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:

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Precipitation Analysis

Query & Save the last 12 months of precipitation data and plot the results (Pandas).

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Station Analysis

Query the annual temperature observation data for the most active station, and plot the results as histogram (Numpy, Pandas).

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Temperature Analysis

Given user input, use the predefined 'calc_temps' function to determine minimum, average, and maximum expected temperatures during the trip duration:¶

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Rainfall Analysis

Calculate the rainfall per weather station using the previous year's matching dates.

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Daily Normal Expectation Analysis

Calculate the daily normals for the trip duration

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