Fashion E-commerce User Data

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➡️The dataset provided consists of two parts: Dataset 1 and Dataset 2, containing information related to fashion e-commerce users.

##### Columns in dataset 1(ds1.csv) has 98913 rows and 24 columns:

| Column | Description |
| --- | --- |
| identifierHash | Unique identifier hash for each entry. |
| type | Type of user. |
| country | Country of the user. |
| language | Language preference of the user. |
| socialNbFollowers | Number of social media followers of the user. |
| socialNbFollows | Number of social media accounts the user follows. |
| socialProductsLiked | Number of social media products liked by the user. |
| productsListed | Number of products listed by the user. |
| productsSold | Number of products sold by the user. |
| productsPassRate | Pass rate of the user's products. |
| productsWished | Number of products wished by the user. |
| productsBought | Number of products bought by the user. |
| gender | Gender of the user. |
| civilityGenderId | Civility gender identifier. |
| civilityTitle | Civility title of the user. |
| hasAnyApp | Indicates if the user has any mobile app. |
| hasAndroidApp | Indicates if the user has an Android app. |
| hasIosApp | Indicates if the user has an iOS app. |
| hasProfilePicture | Indicates if the user has a profile picture. |
| daysSinceLastLogin | Number of days since the user's last login. |
| seniority | User's seniority. |
| seniorityAsMonths | User's seniority in months. |
| seniorityAsYears | User's seniority in years. |
| countryCode | Country code of the user's country. |




##### Columns in dataset 2(ds2) has 62 rows and 32 columns:

| Column | Description |
| --- | --- |
| country | Country name |
| buyers | Total number of buyers in the country |
| topbuyers | Number of top buyers in the country |
| topbuyerratio | Ratio of top buyers in the country |
| femalebuyers | Number of female buyers in the country |
| malebuyers | Number of male buyers in the country |
| topfemalebuyers | Number of top female buyers in the country |
| topmalebuyers | Number of top male buyers in the country |
| femalebuyersratio | Ratio of female buyers in the country |
| topfemalebuyersratio | Ratio of top female buyers in the country |
| boughtperwishlistratio | Ratio of products bought per wishlist in the country |
| boughtperlikeratio | Ratio of products bought per liked product in the country |
| topboughtperwishlistratio | Ratio of products bought per wishlist for top buyers in the country |
| topboughtperlikeratio | Ratio of products bought per liked product for top buyers in the country |
| totalproductsbought | Total number of products bought in the country |
| totalproductswished | Total number of products wished in the country |
| totalproductsliked | Total number of products liked in the country |
| toptotalproductsbought | Total number of products bought by top buyers in the country |
| toptotalproductswished | Total number of products wished by top buyers in the country |
| toptotalproductsliked | Total number of products liked by top buyers in the country |
| meanproductsbought | Mean number of products bought per buyer in the country |
| meanproductswished | Mean number of products wished per buyer in the country |
| meanproductsliked | Mean number of products liked per buyer in the country |
| topmeanproductsbought | Mean number of products bought per buyer for top buyers in the country |
| topmeanproductswished | Mean number of products wished per buyer for top buyers in the country |
| topmeanproductsliked | Mean number of products liked per buyer for top buyers in the country |
| meanofflinedays | Mean number of offline days for buyers in the country |
| topmeanofflinedays | Mean number of offline days for top buyers in the country |
| meanfollowers | Mean number of social media followers for buyers in the country |
| meanfollowing | Mean number of social media accounts followed by buyers in the country |
| topmeanfollowers | Mean number of social media followers for top buyers in the country |
| topmeanfollowing | Mean number of social media accounts followed by top buyers in the country |