Probability Chance

Probability Chance Method

probability.get_chance(
    search_items, 
    csv=False, 
    output_dir='/output'
)

Delivers the risk likelihood (% probability) for flooding to the building footprint broken down by depth threshold and year of annual risk.

This method returns an array of ProbabilityChance product for the given property IDs. Only property IDs are accepted. Optionally creates a csv file.

(More information on the Probability Chance product can be found on the Probability Chance Page on the First Street Foundation API Data Dictionary)

Arguments:

• search_items: list/file of SearchItems, property parcels to retrieve probability chance for.
• csv: bool, whether to create a CSV for the retrieved data.
• output_dir: string, location to output the created CSV (if csv is True).

Example (Command Line):

Call probability.get_chance on a list with 2 FSIDs

python -m firststreet -p probability.get_chance -s 190836953;392804911

Call probability.get_chance on a lat/lng or address

python -m firststreet -p probability.get_chance -s 37.16314,-76.55782;38.50303,-106.72863
python -m firststreet -p probability.get_chance -s "247 Water Street, New York, New York";"135 East 46th Street New York, New York"

Call probability.get_chance on a file of SearchItems

python -m firststreet -p probability.get_chance -s sample_property.txt

Example (Python File):

# Contents of sample.py
# Create a `FirstStreet` object.  
import firststreet
fs = firststreet.FirstStreet("api-key")

# Call probability.get_chance on a list with 2 property FSIDs
probability_chance = fs.probability.get_chance(search_items=[190836953, 193139123])

# Call probability.get_chance on a lat/lng or address
location_summary = fs.probability.get_chance(search_items=[(37.16314,-76.55782)], csv=True)
location_summary = fs.probability.get_chance(search_items=["247 Water Street, New York, New York"], csv=True)

# Call probability.get_chance on a file of SearchItems
probability_chance = fs.probability.get_chance(search_items="sample_property.txt", csv=True)

Probability Chance Objects

ProbabilityChance Object

Key	Type	Description	Example
fsid	str	First Street ID (FSID) is a unique identifier assigned to each location.	392804911
valid_id	bool	Whether the input FSID returned valid data from the server.	True
chance	Array[dict]	The risk likelihood (% probability) for flooding to the building footprint broken down by depth threshold and year of annual risk. The low, mid, high likelihood is returned as [DepthThresholdData] within the associated threshold and year. Available depth thresholds include >0cm, >15cm, and >30cm, returned as [DepthChanceData] and are broken down by the following years within the [DepthChance] model - 2020, 2025, 2030, 2035, 2040, 2045, and 2050.	See below

Chance Dictionary

Key	Type	Description	Example
year	int	The year (2020, 2025, 2030, 2035, 2040, 2045, or 2050) the probability was calculated for.	2020
data	Array[dict]	A collection of Depth Chance Data	See below

Depth Chance Data

Key	Type	Description	Example
threshold	string	The depth threshold in centimeters (0, 15cm, or 30cm) that the probability was calculated for.	0
data	Array[dict]	Depth Threshold Data	See below

Depth Threshold Data

Key	Type	Description	Example
low	int	The likelihood (% probability) of flooding given as a value from 0-1 (rounded to two decimal places) at the specified depth based on the low scenario of the RCP 4.5 emissions curve.	.2
mid	int	The likelihood (% probability) of flooding given as a value from 0-1 (rounded to two decimal places) at the specified depth based on the mid scenario of the RCP 4.5 emissions curve.	.3
high	int	The likelihood (% probability) of flooding given as a value from 0-1 (rounded to two decimal places) at the specified depth based on the high scenario of the RCP 4.5 emissions curve.	.6