Fix `ClassLabel` min max check for `None` values
Fix #6022 
_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) | 0.007108 / 0.011353 (-0.004245) | 0.004446 / 0.011008 (-0.006562) | 0.084013 / 0.038508 (0.045505) | 0.084271 / 0.023109 (0.061162) | 0.324496 / 0.275898 (0.048598) | 0.347783 / 0.323480 (0.024303) | 0.004382 / 0.007986 (-0.003604) | 0.005200 / 0.004328 (0.000872) | 0.065117 / 0.004250 (0.060866) | 0.063368 / 0.037052 (0.026316) | 0.328731 / 0.258489 (0.070242) | 0.356676 / 0.293841 (0.062835) | 0.031155 / 0.128546 (-0.097392) | 0.008672 / 0.075646 (-0.066975) | 0.287573 / 0.419271 (-0.131698) | 0.053692 / 0.043533 (0.010160) | 0.308796 / 0.255139 (0.053657) | 0.330521 / 0.283200 (0.047321) | 0.025010 / 0.141683 (-0.116672) | 1.498968 / 1.452155 (0.046813) | 1.552096 / 1.492716 (0.059380) |

### 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) | 0.263580 / 0.018006 (0.245574) | 0.559765 / 0.000490 (0.559275) | 0.003450 / 0.000200 (0.003250) | 0.000079 / 0.000054 (0.000024) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.029403 / 0.037411 (-0.008008) | 0.088154 / 0.014526 (0.073628) | 0.100372 / 0.176557 (-0.076185) | 0.157777 / 0.737135 (-0.579359) | 0.102273 / 0.296338 (-0.194066) |

### 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) | 0.387027 / 0.215209 (0.171818) | 3.854260 / 2.077655 (1.776605) | 1.875159 / 1.504120 (0.371039) | 1.703734 / 1.541195 (0.162539) | 1.814305 / 1.468490 (0.345815) | 0.482524 / 4.584777 (-4.102253) | 3.463602 / 3.745712 (-0.282110) | 4.004766 / 5.269862 (-1.265095) | 2.406751 / 4.565676 (-2.158925) | 0.057069 / 0.424275 (-0.367206) | 0.007448 / 0.007607 (-0.000159) | 0.465801 / 0.226044 (0.239757) | 4.636700 / 2.268929 (2.367771) | 2.329475 / 55.444624 (-53.115150) | 1.998330 / 6.876477 (-4.878146) | 2.264617 / 2.142072 (0.122544) | 0.577998 / 4.805227 (-4.227230) | 0.130846 / 6.500664 (-6.369818) | 0.059713 / 0.075469 (-0.015756) |

### 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) | 1.275931 / 1.841788 (-0.565857) | 20.396288 / 8.074308 (12.321980) | 13.875242 / 10.191392 (3.683850) | 0.164367 / 0.680424 (-0.516057) | 0.018573 / 0.534201 (-0.515628) | 0.397516 / 0.579283 (-0.181767) | 0.398977 / 0.434364 (-0.035387) | 0.462386 / 0.540337 (-0.077951) | 0.610129 / 1.386936 (-0.776807) |

</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) | 0.006912 / 0.011353 (-0.004441) | 0.004212 / 0.011008 (-0.006797) | 0.065707 / 0.038508 (0.027199) | 0.090435 / 0.023109 (0.067325) | 0.380539 / 0.275898 (0.104641) | 0.412692 / 0.323480 (0.089212) | 0.005545 / 0.007986 (-0.002441) | 0.003657 / 0.004328 (-0.000672) | 0.065380 / 0.004250 (0.061130) | 0.062901 / 0.037052 (0.025848) | 0.385931 / 0.258489 (0.127442) | 0.416272 / 0.293841 (0.122431) | 0.031974 / 0.128546 (-0.096572) | 0.008783 / 0.075646 (-0.066863) | 0.071424 / 0.419271 (-0.347847) | 0.049454 / 0.043533 (0.005921) | 0.374231 / 0.255139 (0.119092) | 0.386530 / 0.283200 (0.103331) | 0.025404 / 0.141683 (-0.116279) | 1.469869 / 1.452155 (0.017715) | 1.548629 / 1.492716 (0.055913) |

### 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) | 0.218413 / 0.018006 (0.200406) | 0.573863 / 0.000490 (0.573373) | 0.004156 / 0.000200 (0.003956) | 0.000097 / 0.000054 (0.000043) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.032610 / 0.037411 (-0.004801) | 0.088270 / 0.014526 (0.073744) | 0.106821 / 0.176557 (-0.069735) | 0.164498 / 0.737135 (-0.572638) | 0.106881 / 0.296338 (-0.189457) |

### 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) | 0.433730 / 0.215209 (0.218520) | 4.323902 / 2.077655 (2.246247) | 2.308607 / 1.504120 (0.804487) | 2.138888 / 1.541195 (0.597693) | 2.246760 / 1.468490 (0.778269) | 0.486863 / 4.584777 (-4.097914) | 3.561826 / 3.745712 (-0.183886) | 5.592685 / 5.269862 (0.322824) | 3.318560 / 4.565676 (-1.247116) | 0.057348 / 0.424275 (-0.366927) | 0.007434 / 0.007607 (-0.000174) | 0.506767 / 0.226044 (0.280723) | 5.083097 / 2.268929 (2.814168) | 2.780618 / 55.444624 (-52.664006) | 2.456924 / 6.876477 (-4.419553) | 2.564184 / 2.142072 (0.422112) | 0.580693 / 4.805227 (-4.224534) | 0.134471 / 6.500664 (-6.366194) | 0.062883 / 0.075469 (-0.012586) |

### 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) | 1.346618 / 1.841788 (-0.495169) | 20.547998 / 8.074308 (12.473690) | 14.404159 / 10.191392 (4.212767) | 0.176612 / 0.680424 (-0.503812) | 0.018372 / 0.534201 (-0.515829) | 0.395636 / 0.579283 (-0.183647) | 0.410661 / 0.434364 (-0.023703) | 0.468782 / 0.540337 (-0.071555) | 0.637476 / 1.386936 (-0.749460) |

</details>
</details>

![](https://cml.dev/watermark.png#0172d4dac0ca823e8bd293cfd4d28e78d92efe42 "CML watermark")
 <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) | 0.009896 / 0.011353 (-0.001457) | 0.004658 / 0.011008 (-0.006351) | 0.101185 / 0.038508 (0.062677) | 0.075480 / 0.023109 (0.052371) | 0.410620 / 0.275898 (0.134722) | 0.470639 / 0.323480 (0.147159) | 0.007042 / 0.007986 (-0.000943) | 0.003909 / 0.004328 (-0.000419) | 0.079676 / 0.004250 (0.075425) | 0.066921 / 0.037052 (0.029869) | 0.423624 / 0.258489 (0.165135) | 0.473008 / 0.293841 (0.179167) | 0.048492 / 0.128546 (-0.080054) | 0.012833 / 0.075646 (-0.062813) | 0.335286 / 0.419271 (-0.083985) | 0.083506 / 0.043533 (0.039973) | 0.401918 / 0.255139 (0.146779) | 0.467975 / 0.283200 (0.184775) | 0.050025 / 0.141683 (-0.091658) | 1.679392 / 1.452155 (0.227237) | 1.852812 / 1.492716 (0.360095) |

### 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) | 0.248067 / 0.018006 (0.230061) | 0.584818 / 0.000490 (0.584328) | 0.021558 / 0.000200 (0.021358) | 0.000104 / 0.000054 (0.000050) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.028572 / 0.037411 (-0.008839) | 0.097212 / 0.014526 (0.082686) | 0.121675 / 0.176557 (-0.054881) | 0.186597 / 0.737135 (-0.550538) | 0.122285 / 0.296338 (-0.174053) |

### 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) | 0.586279 / 0.215209 (0.371070) | 5.634402 / 2.077655 (3.556747) | 2.560648 / 1.504120 (1.056528) | 2.288796 / 1.541195 (0.747601) | 2.402580 / 1.468490 (0.934090) | 0.801453 / 4.584777 (-3.783324) | 5.036654 / 3.745712 (1.290942) | 8.319972 / 5.269862 (3.050110) | 4.665620 / 4.565676 (0.099944) | 0.107292 / 0.424275 (-0.316983) | 0.009206 / 0.007607 (0.001599) | 0.766505 / 0.226044 (0.540461) | 7.333784 / 2.268929 (5.064856) | 3.601875 / 55.444624 (-51.842749) | 2.886388 / 6.876477 (-3.990089) | 3.231797 / 2.142072 (1.089725) | 1.179509 / 4.805227 (-3.625718) | 0.224656 / 6.500664 (-6.276008) | 0.084749 / 0.075469 (0.009280) |

### 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) | 1.772345 / 1.841788 (-0.069443) | 24.138788 / 8.074308 (16.064480) | 20.712416 / 10.191392 (10.521024) | 0.254655 / 0.680424 (-0.425769) | 0.028858 / 0.534201 (-0.505343) | 0.499314 / 0.579283 (-0.079969) | 0.605797 / 0.434364 (0.171433) | 0.567628 / 0.540337 (0.027290) | 0.752288 / 1.386936 (-0.634648) |

</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) | 0.010134 / 0.011353 (-0.001219) | 0.004630 / 0.011008 (-0.006378) | 0.082282 / 0.038508 (0.043774) | 0.081722 / 0.023109 (0.058613) | 0.465018 / 0.275898 (0.189120) | 0.516392 / 0.323480 (0.192912) | 0.006618 / 0.007986 (-0.001368) | 0.004310 / 0.004328 (-0.000018) | 0.078990 / 0.004250 (0.074739) | 0.077729 / 0.037052 (0.040677) | 0.464892 / 0.258489 (0.206403) | 0.510551 / 0.293841 (0.216710) | 0.050750 / 0.128546 (-0.077796) | 0.014402 / 0.075646 (-0.061244) | 0.092587 / 0.419271 (-0.326685) | 0.074769 / 0.043533 (0.031237) | 0.468591 / 0.255139 (0.213452) | 0.508138 / 0.283200 (0.224938) | 0.047774 / 0.141683 (-0.093909) | 1.798354 / 1.452155 (0.346199) | 1.851431 / 1.492716 (0.358714) |

### 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) | 0.282528 / 0.018006 (0.264522) | 0.588286 / 0.000490 (0.587797) | 0.004892 / 0.000200 (0.004692) | 0.000136 / 0.000054 (0.000082) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.037048 / 0.037411 (-0.000364) | 0.101513 / 0.014526 (0.086987) | 0.133238 / 0.176557 (-0.043319) | 0.234799 / 0.737135 (-0.502336) | 0.120636 / 0.296338 (-0.175703) |

### 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) | 0.615377 / 0.215209 (0.400168) | 6.225717 / 2.077655 (4.148062) | 2.974137 / 1.504120 (1.470018) | 2.642168 / 1.541195 (1.100973) | 2.706051 / 1.468490 (1.237561) | 0.837171 / 4.584777 (-3.747606) | 5.143368 / 3.745712 (1.397656) | 4.560241 / 5.269862 (-0.709621) | 2.838375 / 4.565676 (-1.727301) | 0.092505 / 0.424275 (-0.331770) | 0.008962 / 0.007607 (0.001355) | 0.726361 / 0.226044 (0.500317) | 7.323998 / 2.268929 (5.055070) | 3.650531 / 55.444624 (-51.794094) | 2.960886 / 6.876477 (-3.915591) | 3.003889 / 2.142072 (0.861816) | 0.979264 / 4.805227 (-3.825963) | 0.204531 / 6.500664 (-6.296133) | 0.078285 / 0.075469 (0.002816) |

### 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) | 1.774225 / 1.841788 (-0.067563) | 26.399536 / 8.074308 (18.325228) | 22.312890 / 10.191392 (12.121498) | 0.244651 / 0.680424 (-0.435773) | 0.026950 / 0.534201 (-0.507251) | 0.493037 / 0.579283 (-0.086246) | 0.620399 / 0.434364 (0.186036) | 0.748985 / 0.540337 (0.208648) | 0.799766 / 1.386936 (-0.587170) |

</details>
</details>

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