HNG STAGE ZERO: ANALYZING RETAIL SALES DATA AT FIRST GLANCE

RMAG news

Introduction

The Kaggle dataset “Sample Sales Data” by Kyanyoga provides a sample dataset for sales data analysis. It includes sales data with attributes such as order details, product information, customer details, and geographical data, allowing for various analyses like sales trends, product performance, and revenue analysis. This dataset is useful for practicing data analysis, visualization, and predictive modeling.

Purpose: This report aims to analyze the provided sales data to extract meaningful insights that can help understand sales trends, product performance, and revenue generation.

Scope: This report covers data exploration, cleaning, analysis, and visualization of the sales data.

Observations

1. **Dataset Overview:
**

Source: Kaggle — Sample Sales Data by Kyanyoga

Description: The dataset contains 2823 entries and 25 columns including sales records. Columns include order numbers, quantities, prices, sales amounts, dates, statuses, product lines, customer details, and geographical data.

2. Data Exploration
Data Structure:

Number of records: 2823

Number of features: 25 columns
Features include Product Category, Order Quantity, Sales Value, Date, etc.

Initial Observations: Summary statistics of key features such as mean, median, and standard deviation.

3. Data Cleaning
Missing Values:

ADDRESSLINE2 (302 non-null entries).
STATE (1337 non-null entries).
POSTALCODE (2747 non-null entries).
TERRITORY (1749 non-null entries).

*Data Types:
*

Numerical: ORDERNUMBER, QUANTITYORDERED, PRICEEACH, ORDERLINENUMBER, SALES, QTR_ID, MONTH_ID, YEAR_ID, MSRP.
Categorical: STATUS, PRODUCTLINE, PRODUCTCODE, CUSTOMERNAME, PHONE, ADDRESSLINE1, ADDRESSLINE2, CITY, STATE, POSTALCODE, COUNTRY, TERRITORY, CONTACTLASTNAME, CONTACTFIRSTNAME, DEALSIZE.
Date/Time: ORDERDATE.

Conclusion

This analysis is an overview at first glance of sales transactions

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