def updateFigEmplStatus(states, years):
if len(years) > 1:
selectedExtendedDfsForYear1 = toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(usaData.dfsArray, 'index',
['EMPLOYMENT SECTOR']), 'state', states),
'year', [years[0]])
dfYear1 = dfs_sum(
[df['dataFrame'] for df in selectedExtendedDfsForYear1])
selectedExtendedDfsForYear2 = toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(usaData.dfsArray, 'index',
['EMPLOYMENT SECTOR']), 'state', states),
'year', [years[1]])
dfYear2 = dfs_sum(
[df['dataFrame'] for df in selectedExtendedDfsForYear2])
trace = go.Sunburst(
ids=["20" + year for year in years] + [
"20" + year + " - " + status for year in years
for status in dfYear1.columns.tolist()
],
labels=["20" + year for year in years] +
[status for status in dfYear1.columns.tolist()] * 2,
parents=["" for i in range(len(years))] + list(
chain.from_iterable(
("20" + year, "20" + year) for year in years)),
values=[dfYear1.iloc[0, :].sum(), dfYear2.iloc[0, :].sum()] + [
dfYear1.iloc[0, 0], dfYear1.iloc[0, 1], dfYear2.iloc[0, 0],
dfYear2.iloc[0, 1]
],
branchvalues="total",
)
return {
'data': [trace],
'layout': {
'title': "EMPLOYMENT STATUS".title()
}
}
else:
selectedExtendedDfs = toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(usaData.dfsArray, 'index',
['EMPLOYMENT SECTOR']), 'state', states),
'year', [years[0]])
df = dfs_sum([df['dataFrame'] for df in selectedExtendedDfs])
trace = go.Pie(labels=df.columns.tolist(), values=df.iloc[0].tolist())
return {
'data': [trace],
'layout': {
'title': "EMPLOYMENT STATUS".title()
}
}
def updateFigHealthIns(states, ageCateg, year):
global layout, my_colors, my_line_colors
layout1 = copy.deepcopy(layout)
layout1['title'] = "Health Insurance Coverage".title()
if len(year) > 1:
selectedExtendedDfsForYear1 = toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(usaData.dfsArray, 'index', ['AGE']),
'state', states), "columns", ["POPULATION"]), 'year',
[year[0]])
selectedExtendedDfsForYear2 = toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(usaData.dfsArray, 'index', ['AGE']),
'state', states), "columns", ["POPULATION"]), 'year',
[year[1]])
dfYear1 = dfs_sum(
[df['dataFrame'] for df in selectedExtendedDfsForYear1])
dfYear2 = dfs_sum(
[df['dataFrame'] for df in selectedExtendedDfsForYear2])
trace1 = go.Bar(x=[index[:-1] for index in dfYear1.index.tolist()],
y=dfYear1.iloc[:, 0].tolist(),
name="20" + year[0],
marker_color=my_colors[0],
marker_line_color=my_line_colors[0],
marker_line_width=1.5,
opacity=0.6)
trace2 = go.Bar(x=[index[:-1] for index in dfYear2.index.tolist()],
y=dfYear2.iloc[:, 0].tolist(),
name="20" + year[1],
marker_color=my_colors[1],
marker_line_color=my_line_colors[1],
marker_line_width=1.5,
opacity=0.6)
return {'data': [trace1, trace2], 'layout': layout1}
else:
selectedExtendedDfs = toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(usaData.dfsArray, 'index', ['AGE']),
'state', states), "columns", ["POPULATION"]), 'year',
[year[0]])
df = dfs_sum([df['dataFrame'] for df in selectedExtendedDfs])
trace = go.Bar(x=[index[:-1] for index in df.index.tolist()],
y=df.iloc[:, 0].tolist(),
marker_color=my_colors[0],
marker_line_color=my_line_colors[0],
marker_line_width=1.5,
opacity=0.6)
return {'data': [trace], 'layout': layout1}
def updateFigEmplStatus(states, years):
global layout, my_colors, my_line_colors
my_colors1 = copy.deepcopy(my_colors).extend(my_line_colors)
layout1 = copy.deepcopy(layout)
layout1['title'] = "EMPLOYMENT STATUS".title()
if len(years) > 1:
selectedExtendedDfsForYear1 = toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(usaData.dfsArray, 'index',
['EMPLOYMENT SECTOR']), 'state', states),
'year', [years[0]])
dfYear1 = dfs_sum(
[df['dataFrame'] for df in selectedExtendedDfsForYear1])
selectedExtendedDfsForYear2 = toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(usaData.dfsArray, 'index',
['EMPLOYMENT SECTOR']), 'state', states),
'year', [years[1]])
dfYear2 = dfs_sum(
[df['dataFrame'] for df in selectedExtendedDfsForYear2])
trace = go.Sunburst(
ids=["20" + year for year in years] + [
"20" + year + " - " + status for year in years
for status in dfYear1.columns.tolist()
],
labels=["20" + year for year in years] +
[status for status in dfYear1.columns.tolist()] * 2,
parents=["" for i in range(len(years))] + list(
chain.from_iterable(
("20" + year, "20" + year) for year in years)),
values=[dfYear1.iloc[0, :].sum(), dfYear2.iloc[0, :].sum()] + [
dfYear1.iloc[0, 0], dfYear1.iloc[0, 1], dfYear2.iloc[0, 0],
dfYear2.iloc[0, 1]
],
branchvalues="total",
marker=dict(colors=my_colors, autocolorscale=True))
return {'data': [trace], 'layout': layout1}
else:
selectedExtendedDfs = toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(usaData.dfsArray, 'index',
['EMPLOYMENT SECTOR']), 'state', states),
'year', [years[0]])
df = dfs_sum([df['dataFrame'] for df in selectedExtendedDfs])
trace = go.Pie(labels=df.columns.tolist(),
values=df.iloc[0].tolist(),
marker_colors=my_colors,
hole=.3,
opacity=0.7)
return {'data': [trace], 'layout': layout1}
def updateFigEducEnvir(envir, disType):
df = dfs_sum([educaEnvir[dis].df for dis in disType])
if len(envir) == 1:
trace = go.Pie(labels=df.index.values, values=df[envir[0]].tolist())
return {
'data': [trace],
'layout': {
'title':
"Niveau d'éducation dans le monde " + envir[0].lower(),
}
}
else:
trace = go.Sunburst(
ids=[env for env in envir] + [
env + " - " + level for env in envir
for level in df.index.values
],
labels=[env
for env in envir] + [level
for level in df.index.values] * 4,
parents=["" for i in range(len(envir))] +
list(chain.from_iterable((env, env, env, env) for env in envir)),
values=[df[env].sum() for env in envir] +
[df.loc[level][env] for env in envir for level in df.index.values],
branchvalues="total",
)
return {
'data': [trace],
'layout': {
'title': "Niveau d'éducation par environment",
}
}
def updateFigEducEnvir(envir, disType):
global layout, my_colors, my_line_colors
my_colors1 = [
'rgb(136, 207, 241)', 'rgb(249, 215, 214)', 'rgb(184, 235, 255)',
'rgb(255, 184, 199)'
]
layout1 = copy.deepcopy(layout)
layout1['title'] = "Niveau d'éducation dans le monde " + envir[0].lower()
df = dfs_sum([educaEnvir[dis].df for dis in disType])
if len(envir) == 1:
trace = go.Pie(labels=df.index.values,
values=df[envir[0]].tolist(),
marker_colors=my_colors1,
hole=.3,
opacity=0.7)
return {'data': [trace], 'layout': layout1}
else:
layout1 = copy.deepcopy(layout)
layout1['title'] = "Niveau d'éducation par environment"
trace = go.Sunburst(
ids=[env for env in envir] + [
env + " - " + level for env in envir
for level in df.index.values
],
labels=[env
for env in envir] + [level
for level in df.index.values] * 4,
parents=["" for i in range(len(envir))] +
list(chain.from_iterable((env, env, env, env) for env in envir)),
values=[df[env].sum() for env in envir] +
[df.loc[level][env] for env in envir for level in df.index.values],
branchvalues="total",
marker=dict(colors=my_colors, autocolorscale=True))
return {'data': [trace], 'layout': layout1}
def updateFigHealthIns(states, ageCateg, year):
if len(year) > 1:
selectedExtendedDfsForYear1 = toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(usaData.dfsArray, 'index', ['AGE']),
'state', states), "columns", ["POPULATION"]), 'year',
[year[0]])
selectedExtendedDfsForYear2 = toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(usaData.dfsArray, 'index', ['AGE']),
'state', states), "columns", ["POPULATION"]), 'year',
[year[1]])
dfYear1 = dfs_sum(
[df['dataFrame'] for df in selectedExtendedDfsForYear1])
dfYear2 = dfs_sum(
[df['dataFrame'] for df in selectedExtendedDfsForYear2])
trace1 = go.Bar(x=[index[:-1] for index in dfYear1.index.tolist()],
y=dfYear1.iloc[:, 0].tolist(),
name="20" + year[0])
trace2 = go.Bar(x=[index[:-1] for index in dfYear2.index.tolist()],
y=dfYear2.iloc[:, 0].tolist(),
name="20" + year[1])
return {
'data': [trace1, trace2],
'layout': {
'title': "PREVALENCE OF INSURED DISABLED PEOPLE".title()
}
}
else:
selectedExtendedDfs = toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(usaData.dfsArray, 'index', ['AGE']),
'state', states), "columns", ["POPULATION"]), 'year',
[year[0]])
df = dfs_sum([df['dataFrame'] for df in selectedExtendedDfs])
trace = go.Bar(x=[index[:-1] for index in df.index.tolist()],
y=df.iloc[:, 0].tolist())
return {
'data': [trace],
'layout': {
'title': "PREVALENCE OF INSURED DISABLED PEOPLE".title()
}
}
def updateFigActivityEnv(disType, envir):
df = dfs_sum([actEnv[dis].df[envir] for dis in disType])
if len(envir) == 1:
trace = go.Bar(x=df.index.tolist(), y=df[envir[0]].tolist())
return {'data': [trace], 'layout': {}}
else:
trace1 = go.Bar(name="urbain", x=df.index.tolist(), y=df["urbain"])
trace2 = go.Bar(name="Rural", x=df.index.tolist(), y=df["Rural"])
return {'data': [trace1, trace2], 'layout': {}}
def updatePrevSexe(sexe):
df = dfs_sum([
illitAgeSexe[dis].df
for dis in ["Sensoriel", "Chronique", "Moteur", "Mental"]
])
trace = [
go.Bar(x=[s for s in sexe],
y=[df[s].sum() / df["Ensemble"].sum() for s in sexe])
]
return {'data': trace, 'layout': {}}
def updatePrevEnvir(envir):
df = dfs_sum([
illitSexeEnvir[dis].df
for dis in ["Sensoriel", "Chronique", "Moteur", "Mental"]
])
print(envir)
trace = [
go.Bar(x=[e for e in envir],
y=[df.loc[e]["Ensemble"] / df["Ensemble"].sum() for e in envir])
]
return {'data': trace, 'layout': {}}
def updateFigAgeCateg(categories, sexe, disType):
global categToAgeCateg
df = dfs_sum([ageSexe04[dis].df[sexe] for dis in disType])
start = df.index[0]
end = categToAgeCateg[categories[1]]
if len(sexe) == 1:
trace = go.Bar(x=df.index.tolist()[categories[0]:categories[1]],
y=df[sexe[0]])
else:
trace = go.Bar(x=df.index.tolist()[categories[0]:categories[1]],
y=df["Masculin"] + df["Féminin"])
return {'data': [trace], 'layout': {}}
def updateFigMatri(statuses, sexe, disType):
df = dfs_sum([sexeMatri04[dis].df for dis in disType]).loc[statuses]
if len(sexe) == 1:
trace = go.Pie(labels=statuses, values=df[sexe[0]].tolist())
else:
trace = go.Pie(labels=statuses,
values=(df["Masculin"] + df["Féminin"]).tolist())
return {
"data": [trace],
'layout': {
'title': "Prévalence selon la situation matrimoniale",
}
}
def updateFigWorkExp(states, years):
traces = []
for year in years:
selectedExtendedDfs = toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(usaData.dfsArray, 'index',
['WORK EXPERIENCE']), 'state', states),
'year', [year])
df = dfs_sum([df['dataFrame'] for df in selectedExtendedDfs])
traces.append(
go.Bar(x=df.index.tolist(),
y=df.iloc[:, 0].tolist(),
name="20" + year))
return {'data': traces, 'layout': {'title': "WORK EXPERIENCE".title()}}
def updateFigIllitAge(sexe, disType):
df = dfs_sum([illitAgeSexe[dis].df[sexe] for dis in disType])
if len(sexe) == 1:
trace = go.Bar(x=df.index.tolist(), y=df[sexe[0]])
return {"data": [trace], "layout": {}}
else:
trace = [
go.Bar(name="Masculin", x=df.index.tolist(), y=df["Masculin"]),
go.Bar(name="Féminin", x=df.index.tolist(), y=df["Féminin"])
]
return {
"data": trace,
"layout": {
"barmode": 'stack',
}
}
def updateFigIllit(sexe, disType, envir):
df = dfs_sum([illitSexeEnvir[dis].df for dis in disType]).loc[envir][sexe]
if len(sexe) == 1:
trace = go.Pie(labels=envir,
values=df.loc[envir[0]].tolist() +
df.loc[envir[1]].tolist())
else:
trace = go.Sunburst(
ids=[env for env in envir] +
[env + " - " + sex for env in envir for sex in sexe],
labels=[env for env in envir] + [sex for sex in sexe] * 2,
parents=["" for i in range(len(envir))] +
list(chain.from_iterable((env, env) for env in envir)),
values=[df.loc[env].sum() for env in envir] +
[df.loc[env][sex] for env in envir for sex in sexe],
branchvalues="total",
)
return {'data': [trace], 'layout': {}}
def updateFigIllit(sexe, disType, envir):
global layout, my_colors, my_line_colors
my_colors1 = copy.deepcopy(my_colors)
my_colors1.append('rgb(199,255,184)')
layout1 = copy.deepcopy(layout)
layout1['title'] = "Analphabétisme par environnement "
df = dfs_sum([illitSexeEnvir[dis].df for dis in disType]).loc[envir][sexe]
if len(sexe) == 1:
if len(envir) == 2:
trace = go.Pie(labels=envir,
values=df.loc[envir[0]].tolist() +
df.loc[envir[1]].tolist(),
marker_colors=my_colors1,
hole=.3,
opacity=0.7)
else:
trace = trace = go.Pie(labels=sexe,
values=df.loc[envir[0]].tolist(),
marker_colors=my_colors1,
hole=.3,
opacity=0.7)
else:
if len(envir) == 2:
trace = go.Sunburst(
ids=[env for env in envir] +
[env + " - " + sex for env in envir for sex in sexe],
labels=[env for env in envir] + [sex for sex in sexe] * 2,
parents=["" for i in range(len(envir))] +
list(chain.from_iterable((env, env) for env in envir)),
values=[df.loc[env].sum() for env in envir] +
[df.loc[env][sex] for env in envir for sex in sexe],
branchvalues="total",
marker=dict(colors=my_colors, autocolorscale=True))
else:
layout1[
'title'] = "Analphabétisme dans le monde " + envir[0].lower()
trace = trace = go.Pie(labels=sexe,
values=df.loc[envir[0]].tolist(),
marker_colors=my_colors1,
hole=.3,
opacity=0.7)
return {'data': [trace], 'layout': layout1}
def updateFigWorkExp(states, years):
global layout, my_colors
layout1 = copy.deepcopy(layout)
layout1['title'] = "WORK EXPERIENCE".title()
traces = []
for year in years:
selectedExtendedDfs = toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(usaData.dfsArray, 'index',
['WORK EXPERIENCE']), 'state', states),
'year', [year])
df = dfs_sum([df['dataFrame'] for df in selectedExtendedDfs])
traces.append(
go.Scatterpolar(r=df.iloc[:, 0],
theta=df.index,
fill='toself',
name=df.columns.tolist()[0] + ' (20' + year + ')',
line=dict(color=my_colors[years.index(year)])))
layout1['polar'] = dict(radialaxis=dict(visible=True))
layout1['showlegend'] = True
return {'data': traces, 'layout': layout1}
def updateFigIllitAge(sexe, disType):
global layout, my_colors, my_line_colors
my_colors1 = copy.deepcopy(my_colors)
my_colors1.append('rgb(199,255,184)')
my_line_colors1 = copy.deepcopy(my_line_colors)
my_line_colors1.append('rgb(130,255,96)')
layout1 = copy.deepcopy(layout)
layout1['title'] = "Analphabétisme par catégories d'âge"
layout1['barmode'] = 'stack'
df = dfs_sum([illitAgeSexe[dis].df[sexe] for dis in disType])
if len(sexe) == 1:
trace = go.Bar(x=df.index.tolist(),
y=df[sexe[0]],
marker_color=my_colors1[0],
marker_line_color=my_line_colors1[0],
marker_line_width=1.5,
opacity=0.6)
return {"data": [trace], "layout": layout1}
else:
trace = [
go.Bar(name="Masculin",
x=df.index.tolist(),
y=df["Masculin"],
marker_color=my_colors1[0],
marker_line_color=my_line_colors1[0],
marker_line_width=1.5,
opacity=0.6),
go.Bar(name="Féminin",
x=df.index.tolist(),
y=df["Féminin"],
marker_color=my_colors1[1],
marker_line_color=my_line_colors1[1],
marker_line_width=1.5,
opacity=0.6)
]
return {
"data": trace,
"layout": layout1,
}
def updateFigMatri(statuses, sexe, disType):
global layout, my_colors, my_line_colors
my_colors1 = [
'rgb(136, 207, 241)', 'rgb(255, 184, 199)', 'rgb(249, 215, 214)',
'rgb(184, 235, 255)'
]
layout1 = copy.deepcopy(layout)
layout1['title'] = "Prévalence selon la situation matrimoniale"
df = dfs_sum([sexeMatri04[dis].df for dis in disType]).loc[statuses]
if len(sexe) == 1:
trace = go.Pie(labels=statuses,
values=df[sexe[0]].tolist(),
marker_colors=my_colors1,
hole=.3,
opacity=0.7)
else:
trace = go.Pie(labels=statuses,
values=(df["Masculin"] + df["Féminin"]).tolist(),
marker_colors=my_colors1,
hole=.3,
opacity=0.7)
return {"data": [trace], 'layout': layout1}
def updateFigAgeCateg(categories, sexe, disType):
global categToAgeCateg, layout, my_colors, my_line_colors
layout1 = copy.deepcopy(layout)
layout1['title'] = "Prévalence par catégories d'âge"
df = dfs_sum([ageSexe04[dis].df[sexe] for dis in disType])
start = df.index[0]
end = categToAgeCateg[categories[1]]
if len(sexe) == 1:
trace = go.Bar(x=df.index.tolist()[categories[0]:categories[1]],
y=df[sexe[0]],
marker_color=my_colors[0],
marker_line_color=my_line_colors[0],
marker_line_width=1.5,
opacity=0.6)
else:
trace = go.Bar(x=df.index.tolist()[categories[0]:categories[1]],
y=df["Masculin"] + df["Féminin"],
marker_color=my_colors[0],
marker_line_color=my_line_colors[0],
marker_line_width=1.5,
opacity=0.6)
return {'data': [trace], 'layout': layout1}
def updateFigAgeDisNumber(states, ageCateg, year):
if len(year) > 1:
selectedExtendedDfsForYear1 = toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(usaData.dfsArray, 'index', ['AGE']),
'state', states), "columns", ["NUMBER OF DISABILITIES"]),
'year', [year[0]])
selectedExtendedDfsForYear2 = toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(usaData.dfsArray, 'index', ['AGE']),
'state', states), "columns", ["NUMBER OF DISABILITIES"]),
'year', [year[1]])
dfYear1 = dfs_sum(
[df['dataFrame'] for df in selectedExtendedDfsForYear1])
dfYear2 = dfs_sum(
[df['dataFrame'] for df in selectedExtendedDfsForYear2])
fig = make_subplots(rows=1,
cols=2,
subplot_titles=("20" + str(year[0]),
"20" + str(year[1])))
fig.add_trace(go.Bar(
x=[index[:-1] for index in dfYear1.index.tolist()],
y=dfYear1.iloc[:, 0].tolist(),
name=dfYear1.columns.tolist()[0].title()),
row=1,
col=1)
fig.add_trace(go.Bar(
x=[index[:-1] for index in dfYear1.index.tolist()],
y=dfYear1.iloc[:, 1].tolist(),
name=dfYear1.columns.tolist()[1].title()),
row=1,
col=1)
fig.add_trace(go.Bar(
x=[index[:-1] for index in dfYear1.index.tolist()],
y=dfYear2.iloc[:, 0].tolist(),
name=dfYear2.columns.tolist()[0].title()),
row=1,
col=2)
fig.add_trace(go.Bar(
x=[index[:-1] for index in dfYear1.index.tolist()],
y=dfYear2.iloc[:, 1].tolist(),
name=dfYear2.columns.tolist()[1].title()),
row=1,
col=2)
return fig
else:
selectedExtendedDfs = toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(usaData.dfsArray, 'index', ['AGE']), 'state',
states), "columns", ["NUMBER OF DISABILITIES"])
df = dfs_sum([df['dataFrame'] for df in selectedExtendedDfs])
trace1 = go.Bar(x=[index[:-1] for index in df.index.tolist()],
y=df.iloc[:, 0].tolist(),
name=df.columns.tolist()[0].title())
trace2 = go.Bar(x=[index[:-1] for index in df.index.tolist()],
y=df.iloc[:, 1].tolist(),
name=df.columns.tolist()[1].title())
return {
'data': [trace1, trace2],
'layout': {
'title': "AGE BY NUMBER OF DISABILITIES".title()
}
}
def updateFigAge(ageCateg, states, sex, difTypes, year):
global layout, my_colors, my_line_colors
layout1 = copy.deepcopy(layout)
layout1['title'] = "PREVALENCE BY AGE".title()
if len(year) == 1:
selectedExtendedDfs = toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(usaData.dfsArray, 'index', ['SEX']),
'state', states), 'difficulty', difTypes), 'year', year)
df = dfs_sum([df['dataFrame'] for df in selectedExtendedDfs
])[toolz.getAgeOptions(usaData.dfsArray, ageCateg)]
if len(sex) == 2:
trace1 = go.Bar(x=df.columns.tolist(),
y=df.loc["Male"].tolist(),
name='Male',
marker_color=my_colors[0],
marker_line_color=my_line_colors[0],
marker_line_width=1.5,
opacity=0.6)
trace2 = go.Bar(x=df.columns.tolist(),
y=df.loc["Female"].tolist(),
name='Female',
marker_color=my_colors[1],
marker_line_color=my_line_colors[1],
marker_line_width=1.5,
opacity=0.6)
return {'data': [trace1, trace2], 'layout': layout1}
else:
trace = go.Bar(x=df.columns.tolist(),
y=df.loc[sex[0].title()].tolist(),
name=sex[0].title(),
marker_color=my_colors[0],
marker_line_color=my_line_colors[0],
marker_line_width=1.5,
opacity=0.6)
return {'data': [trace], 'layout': layout1}
else:
selectedExtendedDfsForYear1 = toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(usaData.dfsArray, 'index', ['SEX']),
'state', states), 'difficulty', difTypes), 'year',
[year[0]])
selectedExtendedDfsForYear2 = toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(usaData.dfsArray, 'index', ['SEX']),
'state', states), 'difficulty', difTypes), 'year',
[year[1]])
dfYear1 = dfs_sum([
df['dataFrame'] for df in selectedExtendedDfsForYear1
])[toolz.getAgeOptions(usaData.dfsArray, ageCateg)]
dfYear2 = dfs_sum([
df['dataFrame'] for df in selectedExtendedDfsForYear2
])[toolz.getAgeOptions(usaData.dfsArray, ageCateg)]
if len(sex) == 2:
trace1 = go.Bar(x=dfYear1.columns.tolist(),
y=dfYear1.loc["Male"].tolist(),
name='Male (20' + year[0] + ")",
width=0.15,
marker_color=my_colors[0],
marker_line_color=my_line_colors[0],
marker_line_width=1.5,
opacity=0.6)
trace2 = go.Bar(x=dfYear1.columns.tolist(),
y=dfYear1.loc["Female"].tolist(),
name='Female (20' + year[0] + ")",
width=0.15,
marker_color=my_colors[1],
marker_line_color=my_line_colors[1],
marker_line_width=1.5,
opacity=0.6)
trace3 = go.Bar(x=dfYear1.columns.tolist(),
y=dfYear2.loc["Male"].tolist(),
name='Male (20' + year[1] + ")",
width=0.15,
marker_color=my_colors[0],
marker_line_color=my_line_colors[0],
marker_line_width=1.5,
opacity=0.6)
trace4 = go.Bar(x=dfYear1.columns.tolist(),
y=dfYear2.loc["Female"].tolist(),
name='Female (20' + year[1] + ")",
width=0.15,
marker_color=my_colors[1],
marker_line_color=my_line_colors[1],
marker_line_width=1.5,
opacity=0.6)
return {
'data': [trace1, trace2, trace3, trace4],
'layout': layout1
}
else:
traces = [
go.Bar(x=dfYear1.columns.tolist(),
y=dfYear1.loc[sex[0].title()].tolist(),
name=sex[0].title()),
go.Bar(x=dfYear1.columns.tolist(),
y=dfYear2.loc[sex[0].title()].tolist(),
name=sex[0].title())
]
traces = trace = [
go.Bar(name="20" + year[0],
x=dfYear1.columns.tolist(),
y=dfYear1.loc[sex[0].title()].tolist(),
marker_color=my_colors[0],
marker_line_color=my_line_colors[0],
marker_line_width=1.5,
opacity=0.6),
go.Bar(name="20" + year[1],
x=dfYear1.columns.tolist(),
y=dfYear2.loc[sex[0].title()],
marker_color=my_colors[1],
marker_line_color=my_line_colors[1],
marker_line_width=1.5,
opacity=0.6)
]
return {'data': traces, 'layout': layout1}
def updateFigAge(ageCateg, states, sex, difTypes, year):
if len(year) == 1:
selectedExtendedDfs = toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(usaData.dfsArray, 'index', ['SEX']),
'state', states), 'difficulty', difTypes), 'year', year)
df = dfs_sum([df['dataFrame'] for df in selectedExtendedDfs
])[toolz.getAgeOptions(usaData.dfsArray, ageCateg)]
if len(sex) == 2:
trace1 = go.Bar(x=df.columns.tolist(),
y=df.loc["Male"].tolist(),
name='Male')
trace2 = go.Bar(x=df.columns.tolist(),
y=df.loc["Female"].tolist(),
name='Female')
return {
'data': [trace1, trace2],
'layout': {
'title': "PREVALENCE BY AGE".title()
}
}
else:
trace = go.Bar(x=df.columns.tolist(),
y=df.loc[sex[0].title()].tolist(),
name=sex[0].title())
return {
'data': [trace],
'layout': {
'title': "PREVALENCE BY AGE".title()
}
}
else:
selectedExtendedDfsForYear1 = toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(usaData.dfsArray, 'index', ['SEX']),
'state', states), 'difficulty', difTypes), 'year',
[year[0]])
selectedExtendedDfsForYear2 = toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(usaData.dfsArray, 'index', ['SEX']),
'state', states), 'difficulty', difTypes), 'year',
[year[1]])
dfYear1 = dfs_sum([
df['dataFrame'] for df in selectedExtendedDfsForYear1
])[toolz.getAgeOptions(usaData.dfsArray, ageCateg)]
dfYear2 = dfs_sum([
df['dataFrame'] for df in selectedExtendedDfsForYear2
])[toolz.getAgeOptions(usaData.dfsArray, ageCateg)]
if len(sex) == 2:
trace1 = go.Bar(x=dfYear1.columns.tolist(),
y=dfYear1.loc["Male"].tolist(),
name='Male (20' + year[0] + ")",
width=0.15)
trace2 = go.Bar(x=dfYear1.columns.tolist(),
y=dfYear1.loc["Female"].tolist(),
name='Female (20' + year[0] + ")",
width=0.15)
trace3 = go.Bar(x=dfYear1.columns.tolist(),
y=dfYear2.loc["Male"].tolist(),
name='Male (20' + year[1] + ")",
width=0.15)
trace4 = go.Bar(x=dfYear1.columns.tolist(),
y=dfYear2.loc["Female"].tolist(),
name='Female (20' + year[1] + ")",
width=0.15)
return {
'data': [trace1, trace2, trace3, trace4],
'layout': {
'title': "PREVALENCE BY AGE".title(),
}
}
else:
trace = go.Bar(x=df.columns.tolist(),
y=df.loc[sex[0].title()].tolist(),
name=sex[0].title())
return {
'data': [trace],
'layout': {
'title': "PREVALENCE BY AGE".title()
}
}
def updateFigAgeDisNumber(states, ageCateg, year):
global layout, my_colors, my_line_colors
layout1 = copy.deepcopy(layout)
layout1['title'] = "Prevalence BY NUMBER OF DISABILITIES".title()
if len(year) > 1:
selectedExtendedDfsForYear1 = toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(usaData.dfsArray, 'index', ['AGE']),
'state', states), "columns", ["NUMBER OF DISABILITIES"]),
'year', [year[0]])
selectedExtendedDfsForYear2 = toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(usaData.dfsArray, 'index', ['AGE']),
'state', states), "columns", ["NUMBER OF DISABILITIES"]),
'year', [year[1]])
dfYear1 = dfs_sum(
[df['dataFrame'] for df in selectedExtendedDfsForYear1])
dfYear2 = dfs_sum(
[df['dataFrame'] for df in selectedExtendedDfsForYear2])
fig = make_subplots(rows=1,
cols=2,
subplot_titles=("20" + str(year[0]),
"20" + str(year[1])))
fig.add_trace(go.Bar(
x=[index[:-1] for index in dfYear1.index.tolist()],
y=dfYear1.iloc[:, 0].tolist(),
name=dfYear1.columns.tolist()[0].title(),
marker_color=my_colors[0],
marker_line_color=my_line_colors[0],
marker_line_width=1.5,
opacity=0.6),
row=1,
col=1)
fig.add_trace(go.Bar(
x=[index[:-1] for index in dfYear1.index.tolist()],
y=dfYear1.iloc[:, 1].tolist(),
name=dfYear1.columns.tolist()[1].title(),
marker_color=my_colors[1],
marker_line_color=my_line_colors[1],
marker_line_width=1.5,
opacity=0.6),
row=1,
col=1)
fig.add_trace(go.Bar(
x=[index[:-1] for index in dfYear2.index.tolist()],
y=dfYear2.iloc[:, 0].tolist(),
name=dfYear2.columns.tolist()[0].title(),
marker_color=my_colors[0],
marker_line_color=my_line_colors[0],
marker_line_width=1.5,
opacity=0.6,
showlegend=False),
row=1,
col=2)
fig.add_trace(go.Bar(
x=[index[:-1] for index in dfYear2.index.tolist()],
y=dfYear2.iloc[:, 1].tolist(),
name=dfYear2.columns.tolist()[1].title(),
marker_color=my_colors[1],
marker_line_color=my_line_colors[1],
marker_line_width=1.5,
opacity=0.6,
showlegend=False),
row=1,
col=2)
fig.update_layout(barmode='stack')
fig.update_layout(autosize=True)
fig.update_layout(margin=dict(l=30, r=30, b=20, t=40))
fig.update_layout(hovermode="closest")
fig.update_layout(plot_bgcolor="#F9F9F9")
fig.update_layout(paper_bgcolor="#F9F9F9")
fig.update_layout(legend=dict(font=dict(size=10), orientation="h"))
fig.update_layout(yaxis=go.YAxis(showticklabels=False))
fig.update_layout(
title=dict(text='Prevalence By Number Of Disabilities',
x=0.5,
xanchor='center'))
return fig
else:
selectedExtendedDfs = toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(
toolz.dfSelector(usaData.dfsArray, 'index', ['AGE']),
'state', states), "columns", ["NUMBER OF DISABILITIES"]),
'year', [year[0]])
df = dfs_sum([df['dataFrame'] for df in selectedExtendedDfs])
trace1 = go.Bar(x=[index[:-1] for index in df.index.tolist()],
y=df.iloc[:, 0].tolist(),
name=df.columns.tolist()[0].title(),
marker_color=my_colors[0],
marker_line_color=my_line_colors[0],
marker_line_width=1.5,
opacity=0.6)
trace2 = go.Bar(x=[index[:-1] for index in df.index.tolist()],
y=df.iloc[:, 1].tolist(),
name=df.columns.tolist()[1].title(),
marker_color=my_colors[1],
marker_line_color=my_line_colors[1],
marker_line_width=1.5,
opacity=0.6)
return {'data': [trace1, trace2], 'layout': layout1}
