Python Adidas Sales Dashboard using Streamlit and Plotly-II 

In the following video, you'll be guided through the creation of a Python Adidas Sales Dashboard using Streamlit and Plotly. This will enable you to create a dashboard similar to what's achievable with tools like PowerBI and Tableau.
Streamlit is a tool that allows for the rapid development and sharing of data applications.
This video covers follows:
⭐ 𝗧𝗜𝗠𝗘𝗦𝗧𝗔𝗠𝗣𝗦:
00:00 - Introduction
01:00 - Exploring the Data
01:30 - About Streamlit
02:23 - Importing Necessary Packages
03:45 - Reading Data from File
04:08 - Setting the Streamlit Page and Dashboard Heading
08:40 - Adding "Last Updated" Date
10:42 - Creating a Bar Chart Using Plotly (Retailer by Sales)
13:03 - Viewing and Downloading Bar Chart Source Data
17:03 - Creating a Time Series Chart for Sales and Data Viewing
22:22 - Adding a White Line to the Dashboard
23:10 - Creating a Dual-Axis Chart Based on Total Sales and Units Sold
32:25 - Viewing and Downloading Dual-Axis Chart Source Data
34:35 - Creating a TreeMap Chart Based on Region, City, and Sales with Data Set Features View and Download
45:15 - Viewing and Downloading Adidas Sales Source Data
47:10 - Final Dashboard Overview and Its Features with Final Touch 😊
📑 𝗥𝗘𝗦𝗢𝗨𝗥𝗖𝗘𝗦:
Source Code: github.com/AbhisheakSaraswat/...
Raw Data: github.com/AbhisheakSaraswat/...
This video serves as the second installment in our series on Python Streamlit Dashboards. If you haven't already, we recommend watching the first video on Python Interactive Dashboard Development using Streamlit and Plotly.
👉 Python Interactive Dashboard Development using Streamlit and Plotly.
• Python Interactive Das...
Pandas and Plotly are powerful libraries that play essential roles in dashboard development.
➖➖➖➖➖➖➖➖ ➖➖➖➖➖➖➖➖
👍 Pandas:
1.) Data Manipulation
2.) Data Cleaning and Preprocessing
3.) Data Integration
4.) Data Transformation
👍 Plotly:
1.) Interactive Data Visualization
2.) Dynamic Updating
3.) Intuitive Interactivity
4.) Dash Integration
In summary, Pandas and Plotly complement each other in dashboard development. Pandas helps with data manipulation, cleaning, and preprocessing, while Plotly enables interactive and visually appealing data visualizations. Together, they empower you to build powerful and insightful dashboards that effectively present and analyze data.
◼️◼️◼️◼️◼️◼️◼️◼️◼️◼️◼️◼️◼️
𝗖𝗢𝗡𝗡𝗘𝗖𝗧 𝗪𝗜𝗧𝗛 𝗠𝗘:
📝 GitHub: github.com/AbhisheakSaraswat
Linkedin► / abhisheak-saraswat-0b1...
Telegram: t.me/+32-TodtiOvo2Njk9
Python Excel Automation: • Excel Automation Using...
Python Teaser: • A Beautiful Python Pro...
Playlists:
Python Pandas Data Science Tutorial: • Python Pandas Tutorial...
Python Playlist: • Python Tutorial for Be...
Python Data Structure Playlist: • Python Data Structure
Python OOPs Playlist: • Object Oriented Progra...
#python
#programming
#datascience
#machinelearning
#webdevelopment
#code
#developer
#softwareengineering
#opensource
#tutorial
#tech
#coding
#computerprogramming
#pandas
#numpy
#matplotlib
#StreamlitTutorial
#PythonDashboard
#InteractivePlots
#DataVisualization
#StreamlitAndPlotly
#DataAnalysis
#TimeSeriesAnalysis
#PandasTutorial
#PlotlyVisualization
#DataTables
#DashboardDevelopment
#PythonProgramming
#StreamlitExamples
#DataManipulation
#DataFiltering
#DataTransformation
#HierarchicalView
#DataExploration
#DashboardDesign
#StreamlitTips

Наука