def rates(df_states, min_value, window = 3):
states = sorted(set(df_states['state'].tolist()))
l = []
for i in states:
increase_deaths = common.get_rate_increase(
df = df_states[(df_states['state']==i) & (df_states['deaths'] > min_value)],
key = 'deaths', window =window)
increase_cases = common.get_rate_increase(
df = df_states[(df_states['state']==i) & (df_states['cases'] > min_value)],
key = 'cases', window =window)
if len(increase_deaths) == 0 or len(increase_deaths) == 1 or math.isnan(increase_deaths[-1]):
last_value_deaths = None
double_r_deaths = None
else:
last_value_deaths = round(increase_deaths[-1],2)
double_r_deaths = common.get_double_rate(last_value_deaths)
if len(increase_cases) == 0 or len(increase_cases) == 1 or math.isnan(increase_cases[-1]):
last_value_cases = None
double_r_cases = None
else:
last_value_cases= round(increase_cases[-1],2)
double_r_cases = common.get_double_rate(last_value_cases)
l.append([i, last_value_deaths, double_r_deaths,
last_value_cases, double_r_cases])
l.insert(0, ['state', 'deaths_rate', 'deaths_double', 'cases_rate', 'cases_double'])
with open('html_temp/rates.csv', 'w') as write_obj:
writer = csv.writer(write_obj)
writer.writerows(l)
def dy_dx(territory_key, territory, df, window, key, plot_height, plot_width, min_value = 0):
"""
Create a figure and metrics for the rate of increase or decrease
"""
increase = common.get_rate_increase(
df = df[(df[territory_key]==territory) & (df[key] > min_value)],
key = key, window =window)
if len(increase) == 0 or len(increase) == 1 or math.isnan(increase[-1]):
return None, None, None
last_val = increase[-1]
double_rate = common.get_double_rate(last_val)
if last_val < 1:
n = common.get_days_less_than_0(increase)
msg = 'under 1 for {n} days'.format(n = n)
else:
if double_rate > 14:
msg = 'flat'
else:
msg = 'doubles every {b} days'.format(b = round(double_rate))
p = figure( plot_height = plot_height, plot_width = plot_width,
title = '{key}: {msg}'.format(
msg = msg,
key = key,
)
)
p.line(x = range(len(increase)), y = increase )
p.line(x = range(len(increase)), y = [1 for x in increase],
line_dash = 'dashed', color = 'black')
return last_val, double_rate, p
def all_states(df_states,
key,
min_value,
window=3,
plot_height=300,
plot_width=300):
states = sorted(set(df_states['state'].tolist()))
p_list = []
for i in states:
increase = common.get_rate_increase(
df=df_states[(df_states['state'] == i)
& (df_states[key] > min_value)],
key=key,
window=window)
if len(increase) == 0 or len(increase) == 1 or math.isnan(
increase[-1]):
continue
min_val = increase[-1]
if min_val < 1:
n = common.get_days_less_than_0(increase)
msg = 'under 1 for {n} days'.format(n=n)
else:
double_rate = common.get_double_rate(min_val)
msg = 'doubles every {b} days'.format(b=round(double_rate))
p = figure(plot_height=plot_height,
plot_width=plot_width,
title='{state}: {msg}'.format(state=i, msg=msg))
p.line(x=range(len(increase)), y=increase)
p.line(x=range(len(increase)),
y=[1 for x in increase],
line_dash='dashed',
color='black')
p_list.append(p)
grid = gridplot(p_list, ncols=4)
return grid