Blog post: https://lvngd.com/blog/feature-engineering-python-and-pandas/

noise_complaints.py

import requests
import pandas as pd

"""
Script to fetch 50,000 311 noise complaints from NYC Open Data.

Substitute your own API key.
"""

NYC_OPEN_DATA_API_KEY='xxxxxxxxxx'

date = '2020-01-15'
#311 complaints endpoint
endpoint = "https://data.cityofnewyork.us/resource/erm2-nwe9.json?$where=created_date<'{}' AND complaint_type like 'Noise%25'&$limit=50000".format(date)
headers={'X-App-Token': NYC_OPEN_DATA_API_KEY}
result = requests.get(endpoint, headers=headers)
noise_complaints = pd.DataFrame(result.json())

#drop irrelevant columns

columns_to_drop = ['address_type', 'agency',
       'bbl', 'community_board',
       'cross_street_1', 'cross_street_2', 'due_date',
       'facility_type', 'landmark', 
       'intersection_street_1', 'intersection_street_2','location', 
       'open_data_channel_type', 'park_borough', 'park_facility_name',
       'resolution_action_updated_date','unique_key',
       'x_coordinate_state_plane', 'y_coordinate_state_plane','city', 'street_name']

noise_complaints.drop(columns_to_drop,inplace=True,axis=1)

#filter for status == 'Closed' then drop status column

noise_complaints = noise_complaints[noise_complaints.status == 'Closed']
noise_complaints.drop(['status'],inplace=True,axis=1)