Performing Analysis of Meteorological Data

              Performing Analysis of Meteorological Data

 

A few weeks ago, I started working on the dataset named weather History in which I was responsible for performing data cleaning, perform analysis for testing the (given)Hypothesis.

MY WORK ON THIS DATA SET 

Task:- We need to find whether the average Apparent temperature for the month of a month say April starting from 2006 to 2016 and the average humidity for the same period have increased or not.

This dataset provides historical data on many meteorological parameters such as pressure, temperature, humidity, wind_speed, visibility, etc. The dataset has hourly temperature recorded for last 10 years starting from 2006-04-01 00:00:00.000 +0200 to 2016-09-09 23:00:00.000 +0200. It corresponds to Finland, a country in the Northern Europe

Observation 

From the above plot, we can say that humidity remained almost constant in these years. Even the average apparent temperature is almost same (since peaks lie on the same line)

If we want to specifically retrieve the data of a particular month from every year, say April in this case then :

Now since we have been given hourly data, we need to resample it monthly. Resampling is a convenient method for frequency conversion. Object must have a datetime like index

Here "MS" denotes: Month starting We are displaying the average apparent temperature and humidity using mean() function.

Conclusion

Global warming is no doubt deteriorating the climate and is affecting various parameters of the environment.Hence from this analysis we infer that there are either sharp rise in temperatures or sharp falls over the 10 yrs. Hence we can conclude that Global Warming has caused a major difference and unreliability in temperature predictability also taking humidity into consideration we can say that it has almost remained same throughout the past years.