Sentiment

The following endpoints retrieves the daily Sentiment of entities.

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Quotient Ts

Returns the Sentiment timeseries of an entity. Is is calculated as the Quotient of Positive and all mentions of that company.

Sentiment = (Positive + 1) / (Positive + Negative + 2).

Examples

Curl

Note: If you are using Windows, adjust the syntax:

• Replace line breaks (\) with caret (^).
• Use double quotes (") instead of single quotes (').

curl -X 'GET' \
  'https://data.api.yukkalab.com/9-3-5/2023-12-13-0/api/company/apple/quotient_ts?date_from=2024-07-01&date_to=2024-07-05&period=1' \
  -H 'accept: application/json' \
  -H "Authorization: Bearer $YUKKA_TOKEN"

Return type

JSON

Example Response

{"quotient_ts":[{"quotient":0.6909361069836553,"date":"2024-07-01"},{"quotient":0.7656543939801129,"date":"2024-07-02"},{"quotient":0.7824267782426778,"date":"2024-07-03"},{"quotient":0.7459407831900668,"date":"2024-07-04"}],"used_cache":true,"cache_key":"auto_cache_quotient_ts_20ab5f5bd5449493fbded00c779c03ceac6cd7544465dfc2fe4bdf8f627c882c"}

Python

import requests
import os
import pandas as pd

# getting the data
headers = {'Authorization': f'Bearer {os.environ["YUKKA_TOKEN"]}'}
url = f'https://data.api.yukkalab.com/9-3-5/2023-12-13-0/api/company/apple/quotient_ts?date_from=2024-07-01&date_to=2024-07-05&period=1'
data = requests.get(url, headers=headers).json()

# transform into dataframe:
df = pd.DataFrame(data['quotient_ts'])
print(df)

Return type

pd.DataFrame(columns=[date, quotient])

Example Response

   quotient        date
0  0.690936  2024-07-01
1  0.765654  2024-07-02
2  0.782427  2024-07-03
3  0.745941  2024-07-04

Parameters

Name	Type	Description	Notes
date_from	date	Date to start from when using time ranges	[optional]
date_to	date	Date to end from (exclusively) when using time ranges	[optional]
period	date	Rolling average period for the sentiment	[optional][default to 4]
default_time_back	str	Default period of time that is used when no end date is supplied	[optional][default to 1w;]

Authorization

JSON Web Token. Issued by Yukka.

HTTP request headers

• Content-Type: Not defined
• Accept: application/json

HTTP response details

Status code	Description	Response headers
200	Successful Response	-
422	Validation Error	-

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Quotient Ts Itemized

Returns the Sentiment timeseries of multiple entities

Example

Curl

Note: If you are using Windows, adjust the syntax:

• Replace line breaks (\) with caret (^).
• Use double quotes (") instead of single quotes (').

curl -X 'POST' \
  'https://data.api.yukkalab.com/9-3-5/2023-12-13-0/v2/api/portfolio/quotient_ts_itemized?date_from=2024-07-01&date_to=2024-07-05&period=1' \
  -H 'accept: application/json' \
  -H "Authorization: Bearer $YUKKA_TOKEN" \
  -d '["company:apple", "company:sap"]'

Return type

JSON

Example Response

{"quotient_ts_itemized":[{"entity_info":{"type":"company","alpha_id":"apple","compound_key":"company:apple"},"quotient_ts":[{"quotient":0.6909361069836553,"date":"2024-07-01"},{"quotient":0.7656543939801129,"date":"2024-07-02"},{"quotient":0.7824267782426778,"date":"2024-07-03"},{"quotient":0.7459407831900668,"date":"2024-07-04"}]},{"entity_info":{"type":"company","alpha_id":"sap","compound_key":"company:sap"},"quotient_ts":[{"quotient":0.9111111111111111,"date":"2024-07-01"},{"quotient":0.9479166666666666,"date":"2024-07-02"},{"quotient":0.9361702127659575,"date":"2024-07-03"},{"quotient":0.8552631578947368,"date":"2024-07-04"}]}],"used_cache":false,"cache_key":"auto_cache_quotient_ts_itemized_v2_f4e4ee2d3026850fbe4b49828d42ffabd54dad036bcc0ff0058522f52c01236f","last_updated":"2024-07-25T09:14:56.533777+00:00"}

Python

import requests
import os
import pandas as pd

# getting the data
headers = {'Authorization': f'Bearer {os.environ["YUKKA_TOKEN"]}'}
url = f'https://data.api.yukkalab.com/9-3-5/2023-12-13-0/v2/api/portfolio/quotient_ts_itemized?date_from=2024-07-01&date_to=2024-07-05&period=1'
json_data = ['company:apple', "company:sap"]
data = requests.post(url, headers=headers, json=json_data).json()

# transform into dict of dataframes:
results = {}
for events in data['quotient_ts_itemized']:
    df = pd.DataFrame(events['quotient_ts'])
    results[events['entity_info']['compound_key']] = df
print(results)

Return type

Dict[str, pd.DataFrame(columns=[date, quotient])]

Example Response

{'company:apple':
   quotient        date
0  0.690936  2024-07-01
1  0.765654  2024-07-02
2  0.782427  2024-07-03
3  0.745941  2024-07-04, 
'company:sap': 
   quotient        date
0  0.911111  2024-07-01
1  0.947917  2024-07-02
2  0.936170  2024-07-03
3  0.855263  2024-07-04}

Parameters

Name	Type	Description	Notes
date_from	date	Date to start from when using time ranges	[optional]
date_to	date	Date to end from (exclusively) when using time ranges	[optional]
period	date	Rolling average period for the sentiment	[optional][default to 4]
default_time_back	str	Default period of time that is used when no end date is supplied	[optional][default to 1w]

Authorization

JSON Web Token. Issued by Yukka.

HTTP request headers

• Content-Type: Not defined
• Accept: application/json

HTTP response details

Status code	Description	Response headers
200	Successful Response	-
422	Validation Error	-

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