Dataset research report
Speeddating research report
A reproducible data report with schema notes, generated chart evidence, suggested follow-up questions, and export-ready Helix queries.
Executive Summary
Speed dating The Speed dating dataset from OpenML. Configurations and tasks Configuration Task Description dating Binary classification Will the two date? Usage from datasets import load_dataset dataset = load_dataset("mstz/speeddating")["train"] Features Features Type is_dater_male int8 dater_age int8 dated_age int8 age_difference int8 dater_race string dated_race string are_same_race int8… See the full description on the dataset page: https://huggingface.co/datasets/mstz/speeddating.
Research Context
Speeddating: 500 rows by 65 columns. These exploratory charts are generated automatically from the data - open the dataset in Helix to ask your own questions.
Data Profile
Chart Evidence
These views are generated from the dataset profile. Each chart is paired with a Helix query so it can be opened, adjusted, and exported.
Total dater_age by is_dater_male
Top is_dater_male values ranked by summed dater_age.
Open and export this chartdater_age vs dated_age
dater_age vs dated_age, coloured by is_dater_male.
Open and export this chartCorrelation of numeric columns
Pearson correlation between numeric columns.
Open and export this chartdater_age by is_dater_male
Spread of dater_age across is_dater_male groups.
Open and export this chartFollow-Up Queries
Preview Rows
| # | is_dater_maleboolean | dater_ageinteger | dated_ageinteger | age_differenceinteger | dater_racetext | dated_racetext | are_same_raceboolean | same_race_importance_for_daterfloat |
|---|---|---|---|---|---|---|---|---|
| 1 | False | 21 | 27 | 6 | 'Asian/Pacific Islander/Asian-American' | caucasian | False | 2 |
| 2 | False | 21 | 22 | 1 | 'Asian/Pacific Islander/Asian-American' | caucasian | False | 2 |
| 3 | False | 21 | 23 | 2 | 'Asian/Pacific Islander/Asian-American' | caucasian | False | 2 |
| 4 | False | 21 | 24 | 3 | 'Asian/Pacific Islander/Asian-American' | 'Latino/Hispanic American' | False | 2 |
| 5 | False | 21 | 25 | 4 | 'Asian/Pacific Islander/Asian-American' | caucasian | False | 2 |
| 6 | False | 21 | 30 | 9 | 'Asian/Pacific Islander/Asian-American' | caucasian | False | 2 |
Data Dictionary
- is_dater_male datetime
- dater_age datetime
- dated_age datetime
- age_difference numeric
- dater_race datetime
- dated_race datetime
- are_same_race bool
- same_race_importance_for_dater datetime
- same_religion_importance_for_dater datetime
- attractiveness_importance_for_dated datetime
- sincerity_importance_for_dated datetime
- intelligence_importance_for_dated datetime
- humor_importance_for_dated datetime
- ambition_importance_for_dated datetime
- shared_interests_importance_for_dated datetime
- attractiveness_score_of_dater_from_dated datetime
- sincerity_score_of_dater_from_dated datetime
- intelligence_score_of_dater_from_dated datetime
- humor_score_of_dater_from_dated datetime
- ambition_score_of_dater_from_dated datetime
- shared_interests_score_of_dater_from_dated datetime
- attractiveness_importance_for_dater datetime
- sincerity_importance_for_dater datetime
- intelligence_importance_for_dater datetime
- humor_importance_for_dater datetime
- ambition_importance_for_dater datetime
- shared_interests_importance_for_dater datetime
- self_reported_attractiveness_of_dater datetime
- self_reported_sincerity_of_dater datetime
- self_reported_intelligence_of_dater datetime
- self_reported_humor_of_dater datetime
- self_reported_ambition_of_dater datetime
- reported_attractiveness_of_dated_from_dater datetime
- reported_sincerity_of_dated_from_dater datetime
- reported_intelligence_of_dated_from_dater datetime
- reported_humor_of_dated_from_dater datetime
- reported_ambition_of_dated_from_dater datetime
- reported_shared_interests_of_dated_from_dater datetime
- dater_interest_in_sports datetime
- dater_interest_in_tvsports datetime
- dater_interest_in_exercise datetime
- dater_interest_in_dining datetime
- dater_interest_in_museums datetime
- dater_interest_in_art datetime
- dater_interest_in_hiking datetime
- dater_interest_in_gaming datetime
- dater_interest_in_clubbing datetime
- dater_interest_in_reading datetime
- dater_interest_in_tv datetime
- dater_interest_in_theater datetime
- dater_interest_in_movies datetime
- dater_interest_in_concerts datetime
- dater_interest_in_music datetime
- dater_interest_in_shopping datetime
- dater_interest_in_yoga datetime
- interests_correlation numeric
- expected_satisfaction_of_dater datetime
- expected_number_of_likes_of_dater_from_20_people datetime
- expected_number_of_dates_for_dater datetime
- dater_liked_dated datetime
- probability_dated_wants_to_date datetime
- already_met_before bool
- dater_wants_to_date datetime
- dated_wants_to_date datetime
- is_match numeric
Method And Limits
- Load the catalog entry and preview rows from the processed dataset file.
- Infer numeric, categorical, time, and location fields from real columns.
- Generate a small set of defensive Plotly chart specifications from that profile.
- Expose each chart idea as a query link so the report can be rerun or exported in Helix.
This report is intentionally reproducible. It uses the local catalog metadata and generated chart specifications rather than claiming external conclusions beyond the dataset.