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wordpress-booking-appointment-plugins-market-intelligence-sample

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metadata 
language:
  - en
license: cc-by-4.0
size_categories:
  - n<1K
task_categories:
  - tabular-classification
tags:
  - pandas
  - dataframe
  - generated
  - tabular
  - wordpress
  - wordpress-plugins
  - booking
  - appointments
  - reservations
  - market-research
  - competitive-intelligence
  - pricing-research
  - non-government-data
pretty_name: >-
  WordPress Booking & Appointment Plugins Market Intelligence Dataset (Free
  Sample)
configs:
  - config_name: default
    data_files:
      - split: data
        path: data/data.parquet

WordPress Booking & Appointment Plugins Market Intelligence Dataset -- Free Evaluation Sample

This dataset packages public WordPress.org plugin-directory records for booking, appointment, and reservation plugins into one analysis-ready market-intelligence table.

Each row represents one WordPress plugin enriched with install and rating metrics, update recency, support-resolution signals, commercial-language flags, booking-workflow feature flags, buyer-segment heuristics, and normalized source metadata. The result is easier to use for plugin market research, agency stack comparisons, competitive intelligence, and buyer workflow analysis than manually collecting overlapping WordPress directory results by hand.

This repository contains a 60-row free evaluation sample of the full 607-row production dataset.

The sample is fully open and loadable without authentication so you can inspect the schema, explore features, and validate quality before purchasing.

Full Production Dataset

This public repository is a 60-row evaluation sample. The full production-grade dataset contains 607 rows across 74 columns.

After purchase, provide your Hugging Face username and request access on the full dataset page.

Machine Learning and Analysis Use Cases

This dataset is a rich tabular and natural-language playground suitable for:

  • Text Classification: Use text columns like record_id to predict categorical targets such as plugin_slug.
  • Tabular Regression / Classification: Predict requires_plugins_count or plugin_age_days using the other numeric and categorical features.
  • NLP Feature Extraction: Extract embeddings or features from text columns like record_id for downstream tasks.
  • Exploratory Data Analysis: Filter, pivot, and visualize across all columns in pandas, Excel, or any BI tool.

Dataset Structure

  • Rows: 60
  • Columns: 74
  • Split: data
  • File: data/data.parquet

Column Descriptions

  • record_id: Stable unique identifier for the row derived from the WordPress plugin slug.
  • plugin_slug: WordPress.org plugin slug used as the canonical plugin identifier.
  • plugin_name: Human-readable plugin name from the public directory record.
  • plugin_version: Latest plugin version listed in the public WordPress.org API response.
  • author_name: Normalized plugin author name parsed from the API response.
  • author_profile_url: WordPress.org author profile URL when provided by the source API.
  • author_profile_username: Best-effort WordPress.org username extracted from the author profile URL.
  • requires_wordpress_version: Minimum WordPress version listed by the plugin record.
  • tested_wordpress_version: Most recent WordPress version the plugin author reports testing against.
  • requires_php_version: Minimum PHP version listed by the plugin record.
  • requires_plugins: Pipe-delimited list of required companion plugins reported by the API.
  • requires_plugins_count: Number of required companion plugins reported by the API.
  • plugin_added_at: Timestamp when the plugin was first added to the WordPress.org directory.
  • last_updated_at: Timestamp when the plugin record was most recently updated according to the source API.
  • plugin_age_days: Number of days between plugin_added_at and the collection timestamp.
  • days_since_update: Number of days between last_updated_at and the collection timestamp.
  • is_recently_updated_30d: Boolean flag indicating that the plugin was updated within 30 days at collection time.
  • active_installs: Active install count from the public WordPress.org plugin API.
  • downloaded_total: Total historical download count from the public WordPress.org plugin API.
  • active_install_rank: Descending rank of active_installs within this dataset build.
  • download_rank: Descending rank of downloaded_total within this dataset build.
  • install_tier: Best-effort bucket describing plugin adoption level based on active installs.
  • rating_pct: Average user rating expressed as a percentage out of 100 in the source API.
  • rating_score_5pt: Average rating converted into a 5-point scale.
  • num_ratings: Total number of user ratings recorded by the plugin directory.
  • rating_5_count: Count of 5-star ratings from the source API.
  • rating_1_count: Count of 1-star ratings from the source API.
  • five_star_share_pct: Percentage of ratings that are 5-star when num_ratings is available.
  • support_threads_open: Open or unresolved support-thread count reported by the source API.
  • support_threads_resolved: Resolved support-thread count reported by the source API.
  • support_resolution_rate: Resolved support-thread share computed from the two support-thread metrics when possible.
  • short_description_plain: Normalized plain-text short description from the plugin directory.
  • description_plain: Normalized plain-text long description from the plugin directory HTML content.
  • description_word_count: Word count of description_plain after normalization.
  • tag_list: Pipe-delimited list of plugin tags returned by the public API.
  • tag_count: Number of tags attached to the plugin record.
  • matched_query_terms: Pipe-delimited list of search terms that surfaced this plugin during collection.
  • matched_query_term_count: Count of matched search terms associated with the plugin.
  • primary_query_term: First matching collection query term in the configured search-term priority order.
  • scope_keyword_count: Count of booking-market scope keyword groups detected in the plugin text.
  • has_payments_features: Boolean flag indicating payment collection, deposit, or invoicing language.
  • has_google_calendar_sync: Boolean flag indicating Google Calendar, iCal, or calendar-sync language.
  • has_staff_management: Boolean flag indicating staff, employee, or team-booking language.
  • has_sms_reminders: Boolean flag indicating SMS, text reminders, or Twilio language.
  • has_email_reminders: Boolean flag indicating email reminder or notification language.
  • has_recurring_bookings: Boolean flag indicating recurring or repeat-booking language.
  • has_group_bookings: Boolean flag indicating class, capacity, or group-booking language.
  • has_waitlist_features: Boolean flag indicating waitlist language.
  • has_zoom_virtual_meeting_features: Boolean flag indicating Zoom, Google Meet, Webex, or virtual-meeting language.
  • has_woocommerce_features: Boolean flag indicating WooCommerce or ecommerce-booking language.
  • has_events_ticketing_features: Boolean flag indicating event-booking or ticketing language.
  • has_rental_accommodation_features: Boolean flag indicating rentals, hotels, room reservations, or accommodation language.
  • has_restaurant_reservation_features: Boolean flag indicating restaurant or table-reservation language.
  • has_healthcare_clinic_features: Boolean flag indicating clinic, patient, medical, therapy, or telehealth language.
  • has_membership_package_features: Boolean flag indicating package, pass, membership, or subscription language relevant to appointments.
  • has_multilocation_features: Boolean flag indicating multiple-location or branch language.
  • has_mobile_app_features: Boolean flag indicating mobile-app or push-notification language.
  • has_form_builder_features: Boolean flag indicating form-builder integration language.
  • has_webhook_automation_features: Boolean flag indicating webhook, Zapier, Make, or automation language.
  • has_commercial_terms: Boolean flag indicating premium, pro, paid, upgrade, add-on, or pricing language.
  • feature_flag_count: Count of derived booking-workflow boolean feature flags that evaluated to true for the plugin.
  • primary_booking_segment: Best-effort primary booking-market segment inferred from the plugin text.
  • monetization_signal: Best-effort commercial model label inferred from plugin text and homepage metadata.
  • market_signal_score: Heuristic 0-100 score combining installs, ratings, feature depth, recency, and commercial signals.
  • plugin_directory_url: Canonical WordPress.org plugin-directory URL for the plugin.
  • homepage_url: Homepage URL reported by the plugin API, which may point to WordPress.org or an external vendor site.
  • homepage_domain: Normalized homepage domain parsed from homepage_url when available.
  • download_link: Direct download ZIP URL reported by the source API.
  • icon_1x_url: Primary plugin icon URL when provided by the source API.
  • icon_2x_url: Higher-resolution plugin icon URL when provided by the source API.
  • source_api_url: Reproducible WordPress.org API URL pattern for retrieving plugin_information by slug.
  • source_url: Top-level public source page used for collection.
  • source_domain: Source domain used for collection.
  • last_collected_at: Timestamp when this dataset run collected and normalized the row.

Loading the Dataset 

from datasets import load_dataset

dataset = load_dataset("Karmane/wordpress-booking-appointment-plugins-market-intelligence-sample")
print(dataset)
print(dataset["data"][0])

# Get as a pandas DataFrame
# df = dataset["data"].to_pandas()

Intended Use

This dataset is intended for research, experimentation, analysis, model prototyping, dashboard building, and market research.

Karmane. (2025). WordPress Booking & Appointment Plugins Market Intelligence Dataset (Free Sample). Hugging Face. https://huggingface.co/datasets/Karmane/wordpress-booking-appointment-plugins-market-intelligence-sample