SQL Challenge

Objective:

To use Python and SQLAlchemy to do basic climate analysis and data exploration of a climate database.

Precipitation Analysis

• Designed a query to retrieve the last 12 months of precipitation data.

• Loaded the query results into a Pandas DataFrame and set the index to the date column.

• Sorted the DataFrame values by date.

• Ploted the results using the DataFrame plot method.

  

• Used Pandas to print the summary statistics for the precipitation data.

Station Analysis

• Designed a query to calculate the total number of stations.

• Designed a query to find the most active stations.

• Designed a query to retrieve the last 12 months of temperature observation data (TOBS).

  

Climate App

After completing the initial analysis, the next step was to design a Flask API based on the queries just developed.

• Convert the query results to a dictionary using date as the key and prcp as the value.

• Return the JSON representation of your dictionary.

Technologies:

• SQL Alchemy
• Jupyter Notebook
• Python `