Update README.md

[NinoRisteski]

fixed a few typos

[stevhliu]

Thanks for fixing the typos and clarification!

[HuggingFaceDocBuilderDev]

The documentation is not available anymore as the PR was closed or merged.

[mariosasko]

Nice!

I took the liberty to commit the suggestions myself 🙂.

[github-actions]

Show benchmarks

PyArrow==8.0.0

Show updated benchmarks!

Benchmark: benchmark_array_xd.json

metric	read_batch_formatted_as_numpy after write_array2d	read_batch_formatted_as_numpy after write_flattened_sequence	read_batch_formatted_as_numpy after write_nested_sequence	read_batch_unformated after write_array2d	read_batch_unformated after write_flattened_sequence	read_batch_unformated after write_nested_sequence	read_col_formatted_as_numpy after write_array2d	read_col_formatted_as_numpy after write_flattened_sequence	read_col_formatted_as_numpy after write_nested_sequence	read_col_unformated after write_array2d	read_col_unformated after write_flattened_sequence	read_col_unformated after write_nested_sequence	read_formatted_as_numpy after write_array2d	read_formatted_as_numpy after write_flattened_sequence	read_formatted_as_numpy after write_nested_sequence	read_unformated after write_array2d	read_unformated after write_flattened_sequence	read_unformated after write_nested_sequence	write_array2d	write_flattened_sequence	write_nested_sequence
new / old (diff)	0.006757 / 0.011353 (-0.004596)	0.004233 / 0.011008 (-0.006775)	0.084123 / 0.038508 (0.045614)	0.077513 / 0.023109 (0.054404)	0.357024 / 0.275898 (0.081126)	0.392956 / 0.323480 (0.069476)	0.005408 / 0.007986 (-0.002577)	0.003363 / 0.004328 (-0.000966)	0.064395 / 0.004250 (0.060145)	0.054711 / 0.037052 (0.017659)	0.367287 / 0.258489 (0.108798)	0.402934 / 0.293841 (0.109093)	0.031845 / 0.128546 (-0.096701)	0.008646 / 0.075646 (-0.067000)	0.288740 / 0.419271 (-0.130531)	0.053171 / 0.043533 (0.009638)	0.360711 / 0.255139 (0.105572)	0.388707 / 0.283200 (0.105507)	0.025321 / 0.141683 (-0.116361)	1.500684 / 1.452155 (0.048529)	1.585747 / 1.492716 (0.093030)

Benchmark: benchmark_getitem_100B.json

metric	get_batch_of_1024_random_rows	get_batch_of_1024_rows	get_first_row	get_last_row
new / old (diff)	0.207329 / 0.018006 (0.189323)	0.465304 / 0.000490 (0.464814)	0.003229 / 0.000200 (0.003029)	0.000080 / 0.000054 (0.000025)

Benchmark: benchmark_indices_mapping.json

metric	select	shard	shuffle	sort	train_test_split
new / old (diff)	0.028752 / 0.037411 (-0.008659)	0.085327 / 0.014526 (0.070802)	0.332210 / 0.176557 (0.155653)	0.178779 / 0.737135 (-0.558356)	0.097765 / 0.296338 (-0.198573)

Benchmark: benchmark_iterating.json

metric	read 5000	read 50000	read_batch 50000 10	read_batch 50000 100	read_batch 50000 1000	read_formatted numpy 5000	read_formatted pandas 5000	read_formatted tensorflow 5000	read_formatted torch 5000	read_formatted_batch numpy 5000 10	read_formatted_batch numpy 5000 1000	shuffled read 5000	shuffled read 50000	shuffled read_batch 50000 10	shuffled read_batch 50000 100	shuffled read_batch 50000 1000	shuffled read_formatted numpy 5000	shuffled read_formatted_batch numpy 5000 10	shuffled read_formatted_batch numpy 5000 1000
new / old (diff)	0.403710 / 0.215209 (0.188501)	4.027069 / 2.077655 (1.949414)	2.053451 / 1.504120 (0.549331)	1.906647 / 1.541195 (0.365452)	1.992507 / 1.468490 (0.524017)	0.490203 / 4.584777 (-4.094574)	3.696569 / 3.745712 (-0.049143)	3.319919 / 5.269862 (-1.949943)	2.072794 / 4.565676 (-2.492883)	0.057893 / 0.424275 (-0.366383)	0.007723 / 0.007607 (0.000116)	0.485400 / 0.226044 (0.259355)	4.842891 / 2.268929 (2.573963)	2.578949 / 55.444624 (-52.865675)	2.229217 / 6.876477 (-4.647259)	2.468017 / 2.142072 (0.325945)	0.595236 / 4.805227 (-4.209992)	0.135641 / 6.500664 (-6.365023)	0.061232 / 0.075469 (-0.014237)

Benchmark: benchmark_map_filter.json

metric	filter	map fast-tokenizer batched	map identity	map identity batched	map no-op batched	map no-op batched numpy	map no-op batched pandas	map no-op batched pytorch	map no-op batched tensorflow
new / old (diff)	1.307059 / 1.841788 (-0.534729)	20.108581 / 8.074308 (12.034273)	14.438985 / 10.191392 (4.247593)	0.168878 / 0.680424 (-0.511545)	0.018208 / 0.534201 (-0.515993)	0.395986 / 0.579283 (-0.183297)	0.427440 / 0.434364 (-0.006924)	0.459917 / 0.540337 (-0.080421)	0.631379 / 1.386936 (-0.755557)

PyArrow==latest

Show updated benchmarks!

Benchmark: benchmark_array_xd.json

metric	read_batch_formatted_as_numpy after write_array2d	read_batch_formatted_as_numpy after write_flattened_sequence	read_batch_formatted_as_numpy after write_nested_sequence	read_batch_unformated after write_array2d	read_batch_unformated after write_flattened_sequence	read_batch_unformated after write_nested_sequence	read_col_formatted_as_numpy after write_array2d	read_col_formatted_as_numpy after write_flattened_sequence	read_col_formatted_as_numpy after write_nested_sequence	read_col_unformated after write_array2d	read_col_unformated after write_flattened_sequence	read_col_unformated after write_nested_sequence	read_formatted_as_numpy after write_array2d	read_formatted_as_numpy after write_flattened_sequence	read_formatted_as_numpy after write_nested_sequence	read_unformated after write_array2d	read_unformated after write_flattened_sequence	read_unformated after write_nested_sequence	write_array2d	write_flattened_sequence	write_nested_sequence
new / old (diff)	0.007002 / 0.011353 (-0.004351)	0.004120 / 0.011008 (-0.006888)	0.064817 / 0.038508 (0.026309)	0.081297 / 0.023109 (0.058188)	0.405598 / 0.275898 (0.129700)	0.442360 / 0.323480 (0.118880)	0.005475 / 0.007986 (-0.002511)	0.003483 / 0.004328 (-0.000845)	0.064750 / 0.004250 (0.060499)	0.058111 / 0.037052 (0.021059)	0.410154 / 0.258489 (0.151665)	0.445137 / 0.293841 (0.151296)	0.033314 / 0.128546 (-0.095232)	0.008747 / 0.075646 (-0.066899)	0.071595 / 0.419271 (-0.347676)	0.048894 / 0.043533 (0.005361)	0.409162 / 0.255139 (0.154023)	0.428877 / 0.283200 (0.145677)	0.024127 / 0.141683 (-0.117556)	1.521369 / 1.452155 (0.069214)	1.573505 / 1.492716 (0.080789)

Benchmark: benchmark_getitem_100B.json

metric	get_batch_of_1024_random_rows	get_batch_of_1024_rows	get_first_row	get_last_row
new / old (diff)	0.233199 / 0.018006 (0.215193)	0.455619 / 0.000490 (0.455129)	0.003688 / 0.000200 (0.003488)	0.000081 / 0.000054 (0.000027)

Benchmark: benchmark_indices_mapping.json

metric	select	shard	shuffle	sort	train_test_split
new / old (diff)	0.033186 / 0.037411 (-0.004225)	0.100528 / 0.014526 (0.086003)	0.105617 / 0.176557 (-0.070940)	0.159437 / 0.737135 (-0.577698)	0.108064 / 0.296338 (-0.188274)

Benchmark: benchmark_iterating.json

metric	read 5000	read 50000	read_batch 50000 10	read_batch 50000 100	read_batch 50000 1000	read_formatted numpy 5000	read_formatted pandas 5000	read_formatted tensorflow 5000	read_formatted torch 5000	read_formatted_batch numpy 5000 10	read_formatted_batch numpy 5000 1000	shuffled read 5000	shuffled read 50000	shuffled read_batch 50000 10	shuffled read_batch 50000 100	shuffled read_batch 50000 1000	shuffled read_formatted numpy 5000	shuffled read_formatted_batch numpy 5000 10	shuffled read_formatted_batch numpy 5000 1000
new / old (diff)	0.435509 / 0.215209 (0.220300)	4.339920 / 2.077655 (2.262265)	2.368983 / 1.504120 (0.864863)	2.211761 / 1.541195 (0.670566)	2.301701 / 1.468490 (0.833211)	0.495144 / 4.584777 (-4.089633)	3.768882 / 3.745712 (0.023170)	3.348940 / 5.269862 (-1.920922)	2.081142 / 4.565676 (-2.484534)	0.058184 / 0.424275 (-0.366091)	0.007597 / 0.007607 (-0.000010)	0.508806 / 0.226044 (0.282762)	5.089226 / 2.268929 (2.820297)	2.851930 / 55.444624 (-52.592694)	2.512144 / 6.876477 (-4.364332)	2.724461 / 2.142072 (0.582388)	0.593446 / 4.805227 (-4.211781)	0.134908 / 6.500664 (-6.365756)	0.060811 / 0.075469 (-0.014658)

Benchmark: benchmark_map_filter.json

metric	filter	map fast-tokenizer batched	map identity	map identity batched	map no-op batched	map no-op batched numpy	map no-op batched pandas	map no-op batched pytorch	map no-op batched tensorflow
new / old (diff)	1.362279 / 1.841788 (-0.479508)	20.548216 / 8.074308 (12.473908)	15.179181 / 10.191392 (4.987789)	0.170249 / 0.680424 (-0.510175)	0.020772 / 0.534201 (-0.513429)	0.398737 / 0.579283 (-0.180546)	0.441487 / 0.434364 (0.007124)	0.480096 / 0.540337 (-0.060242)	0.645825 / 1.386936 (-0.741111)