This is a basic project for a virtual internship which I was a part of, and I performed the following tasks:

• Data Cleaning and Preparation

• Data Analysis and Visualization

Hourly temperature data is available for the last ten years, from 2006–04–01 00:00:00.000+0200 to 2016–09–09 23:00:00.000 +0200.

Finland, a country in Northern Europe, is the country to which it corresponds. Both Google Drive and Kaggle have access to the dataset.

"Has the Apparent Temperature and Humidity compared monthly across 10 years of data indicate an increase due to global warming?" is the null hypothesis.

The hypothesis requires us to determine whether the average apparent temperature for the month of May, say, April, has increased or decreased between 2006 and 2016, as well as the average humidity for the same period. Over a ten-year period, this monthly analysis must be completed for all 12 months.

In the attached Jupyter Notebook file, I have completed a lot of different analysis to prove this hypothesis.

For more information, give a read to my blog based on this project: https://medium.com/@abdullahw72/performing-analysis-of-meteorological-data-a5e993061fc7