Performing Analysis of Meteorological Data

Project - I

Table of Contents

• Installation
• Objective
• Dataset Insight
• Results
• Licensing, Authors, and Acknowledgements

Installation

You need to be able to work in a Jupyter Notebook on your computer. The following packages (libraries) need to be installed. You can install these packages via conda or pip.

• Pandas
• Matplotlib
• Seaborn
• jupyterthemes

Objective:

Perform Data Cleaning, Perform Analysis for Testing the (given) Hypothesis and finally put-forth your conclusion by writing a blog article.

Dataset Insight:

The Meteorological Dataset Consists of:

• Total Number of Data Point: 96453
• Total Number of Attribute/Columns in data set is 11.

Attribute Information:

• Formatted Date
• Summary
• Precip Type
• Temperature (C)
• Apparent Temperature (C)
• Humidity
• Wind Speed (km/h)
• Wind Bearing (degrees)
• Visibility (km)
• Pressure (millibars)
• Daily Summary

Results:

The main findings of the code can be found at the post available here or here

Licensing, Authors, Acknowledgements

Must give credit to Kaggle for the data. You can find the Licensing for the data and other descriptive information at the Kaggle link available here.