Pandas 0.12 is much faster than Pandas 0.18
Hello,

I am running the code below in pandas 0.18 and benchmarking it against pandas 0.12 and the profiling shows that 0.18 performs much slower on this. I put the output in the details section. Could you please advise?

Thank you so very much for your help,
Giuliano

```
from datetime import date, timedelta
from time import time
import pandas as pd

sizes = [500]

base_date = date(2016,10,31)

for n in sizes:
    dates = [base_date - timedelta(days = x) for x in range(1, n, 1)]
    dates_df = pd.DataFrame({'DATE' : dates, 'key' : 1})
    identifiers = range(1, 5000)
    identifiers_df = pd.DataFrame({'IDENTIFIER' : identifiers, 'key' : 1})

    df = pd.merge(dates_df, identifiers_df, on='key')
    df = df.set_index(['DATE', 'IDENTIFIER'])
    df = df.sort_index(axis = 0, level = ['DATE', 'IDENTIFIER'], ascending=False)

    start_time = time()
    for d in dates:
        temp = df.loc[d]

    end_time = time()

    print ('%s %s' % (n, end_time - start_time))
```
<details>
# Output from 0.18
/opt/anaconda/base/envs/pandas0.18/bin/python2.7 /home/gamantini/QA/avoitenok/pandas_migration/testDatesPerformance.py
500 5.26671504974
         337459 function calls (331370 primitive calls) in 14.176 seconds

   Ordered by: standard name

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        1    0.000    0.000   14.176   14.176 <string>:1(<module>)
     1519    0.002    0.000    0.002    0.000 __init__.py:157(iteritems)
        1    0.000    0.000    0.000    0.000 __init__.py:22(find_module)
        2    0.000    0.000    0.000    0.000 _methods.py:34(_prod)
     1027    0.001    0.000    0.023    0.000 _methods.py:37(_any)
        7    0.000    0.000    0.000    0.000 _methods.py:40(_all)
        6    0.020    0.003    2.945    0.491 algorithms.py:145(factorize)
        6    0.000    0.000    0.007    0.001 algorithms.py:616(_get_data_algo)
       11    0.000    0.000    0.000    0.000 algorithms.py:807(_get_take_nd_function)
       11    0.012    0.001    0.527    0.048 algorithms.py:840(take_nd)
      499    0.002    0.000    0.004    0.000 base.py:1016(_convert_slice_indexer)
     2002    0.001    0.000    0.004    0.000 base.py:106(_reset_cache)
        1    0.000    0.000    0.000    0.000 base.py:1136(_cleanup)
       14    0.000    0.000    0.000    0.000 base.py:1143(_engine)
       15    0.000    0.000    0.000    0.000 base.py:1146(<lambda>)
        1    0.000    0.000    0.000    0.000 base.py:1172(inferred_type)
        6    0.000    0.000    0.000    0.000 base.py:1233(__contains__)
    16/14    0.001    0.000    0.003    0.000 base.py:124(__new__)
       10    0.000    0.000    0.000    0.000 base.py:1247(__getitem__)
        1    0.000    0.000    0.000    0.000 base.py:1281(_ensure_compat_append)
        1    0.000    0.000    0.000    0.000 base.py:1308(append)
        1    0.000    0.000    0.000    0.000 base.py:1326(_ensure_compat_concat)
      499    0.005    0.000    0.047    0.000 base.py:1360(take)
        4    0.000    0.000    0.000    0.000 base.py:1415(hasnans)
        5    0.000    0.000    0.000    0.000 base.py:1507(equals)
        1    0.000    0.000    0.000    0.000 base.py:1520(identical)
        1    0.000    0.000    0.003    0.003 base.py:169(_box_values)
        1    0.000    0.000    0.000    0.000 base.py:1770(_wrap_union_result)
        1    0.000    0.000    0.000    0.000 base.py:1774(intersection)
     2007    0.013    0.000    0.043    0.000 base.py:1915(get_loc)
        2    0.000    0.000    0.000    0.000 base.py:2028(get_indexer)
      998    0.002    0.000    0.002    0.000 base.py:218(freqstr)
        2    0.000    0.000    0.000    0.000 base.py:2201(_possibly_promote)
        1    0.000    0.000    0.000    0.000 base.py:227(inferred_freq)
        1    0.000    0.000    0.000    0.000 base.py:2276(_can_reindex)
        1    0.000    0.000    0.000    0.000 base.py:2295(reindex)
      998    0.001    0.000    0.002    0.000 base.py:2795(_maybe_cast_indexer)
     1497    0.001    0.000    0.002    0.000 base.py:2810(_validate_indexer)
        1    0.000    0.000    0.000    0.000 base.py:3001(delete)
        1    0.000    0.000    0.000    0.000 base.py:3031(drop)
     1517    0.006    0.000    0.011    0.000 base.py:309(_simple_new)
        2    0.000    0.000    0.000    0.000 base.py:321(_isnan)
        2    0.000    0.000    0.000    0.000 base.py:326(hasnans)
     3527    0.002    0.000    0.004    0.000 base.py:3381(_ensure_index)
        1    0.000    0.000    0.000    0.000 base.py:3412(_get_na_value)
     2002    0.003    0.000    0.012    0.000 base.py:3417(_ensure_frozen)
        1    0.000    0.000    0.000    0.000 base.py:3425(_ensure_has_len)
     2506    0.011    0.000    0.070    0.000 base.py:346(_shallow_copy)
        1    0.000    0.000    0.000    0.000 base.py:354(_shallow_copy_with_infer)
        5    0.000    0.000    0.000    0.000 base.py:383(is_)
     3523    0.003    0.000    0.003    0.000 base.py:403(_reset_identity)
     3579    0.002    0.000    0.003    0.000 base.py:409(__len__)
        1    0.000    0.000    0.000    0.000 base.py:415(__array__)
        4    0.000    0.000    0.000    0.000 base.py:430(dtype)
     2542    0.003    0.000    0.006    0.000 base.py:440(values)
       10    0.000    0.000    0.000    0.000 base.py:445(get_values)
        5    0.000    0.000    0.000    0.000 base.py:490(_coerce_to_ndarray)
     2508    0.011    0.000    0.014    0.000 base.py:506(_get_attributes_dict)
        2    0.000    0.000    0.000    0.000 base.py:510(view)
     6001    0.011    0.000    0.015    0.000 base.py:711(__getitem__)
     2002    0.001    0.000    0.002    0.000 base.py:774(_shallow_copy)
        1    0.000    0.000    0.000    0.000 base.py:778(_assert_can_do_setop)
        2    0.000    0.000    0.000    0.000 base.py:791(nlevels)
        1    0.000    0.000    0.000    0.000 base.py:795(_get_names)
     2003    0.001    0.000    0.002    0.000 base.py:798(_set_names)
     2003    0.004    0.000    0.013    0.000 base.py:806(set_names)
     2002    0.002    0.000    0.015    0.000 base.py:865(rename)
        8    0.000    0.000    0.000    0.000 base.py:870(_values)
        2    0.000    0.000    0.000    0.000 base.py:914(is_monotonic)
        1    0.000    0.000    0.000    0.000 base.py:919(is_monotonic_increasing)
       10    0.000    0.000    0.000    0.000 base.py:938(is_unique)
      499    0.001    0.000    0.005    0.000 base.py:972(_convert_scalar_indexer)
        6    0.003    0.001    3.767    0.628 categorical.py:222(__init__)
        4    0.010    0.003    2.967    0.742 categorical.py:374(from_array)
        8    0.000    0.000    0.000    0.000 categorical.py:436(_get_codes)
        6    0.000    0.000    0.003    0.000 categorical.py:470(_validate_categories)
        6    0.000    0.000    0.000    0.000 categorical.py:534(_get_categories)
        6    0.000    0.000    0.000    0.000 categorical.py:565(set_ordered)
     1500    0.002    0.000    0.002    0.000 collections.py:78(__iter__)
        4    0.000    0.000    0.000    0.000 common.py:1011(_possibly_cast_to_datetime)
       10    0.000    0.000    0.802    0.080 common.py:1111(_possibly_infer_to_datetimelike)
        2    0.000    0.000    0.801    0.401 common.py:1147(_try_datetime)
     2497    0.005    0.000    0.017    0.000 common.py:1203(is_bool_indexer)
        2    0.000    0.000    0.000    0.000 common.py:1226(_default_index)
        2    0.000    0.000    0.000    0.000 common.py:1268(_try_sort)
        1    0.000    0.000    0.000    0.000 common.py:1276(_count_not_none)
        3    0.000    0.000    0.000    0.000 common.py:1277(<genexpr>)
       11    0.000    0.000    0.000    0.000 common.py:1380(_asarray_tuplesafe)
        1    0.000    0.000    0.000    0.000 common.py:1412(_index_labels_to_array)
        3    0.000    0.000    0.000    0.000 common.py:1427(_maybe_make_list)
        1    0.000    0.000    0.000    0.000 common.py:1456(is_period_arraylike)
       12    0.000    0.000    0.000    0.000 common.py:1491(_get_dtype)
     2055    0.006    0.000    0.009    0.000 common.py:1511(_get_dtype_type)
        5    0.000    0.000    0.000    0.000 common.py:1532(is_dtype_equal)
        4    0.000    0.000    0.000    0.000 common.py:1550(is_integer_dtype)
        4    0.000    0.000    0.000    0.000 common.py:1561(is_int_or_datetime_dtype)
     1011    0.002    0.000    0.005    0.000 common.py:1567(is_datetime64_dtype)
       64    0.000    0.000    0.000    0.000 common.py:1575(is_datetime64tz_dtype)
        8    0.000    0.000    0.000    0.000 common.py:1592(is_timedelta64_dtype)
        6    0.000    0.000    0.000    0.000 common.py:1602(is_datetime_or_timedelta_dtype)
        1    0.000    0.000    0.000    0.000 common.py:165(_isnull_ndarraylike)
        6    0.000    0.000    0.000    0.000 common.py:1664(needs_i8_conversion)
        1    0.000    0.000    0.000    0.000 common.py:1675(is_string_dtype)
        1    0.000    0.000    0.000    0.000 common.py:1680(is_string_like_dtype)
        6    0.000    0.000    0.000    0.000 common.py:1686(is_float_dtype)
        8    0.000    0.000    0.000    0.000 common.py:1696(is_bool_dtype)
        6    0.000    0.000    0.000    0.000 common.py:1705(is_sparse)
       58    0.000    0.000    0.001    0.000 common.py:1710(is_datetimetz)
        2    0.000    0.000    0.000    0.000 common.py:1717(is_extension_type)
       16    0.000    0.000    0.000    0.000 common.py:1731(is_categorical)
       70    0.000    0.000    0.001    0.000 common.py:1736(is_categorical_dtype)
     1008    0.002    0.000    0.009    0.000 common.py:1745(is_object_dtype)
     5019    0.005    0.000    0.008    0.000 common.py:1763(is_list_like)
        4    0.000    0.000    0.000    0.000 common.py:1788(is_hashable)
     1002    0.001    0.000    0.001    0.000 common.py:1846(_apply_if_callable)
        5    0.000    0.000    0.000    0.000 common.py:272(array_equivalent)
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        2    0.000    0.000    0.000    0.000 common.py:446(_infer_dtype_from_scalar)
        8    0.000    0.000    0.001    0.000 common.py:527(_maybe_promote)
        5    0.000    0.000    0.000    0.000 common.py:73(isnull)
        5    0.000    0.000    0.000    0.000 common.py:94(_isnull_new)
        2    0.000    0.000    0.001    0.000 common.py:998(_possibly_convert_platform)
        2    0.000    0.000    0.000    0.000 decorators.py:65(wrapper)
       27    0.000    0.000    0.000    0.000 dtypes.py:122(construct_from_string)
        9    0.000    0.000    0.000    0.000 dtypes.py:159(__init__)
        9    0.000    0.000    0.000    0.000 dtypes.py:191(construct_from_string)
      134    0.000    0.000    0.001    0.000 dtypes.py:74(is_dtype)
        4    0.000    0.000    0.002    0.000 frame.py:1973(__getitem__)
      503    0.000    0.000    0.000    0.000 frame.py:199(_constructor)
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      505    0.004    0.000    0.011    0.000 frame.py:210(__init__)
        4    0.000    0.000    0.001    0.000 frame.py:2331(_box_item_values)
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        1    0.000    0.000    2.401    2.401 frame.py:2769(set_index)
        2    0.000    0.000    0.003    0.001 frame.py:307(_init_dict)
        1    0.022    0.022    5.554    5.554 frame.py:3227(sort_index)
        1    0.000    0.000    0.000    0.000 frame.py:434(axes)
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      500    0.002    0.000    0.019    0.000 function.py:36(__call__)
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      503    0.001    0.000    0.001    0.000 generic.py:124(_init_mgr)
      998    0.001    0.000    0.002    0.000 generic.py:1312(_indexer)
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      499    0.001    0.000    0.003    0.000 generic.py:1402(_is_view)
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      499    0.006    0.000    0.167    0.000 generic.py:1447(_slice)
      998    0.003    0.000    0.005    0.000 generic.py:1467(_set_is_copy)
        2    0.000    0.000    0.108    0.054 generic.py:1580(__delitem__)
      499    0.014    0.000    2.877    0.006 generic.py:1643(xs)
        1    0.000    0.000    0.001    0.001 generic.py:1846(drop)
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        1    0.000    0.000    0.000    0.000 {pandas.tslib.build_field_sarray}
        1    0.000    0.000    0.000    0.000 {pandas.tslib.is_timestamp_array}
     1003    0.002    0.000    0.002    0.000 {pandas.tslib.maybe_get_tz}
        3    0.000    0.000    0.000    0.000 {pandas.tslib.unique_deltas}
        8    0.000    0.000    0.000    0.000 {range}
        2    0.000    0.000    0.000    0.000 {setattr}
     1002    0.004    0.000    0.013    0.000 {sorted}
        6    0.000    0.000    0.000    0.000 {sum}
        2    0.000    0.000    0.000    0.000 {time.time}



Process finished with exit code 0
# Output from 0.12
/opt/epd/7.3-2_pandas0.12/bin/python2.7 /home/gamantini/QA/avoitenok/pandas_migration/testDatesPerformance.py
500 0.138274908066
         91488 function calls (90977 primitive calls) in 2.079 seconds

   Ordered by: standard name

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        1    0.000    0.000    2.079    2.079 <string>:1(<module>)
        4    0.000    0.000    0.000    0.000 _methods.py:20(_prod)
       11    0.000    0.000    0.011    0.001 _methods.py:24(_any)
        1    0.000    0.000    0.000    0.000 _methods.py:28(_all)
        2    0.008    0.004    0.309    0.154 algorithms.py:105(factorize)
        2    0.000    0.000    0.000    0.000 algorithms.py:298(_get_data_algo)
        1    0.000    0.000    0.000    0.000 arraysetops.py:281(in1d)
        1    0.000    0.000    0.000    0.000 arraysetops.py:388(setdiff1d)
        2    0.000    0.000    0.000    0.000 arraysetops.py:90(unique)
     1000    0.000    0.000    0.000    0.000 base.py:45(_constructor)
        2    0.000    0.000    0.000    0.000 categorical.py:111(_set_levels)
        2    0.000    0.000    0.000    0.000 categorical.py:119(_get_levels)
        2    0.000    0.000    0.000    0.000 categorical.py:71(__init__)
        2    0.001    0.000    0.310    0.155 categorical.py:87(from_array)
        2    0.000    0.000    0.001    0.000 common.py:1138(_possibly_convert_platform)
        4    0.000    0.000    0.000    0.000 common.py:1167(_possibly_cast_to_datetime)
     1504    0.001    0.000    0.003    0.000 common.py:1232(_is_bool_indexer)
        2    0.000    0.000    0.000    0.000 common.py:1292(_try_sort)
        3    0.000    0.000    0.000    0.000 common.py:1369(split_ranges)
       16    0.000    0.000    0.000    0.000 common.py:1468(_asarray_tuplesafe)
        1    0.000    0.000    0.000    0.000 common.py:1496(_index_labels_to_array)
        3    0.000    0.000    0.000    0.000 common.py:1511(_maybe_make_list)
        2    0.000    0.000    0.000    0.000 common.py:1517(is_bool)
     1502    0.001    0.000    0.001    0.000 common.py:1521(is_integer)
        5    0.000    0.000    0.000    0.000 common.py:1525(is_float)
        2    0.000    0.000    0.000    0.000 common.py:1542(is_integer_dtype)
        4    0.000    0.000    0.000    0.000 common.py:1552(_is_int_or_datetime_dtype)
        4    0.000    0.000    0.000    0.000 common.py:1561(is_datetime64_dtype)
        2    0.000    0.000    0.000    0.000 common.py:1583(is_float_dtype)
        4    0.000    0.000    0.000    0.000 common.py:1611(is_list_like)
        8    0.000    0.000    0.000    0.000 common.py:431(_get_take_nd_function)
        8    0.013    0.002    0.204    0.025 common.py:462(take_nd)
        2    0.000    0.000    0.000    0.000 common.py:677(_infer_dtype_from_scalar)
        5    0.000    0.000    0.000    0.000 common.py:728(_maybe_promote)
        1    0.000    0.000    0.000    0.000 frame.py:1722(as_matrix)
      504    0.001    0.000    0.039    0.000 frame.py:1986(__getitem__)
      499    0.000    0.000    0.033    0.000 frame.py:2008(_getitem_slice)
      499    0.002    0.000    0.033    0.000 frame.py:2063(_slice)
        5    0.000    0.000    0.000    0.000 frame.py:2075(_box_item_values)
     1501    0.004    0.000    0.007    0.000 frame.py:2090(__setattr__)
      499    0.004    0.000    0.127    0.000 frame.py:2264(xs)
        1    0.000    0.000    0.001    0.001 frame.py:2573(reindex)
        1    0.000    0.000    0.000    0.000 frame.py:2709(_reindex_columns)
        1    0.000    0.000    0.000    0.000 frame.py:2717(_reindex_with_indexers)
        1    0.000    0.000    0.342    0.342 frame.py:2771(set_index)
        1    0.000    0.000    0.053    0.053 frame.py:2963(take)
        1    0.024    0.024    1.380    1.380 frame.py:3207(sort_index)
      505    0.001    0.000    0.006    0.000 frame.py:386(__init__)
      502    0.000    0.000    0.000    0.000 frame.py:466(_init_mgr)
        2    0.000    0.000    0.003    0.001 frame.py:480(_init_dict)
        1    0.000    0.000    0.000    0.000 frame.py:530(_init_ndarray)
        2    0.000    0.000    0.002    0.001 frame.py:5663(_arrays_to_mgr)
        2    0.000    0.000    0.000    0.000 frame.py:5682(extract_index)
        1    0.000    0.000    0.000    0.000 frame.py:5734(_prep_ndarray)
        1    0.000    0.000    0.000    0.000 frame.py:583(axes)
        2    0.000    0.000    0.001    0.001 frame.py:5908(_homogenize)
        1    0.000    0.000    0.000    0.000 frame.py:795(__len__)
        2    0.000    0.000    0.000    0.000 frame.py:799(__contains__)
        4    0.000    0.000    0.001    0.000 fromnumeric.py:2022(prod)
        3    0.000    0.000    0.000    0.000 function_base.py:3384(delete)
      499    0.001    0.000    0.002    0.000 function_base.py:35(iterable)
      499    0.000    0.000    0.001    0.000 generic.py:102(_indexer)
        1    0.000    0.000    0.001    0.001 generic.py:380(drop)
      505    0.001    0.000    0.001    0.000 generic.py:605(__init__)
        1    0.000    0.000    0.000    0.000 generic.py:651(ndim)
      500    0.001    0.000    0.003    0.000 generic.py:655(_set_axis)
      500    0.001    0.000    0.001    0.000 generic.py:66(_get_axis_number)
        5    0.000    0.000    0.000    0.000 generic.py:662(_get_item_cache)
      500    0.000    0.000    0.000    0.000 generic.py:675(_clear_item_cache)
        2    0.000    0.000    0.001    0.000 generic.py:682(__delitem__)
     1000    0.002    0.000    0.007    0.000 generic.py:750(_consolidate_inplace)
     1000    0.001    0.000    0.002    0.000 generic.py:751(<lambda>)
        1    0.000    0.000    0.000    0.000 generic.py:778(_is_mixed_type)
     1001    0.001    0.000    0.002    0.000 generic.py:78(_get_axis_name)
        1    0.000    0.000    0.000    0.000 generic.py:780(<lambda>)
     1001    0.001    0.000    0.004    0.000 generic.py:788(_protect_consolidate)
     1000    0.001    0.000    0.003    0.000 generic.py:90(_get_axis)
        1    0.000    0.000    0.031    0.031 generic.py:950(copy)
        3    0.036    0.012    0.041    0.014 groupby.py:2427(get_group_index)
        1    0.000    0.000    0.000    0.000 groupby.py:2450(_int64_overflow_possible)
        1    0.001    0.001    0.781    0.781 groupby.py:2473(_indexer_from_factorized)
        1    0.016    0.016    1.302    1.302 groupby.py:2497(_lexsort_indexer)
        1    0.000    0.000    0.658    0.658 groupby.py:2567(_compress_group_index)
        1    0.004    0.004    0.337    0.337 groupby.py:2587(_reorder_by_uniques)
        3    0.000    0.000    0.000    0.000 index.py:1261(delete)
        1    0.000    0.000    0.000    0.000 index.py:1291(drop)
      503    0.002    0.000    0.005    0.000 index.py:1341(__new__)
      520    0.000    0.000    0.001    0.000 index.py:135(__array_finalize__)
        5    0.000    0.000    0.000    0.000 index.py:1382(is_all_dates)
        2    0.000    0.000    0.000    0.000 index.py:1430(__new__)
     1000    0.001    0.000    0.001    0.000 index.py:1473(__array_finalize__)
      502    0.000    0.000    0.000    0.000 index.py:1509(__len__)
        1    0.000    0.000    0.000    0.000 index.py:1519(inferred_type)
     1497    0.006    0.000    0.010    0.000 index.py:1533(_get_level_number)
        1    0.000    0.000    0.007    0.007 index.py:1730(lexsort_depth)
        1    0.000    0.000    0.310    0.310 index.py:1745(from_arrays)
        1    0.000    0.000    0.000    0.000 index.py:180(_assert_can_do_setop)
     1500    0.001    0.000    0.001    0.000 index.py:1808(nlevels)
      998    0.008    0.000    0.019    0.000 index.py:1843(__getitem__)
        1    0.000    0.000    0.037    0.037 index.py:1872(take)
        6    0.000    0.000    0.000    0.000 index.py:189(dtype)
      499    0.003    0.000    0.035    0.000 index.py:1957(droplevel)
      998    0.001    0.000    0.004    0.000 index.py:1982(<genexpr>)
        1    0.000    0.000    0.000    0.000 index.py:199(_get_names)
        1    0.000    0.000    0.000    0.000 index.py:202(_set_names)
      499    0.002    0.000    0.072    0.000 index.py:2287(get_loc_level)
      499    0.003    0.000    0.052    0.000 index.py:2299(_drop_levels)
       36    0.000    0.000    0.000    0.000 index.py:236(values)
      499    0.002    0.000    0.014    0.000 index.py:2385(_get_level_indexer)
        2    0.000    0.000    0.000    0.000 index.py:240(is_monotonic)
        9    0.000    0.000    0.000    0.000 index.py:247(is_unique)
        1    0.000    0.000    0.000    0.000 index.py:266(_cleanup)
     1546    0.001    0.000    0.002    0.000 index.py:2665(_ensure_index)
       13    0.000    0.000    0.000    0.000 index.py:269(_engine)
       14    0.000    0.000    0.000    0.000 index.py:272(<lambda>)
        2    0.000    0.000    0.000    0.000 index.py:282(inferred_type)
        4    0.000    0.000    0.000    0.000 index.py:293(__iter__)
       24    0.000    0.000    0.000    0.000 index.py:318(__contains__)
        8    0.000    0.000    0.000    0.000 index.py:332(__getitem__)
        2    0.000    0.000    0.000    0.000 index.py:347(append)
        2    0.000    0.000    0.000    0.000 index.py:378(_ensure_compat_concat)
      500    0.003    0.000    0.025    0.000 index.py:390(take)
        2    0.000    0.000    0.000    0.000 index.py:450(equals)
        1    0.000    0.000    0.000    0.000 index.py:622(_wrap_union_result)
        1    0.000    0.000    0.000    0.000 index.py:626(intersection)
      513    0.001    0.000    0.001    0.000 index.py:708(get_loc)
        3    0.000    0.000    0.000    0.000 index.py:770(get_indexer)
        3    0.000    0.000    0.000    0.000 index.py:847(_possibly_promote)
       19    0.000    0.000    0.001    0.000 index.py:86(__new__)
        3    0.000    0.000    0.000    0.000 index.py:860(isin)
        3    0.000    0.000    0.000    0.000 index.py:876(_array_values)
        3    0.000    0.000    0.000    0.000 index.py:879(_get_method)
        1    0.000    0.000    0.000    0.000 index.py:889(reindex)
      499    0.001    0.000    0.002    0.000 indexing.py:1077(_is_list_like)
        1    0.000    0.000    0.000    0.000 indexing.py:32(__init__)
      499    0.001    0.000    0.128    0.000 indexing.py:51(_get_label)
      499    0.001    0.000    0.136    0.000 indexing.py:695(__getitem__)
      499    0.001    0.000    0.135    0.000 indexing.py:771(_getitem_axis)
      504    0.002    0.000    0.005    0.000 indexing.py:910(_convert_to_index_sliceable)
      499    0.001    0.000    0.003    0.000 indexing.py:938(_is_index_slice)
      998    0.001    0.000    0.002    0.000 indexing.py:939(_is_valid_index)
      998    0.001    0.000    0.002    0.000 indexing.py:943(_crit)
      500    0.000    0.000    0.000    0.000 internals.py:1016(ndim)
        9    0.000    0.000    0.000    0.000 internals.py:102(__contains__)
      502    0.001    0.000    0.002    0.000 internals.py:1020(set_axis)
        8    0.000    0.000    0.000    0.000 internals.py:105(__len__)
        6    0.000    0.000    0.000    0.000 internals.py:1072(_set_ref_locs)
      553    0.000    0.000    0.000    0.000 internals.py:1177(_get_items)
        5    0.000    0.000    0.000    0.000 internals.py:1227(shape)
       15    0.000    0.000    0.000    0.000 internals.py:1229(<genexpr>)
        5    0.000    0.000    0.000    0.000 internals.py:1231(_verify_integrity)
       12    0.000    0.000    0.000    0.000 internals.py:1233(<genexpr>)
      513    0.000    0.000    0.000    0.000 internals.py:128(dtype)
        2    0.000    0.000    0.031    0.016 internals.py:132(copy)
     1505    0.001    0.000    0.001    0.000 internals.py:1350(is_consolidated)
      506    0.002    0.000    0.002    0.000 internals.py:1358(_consolidate_check)
        1    0.000    0.000    0.000    0.000 internals.py:1363(is_mixed_type)
      499    0.002    0.000    0.024    0.000 internals.py:1431(get_slice)
      499    0.004    0.000    0.007    0.000 internals.py:1459(_slice_blocks)
        1    0.000    0.000    0.046    0.046 internals.py:147(reindex_axis)
        1    0.000    0.000    0.031    0.031 internals.py:1487(copy)
        1    0.000    0.000    0.000    0.000 internals.py:1505(as_matrix)
     1000    0.001    0.000    0.001    0.000 internals.py:1626(consolidate)
      503    0.000    0.000    0.001    0.000 internals.py:1640(_consolidate_inplace)
        5    0.000    0.000    0.000    0.000 internals.py:1653(get)
        2    0.000    0.000    0.001    0.000 internals.py:1704(delete)
        5    0.000    0.000    0.000    0.000 internals.py:181(get)
        2    0.000    0.000    0.000    0.000 internals.py:1816(set_items_norename)
        2    0.000    0.000    0.000    0.000 internals.py:1823(_delete_from_all_blocks)
        2    0.000    0.000    0.000    0.000 internals.py:1841(_delete_from_block)
        7    0.000    0.000    0.000    0.000 internals.py:1934(_find_block)
        7    0.000    0.000    0.000    0.000 internals.py:1940(_check_have)
        1    0.000    0.000    0.000    0.000 internals.py:1971(reindex_indexer)
        1    0.000    0.000    0.000    0.000 internals.py:1987(_reindex_indexer_items)
        1    0.000    0.000    0.000    0.000 internals.py:2108(_maybe_rename_join)
        1    0.000    0.000    0.000    0.000 internals.py:2219(create_block_manager_from_blocks)
        2    0.000    0.000    0.001    0.000 internals.py:2236(create_block_manager_from_arrays)
        2    0.000    0.000    0.001    0.000 internals.py:2254(form_blocks)
        1    0.000    0.000    0.000    0.000 internals.py:2338(_simple_blockify)
        2    0.000    0.000    0.000    0.000 internals.py:2351(_multi_blockify)
        3    0.000    0.000    0.000    0.000 internals.py:2355(<lambda>)
        3    0.000    0.000    0.000    0.000 internals.py:2368(_stack_arrays)
        4    0.000    0.000    0.000    0.000 internals.py:2372(_asarray_compat)
        3    0.000    0.000    0.000    0.000 internals.py:2379(_shape_compat)
        4    0.000    0.000    0.000    0.000 internals.py:2531(_possibly_convert_to_indexer)
      509    0.001    0.000    0.001    0.000 internals.py:37(__init__)
        3    0.000    0.000    0.000    0.000 internals.py:688(__init__)
      509    0.000    0.000    0.000    0.000 internals.py:76(set_ref_locs)
        2    0.000    0.000    0.000    0.000 internals.py:83(set_ref_items)
      509    0.001    0.000    0.017    0.000 internals.py:932(make_block)
      505    0.002    0.000    0.005    0.000 internals.py:989(__init__)
        2    0.000    0.000    0.000    0.000 merge.py:1195(_concat_indexes)
        1    0.000    0.000    0.000    0.000 merge.py:1299(_should_fill)
        2    0.000    0.000    0.000    0.000 merge.py:1305(_any)
        1    0.000    0.000    0.001    0.001 merge.py:157(__init__)
        1    0.000    0.000    0.197    0.197 merge.py:182(get_result)
        1    0.004    0.004    0.017    0.017 merge.py:201(_maybe_add_join_keys)
        1    0.000    0.000    0.083    0.083 merge.py:244(_get_join_info)
        1    0.000    0.000    0.000    0.000 merge.py:274(_get_merge_data)
        1    0.001    0.001    0.199    0.199 merge.py:28(merge)
        1    0.000    0.000    0.001    0.001 merge.py:284(_get_merge_keys)
        1    0.000    0.000    0.000    0.000 merge.py:307(<lambda>)
        1    0.000    0.000    0.000    0.000 merge.py:308(<lambda>)
        1    0.000    0.000    0.000    0.000 merge.py:371(_validate_specification)
        1    0.000    0.000    0.077    0.077 merge.py:420(_get_join_indexers)
        2    0.000    0.000    0.000    0.000 merge.py:578(_factorize_keys)
        1    0.000    0.000    0.000    0.000 merge.py:641(__init__)
        1    0.000    0.000    0.014    0.014 merge.py:664(_prepare_blocks)
        1    0.000    0.000    0.098    0.098 merge.py:676(get_result)
        6    0.000    0.000    0.000    0.000 merge.py:692(<genexpr>)
        2    0.000    0.000    0.083    0.042 merge.py:698(_get_merged_block)
        1    0.000    0.000    0.037    0.037 merge.py:706(_merge_blocks)
        3    0.000    0.000    0.000    0.000 merge.py:717(<genexpr>)
        2    0.000    0.000    0.000    0.000 merge.py:740(__init__)
        2    0.009    0.005    0.014    0.007 merge.py:744(mask_info)
        2    0.000    0.000    0.014    0.007 merge.py:753(get_upcasted_blocks)
        1    0.000    0.000    0.046    0.046 merge.py:759(reindex_block)
        2    0.000    0.000    0.000    0.000 merge.py:769(_may_need_upcasting)
        1    0.000    0.000    0.000    0.000 merge.py:803(_get_merge_block_kinds)
        1    0.000    0.000    0.000    0.000 merge.py:810(_get_block_dtype)
     1507    0.002    0.000    0.003    0.000 numeric.py:1666(isscalar)
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       75    0.000    0.000    0.000    0.000 numeric.py:252(asarray)
        4    0.000    0.000    0.000    0.000 series.py:1297(values)
        4    0.000    0.000    0.001    0.000 series.py:3299(_sanitize_array)
        2    0.000    0.000    0.000    0.000 series.py:3310(_try_cast)
        5    0.000    0.000    0.000    0.000 series.py:501(from_array)
        5    0.000    0.000    0.000    0.000 series.py:532(__array_finalize__)
        1    0.018    0.018    2.079    2.079 testDatesPerformance.py:6(testPerformance)
        4    0.000    0.000    0.000    0.000 {any}
     2517    0.001    0.000    0.001    0.000 {getattr}
       11    0.000    0.000    0.000    0.000 {hasattr}
       24    0.000    0.000    0.000    0.000 {hash}
    19344    0.006    0.000    0.006    0.000 {isinstance}
     1159    0.000    0.000    0.000    0.000 {issubclass}
      503    0.000    0.000    0.000    0.000 {iter}
8704/8193    0.002    0.000    0.002    0.000 {len}
        2    0.000    0.000    0.000    0.000 {max}
        1    0.000    0.000    0.000    0.000 {method 'all' of 'numpy.ndarray' objects}
       11    0.000    0.000    0.011    0.001 {method 'any' of 'numpy.ndarray' objects}
      539    0.000    0.000    0.000    0.000 {method 'append' of 'list' objects}
        4    0.148    0.037    0.148    0.037 {method 'argsort' of 'numpy.ndarray' objects}
        2    0.064    0.032    0.064    0.032 {method 'astype' of 'numpy.ndarray' objects}
      500    0.000    0.000    0.000    0.000 {method 'clear' of 'dict' objects}
        1    0.000    0.000    0.000    0.000 {method 'clear_mapping' of 'pandas.index.IndexEngine' objects}
        3    0.031    0.010    0.031    0.010 {method 'copy' of 'numpy.ndarray' objects}
     1497    0.001    0.000    0.001    0.000 {method 'count' of 'list' objects}
        1    0.000    0.000    0.000    0.000 {method 'disable' of '_lsprof.Profiler' objects}
        6    0.000    0.000    0.000    0.000 {method 'extend' of 'list' objects}
        2    0.440    0.220    0.440    0.220 {method 'factorize' of 'pandas.hashtable.Factorizer' objects}
        4    0.000    0.000    0.000    0.000 {method 'factorize' of 'pandas.hashtable.Int64Factorizer' objects}
        2    0.000    0.000    0.000    0.000 {method 'fill' of 'numpy.ndarray' objects}
        2    0.000    0.000    0.000    0.000 {method 'flatten' of 'numpy.ndarray' objects}
     1512    0.000    0.000    0.000    0.000 {method 'get' of 'dict' objects}
        2    0.000    0.000    0.000    0.000 {method 'get_count' of 'pandas.hashtable.Int64Factorizer' objects}
        3    0.000    0.000    0.000    0.000 {method 'get_indexer' of 'pandas.index.IndexEngine' objects}
        1    0.062    0.062    0.062    0.062 {method 'get_labels' of 'pandas.hashtable.Int64HashTable' objects}
        1    0.190    0.190    0.190    0.190 {method 'get_labels' of 'pandas.hashtable.PyObjectHashTable' objects}
        1    0.320    0.320    0.320    0.320 {method 'get_labels_groupby' of 'pandas.hashtable.Int64HashTable' objects}
      513    0.001    0.000    0.001    0.000 {method 'get_loc' of 'pandas.index.IndexEngine' objects}
     1497    0.002    0.000    0.002    0.000 {method 'index' of 'list' objects}
        4    0.000    0.000    0.000    0.000 {method 'keys' of 'dict' objects}
        2    0.013    0.006    0.013    0.006 {method 'nonzero' of 'numpy.ndarray' objects}
     1501    0.001    0.000    0.001    0.000 {method 'pop' of 'list' objects}
        3    0.139    0.046    0.139    0.046 {method 'put' of 'numpy.ndarray' objects}
        4    0.000    0.000    0.000    0.000 {method 'ravel' of 'numpy.ndarray' objects}
       16    0.011    0.001    0.011    0.001 {method 'reduce' of 'numpy.ufunc' objects}
      998    0.004    0.000    0.004    0.000 {method 'searchsorted' of 'numpy.ndarray' objects}
        3    0.000    0.000    0.000    0.000 {method 'setdefault' of 'dict' objects}
        2    0.000    0.000    0.000    0.000 {method 'sort' of 'numpy.ndarray' objects}
        2    0.000    0.000    0.000    0.000 {method 'startswith' of 'str' objects}
      506    0.097    0.000    0.097    0.000 {method 'take' of 'numpy.ndarray' objects}
        1    0.000    0.000    0.000    0.000 {method 'to_array' of 'pandas.hashtable.Int64Vector' objects}
        1    0.000    0.000    0.000    0.000 {method 'to_array' of 'pandas.hashtable.ObjectVector' objects}
     2035    0.003    0.000    0.005    0.000 {method 'view' of 'numpy.ndarray' objects}
        1    0.000    0.000    0.000    0.000 {min}
        7    0.012    0.002    0.012    0.002 {numpy.core.multiarray.arange}
      583    0.001    0.000    0.001    0.000 {numpy.core.multiarray.array}
        4    0.000    0.000    0.000    0.000 {numpy.core.multiarray.concatenate}
     1017    0.012    0.000    0.012    0.000 {numpy.core.multiarray.empty}
        4    0.008    0.002    0.008    0.002 {numpy.core.multiarray.putmask}
        4    0.003    0.001    0.003    0.001 {numpy.core.multiarray.zeros}
       20    0.000    0.000    0.000    0.000 {pandas.algos.ensure_int64}
        1    0.000    0.000    0.000    0.000 {pandas.algos.ensure_object}
      507    0.000    0.000    0.000    0.000 {pandas.algos.ensure_platform_int}
        1    0.000    0.000    0.000    0.000 {pandas.algos.inner_join_indexer_object}
        1    0.077    0.077    0.077    0.077 {pandas.algos.inner_join}
        2    0.120    0.060    0.120    0.060 {pandas.algos.take_1d_int64_int64}
        1    0.000    0.000    0.000    0.000 {pandas.algos.take_1d_object_object}
        2    0.009    0.005    0.009    0.005 {pandas.algos.take_2d_axis0_int64_int64}
        2    0.023    0.012    0.023    0.012 {pandas.algos.take_2d_axis1_int64_int64}
        1    0.024    0.024    0.024    0.024 {pandas.algos.take_2d_axis1_object_object}
       23    0.014    0.001    0.014    0.001 {pandas.lib.infer_dtype}
        1    0.007    0.007    0.007    0.007 {pandas.lib.is_lexsorted}
        3    0.000    0.000    0.000    0.000 {pandas.lib.ismember}
        4    0.000    0.000    0.000    0.000 {pandas.lib.list_to_object_array}
        2    0.001    0.000    0.001    0.000 {pandas.lib.maybe_convert_objects}
        2    0.000    0.000    0.000    0.000 {pandas.tslib.is_timestamp_array}
      502    0.000    0.000    0.000    0.000 {range}
        1    0.000    0.000    0.000    0.000 {setattr}
     1000    0.002    0.000    0.006    0.000 {sorted}
        6    0.000    0.000    0.000    0.000 {sum}
        2    0.000    0.000    0.000    0.000 {time.time}
        9    0.000    0.000    0.000    0.000 {zip}



Process finished with exit code 0

</details>
