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Retail store analysis in Malls located in Istanbul using Python

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Retail-Store-Analysis

About Dataset

Dataset is collected from Kaggle: https://www.kaggle.com/datasets/mehmettahiraslan/customer-shopping-dataset.

Context

The dataset contains shopping information from 10 different malls between 2021 and 2023 in Istanbul. The data gathered from various ages and genders to provide a comprehensive view of shopping habits in Istanbul.

Content

Attribute Information:

invoice_no: Invoice number. Nominal. A combination of the letter 'I' and a 6-digit integer uniquely assigned to each operation. customer_id: Customer number. Nominal. A combination of the letter 'C' and a 6-digit integer uniquely assigned to each operation. gender: String variable of the customer's gender. age: Positive Integer variable of the customers age. category: String variable of the category of the purchased product. quantity: The quantities of each product (item) per transaction. Numeric. price: Unit price. Numeric. Product price per unit in Turkish Liras (TL). payment_method: String variable of the payment method (cash, credit card or debit card) used for the transaction. invoice_date: Invoice date. The day when a transaction was generated. shopping_mall: String variable of the name of the shopping mall where the transaction was made.

Analysis

Exploratory Data Analysis (EDA)

To understand the data using Python. Check any duplicate and null data.

Cleaning data

Data cleaning by standardize the data format using Pandas.

Univariate analysis

Analysis each parameter data to gather information of data information of each parameter.

Multivariate analysis

Analysis combined parameters to gather further information based on the dataset.

Machine Learning

Analysis the dataset further through machine learning.