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PERF: slow conversion of single series to data frame #5568

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Merged
merged 1 commit into from
Nov 21, 2013
Merged

PERF: slow conversion of single series to data frame #5568

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2 changes: 1 addition & 1 deletion pandas/core/frame.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4575,7 +4575,7 @@ def extract_index(data):


def _prep_ndarray(values, copy=True):
if not isinstance(values, np.ndarray):
if not isinstance(values, (np.ndarray,Series)):
if len(values) == 0:
return np.empty((0, 0), dtype=object)

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9 changes: 7 additions & 2 deletions vb_suite/frame_ctor.py
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Expand Up @@ -25,19 +25,24 @@
frame_ctor_nested_dict = Benchmark("DataFrame(data)", setup)

# From JSON-like stuff

frame_ctor_list_of_dict = Benchmark("DataFrame(dict_list)", setup,
start_date=datetime(2011, 12, 20))

series_ctor_from_dict = Benchmark("Series(some_dict)", setup)

# nested dict, integer indexes, regression described in #621

setup = common_setup + """
data = dict((i,dict((j,float(j)) for j in xrange(100))) for i in xrange(2000))
"""
frame_ctor_nested_dict_int64 = Benchmark("DataFrame(data)", setup)

# from a mi-series
setup = common_setup + """
mi = MultiIndex.from_tuples([(x,y) for x in range(100) for y in range(100)])
s = Series(randn(10000), index=mi)
"""
frame_from_series = Benchmark("DataFrame(s)", setup)

#----------------------------------------------------------------------
# get_numeric_data

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