[Docs] Add description of `select_columns` to guide

Closes #6116 


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

<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) | 0.007755 / 0.011353 (-0.003598) | 0.004618 / 0.011008 (-0.006391) | 0.098132 / 0.038508 (0.059624) | 0.086759 / 0.023109 (0.063650) | 0.374668 / 0.275898 (0.098770) | 0.417131 / 0.323480 (0.093651) | 0.004604 / 0.007986 (-0.003382) | 0.005461 / 0.004328 (0.001132) | 0.077249 / 0.004250 (0.072999) | 0.063247 / 0.037052 (0.026195) | 0.391801 / 0.258489 (0.133312) | 0.432139 / 0.293841 (0.138298) | 0.036755 / 0.128546 (-0.091791) | 0.010011 / 0.075646 (-0.065636) | 0.346175 / 0.419271 (-0.073097) | 0.061503 / 0.043533 (0.017971) | 0.374063 / 0.255139 (0.118924) | 0.435873 / 0.283200 (0.152673) | 0.029476 / 0.141683 (-0.112207) | 1.786945 / 1.452155 (0.334790) | 1.857190 / 1.492716 (0.364474) |

### 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) | 0.253939 / 0.018006 (0.235933) | 0.506847 / 0.000490 (0.506358) | 0.007278 / 0.000200 (0.007079) | 0.000451 / 0.000054 (0.000397) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.032938 / 0.037411 (-0.004474) | 0.097493 / 0.014526 (0.082967) | 0.112090 / 0.176557 (-0.064467) | 0.177986 / 0.737135 (-0.559149) | 0.112060 / 0.296338 (-0.184278) |

### 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) | 0.481858 / 0.215209 (0.266649) | 4.814894 / 2.077655 (2.737239) | 2.496428 / 1.504120 (0.992308) | 2.309965 / 1.541195 (0.768770) | 2.393819 / 1.468490 (0.925329) | 0.564670 / 4.584777 (-4.020107) | 4.151222 / 3.745712 (0.405510) | 3.676115 / 5.269862 (-1.593747) | 2.346165 / 4.565676 (-2.219512) | 0.066344 / 0.424275 (-0.357931) | 0.009006 / 0.007607 (0.001399) | 0.567699 / 0.226044 (0.341654) | 5.686799 / 2.268929 (3.417871) | 3.031044 / 55.444624 (-52.413580) | 2.606259 / 6.876477 (-4.270217) | 2.864876 / 2.142072 (0.722804) | 0.681730 / 4.805227 (-4.123498) | 0.155405 / 6.500664 (-6.345259) | 0.071492 / 0.075469 (-0.003977) |

### 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) | 1.514446 / 1.841788 (-0.327341) | 22.624912 / 8.074308 (14.550604) | 16.754145 / 10.191392 (6.562753) | 0.193113 / 0.680424 (-0.487311) | 0.021808 / 0.534201 (-0.512393) | 0.468241 / 0.579283 (-0.111042) | 0.499647 / 0.434364 (0.065283) | 0.539571 / 0.540337 (-0.000766) | 0.771268 / 1.386936 (-0.615668) |

</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) | 0.007562 / 0.011353 (-0.003791) | 0.004548 / 0.011008 (-0.006460) | 0.075998 / 0.038508 (0.037490) | 0.081648 / 0.023109 (0.058539) | 0.462876 / 0.275898 (0.186978) | 0.499366 / 0.323480 (0.175886) | 0.005839 / 0.007986 (-0.002147) | 0.003753 / 0.004328 (-0.000576) | 0.075918 / 0.004250 (0.071668) | 0.063233 / 0.037052 (0.026181) | 0.459024 / 0.258489 (0.200535) | 0.506388 / 0.293841 (0.212547) | 0.036179 / 0.128546 (-0.092367) | 0.009961 / 0.075646 (-0.065685) | 0.082061 / 0.419271 (-0.337211) | 0.056469 / 0.043533 (0.012936) | 0.459567 / 0.255139 (0.204428) | 0.482578 / 0.283200 (0.199378) | 0.026363 / 0.141683 (-0.115320) | 1.742247 / 1.452155 (0.290092) | 1.807166 / 1.492716 (0.314450) |

### 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) | 0.330526 / 0.018006 (0.312520) | 0.511674 / 0.000490 (0.511184) | 0.040969 / 0.000200 (0.040769) | 0.000176 / 0.000054 (0.000121) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.035492 / 0.037411 (-0.001920) | 0.104338 / 0.014526 (0.089813) | 0.116973 / 0.176557 (-0.059583) | 0.180218 / 0.737135 (-0.556917) | 0.118801 / 0.296338 (-0.177538) |

### 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) | 0.492196 / 0.215209 (0.276987) | 4.910271 / 2.077655 (2.832616) | 2.542562 / 1.504120 (1.038442) | 2.333516 / 1.541195 (0.792321) | 2.439682 / 1.468490 (0.971192) | 0.571966 / 4.584777 (-4.012811) | 4.089801 / 3.745712 (0.344089) | 3.732129 / 5.269862 (-1.537733) | 2.375887 / 4.565676 (-2.189789) | 0.067376 / 0.424275 (-0.356900) | 0.008350 / 0.007607 (0.000743) | 0.583942 / 0.226044 (0.357897) | 5.840002 / 2.268929 (3.571074) | 3.062520 / 55.444624 (-52.382104) | 2.722512 / 6.876477 (-4.153965) | 2.938307 / 2.142072 (0.796234) | 0.689459 / 4.805227 (-4.115769) | 0.155632 / 6.500664 (-6.345032) | 0.072387 / 0.075469 (-0.003082) |

### 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) | 1.595587 / 1.841788 (-0.246201) | 23.035478 / 8.074308 (14.961170) | 16.457675 / 10.191392 (6.266283) | 0.170819 / 0.680424 (-0.509605) | 0.022042 / 0.534201 (-0.512159) | 0.466824 / 0.579283 (-0.112459) | 0.486350 / 0.434364 (0.051986) | 0.574330 / 0.540337 (0.033993) | 0.764913 / 1.386936 (-0.622023) |

</details>
</details>

![](https://cml.dev/watermark.png#664a1cb72ea1e6ef7c47e671e2686ca4a35e8d63 "CML watermark")