def get_test_vol(show_plot=False, show_table=False):
test_metrics_file = "./data/TABLE_DAILY_TESTING_METRICS.csv"
test_metrics_headers = [
"Total", "PCR_Tests", "Antigen_Tests", "Pos_Percent"
]
test_metrics_daily_df = load_ncdhhs_data(test_metrics_file,
test_metrics_headers,
show_table=False)
test_metrics_weekly_df = aggregate_weekly(test_metrics_daily_df,
'Total',
show_table=False)
test_metrics_lowess_df = dataframe_lowess(test_metrics_weekly_df,
y_col_name='Total',
x_col_name='Week',
frac_in=0.1,
show_plot=show_plot,
show_table=False)
test_metrics_lowess_df.iat[0, 2] = test_metrics_lowess_df.iat[0, 0]
adj_index = test_metrics_lowess_df.index
adj_index.strftime('% B % d, % Y, % r')
test_metrics_lowess_df['DateString'] = adj_index
if show_table:
print(test_metrics_lowess_df)
return test_metrics_lowess_df
def get_hospital_stats(show_plot=False, col_select = 'Inpatient_Beds_Used'):
hospital_stats_file = "./data/HOSPITAL_BEDS_VENTILATORS.csv"
hospital_stats_headers = ["Vents_Used", "Vents_Avail","ICU_Beds_Used",
"ICU_Beds_Empty_Staffed", "Inpatient_Beds_Used",
"Inpatient_Beds_Empty_Staffed"]
hospital_stats_daily_df = load_ncdhhs_data(hospital_stats_file,
hospital_stats_headers,
show_table=False)
# Drop all rows with NaN
hospital_stats_daily_df = hospital_stats_daily_df.dropna(axis=0, how='any')
# Create a sequence of integers to reference as week from start
hospital_stats_daily_df['Day'] = range(1,len(hospital_stats_daily_df) + 1)
# Add in unstaffed - this is probably not quite right - but close
hospital_stats_daily_df["ICU_Unstaffed"] = 1039
hospital_stats_daily_df["Inpatient_Beds_Unstaffed"] = 4295
hospital_stats_daily_lowess_df = dataframe_lowess(hospital_stats_daily_df,
y_col_name= col_select,
x_col_name='Day',
frac_in=0.3,
show_plot=show_plot,
show_table=False)
adj_index = hospital_stats_daily_lowess_df.index
adj_index.strftime('% B % d, % Y, % r')
hospital_stats_daily_lowess_df['DateString'] = adj_index
return hospital_stats_daily_lowess_df
def get_deaths(show_plot=False, show_table=False):
cases_deaths_file = "./data/TABLE_DAILY_CASE&DEATHS_METRICS.csv"
cases_deaths_headers = ["Cases", "PCR", "Antigen", "Deaths"]
cases_deaths_daily_df = load_ncdhhs_data(cases_deaths_file,
cases_deaths_headers,
show_table=show_table)
deaths_weekly_df = aggregate_weekly(cases_deaths_daily_df,
'Deaths',
show_table=show_table)
deaths_lowess_df = dataframe_lowess(deaths_weekly_df,
y_col_name='Deaths',
x_col_name='Week',
frac_in=0.2,
it_in=0,
show_plot=show_plot,
show_table=show_table)
deaths_lowess_df = deaths_lowess_df.drop(deaths_lowess_df.index[[0, 1]])
deaths_lowess_df['Week'] = range(1, len(deaths_lowess_df) + 1)
adj_index = deaths_lowess_df.index
adj_index.strftime('% B % d, % Y, % r')
deaths_lowess_df['DateString'] = adj_index
if show_table:
print(deaths_lowess_df)
return (deaths_lowess_df)
def get_hospital_metrics(show_plot=False, col_select="Hospitalizations"):
hospital_metrics_file = "./data/HOSPITAL_METRICS_STATE.csv"
hospital_metrics_headers = ["Hospitalizations", "ICU", "Confirmed", "Suspected"]
hospital_metrics_daily_df = load_ncdhhs_data(hospital_metrics_file,
hospital_metrics_headers,
show_table=False)
# Drop all rows with NaN
hospital_metrics_daily_df = hospital_metrics_daily_df.dropna(axis=0, how='any')
# Create a sequence of integers to reference as week from start
hospital_metrics_daily_df['Day'] = range(1,len(hospital_metrics_daily_df) + 1)
hospital_metrics_daily_lowess_df = dataframe_lowess(hospital_metrics_daily_df,
y_col_name=col_select,
x_col_name='Day',
frac_in=0.1,
show_plot=show_plot,
show_table=False)
adj_index = hospital_metrics_daily_lowess_df.index
adj_index.strftime('% B % d, % Y, % r')
hospital_metrics_daily_lowess_df['DateString'] = adj_index
return hospital_metrics_daily_lowess_df