vDataFrame.expected_store_usage¶
In [ ]:
vDataFrame.expected_store_usage()
Returns the vDataFrame expected store usage.
Parameters¶
| Name | Type | Optional | Description |
|---|---|---|---|
unit | str | ✓ | unit used for the computation.
|
Returns¶
tablesample : An object containing the result. For more information, see utilities.tablesample.
Example¶
In [167]:
from verticapy.datasets import load_market
market = load_market()
display(market)
 | 123 PriceFloat | Abc FormVarchar(32) | Abc NameVarchar(32) |
| 1 | 1.1193087167 | Fresh | Acorn squash |
| 2 | 1.1722478842 | Fresh | Acorn squash |
| 3 | 1.56751539145 | Fresh | Apples |
| 4 | 1.6155336441 | Fresh | Apples |
| 5 | 0.5104657455 | Frozen | Apples |
| 6 | 0.537867915537 | Frozen | Apples |
| 7 | 0.6311325278 | Ready to drink | Apples |
| 8 | 0.727287713105 | Ready to drink | Apples |
| 9 | 7.3309645323 | Dried | Apricots |
| 10 | 7.73397208999 | Dried | Apricots |
| 11 | 3.0400719671 | Fresh | Apricots |
| 12 | 3.087137817 | Fresh | Apricots |
| 13 | 1.4742760156 | Packed in juice | Apricots |
| 14 | 1.64748926094 | Packed in juice | Apricots |
| 15 | 1.55204253208 | Packed in syrup, syrup discarded | Apricots |
| 16 | 1.8552908088 | Packed in syrup, syrup discarded | Apricots |
| 17 | 3.3174627313 | Canned | Artichoke |
| 18 | 3.38561047493 | Canned | Artichoke |
| 19 | 2.21305047929 | Fresh | Artichoke |
| 20 | 2.3637333814 | Fresh | Artichoke |
| 21 | 5.7683252728 | Frozen | Artichoke |
| 22 | 6.22141832776 | Frozen | Artichoke |
| 23 | 2.5802971683 | Canned | Asparagus |
| 24 | 2.7200086787 | Canned | Asparagus |
| 25 | 3.0756105724 | Fresh | Asparagus |
| 26 | 3.21349409304 | Fresh | Asparagus |
| 27 | 5.85731991397 | Frozen | Asparagus |
| 28 | 6.0657860935 | Frozen | Asparagus |
| 29 | 2.225544076 | Fresh | Avocado |
| 30 | 2.23587438158 | Fresh | Avocado |
| 31 | 0.5494172928 | Fresh | Bananas |
| 32 | 0.566983414531 | Fresh | Bananas |
| 33 | 0.9427311158 | Canned | Beets |
| 34 | 1.01727546324 | Canned | Beets |
| 35 | 3.41021478336 | Frozen | Berries, mixed |
| 36 | 3.63694066 | Frozen | Berries, mixed |
| 37 | 0.945681045 | Canned | Black beans |
| 38 | 0.980579717755 | Canned | Black beans |
| 39 | 1.4038762924 | Dried | Black beans |
| 40 | 1.48978420263 | Dried | Black beans |
| 41 | 5.661671336 | Fresh | Blackberries |
| 42 | 5.77470825035 | Fresh | Blackberries |
| 43 | 3.38850085426 | Frozen | Blackberries |
| 44 | 3.6920108696 | Frozen | Blackberries |
| 45 | 0.910440813422 | Canned | Blackeye peas |
| 46 | 0.9310398825 | Canned | Blackeye peas |
| 47 | 1.58990085218 | Dried | Blackeye peas |
| 48 | 1.613022434 | Dried | Blackeye peas |
| 49 | 4.3911083709 | Fresh | Blueberries |
| 50 | 4.73462168973 | Fresh | Blueberries |
| 51 | 3.471925452 | Frozen | Blueberries |
| 52 | 3.64325041591 | Frozen | Blueberries |
| 53 | 2.3624557989 | Florets | Broccoli |
| 54 | 2.56847143403 | Florets | Broccoli |
| 55 | 1.8227837671 | Frozen | Broccoli |
| 56 | 1.86970036313 | Frozen | Broccoli |
| 57 | 1.63609690647 | Heads | Broccoli |
| 58 | 1.9191171292 | Heads | Broccoli |
| 59 | 2.76355337151 | Fresh | Brussels sprouts |
| 60 | 2.9620929796 | Fresh | Brussels sprouts |
| 61 | 2.0397358015 | Frozen | Brussels sprouts |
| 62 | 2.13825366618 | Frozen | Brussels sprouts |
| 63 | 1.24473670387 | Fresh | Butternut squash |
| 64 | 1.2920110231 | Fresh | Butternut squash |
| 65 | 0.579208394258 | Fresh green cabbage | Cabbage |
| 66 | 0.6238712291 | Fresh green cabbage | Cabbage |
| 67 | 1.0241250285 | Fresh red cabbage | Cabbage |
| 68 | 1.05644972791 | Fresh red cabbage | Cabbage |
| 69 | 1.153095782 | Sauerkraut | Cabbage |
| 70 | 1.26463509211 | Sauerkraut | Cabbage |
| 71 | 0.520793672 | Fresh | Cantaloupe |
| 72 | 0.535873776106 | Fresh | Cantaloupe |
| 73 | 0.9231914223 | Canned | Carrots |
| 74 | 1.06049032785 | Canned | Carrots |
| 75 | 0.741539992379 | Cooked whole | Carrots |
| 76 | 0.7737514155 | Cooked whole | Carrots |
| 77 | 1.3965860252 | Frozen | Carrots |
| 78 | 1.46051272856 | Frozen | Carrots |
| 79 | 1.4373172338 | Raw baby | Carrots |
| 80 | 1.44745804876 | Raw baby | Carrots |
| 81 | 0.741539992379 | Raw whole | Carrots |
| 82 | 0.7737514155 | Raw whole | Carrots |
| 83 | 3.1279734694 | Florets | Cauliflower |
| 84 | 3.27064843515 | Florets | Cauliflower |
| 85 | 1.6814349408 | Frozen | Cauliflower |
| 86 | 1.716444729 | Frozen | Cauliflower |
| 87 | 1.22881085623 | Heads | Cauliflower |
| 88 | 1.416972077 | Heads | Cauliflower |
| 89 | 2.1340528999 | Sticks | Celery |
| 90 | 2.2049694293 | Sticks | Celery |
| 91 | 1.0928457916 | Trimmed bunches | Celery |
| 92 | 1.11365395418 | Trimmed bunches | Celery |
| 93 | 3.51874337733 | Canned, packed in syrup or water | Cherries |
| 94 | 3.7259182628 | Canned, packed in syrup or water | Cherries |
| 95 | 3.2130681107 | Fresh | Cherries |
| 96 | 3.59298975549 | Fresh | Cherries |
| 97 | 0.8534190293 | Canned | Collard greens |
| 98 | 0.902593822572 | Canned | Collard greens |
| 99 | 2.6294683753 | Fresh | Collard greens |
| 100 | 2.63083790515 | Fresh | Collard greens |
In [168]:
market.expected_store_usage(unit = "kb")
| expected_size (kb) | max_size (kb) | type |
| "Price" | 0.0078125 | 2.453125 | float |
| "Form" | 2.423828125 | 9.8125 | varchar(32) |
| "Name" | 2.888671875 | 9.8125 | varchar(32) |
| separator | 0.919921875 | 0.919921875 | |
| header | 0.021484375 | 0.021484375 | |
| rawsize | 6.26171875 | 23.01953125 |
Out[168]:
See Also¶
| vDataFrame.memory_usage | Returns the vDataFrame memory usage. |