{"id":19920,"date":"2021-02-07T22:41:58","date_gmt":"2021-02-08T03:41:58","guid":{"rendered":"http:\/\/bangla.salearningschool.com\/recent-posts\/?p=19920"},"modified":"2025-06-25T02:24:50","modified_gmt":"2025-06-25T02:24:50","slug":"health_status_visualizations-health-system-performance-canada-and-others","status":"publish","type":"post","link":"http:\/\/bangla.sitestree.com\/?p=19920","title":{"rendered":"health_status_visualizations, Health System Performance, Canada and Others"},"content":{"rendered":"\n
\"Justetc<\/a><\/figure>\n\n\n\n

Justetc Social Services (non-profit)<\/a>Jan 31<\/a> \u00b7 4 min read<\/p>\n\n\n\n

import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inlinefrom __future__ import print_function
from ipywidgets import interact, interactive, fixed, interact_manual
import ipywidgets as widgetshealth_status = pd.read_excel('..\/data\/health-status.xls')
health_status.head()<\/pre>\n\n\n\n
\"png\"\/<\/figure>\n\n\n\n
health_status.set_index(['Indicator'])
#health_status.loc[health_status['Cancer Mortality (F)']]
#health_status.index.unique()
indicators = pd.Index(health_status['Indicator']).unique()
years = health_status['Data year'].unique()
indicators[0], years[0]('Cancer Mortality (F)', '2013')cancer_mortality_2013 = health_status.loc[  (health_status['Indicator'] == indicators[0]) & (health_status['Data year'] == years[0]) ]
cancer_mortality = health_status.loc[  (health_status['Indicator'] == indicators[0])  & (health_status['Data year'] != 2012) ]
cancer_mortality<\/pre>\n\n\n\n
\"png\"\/<\/figure>\n\n\n\n
plt.rcParams['figure.figsize'] = [15, 9]
#plt.scatter(cancer_mortality['Data year'], cancer_mortality['Value']) #, s=cancer_mortality['Value']*10)
for aYear in years: 
    data = health_status.loc[  (health_status['Indicator'] == indicators[0])  & (health_status['Data year'] == aYear) ]
    plt.scatter(data['Data year'], data['Region'], s=cancer_mortality['Value']*10 )
    plt.show()<\/pre>\n\n\n\n
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years = [ int(aYear) for aYear in years if (aYear != 'Not applicable') and len( str(aYear).split(' ')) <= 1 ]
years = sorted(years)
years[2012, 2013, 2013, 2014, 2014, 2015, 2015]plt.rcParams['figure.figsize'] = [8, 15]
from matplotlib import pyplot as plt
f = plt.figure()
ax = f.gca()
f.show()
#years = [2012, 2013, 2014, 2015, 2016, 2017, 2018]
for aYear in years: 
    #print(aYear)     
    if (aYear=='Not applicable'):
        continue
    #ax = fig.add_subplot(111)
    data = health_status.loc[  (health_status['Indicator'] == indicators[0])  & (health_status['Data year'] == aYear) ]
    ax.scatter(data['Data year'], data['Region'], s=cancer_mortality['Value']*20 )
    #line1.set_ydata(data['Region'])
    f.canvas.draw()
    #plt.show()
    #plt.pause(1)
    #ax.clear()
    #fig.canvas.draw()
    
#plt.legend()C:\\ProgramData\\Anaconda3\\lib\\site-packages\\matplotlib\\figure.py:445: UserWarning: Matplotlib is currently using module:\/\/ipykernel.pylab.backend_inline, which is a non-GUI backend, so cannot show the figure.
  % get_backend())<\/pre>\n\n\n\n
\"png\"\/<\/figure>\n\n\n\n
plt.rcParams['figure.figsize'] = [5, 5]
plt.ion()
fig = plt.figure()
ax = fig.add_subplot(111)
#line1, = ax.plot(cancer_mortality_2013['Data year'], cancer_mortality_2013['Region'], 'b')
#pl = ax.scatter(cancer_mortality_2013['Data year'], cancer_mortality_2013['Region'], s=cancer_mortality_2013['Value']*30 )

fig = plt.figure()
ax = fig.add_subplot(111)
years = [2012, 2013, 2014, 2015]
for aYear in years: 
    print(aYear)        
    ax = fig.add_subplot(111)
    data = health_status.loc[  (health_status['Indicator'] == indicators[0])  & (health_status['Data year'] == aYear) ]
    ax.scatter(data['Data year'], data['Region'], s=cancer_mortality['Value']*10 )
    #line1.set_ydata(data['Region'])
    plt.show()
    plt.pause(0.0001)
    ax.clear()
    #fig.canvas.draw()
    
#for phase in np.linspace(0, 10*np.pi, 100):
#line1.set_ydata(np.sin(0.5 * x + phase))
#fig.canvas.draw()2012


C:\\ProgramData\\Anaconda3\\lib\\site-packages\\matplotlib\\figure.py:98: MatplotlibDeprecationWarning: 
Adding an axes using the same arguments as a previous axes currently reuses the earlier instance.  In a future version, a new instance will always be created and returned.  Meanwhile, this warning can be suppressed, and the future behavior ensured, by passing a unique label to each axes instance.
  \"Adding an axes using the same arguments as a previous axes \"<\/pre>\n\n\n\n
\"png\"\/<\/figure>\n\n\n\n
\"png\"\/<\/figure>\n\n\n\n
2013
2014
2015plt.rcParams['figure.figsize'] = [15, 9]
plt.scatter(cancer_mortality_2013['Data year'], cancer_mortality_2013['Region'], s=cancer_mortality_2013['Value']*30 )
plt.show()<\/pre>\n\n\n\n
\"png\"\/<\/figure>\n\n\n\n
plt.rcParams['figure.figsize'] = [15, 9]
plt.scatter(cancer_mortality_2013['Region'],  cancer_mortality_2013['Value'], s=cancer_mortality_2013['Value']*30 )
plt.show()<\/pre>\n\n\n\n
\"png\"\/<\/figure>\n\n\n\n
plt.rcParams['figure.figsize'] = [100, 50]
from matplotlib import pyplot as plt
f = plt.figure()
ax = f.gca()
f.show()
#years = [2012, 2013, 2014, 2015, 2016, 2017, 2018]
for aYear in years: 
    #print(aYear)     
    if (aYear=='Not applicable'):
        continue
    #ax = fig.add_subplot(111)
    data = health_status.loc[  (health_status['Indicator'] == indicators[0])  & (health_status['Data year'] == aYear) ]
    #ax.scatter(data['Data year'], data['Region'], s=cancer_mortality['Value']*20 )
    ax.scatter(data['Region'], data['Value'], s=cancer_mortality['Value']*100 )
    #line1.set_ydata(data['Region'])
    f.canvas.draw()
    #plt.show()
    #plt.pause(1)
    #ax.clear()
    #fig.canvas.draw()
    
#plt.legend()<\/pre>\n\n\n\n
\"png\"\/<\/figure>\n\n\n\n
def f(x):
    return x


w = interact(f, x=indicators);
interact(f, x=years);interactive(children=(Dropdown(description='x', options=('Cancer Mortality (F)', 'Cancer Mortality (M)', 'Hear\u2026



interactive(children=(Dropdown(description='x', options=(2012, 2013, 2014, 2015), value=2012), Output()), _dom\u2026w = interactive(f, x=indicators);type(w)ipywidgets.widgets.interaction.interactivew.children(Dropdown(description='x', options=('Cancer Mortality (F)', 'Cancer Mortality (M)', 'Heart Disease Mortality', 'Infant Mortality', 'Life Expectancy at Birth (F)', 'Life Expectancy at Birth (M)', 'Perceived Health Status', 'Stroke Mortality', 'Suicide (F)', 'Suicide (M)', 'Transport Accident Mortality (F)', 'Transport Accident Mortality (M)'), value='Cancer Mortality (F)'),
 Output())display(w)interactive(children=(Dropdown(description='x', options=('Cancer Mortality (F)', 'Cancer Mortality (M)', 'Hear\u2026w.result'Perceived Health Status'<\/pre>\n","protected":false},"excerpt":{"rendered":"
Justetc Social Services (non-profit)Jan 31 \u00b7 4 min read import pandas as pdimport matplotlib.pyplot as plt%matplotlib inlinefrom __future__ import print_functionfrom ipywidgets import interact, interactive, fixed, interact_manualimport ipywidgets as widgetshealth_status = pd.read_excel(‘..\/data\/health-status.xls’)health_status.head() health_status.set_index([‘Indicator’])#health_status.loc[health_status[‘Cancer Mortality (F)’]]#health_status.index.unique()indicators = pd.Index(health_status[‘Indicator’]).unique()years = health_status[‘Data year’].unique()indicators[0], years[0](‘Cancer Mortality (F)’, ‘2013’)cancer_mortality_2013 = health_status.loc[ (health_status[‘Indicator’] == indicators[0]) & (health_status[‘Data year’] == years[0]) ]cancer_mortality = health_status.loc[ (health_status[‘Indicator’] == … <\/p>\n
Continue reading<\/a><\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[1903,1894,1919,182],"tags":[],"class_list":["post-19920","post","type-post","status-publish","format-standard","hentry","category-data-visualization","category-health-system-performance","category-visualize-health-system-performance","category---blog","item-wrap"],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"jetpack-related-posts":[{"id":19914,"url":"http:\/\/bangla.sitestree.com\/?p=19914","url_meta":{"origin":19920,"position":0},"title":"IPywidgets, interactive","author":"Sayed","date":"February 7, 2021","format":false,"excerpt":"Justetc Social Services (non-profit)\u00b7Jan 31 from __future__ import print_functionfrom ipywidgets import interact, interactive, fixed, interact_manualimport ipywidgets as widgetsdef f(x): return xinteract(f, x=10);interactive(children=(IntSlider(value=10, description='x', max=30, min=-10), Output()), _dom_classes=('widget-\u2026interact(f, x=True);interactive(children=(Checkbox(value=True, description='x'), Output()), _dom_classes=('widget-interact',))interact(f, x='Hi there!');interactive(children=(Text(value='Hi there!', description='x'), Output()), _dom_classes=('widget-interact',))@interact(x=True, y=1.0)def g(x, y): return (x, y)interactive(children=(Checkbox(value=True, description='x'), FloatSlider(value=1.0, description='y', max=3.0, \u2026interact(f, x=['apples','oranges']);interactive(children=(Dropdown(description='x', options=('apples',\u2026","rel":"","context":"In "Data Visualization"","block_context":{"text":"Data Visualization","link":"http:\/\/bangla.sitestree.com\/?cat=1903"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":19916,"url":"http:\/\/bangla.sitestree.com\/?p=19916","url_meta":{"origin":19920,"position":1},"title":"How to use ipywidgets, interactive as used in the project","author":"Sayed","date":"February 7, 2021","format":false,"excerpt":"Justetc Social Services (non-profit)Jan 31\u00a0\u00b7\u00a01\u00a0min read from __future__ import print_functionfrom ipywidgets import interact, interactive, fixed, interact_manualimport ipywidgets as widgetsdef f(x): return xinteract(f, x=10);interactive(children=(IntSlider(value=10, description='x', max=30, min=-10), Output()), _dom_classes=('widget-\u2026interact(f, x=True);interactive(children=(Checkbox(value=True, description='x'), Output()), _dom_classes=('widget-interact',))interact(f, x='Hi there!');interactive(children=(Text(value='Hi there!', description='x'), Output()), _dom_classes=('widget-interact',))@interact(x=True, y=1.0)def g(x, y): return (x, y)interactive(children=(Checkbox(value=True, description='x'), FloatSlider(value=1.0, description='y', max=3.0, \u2026interact(f, x=['apples','oranges']);interactive(children=(Dropdown(description='x',\u2026","rel":"","context":"In "Data Visualization"","block_context":{"text":"Data Visualization","link":"http:\/\/bangla.sitestree.com\/?cat=1903"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":19909,"url":"http:\/\/bangla.sitestree.com\/?p=19909","url_meta":{"origin":19920,"position":2},"title":"About the Project : Benchmarking Canada\u2019s Health Care Systems: International Comparisons, 2017","author":"Sayed","date":"February 7, 2021","format":false,"excerpt":"Justetc Social Services (non-profit)Jan 31\u00a0\u00b7\u00a01\u00a0min read Project : Benchmarking Canada\u2019s Health Care Systems: International Comparisons, 2017 By Sayed Ahmed Objective: Visualize the performance of Canadian Healthcare System Performance against other countries Short Description\u00a0: Analyze, compare, and visualize the performance of Canadian healthcare system against other countries using public dataset. The\u2026","rel":"","context":"In "Data Visualization"","block_context":{"text":"Data Visualization","link":"http:\/\/bangla.sitestree.com\/?cat=1903"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":19922,"url":"http:\/\/bangla.sitestree.com\/?p=19922","url_meta":{"origin":19920,"position":3},"title":"interactive_health_status_visualizations, Health System Performance, Canada and Others","author":"Sayed","date":"February 7, 2021","format":false,"excerpt":"Justetc Social Services (non-profit)Jan 31\u00a0\u00b7\u00a05\u00a0min read import pandas as pdimport matplotlib.pyplot as plt%matplotlib inlinefrom __future__ import print_functionfrom ipywidgets import interact, interactive, fixed, interact_manualimport ipywidgets as widgetshealth_status = pd.read_excel('..\/data\/health-status.xls')health_status.head() # find all indicatorshealth_status.set_index(['Indicator'])indicators = pd.Index(health_status['Indicator']).unique()# find all yearsyears = health_status['Data year'].unique()indicators[0], years[0]('Cancer Mortality (F)', '2013')# sort yearsyears = [ int(aYear) for\u2026","rel":"","context":"In "Data Visualization"","block_context":{"text":"Data Visualization","link":"http:\/\/bangla.sitestree.com\/?cat=1903"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":19924,"url":"http:\/\/bangla.sitestree.com\/?p=19924","url_meta":{"origin":19920,"position":4},"title":"non_med_determinants_visualizations, Health System Performance, Canada and Others","author":"Sayed","date":"February 7, 2021","format":false,"excerpt":"Justetc Social Services (non-profit)Jan 31\u00a0\u00b7\u00a05\u00a0min read import pandas as pdimport matplotlib.pyplot as plt%matplotlib inlinefrom __future__ import print_functionfrom ipywidgets import interact, interactive, fixed, interact_manualimport ipywidgets as widgetsnon_med_determinants = pd.read_excel('..\/data\/non-med-determinants.xls')non_med_determinants.head() # find all indicatorsnon_med_determinants.set_index(['Indicator'])indicators = pd.Index(non_med_determinants['Indicator']).unique()# find all yearsyears = non_med_determinants['Data year'].dropna().unique()indicators[0], years('Alcohol Consumption: Adults', array(['2014', '2015', '2013', 2015, 'Not applicable', '2016'],\u2026","rel":"","context":"In "Data Visualization"","block_context":{"text":"Data Visualization","link":"http:\/\/bangla.sitestree.com\/?cat=1903"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":19918,"url":"http:\/\/bangla.sitestree.com\/?p=19918","url_meta":{"origin":19920,"position":5},"title":"access_to_care, primary-prescribing, Health System Performance, Canada and Others","author":"Sayed","date":"February 7, 2021","format":false,"excerpt":"Justetc Social Services (non-profit)Jan 31\u00a0\u00b7\u00a05\u00a0min read import pandas as pdimport matplotlib.pyplot as plt%matplotlib inlinefrom __future__ import print_functionfrom ipywidgets import interact, interactive, fixed, interact_manualimport ipywidgets as widgetsaccess_to_care = pd.read_excel('..\/data\/access-to-care.xls')access_to_care.head() # find all indicatorsaccess_to_care.set_index(['Indicator'])indicators = pd.Index(access_to_care['Indicator']).unique()# find all yearsyears = access_to_care['Data year'].dropna().unique()indicators[0], years('Inability to Pay for Medical Bills', array(['2016', 2016, 'Not applicable',\u2026","rel":"","context":"In "Data Visualization"","block_context":{"text":"Data Visualization","link":"http:\/\/bangla.sitestree.com\/?cat=1903"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]}],"_links":{"self":[{"href":"http:\/\/bangla.sitestree.com\/index.php?rest_route=\/wp\/v2\/posts\/19920","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/bangla.sitestree.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/bangla.sitestree.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/bangla.sitestree.com\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"http:\/\/bangla.sitestree.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=19920"}],"version-history":[{"count":1,"href":"http:\/\/bangla.sitestree.com\/index.php?rest_route=\/wp\/v2\/posts\/19920\/revisions"}],"predecessor-version":[{"id":19921,"href":"http:\/\/bangla.sitestree.com\/index.php?rest_route=\/wp\/v2\/posts\/19920\/revisions\/19921"}],"wp:attachment":[{"href":"http:\/\/bangla.sitestree.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=19920"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/bangla.sitestree.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=19920"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/bangla.sitestree.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=19920"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}