· Creating environments · Discovering benchmarks ·· Uninstalling from conda-py3.6-Cython-matplotlib-numexpr-numpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt ·· Installing into conda-py3.6-Cython-matplotlib-numexpr-numpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt · Running 11 total benchmarks (1 commits * 1 environments * 11 benchmarks) [ 0.00%] · For pandas commit hash 7829ad32: [ 0.00%] ·· Building for conda-py3.6-Cython-matplotlib-numexpr-numpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt [ 0.00%] ·· Benchmarking conda-py3.6-Cython-matplotlib-numexpr-numpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt [ 9.09%] ··· Running gil.ParallelReadCSV.time_read_csv ok [ 9.09%] ···· ========== ============ dtype ---------- ------------ float 323ms object 16.2±0.2ms datetime 316ms ========== ============ [ 18.18%] ··· Running io.csv.ReadCSVCategorical.time_convert_direct 43.9±0.5ms [ 27.27%] ··· Running io.csv.ReadCSVCategorical.time_convert_post 62.4±0.9ms [ 36.36%] ··· Running io.csv.ReadCSVComment.time_comment 24.7±0.1ms [ 45.45%] ··· Running ...sv.ReadCSVDInferDatetimeFormat.time_read_csv ok [ 45.45%] ···· ======================= ========= ============= infer_datetime_format format ----------------------- --------- ------------- True custom 7.20±0.3ms True iso8601 2.63±0.02ms True ymd 2.62±0.04ms False custom 210±3ms False iso8601 2.28±0.08ms False ymd 2.04±0.01ms ======================= ========= ============= [ 54.55%] ··· Running io.csv.ReadCSVFloatPrecision.time_read_csv ok [ 54.55%] ···· ===== ========= ============= ============= ============= -- float_precision --------------- ----------------------------------------- sep decimal None high round_trip ===== ========= ============= ============= ============= , . 2.28±0.03ms 2.18±0.01ms 2.95±0.02ms , _ 2.18±0.02ms 2.25±0.01ms 2.33±0.1ms ; . 2.36±0.04ms 2.18±0.02ms 2.95±0.03ms ; _ 2.18±0.03ms 2.18±0.03ms 2.21±0.04ms ===== ========= ============= ============= ============= [ 63.64%] ··· Running ...SVFloatPrecision.time_read_csv_python_engine ok [ 63.64%] ···· ===== ========= ============= ============= ============= -- float_precision --------------- ----------------------------------------- sep decimal None high round_trip ===== ========= ============= ============= ============= , . 4.97±0.02ms 5.09±0.3ms 5.07±0.07ms , _ 4.14±0.04ms 4.06±0.03ms 4.05±0.05ms ; . 5.03±0.06ms 4.92±0.01ms 4.98±0.02ms ; _ 4.08±0.03ms 4.22±0.07ms 4.08±0.05ms ===== ========= ============= ============= ============= [ 72.73%] ··· Running io.csv.ReadCSVParseDates.time_baseline 1.84±0.01ms [ 81.82%] ··· Running io.csv.ReadCSVParseDates.time_multiple_date 2.17±0.02ms [ 90.91%] ··· Running io.csv.ReadCSVSkipRows.time_skipprows ok [ 90.91%] ···· ========== ============= skiprows ---------- ------------- None 23.3±0.2ms 10000 14.3±0.07ms ========== ============= [100.00%] ··· Running io.csv.ReadCSVThousands.time_thousands ok [100.00%] ···· ===== ============ ============ -- thousands ----- ------------------------- sep None , ===== ============ ============ , 22.0±0.4ms 22.7±1ms | 21.6±0.2ms 22.3±0.1ms ===== ============ ============