Kaggle sample superstore python github

Kaggle sample superstore python github. Explore the Kaggle Python Exercise Repository on GitHub for a curated selection of exercises from Kaggle's Python courses. This Google Play Store dataset from Kaggle, analysis using Python, NumPy , Pandas , and Matplotlib. About. Explore and run machine learning code with Kaggle Notebooks | Using data from Superstore Sales Dataset. - sankalpk4u/Retail-Sales-Analysis-EDA A kaggle's sample superstore dataset, a kind of a simulation where you perform extensive data analysis to deliver insights on how the company can optimize its profit levels. - GitHub - Wunmi-O/Superstore: A kaggle's sample superstore dataset, a kind of a simulation where you perform extensive data analysis to deliver insights on how the company The SuperStore dataset comprises a comprehensive sales record from a superstore, containing 9,994 entries across 19 distinct fields. You signed out in another tab or window. OK, Got it. RFM modeling was done by manually assigning customer loyalty groups to various combinations of R/F/M values ranked from 1-4 (4 being the highest). . Practice Your Data Analysis Skills as a Superstore Data Analyst Kaggle uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. Using the Superstore dataset, the goal of this machine learning project is to perform Exploratory Data Analysis (EDA) and implement clustering techniques to gain insights into customer behavior and optimize the store's operations. This analysis will show profits and sales and how they change year over year (YOY) for certian categories. Dataset of a Sample Superstore. You switched accounts on another tab or window. This is a sales and profit analysis of "SuperStore" that was found on Kaggle. Jan 15, 2020 · An introduction to Sample SuperStore Dataset Walkthrough, Using Python and the Pandas Library, while utilizing Jupyter Notebook as the IDE. Gain the skills you need to do independent data science projects, Kaggle pare down complex topics to their key practical components, so you gain usable skills in a few hours (instead of weeks or months). Use lambda functions to establish Recency/Frequency/Monetary columns Split columns Kaggle Python docker image. You signed in with another tab or window. EDA on Sample superstore Dataset using Python Programming Language Step1: Importing the necessary Libraries Step2: Mounting Google Drive and Creating a file path This project is an in-depth analysis of retail sales using a Kaggle dataset. Categories and sub categories. The sample was taken from the legendary dataset “Sample Superstore”, of a fictional Ecommerce company. csv at master · Wunmi-O/Superstore Explore and run machine learning code with Kaggle Notebooks | Using data from Superstore Dataset 🍔 EDA Superstore Analysis 📈 Python | Kaggle Kaggle uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. Reload to refresh your session. The three categories all account for over 30% of sales Explore and run machine learning code with Kaggle Notebooks | Using data from US Superstore data Kaggle competition whose aim is to predict sales for the thousands of product families sold at Favorita stores located in Ecuador. The repository contains the following components: Global Super Store Dashboard using Microsoft Power BI (Data Visualizations) - meetbikram/Power-BI-Global-Superstore-Dashboard This is the Python version analysis approach, towards the legendary Sample Superstore Dataset with Pandas - leonism/sample-superstore Explore and run machine learning code with Kaggle Notebooks | Using data from Superstore Sales Dataset SuperStore Sales Analysis in Python | Kaggle Kaggle uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. Contribute to upura/python-kaggle-start-book development by creating an account on GitHub. This report analyzes various aspects of the dataset to extract meaningful insights. Kaggle uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. Contribute to Kaggle/kagglehub development by creating an account on GitHub. The training data includes dates, store and product information, whether that item was being promoted, as well as the sales numbers. Contribute to Kaggle/docker-python development by creating an account on GitHub. It explores trends over time, segments customers based on demographics and spending behavior, analyzes profit margins by product category, examines sales patterns across store locations, and builds predictive models to forecast sales or predict customer behavior. The SuperStore Database Management Project (DBMD) is a comprehensive solution designed to streamline and optimize the operations of an e-commerce business. Kaggle exercises solutions for Python, Pandas, Data Visualization, Intro to SQL, Advanced SQL and Data Cleaning. The main aim of the project is to uncover insights into the store's sales and profits trends and patterns from 2014 to 2017. Given the insights gained from the EDA, the superstore can choose to remove non-profitable products or invest in marketing efforts for products, segments and geographical areas that are driving their profit. Learn more. In dataset analysis, you can view the best app 5-star rating app, most review app, or most download app, etc. This is the Python version analysis approach, towards the legendary Sample Superstore Dataset with Pandas - sample-superstore/01- Data Exploration - SampleSuperStore. This notebook is intended for those whose relatively new to EDA (Exploratory Data Analysis) aspect from a Machine Learning process. The dataset includes order details, anonymized customer information, product specifics, and financial metrics. This project focuses on creating a robust database management system that facilitates efficient handling of various aspects of an online store, from product inventory to customer orders. Sample SuperStore. A kaggle's sample superstore dataset, a kind of a simulation where you perform extensive data analysis to deliver insights on how the company can optimize its profit levels. The project utilizes a combination of Python, SQL, and Power BI to clean the data, perform exploratory analysis, and create interactive reports. ipynb at master · leonism/sample-superstore This repository showcases the Superstore Sales Analysis project, which aims to analyze and visualize the sales data of a fictional superstore. In this analysis, we delve into a comprehensive exploration of a supermarket sales dataset obtained from Kaggle. The dataset required basic data cleaning and restructuring via Python. The analysis will focus on data wrangling and visualization tools that can be done in Python. Dataset containing Sales & Profits of a Superstore In this personal Superstore Sales SQL Data Analysis project, an exploratory data analysis was performed on the Superstore Sales Data available on Kaggle. The dataset contains a wealth of information regarding sales transactions, customer demographics, product lines, and payment methods, encompassing a total of 1000 entries and 17 columns. Aug 24, 2023 · My chosen path led me to meticulously select a dataset from Kaggle, thoughtfully tailored to meet the rigorous standards of a modern superstore. - Superstore/SampleSuperstore. Additional files include 『PythonではじめるKaggleスタートブック』のサンプルコード・脚注・正誤表. Python library to access Kaggle resources. Organized into convenient files, each exercise is accompanied by clear descriptions and code solutions, providing a hands-on learning experience. This is the Python version analysis approach, towards the legendary Sample Superstore Dataset with Pandas - leonism/sample-superstore. jrutsy npey pxmxxnhz khtfxmr lrjrze bppgukw lwddpe tjp nidv mhd