For this project, I implemented data analysis using R. I used the libraries readr, and dplyr which helped me to build the project. I analyze the dataset from 2015 that contains over 39,000 data points about weather conditions in London to gain a better understanding and insight about weather condition during that time.
I could not find the dataset that I used for this code, therefore to prove I understand how to analyze similar datasets with another project called Variance in Weather in London, England Project that I will expand on more.
For this project, I implemented data analysis using R. I used the libraries readr, dplyr and tidyverse which helped me to build the project. I analyze the 2015 data of Smeteostat.net to gain a better understanding and insight of the weather conditions in London, England.
This data comes from meteostat.net
Here are the results I gained through data analysis of the England_data.csv data.
I first read the England_data csv and set it equal to England_df.
I then inspected the data and gleamed that there was 365 rows and 11 columns of data.
The average precipitation was then calculated for all of 2015 equalling 1.512707 mm.
The precipitation variance for the year was 15.90826 mm and the precipitation standard deviation was 3.988516 mm.
I inspect and defined june and july.
Afterwards I found the monthly mean of the precipitation in june and july, which were 0.4233333 mm and 2.325806 mm respectfully.
The monthly standard deviation of the precipitation in june and july, which were 1.14521 mm and 6.959692 mm.
Afterwards, I analyzed the precipitation of all the months.
Finally, I plotted the data to gain better understanding of trends and averages. I decided to analyze June and July since those two months are heavy vacation times for tourist.
I could gleam from the plots that at late June and early July it is the hottest out for London and best to avoid when on vacation. Based on the data, it is best to go on vacation to London during the fall when the chance of rain is low and its not too hot.
In conclusion, I was able to analyze and extract a lot of information about the weather of London during 2015 with the data given.