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Dataset research report

Churn Prediction research report

A reproducible data report with schema notes, generated chart evidence, suggested follow-up questions, and export-ready Helix queries.

storageHf descriptionscikit-learn--churn-prediction.parquet view_list500 rows

Executive Summary

Customer churn prediction dataset of a fictional telecommunication company made by IBM Sample Datasets. Context Predict behavior to retain customers. You can analyze all relevant customer data and develop focused customer retention programs. Content Each row represents a customer, each column contains customer’s attributes described on the column metadata. The data set includes information about: Customers who left within the last month: the column is called Churn Services that each customer… See the full description on the dataset page: https://huggingface.co/datasets/scikit-learn/churn-prediction.

Finding 1The dataset has 500 rows available in the catalog.
Finding 2The catalog exposes 21 documented or inferred columns.
Finding 3Helix has 6 ready query prompts for this dataset.
Finding 4This report includes 5 generated chart views.

Research Context

Churn Prediction: 500 rows by 21 columns. These exploratory charts are generated automatically from the data - open the dataset in Helix to ask your own questions.

Data Profile

Rows500
Columns21
Numeric cols3
Categorical cols16

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.

Follow-Up Queries

Preview Rows

# customerIDtext gendertext SeniorCitizeninteger Partnertext Dependentstext tenureinteger PhoneServicetext MultipleLinestext
1 7590-VHVEGFemale0YesNo1NoNo phone service
2 5575-GNVDEMale0NoNo34YesNo
3 3668-QPYBKMale0NoNo2YesNo
4 7795-CFOCWMale0NoNo45NoNo phone service
5 9237-HQITUFemale0NoNo2YesNo
6 9305-CDSKCFemale0NoNo8YesYes

Data Dictionary

  • customerID text
  • gender categorical
  • SeniorCitizen numeric
  • Partner categorical
  • Dependents categorical
  • tenure numeric
  • PhoneService categorical
  • MultipleLines categorical
  • InternetService categorical
  • OnlineSecurity categorical
  • OnlineBackup categorical
  • DeviceProtection categorical
  • TechSupport categorical
  • StreamingTV categorical
  • StreamingMovies categorical
  • Contract categorical
  • PaperlessBilling categorical
  • PaymentMethod categorical
  • MonthlyCharges datetime
  • TotalCharges text
  • Churn categorical

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.

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