<jupyter_start><jupyter_text><jupyter_code># Setup
# rerun this cell whenever you open Google colab 
!git clone https://github.com/jhnnxyz/TheBigApple.git
%cd TheBigApple/notebooks
%env PYTHONPATH=.:$PYTHONPATH
%pip install sodapy
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from sodapy import Socrata

%matplotlib inline
client = Socrata("data.cityofnewyork.us", None)

query = """
select * 
where
    created_date between '2020-01-01T00:00:00.000' 
    and '2020-12-31T00:00:00.000'
limit 2270937 
""" 

# random huge number set in the limit to overcome 1000 api limit
res = client.get("erm2-nwe9", query=query)
df = pd.DataFrame.from_records(res)
df.head()<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.10848400556328233, 'fraction_numerical': 0.06536856745479833, 'mean_word_length': 5.206896551724138, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 1, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '523334', 'license': 'MIT', 'n_tokens_mistral': 305, 'n_tokens_neox': 269, 'n_words': 69, 'path': 'notebooks/NYC311_data.ipynb', 'repo_name': 'DataLovecraft/NYC311-Predictor-app', 'size': '719'}