Write an Earthquake class that demonstrates the following
aspects of OOP in Python:
1. Create a basic class that can hold all relevant earthquake data saved in index.sqlite see below
2. Appropriately create a constructor to set all
data values .
3. Create a regular class method that returns all
or part of the Earthquake data as a dictionary object.
4. Override the __str__ method to print a
reasonable string representation of an Earthquake.
5. Use the @property decorator to make at least
one property in your Earthquake class private.
6. Use the @???.setter method to
validate the private property in some way (e.g. check if its numeric, change
it's data type, change it's length...) before setting its value.
Write a second class called Point, Position or Time to store one
or more pieces of earthquake data.This class can be included in the
Earthquake.py file.
·
The class could store
latitude & longitude OR latitude and longitude and depth OR timestamp
·
You should use this
class in the Earthquake class instead of storing the vales as primitive data
types
·
This class should
include an __init__ method and a __str__ method. If you create class to
stor time, the __str__ method should return a formatted string, not a
timestamp.
You may use the Author and Article classes presented in lecture
as a starting point for these classes.
Earthquake_stats.py
Write an Earthquake_stats class that uses the Earthquake object
AND a Pandas dataframe to process earthquake data and display basic statistics.
·
You should import the
Earthquake module to use in this application.
·
You will read
Earthquakes from the database, just like in stats.py, but instead of
putting them into individual lists for each type of date, you will create a
list of Earthquake objects.
·
You will list of
earthquake objects to a Panda's Dataframe.
o See https://stackoverflow.com/questions/47623014/converting-a-list-of-objects-to-a-pandas-dataframe (Links to an external site.) for an
example of how to use a custom method to turn you object into a dictionary AND
use list comprehension to create a list of Earthquake dictionaries to create
your DataFrame.
·
Display either the
first 5 or last 5 earthquakes in the dataframe to the screen.
·
Use the dataframe to
compute basic statistics for the entire population of earthquakes
·
Compute the same basic
statistics for earthquakes filtered on Region. Computer a separate set of
statistics for two different regions that have at least 200 earthquakes in your
sample.
·
Compute the same basic
statistics for all earthquakes filtered by either felt, tsunami or depth
e.g felt > 0, tsunami > 0, depth < 50 or depth<100.
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