Improve the performance of instantiating a Series object with dictionary data and a datetimeindex · Issue #14894 · pandas-dev/pandas (original) (raw)

The current code path always results in an exception on:

which is then caught. Only a slight performance advantage is seen but hopefully the code change makes it less confusing for newcomers like me.

Code Sample, a copy-pastable example if possible

dr = pd.date_range( start=datetime(2015, 10, 26), end=datetime(2016, 1, 1), freq='10s' ) data = {d: v for d, v in zip(dr, range(len(dr)))} s = Series(data=data, index=dr)

Problem description

The current code path always results in an exception on:

which is then caught. Only a slight performance advantage is seen but hopefully the code change makes it less confusing for newcomers like me.

ASV output of new benchmark
Running 2 total benchmarks (2 commits * 1 environments * 1 benchmarks)
[ 0.00%] · For pandas commit hash 5f05fdc:
[ 0.00%] ·· Building for conda-py2.7-Cython-matplotlib-numexpr-numpy-openpyxl-pytables-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt.................................
[ 0.00%] ·· Benchmarking conda-py2.7-Cython-matplotlib-numexpr-numpy-openpyxl-pytables-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt
[ 50.00%] ··· Running ...x.time_series_constructor_no_data_datetime_index 3.26s
[ 50.00%] · For pandas commit hash 3ba2cff:
[ 50.00%] ·· Building for conda-py2.7-Cython-matplotlib-numexpr-numpy-openpyxl-pytables-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt...
[ 50.00%] ·· Benchmarking conda-py2.7-Cython-matplotlib-numexpr-numpy-openpyxl-pytables-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt
[100.00%] ··· Running ...x.time_series_constructor_no_data_datetime_index 3.77s before after ratio
[3ba2cff] [5f05fdc]

• ```

3.77s 3.26s 0.87 series_methods.series_constructor_dict_data_datetime_index.time_series_constructor_no_data_datetime_index
```