Skip to content

About

No description, website, or topics provided.

Resources

Stars

0 stars

Watchers

1 watching

Forks

Latest commit

 

History

49 Commits

Folders and files

NameName
Last commit message
Last commit date
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Pepsico Inc. Dashboard

Welcome to the Pepsico Inc. dashboard, a powerful solution built using Streamlit to help you explore and analyze the most desired KPIs of Pepsico Inc. and market trends.

Try the dashboard: Pepsico Inc. Dashboard

Screenshot 2023-05-23 at 20 45 02

Features

The Pepsico Inc. dashboard provides the following features:

  1. Easy Navigation: Navigate to different tabs to explore various aspects of H&M's data, such as Revenue, Marketing, and Resources.
  2. Interactive Filters: Use multiple filters to quickly sift through data and narrow down the information you're looking for (e.g. year and month, sales channel, etc.).
  3. Visually Appealing Charts and Graphs: Gain insights through simple and colorful visualizations that provide a comprehensive overview of each KPI.
  4. Data-Driven Decisions: Leverage the power of data to drive success for your business and stay ahead of the competition.

How to Use

  1. Navigate through the Total Market, New York and Pepsico (New York) tabs.
  2. On each page, use the sidebar filters to explore data based on your preferences.
  3. View the KPIs and charts displayed on the pages to understand trends and patterns in the data.

Page Structure:

  1. KPIs: Numbers dedicated to the analysis of Pepsico Inc.'s revenue, market share and products sold on deal
  2. Total Market: Tab dedicated to the analysis of top performing regions for Pepsico Inc.
  3. New York: Tab dedicated to the analysis of the performance of the New York market
  4. Pepsico (New York): Tab dedicated to the analysis of Pepsico Inc.'s performance in the New York market

Required Modules

Before using the dashboard, the following Python modules must be installed:

  1. Streamlit: pip install streamlit
  2. Pandas: pip install pandas
  3. Altair: pip install altair
  4. Pillow: pip install pillow

About

No description, website, or topics provided.

Resources

Stars

0 stars

Watchers

1 watching

Forks

Releases

Packages

Contributors

Languages