Performing Analysis of Meteorological Data
In this blog, we are going to analyze the data from the Weather data-set of Finland, a country in Northern Europe. You can find the data-set on Kaggle (https://www.kaggle.com/muthuj7/weather-dataset). We are going to use the NumPy, pandas, and the matplotlib libraries of Python.
Following is the Hypothesis of the Analysis: “Has the Apparent temperature and humidity compared monthly across 10 years of the data indicate an increase due to Global warming.”
Let us start by importing the required libraries and our data-set:
Here is a small preview of how our data-set looks:
Now we need to drop the unwanted data, convert the data into our need and resample our data :
Here is how the data looks after resampling:
As we can see, both the peaks and the troughs are almost the same throughout the period of 10 years. Here is a plot of the average temperature and humidity of the month of April over 10 years.
We can clearly see that there is a sharp rise in temperature in the year 2009 whereas there is a fall in temperature in the year 2015. Hence we can conclude that global warming has caused uncertainty in temperature over the past 10 years while the average humidity has remained constant throughout the 10 years.
