⚡ In this project , developing of Internet Browser's Google Trend Dashboard made with Python and Streamlit after that deployed to Heroku using Git.
Time series data is everywhere; from temperature records, to unemployment rates, to the S&P 500 Index. Another rich source of time series data is Google Trends, where you can freely download the search interest of terms and topics from as far back as 2004. This project dives into manipulating and visualizing Google Trends data to find unique insights.In the project , I will analyze the worldwide search interest of five major internet browsers to calculate metrics such as rolling average.
Analyze web browser market share between 2004-2020 using Google Trends and time series manipulation.
In this project I used Python with pandas for time series data analysis and data visualization (plot , rolling average plot) for Google trend with search interest analysis.
*It may take a while to run app from Heroku server which I use free dyno hours for every months , please wait until it runs !
