Benchmarks
Date Language Batch Benchmark Mean Z-Score
2021-10-05 23:26 Python csv-read uncompressed, streaming, fanniemae_2016Q4 14.937 s -0.283445
2021-10-05 23:31 Python dataframe-to-table type_integers 0.011 s 0.205666
2021-10-05 23:31 Python dataframe-to-table type_nested 2.895 s 0.608492
2021-10-05 23:26 Python csv-read uncompressed, file, fanniemae_2016Q4 1.159 s 0.827479
2021-10-05 23:31 Python dataframe-to-table chi_traffic_2020_Q1 19.445 s 1.209105
2021-10-05 23:31 Python dataframe-to-table type_floats 0.012 s -1.534612
2021-10-05 23:27 Python csv-read gzip, streaming, fanniemae_2016Q4 14.880 s -0.309975
2021-10-05 23:32 Python dataset-filter nyctaxi_2010-01 4.371 s -0.147647
2021-10-05 23:29 Python csv-read gzip, file, nyctaxi_2010-01 9.041 s 1.274007
2021-10-05 23:31 Python dataframe-to-table type_dict 0.011 s 1.683843
2021-10-05 23:29 Python csv-read gzip, streaming, nyctaxi_2010-01 10.511 s 1.365244
2021-10-05 23:32 Python dataframe-to-table type_simple_features 0.912 s 0.084432
2021-10-05 23:28 Python csv-read gzip, file, fanniemae_2016Q4 6.036 s -1.235119
2021-10-05 23:28 Python csv-read uncompressed, streaming, nyctaxi_2010-01 10.503 s 1.480676
2021-10-05 23:28 Python csv-read uncompressed, file, nyctaxi_2010-01 1.013 s 0.021938
2021-10-05 23:31 Python dataframe-to-table type_strings 0.372 s 0.014734