Analyse Sqlite file with climate data using SQLAlchemy ORM queries, Pandas, and Matplotlib.
- Design a query to retrieve 12 months of precipitation data.
- 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.
- Use Pandas to print the summary statistics for the precipitation data.
- 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.
- List the station that has the highest number of observations.
- Design a query to retrieve 12 months of temperature observation data.
- Filter by the station with the highest number of observations.
- Plot the results as a histogram.
- Calculate and plot the min, avg, and max temperature from chosen date range as a bar chart.
- Use the average temperature as the bar height.
- Use the peak-to-peak value as the y error bar.
