Climate Analysis and Exploration
- This project used Python and SQLAlchemy, an ORM, to do a basic analysis of a SQLite database containing climate data.
- The development was conducted in climate_analysis.ipynb (Jupyter Notebook), and the application was completed in climate_app.py.
- The python file utilizes flask routing and templating to display a few results from the analysis.
- The main python packages which were used are Pandas, MatPlotlib & Numpy, flask, & SQLAlchemy.
- Charts were generated during this analysis and are provided below.
- The following is a basic breakdown of the analysis portion completed in Jupyter notebook:
Precipitation Analysis
Query & Save the last 12 months of precipitation data and plot the results (Pandas).
Station Analysis
Query the annual temperature observation data for the most active station, and plot the results as histogram (Numpy, Pandas).
Temperature Analysis
Given user input, use the predefined 'calc_temps' function to determine minimum, average, and maximum expected temperatures during the trip duration:¶
Rainfall Analysis
Calculate the rainfall per weather station using the previous year's matching dates.
Daily Normal Expectation Analysis
Calculate the daily normals for the trip duration
Copyright
Data Boot Camp ©2018. All Rights Reserved.