ViewsData views

Dataset histogram

Inspect feature and target distributions in an onboarded dataset.
View as Markdown

The Dataset histogram view describes the distribution of values in a dataset.

Use it to inspect categorical frequencies, numeric bins, target statistics, and masked or infrequent values before training, model review, or explanation work.

When to use

Use caseDescription
Inspect data distributionReview how feature and target values are distributed across the dataset.
Check categorical balanceCompare category frequencies and frequency fractions for categorical fields.
Review numeric binsInspect bin ranges and frequencies for numeric fields.
Investigate target behaviourUse target summary statistics to understand how target values vary across bins or categories.
Focus on selected fieldsUse fields to return histogram data for specific dataset fields.

Generate the view

Generate the Dataset histogram view from a dataset.

POST
/datasets/:datasetId/views
1curl -X POST https://api.hi.umnai.com/datasets/datasetId/views \
2     -H "Authorization: Bearer <token>" \
3     -H "Content-Type: application/json" \
4     -d '{
5  "data": [
6    {
7      "view_type": "HISTOGRAM"
8    }
9  ]
10}'
Response
1{
2  "data": [
3    {
4      "view_type": "HISTOGRAM",
5      "view_data": {
6        "columns": [
7          "bin_index",
8          "bin_low",
9          "bin_high",
10          "token",
11          "field_type",
12          "is_categorical",
13          "frequency",
14          "target_min",
15          "target_max",
16          "target_mean",
17          "target_sum",
18          "target_var",
19          "target_stddev",
20          "frequency_fraction",
21          "is_masked_token",
22          "is_infrequent",
23          "field"
24        ],
25        "index": [
26          0,
27          1,
28          2,
29          3,
30          4,
31          5,
32          6,
33          7,
34          8,
35          9,
36          10,
37          11,
38          12,
39          13,
40          14,
41          15,
42          16,
43          17,
44          18,
45          19,
46          20,
47          21,
48          22,
49          23,
50          24,
51          25,
52          26,
53          27,
54          28,
55          29,
56          30,
57          31,
58          32,
59          33,
60          34,
61          35,
62          36,
63          37,
64          38,
65          39,
66          40,
67          41,
68          42,
69          43,
70          44,
71          45,
72          46,
73          47,
74          48,
75          49,
76          50,
77          51,
78          52,
79          53,
80          54,
81          55,
82          56,
83          57,
84          58,
85          59,
86          60,
87          61,
88          62,
89          63,
90          64,
91          65,
92          66,
93          67,
94          68,
95          69,
96          70,
97          71,
98          72,
99          73,
100          74,
101          75,
102          76,
103          77,
104          78,
105          79,
106          80,
107          81,
108          82,
109          83,
110          84,
111          85,
112          86,
113          87,
114          88,
115          89,
116          90,
117          91,
118          92,
119          93,
120          94,
121          95,
122          96,
123          97,
124          98,
125          99,
126          100,
127          101,
128          102,
129          103,
130          104,
131          105,
132          106,
133          107,
134          108,
135          109,
136          110,
137          111,
138          112
139        ],
140        "data": [
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142            null,
143            null,
144            null,
145            "10th",
146            "FEATURE",
147            true,
148            1950,
149            [
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152            [
153              1
154            ],
155            [
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157            ],
158            [
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161            [
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163            ],
164            [
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166            ],
167            0.0278547553,
168            false,
169            false,
170            "education"
171          ],
172          [
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176            "11th",
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180            [
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183            [
184              1
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186            [
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189            [
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192            [
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198            0.0356969403,
199            false,
200            false,
201            "education"
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203          [
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206            null,
207            "12th",
208            "FEATURE",
209            true,
210            929,
211            [
212              0
213            ],
214            [
215              1
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217            [
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219            ],
220            [
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223            [
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226            [
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229            0.0132702911,
230            false,
231            false,
232            "education"
233          ],
234          [
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236            null,
237            null,
238            "1st-4th",
239            "FEATURE",
240            true,
241            374,
242            [
243              0
244            ],
245            [
246              1
247            ],
248            [
249              0.0294117647
250            ],
251            [
252              11
253            ],
254            [
255              0.0285467128
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257            [
258              0.1689577249
259            ],
260            0.0053423992,
261            false,
262            false,
263            "education"
264          ],
265          [
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269            "5th-6th",
270            "FEATURE",
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273            [
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275            ],
276            [
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279            [
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285            [
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296          [
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300            "7th-8th",
301            "FEATURE",
302            true,
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304            [
305              0
306            ],
307            [
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309            ],
310            [
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316            [
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341            [
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362            "Assoc-acdm",
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364            true,
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384            0.0313401708,
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393            "Assoc-voc",
394            "FEATURE",
395            true,
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397            [
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403            [
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415            0.0406393738,
416            false,
417            false,
418            "education"
419          ],
420          [
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422            null,
423            null,
424            "Bachelors",
425            "FEATURE",
426            true,
427            10936,
428            [
429              0
430            ],
431            [
432              1
433            ],
434            [
435              0.404444038
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437            [
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440            [
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446            0.1562151816,
447            false,
448            false,
449            "education"
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451          [
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455            "Doctorate",
456            "FEATURE",
457            true,
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459            [
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464            ],
465            [
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486            "HS-grad",
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488            true,
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508            0.3138302431,
509            false,
510            false,
511            "education"
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513          [
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516            null,
517            "Masters",
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519            true,
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521            [
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523            ],
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527            [
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539            0.0517955604,
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541            false,
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548            "Preschool",
549            "FEATURE",
550            true,
551            117,
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555            [
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570            0.0016712853,
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610            "Some-college",
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1100            "native_45_country"
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1102          [
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1104            null,
1105            null,
1106            "Cambodia",
1107            "FEATURE",
1108            true,
1109            40,
1110            [
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1113            [
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1116            [
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1122            [
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1125            [
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1129            false,
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1131            "native_45_country"
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1133          [
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1135            null,
1136            null,
1137            "Canada",
1138            "FEATURE",
1139            true,
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1144            [
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1147            [
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1153            [
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1156            [
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1159            0.0037568208,
1160            false,
1161            false,
1162            "native_45_country"
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1164          [
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1166            null,
1167            null,
1168            "China",
1169            "FEATURE",
1170            true,
1171            196,
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1175            [
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1178            [
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1184            [
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1187            [
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1190            0.00279976,
1191            false,
1192            false,
1193            "native_45_country"
1194          ],
1195          [
1196            null,
1197            null,
1198            null,
1199            "Columbia",
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3461            null,
3462            "Private",
3463            "FEATURE",
3464            true,
3465            47468,
3466            [
3467              0
3468            ],
3469            [
3470              1
3471            ],
3472            [
3473              0.2063916744
3474            ],
3475            [
3476              9797
3477            ],
3478            [
3479              0.1637941511
3480            ],
3481            [
3482              0.4047149011
3483            ],
3484            0.6780561666,
3485            false,
3486            false,
3487            "workclass"
3488          ],
3489          [
3490            null,
3491            null,
3492            null,
3493            "Self-emp-inc",
3494            "FEATURE",
3495            true,
3496            2223,
3497            [
3498              0
3499            ],
3500            [
3501              1
3502            ],
3503            [
3504              0.5537561853
3505            ],
3506            [
3507              1231
3508            ],
3509            [
3510              0.2471102725
3511            ],
3512            [
3513              0.4971018734
3514            ],
3515            0.031754421,
3516            false,
3517            false,
3518            "workclass"
3519          ],
3520          [
3521            null,
3522            null,
3523            null,
3524            "Self-emp-not-inc",
3525            "FEATURE",
3526            true,
3527            5225,
3528            [
3529              0
3530            ],
3531            [
3532              1
3533            ],
3534            [
3535              0.2750239234
3536            ],
3537            [
3538              1437
3539            ],
3540            [
3541              0.199385765
3542            ],
3543            [
3544              0.4465263318
3545            ],
3546            0.0746364597,
3547            false,
3548            false,
3549            "workclass"
3550          ],
3551          [
3552            null,
3553            null,
3554            null,
3555            "State-gov",
3556            "FEATURE",
3557            true,
3558            2792,
3559            [
3560              0
3561            ],
3562            [
3563              1
3564            ],
3565            [
3566              0.2596704871
3567            ],
3568            [
3569              725
3570            ],
3571            [
3572              0.1922417252
3573            ],
3574            [
3575              0.4384537892
3576            ],
3577            0.0398822958,
3578            false,
3579            false,
3580            "workclass"
3581          ],
3582          [
3583            null,
3584            null,
3585            null,
3586            "Without-pay",
3587            "FEATURE",
3588            true,
3589            33,
3590            [
3591              0
3592            ],
3593            [
3594              1
3595            ],
3596            [
3597              0.0606060606
3598            ],
3599            [
3600              2
3601            ],
3602            [
3603              0.056932966
3604            ],
3605            [
3606              0.2386062992
3607            ],
3608            0.0004713882,
3609            false,
3610            false,
3611            "workclass"
3612          ],
3613          [
3614            null,
3615            null,
3616            null,
3617            "__MASK__",
3618            "FEATURE",
3619            true,
3620            1692,
3621            [
3622              0
3623            ],
3624            [
3625              1
3626            ],
3627            [
3628              0.2742316785
3629            ],
3630            [
3631              464
3632            ],
3633            [
3634              0.199028665
3635            ],
3636            [
3637              0.4462581807
3638            ],
3639            0.0241693569,
3640            true,
3641            false,
3642            "workclass"
3643          ]
3644        ],
3645        "foreign_keys": [],
3646        "labels": [],
3647        "types": [
3648          {
3649            "data_type": "ANY"
3650          },
3651          {
3652            "data_type": "ANY"
3653          },
3654          {
3655            "data_type": "ANY"
3656          },
3657          {
3658            "data_type": "STRING",
3659            "format": null
3660          },
3661          {
3662            "data_type": "STRING",
3663            "format": null
3664          },
3665          {
3666            "data_type": "BOOLEAN"
3667          },
3668          {
3669            "data_type": "NUMBER",
3670            "format": "INT64"
3671          },
3672          {
3673            "data_type": "ARRAY",
3674            "format": {
3675              "data_type": "NUMBER",
3676              "format": "INT64"
3677            }
3678          },
3679          {
3680            "data_type": "ARRAY",
3681            "format": {
3682              "data_type": "NUMBER",
3683              "format": "INT64"
3684            }
3685          },
3686          {
3687            "data_type": "ARRAY",
3688            "format": {
3689              "data_type": "NUMBER",
3690              "format": "FLOAT64"
3691            }
3692          },
3693          {
3694            "data_type": "ARRAY",
3695            "format": {
3696              "data_type": "NUMBER",
3697              "format": "INT64"
3698            }
3699          },
3700          {
3701            "data_type": "ARRAY",
3702            "format": {
3703              "data_type": "NUMBER",
3704              "format": "FLOAT64"
3705            }
3706          },
3707          {
3708            "data_type": "ARRAY",
3709            "format": {
3710              "data_type": "NUMBER",
3711              "format": "FLOAT64"
3712            }
3713          },
3714          {
3715            "data_type": "NUMBER",
3716            "format": "FLOAT64"
3717          },
3718          {
3719            "data_type": "BOOLEAN"
3720          },
3721          {
3722            "data_type": "BOOLEAN"
3723          },
3724          {
3725            "data_type": "STRING",
3726            "format": null
3727          }
3728        ]
3729      },
3730      "views_version": {
3731        "major_version": 0,
3732        "minor_version": 5,
3733        "patch_version": 0,
3734        "build_version": "dev76"
3735      },
3736      "output_version": {
3737        "major_version": 1,
3738        "minor_version": 1,
3739        "patch_version": 1,
3740        "build_version": null
3741      }
3742    }
3743  ]
3744}

The request needs view_type set to HISTOGRAM.

Filter by field

Use fields when you only need histogram rows for specific dataset fields.

POST
/datasets/:datasetId/views
1curl -X POST https://api.hi.umnai.com/datasets/datasetId/views \
2     -H "Authorization: Bearer <token>" \
3     -H "Content-Type: application/json" \
4     -d '{
5  "data": [
6    {
7      "view_type": "HISTOGRAM",
8      "fields": [
9        "gender"
10      ]
11    }
12  ]
13}'
Response
1{
2  "data": [
3    {
4      "view_type": "HISTOGRAM",
5      "view_data": {
6        "columns": [
7          "bin_index",
8          "bin_low",
9          "bin_high",
10          "token",
11          "field_type",
12          "is_categorical",
13          "frequency",
14          "target_min",
15          "target_max",
16          "target_mean",
17          "target_sum",
18          "target_var",
19          "target_stddev",
20          "frequency_fraction",
21          "is_masked_token",
22          "is_infrequent",
23          "field"
24        ],
25        "index": [
26          17,
27          18,
28          19
29        ],
30        "data": [
31          [
32            null,
33            null,
34            null,
35            "Female",
36            "FEATURE",
37            true,
38            22198,
39            [
40              0
41            ],
42            [
43              1
44            ],
45            [
46              0.1159113434
47            ],
48            [
49              2573
50            ],
51            [
52              0.1024759038
53            ],
54            [
55              0.3201185778
56            ],
57            0.3170871068,
58            false,
59            false,
60            "gender"
61          ],
62          [
63            null,
64            null,
65            null,
66            "Male",
67            "FEATURE",
68            true,
69            41938,
70            [
71              0
72            ],
73            [
74              1
75            ],
76            [
77              0.2931708713
78            ],
79            [
80              12295
81            ],
82            [
83              0.2072217115
84            ],
85            [
86              0.4552161152
87            ],
88            0.5990629375,
89            false,
90            false,
91            "gender"
92          ],
93          [
94            null,
95            null,
96            null,
97            "__MASK__",
98            "FEATURE",
99            true,
100            5870,
101            [
102              0
103            ],
104            [
105              1
106            ],
107            [
108              0.2081771721
109            ],
110            [
111              1222
112            ],
113            [
114              0.1648394371
115            ],
116            [
117              0.4060388203
118            ],
119            0.0838499557,
120            true,
121            false,
122            "gender"
123          ]
124        ],
125        "foreign_keys": [],
126        "labels": [],
127        "types": [
128          {
129            "data_type": "ANY"
130          },
131          {
132            "data_type": "ANY"
133          },
134          {
135            "data_type": "ANY"
136          },
137          {
138            "data_type": "STRING",
139            "format": null
140          },
141          {
142            "data_type": "STRING",
143            "format": null
144          },
145          {
146            "data_type": "BOOLEAN"
147          },
148          {
149            "data_type": "NUMBER",
150            "format": "INT64"
151          },
152          {
153            "data_type": "ARRAY",
154            "format": {
155              "data_type": "NUMBER",
156              "format": "INT64"
157            }
158          },
159          {
160            "data_type": "ARRAY",
161            "format": {
162              "data_type": "NUMBER",
163              "format": "INT64"
164            }
165          },
166          {
167            "data_type": "ARRAY",
168            "format": {
169              "data_type": "NUMBER",
170              "format": "FLOAT64"
171            }
172          },
173          {
174            "data_type": "ARRAY",
175            "format": {
176              "data_type": "NUMBER",
177              "format": "INT64"
178            }
179          },
180          {
181            "data_type": "ARRAY",
182            "format": {
183              "data_type": "NUMBER",
184              "format": "FLOAT64"
185            }
186          },
187          {
188            "data_type": "ARRAY",
189            "format": {
190              "data_type": "NUMBER",
191              "format": "FLOAT64"
192            }
193          },
194          {
195            "data_type": "NUMBER",
196            "format": "FLOAT64"
197          },
198          {
199            "data_type": "BOOLEAN"
200          },
201          {
202            "data_type": "BOOLEAN"
203          },
204          {
205            "data_type": "STRING",
206            "format": null
207          }
208        ]
209      },
210      "views_version": {
211        "major_version": 0,
212        "minor_version": 5,
213        "patch_version": 0,
214        "build_version": "dev76"
215      },
216      "output_version": {
217        "major_version": 1,
218        "minor_version": 1,
219        "patch_version": 1,
220        "build_version": null
221      }
222    }
223  ]
224}

This is useful when the dataset has many fields and you only need to inspect a small subset.

Output

The response follows the shared Response structure format.

The Dataset histogram view returns a single dataframe in view_data.

DataframeDescription
view_dataHistogram rows for dataset fields, including bin information, frequency values, target statistics, and field metadata.

Interpret the result

The Dataset histogram view is easiest to read by selecting a field first, then comparing the bins or categories for that field.

Start with the field

Use field to identify the dataset field represented by each row.

Use field_type to distinguish features from targets. Feature rows describe input distributions. Target rows describe target distributions.

Separate categorical and numeric fields

Use is_categorical to understand how to read the row.

For categorical fields, token identifies the category. For numeric fields, bin_index, bin_low, and bin_high describe the numeric bin.

Review frequency

Use frequency to see the number of rows in the category or bin.

Use frequency_fraction to compare categories or bins on a normalized scale. This is usually the easiest way to spot imbalance across a field.

Check infrequent or masked values

Use is_infrequent to identify rare categories.

Use is_masked_token to identify masked tokens. These rows are useful when reviewing whether sensitive, missing, rare, or protected values are being represented as expected.

Inspect target statistics

Use the target_* fields to understand how target values behave within each category or bin.

For example, target_mean can show whether a category or numeric range is associated with higher or lower target values. target_min, target_max, target_sum, target_var, and target_stddev provide additional context.

Options

The Dataset histogram view supports one view-specific option.

OptionUse
fieldsRestrict the histogram output to one or more dataset fields.

Fields

Use fields to request histogram rows for specific fields.

If fields is omitted, the view returns histogram rows for the default set of available dataset fields.

Field reference

The Dataset histogram view returns a dataframe, so individual columns are not documented as standalone API schema properties.

view_data

The view_data dataframe contains the histogram output.

FieldDescription
bin_indexIndex of the numeric bin, when the row represents a numeric bin.
bin_lowLower bound of the numeric bin, when available.
bin_highUpper bound of the numeric bin, when available.
tokenCategory token, when the row represents a categorical value.
field_typeType of field represented by the row, such as FEATURE or TARGET.
is_categoricalWhether the field is categorical.
frequencyNumber of dataset rows in the category or bin.
target_minMinimum target value for rows in the category or bin.
target_maxMaximum target value for rows in the category or bin.
target_meanMean target value for rows in the category or bin.
target_sumSum of target values for rows in the category or bin.
target_varVariance of target values for rows in the category or bin.
target_stddevStandard deviation of target values for rows in the category or bin.
frequency_fractionFraction of dataset rows represented by the category or bin.
is_masked_tokenWhether the row represents a masked token.
is_infrequentWhether the row represents an infrequent category or value.
fieldDataset field represented by the row.