)]
for value in values:
counter[value] += 1
result = Series(counter)
if sort:
result.sort()
if not ascending:
result = result[::-1]
return result
def value_counts(values, sort=True, ascending=False):
"""
Compute a histogram of the counts of non-null values
Parameters
----------
values : ndarray (1-d)
sort : boolean, default True
Sort by values
ascending : boolean, default False
Sort in ascending order
Returns
-------
value_counts : Series
"""
from pandas.core.series import Series
from collections import defaultdict
if com.is_integer_dtype(values.dtype):
values = com._ensure_int64(values)
keys, counts = lib.value_count_int64(values)
result = Series(counts, index=keys)
else:
counter = defaultdict(lambda: 0)
values = values[com.notnull(values)]
for value in values:
counter[value] += 1
result = Series(counter)
if sort:
result.sort()
if not ascending:
result = result[::-1]
return result