Explore Data Analysis in Python | Superstore Sales Analysis | Step-by-Step Guide

Do you want to know how to analyze Superstore sales data? If so, then this data analysis tutorial is for you! In this video, we'll walk you through the steps needed to analyze sales data from a Superstore. We will be using Python to perform an exploratory data analysis to uncover insights into the store’s sales trends and patterns. We will also be answering questions such as which category is best selling and most profitable, what are the best selling and most profitable sub-category, which is the top selling sub-category, which customer segment is most profitable. ____________________________________________ SUBSCRIBE! Do you want to become a Data Analyst? That's what this channel is all about! My goal is to help you learn everything you need in order to start your career or even switch your career into Data Analytics. Be sure to subscribe to not miss out on any content! ____________________________________________ 0:43 - Importing Python Libraries 2:15 - Importing the dataset 8:59 - Analyzing shape of Dataset 11:55 - Data Cleaning filling empty columns 16:32 - Data Description 19:35 - Data cleaning Duplicates 25:02 - Exploratory Data Analysis 25:20 - Customer Segmentation 37:58 - Sales Per Customer Segment 41:31 - Customer Loyalty 49:05 - Geographical Analysis of Customers and Sales 1:02:06 - Product Category Segmentation 1:08:31 - Sales Per Product Category 1:11:40 - Sales according to individual products 1:18:07 - Sales Trends Analysis 1:30:07 - Quarterly Sales 1:38:10 - Monthly Sales Trends for 2018 #DataAnalytics, #DataAnalysisProject #data analytics for beginners #data analytics