def main(t_current):
# Call the police API
api = PoliceAPI()
# Define tables
crime_categories = pd.DataFrame({'id': [], 'description': []})
outcome_categories = pd.DataFrame({'id': [], 'description': []})
streets = pd.DataFrame({'id': [], 'name': []})
crimes = pd.DataFrame({
'persistent_id': [],
'category': [],
'street': [],
'city': [],
'latitude': [],
'longitude': [],
'date': [],
'context': []
})
outcomes = pd.DataFrame({
'crime': [],
'category': [],
'date': [],
'person_id': []
})
# Transform dates into pandas Series for better manipulation
dates = pd.Series(api.get_dates())
# Get Forces
forces = api.get_forces()
# Get neighbourhoods
neighbourhoods = [f.neighbourhoods for f in forces]
nb_flat = [n for sublist in neighbourhoods for n in sublist]
s_nb_flat = pd.Series(nb_flat).unique()
first_job(api, dates, t_current)
t_last_update = api.get_latest_date()
second_job(api, dates, t_last_update, t_current)
last_job(api, t_current)
'Drugs': 'Blue',
'Bicycle theft': 'Green',
'Criminal damage and arson': 'light yellow',
'Other theft': 'light green',
'Possession of weapons': 'cyan',
'Public order': 'white',
'Shoplifting': 'grey',
'Theft from the person': 'light orange',
'Vehicle crime': 'brown',
'Other crime': 'light blue',
'Robbery': 'Yellow'
}
police = PoliceAPI()
# Get the date range of data
dt_range = police.get_dates()
def format_date_range(date_range):
month_dict = {
1: 'Jan',
2: 'Feb',
3: 'Mar',
4: 'Apr',
5: 'May',
6: 'Jun',
7: 'Jul',
8: 'Aug',
9: 'Sep',
10: 'Oct',
11: 'Nov',
