Analyzing weather data
Analyzing weather data using PySpark can provide valuable insights into weather patterns and trends, which can have practical applications in various industries. For instance, in the agriculture industry, knowing the weather patterns in a region can help farmers plan their crops and irrigation schedule accordingly. In the tourism industry, weather data can be used to optimize travel packages and recommend the best time to visit a particular destination. In the case of disaster response, accurate weather data and predictions can help authorities prepare and respond appropriately.
Input : We would be using the city temperature dataset as the input with the attributes Region,Country, State, City, Month, Day, Year, AvgTemperature Job pipeline:
● Ingestion of CSV files with the read method
● Cleaning the data by treating duplicates and Null values
● Filtering the data and selecting specific columns
● Performing custom computations with UDFs
● Running analytics and creating plots