property price predictor
Project description
nyc_prop_prediction
This is a library designed for quick prediciton of housing prices in nyc
Example
Suppose I want to find companies that have filed either an S-1, 10-K or 10-Q between January 2021 and March 2023
predictor = predict()
sqft = 500
year_built = 1970
year_sold = 2023
num_libraries = 1
num_parks = 5
num_schools = 0
zipcode = 10037
mod = nyc_prop_prediction.predict()
input = [[sqft,year_built,year_sold,num_libraries,num_parks,num_schools]]
print(predictor.predict_price(input_type='zipcode',model='gradient',inputs=input))
Installation
nyc_prop_prediction
can be installed via PyPi by running:
pip install nyc_prop_prediction
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
nyc_prop_prediction-0.1.3.tar.gz
(125.4 kB
view hashes)
Built Distribution
Close
Hashes for nyc_prop_prediction-0.1.3.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | cc783803a0d79b6d4e79ac84e6caa08598c6c70867c1afe4fe2ad20924f06cbd |
|
MD5 | c2d0a210c45384030be72d62f80a5507 |
|
BLAKE2b-256 | 648c781497301b555df7af5f6c0178518feab05d8aa820298a777b72b469fbfc |
Close
Hashes for nyc_prop_prediction-0.1.3-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 818bb451d7c86dffff49ffd47e6703e3f64a8902a328330bffc8b8011467b823 |
|
MD5 | e1d8b796554e6a0af51149529dd41321 |
|
BLAKE2b-256 | 5b0dc836475f87b5dc4bf83cde9c671407896a16890eece01c77d4097ba01778 |