def total_death_chart(root):
global fig, ax
total_death_date = [
i.replace('\"', '')
for i in list(set(re.findall(r'categories:.*', main[33])))[0].replace(
'categories: [', '').replace(']', '').replace('}', '').replace(
' ', '').split(',') if i != ''
]
total_death = [
int(i)
for i in data[10][0].replace('data: [', '').replace(']', '').replace(
'}', '').replace(' ', '').split(',') if i != ''
]
fig, ax = plt.subplots()
plt.xticks(np.arange(0, len(total_death_date), 5.0))
def format_func(value, tick_number):
return ShortScale(int(value))
ax.yaxis.set_major_formatter(plt.FuncFormatter(format_func))
fig.set_size_inches(13, 6)
line_info, datax = plot_line(total_death_date, total_death, 'white',
'Deaths', ax, fig, 'Total Deaths')
plt.xticks(rotation=45)
canvas = FigureCanvasTkAgg(fig, master=root)
plot_widget = canvas.get_tk_widget()
fig.canvas.mpl_connect(
"motion_notify_event",
lambda event: hover(event, line_info, fig, ax, datax))
return plot_widget
def active_cases_chart(root):
active_cases_date = [
i.replace('\"', '')
for i in list(set(re.findall(r'categories:.*', main[25])))[0].replace(
'categories: [', '').replace(']', '').replace('}', '').replace(
' ', '').split(',') if i != ''
]
active_cases = [
int(i)
for i in data[3][0].replace('data: [', '').replace(']', '').replace(
'}', '').replace(' ', '').split(',') if i != ''
]
fig, ax = plt.subplots()
x_ticks = np.arange(0, len(active_cases_date), 6)
plt.xticks(x_ticks)
def format_func(value, tick_number):
return ShortScale(int(value))
ax.yaxis.set_major_formatter(plt.FuncFormatter(format_func))
fig.set_size_inches(13, 6)
line_info, datax = plot_line(active_cases_date, active_cases, 'white',
'Currently Infected', ax, fig, 'Active Cases')
plt.xticks(rotation=45)
canvas = FigureCanvasTkAgg(fig, master=root)
plot_widget = canvas.get_tk_widget()
fig.canvas.mpl_connect(
"motion_notify_event",
lambda event: hover(event, line_info, fig, ax, datax))
return plot_widget
def infected_vs_recovered_chart(root):
date = [
i.replace('\"', '')
for i in list(set(re.findall(r'categories:.*', main[28])))[0].replace(
'categories: [', '').replace(']', '').replace('}', '').replace(
' ', '').split(',') if i != ''
]
daily_cases = [
i for i in data[2][0].replace('data: [', '').replace(']', '').replace(
'}', '').replace(' ', '').split(',') if i != ''
]
daily_cases = [
0 if daily_cases[i] == 'null' else int(daily_cases[i])
for i in range(len(daily_cases))
]
daily_cured = [
i for i in data[5][0].replace('data: [', '').replace(']', '').replace(
'}', '').replace(' ', '').split(',') if i != ''
]
daily_cured = [
0 if daily_cured[i] == 'null' else int(daily_cured[i])
for i in range(len(daily_cured))
]
fig, ax = plt.subplots()
x_ticks = np.arange(0, len(date), 5)
plt.xticks(x_ticks)
def format_func(value, tick_number):
return ShortScale(int(value))
ax.yaxis.set_major_formatter(plt.FuncFormatter(format_func))
fig.set_size_inches(13, 6)
line_info1, line_info2, datax = plot_double_line(
date, daily_cured, date, daily_cases, '#baffba', '#ffbaba',
'New Recoviries', 'New Infected', ax, fig,
'New Cases vs. New Recoveries')
plt.xticks(rotation=45)
canvas = FigureCanvasTkAgg(fig, master=root)
plot_widget = canvas.get_tk_widget()
fig.canvas.mpl_connect(
"motion_notify_event",
lambda event: hover(event, line_info1, fig, ax, datax))
fig.canvas.mpl_connect(
"motion_notify_event",
lambda event: hover(event, line_info2, fig, ax, datax))
return plot_widget
def outcome_of_total_close_cases(root):
date = [i.replace('\"', '') for i in list(set(re.findall(r'categories:.*', main[32])))[0].replace('categories: [', '').replace(']', '').replace('}', '').replace(' ', '').split(',') if i != '']
death_rate = [i for i in data[9][0].replace('data: [', '').replace(']', '').replace('}', '').replace(' ', '').split(',') if i != '']
death_rate = [0 if death_rate[i] == 'null' else float(death_rate[i]) for i in range(len(death_rate))]
recovery_rate = [i for i in data[9][1].replace('data: [', '').replace(']', '').replace('}', '').replace(' ', '').split(',') if i != '']
recovery_rate = [0 if recovery_rate[i] == 'null' else float(recovery_rate[i]) for i in range(len(recovery_rate))]
fig, ax = plt.subplots()
x_ticks = np.arange(0, len(date), 10)
plt.xticks(x_ticks)
fig.set_size_inches(13, 6)
line_info1, line_info2, datax = plot_double_line(date, death_rate, date, recovery_rate, '#ffbaba', '#baffba', 'Death Rate', 'Recovery Rate', ax, fig, 'Outcome of total closed cases (recovery rate vs death rate)')
plt.xticks(rotation=45)
canvas = FigureCanvasTkAgg(fig, master=root)
plot_widget = canvas.get_tk_widget()
fig.canvas.mpl_connect("motion_notify_event", lambda event: hover(event, line_info1, fig, ax, datax))
fig.canvas.mpl_connect("motion_notify_event", lambda event: hover(event, line_info2, fig, ax, datax))
return plot_widget
def total_serious_and_critical_cases(root):
total_serious_and_critical_cases_date = [i.replace('\"', '') for i in list(set(re.findall(r'categories:.*', main[31])))[0].replace('categories: [', '').replace(']', '').replace('}', '').replace(' ', '').split(',') if i != '']
total_serious_and_critical_cases = [i for i in data[7][0].replace('data: [', '').replace(']', '').replace('}', '').replace(' ', '').split(',') if i != '']
total_serious_and_critical_cases = [0 if total_serious_and_critical_cases[i] == 'null' else int(total_serious_and_critical_cases[i]) for i in range(len(total_serious_and_critical_cases))]
fig, ax = plt.subplots()
x_ticks = np.arange(0, len(total_serious_and_critical_cases_date), 10)
plt.xticks(x_ticks)
def format_func(value, tick_number):
return ShortScale(int(value))
ax.yaxis.set_major_formatter(plt.FuncFormatter(format_func))
fig.set_size_inches(13, 6)
line_info, datax = plot_line(total_serious_and_critical_cases_date, total_serious_and_critical_cases, 'white', 'Serious and Critical Cases', ax, fig, 'Total Serious and Critical Cases')
plt.xticks(rotation=45)
canvas = FigureCanvasTkAgg(fig, master=root)
plot_widget = canvas.get_tk_widget()
fig.canvas.mpl_connect("motion_notify_event", lambda event: hover(event, line_info, fig, ax, datax))
return plot_widget