💡API Reference

List of all companies covered

Gives you a list of the whole universe of companies available. No query parameters are required.

GEThttps://api.esganalytics.io/api/company/

Response

200

Default response

Body

*/*

idnumber

company_namestring

sectorstring

industrystring

gicSectorstring

gicGroupstring

gicIndustrystring

gicSubIndustrystring

urlstring

company_pulsenumber

Request

JavaScriptCurlPython

const response = await fetch('https://api.esganalytics.io/api/company/', {
    method: 'GET',
    headers: {},
});
const data = await response.json();

Response

200

[
  {
    "id": 0,
    "company_name": "text",
    "sector": "text",
    "industry": "text",
    "gicSector": "text",
    "gicGroup": "text",
    "gicIndustry": "text",
    "gicSubIndustry": "text",
    "url": "text",
    "company_pulse": 0
  }
]

Company Details

Query params: company_id or isin

Search by company id or ISIN

Gives you a summary company profile and ESG snapshot including:

• Company description and sector information

• Listed securities

• AI based ESG pulse and positive/negative ratio (how many instances have been + or - all time)

• Executive salaries and payments

• Activity involvement (e.g is the company involved in weapons manufacturing)

GEThttps://api.esganalytics.io/api/company/details/

Query parameters

Response

200

Default response

Body

*/*

company_detailarray of object

securitiesarray of object

executivesarray of object

all_executivesarray of object

indicatorsarray of object

Request

JavaScriptCurlPython

const response = await fetch('https://api.esganalytics.io/api/company/details/', {
    method: 'GET',
    headers: {},
});
const data = await response.json();

Response

200

{
  "company_detail": [
    {
      "id": 0,
      "company_name": "text",
      "description": "text",
      "gicSector": "text",
      "gicSubIndustry": "text",
      "company_pulse": 0,
      "pos_neg_ratio": [
        {
          "sentiment_rank": "text",
          "total": 0
        }
      ]
    }
  ],
  "securities": [
    {
      "exchange": "text",
      "exchange_id": 0,
      "code": "text",
      "securities_type": "text",
      "currency_code": "text"
    }
  ],
  "executives": [
    {
      "name": "text",
      "title": "text",
      "dob": "text",
      "salary": 0,
      "bonus": 0,
      "stock_awards": 0,
      "option_awards": 0,
      "non_equity_incentives": 0,
      "pension_and_deferred": 0,
      "other_comp": 0,
      "total_compensation": 0
    }
  ],
  "all_executives": [
    {
      "name": "text",
      "title": "text",
      "dob": "text",
      "salary": 0,
      "bonus": 0,
      "stock_awards": 0,
      "option_awards": 0,
      "non_equity_incentives": 0,
      "pension_and_deferred": 0,
      "other_comp": 0,
      "total_compensation": 0
    }
  ],
  "indicators": [
    {
      "Adult Activity": "text",
      "Alcohol": "text",
      "Animal Testing": "text",
      "Catholic Values": "text",
      "Controversial Weapons": "text",
      "Small Arms": "text",
      "Fur & Leather": "text",
      "Gambling": "text",
      "GMO": "text",
      "Military Contracts": "text",
      "Nuclear": "text",
      "Pesticides": "text",
      "Palm Oil": "text",
      "Coal": "text",
      "Tobacco": "text",
      "Gender Equality": "text",
      "Renewable Energy": "text",
      "Clean Oceans": "text",
      "Oil & Gas": "text",
      "Deforestation Financing": "text",
      "Deforestation": "text",
      "Prison Industry": "text",
      "Innovation": "text"
    }
  ]
}

Company Screening

Query params: company_id

Gives you company Activity involvement (e.g is the company involved in weapons manufacturing)

GEThttps://api.esganalytics.io/api/company/screening/

Query parameters

Response

200

Default response

Body

*/*

detailsarray of object

indicatorsarray of object

Request

JavaScriptCurlPython

const response = await fetch('https://api.esganalytics.io/api/company/screening/', {
    method: 'GET',
    headers: {},
});
const data = await response.json();

Response

200

{
  "details": [
    {
      "id": 0,
      "company_name": "text"
    }
  ],
  "indicators": [
    {
      "Adult Activity": "text",
      "Alcohol": "text",
      "Animal Testing": "text",
      "Catholic Values": "text",
      "Controversial Weapons": "text",
      "Small Arms": "text",
      "Fur & Leather": "text",
      "Gambling": "text",
      "GMO": "text",
      "Military Contracts": "text",
      "Nuclear": "text",
      "Pesticides": "text",
      "Palm Oil": "text",
      "Coal": "text",
      "Tobacco": "text",
      "Gender Equality": "text",
      "Renewable Energy": "text",
      "Clean Oceans": "text",
      "Oil & Gas": "text",
      "Deforestation Financing": "text",
      "Deforestation": "text",
      "Prison Industry": "text",
      "Innovation": "text"
    }
  ]
}

Company ESG Sentiment / ESG Pulse

Query Params: company_id, group by (week, month, year), filter_options

Gives you a time series of the ESG sentiment grouped by week month or year

Provides the stock price if available for easy comparison

You can filter this by ESG topic, if you do the structure of this field is an array, with the topics separated by commas e.g ["Business Model Resilience","Product Design & Lifecycle Management"]

Response - all based on group by fields:

• Sent_queryset - the overall ESG sentiment

• Filtered_queryset - the filtered ESG sentiment if filter options were used

• Stock_queryset - the stock price

GEThttps://api.esganalytics.io/api/company/sentiment/

Query parameters

Response

200

Default response

Body

*/*

sent_querysetarray of object

filtered_querysetarray of object

stock_querysetarray of object

Request

JavaScriptCurlPython

const response = await fetch('https://api.esganalytics.io/api/company/sentiment/?group_by=text', {
    method: 'GET',
    headers: {},
});
const data = await response.json();

Response

200

{
  "sent_queryset": [
    {
      "date": "text",
      "average_sentiment": 0,
      "sent_mov_avg": 0
    }
  ],
  "filtered_queryset": [
    {
      "date": "text",
      "filtered_average_sentiment": 0,
      "filtered_sent_mov_avg": 0
    }
  ],
  "stock_queryset": [
    {
      "date": "text",
      "price": 0
    }
  ]
}

External Scores

Query Params: Company_ID

Provides external scores and a correlation matrix + normalized scores

GEThttps://api.esganalytics.io/api/external/

Query parameters

Response

200

Default response

Body

*/*

detailsarray of object

correlationarray of array of array of array of array of number

Request

JavaScriptCurlPython

const response = await fetch('https://api.esganalytics.io/api/external/', {
    method: 'GET',
    headers: {},
});
const data = await response.json();

Response

200

{
  "details": [
    {
      "update_date": "text",
      "snp": 0,
      "snp_link": "text",
      "refinitiv": 0,
      "refinitiv_link": "text",
      "sustainalytics": 0,
      "sustainalytics_link": "text",
      "msci": "text",
      "msci_link": "text",
      "snp_norm": 0,
      "refinitiv_norm": 0,
      "sustainalytics_norm": 0,
      "msci_norm": 0
    }
  ],
  "correlation": [
    [
      [
        [
          [
            0
          ]
        ]
      ]
    ]
  ]
}

Industry Details

Query params: gicSector, time (optional)

Provides a list of companies in a given GIC sector and the total articles and overall sentiment

If no time filter, the data returned will be for all time. Alternatively, this can be for the last week, month or year (if companies do not have any data here then they will not be included)

GEThttps://api.esganalytics.io/api/company/sector-chart

Query parameters

Response

200

Default response

Body

*/*

sectorChartarray of object

Request

JavaScriptCurlPython

const response = await fetch('https://api.esganalytics.io/api/company/sector-chart?gicSector=text', {
    method: 'GET',
    headers: {},
});
const data = await response.json();

Response

200

{
  "sectorChart": [
    {
      "company_id": 0,
      "company_name": "text",
      "nlp_items": 0,
      "sent_avg": "text"
    }
  ]
}

ESG Event Feed / Snapshot

For the ESG Event Feed:

Query params - company_id, feed_type=mini

Allows you to get a feed of ESG events picked up by the AI algorithm for a company. This feed includes the headlines, links. You can further filter by sentiment score or esg_topic, or both. This is a paginated response

Optional Query params: sentiment_score (between -1 and 1), comparison (greater, less, or equal), esg_topics

Example: /api/company/nlp/company_id=190187&feed_type=mini&page=1&sentiment_score=0.1&comparison=greater&esg_topics=WATER+%26+WASTEWATER+MANAGEMENT

ESG Topics available:'GHG Emissions', 'Air Quality', 'Energy Management', 'Water & Wastewater Management', 'Waste & Hazardous Materials Management', 'Ecological Impacts', 'Product Design & Lifecycle Management', 'Business Model Resilience', 'Supply Chain Management', 'Materials Sourcing & Efficiency', 'Physical Impacts of Climate Change', 'Labor Practices', 'Employee Health & Safety', 'Employee Engagement, Diversity & Inclusion', 'Human Rights & Community Relations', 'Customer Privacy', 'Data Security', 'Access & Affordability', 'Product Quality & Safety', 'Customer Welfare', 'Selling Practices & Product Labeling', 'Business Ethics', 'Competitive Behavior', 'Management of the Legal & Regulatory Environment', 'Critical Incident Risk Management', 'Systemic Risk Management'

For an ESG snapshot vs industry

Query params - company_id, feed_type=flags

No filtering available - see Getting Started for an example

GEThttps://api.esganalytics.io/api/company/nlp/

Query parameters

Response

200

Default response

Body

*/*

countnumber

nextstring

previousstring

resultsobject

Request

JavaScriptCurlPython

const response = await fetch('https://api.esganalytics.io/api/company/nlp/?feed_type=text', {
    method: 'GET',
    headers: {},
});
const data = await response.json();

Response

200

{
  "count": 0,
  "next": "text",
  "previous": "text",
  "results": {
    "details": [
      {
        "id": 0,
        "company_name": "text"
      }
    ],
    "analysis": [
      {
        "id": 0,
        "published_at": "text",
        "title": "text",
        "source": "text",
        "source_fk": "text",
        "sentiment_score": 0,
        "sentiment_rank": "text",
        "esg_topics": [
          "text"
        ],
        "url": "text"
      }
    ]
  }
}

Industry and market ESG Feed

Query Params - feed_type (industry or recent)

Industry feed type = gives you a snapshot of ESG scores by GIC industry and historical time series

Recent feed type - gives you the latest ESG events across all companies as well as the current top 10 and bottom 10 companies

GEThttps://api.esganalytics.io/api/company/nlp/summary/

Query parameters

Response

200

Default response

Body

*/*

recentarray of object

top_pulsearray of object

bottom_pulsearray of object

Request

JavaScriptCurlPython

const response = await fetch('https://api.esganalytics.io/api/company/nlp/summary/', {
    method: 'GET',
    headers: {},
});
const data = await response.json();

Response

200

{
  "recent": [
    {
      "published_at": "text",
      "company_id_id": 0,
      "company_name": "text",
      "esg_topics": [
        "text"
      ],
      "title": "text",
      "sentiment_rank": "text"
    }
  ],
  "top_pulse": [
    {
      "company_id_id": 0,
      "company_name": "text",
      "average_sentiment": 0
    }
  ],
  "bottom_pulse": [
    {
      "company_id_id": 0,
      "company_name": "text",
      "average_sentiment": 0
    }
  ]
}

ESG Event Detail

Query params - id (from the ESG Event feed)

Provides the full text for any event that was picked up in company/NLP along with additional information

GEThttps://api.esganalytics.io/api/company/nlp/item/

Query parameters

Response

200

Default response

Body

*/*

idnumber

published_atstring

titlestring

sourcestring

source_fkstring

entitiesarray of object

full_textstring

sentiment_scorenumber

sentiment_rankstring

esg_topicsarray of string

company_namestring

company_idnumber

urlstring

Request

JavaScriptCurlPython

const response = await fetch('https://api.esganalytics.io/api/company/nlp/item/', {
    method: 'GET',
    headers: {},
});
const data = await response.json();

Response

200

[
  {
    "id": 0,
    "published_at": "text",
    "title": "text",
    "source": "text",
    "source_fk": "text",
    "entities": [
      {
        "end": 0,
        "type": "text",
        "start": 0
      }
    ],
    "full_text": "text",
    "sentiment_score": 0,
    "sentiment_rank": "text",
    "esg_topics": [
      "text"
    ],
    "company_name": "text",
    "company_id": 0,
    "url": "text"
  }
]

ESG Clustered Events (BETA)

Query params - company_id

Provides a summary of the clustered events (e.g articles that are similar, or from different sources) for a given company

GEThttps://api.esganalytics.io/api/company/nlp/events/

Response

200

Default response

Body

*/*

eventsarray of object

companies_number_of_eventsarray of object

Request

JavaScriptCurlPython

const response = await fetch('https://api.esganalytics.io/api/company/nlp/events/', {
    method: 'GET',
    headers: {},
});
const data = await response.json();

Response

200

{
  "events": [
    {
      "id": 0,
      "article_ids": [
        0
      ],
      "last_updated": "text",
      "first_updated": "text",
      "event_sentiment": "text",
      "event_name": "text",
      "count": 0
    }
  ],
  "companies_number_of_events": [
    {
      "number_of_events": 0
    }
  ]
}

ESG Clustered Event Detail

Query params - event_id

Provides detailed view for a specific clustered event

GEThttps://api.esganalytics.io/api/company/nlp/events/details/

Response

200

Default response

Body

*/*

analysisarray of object

Request

JavaScriptCurlPython

const response = await fetch('https://api.esganalytics.io/api/company/nlp/events/details/', {
    method: 'GET',
    headers: {},
});
const data = await response.json();

Response

200

{
  "analysis": [
    {
      "id": 0,
      "published_at": "text",
      "title": "text",
      "source": "text",
      "source_fk": "text",
      "sentiment_score": 0,
      "sentiment_rank": "text",
      "esg_topics": [
        "text"
      ],
      "url": "text"
    }
  ]
}

GET https://api.esganalytics.io/api/company/nlp/daily/

Query Parameters

Name	Type	Description
published_at	String	ISO Date for query

200: OK

{
    "count": 91,
    "next": "http://127.0.0.1:8001/api/company/nlp/daily/?page=2&published_at=2023-04-23",
    "previous": null,
    "results": {
        "details": "All flagged ESG relevant topics across universe for 2023-04-22 to 2023-04-23",
        "items": [
            {
                "id": 62215276,
                "published_at": "2023-04-22T23:30:00Z",
                "title": "ROSEN, A RESPECTED AND LEADING FIRM, Encourages Amgen Inc. Investors with Losses to Secure Counsel Before Important Deadline in Securities Class Action - AMGN",
                "tagged_sentences": [
                    {
                        "topic": "Selling Practices & Product Labeling",
                        "sentence": "According to the lawsuit, defendants throughout the Class Period made false and/or misleading statements and/or failed to disclose that: (1) the U.S. government claimed Amgen owed more than $3 billion in back taxes for tax years 2010, 2011, and 2012; (2) the U.S. government claimed Amgen owed more than $5 billion in back taxes for tax years 2013, 2014, and 2015; (3) the U.S. government would likely claim Amgen owed materially more to the U.S. government than investors had been led to believe for subsequent tax years for which the Company had used the same profit allocation treatment between its U.S. and Puerto Rico operations; (4) Amgen had not taken sufficient accruals to account for its outstanding tax liabilities; (5) Amgen had failed to comply with ASC 450 and other rules and regulations regarding the preparation of its periodic SEC filings; and (6) Amgen's refusal to pay taxes claimed by the U.S. government exposed the Company to a substantial risk of severe financial penalties imposed by the IRS.",
                        "esg_pulse": -0.9829
                    }
                ],
                "source": "PRNewswire",
                "source_fk": "",
                "sentiment_score": -0.9829,
                "sentiment_rank": "negative",
                "tagged_sent_topics": [
                    "Selling Practices & Product Labeling"
                ],
                "url": "https://www.prnewswire.com/news-releases/rosen-a-respected-and-leading-firm-encourages-amgen-inc-investors-with-losses-to-secure-counsel-before-important-deadline-in-securities-class-action--amgn-301804323.html"
            },
            {...}
            ]
        }    
{