Performing Analysis of Meteorological Data

One type of data that’s easier to find on the net is Weather data. Many sites provide historical data on many meteorological parameters such as pressure, temperature, humidity, wind, speed, visibility, etc.

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 monthly analysis has to be done for all 12 months over the 10 year period.

The dataset used for this project is downloaded from Kaggle. 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.

The libraries used here are numpy , pandas and matplotlib.

The Null Hypothesis is

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

The implementation in Jupyter notebook is as follows:

Step 1 : Importing the required libraries

Importing the required libraries

Step 2: Importing the dataset

Importing the dataset

Step 3: Viewing the first 5 rows present in the dataset

First 5 rows present in the dataset

Step 4: Summary of the dataset

Summary of the dataset

Step 5: Dropping the Unnecessary columns and selecting the required columns

Selecting the required data

Step 6: Viewing the new data

First 5 rows present in the new dataset

Step 7: Resampling the data

In this step the contents of the column “ Formatted Date” are converted to +00:00 UTC

Resampling of new dataset

Step 8: Viewing the resampled dataset

First 5 rows present in the resampled dataset

Step 9: Checking for null values in the new dataset

Checking for null values

Step 10: Plotting a Line graph for all the 12 months

Line graph for the entire data

From the above line graph we can see that both the peaks and the troughs are almost same throughout the period of 10 years.

Step 11: Plotting a Line graph for the month of January

Line graph for the month of January

We can analyze that for the month for January , there isn’t any change in the humidity for the past ten years (2006–2016) whereas the temperature increases in the year 2007 and gradually drops until the year 2010 and again the temperature gradually increases until the year 2014 and then it drops for the rest of the years.

Step 12: Plotting a Line graph for the month of February

Line graph for the month of February

We can analyze that for the month for February , there isn’t any change in the humidity for the past ten years (2006–2016) whereas the temperature increases in the year 2007 and gradually drops until the year 2012 and again the temperature gradually increases until the year 2014.

Step 13: Plotting a Line graph for the month of March

Line graph for the month of March

We can analyze that for the month for March , there isn’t any change in the humidity for the past ten years (2006–2016) whereas the temperature increases in the year 2007 and gradually drops and remains fairly constant until the year 2011 and then for the rest of the years there is a frequent rise and drop in the temperature.

Step 14: Plotting a Line graph for the month of April

Line graph for the month of April

We can analyze that for the month for April, there isn’t any change in the humidity for the past ten years(2006–2010) whereas the temperature increases sharply in 2009 and drops in 2015 for rest of the years there isn’t any sharp change in the temperature.

Step 15: Plotting a Line graph for the month of May

Line graph for the month of May

We can analyze that for the month for May , there isn’t any change in the humidity for the past ten years(2006–2010). Also there isn’t any sharp changes in the temperature too for the past ten years(2006–2016).

Step 16: Plotting a Line graph for the month of June

Line graph for the month of June

We can analyze that for the month for June , there isn’t any change in the humidity for the past ten years(2006–2010). Also there isn’t any sharp changes in the temperature too for the past ten years(2006–2016).

Step 17: Plotting a Line graph for the month of July

Line graph for the month of July

We can analyze that for the month for July , there isn’t any change in the humidity for the past ten years(2006–2010). Also there isn’t any sharp changes in the temperature too for the past ten years(2006–2016).The peak temperature is in the year 2012.

Step 18: Plotting a Line graph for the month of August

Line graph for the month of August

We can analyze that for the month for August, there isn’t any change in the humidity for the past ten years(2006–2010). Also there isn’t any sharp changes in the temperature too for the past ten years(2006–2016).The peak temperature is in the year 2015.

Step 19: Plotting a Line graph for the month of September

Line graph for the month of September

We can analyze that for the month for September , there isn’t any change in the humidity for the past ten years (2006–2016) whereas the temperature increases until the year 2009 and then it frequently rises and drops until year 2013 and then for the rest of the years there is a frequent increase in the temperature.

Step 20: Plotting a Line graph for the month of October

Line graph for the month of October

We can analyze that for the month for October , there isn’t any change in the humidity for the past ten years (2006–2016) whereas the temperature increases in the year 2008 and then it frequently drops until year 2010 and then for the rest of the years there is a frequent increase in the temperature.

Step 21: Plotting a Line graph for the month of November

Line graph for the month of November

We can analyze that for the month for November, there isn’t any change in the humidity for the past ten years (2006–2016) whereas the temperature increases in the year 2007 until 2010 and then it drops in the year 2011 and again rises in the year 2012 and then for the rest of the years there is a frequent drop in the temperature.

Step 21: Plotting a Line graph for the month of December

Line graph for the month of December

We can analyze that for the month for December, there isn’t any change in the humidity for the past ten years (2006–2016) whereas the temperature frequently rises and drops.

Conclusion

Hence from the above line graphs , we can conclude that global warming has caused an uncertainty in temperature over the past ten years while the humidity remained almost constant in the past ten years from 2006 to 2016.

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