chore: fix typos in docs

[hattizai]

No description provided.

[albertvillanova]

Thanks for the fixes.

[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)	0.005319 / 0.011353 (-0.006034)	0.003979 / 0.011008 (-0.007030)	0.063858 / 0.038508 (0.025350)	0.031064 / 0.023109 (0.007955)	0.232761 / 0.275898 (-0.043137)	0.260362 / 0.323480 (-0.063118)	0.004271 / 0.007986 (-0.003715)	0.002801 / 0.004328 (-0.001527)	0.049471 / 0.004250 (0.045220)	0.043432 / 0.037052 (0.006379)	0.247467 / 0.258489 (-0.011022)	0.271926 / 0.293841 (-0.021915)	0.030063 / 0.128546 (-0.098483)	0.012659 / 0.075646 (-0.062988)	0.204650 / 0.419271 (-0.214622)	0.036340 / 0.043533 (-0.007192)	0.237480 / 0.255139 (-0.017659)	0.255955 / 0.283200 (-0.027244)	0.017922 / 0.141683 (-0.123761)	1.152251 / 1.452155 (-0.299904)	1.195610 / 1.492716 (-0.297106)

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)	0.095411 / 0.018006 (0.077405)	0.296836 / 0.000490 (0.296346)	0.000226 / 0.000200 (0.000026)	0.000054 / 0.000054 (-0.000001)

Benchmark: benchmark_indices_mapping.json

metric	select	shard	shuffle	sort	train_test_split
new / old (diff)	0.018547 / 0.037411 (-0.018865)	0.063423 / 0.014526 (0.048897)	0.073587 / 0.176557 (-0.102970)	0.120327 / 0.737135 (-0.616808)	0.076185 / 0.296338 (-0.220154)

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)	0.282815 / 0.215209 (0.067606)	2.781204 / 2.077655 (0.703549)	1.432489 / 1.504120 (-0.071631)	1.312018 / 1.541195 (-0.229177)	1.328290 / 1.468490 (-0.140200)	0.734169 / 4.584777 (-3.850608)	2.380654 / 3.745712 (-1.365058)	2.904945 / 5.269862 (-2.364916)	1.872079 / 4.565676 (-2.693598)	0.078329 / 0.424275 (-0.345946)	0.005151 / 0.007607 (-0.002457)	0.338957 / 0.226044 (0.112912)	3.353638 / 2.268929 (1.084709)	1.812223 / 55.444624 (-53.632401)	1.514860 / 6.876477 (-5.361617)	1.528539 / 2.142072 (-0.613533)	0.798711 / 4.805227 (-4.006516)	0.135129 / 6.500664 (-6.365535)	0.042355 / 0.075469 (-0.033114)

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)	0.954665 / 1.841788 (-0.887122)	11.431925 / 8.074308 (3.357617)	9.652583 / 10.191392 (-0.538809)	0.132538 / 0.680424 (-0.547886)	0.015517 / 0.534201 (-0.518683)	0.303826 / 0.579283 (-0.275457)	0.267530 / 0.434364 (-0.166834)	0.340775 / 0.540337 (-0.199562)	0.429909 / 1.386936 (-0.957027)

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)	0.005819 / 0.011353 (-0.005533)	0.003829 / 0.011008 (-0.007179)	0.049707 / 0.038508 (0.011199)	0.030810 / 0.023109 (0.007701)	0.269637 / 0.275898 (-0.006261)	0.295857 / 0.323480 (-0.027623)	0.004462 / 0.007986 (-0.003523)	0.002823 / 0.004328 (-0.001505)	0.048544 / 0.004250 (0.044294)	0.039692 / 0.037052 (0.002639)	0.286837 / 0.258489 (0.028348)	0.319874 / 0.293841 (0.026034)	0.033319 / 0.128546 (-0.095227)	0.012318 / 0.075646 (-0.063329)	0.060319 / 0.419271 (-0.358953)	0.034341 / 0.043533 (-0.009192)	0.271132 / 0.255139 (0.015993)	0.292577 / 0.283200 (0.009377)	0.018298 / 0.141683 (-0.123384)	1.136871 / 1.452155 (-0.315284)	1.192894 / 1.492716 (-0.299822)

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)	0.098890 / 0.018006 (0.080884)	0.307830 / 0.000490 (0.307341)	0.000214 / 0.000200 (0.000014)	0.000044 / 0.000054 (-0.000010)

Benchmark: benchmark_indices_mapping.json

metric	select	shard	shuffle	sort	train_test_split
new / old (diff)	0.023066 / 0.037411 (-0.014346)	0.076732 / 0.014526 (0.062206)	0.088154 / 0.176557 (-0.088403)	0.129849 / 0.737135 (-0.607286)	0.089368 / 0.296338 (-0.206970)

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)	0.298298 / 0.215209 (0.083089)	2.914801 / 2.077655 (0.837147)	1.609280 / 1.504120 (0.105160)	1.486971 / 1.541195 (-0.054223)	1.496254 / 1.468490 (0.027764)	0.723780 / 4.584777 (-3.860997)	0.972436 / 3.745712 (-2.773276)	2.993773 / 5.269862 (-2.276089)	1.911170 / 4.565676 (-2.654506)	0.080599 / 0.424275 (-0.343677)	0.005713 / 0.007607 (-0.001894)	0.350510 / 0.226044 (0.124465)	3.464035 / 2.268929 (1.195107)	2.001558 / 55.444624 (-53.443066)	1.691888 / 6.876477 (-5.184589)	1.732348 / 2.142072 (-0.409724)	0.818572 / 4.805227 (-3.986655)	0.136770 / 6.500664 (-6.363894)	0.041722 / 0.075469 (-0.033748)

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)	1.021225 / 1.841788 (-0.820563)	11.941224 / 8.074308 (3.866915)	10.118500 / 10.191392 (-0.072892)	0.146167 / 0.680424 (-0.534257)	0.015700 / 0.534201 (-0.518501)	0.301511 / 0.579283 (-0.277772)	0.122716 / 0.434364 (-0.311648)	0.349048 / 0.540337 (-0.191290)	0.444940 / 1.386936 (-0.941996)