Function
Query Functions
There a few functions that you can apply to queries to gather even more insight into the data.
You can retrieve a listing of the available functions in a dataset with the following request:
GET /dataset/<DATASET_ID> HTTP/1.1
Authorization: token 01234567890123456789
X-API-Version: 20151130
A sample response is as follows:
{
...
"id": "job_listings",
"truncate_limit": 500000,
"functions": {
"genderdecoder": {
"description": "Analyze potential gender bias in job listings.",
"blog_url": "https://blog.thinknum.com/job-listings/"
},
"sales": {
"description": "See which individual jobs have been filled within the defined Lookahead Days. ",
"blog_url": "https://blog.thinknum.com/job-listings/#recruitment-analysis-function"
},
"changeovertime": {
"description": "Calculate the difference between a data point today and a user defined frequency.",
"blog_url": "https://blog.thinknum.com/change-over-time/"
}
},
...
}
Note: Currently, you can only apply functions against the “Store Locations” dataset.
Nearby Competitors
This is a function that can be applied to queries that contain coordinate data. For each item in the query, It provides a count of the numbers of competitors (provided in a list either by ticker and/or entity) within a specified distance.
The nearby function has the following parameters:
Parameter | Description | Required? |
---|---|---|
dataset | The dataset of the competitors | Yes |
tickers | List of competitor tickers | No, if entities is defined; yes, otherwise. |
entities | List of competitor entities | No, if tickers is defined; yes, otherwise. |
distance | The radius in miles to consider as "nearby" | Yes |
For example, if you are analyzing the "Store Locations" dataset, and you would like to see how many Ralph Lauren stores are within 5 miles of each Nordstrom store, you can run the following query:
POST /dataset/store/query/ HTTP/1.1
Authorization: token 01234567890123456789
X-API-Version: 20151130
{
"tickers": [
"nyse:jwn"
],
"functions": [
{
"function": "nearby",
"parameters": {
"dataset": "store",
"dataset_type": "dataset",
"distance": 5,
"entities": [],
"is_include_closed": false,
"tickers": [
"nyse:rl"
]
}
}
]
}
curl -X POST "https://data.thinknum.com/datasets/store/query/" \
-H "Accept: application/json" \
-H "X-API-Version: 20151130" \
-H "Authorization: token 01234567890123456789" \
-d $'{
"tickers": [
"nyse:jwn"
],
"functions": [
{
"function": "nearby",
"parameters": {
"dataset": "store",
"dataset_type": "dataset",
"distance": 5,
"entities": [],
"is_include_closed": false,
"tickers": [
"nyse:rl"
]
}
}
]
}'
response = requests.post(
url='https://data.thinknum.com/datasets/store/query/',
headers={
'Authorization': 'token 01234567890123456789',
'X-API-Version': '20151130',
'Accept': 'application/json'
},
data=json.dumps({
"tickers": [
"nyse:jwn"
],
"functions": [
{
"function": "nearby",
"parameters": {
"dataset": "store",
"dataset_type": "dataset",
"distance": 5,
"entities": [],
"is_include_closed": false,
"tickers": [
"nyse:rl"
]
}
}
]
})
)
results = json.loads(response.text)
A sample response follows:
{
"state": "running",
"total": 0,
"id": "33afc36bb52fcb5e26aaf94ddfb2c91341a2a673bb1210341dcc1764a955c9cd",
"formats": [
"application/vnd.thinknum.table+json",
"application/vnd.thinknum.map+json"
]
}
To check if query is done:
HEAD datasets/store/query/33afc36bb52fcb5e26aaf94ddfb2c91341a2a673bb1210341dcc1764a955c9cd HTTP/1.1
Authorization: token 01234567890123456789
X-API-Version: 20151130
Accept: application/vnd.thinknum.table+json
Content-Type: application/x-www-form-urlencoded; charset=utf-8
curl -I HEAD "https://data.thinknum.com/datasets/store/query/33afc36bb52fcb5e26aaf94ddfb2c91341a2a673bb1210341dcc1764a955c9cd" \
-H "Accept: application/vnd.thinknum.table+json" \
-H "X-API-Version: 20151130" \
-H "Authorization: token 01234567890123456789"
response = requests.head(
url='https://data.thinknum.com/datasets/store/query/33afc36bb52fcb5e26aaf94ddfb2c91341a2a673bb1210341dcc1764a955c9cd',
headers={
'Authorization': 'token 01234567890123456789',
'X-API-Version': '20151130',
'Accept': 'application/vnd.thinknum.table+json'
}
)
results = dict(response.headers)
A sample response follows:
HTTP/1.1 200 OK
Server: nginx
Date: Wed, 28 Apr 2021 16:23:07 GMT
Content-Type: application/json
Connection: keep-alive
X-Truncated: false
X-Formats: application/vnd.thinknum.table+json, application/vnd.thinknum.map+json, text/csv, application/vnd.ms-excel, application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
X-Total: 963
X-State: complete
Strict-Transport-Security: max-age=15768000
To retrieve data:
GET /datasets/store/query/33afc36bb52fcb5e26aaf94ddfb2c91341a2a673bb1210341dcc1764a955c9cd?limit=10&start=1
Authorization: token 01234567890123456789
X-API-Version: 20151130
Accept: application/vnd.thinknum.table+json
Content-Type: application/json
curl -X GET "https://data.thinknum.com/datasets/store/query/33afc36bb52fcb5e26aaf94ddfb2c91341a2a673bb1210341dcc1764a955c9cd?limit=10&start=1" \
-H "Accept: application/vnd.thinknum.table+json" \
-H "Content-Type: application/json" \
-H "X-API-Version: 20151130" \
-H "Authorization: token 01234567890123456789"
response = requests.get(
url='https://data.thinknum.com/datasets/store/query/33afc36bb52fcb5e26aaf94ddfb2c91341a2a673bb1210341dcc1764a955c9cd',
headers={
'Authorization': 'token 01234567890123456789',
'X-API-Version': '20151130',
'Accept': 'application/vnd.thinknum.table+json'
}
)
results = json.loads(response.text)
A sample response follows:
{
"group_fields": [
{
"length": 320,
"options": [],
"display_name": "Ticker Symbol",
"format": "ticker",
"metric": false,
"type": "string",
"id": "dataset__entity__entity_ticker__ticker__ticker",
"summary": "The full ticker symbol, defined as the financial market of the company, followed by a colon (:), and then the identifier of the company. ex. NASDAQ:AAPL"
},
{
"length": 255,
"options": [],
"display_name": "Entity Name",
"format": null,
"metric": false,
"type": "string",
"id": "dataset__entity__name",
"summary": "The name of a specific entity belonging to a ticker within this dataset."
},
...
{
"length": null,
"options": [],
"display_name": "Competition #1",
"format": null,
"metric": true,
"type": "number",
"id": "$nearby_1@count",
"summary": ""
}
],
"total": 963,
"id": "33afc36bb52fcb5e26aaf94ddfb2c91341a2a673bb1210341dcc1764a955c9cd",
"count": 10,
"rows": [
[
"nyse:jwn",
"Nordstrom",
...
0
],
...
[
"nyse:jwn",
"Nordstrom",
...
2
]
],
"fields": [
{
"display_name": "Ticker Symbol",
"format": "ticker",
"metric": false,
"id": "dataset__entity__entity_ticker__ticker__ticker",
"length": 320,
"summary": "The full ticker symbol, defined as the financial market of the company, followed by a colon (:), and then the identifier of the company. ex. NASDAQ:AAPL",
"type": "string",
"options": []
},
{
"display_name": "Entity Name",
"format": null,
"metric": false,
"id": "dataset__entity__name",
"length": 255,
"summary": "The name of a specific entity belonging to a ticker within this dataset.",
"type": "string",
"options": []
},
...
{
"display_name": "Competition #1",
"format": null,
"metric": true,
"id": "$nearby_1@count",
"length": null,
"summary": "",
"type": "number",
"options": []
}
],
"sort_fields": [],
"start": 1,
"state": "complete",
"limit": 10,
"last_date_updated": "2021-03-26T16:00:35Z"
}
Nearest Competitor
While the Nearby Competitors function returns a count of the competitors within a specified distance, the Nearest Competitor returns the closest competitor for each item in the query.
The Nearest Competitor function has the following parameters:
Parmeter | Description | Required? |
---|---|---|
dataset | The dataset of the competitors | Yes |
tickers | List of competitor tickers | No, if entities is defined; yes, otherwise. |
entities | List of competitor entities | No, if tickers is defined; yes, otherwise. |
For example, if you are analyzing the "Store Locations" dataset, and you would like to see how close each Nordstrom store is to a Ralph Lauren store, you can run the following query:
POST /dataset/store/query/ HTTP/1.1
Authorization: token 01234567890123456789
X-API-Version: 20151130
{
"tickers": [
"nyse:jwn"
],
"functions": [
{
"function": "nearest",
"parameters": {
"dataset_type": "dataset",
"dataset": "store",
"tickers": [
"nyse:rl"
],
"entities": [],
"ranks": [
1
],
"is_include_closed": false
}
}
]
}
curl -X POST "https://data.thinknum.com/datasets/store/query/" \
-H "Accept: application/json" \
-H "X-API-Version: 20151130" \
-H "Authorization: token 01234567890123456789" \
-d $'{
"tickers": [
"nyse:jwn"
],
"functions": [
{
"function": "nearest",
"parameters": {
"dataset_type": "dataset",
"dataset": "store",
"tickers": [
"nyse:rl"
],
"entities": [],
"ranks": [
1
],
"is_include_closed": false
}
}
]
}'
response = requests.post(
url='https://data.thinknum.com/datasets/store/query/',
headers={
'Authorization': 'token 01234567890123456789',
'X-API-Version': '20151130',
'Accept': 'application/json'
},
data=json.dumps({
"tickers": [
"nyse:jwn"
],
"functions": [
{
"function": "nearest",
"parameters": {
"dataset_type": "dataset",
"dataset": "store",
"tickers": [
"nyse:rl"
],
"entities": [],
"ranks": [
1
],
"is_include_closed": false
}
}
]
})
)
results = json.loads(response.text)
A sample response follows:
{
"state": "complete",
"total": 963,
"id": "dfe76829a25074868ee8018ac2c2d0cdc074c3e86ec80f9897ee41570950f441",
"formats": [
"application/vnd.thinknum.table+json",
"application/vnd.thinknum.map+json"
]
}
To check if query is completed:
HEAD datasets/store/query/dfe76829a25074868ee8018ac2c2d0cdc074c3e86ec80f9897ee41570950f441 HTTP/1.1
Authorization: token 01234567890123456789
X-API-Version: 20151130
Accept: application/vnd.thinknum.table+json
Content-Type: application/x-www-form-urlencoded; charset=utf-8
curl -I HEAD "https://data.thinknum.com/datasets/store/query/dfe76829a25074868ee8018ac2c2d0cdc074c3e86ec80f9897ee41570950f441" \
-H "Accept: application/vnd.thinknum.table+json" \
-H "X-API-Version: 20151130" \
-H "Authorization: token 01234567890123456789"
response = requests.head(
url='https://data.thinknum.com/datasets/store/query/dfe76829a25074868ee8018ac2c2d0cdc074c3e86ec80f9897ee41570950f441',
headers={
'Authorization': 'token 01234567890123456789',
'X-API-Version': '20151130',
'Accept': 'application/vnd.thinknum.table+json'
}
)
results = dict(response.headers)
A sample response follows:
HTTP/1.1 200 OK
Server: nginx
Date: Wed, 28 Apr 2021 16:29:50 GMT
Content-Type: application/json
Connection: keep-alive
X-Truncated: false
X-Formats: application/vnd.thinknum.table+json, application/vnd.thinknum.map+json, text/csv, application/vnd.ms-excel, application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
X-Total: 963
X-State: complete
Strict-Transport-Security: max-age=15768000
To retrieve data:
GET /datasets/store/query/dfe76829a25074868ee8018ac2c2d0cdc074c3e86ec80f9897ee41570950f441?limit=10&start=1
Authorization: token 01234567890123456789
X-API-Version: 20151130
Accept: application/vnd.thinknum.table+json
Content-Type: application/json
curl -X GET "https://data.thinknum.com/datasets/store/query/dfe76829a25074868ee8018ac2c2d0cdc074c3e86ec80f9897ee41570950f441?limit=10&start=1" \
-H "Accept: application/vnd.thinknum.table+json" \
-H "Content-Type: application/json" \
-H "X-API-Version: 20151130" \
-H "Authorization: token 01234567890123456789"
response = requests.get(
url='https://data.thinknum.com/datasets/store/query/dfe76829a25074868ee8018ac2c2d0cdc074c3e86ec80f9897ee41570950f441',
headers={
'Authorization': 'token 01234567890123456789',
'X-API-Version': '20151130',
'Accept': 'application/vnd.thinknum.table+json'
}
)
results = json.loads(response.text)
A sample response follows:
{
"group_fields": [
{
"length": 320,
"options": [],
"display_name": "Ticker Symbol",
"format": "ticker",
"metric": false,
"type": "string",
"id": "dataset__entity__entity_ticker__ticker__ticker",
"summary": "The full ticker symbol, defined as the financial market of the company, followed by a colon (:), and then the identifier of the company. ex. NASDAQ:AAPL"
},
{
"length": 255,
"options": [],
"display_name": "Entity Name",
"format": null,
"metric": false,
"type": "string",
"id": "dataset__entity__name",
"summary": "The name of a specific entity belonging to a ticker within this dataset."
},
...
{
"length": null,
"options": [],
"display_name": "Nearest Store #1",
"format": null,
"metric": false,
"type": "number",
"id": "$nearest_1_1.rank",
"summary": ""
},
{
"length": null,
"options": [],
"display_name": "Nearest Ticker #1",
"format": null,
"metric": false,
"type": "number",
"id": "$nearest_1_1.ticker",
"summary": ""
},
{
"length": null,
"options": [],
"display_name": "Nearest Entity #1",
"format": null,
"metric": false,
"type": "number",
"id": "$nearest_1_1.entity",
"summary": ""
},
{
"length": null,
"options": [],
"display_name": "Nearest Distance #1",
"format": null,
"metric": true,
"type": "number",
"id": "$nearest_1_1.dist",
"summary": ""
},
{
"length": null,
"options": [],
"display_name": "Nearest Store Name #1",
"format": null,
"metric": false,
"type": "number",
"id": "$nearest_1_1.storefront_name",
"summary": ""
},
{
"length": null,
"options": [],
"display_name": "Nearest Store Street #1",
"format": null,
"metric": false,
"type": "number",
"id": "$nearest_1_1.street",
"summary": ""
},
{
"length": null,
"options": [],
"display_name": "Nearest Store City #1",
"format": null,
"metric": false,
"type": "number",
"id": "$nearest_1_1.city",
"summary": ""
},
{
"length": null,
"options": [],
"display_name": "Nearest Store State #1",
"format": null,
"metric": false,
"type": "number",
"id": "$nearest_1_1.state",
"summary": ""
},
{
"length": null,
"options": [],
"display_name": "Nearest Store Country #1",
"format": null,
"metric": false,
"type": "number",
"id": "$nearest_1_1.country",
"summary": ""
},
{
"length": null,
"options": [],
"display_name": "Nearest Store Postal Code #1",
"format": null,
"metric": false,
"type": "number",
"id": "$nearest_1_1.postal_code",
"summary": ""
},
{
"length": null,
"options": [],
"display_name": "Nearest Store Is Closed #1",
"format": null,
"metric": false,
"type": "boolean",
"id": "$nearest_1_1.is_closed",
"summary": ""
}
],
"total": 963,
"id": "dfe76829a25074868ee8018ac2c2d0cdc074c3e86ec80f9897ee41570950f441",
"count": 10,
"rows": [
[
"nyse:jwn",
"Nordstrom",
...
1,
"nyse:rl",
"Ralph Lauren",
29.2719080003088,
"RALPH LAUREN",
"Houston Galleria, 5015 Westheimer",
"Houston, TX",
"TX",
"USA",
"77056",
false
],
...
[
"nyse:jwn",
"Nordstrom",
...
1,
"nyse:rl",
"Ralph Lauren",
41.8697883953577,
"POLO RALPH LAUREN FACTORY STORE",
"Edinburgh Premium Outlets, 3026 Outlet Drive, Suite G - 040",
"Edinburgh, IN",
"IN",
"USA",
"46124",
false
]
],
"fields": [
{
"display_name": "Ticker Symbol",
"format": "ticker",
"metric": false,
"id": "dataset__entity__entity_ticker__ticker__ticker",
"length": 320,
"summary": "The full ticker symbol, defined as the financial market of the company, followed by a colon (:), and then the identifier of the company. ex. NASDAQ:AAPL",
"type": "string",
"options": []
},
{
"display_name": "Entity Name",
"format": null,
"metric": false,
"id": "dataset__entity__name",
"length": 255,
"summary": "The name of a specific entity belonging to a ticker within this dataset.",
"type": "string",
"options": []
},
...
{
"display_name": "Nearest Store #1",
"format": null,
"metric": false,
"id": "$nearest_1_1.rank",
"length": null,
"summary": "",
"type": "number",
"options": []
},
{
"display_name": "Nearest Ticker #1",
"format": null,
"metric": false,
"id": "$nearest_1_1.ticker",
"length": null,
"summary": "",
"type": "number",
"options": []
},
{
"display_name": "Nearest Entity #1",
"format": null,
"metric": false,
"id": "$nearest_1_1.entity",
"length": null,
"summary": "",
"type": "number",
"options": []
},
{
"display_name": "Nearest Distance #1",
"format": null,
"metric": true,
"id": "$nearest_1_1.dist",
"length": null,
"summary": "",
"type": "number",
"options": []
},
{
"display_name": "Nearest Store Name #1",
"format": null,
"metric": false,
"id": "$nearest_1_1.storefront_name",
"length": null,
"summary": "",
"type": "number",
"options": []
},
{
"display_name": "Nearest Store Street #1",
"format": null,
"metric": false,
"id": "$nearest_1_1.street",
"length": null,
"summary": "",
"type": "number",
"options": []
},
{
"display_name": "Nearest Store City #1",
"format": null,
"metric": false,
"id": "$nearest_1_1.city",
"length": null,
"summary": "",
"type": "number",
"options": []
},
{
"display_name": "Nearest Store State #1",
"format": null,
"metric": false,
"id": "$nearest_1_1.state",
"length": null,
"summary": "",
"type": "number",
"options": []
},
{
"display_name": "Nearest Store Country #1",
"format": null,
"metric": false,
"id": "$nearest_1_1.country",
"length": null,
"summary": "",
"type": "number",
"options": []
},
{
"display_name": "Nearest Store Postal Code #1",
"format": null,
"metric": false,
"id": "$nearest_1_1.postal_code",
"length": null,
"summary": "",
"type": "number",
"options": []
},
{
"display_name": "Nearest Store Is Closed #1",
"format": null,
"metric": false,
"id": "$nearest_1_1.is_closed",
"length": null,
"summary": "",
"type": "boolean",
"options": []
}
],
"sort_fields": [],
"start": 1,
"state": "complete",
"limit": 10,
"last_date_updated": "2021-03-26T16:00:35Z"
}
Sales Analyzer
This is a function that can be applied to "Car Inventory" dataset to see which cars have been sold. Since each vehicle has a unique identification number, users are able to see when a vehicle is added or removed. Tracking the number of vehicles leaving inventory allows users to predict sales figures
The sales function has the following parameters:
Parameter | Description | Required |
---|---|---|
lookahead_day_count | The number of days in the future that will be checked to see if same VIN returns | Yes |
For example, if you are analyzing the "Car Inventory" dataset, and you would like to see which car have been sold from Carvana, you can run the following query:
POST /dataset/store/query/ HTTP/1.1
Authorization: token 01234567890123456789
X-API-Version: 20151130
{
"tickers": [
"nyse:cvna"
],
"filters": [
{
"column": "as_of_date",
"type": "[]",
"value": [
"2021-01-01",
"2021-01-31"
]
}
],
"functions": [
{
"function": "sales",
"parameters": {
"lookahead_day_count": 2
}
}
]
}
curl -X POST "https://data.thinknum.com/datasets/store/query/" \
-H "Accept: application/json" \
-H "X-API-Version: 20151130" \
-H "Authorization: token 01234567890123456789" \
-d $'{
"tickers": [
"nyse:cvna"
],
"filters": [
{
"column": "as_of_date",
"type": "[]",
"value": [
"2021-01-01",
"2021-01-31"
]
}
],
"functions": [
{
"function": "sales",
"parameters": {
"lookahead_day_count": 2
}
}
]
}'
response = requests.post(
url='https://data.thinknum.com/datasets/store/query/',
headers={
'Authorization': 'token 01234567890123456789',
'X-API-Version': '20151130',
'Accept': 'application/json'
},
data=json.dumps({
"tickers": [
"nyse:cvna"
],
"filters": [
{
"column": "as_of_date",
"type": "[]",
"value": [
"2021-01-01",
"2021-01-31"
]
}
],
"functions": [
{
"function": "sales",
"parameters": {
"lookahead_day_count": 2
}
}
]
})
)
results = json.loads(response.text)
A sample response follows:
{
"state": "running",
"total": 0,
"id": "bb6a3c405cbe2fff1c5522892aecabf7a7a8b83549d3567ce16d4146cc930d23",
"formats": [
"application/vnd.thinknum.table+json"
]
}
To check if query is completed:
HEAD datasets/store/query/bb6a3c405cbe2fff1c5522892aecabf7a7a8b83549d3567ce16d4146cc930d23 HTTP/1.1
Authorization: token 01234567890123456789
X-API-Version: 20151130
Accept: application/vnd.thinknum.table+json
Content-Type: application/x-www-form-urlencoded; charset=utf-8
curl -I HEAD "https://data.thinknum.com/datasets/store/query/bb6a3c405cbe2fff1c5522892aecabf7a7a8b83549d3567ce16d4146cc930d23" \
-H "Accept: application/vnd.thinknum.table+json" \
-H "X-API-Version: 20151130" \
-H "Authorization: token 01234567890123456789"
response = requests.head(
url='https://data.thinknum.com/datasets/store/query/bb6a3c405cbe2fff1c5522892aecabf7a7a8b83549d3567ce16d4146cc930d23',
headers={
'Authorization': 'token 01234567890123456789',
'X-API-Version': '20151130',
'Accept': 'application/vnd.thinknum.table+json'
}
)
results = dict(response.headers)
A sample response follows:
HTTP/1.1 200 OK
Server: nginx
Date: Thu, 29 Apr 2021 17:53:59 GMT
Content-Type: application/json
Connection: keep-alive
X-Truncated: true
X-Formats: application/vnd.thinknum.table+json, text/csv
X-Total: 500000
X-State: complete
Strict-Transport-Security: max-age=15768000
To retrieve data:
GET /datasets/store/query/bb6a3c405cbe2fff1c5522892aecabf7a7a8b83549d3567ce16d4146cc930d23?limit=10&start=1
Authorization: token 01234567890123456789
X-API-Version: 20151130
Accept: application/vnd.thinknum.table+json
Content-Type: application/json
curl -X GET "https://data.thinknum.com/datasets/store/query/bb6a3c405cbe2fff1c5522892aecabf7a7a8b83549d3567ce16d4146cc930d23?limit=10&start=1" \
-H "Accept: application/vnd.thinknum.table+json" \
-H "Content-Type: application/json" \
-H "X-API-Version: 20151130" \
-H "Authorization: token 01234567890123456789"
response = requests.get(
url='https://data.thinknum.com/datasets/store/query/bb6a3c405cbe2fff1c5522892aecabf7a7a8b83549d3567ce16d4146cc930d23',
headers={
'Authorization': 'token 01234567890123456789',
'X-API-Version': '20151130',
'Accept': 'application/vnd.thinknum.table+json'
}
)
results = json.loads(response.text)
A sample response follows:
{
"group_fields": [
{
"length": 320,
"options": [],
"display_name": "Ticker Symbol",
"format": "ticker",
"metric": false,
"type": "string",
"id": "dataset__entity__entity_ticker__ticker__ticker",
"summary": "The full ticker symbol, defined as the financial market of the company, followed by a colon (:), and then the identifier of the company. ex. NASDAQ:AAPL"
},
...
{
"length": null,
"options": [],
"display_name": "Is Sold",
"format": null,
"metric": false,
"type": "boolean",
"id": "is_sold",
"summary": ""
},
{
"length": null,
"options": [],
"display_name": "Sold (2 Lookahead Days)",
"format": null,
"metric": false,
"type": "boolean",
"id": "$sales_1#sold",
"summary": ""
},
{
"length": null,
"options": [],
"display_name": "Days filled",
"format": null,
"metric": true,
"type": "number",
"id": "$sales_1#days_filled",
"summary": ""
},
{
"length": null,
"options": [],
"display_name": "Days since posted",
"format": null,
"metric": true,
"type": "number",
"id": "$sales_1#days_since_posted",
"summary": ""
}
],
"total": 500000,
"id": "58caab53e58c7a4affafb703cc693065cff94043f21b5ba7814fce0a575cd305",
"count": 10,
"rows": [
[
"nyse:cvna",
...
null,
false,
null,
89
],
...
[
"nyse:cvna",
...
null,
false,
null,
89
]
],
"fields": [
{
"display_name": "Ticker Symbol",
"format": "ticker",
"metric": false,
"id": "dataset__entity__entity_ticker__ticker__ticker",
"length": 320,
"summary": "The full ticker symbol, defined as the financial market of the company, followed by a colon (:), and then the identifier of the company. ex. NASDAQ:AAPL",
"type": "string",
"options": []
},
...
{
"display_name": "Is Sold",
"format": null,
"metric": false,
"id": "is_sold",
"length": null,
"summary": "",
"type": "boolean",
"options": []
},
{
"display_name": "Sold (2 Lookahead Days)",
"format": null,
"metric": false,
"id": "$sales_1#sold",
"length": null,
"summary": "",
"type": "boolean",
"options": []
},
{
"display_name": "Days filled",
"format": null,
"metric": true,
"id": "$sales_1#days_filled",
"length": null,
"summary": "",
"type": "number",
"options": []
},
{
"display_name": "Days since posted",
"format": null,
"metric": true,
"id": "$sales_1#days_since_posted",
"length": null,
"summary": "",
"type": "number",
"options": []
}
],
"sort_fields": [
{
"column": "as_of_date",
"order": "desc"
}
],
"start": 1,
"state": "complete",
"limit": 10,
"last_date_updated": "2021-04-25T00:07:33Z"
}
Updated over 3 years ago