Performing Analysis of Meteorological Data

Global warming refers to the gradual rise in the overall temperature of the atmosphere of the Earth. It is a big challenge that we are facing today globally. Here we are going to check whether there is any impact on weather due to global warming in Finland (a country in Northern Europe) by using Data Analytics. please refer to this data set used in the Analysis given below:

The hypothesis of are given below:

“Has the Apparent temperature and humidity compared monthly across 10 years of the data indicate an increase due to Global warming”

The Ho means 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.

Step-1:

Import the required libraries :

Required libraries

Step-2:

Importing our data set:

importing the data set

Step-3:

Find the dimensions of the data set using shape function:

‘weatherHistory’ Data set has(96453 rows and 11 columns respectively)

Step-4

Getting a small view of the data set using head() function

view of the first five rows of the data set

Step-5:

Getting statistical summary of DataFrame using describe() function :

Step-6:

Now, obtaining a concise summary of a DataFrame using info() function:

Step-7:

As per Hypothesis , we only require Apparent temperature and Humidity for further analysis, so drop other unwanted columns from the data set.

Then, we will convert the Timezone to +00:00 UTC .

Step-8:

Plot graph for all the months:

Drawing graph for all months

Step-9:

finally, we will plot a graph for specific month(April).

variation in Apparent tempreature and Humidity with time

Conclusion:

Global warming has an adverse impact on our environment .from the analysis of ( ‘weatherHistory’) data set,we find that there is either a sharp rise in temperatures or sharp falls over the 10 yrs. Also, we observed that there isn’t any change in humidity in the past 10 years(2006–2010) for the month of April. whereas, temperature increases sharply in 2009 and drops in 2015 for the rest of years there isn’t any sharp change in the temperature.