Debbie Choong, Tan Chun Rong, Low Yan Rou, Chu Wei Ming
26/1/2022
Firstly, we ask ourselves questions as asking a correct question is considered one of the most important steps before tackling a data science problem.
- What is the weather like tomorrow at Kuala Lumpur?
- Should I have outdoor activities at Seremban 4 days from now?
- Do I need to bring my umbrella when I go out?
1. Finding and getting data
Finding relevant data to the shiny app, which in this case in the weather, temperature, pressure and humidity
2. Cleaning data
Data used in our weather forecast app is constantly being updated
3. Analysing data
Perform Exploratory Data Analysis(EDA) to have visual representation to have better understanding of data obtained
4. Model Building and Deployment
Use shiny app to deploy product and have user guide
Weather Dataset
- Shiny app will display the weather description, wind speed according to time
- Shiny app will also display visual representation(line graph) for weekly temperature, pressure and humidity based on time and date
- All data on the weather will be constantly updated according to real time
City Dataset
- Shiny app will display the weather based on the city that user can choose
- Cities are all based in Malaysia
Summary of experience
- Learned to extract real time data
- Learned to utilise new packages in R
- Gained experience solving real world problems
Link to shiny application:
Source code: