Plotting COVID-19 data
multiple ways to see it.
#collapse
import numpy as np
import librosa
import matplotlib.pyplot as plt
import pickle
from PyEMD import EMD
import numpy as np
import os
import pandas as pd
from scipy import signal
from sklearn.preprocessing import normalize
from scipy.signal import medfilt
from scipy.signal import savgol_filter
import datetime
from matplotlib.ticker import (MultipleLocator, FormatStrFormatter,
AutoMinorLocator)
from mpl_toolkits.axes_grid1 import make_axes_locatable
import matplotlib as mpl
from datetime import date
mpl.rcParams['figure.dpi'] = 100
#collapse
path_data = './my_data/'
path_store_figure = './figures/'
# df = pd.read_csv(path_data+'owid-covid-data.csv')
url = 'https://covid19.who.int/WHO-COVID-19-global-data.csv'
df = pd.read_csv(url)
dates = df['Date_reported'].unique()
dates = [datetime.datetime.strptime(ts, "%Y-%m-%d") for ts in dates]
dates.sort()
sorteddates = [datetime.datetime.strftime(ts, "%Y-%m-%d") for ts in dates]
data_1 = []
data_2 = []
for i in range(len(dates)):
data_1.append(np.sum(df.loc[df['Date_reported']==sorteddates[i]]['Cumulative_deaths'].values))
data_2.append(np.sum(df.loc[df['Date_reported']==sorteddates[i]]['Cumulative_cases'].values))
countries = df['Country'].unique()
all_country = np.zeros((len(countries),len(sorteddates)))
for i in range(len(countries)):
temp = df[df['Country']==countries[i]]
for j in range(len(sorteddates)):
temp_1 = temp[temp['Date_reported']==sorteddates[j]]
if len(temp_1):
all_country[i,j] = temp_1['New_cases']
#collapse
S = []
for i in range(all_country.shape[0]):
# s = all_country[np.where(countries=='United States of America')[0][0],:]
s = np.nan_to_num(all_country[i,:])+1e-10
s[s<0] = 0
s = s/np.max(np.abs(s))
S.append(s)
# take fft
nfft = 512
S = np.array(S)
S_fft = np.abs(np.fft.rfft(S,nfft,axis=1))
# normalize
for i in range(S.shape[0]):
S_fft[i,:] = S_fft[i,:]/(np.max(S_fft[i,:])+10e-10)
#mean and std
S_fft = 20*np.log10(S_fft+10e-20)
S_mu = np.mean(S_fft,axis=0)
S_std = np.std(S_fft,axis=0)/np.sqrt(all_country.shape[0])
# plot time series
fig = plt.subplots(figsize=[6,4])
plt.xkcd()
ax = plt.subplot(1,1,1)
clr_1 = 'tab:blue'
ax.plot(np.sum(all_country,axis=0),label='WORLDWIDE')
ax.plot(all_country[np.where(countries=='United States of America')[0][0],:],label='USA',linewidth=.5)
ax.plot(all_country[np.where(countries=='India')[0][0],:],label='INDIA',linewidth=.5)
ax.plot(all_country[np.where(countries=='Brazil')[0][0],:],label='BRASIL',linewidth=.5)
ax.legend(loc='upper left',fontsize=10,frameon=False)
ax.grid(axis='both', color='gray', linestyle='--', linewidth=.75,alpha=.1)
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
ax.xaxis.set_ticks_position('bottom')
ax.set_xlabel('DAYS SINCE 3rd JAN 2020')
ax.set_ylabel('DAILY COVID-19 CASES')
# ax.text(.3,-5,'MAG. SPECTRUM OF \nDAILY CASES COVID TRACES \nAVG. ACROSS 252 COUNTRIES',\
# c=clr_1,fontsize=6)
fmt = 'png'
plt.savefig('/Users/neeks/Desktop/Documents/work/code/python_codes/notebookCodes/coswara/figures/'\
+'covid_trace_spectrum.'+fmt, dpi=300, format=fmt,transparent=False,bbox_inches='tight')
plt.show()
# plot spectrum
fig = plt.subplots(figsize=[6,4])
ax = plt.subplot(1,1,1)
fs = 1
faxis = np.arange(0,nfft/2+1)*fs/nfft
clr_1 = 'tab:blue'
ax.plot(faxis,S_mu,c=clr_1,linewidth=2)
# ax.plot(faxis,S_mu - S_std,color='r',alpha=.3,linewidth=.5)
# ax.plot(faxis,S_mu + S_std,color='r',alpha=.3,linewidth=.5)
ax.vlines(1/7, -35, 0, colors='gray', linestyles='--',alpha=.3)
ax.vlines(2/7, -35, 0, colors='gray', linestyles='--',alpha=.3)
ax.grid(axis='both', color='gray', linestyle='--', linewidth=.75,alpha=.1)
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
ax.xaxis.set_ticks_position('bottom')
ax.set_xlabel('FREQUENCY [in 1/DAY]')
ax.set_ylabel('SPECTRAL POWER [in dB]')
ax.text(.3,-5,'MAG. SPECTRUM OF \nDAILY CASES COVID TRACES \nAVG. ACROSS 252 COUNTRIES',\
c=clr_1,fontsize=6)
fmt = 'png'
plt.savefig('/Users/neeks/Desktop/Documents/work/code/python_codes/notebookCodes/coswara/figures/'\
+'covid_trace_time_domain.'+fmt, dpi=300, format=fmt,transparent=False,bbox_inches='tight')
plt.show()
#collapse
import json
import requests
import seaborn as sns
from scipy.signal import savgol_filter
sns.set(style="ticks")
mpl.rcParams.update(mpl.rcParamsDefault)
# get COVID data from COVID19india.ORG
resp = requests.get('https://api.covid19india.org/data.json')
if resp.status_code != 200:
# This means something went wrong.
raise ApiError('GET /tasks/ {}'.format(resp.status_code))
daily_testing = {}
daily_testing['totalsamplestested'] = []
daily_testing['samplereportedtoday'] = []
daily_testing['date'] = []
daily_testing['vaccinated'] = []
for item in resp.json()['tested']:
if item['totalsamplestested']!='':
daily_testing['totalsamplestested'].append(int(item['totalsamplestested']))
else:
daily_testing['totalsamplestested'].append(0)
if item['totalindividualsvaccinated']!='':
daily_testing['vaccinated'].append(int(item['totalindividualsvaccinated']))
else:
daily_testing['vaccinated'].append(0)
# daily_testing['date'].append(item['updatetimestamp'])
daily_cases = {}
daily_cases['dailyconfirmed'] = []
daily_cases['dailydeceased'] = []
daily_cases['dailyrecovered'] = []
daily_cases['date'] = []
for item in resp.json()['cases_time_series']:
daily_cases['dailyconfirmed'].append(int(item['dailyconfirmed']))
daily_cases['dailydeceased'].append(int(item['dailydeceased']))
daily_cases['dailyrecovered'].append(int(item['dailyrecovered']))
daily_cases['date'].append(item['date'])
total_cases = {}
total_cases['totalconfirmed'] = []
total_cases['totaldeceased'] = []
total_cases['totalrecovered'] = []
total_cases['date'] = []
for item in resp.json()['cases_time_series']:
total_cases['totalconfirmed'].append(int(item['totalconfirmed']))
total_cases['totaldeceased'].append(int(item['totaldeceased']))
total_cases['totalrecovered'].append(int(item['totalrecovered']))
total_cases['date'].append(item['date'])
#collapse
fig = plt.subplots(figsize=(10,5))
clr_1 = "tab:blue"
clr_2 = "tab:orange"
clr_3 = "tab:green"
ax = plt.subplot(1,1,1)
ax.semilogy([24*60*60/i if i>0 else 0 for i in daily_cases['dailyconfirmed']],color=clr_1,label='SOMEONE BECOMES A PATIENT',
basey=2)
ax.plot([24*60*60/i if i>0 else 0 for i in daily_cases['dailyrecovered']],color=clr_2,label='SOMEONE RECOVERS')
ax.plot([24*60*60/i if i>0 else 0 for i in daily_cases['dailydeceased']],color=clr_3,label='SOMEONE DIES')
ax.xaxis.set_minor_locator(AutoMinorLocator())
ax.yaxis.set_minor_locator(AutoMinorLocator())
ax.tick_params(which='both', width=2)
ax.grid(axis='y', color='gray', linestyle='--', linewidth=.75,alpha=.1)
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
ax.xaxis.set_ticks_position('bottom')
ax.spines['bottom'].set_position(('axes', -.05))
ax.yaxis.set_ticks_position('left')
ax.text(300,2**16,'SOMEONE GETS COVID',fontsize=10,color=clr_1)
ax.text(300,2**15,'SOMEONE IS NO MORE',fontsize=10,color=clr_3)
ax.text(300,2**14,'SOMEONE RECOVERS',fontsize=10,color=clr_2)
xticks = [0,55,76,95,109,123,153,184,215,len(total_cases['totalconfirmed'])-1]
cnt = 0
str_lock = ['FIRST CASE','LOCKDOWN-1','LOCKDOWN-2','LOCKDOWN-3','LOCKDOWN-4','UNLOCK-1','UNLOCK-2','UNLOCK-3'\
,'UNLOCK-4',' ']
xlabels = []
ind_1 = 6
for i in xticks:
ax.vlines(i,min(total_cases['totaldeceased']),max(total_cases['totaldeceased']),
linestyles ="--", colors ="gray",alpha=0.5,linewidth=.75)
ax.vlines(i,min(total_cases['totaldeceased']),max(total_cases['totaldeceased']),
linestyles ="--", colors ="gray",alpha=0.5,linewidth=.75)
ax.text(x=i-6,y=25000,s=str_lock[cnt],rotation=90,fontsize=7,color='gray',alpha=0.6)
if i == len(total_cases['totalconfirmed']):
xlabels.append(total_cases['date'][-1][:ind_1])
else:
xlabels.append(total_cases['date'][xticks[cnt]][:ind_1])
ax.text(i-6,.3,xlabels[cnt],rotation=90,fontsize=7,color='gray',alpha=0.8)
cnt = cnt+1
ax.set_ylabel('EVERY FEW SECONDS IN INDIA',fontsize=10)
ax.set_xlabel('DAYS SINCE FIRST CASE ',fontsize=10)
ax.spines['top'].set_color('none')
ax.spines['bottom'].set_color('gray')
ax.spines["left"].set_color('gray')
ax.tick_params(axis='x', colors='gray')
ax.text(250,.5,'by @neeksww',fontsize=8,color='gray',alpha=0.6)
ax.text(250,.25,'data source: https://www.covid19india.org/',fontsize=8,color='gray',alpha=0.6)
ax.set_xlim(55,550)
fmt = 'png'
plt.savefig('/Users/neeks/Desktop/Documents/work/code/python_codes/notebookCodes/coswara/figures/'\
+'covid_status_time_whole_india.'+fmt, dpi=300, format=fmt,transparent=True,bbox_inches='tight')
plt.show()
#collapse
# get vaccination data
url = 'https://raw.githubusercontent.com/owid/covid-19-data/master/public/data/vaccinations/vaccinations.csv'
df = pd.read_csv(url)
df = df[df['location']=='India'].reset_index(drop=True)
vals = df['total_vaccinations'].values
d_0 = date(2020, 1, 30)
d_1 = date(int(df['date'][0].split('-')[0]), int(df['date'][0].split('-')[1][1]), int(df['date'][0].split('-')[2]))
d_2 = date(int(df['date'][len(df)-1].split('-')[0]), int(df['date'][len(df)-1].split('-')[1][1]), int(df['date'][len(df)-1].split('-')[2]))
delta = d_1 - d_0
delta.days
daily_cases['vaccinations'] = []
cnt = 0
for i in range(len(daily_cases['dailydeceased'])):
if i < (d_1-d_0).days:
daily_cases['vaccinations'].append(0)
elif i < (d_2-d_0).days:
daily_cases['vaccinations'].append(vals[cnt])
cnt = cnt+1
else:
daily_cases['vaccinations'].append(vals[cnt-1])
daily_cases['vaccinations'] = np.array([0] + list(np.diff(daily_cases['vaccinations'])))
daily_cases['vaccinations'][daily_cases['vaccinations']==0] = np.nan
#plot everything
fig = plt.subplots(figsize=(10,6))
clr_1 = "tab:blue"
clr_2 = "tab:red"
clr_3 = "tab:green"
clr_4 = 'cornflowerblue'
LW = 1.5
ax1 = plt.subplot(1,1,1)
x_11 = np.arange(0,len(daily_cases['dailyconfirmed']),1)
y_11 = daily_cases['dailyconfirmed']
y_12 = daily_cases['dailyrecovered']
y_max = np.ceil(max(y_11)/1e5)*1e5
ax1.plot(x_11,y_11,color=clr_1,label='DAILY CASES', linewidth = LW)
ax1.plot(x_11,y_12,color=clr_2,label='DAILY RECOVERED', linewidth = LW)
ax1.grid(axis='both', color='gray', linestyle='--', linewidth=.75,alpha=.1)
ax1.spines['top'].set_color('none')
ax1.spines['bottom'].set_position('center')
ax1.spines["left"].set_bounds(0, y_max)
ax1.spines["left"].set_color('gray')
ax1.spines["right"].set_bounds(0, 0)
ax1.spines['bottom'].set_color('gray')
ax1.tick_params(axis='y', colors='gray')
ax1.tick_params(axis='x', colors='gray')
ax1.set_yticks(np.arange(0, y_max,50000))
ax1.set_ylim([-y_max,y_max])
top_pad_1 = 50000
top_pad_2 = 100000
ax1.text(10,y_max-top_pad_1,'INDIA',fontsize=10,color='k')
ax1.text(10,y_max-top_pad_2,'DAILY CASES',fontsize=10,color=clr_1)
ax1.text(85,y_max-top_pad_2,'DAILY RECOVERY',fontsize=10,color=clr_2)
ax1.text(180,y_max-top_pad_2,'DAILY DECEASED',fontsize=10,color=clr_3)
ax1.text(275,y_max-top_pad_2,'DAILY VACCINATION',fontsize=10,color=clr_4)
ax1.text(230,-20000,'DAYS',fontsize=10,color='k')
ax1.tick_params(axis='y', colors='gray',direction='out')
ax2 = ax1.twinx()
x_21 = np.arange(0,len(daily_cases['dailydeceased']),1)
y_21 = daily_cases['dailydeceased']
y_max = np.ceil(max(y_21)/1e3)*1e3
ax2.plot(x_21,y_21,color=clr_3,label='DAILY DECEASED', linewidth = LW)
ax2.grid(axis='both',color='gray', linestyle='--', linewidth=.75,alpha=.1)
# ax2.xaxis.set_minor_locator(AutoMinorLocator())
# ax2.yaxis.set_minor_locator(AutoMinorLocator())
ax2.spines['top'].set_color('none')
ax2.spines['bottom'].set_position('center')
ax2.spines["left"].set_bounds(0, y_max)
ax2.spines["left"].set_bounds(0, 0)
ax2.spines["right"].set_bounds(0, y_max)
ax2.spines["right"].set_position(('axes',0))
ax2.spines['bottom'].set_color('gray')
ax2.spines["right"].set_color('gray')
ax2.tick_params(axis='x', colors='gray')
ax2.set_yticks(np.arange(0,y_max,500)[1:])
ax2.set_ylim([-y_max,y_max])
plt.gca().invert_yaxis()
ax1.tick_params(axis='y', colors='gray',direction='in', pad=10)
ax2.tick_params(axis='y', colors='gray',direction='out', pad=-40)
xticks = [0,55,76,95,109,123,153,184,215,len(total_cases['totalconfirmed'])-1]
cnt = 0
str_lock = ['FIRST CASE','LOCKDOWN-1','LOCKDOWN-2','LOCKDOWN-3','LOCKDOWN-4','UNLOCK-1','UNLOCK-2','UNLOCK-3'\
,'UNLOCK-4',' ']
xlabels = []
ind_1 = 6
for i in xticks:
ax1.vlines(i,0,max(daily_cases['dailyconfirmed']),
linestyles ="--", colors ="gray",alpha=0.5,linewidth=.75)
ax2.vlines(i,min(total_cases['totaldeceased']),max(total_cases['totaldeceased']),
linestyles ="--", colors ="gray",alpha=0.5,linewidth=.75)
ax1.text(i-6,250000,str_lock[cnt],rotation=90,fontsize=7,color='gray',alpha=0.4)
if i == len(total_cases['totalconfirmed']):
xlabels.append(total_cases['date'][-1][:ind_1])
else:
xlabels.append(total_cases['date'][xticks[cnt]][:ind_1])
ax1.text(i-6,100000,xlabels[cnt],rotation=90,fontsize=7,color='gray',alpha=0.4)
cnt = cnt+1
ax1.set_ylabel('NUMBER OF INDIVIDUALS',fontsize=10)
ax2.text(10,y_max-300,'by @neeksww',fontsize=8,color='gray',alpha=0.6)
ax2.text(10,y_max-100,'data source: https://www.covid19india.org/',fontsize=8,color='gray',alpha=0.6)
ax3 = ax1.twinx()
x_31 = np.arange(0,len(daily_cases['vaccinations']))
# y_31 = savgol_filter(daily_cases['vaccinations'],3,1)
y_31 = daily_cases['vaccinations']
y_max = np.ceil(np.max(np.nan_to_num(np.array(y_31)))/1e6)*1e6
LW = 2
ax3.plot(x_31,y_31,color=clr_4,label='DAILY DECEASED', alpha=.5, linewidth = LW)
ax3.spines['top'].set_color('none')
ax3.spines['bottom'].set_position('center')
ax3.spines["left"].set_bounds(0,0)
ax3.spines["right"].set_color(clr_4)
ax3.spines["left"].set_color('gray')
ax3.spines["right"].set_bounds(0, y_max)
ax3.spines['bottom'].set_color('gray')
ax3.tick_params(axis='y', colors=clr_4)
ax3.set_yticks(np.arange(0, y_max,5000000))
ax3.set_ylim([-y_max,y_max])
ax3.set_ylabel('VACCINATIONS',fontsize=10,color=clr_4)
fmt = 'png'
plt.savefig('/Users/neeks/Desktop/Documents/work/code/python_codes/notebookCodes/coswara/figures/'\
+'covid_status_whole_india.'+fmt, dpi=300, format=fmt,transparent=True,bbox_inches='tight')
plt.show()
#collapse
dataset = {}
dataset['month'] = []
dataset['day'] = []
dataset['year'] = []
dataset['dailyconfirmed'] = daily_cases['dailyconfirmed']
dataset['dailyrecovered'] = daily_cases['dailyrecovered']
dataset['dailydeceased'] = daily_cases['dailydeceased']
# date creation
for date in total_cases['date']:
day = int(date.split(' ' )[0])
month = date.split(' ')[1]
if month == 'January':
month_val = 1
if month == 'February':
month_val = 2
if month == 'March':
month_val = 3
if month == 'April':
month_val = 4
if month == 'May':
month_val = 5
if month == 'June':
month_val = 6
if month == 'July':
month_val = 7
if month == 'August':
month_val = 8
if month == 'September':
month_val = 9
if month == 'October':
month_val = 10
if month == 'November':
month_val = 11
if month == 'December':
month_val = 12
year_val = 2020
day_val = datetime.datetime(year_val, month_val, day).strftime("%A")
# push into dict
dataset['day'].append(day_val)
dataset['month'].append(month_val)
dataset['year'].append(year_val)
df = pd.DataFrame.from_dict(dataset)
label_day = ['Monday','Tuesday','Wednesday','Thursday','Friday','Saturday','Sunday']
fig = plt.subplots(figsize=[9,5])
ax = plt.subplot(1,1,1)
day_mu = []
for i in label_day:
# if i == 'Monday' or i == 'Saturday':
temp = df[df['day']==i]['dailyconfirmed'].values
ax.plot(temp,'-',label=i[:3],marker='o',markeredgecolor='k')
day_mu.append(np.mean(df[df['day']==i]['dailyconfirmed']))
ax.grid(True)
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
ax1.grid(color='gray', linestyle='--', linewidth=1,alpha=.1)
ax.set_xlabel('COUNT OF DAY SINCE FIRST COVID-19 CASE',fontsize=14)
ax.set_ylabel('POSITIVE CASE COUNT',fontsize=14)
ax.xaxis.set_minor_locator(AutoMinorLocator())
ax.yaxis.set_minor_locator(AutoMinorLocator())
ax.tick_params(which='both', width=2)
ax.tick_params(which='major', length=7)
ax.tick_params(which='minor', length=4, color='gray')
ax.legend(frameon=False,fontsize=14)
plt.xticks(fontsize=13)
plt.yticks(fontsize=13)
plt.show()
#collapse
df = pd.read_csv('./my_data/covid/tested_numbers_icmr_data.csv')
dates = df["Tested As Of"].values
daily_RTPCR_tets = df["Daily RTPCR tests"].values
temp = df["Total Samples Tested"].values
temp = df["Total Positive Cases"].values
df = pd.read_csv('./my_data/covid/state_wise_daily.csv')
df = pd.read_csv('https://api.covid19india.org/csv/latest/state_wise_daily.csv')
# temp_1 = normalize(temp_1,norm='max', axis=0)
state_labels = ['KA','TN','MH','DL','GJ','KL']
state_labels = ['MH','KA','AP','UP','TN','RJ','TG','AS','CH','KL','DL','BR',\
'GJ','OR','WB','HR','JK','HP','MP','PB','NL','GA','JH','AN',\
'MN','ML','SK','TR',
]
state_labels_= ['MH','KA','AP','UP','TN','RJ','TS','AS','CG','KL','DL','BR',\
'GJ','OD','WB','HR','JK','HP','MP','PB','NL','GA','JH','AN',\
'MN','ML','SK','TR'
]
clr_1 = 'tab:blue'
clr_2 = 'tab:orange'
cnt = 0
start_cases = []
start_decea = []
current_cases = []
for i in state_labels:
cnt+= 1
start_cases.append(np.where(np.cumsum(df[df['Status']=='Confirmed'][i].values)>5)[0][0])
start_decea.append(np.where(np.cumsum(df[df['Status']=='Deceased'][i].values)>5)[0][0])
current_cases.append(df[df['Status']=='Confirmed'][i].values[-1])
indx = np.argsort(current_cases)[::-1]
fig = plt.subplots(figsize=[50,30])
cnt = 0
all_states_cases = []
all_states_decea = []
plt.xkcd()
for i in indx:
cnt+= 1
ax1 = plt.subplot(4,7,cnt)
ax2 = ax1.twinx()
temp_1 = medfilt(df[df['Status']=='Confirmed'][state_labels[i]].values,3)
all_states_cases.append(temp_1/max(temp_1))
# temp_1 = savgol_filter(df[df['Status']=='Confirmed'][state_labels[i]].values,window_length=7, polyorder=1,\
# deriv=0, delta=1.0, axis=0, mode='nearest')
temp_2 = medfilt(df[df['Status']=='Deceased'][state_labels[i]].values,3)
all_states_decea.append(temp_2/(max(temp_2)))
# temp_2 = savgol_filter(df[df['Status']=='Deceased'][state_labels[i]].values,window_length=7, polyorder=1,\
# deriv=0, delta=1.0, axis=0, mode='nearest')
ax1.plot(np.arange(0,len(temp_1),1),temp_1,color=clr_1, linewidth=3)
ax1.spines['right'].set_color('none')
ax1.spines['left'].set_color('none')
ax1.spines['top'].set_color('none')
ax1.spines['bottom'].set_color('gray')
ax1.tick_params(axis='y', colors=clr_1)
ax2.tick_params(axis='x', colors='gray')
ax1.text(0,max(temp_1)-0.0*max(temp_1),'Indian State: '+state_labels_[i],fontsize=12,color='tab:red',alpha=0.9,
fontweight='bold')
# ,\bbox=dict(facecolor='gray', alpha=0.2))
ax1.text(0,max(temp_1)-0.1*max(temp_1),'daily cases',fontsize=14,color=clr_1)
ax1.text(0,max(temp_1)-0.15*max(temp_1),'daily deceased',fontsize=14,color=clr_2)
ax1.text(0,max(temp_1)-0.3*max(temp_1),'For days since:\n'+ df['Date'][0].split('-20')[0] +' to '+\
df['Date'][len(df)-1].split('-20')[0],fontsize=14,color='black',alpha=0.75)
ax1.text(0,max(temp_1)-0.5*max(temp_1),'With three sample\n median filtered',fontsize=10,color='gray',
rotation=0,alpha=0.6)
ax1.text(0,max(temp_1)-0.9*max(temp_1),'data source:\n https://www.covid19india.org/',fontsize=10,color='gray',
rotation=0,alpha=0.4)
if cnt == 4:
ax1.text(len(temp_1)-10,0,'@neeksww',fontsize=14,color='gray',
rotation=90,alpha=0.3)
ax1.grid(color='gray', linestyle='--', linewidth=1,alpha=.1)
ax2.plot(np.arange(0,len(temp_2),1),temp_2,color=clr_2, linewidth=3)
ax2.tick_params(axis='x', labelcolor=clr_2)
ax2.spines['top'].set_color('none')
ax2.spines['right'].set_color('none')
ax2.spines['left'].set_color('none')
ax2.spines['bottom'].set_color('gray')
ax2.tick_params(axis='y', colors=clr_2)
# clr_face = (79/256,178/256,151/256)
# ax1.set_facecolor(clr_face)
# ax2.set_facecolor(clr_face)
fmt = 'png'
plt.savefig('/Users/neeks/Desktop/Documents/work/code/python_codes/notebookCodes/coswara/figures/'\
+'covid_status_india.'+fmt, dpi=300, format=fmt,transparent=False,bbox_inches='tight')
plt.show()
#collapse
if 0:
len(all_states_cases[0])
x = signal.correlate(all_states_cases[0],all_states_cases[4])
print(396-np.argmax(x))
print(x.shape)
plt.plot(x.T)
plt.show()
fig, ax = plt.subplots(figsize=[12,6])
for i in range(len(all_states_cases)):
plt.plot(all_states_cases[i])
plt.show()
fig, ax = plt.subplots(figsize=[12,6])
im = ax.imshow(all_states_cases,origin='lower',aspect='auto',extent =\
[0,temp_1.shape[0], 0, len(all_states_cases)],
cmap='Blues',vmin = 0, vmax =1)
divider = make_axes_locatable(ax)
colorbar_ax = fig.add_axes([.95, 0.1, 0.015, 0.5])
fig.colorbar(im, cax=colorbar_ax)
plt.show()
fig, ax = plt.subplots(figsize=[12,6])
im = ax.imshow(all_states_decea,origin='lower',aspect='auto',extent =\
[0,temp_1.shape[0], 0, len(all_states_cases)],
cmap='Blues',vmin = 0, vmax =1)
divider = make_axes_locatable(ax)
colorbar_ax = fig.add_axes([.95, 0.1, 0.015, 0.5])
fig.colorbar(im, cax=colorbar_ax)
plt.show()
Thats' it for now!