Introducing the Forecasts API — Event-driven forecasts for precise demand planning. Fast, accurate, and easy to run.
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  • Introduction
  • Swagger UI
  • Loop
  • System Status
  • Getting Started
    • API Quickstart
    • Data Science Notebooks
    • PredictHQ Data
      • Data Accuracy
      • Event Categories
        • Attendance-Based Events
        • Non-Attendance-Based Events
        • Unscheduled Events
        • Live TV Events
      • Labels
      • Entities
      • Ranks
        • PHQ Rank
        • Local Rank
        • Aviation Rank
      • Predicted Attendance
      • Predicted End Times
      • Predicted Event Spend
      • Predicted Events
      • Predicted Impact Patterns
    • Guides
      • Geolocation Guides
        • Overview
        • Searching by Location
          • Find Events by Latitude/Longitude and Radius
          • Find Events by Place ID
          • Find Events by IATA Code
          • Find Events by Country Code
          • Find Events by Placekey
          • Working with Location-Based Subscriptions
        • Understanding Place Hierarchies
        • Working with Polygons
        • Join Events using Placekey
      • Date and Time Guides
        • Working with Recurring Events
        • Working with Multi-day and Umbrella Events
        • Working with Dates, Times and Timezones
      • Events API Guides
        • Understanding Relevance Field in Event Results
        • Attendance-Based Events Notebooks
        • Non-Attendance-Based Events Notebooks
        • Severe Weather Events Notebooks
        • Academic Events Notebooks
        • Working with Venues Notebook
      • Features API Guides
        • Increase Accuracy with the Features API
        • Get ML Features
        • Demand Forecasting with Event Features
      • Forecasts API Guides
        • Getting Started with Forecasts API
        • Understanding Forecast Accuracy Metrics
        • Troubleshooting Guide for Forecasts API
      • Live TV Event Guides
        • Find Broadcasts by County Place ID
        • Find Broadcasts by Latitude and Longitude
        • Find all Broadcasts for an Event
        • Find Broadcasts for Specific Sport Types
        • Aggregating Live TV Events
        • Live TV Events Notebooks
      • Beam Guides
        • ML Features by Location
        • ML Features by Group
      • Demand Surge API Guides
        • Demand Surge Notebook
      • Guide to Protecting PredictHQ Data
      • Streamlit Demo Apps
      • Guide to Bulk Export Data via the WebApp
      • Industry-Specific Event Filters
      • Tutorials
        • Filtering and Finding Relevant Events
        • Improving Demand Forecasting Models with Event Features
        • Using Event Data in Power BI
        • Using Event Data in Tableau
        • Connecting to PredictHQ APIs with Microsoft Excel
        • Loading Event Data into a Data Warehouse
        • Displaying Events in a Heatmap Calendar
        • Displaying Events on a Map
    • Tutorials by Use Case
      • Demand Forecasting with ML Models
      • Dynamic Pricing
      • Inventory Management
      • Workforce Optimization
      • Visualization and Insights
  • Integrations
    • Integration Guides
      • Keep Data Updated via API
      • Integrate with Beam
      • Integrate with Loop Links
    • Third-Party Integrations
      • Receive Data via Snowflake
        • Example SQL Queries for Snowflake
        • Snowflake Data Science Guide
          • Snowpark Method Guide
          • SQL Method Guide
      • Receive Data via AWS Data Exchange
        • CSV/Parquet Data Structure for ADX
        • NDJSON Data Structure for ADX
      • Integrate with Databricks
      • Integrate with Tableau
      • Integrate with a Demand Forecast in PowerBI
      • Google Cloud BigQuery
    • PredictHQ SDKs
      • Python SDK
      • Javascript SDK
  • API Reference
    • API Overview
      • Authenticating
      • API Specs
      • Rate Limits
      • Pagination
      • API Changes
      • Attribution
      • Troubleshooting
    • Events
      • Search Events
      • Get Event Counts
    • Broadcasts
      • Search Broadcasts
      • Get Broadcasts Count
    • Features
      • Get ML Features
    • Forecasts
      • Models
        • Create Model
        • Update Model
        • Replace Model
        • Delete Model
        • Search Models
        • Get Model
        • Train Model
      • Demand Data
        • Upload Demand Data
        • Get Demand Data
      • Forecasts
        • Get Forecast
      • Algorithms
        • Get Algorithms
    • Beam
      • Create an Analysis
      • Upload Demand Data
      • Search Analyses
      • Get an Analysis
      • Update an Analysis
      • Partially Update an Analysis
      • Get Correlation Results
      • Get Feature Importance
      • Refresh an Analysis
      • Delete an Analysis
      • Analysis Groups
        • Create an Analysis Group
        • Get an Analysis Group
        • Search Analysis Groups
        • Update an Analysis Group
        • Partially Update an Analysis Group
        • Refresh an Analysis Group
        • Delete an Analysis Group
        • Get Feature Importance for an Analysis Group
    • Demand Surge
      • Get Demand Surges
    • Suggested Radius
      • Get Suggested Radius
    • Saved Locations
      • Create a Saved Location
      • Search Saved Locations
      • Get a Saved Location
      • Search Events for a Saved Location
      • Update a Saved Location
      • Delete a Saved Location
    • Loop
      • Loop Links
        • Create a Loop Link
        • Search Loop Links
        • Get a Loop Link
        • Update a Loop Link
        • Delete a Loop Link
      • Loop Settings
        • Get Loop Settings
        • Update Loop Settings
      • Loop Submissions
        • Search Submitted Events
      • Loop Feedback
        • Search Feedback
    • Places
      • Search Places
      • Get Place Hierarchies
  • WebApp Support
    • WebApp Overview
      • Using the WebApp
      • API Tools
      • Events Search
      • How to Create an API Token
    • Getting Started
      • Can I Give PredictHQ a Go on a Free Trial Basis?
      • How Do I Get in Touch if I Need Help?
      • Using AWS Data Exchange to Access PredictHQ Events Data
      • Using Snowflake to Access PredictHQ Events Data
      • What Happens at the End of My Free Trial?
      • Export Events Data from the WebApp
    • Account Management
      • Managing your Account Settings
      • How Do I Change My Name in My Account?
      • How Do I Change My Password?
      • How Do I Delete My Account?
      • How Do I Invite People Into My Organization?
      • How Do I Log In With My Google or LinkedIn Account?
      • How Do I Update My Email Address?
      • I Signed Up Using My Google/LinkedIn Account, but I Want To Log In With My Own Email
    • API Plans, Pricing & Billing
      • Do I Need To Provide Credit Card Details for the 14-Day Trial?
      • How Do I Cancel My API Subscription?
      • Learn About Our 14-Day Trial
      • What Are the Definitions for "Storing" and "Caching"?
      • What Attribution Do I Have To Give PredictHQ?
      • What Does "Commercial Use" Mean?
      • What Happens If I Go Over My API Plan's Rate Limit?
    • FAQ
      • How Does PredictHQ Support Placekey?
      • Using Power BI and Tableau With PredictHQ Data
      • Can I Download a CSV of Your Data?
      • Can I Suggest a New Event Category?
      • Does PredictHQ Have Historical Event Data?
      • Is There a PredictHQ Mobile App?
      • What Are Labels?
      • What Countries Do You Have School Holidays For?
      • What Do The Different Event Ranks Mean?
      • What Does Event Visibility Window Mean?
      • What Is the Difference Between an Observed Holiday and an Observance?
    • Tools
      • Is PHQ Attendance Available for All Categories?
      • See Event Trends in the WebApp
      • What is Event Trends?
      • Live TV Events
        • What is Live TV Events?
        • Can You Access Live TV Events via the WebApp?
        • How Do I Integrate Live TV Events into Forecasting Models?
      • Labels
        • What Does the Closed-Doors Label Mean?
    • Beam (Relevancy Engine)
      • An Overview of Beam - Relevancy Engine
      • Creating an Analysis in Beam
      • Uploading Your Demand Data to Beam
      • Viewing the List of Analysis in Beam
      • Viewing the Table of Results in Beam
      • Viewing the Category Importance Information in Beam
      • Feature Importance With Beam - Find the ML Features to Use in Your Forecasts
      • Beam Value Quantification
      • Exporting Correlation Data With Beam
      • Getting More Details on a Date on the Beam Graph
      • Grouping Analyses in Beam
      • Using the Beam Graph
      • Viewing the Time Series Impact Analysis in Beam
    • Location Insights
      • An Overview of Location Insights
      • How to Set a Default Location
      • How Do I Add a Location?
      • How Do I Edit a Location?
      • How Do I Share Location Insights With My Team?
      • How Do I View Details for One Location?
      • How Do I View My Saved Locations as a List?
      • Search and View Event Impact in Location Insights
      • What Do Each of the Columns Mean?
      • What Is the Difference Between Center Point & Radius and City, State, Country?
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  1. Integrations
  2. Third-Party Integrations
  3. Receive Data via AWS Data Exchange

CSV/Parquet Data Structure for ADX

Data can be provided as NDJSON, CSV or Parquet. This document describes the CSV/Parquet data structure.

Field
Description

EVENT_ID

The unique identifier of the event.

CREATE_DT

The date and time the event was first seen by PredictHQ in UTC. Also called first_seen in the Events API.

UPDATE_DT

The date and time the event was last updated in UTC.

TITLE

The title of the event.

CATEGORY

The category of the event.

LABELS

DESCRIPTION

The description of the event.

EVENT_START

The date and time the event starts, recorded in UTC. If the TIMEZONE field is null, the time represents the same relative time across all timezones.

Additionally, if an event has a start time of midnight in its local timezone, this may indicate that the actual time is unknown. You may wish to omit the time when displaying such events.

EVENT_END

The date and time the event ends, recorded in UTC. If the TIMEZONE field is null, the time represents the same relative time across all timezones.

PREDICTED_END

The date and time PredictHQ predicts the event will end, recorded in UTC. If the TIMEZONE field is null, the time represents the same relative time across all timezones. This value is present where an actual EVENT_END is unknown.

TIMEZONE

The time zone of the event in TZ Database format. This is helpful so you know which time zone to convert the dates to (if needed). If the time zone is null, the start and end date should be regarded as time zone agnostic and already being in local time.

ENTITIES

GEO

IMPACT_PATTERNS

SCOPE

The geographical scope the events apply to. Possible values are:

  • locality

  • localadmin

  • county

  • region

  • country

PLACEKEY

COUNTRY_CODE

The country code in ISO 3166-1 alpha 2 format. This value is typically present, but in some cases such as events occurring outside any country (e.g. an earthquake in the middle of the ocean), it may be empty.

PLACE_HIERARCHIES

An array of place hierarchies for the event. Each hierarchy is an array of place ids. The final place in a hierarchy is a specific place the event applies to. Each place is a sub-place of the place immediately preceding it in the hierarchy. An empty array is possible and valid.

PHQ_ATTENDANCE

A numerical value that reflects the predicted attendance for supported attendance-based categories. Supported categories include concerts, performing arts, sports, expos, conferences, community, and festivals. Some academic and school holiday events may also include a phq_attendance value to indicate student numbers.

For multi-day events, phq_attendance represents total attendance across the entire duration, except for certain categories like conferences, where it reflects daily attendance.

PHQ_RANK

A log scale numerical value between 0 and 100 with a five-level hierarchical impact schema. It is designed to represent the potential impact of an event independent of its geographical location.

LOCAL_RANK

Similar to PHQ Rank, this is a log scale numerical value between 0 and 100 with a five-level hierarchical impact schema. It is designed to represent the potential impact of an event on its local geographical area.

Local Rank is calculated for events in the categories community, concerts, conferences, expos, sports, festivals, performing-arts. If local_rank is not intended to be available for an event, this field will be null.

AVIATION_RANK

A log scale numerical value between 0 and 100 with a five-level hierarchical impact schema. Aviation Rank indicates how much an event will impact flight bookings by considering both domestic and international travel.

STATUS

The publication state of the event.

Possible values:

  • active - The event is an active event.

  • postponed - The event is a postponed event, and is expected to occur at a later date.

  • cancelled - The event is a cancelled event and is not expected to occur at a later date.

BRAND_SAFE

Whether or not this event is considered brand-safe. Examples of brand-unsafe events include content that promotes hate, violence, or discrimination, coarse language, content that is sexually suggestive or explicit, etc.

PARENT_EVENT_ID

CANCELLED_DT

The date and time the event was marked as cancelled, presented in the UTC timezone. This field will be null if STATUS is not set to "cancelled" or if the cancellation date is unavailable.

POSTPONED_DT

The date and time the event was marked as postponed, presented in the UTC timezone. This field will be null if STATUS is not set to "postponed" or if the postponement date is unavailable. Note that this field does not represent the new date and time of the postponed event.

PREDICTED_EVENT_SPEND_ACCOMMODATION

PREDICTED_EVENT_SPEND_HOSPITALITY

PREDICTED_EVENT_SPEND_TRANSPORTATION

PHQ_LABELS

ALTERNATE_IDS

All alternate IDs for the event. Any event IDs that may have been used for this event in the past will be included here. It does not include the current event ID.

EVENT_START_LOCAL

The date and time when the event begins, expressed in the event's local time zone.

EVENT_END_LOCAL

The date and time when the event ends, expressed in the event's local time zone.

PREDICTED_END_LOCAL

The date and time when the event is predicted to end, expressed in the event's local time zone.

REGION

The region in which the event will be occurring. This field will be null if the event covers more than a single region.

LOCALITY

The locality in which the event will be occurring. A locality is most commonly referred to as a city or town. This field will be null if the event covers more than a single locality.

POSTCODE

The postal code or ZIP code in which the event will be occurring. This field will be null if the event covers more than a single post code.

FORMATTED_ADDRESS

A full formatted address which can include street addresses, locality, postcode, region, and country.

ROW_INSERTED_DT

The date and time this row was inserted in UTC. The row may have been deleted and inserted multiple times so it does not reflect when an event is first seen, use CREATE_DT for that.

ROW_UPDATED_DT

The date and time this row was last updated in UTC.

CHANGE_ACTION

Indicates if the record has been updated, deleted or inserted. Use when processing the data file to keep your database updated.

Possible values:

  • insert - new record, not previously seen.

  • update - existing record, updated values.

  • delete - deleted record, remove from your dataset.

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The labels associated with the event. The LABELS field is representing PredictHQ's legacy labels, and it's suggested to use the PHQ_LABELS field instead where possible. See also our docs.

An array of entities linked to the event. This is a complex data type, please see for details.

The geographic details (location) of the event in GeoJSON format. See for more information on handling GEO data.

Also known as “Predicted Impact Patterns”. This field shows impact for leading days (days before the event), lagging days (days after an event) and the days the event occurs. It contains details such as the industry vertical the impact pattern applies to, the type of impact shown in the impact pattern, and an array of objects for each day showing the date in the local timezone of the event and the value of the impact_type for that given day. See also our docs.

The Placekey identifier for the physical address where the event takes place. See . This field will be null if the "What" part or the "Where" part of the Placekey for the event address couldn't be retrieved.

See also the .

For details see our .

See also our .

See also our .

Aviation Rank is no longer actively supported. For more information, see the .

predicted - The event is a predicted event. For details, see our .

Used to indicate if this event is part of a larger event. These types of events are called umbrella events in the system. For example, a large multi-day parent umbrella event may have individual child events for sessions on different days. This field only shows if a child event has a parent id. It does not indicate if a parent event has child events. For details see our .

The total predicted event spend for the accommodation industry. This field will be null if the predicted event spend is not supported for this event. See also our docs.

The total predicted event spend for the hospitality industry. This field will be null if the predicted event spend is not supported for this event. See also our docs.

The total predicted event spend for the transportation industry. This field will be null if the predicted event spend is not supported for this event. See also our docs.

The PHQ Labels associated with the event. This field will be null if there are no PHQ Labels for this event. See also our docs.

Labels
Events API
geolocation guides
Impact Patterns
Placekey
Place Hierarchies guide
Predicted Attendance guide
PHQ Rank docs
Local Rank docs
Aviation Rank docs
Predicted Events page
Umbrella Events docs
Predicted Event Spend
Predicted Event Spend
Predicted Event Spend
Labels