Baselight

CTR In Advertisement

Predict the ad click rate of a customer

@kaggle.arashnic_ctr_in_advertisement

Ad Click Prediction Train 1
@kaggle.arashnic_ctr_in_advertisement.ad_click_prediction_train_1

  • 6.08 MB
  • 463291 rows
  • 15 columns
session_id

Session Id

datetime

DateTime

user_id

User Id

product

Product

campaign_id

Campaign Id

webpage_id

Webpage Id

product_category_1

Product Category 1

product_category_2

Product Category 2

user_group_id

User Group Id

gender

Gender

age_level

Age Level

user_depth

User Depth

city_development_index

City Development Index

var_1

Var 1

is_click

Is Click

140690Sun Jul 02 2017 00:00:00 GMT+0000 (Coordinated Universal Time)858557C35952013787410Female433
333291Sun Jul 02 2017 00:00:00 GMT+0000 (Coordinated Universal Time)243253C1059601108558Female22
129781Sun Jul 02 2017 00:00:00 GMT+0000 (Coordinated Universal Time)243253C3595201378748Female22
464848Sun Jul 02 2017 00:00:00 GMT+0000 (Coordinated Universal Time)1097446I3595201378733Male3321
90569Sun Jul 02 2017 00:01:00 GMT+0000 (Coordinated Universal Time)663656C4054906030532Male2321
151475Sun Jul 02 2017 00:01:00 GMT+0000 (Coordinated Universal Time)509591I3595201378721Male13
17583Sun Jul 02 2017 00:01:00 GMT+0000 (Coordinated Universal Time)1091463F4054906030539Female334
461128Sun Jul 02 2017 00:01:00 GMT+0000 (Coordinated Universal Time)469098C3609361378734Male434
390699Sun Jul 02 2017 00:02:00 GMT+0000 (Coordinated Universal Time)611906H105960110855270915nan
353607Sun Jul 02 2017 00:02:00 GMT+0000 (Coordinated Universal Time)418107B3609361378724Male434

CREATE TABLE ad_click_prediction_train_1 (
  "session_id" BIGINT,
  "datetime" TIMESTAMP,
  "user_id" BIGINT,
  "product" VARCHAR,
  "campaign_id" BIGINT,
  "webpage_id" BIGINT,
  "product_category_1" BIGINT,
  "product_category_2" DOUBLE,
  "user_group_id" DOUBLE,
  "gender" VARCHAR,
  "age_level" DOUBLE,
  "user_depth" DOUBLE,
  "city_development_index" DOUBLE,
  "var_1" BIGINT,
  "is_click" BIGINT
);

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