def getSexGeneral():
global ageSexe04, usaData
df = pd.DataFrame(index=['Male', 'Female'],
columns=['Morocco', 'Usa'],
data=[[0, 0], [0, 0]])
SexeMar = [
ageSexe04[disType].df[['Masculin', 'Féminin']]
for disType in ageSexe04.keys()
]
sumUsa = 0
usefulDfs = toolz.dfSelector(
toolz.dfSelector(toolz.dfSelector(usaData.dfsArray, 'index', ['SEX']),
'year', ['16']), 'difficulty',
['self-care ', 'vision ', 'hearing ', 'cognitive ', 'ambulatory '])
for tmpExtDf in usefulDfs:
for option in ['Male', 'Female']:
df.loc[option]['Usa'] += tmpExtDf['dataFrame'].loc[option].sum()
for tmpDf in SexeMar:
for option in ['Masculin', 'Féminin']:
if option == 'Masculin':
df.loc['Male']['Morocco'] += tmpDf[option].sum()
elif option == 'Féminin':
df.loc['Female']['Morocco'] += tmpDf[option].sum()
return df
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 getDisTypeGeneral():
global ageSexe04, usaData
df = pd.DataFrame(index=[disType for disType in ageSexe04.keys()],
columns=['Morocco', 'Usa'])
sumMar = pd.Series(index=[disType for disType in ageSexe04.keys()],
data=[
ageSexe04[disType].df['Ensemble'].sum()
for disType in ageSexe04.keys()
]).sum()
for disType in ageSexe04.keys():
df.loc[disType,
'Morocco'] = (ageSexe04[disType].df['Ensemble'].sum()) / sumMar
sumUsa = 0
usefulDfs = toolz.dfSelector(
toolz.dfSelector(usaData.dfsArray, 'difficulty', [
'independent living ', 'self-care ', 'vision ', 'hearing ',
'cognitive ', 'ambulatory '
]), 'year', ['16'])
for tmpDf in usefulDfs:
sumUsa += tmpDf['dataFrame'].sum().sum()
convDict = {
"Sensoriel":
toolz.dfSelector(
toolz.dfSelector(usaData.dfsArray, 'difficulty',
['vision ', 'hearing ']), 'year', ['16']),
"Moteur":
toolz.dfSelector(
toolz.dfSelector(usaData.dfsArray, 'difficulty',
['independent living ', 'self-care ']), 'year',
['16']),
"Chronique":
toolz.dfSelector(
toolz.dfSelector(usaData.dfsArray, 'difficulty', ['ambulatory ']),
'year', ['16']),
"Mental":
toolz.dfSelector(
toolz.dfSelector(usaData.dfsArray, 'difficulty', ['cognitive ']),
'year', ['16'])
}
for disType in df.index.tolist():
tmpSum = 0
for tmpExtDf in convDict[disType]:
tmpSum += tmpExtDf['dataFrame'].sum().sum()
df.loc[disType, 'Usa'] = tmpSum / sumUsa
return df
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 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 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 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}
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 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 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 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 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()
}
}