Retrieve Aggregated Stats of Specific Segmentation via REST API
In cases where users might want aggregated stats of a specific segmentation for different reasons, such as checking a hypothesis or collecting data to re-train a model.
For this, users can now leverage Mona's /stats REST API endpoint to retrieve said segmentation stats.
To access Mona's API, first, an accessToken must be generated and added to the request.
Once users have their accessToken they can add it to their authorization and send a POST request with the following mandatory params:
- "contextClass": the context class of the desired segmentation.
- "dimension": the segmentation field we are looking for.
- "targetTimeRange": the time range of the target set. Expected format is an array of timestamps.
- "comparedTimeRange": the time range of the compared set (benchmark). Expected format is an array of timestamps. If not comparing time periods, set as [null, null].
- "metric_1_field": the first metric field we wish to get stats of.
- "metric_2_field": the second metric field we wish to get stats of.
- "metric_1_type": the type of metric for the corresponding metric field. Possible values are - average, sum, variance, normalized_variance, std, standard_error, interquartile range, and existence ratio.
- "metric_2_type": the type of metric for the corresponding metric field.
- "minSegmentSize": the minimum size of segments we want stats for.
- "sortFunction": the sorting for the segments. Possible values are - SIZE_TOP, SIZE_INC, SIZE_DEC, METRIC_1_TOP, METRIC_1_BOTTOM, METRIC_1_INC, METRIC_1_DEC, METRIC_2_TOP, METRIC_2_BOTTOM, METRIC_2_INC, METRIC_2_DEC
Optional args for segments:
- "baseline_segment": The baseline of the segments. If not added the baseline is all data. Expecated format is SegmentType.
- "excluded_segments": Segments to exclude from the data. Expecated format is SegmentListType
- "target_segments_filter": A filter for the target time period. Expecated format is SegmentType.
- "compared_segments_filter":A filter for the compared time period. Expecated format is SegmentType.
In the following example, we are looking for the stats of different segments in the "purpose" segmentation, in a 7 days time range, compared to 2 weeks prior to that, with the average of "credit_score" and "loan_taken".
The segments filters will allow us to look only at the "city": "Arkansas_Fort Smith", "offered_amount": 140 ≤ X ≥ 2100, while excluding "occupation": "no category", and in the target set looking at "stage": "inference" and in the benchmark set at "stage": "train".
curl --location --request POST 'https://api{YOUR-USER-ID}.monalabs.io/stats' \
--header 'Authorization: Bearer YOUR-ACCESS-TOKEN' \
--header 'Content-Type: application/json' \
--data-raw '{
"contextClass": "LOAN_APPLICATION_TUTORIAL",
"dimension": "purpose",
"targetTimeRange": [
1618876800,
1619481659
],
"comparedTimeRange": [
1617667200,
1618876799
],
"metric_1_field": "credit_score",
"metric_2_field": "loan_taken",
"metric_1_type": "average",
"metric_2_type": "average",
"minSegmentSize": 0,
"sortFunction": "SIZE_TOP",
"timeZone": "UTC",
"negativeSegments": [
{
"occupation": [
{
"value": "no category"
}
]
}
],
"baselineSegment": {
"city": [
{
"value": "Arkansas_Fort Smith"
}
],
"offered_amount": [
{
"max_value": 2100,
"min_value": 1400
}
]
},
"targetSegmentsFilter": {
"stage": [
{
"value": "inference"
}
]
},
"comparedSegmentsFilter": {
"stage": [
{
"value": "train"
}
]
}
}'
import requests
url = "https://api{YOUR-USER-ID}.monalabs.io/stats"
payload={
"contextClass": "LOAN_APPLICATION_TUTORIAL",
"dimension": "purpose",
"targetTimeRange": [
1618876800,
1619481659
],
"comparedTimeRange": [
1617667200,
1618876799
],
"metric_1_name": "credit_score",
"metric_2_name": "loan_taken",
"metric_1_type": "average",
"metric_2_type": "average",
"minSegmentSize": 0,
"sortFunction": "SIZE_TOP",
"timeZone": "UTC",
"negativeSegments": [
{
"occupation": [
{
"value": "no category"
}
]
}
],
"baselineSegment": {
"city": [
{
"value": "Arkansas_Fort Smith"
}
],
"offered_amount": [
{
"max_value": 2100,
"min_value": 1400
}
]
},
"targetSegmentsFilter": {
"stage": [
{
"value": "inference"
}
]
},
"comparedSegmentsFilter": {
"stage": [
{
"value": "train"
}
]
}
}
headers = {
'Authorization': 'Bearer YOUR-ACCESS-TOKEN',
'Content-Type': 'application/json'
}
response = requests.request("POST", url, headers=headers, json=payload)
print(response.text)
from mona_sdk.client import Client
api_key = <YOUR-API-KEY>
secret = <YOUR-SECRET>
my_mona_client = Client(api_key, secret)
my_mona_client.get_aggregated_stats_of_a_specific_segmentation(
context_class="LOAN_APPLICATION_TUTORIAL",
dimension="purpose",
target_time_range=[1618876800, 1619481659],
compared_time_range=[1617667200, 1618876799],
metric_1_field="credit_score",
metric_2_field="loan_taken",
metric_1_type="average",
metric_2_type="average",
min_segment_size=0,
sort_function="SIZE_TOP",
excluded_segments=[{"occupation": [{"value": "no category"}]}],
baseline_segment={
"city": [{"value": "Arkansas_Fort Smith"}],
"offered_amount": [{"max_value": 2100, "min_value": 1400}],
},
target_segments_filter={"stage": [{"value": "inference"}]},
compared_segments_filter={"stage": [{"value": "train"}]},
)
The response will be the stats of the chosen metrics in different segments of the segmentation field both in the target period and the compared period, sorted by size.
{
"response_data": [
[
{
"amount": 25,
"ratio": 1,
"average_x": 0.4652754297852516,
"average_y": 0.56,
"standard_error_x": 0.0447339284909803,
"standard_error_y": 0.09927738916792686,
"sum_x": 11,
"sum_y": 14,
"std_x": 0.22366964245490148,
"std_y": 0.4963869458396343,
"variance_x": 0.05002810895590347,
"variance_y": 0.2464,
"normalized_variance_x": 0.10752364245624145,
"normalized_variance_y": 0.43999999999999995,
"segment": "__baseline__",
"segment_json_representation": "{\"city\": [{\"value\": \"Arkansas_Fort Smith\"}], \"offered_amount\": [{\"min_value\": 1400, \"max_value\": 2100}]}",
"timestamp_from": 1618876800,
"timestamp_to": 1619481659,
"sampling_factor": 1,
"failed_shards_factor": 1.0
},
{
"amount": 41,
"ratio": 1,
"average_x": 0.46356988607383354,
"average_y": 0.5121951219512195,
"standard_error_x": 0.03816520993420406,
"standard_error_y": 0.07806365117108506,
"sum_x": 19,
"sum_y": 21,
"std_x": 0.24437658075641494,
"std_y": 0.49985125687607795,
"variance_x": 0.059719913222196594,
"variance_y": 0.2498512790005949,
"normalized_variance_x": 0.12882612744324143,
"normalized_variance_y": 0.4878048780487805,
"segment": "__baseline__",
"segment_json_representation": "{\"city\": [{\"value\": \"Arkansas_Fort Smith\"}], \"offered_amount\": [{\"min_value\": 1400, \"max_value\": 2100}]}",
"timestamp_from": 1617667200,
"timestamp_to": 1618876799,
"sampling_factor": 1,
"failed_shards_factor": 1.0
}
],
[
{
"amount": 7,
"ratio": 0.28,
"average_x": 0.6103763282299042,
"average_y": 0.2857142857142857,
"standard_error_x": 0.049666561609647435,
"standard_error_y": 0.17074694419062766,
"sum_x": 4,
"sum_y": 2,
"std_x": 0.13140537049479498,
"std_y": 0.45175395145262565,
"variance_x": 0.01726737139487433,
"variance_y": 0.20408163265306123,
"normalized_variance_x": 0.028289713405088686,
"normalized_variance_y": 0.7142857142857143,
"segment": "Home construction (city:Arkansas_Fort Smith, offered_amount:1400.00 <= x < 2100.00)",
"segment_json_representation": "{\"city\": [{\"value\": \"Arkansas_Fort Smith\"}], \"offered_amount\": [{\"min_value\": 1400, \"max_value\": 2100}], \"purpose\": [{\"value\": \"Home construction\"}]}",
"timestamp_from": 1618876800,
"timestamp_to": 1619481659,
"sampling_factor": 1,
"failed_shards_factor": 1
},
{
"amount": 7,
"ratio": 0.17073170731707318,
"average_x": 0.37145848146506716,
"average_y": 0.5714285714285714,
"standard_error_x": 0.06771791345676628,
"standard_error_y": 0.1870439059165649,
"sum_x": 2,
"sum_y": 4,
"std_x": 0.17916475831079787,
"std_y": 0.4948716593053935,
"variance_x": 0.03210001062056662,
"variance_y": 0.2448979591836735,
"normalized_variance_x": 0.0864161466820226,
"normalized_variance_y": 0.42857142857142866,
"segment": "Home construction (city:Arkansas_Fort Smith, offered_amount:1400.00 <= x < 2100.00)",
"segment_json_representation": "{\"city\": [{\"value\": \"Arkansas_Fort Smith\"}], \"offered_amount\": [{\"min_value\": 1400, \"max_value\": 2100}], \"purpose\": [{\"value\": \"Home construction\"}]}",
"timestamp_from": 1617667200,
"timestamp_to": 1618876799,
"sampling_factor": 1,
"failed_shards_factor": 1
}
],
[
{
"amount": 4,
"ratio": 0.16,
"average_x": 0.5605046730488539,
"average_y": 0.25,
"standard_error_x": 0.1508383338304452,
"standard_error_y": 0.21650635094610965,
"sum_x": 2,
"sum_y": 1,
"std_x": 0.3016766676608904,
"std_y": 0.4330127018922193,
"variance_x": 0.0910088118109793,
"variance_y": 0.1875,
"normalized_variance_x": 0.162369407762363,
"normalized_variance_y": 0.75,
"segment": "Hospital Services (city:Arkansas_Fort Smith, offered_amount:1400.00 <= x < 2100.00)",
"segment_json_representation": "{\"city\": [{\"value\": \"Arkansas_Fort Smith\"}], \"offered_amount\": [{\"min_value\": 1400, \"max_value\": 2100}], \"purpose\": [{\"value\": \"Hospital Services\"}]}",
"timestamp_from": 1618876800,
"timestamp_to": 1619481659,
"sampling_factor": 1,
"failed_shards_factor": 1
},
{
"amount": 1,
"ratio": 0.024390243902439025,
"average_x": 0.9431050419807434,
"average_y": 0.0,
"standard_error_x": 0.0,
"standard_error_y": 0.0,
"sum_x": 0,
"sum_y": 0,
"std_x": 0.0,
"std_y": 0.0,
"variance_x": 0.0,
"variance_y": 0.0,
"normalized_variance_x": 0.0,
"normalized_variance_y": 0,
"segment": "Hospital Services (city:Arkansas_Fort Smith, offered_amount:1400.00 <= x < 2100.00)",
"segment_json_representation": "{\"city\": [{\"value\": \"Arkansas_Fort Smith\"}], \"offered_amount\": [{\"min_value\": 1400, \"max_value\": 2100}], \"purpose\": [{\"value\": \"Hospital Services\"}]}",
"timestamp_from": 1617667200,
"timestamp_to": 1618876799,
"sampling_factor": 1,
"failed_shards_factor": 1
}
],
[
{
"amount": 3,
"ratio": 0.12,
"average_x": 0.2782125473022461,
"average_y": 0.6666666666666666,
"standard_error_x": 0.02277204146136785,
"standard_error_y": 0.2721655269759087,
"sum_x": 0,
"sum_y": 2,
"std_x": 0.03944233280315414,
"std_y": 0.4714045207910317,
"variance_x": 0.0015556976169547692,
"variance_y": 0.22222222222222224,
"normalized_variance_x": 0.005591759365420287,
"normalized_variance_y": 0.33333333333333337,
"segment": "Existing debts (city:Arkansas_Fort Smith, offered_amount:1400.00 <= x < 2100.00)",
"segment_json_representation": "{\"city\": [{\"value\": \"Arkansas_Fort Smith\"}], \"offered_amount\": [{\"min_value\": 1400, \"max_value\": 2100}], \"purpose\": [{\"value\": \"Existing debts\"}]}",
"timestamp_from": 1618876800,
"timestamp_to": 1619481659,
"sampling_factor": 1,
"failed_shards_factor": 1
},
{
"amount": 2,
"ratio": 0.04878048780487805,
"average_x": 0.543609693646431,
"average_y": 0.5,
"standard_error_x": 0.19223399930444662,
"standard_error_y": 0.35355339059327373,
"sum_x": 1,
"sum_y": 1,
"std_x": 0.27185992896556854,
"std_y": 0.5,
"variance_x": 0.07390782097716397,
"variance_y": 0.25,
"normalized_variance_x": 0.13595751113524907,
"normalized_variance_y": 0.5,
"segment": "Existing debts (city:Arkansas_Fort Smith, offered_amount:1400.00 <= x < 2100.00)",
"segment_json_representation": "{\"city\": [{\"value\": \"Arkansas_Fort Smith\"}], \"offered_amount\": [{\"min_value\": 1400, \"max_value\": 2100}], \"purpose\": [{\"value\": \"Existing debts\"}]}",
"timestamp_from": 1617667200,
"timestamp_to": 1618876799,
"sampling_factor": 1,
"failed_shards_factor": 1
}
],
[
{
"amount": 3,
"ratio": 0.12,
"average_x": 0.4424300690491994,
"average_y": 0.6666666666666666,
"standard_error_x": 0.07727828414048,
"standard_error_y": 0.2721655269759087,
"sum_x": 1,
"sum_y": 2,
"std_x": 0.13384991445305555,
"std_y": 0.4714045207910317,
"variance_x": 0.017915799599090287,
"variance_y": 0.22222222222222224,
"normalized_variance_x": 0.04049408223449207,
"normalized_variance_y": 0.33333333333333337,
"segment": "Surgery (city:Arkansas_Fort Smith, offered_amount:1400.00 <= x < 2100.00)",
"segment_json_representation": "{\"city\": [{\"value\": \"Arkansas_Fort Smith\"}], \"offered_amount\": [{\"min_value\": 1400, \"max_value\": 2100}], \"purpose\": [{\"value\": \"Surgery\"}]}",
"timestamp_from": 1618876800,
"timestamp_to": 1619481659,
"sampling_factor": 1,
"failed_shards_factor": 1
},
{
"amount": 1,
"ratio": 0.024390243902439025,
"average_x": 0.3281591236591339,
"average_y": 1.0,
"standard_error_x": 0.0,
"standard_error_y": 0.0,
"sum_x": 0,
"sum_y": 1,
"std_x": 0.0,
"std_y": 0.0,
"variance_x": 0.0,
"variance_y": 0.0,
"normalized_variance_x": 0.0,
"normalized_variance_y": 0.0,
"segment": "Surgery (city:Arkansas_Fort Smith, offered_amount:1400.00 <= x < 2100.00)",
"segment_json_representation": "{\"city\": [{\"value\": \"Arkansas_Fort Smith\"}], \"offered_amount\": [{\"min_value\": 1400, \"max_value\": 2100}], \"purpose\": [{\"value\": \"Surgery\"}]}",
"timestamp_from": 1617667200,
"timestamp_to": 1618876799,
"sampling_factor": 1,
"failed_shards_factor": 1
}
],
[
{
"amount": 2,
"ratio": 0.08,
"average_x": 0.5445045232772827,
"average_y": 0.5,
"standard_error_x": 0.1973201650789079,
"standard_error_y": 0.35355339059327373,
"sum_x": 1,
"sum_y": 1,
"std_x": 0.27905285358428955,
"std_y": 0.5,
"variance_x": 0.07787049509353494,
"variance_y": 0.25,
"normalized_variance_x": 0.1430116587918229,
"normalized_variance_y": 0.5,
"segment": "Household (city:Arkansas_Fort Smith, offered_amount:1400.00 <= x < 2100.00)",
"segment_json_representation": "{\"city\": [{\"value\": \"Arkansas_Fort Smith\"}], \"offered_amount\": [{\"min_value\": 1400, \"max_value\": 2100}], \"purpose\": [{\"value\": \"Household\"}]}",
"timestamp_from": 1618876800,
"timestamp_to": 1619481659,
"sampling_factor": 1,
"failed_shards_factor": 1
}
],
[
{
"amount": 1,
"ratio": 0.04,
"average_x": 0.26755452156066895,
"average_y": 1.0,
"standard_error_x": 0.0,
"standard_error_y": 0.0,
"sum_x": 0,
"sum_y": 1,
"std_x": 0.0,
"std_y": 0.0,
"variance_x": 0.0,
"variance_y": 0.0,
"normalized_variance_x": 0.0,
"normalized_variance_y": 0.0,
"segment": "Car insurance (city:Arkansas_Fort Smith, offered_amount:1400.00 <= x < 2100.00)",
"segment_json_representation": "{\"city\": [{\"value\": \"Arkansas_Fort Smith\"}], \"offered_amount\": [{\"min_value\": 1400, \"max_value\": 2100}], \"purpose\": [{\"value\": \"Car insurance\"}]}",
"timestamp_from": 1618876800,
"timestamp_to": 1619481659,
"sampling_factor": 1,
"failed_shards_factor": 1
},
{
"amount": 2,
"ratio": 0.04878048780487805,
"average_x": 0.8422092497348785,
"average_y": 0.0,
"standard_error_x": 0.020222416163739296,
"standard_error_y": 0.0,
"sum_x": 1,
"sum_y": 0,
"std_x": 0.028598815202713013,
"std_y": 0.0,
"variance_x": 0.0008178922309989289,
"variance_y": 0.0,
"normalized_variance_x": 0.00097112710559329,
"normalized_variance_y": 0,
"segment": "Car insurance (city:Arkansas_Fort Smith, offered_amount:1400.00 <= x < 2100.00)",
"segment_json_representation": "{\"city\": [{\"value\": \"Arkansas_Fort Smith\"}], \"offered_amount\": [{\"min_value\": 1400, \"max_value\": 2100}], \"purpose\": [{\"value\": \"Car insurance\"}]}",
"timestamp_from": 1617667200,
"timestamp_to": 1618876799,
"sampling_factor": 1,
"failed_shards_factor": 1
}
],
[
{
"amount": 1,
"ratio": 0.04,
"average_x": 0.2250485122203827,
"average_y": 1.0,
"standard_error_x": 0.0,
"standard_error_y": 0.0,
"sum_x": 0,
"sum_y": 1,
"std_x": 0.0,
"std_y": 0.0,
"variance_x": 0.0,
"variance_y": 0.0,
"normalized_variance_x": 0.0,
"normalized_variance_y": 0.0,
"segment": "Credit score improvement (city:Arkansas_Fort Smith, offered_amount:1400.00 <= x < 2100.00)",
"segment_json_representation": "{\"city\": [{\"value\": \"Arkansas_Fort Smith\"}], \"offered_amount\": [{\"min_value\": 1400, \"max_value\": 2100}], \"purpose\": [{\"value\": \"Credit score improvement\"}]}",
"timestamp_from": 1618876800,
"timestamp_to": 1619481659,
"sampling_factor": 1,
"failed_shards_factor": 1
},
{
"amount": 8,
"ratio": 0.1951219512195122,
"average_x": 0.4546951185911894,
"average_y": 0.25,
"standard_error_x": 0.0854432560498745,
"standard_error_y": 0.15309310892394862,
"sum_x": 3,
"sum_y": 2,
"std_x": 0.24167002303809906,
"std_y": 0.4330127018922193,
"variance_x": 0.05840440003523534,
"variance_y": 0.1875,
"normalized_variance_x": 0.12844738737506878,
"normalized_variance_y": 0.75,
"segment": "Credit score improvement (city:Arkansas_Fort Smith, offered_amount:1400.00 <= x < 2100.00)",
"segment_json_representation": "{\"city\": [{\"value\": \"Arkansas_Fort Smith\"}], \"offered_amount\": [{\"min_value\": 1400, \"max_value\": 2100}], \"purpose\": [{\"value\": \"Credit score improvement\"}]}",
"timestamp_from": 1617667200,
"timestamp_to": 1618876799,
"sampling_factor": 1,
"failed_shards_factor": 1
}
],
[
{
"amount": 1,
"ratio": 0.04,
"average_x": 0.3157288730144501,
"average_y": 1.0,
"standard_error_x": 0.0,
"standard_error_y": 0.0,
"sum_x": 0,
"sum_y": 1,
"std_x": 0.0,
"std_y": 0.0,
"variance_x": 0.0,
"variance_y": 0.0,
"normalized_variance_x": 0.0,
"normalized_variance_y": 0.0,
"segment": "Investment (city:Arkansas_Fort Smith, offered_amount:1400.00 <= x < 2100.00)",
"segment_json_representation": "{\"city\": [{\"value\": \"Arkansas_Fort Smith\"}], \"offered_amount\": [{\"min_value\": 1400, \"max_value\": 2100}], \"purpose\": [{\"value\": \"Investment\"}]}",
"timestamp_from": 1618876800,
"timestamp_to": 1619481659,
"sampling_factor": 1,
"failed_shards_factor": 1
},
{
"amount": 1,
"ratio": 0.024390243902439025,
"average_x": 0.6919273138046265,
"average_y": 0.0,
"standard_error_x": 0.0,
"standard_error_y": 0.0,
"sum_x": 0,
"sum_y": 0,
"std_x": 0.0,
"std_y": 0.0,
"variance_x": 0.0,
"variance_y": 0.0,
"normalized_variance_x": 0.0,
"normalized_variance_y": 0,
"segment": "Investment (city:Arkansas_Fort Smith, offered_amount:1400.00 <= x < 2100.00)",
"segment_json_representation": "{\"city\": [{\"value\": \"Arkansas_Fort Smith\"}], \"offered_amount\": [{\"min_value\": 1400, \"max_value\": 2100}], \"purpose\": [{\"value\": \"Investment\"}]}",
"timestamp_from": 1617667200,
"timestamp_to": 1618876799,
"sampling_factor": 1,
"failed_shards_factor": 1
}
],
[
{
"amount": 1,
"ratio": 0.04,
"average_x": 0.11350111663341522,
"average_y": 1.0,
"standard_error_x": 0.0,
"standard_error_y": 0.0,
"sum_x": 0,
"sum_y": 1,
"std_x": 0.0,
"std_y": 0.0,
"variance_x": 0.0,
"variance_y": 0.0,
"normalized_variance_x": 0.0,
"normalized_variance_y": 0.0,
"segment": "Transportation (city:Arkansas_Fort Smith, offered_amount:1400.00 <= x < 2100.00)",
"segment_json_representation": "{\"city\": [{\"value\": \"Arkansas_Fort Smith\"}], \"offered_amount\": [{\"min_value\": 1400, \"max_value\": 2100}], \"purpose\": [{\"value\": \"Transportation\"}]}",
"timestamp_from": 1618876800,
"timestamp_to": 1619481659,
"sampling_factor": 1,
"failed_shards_factor": 1
}
],
[
{
"amount": 1,
"ratio": 0.04,
"average_x": 0.5264514684677124,
"average_y": 1.0,
"standard_error_x": 0.0,
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Updated about 2 years ago