Issue: Updated Quickstart Notebook link
State: closed
Author: Codeblockz

Fixed Quickstart Notebook Link in the [Overview notebook](https://github.com/huggingface/datasets/blob/main/notebooks/Overview.ipynb)

Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6685). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.

<details>
<summary>Show benchmarks</summary>

PyArrow==8.0.0

<details>
<summary>Show updated benchmarks!</summary>

### 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) | 0.005386 / 0.011353 (-0.005967) | 0.003707 / 0.011008 (-0.007301) | 0.062661 / 0.038508 (0.024153) | 0.029058 / 0.023109 (0.005949) | 0.249669 / 0.275898 (-0.026230) | 0.280996 / 0.323480 (-0.042484) | 0.004041 / 0.007986 (-0.003945) | 0.002713 / 0.004328 (-0.001616) | 0.047914 / 0.004250 (0.043664) | 0.042014 / 0.037052 (0.004961) | 0.265209 / 0.258489 (0.006720) | 0.297320 / 0.293841 (0.003479) | 0.028323 / 0.128546 (-0.100223) | 0.010844 / 0.075646 (-0.064802) | 0.205895 / 0.419271 (-0.213377) | 0.035997 / 0.043533 (-0.007536) | 0.245069 / 0.255139 (-0.010070) | 0.266159 / 0.283200 (-0.017040) | 0.017590 / 0.141683 (-0.124093) | 1.132046 / 1.452155 (-0.320109) | 1.177496 / 1.492716 (-0.315220) |

### 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) | 0.105441 / 0.018006 (0.087435) | 0.301321 / 0.000490 (0.300831) | 0.000211 / 0.000200 (0.000011) | 0.000064 / 0.000054 (0.000010) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.018687 / 0.037411 (-0.018724) | 0.061221 / 0.014526 (0.046695) | 0.072556 / 0.176557 (-0.104001) | 0.119641 / 0.737135 (-0.617495) | 0.073781 / 0.296338 (-0.222557) |

### 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) | 0.284564 / 0.215209 (0.069354) | 2.795786 / 2.077655 (0.718131) | 1.437059 / 1.504120 (-0.067061) | 1.309319 / 1.541195 (-0.231876) | 1.315849 / 1.468490 (-0.152641) | 0.578571 / 4.584777 (-4.006206) | 2.350754 / 3.745712 (-1.394958) | 2.758499 / 5.269862 (-2.511362) | 1.705545 / 4.565676 (-2.860131) | 0.063660 / 0.424275 (-0.360615) | 0.005506 / 0.007607 (-0.002101) | 0.334915 / 0.226044 (0.108871) | 3.295922 / 2.268929 (1.026994) | 1.796513 / 55.444624 (-53.648111) | 1.488113 / 6.876477 (-5.388364) | 1.523042 / 2.142072 (-0.619031) | 0.648169 / 4.805227 (-4.157058) | 0.119321 / 6.500664 (-6.381343) | 0.041932 / 0.075469 (-0.033537) |

### 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) | 0.982432 / 1.841788 (-0.859356) | 11.344780 / 8.074308 (3.270472) | 9.627219 / 10.191392 (-0.564173) | 0.142590 / 0.680424 (-0.537834) | 0.013899 / 0.534201 (-0.520302) | 0.286335 / 0.579283 (-0.292948) | 0.266552 / 0.434364 (-0.167812) | 0.320361 / 0.540337 (-0.219977) | 0.420303 / 1.386936 (-0.966633) |

</details>
PyArrow==latest

<details>
<summary>Show updated benchmarks!</summary>

### 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) | 0.005251 / 0.011353 (-0.006102) | 0.003515 / 0.011008 (-0.007494) | 0.049344 / 0.038508 (0.010836) | 0.032055 / 0.023109 (0.008945) | 0.280653 / 0.275898 (0.004755) | 0.303989 / 0.323480 (-0.019491) | 0.004402 / 0.007986 (-0.003584) | 0.002758 / 0.004328 (-0.001570) | 0.050947 / 0.004250 (0.046697) | 0.044405 / 0.037052 (0.007353) | 0.292856 / 0.258489 (0.034367) | 0.325307 / 0.293841 (0.031466) | 0.047720 / 0.128546 (-0.080827) | 0.010589 / 0.075646 (-0.065057) | 0.057728 / 0.419271 (-0.361543) | 0.033842 / 0.043533 (-0.009691) | 0.285443 / 0.255139 (0.030304) | 0.300013 / 0.283200 (0.016814) | 0.017444 / 0.141683 (-0.124238) | 1.152880 / 1.452155 (-0.299275) | 1.200670 / 1.492716 (-0.292046) |

### 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) | 0.092355 / 0.018006 (0.074349) | 0.307907 / 0.000490 (0.307418) | 0.000226 / 0.000200 (0.000026) | 0.000053 / 0.000054 (-0.000001) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.021624 / 0.037411 (-0.015787) | 0.075855 / 0.014526 (0.061329) | 0.087109 / 0.176557 (-0.089447) | 0.124859 / 0.737135 (-0.612276) | 0.088933 / 0.296338 (-0.207406) |

### 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) | 0.294213 / 0.215209 (0.079004) | 2.893146 / 2.077655 (0.815491) | 1.595061 / 1.504120 (0.090942) | 1.480959 / 1.541195 (-0.060236) | 1.528277 / 1.468490 (0.059787) | 0.570273 / 4.584777 (-4.014504) | 2.412948 / 3.745712 (-1.332764) | 2.675009 / 5.269862 (-2.594852) | 1.724005 / 4.565676 (-2.841671) | 0.063359 / 0.424275 (-0.360916) | 0.005008 / 0.007607 (-0.002599) | 0.346570 / 0.226044 (0.120526) | 3.456566 / 2.268929 (1.187637) | 1.973109 / 55.444624 (-53.471515) | 1.657562 / 6.876477 (-5.218915) | 1.790086 / 2.142072 (-0.351986) | 0.655277 / 4.805227 (-4.149950) | 0.117985 / 6.500664 (-6.382679) | 0.041128 / 0.075469 (-0.034342) |

### 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) | 1.001428 / 1.841788 (-0.840360) | 11.953458 / 8.074308 (3.879150) | 10.188439 / 10.191392 (-0.002953) | 0.140863 / 0.680424 (-0.539561) | 0.015278 / 0.534201 (-0.518923) | 0.288193 / 0.579283 (-0.291090) | 0.281732 / 0.434364 (-0.152632) | 0.328034 / 0.540337 (-0.212304) | 0.414571 / 1.386936 (-0.972365) |

</details>
</details>

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