docs: update dataset information

README.md

@@ -1,3 +1,36 @@
----
-license: ecl-2.0
----
+---
+license: ecl-2.0
+task_categories:
+- text-classification
+language:
+- en
+tags:
+- public
+- text
+- tabular
+- customer-churn-analysis
+- education
+pretty_name: Teclo Churn 7k
+size_categories:
+- 1K<n<10K
+---
+
+# Telco Churn 7k
+
+A 7,043-row customer-retention dataset drawn from a U.S. telecom provider. Each record profiles one account with 21 concise attributes and a **Churn** flag (*Yes* / *No*) indicating whether the customer left within the last month. The schema is:
+
+- **customerID** – unique subscriber identifier  
+- **gender** – {Female, Male}  
+- **SeniorCitizen** – {0, 1}  
+- **Partner**, **Dependents** – {Yes, No}  
+- **tenure** – months of service (0–72)  
+- **PhoneService**, **MultipleLines** – {Yes, No, No phone service}  
+- **InternetService** – {DSL, Fiber optic, No}  
+- **OnlineSecurity**, **OnlineBackup**, **DeviceProtection**, **TechSupport**, **StreamingTV**, **StreamingMovies** – {Yes, No, No internet service}  
+- **Contract** – {Month-to-month, One year, Two year}  
+- **PaperlessBilling** – {Yes, No}  
+- **PaymentMethod** – {Electronic check, Mailed check, Bank transfer (automatic), Credit card (automatic)}  
+- **MonthlyCharges**, **TotalCharges** – numeric fees in USD  
+- **Churn** – target label for churn prediction
+
+The dataset mixes categorical, numeric and missing-value patterns typical of real CRM exports, making it a standard benchmark for churn-modeling and customer-analytics pipelines.