def get_predictions():
'''Function that runs once a week to calculte new predictions on the current data and stores the predictions on a Postgres DB.'''
now = datetime.now()
current_time = now.strftime("%H:%M:%S")
print('UPDATING PREDICTION DATA ' + str(datetime.today()) + ' AT ' +
str(current_time) + "\n\n\n")
df = __get_data()
location_list = hf.get_df_by_location(df)
location_list = hf.format_dfs_for_prediction(location_list)
tampa_prediction = hf.get_prediction(location_list[0])
st_pete_prediction = hf.get_prediction(location_list[1])
health_prediction = hf.get_prediction(location_list[2])
# sarasota_prediction = hf.get_prediction(location_list[3])
new_df = pd.merge(tampa_prediction, st_pete_prediction, on=['ds'])
new_df = pd.merge(new_df, health_prediction, on=['ds'])
# new_df = pd.merge(new_df, sarasota_prediction, on=['ds'])
new_df = new_df.rename(
columns={
'ds': 'DS',
'yhat_x': 'YHAT_TAMPA',
'yhat_y': 'YHAT_ST_PETE',
'yhat': 'YHAT_HEALTH'
})
new_df.to_sql('prediction',
con=db.engine,
if_exists='replace',
index=False)
def create_general_graphs(data, graph_type):
df = hf.string_to_df(data)
prediction_df = pd.read_sql_table('prediction', con=db.engine)
df['dates'] = df['dates'].apply(lambda date: datetime.strptime(date, "%B %d %Y"))
location_list = hf.get_daily_cases_by_location(hf.get_df_by_location(df))
prediction_list = hf.get_prediction_by_location(prediction_df)
return dict(data=gg.generate_daily_bar_graph(location_list),
layout=gg.generate_bar_layout('Daily Cases on USF Campuses', 'group')), \
dict(data=gg.generate_total_scatter(graph_type, location_list, prediction_list),
layout=gg.general_graph_layout('Total Cases USF Campuses'))
def update_cards(data):
df = hf.string_to_df(data)
dfs_by_location = hf.get_df_by_location(df)
total_cases_tampa, total_cases_st_pete, total_cases_health = hf.get_total_cases_by_location(dfs_by_location)
daily_cases_tampa, daily_cases_st_pete, daily_cases_tampa_health = hf.get_daily_cases_by_location(
dfs_by_location)
return str(total_cases_tampa), \
str(total_cases_health), \
str(total_cases_st_pete), \
hf.create_daily_cases_str(daily_cases_tampa), \
hf.create_daily_cases_str(daily_cases_tampa_health), \
hf.create_daily_cases_str(daily_cases_st_pete), \
def updateCards(data):
try:
df = hf.string_to_df(data)
# Get for each location
dfByLocation = hf.get_df_by_location(df)
# Get total cases for each location
totalCasesTampa, totalCasesStPete, totalCasesHealth, totalCasesSarasota = hf.get_total_cases_by_location(
dfByLocation)
# Get daily cases for each location
dailyCasesTampa, dailyCasesStPete, dailyCasesHealth, dailyCasesSarasota = hf.get_daily_cases_by_location(
dfByLocation)
return totalCasesTampa + ' cases', totalCasesHealth + ' cases',totalCasesStPete + ' cases',\
hf.create_daily_cases_string(dailyCasesTampa), hf.create_daily_cases_string(dailyCasesHealth),\
hf.create_daily_cases_string(dailyCasesStPete), totalCasesSarasota + ' cases',\
hf.create_daily_cases_string(dailyCasesSarasota)
except Exception as e:
print('updateCards: ', e)
raise PreventUpdate