Part 1: Analyze and Explore the Climate Data In this section, you’ll use Python and SQLAlchemy to do a basic climate analysis and data exploration of your climate database. Specifically, you’ll use SQLAlchemy ORM queries, Pandas, and Matplotlib. To do so, complete the following steps:
Note that you’ll use the provided files (climate_starter.ipynb and hawaii.sqlite) to complete your climate analysis and data exploration.
Use the SQLAlchemy create_engine() function to connect to your SQLite database.
Use the SQLAlchemy automap_base() function to reflect your tables into classes, and then save references to the classes named station and measurement.
Link Python to the database by creating a SQLAlchemy session.
Perform a precipitation analysis and then a station analysis by completing the steps in the following two subsections. Precipitation Analysis Station Analysis
Part 2: Design Your Climate App Now that you’ve completed your initial analysis, you’ll design a Flask API based on the queries that you just developed