🎯Project Overview:
This project focuses on developing skills in data visualization using Microsoft Power BI. The main objective is to create an animated scatter chart that displays population trends for various cities over time. The project involves data preprocessing using Python, followed by visualization and animation in Power BI.
🛠️Technologies Used:
Python (Jupyter Notebook)
Microsoft Power BI
Microsoft Excel
Camtasia (for screen recording)
🔍Key Steps:
🔄Data Preprocessing:
A Python script is written in Jupyter Notebook to format the initial CSV data file. The script merges 'Place' and 'State' columns, transposes 'Years' and 'Population' into columns, and creates a new 'Student First Name - Rank' column.
📊Power BI Visualization:
The preprocessed data is imported into Power BI. A scatter chart is created with the following configurations:
X-axis: Student-Rank
Y-axis: Population
Size: Workforce (a calculated measure)
Legend: State-Place
Play axis: Year
🎬Animation: The 'play axis' feature in Power BI is used to animate the scatter chart over different years.
Additional Features: A rank slicer is added to filter the data by rank and a new measure 'workforce' is created to represent 60% of the population.
Recording: Camtasia is used to record the animated visualization from Power BI. The recording is edited to slow down the animation for better visibility.
💡Results:
The project results in an interactive, animated scatter chart that visualizes population trends across different cities over time. Key features of the final visualization include:
A dynamic representation of population changes over years. The ability to filter data by rank using a slicer. Representation of workforce size (60% of population) through bubble size. Clear labeling of city-state combinations. A recorded video of the animation for easy sharing and presentation.
This project demonstrates the process of transforming raw data into an engaging, informative visual representation using modern data visualization tools and techniques. CopyRe