· 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 312ms object 16.4±0.07ms datetime 325ms ========== ============= [ 18.18%] ··· Running io.csv.ReadCSVCategorical.time_convert_direct 45.0±0.5ms [ 27.27%] ··· Running io.csv.ReadCSVCategorical.time_convert_post 59.8±0.8ms [ 36.36%] ··· Running io.csv.ReadCSVComment.time_comment 2.40±0.04ms [ 45.45%] ··· Running ...sv.ReadCSVDInferDatetimeFormat.time_read_csv ok [ 45.45%] ···· ======================= ========= ============= infer_datetime_format format ----------------------- --------- ------------- True custom 1.50±0.03ms True iso8601 1.48±0.02ms True ymd 1.43±0.03ms False custom 204±2ms False iso8601 1.43±0.03ms False ymd 1.45±0.03ms ======================= ========= ============= [ 54.55%] ··· Running io.csv.ReadCSVFloatPrecision.time_read_csv ok [ 54.55%] ···· ===== ========= ============= ============= ============= -- float_precision --------------- ----------------------------------------- sep decimal None high round_trip ===== ========= ============= ============= ============= , . 1.92±0.02ms 1.97±0.04ms 2.08±0.08ms , _ 2.12±0.04ms 2.01±0.07ms 1.94±0.02ms ; . 2.06±0.07ms 2.03±0.06ms 1.95±0.02ms ; _ 1.89±0.02ms 1.92±0.03ms 1.98±0.04ms ===== ========= ============= ============= ============= [ 63.64%] ··· Running ...SVFloatPrecision.time_read_csv_python_engine ok [ 63.64%] ···· ===== ========= ============= ============= ============= -- float_precision --------------- ----------------------------------------- sep decimal None high round_trip ===== ========= ============= ============= ============= , . 2.12±0.06ms 2.03±0.02ms 2.02±0.03ms , _ 2.02±0.1ms 2.09±0.03ms 2.07±0.03ms ; . 2.05±0.03ms 2.13±0.03ms 2.12±0.04ms ; _ 2.03±0.02ms 2.03±0.02ms 2.00±0.01ms ===== ========= ============= ============= ============= [ 72.73%] ··· Running io.csv.ReadCSVParseDates.time_baseline 3.32±0.04ms [ 81.82%] ··· Running io.csv.ReadCSVParseDates.time_multiple_date 3.41±0.09ms [ 90.91%] ··· Running io.csv.ReadCSVSkipRows.time_skipprows ok [ 90.91%] ···· ========== ============= skiprows ---------- ------------- None 23.0±0.07ms 10000 14.2±0.3ms ========== ============= [100.00%] ··· Running io.csv.ReadCSVThousands.time_thousands ok [100.00%] ···· ===== ============ ============ -- thousands ----- ------------------------- sep None , ===== ============ ============ , 22.0±0.4ms 21.7±0.2ms | 21.2±0.1ms 22.8±0.9ms ===== ============ ============