Performing Analysis of Meteorological Data
As I already had fundamental knowledge of python and its libraries used for data science, I directly started working on the project. Firstly, I imported all the required libraries such as pandas, numpy, seaborn and matplotlib. I then fetched the data form the csv file I downloaded from the mentioned data source via pandas function and converted it to dataframe. Secondly, I filtered the data by screening for null values and getting data types of all the columns. Then I converted the 'Formatted Date' column into a datetime format so that the kernel doesn't consider it as a number and it can be used later on for resample. I used the set index command to set 'Formatted Date' as the index of the dataframe and then resampled the data to 'MS' which helped me in data reduction. Thirdly, I used the matplotlib and seaborn libraries to draw graphs which showed a direct comparison between apparent temperature and humidity. At last, I used a pairplot to showcase the re...