Climate analysis and data exploration from climate database

1. Precipitation Analysis

• Design a query to retrieve the last 12 months of precipitation data.
• Select only the date and prcp values.
• Load the query results into a Pandas DataFrame and set the index to the date column.
• Sort the DataFrame values by date.
• Plot the results using the DataFrame plot method.

2. Station Analysis

• Design a query to calculate the total number of stations.
• Design a query to find the most active stations.
• List the stations and observation counts in descending order.
• Which station has the highest number of observations?
• Design a query to retrieve the last 12 months of temperature observation data (tobs).
• Filter by the station with the highest number of observations.

3. Temperature Analysis of my Trip : 12-27-2015 to 01-10-2016

• Use the calc_temps function to calculate the min, avg, and max temperatures for your trip
• Plot the min, avg, and max temperature from your previous query as a bar chart.

4. Rainfall per Weather Station

• Design a query to calculate the total amount of precipitaion for the most popular station

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• Flask Visual - Browser Display
• Flask - Python
• Jupyter Notebook - Code