def gen_sunburst(clicks, yearpick, grouppicker, countrypick, stylepick):
if clicks:
if isinstance(yearpick, str):
filtered_byyear = popAgeGroup()[popAgeGroup()['time'].isin(
[yearpick])]
else:
filtered_byyear = popAgeGroup()[popAgeGroup()['time'].isin(
yearpick)]
if isinstance(grouppicker, str):
filter_bygroup = filtered_byyear[filtered_byyear['indic_de'].isin(
[grouppicker])]
else:
filter_bygroup = filtered_byyear[filtered_byyear['indic_de'].isin(
grouppicker)]
if isinstance(countrypick, str):
filter_bycountry = filter_bygroup[filter_bygroup['geo'].isin(
[countrypick])]
else:
filter_bycountry = filter_bygroup[filter_bygroup['geo'].isin(
countrypick)]
''''PX is being used rather then go.Sunburst due to px requirements fitting more easily with our
requirements as go.Scatter required all possible parent relation ships to be given '''
sunburstout = (px.sunburst(filter_bycountry,
path=['time', 'geo', 'indic_de'],
values='values',
height=800,
template=stylepick))
return sunburstout
def update_graph(picked_year, xaxis_name, yaxis_name):
filtered_df = popAgeGroup()[popAgeGroup()['time'] == picked_year]
traces = []
for country_name in filtered_df['geo'].unique():
df_by_country = filtered_df[filtered_df['geo'] == country_name]
traces.append(
go.Scatter(x=df_by_country[xaxis_name],
y=df_by_country[yaxis_name],
mode='markers',
marker={
'size': 15,
'opacity': 0.5,
'line': {
'width': 0.5,
'color': 'white'
}
}))
return {
'data':
traces,
'layout':
go.Layout(title='population from groups',
xaxis={'title': xaxis_name},
yaxis={'title': yaxis_name},
hovermode='closest'),
}
def gen_table(clicks, yearpick, grouppicker, countrypick):
"""filtering by year down to group down to country selected"""
if clicks:
if isinstance(yearpick, str):
filtered_by_year = popAgeGroup()[popAgeGroup()['time'].isin(
[yearpick])]
else:
filtered_by_year = popAgeGroup()[popAgeGroup()['time'].isin(
yearpick)]
if isinstance(grouppicker, str):
filter_by_group = filtered_by_year[
filtered_by_year['indic_de'].isin([grouppicker])]
else:
filter_by_group = filtered_by_year[
filtered_by_year['indic_de'].isin(grouppicker)]
if isinstance(countrypick, str):
filter_by_country = filter_by_group[filter_by_group['geo'].isin(
[countrypick])]
else:
filter_by_country = filter_by_group[filter_by_group['geo'].isin(
countrypick)]
table_out = dt.DataTable(
data=filter_by_country.to_dict('records'),
columns=[{
'name': i,
'id': i
} for i in filter_by_country.columns],
fixed_rows={'headers': True},
page_size=30,
style_table={
'height': '300px',
'overflowY': 'auto'
},
style_header={
'backgroundColor': 'white',
'fontWeight': 'bold'
},
export_format='xlsx',
export_headers='display',
)
return table_out
import dash_core_components as dcc
import dash_html_components as html
import dash_bootstrap_components as dbc
from dash.dependencies import Input, Output
from apps.navbar import Navbar
from app import app
from apps.eurostatapi import popAgeGroup
import plotly.graph_objs as go
import plotly.express as px
nav = Navbar()
year_options = []
for time in popAgeGroup()['time'].unique():
year_options.append({'label': str(time), 'value': time})
features = popAgeGroup().columns
body = html.Div([
html.Div([
html.H3('Population'),
html.Div(id='app-2-display-value'),
dcc.Link('Go to App 1', href='/apps/page1'),
html.Div([
html.Div([
dcc.Dropdown(id='xaxis',
options=[{
'label': i,
'value': i
} for i in features],
value='indic_de')
import time
import dash
import dash_bootstrap_components as dbc
import dash_core_components as dcc
import dash_html_components as html
import numpy as np
import plotly.express as px
import plotly.graph_objs as go
from dash.dependencies import Input, Output, State
from apps.eurostatapi import popAgeGroup
from app import app
from apps.navbar import Navbar
nav = Navbar()
body = html.H4('Under construction')
features = popAgeGroup().columns
def PageLayOut():
layout = html.Div([nav, body])
return layout
def generate_graphs(n_clicks, yearpick, xaxis_name, yaxis_name, grouppicker,
stylepick, countrypick):
if not n_clicks:
# generate empty graphs when app loads
return {
k: go.Figure(data=[])
for k in ["scatter", "pie", 'bar', 'sun']
}
"""isinstance used due to a dropdown single item is a string not a list object and requires to be given []"""
"""to present is as a list for .isin to read"""
if n_clicks:
if isinstance(yearpick, str):
filtered_year = popAgeGroup()[popAgeGroup()['time'].isin(
[yearpick])]
else:
filtered_year = popAgeGroup()[popAgeGroup()['time'].isin(yearpick)]
if isinstance(grouppicker, str):
filtered_group = filtered_year[filtered_year['indic_de'].isin(
[grouppicker])]
else:
filtered_group = filtered_year[filtered_year['indic_de'].isin(
grouppicker)]
if isinstance(countrypick, str):
filtered_country = filtered_group[filtered_group['geo'].isin(
[countrypick])]
else:
filtered_country = filtered_group[filtered_group['geo'].isin(
countrypick)]
traces = []
traces2 = []
traces3 = []
for country_name in filtered_country['geo'].unique():
df_by_country = filtered_country[filtered_country['geo'] ==
country_name]
(go.Figure(
traces3.append(
go.Bar(x=df_by_country[df_by_country['geo'] ==
country_name]['time'],
y=df_by_country[df_by_country['geo'] == country_name]
['values'],
textposition='auto',
name=country_name,
text=df_by_country['indic_de'],
hoverinfo='name+text+x+y'))))
"""generating the scatter plot"""
go.Figure(
traces.append(
go.Scatter(x=df_by_country[xaxis_name],
y=df_by_country[yaxis_name],
mode='markers',
marker={
'size': 14,
'opacity': 0.5,
'line': {
'width': 1
},
},
name=country_name,
text=df_by_country['time'],
hoverinfo='x+y+text')))
"""generating the Pie chart"""
(go.Figure(
traces2.append(
go.Pie(name="pop",
values=filtered_country[yaxis_name],
labels=filtered_country[xaxis_name],
textinfo='value+label'))))
''''filling pie figure with data and layout'''
pie = {
'data':
traces2,
'layout':
go.Layout(
title='% population from groups {} in the year {} '.format(
grouppicker, yearpick),
template=stylepick,
height=800,
)
}
''''filling scatter figure with data and layout'''
scatter = {
'data':
traces,
'layout':
go.Layout(title='% population from groups {} in the year {} '.format(
grouppicker, yearpick),
xaxis={'title': xaxis_name},
yaxis={'title': yaxis_name},
hoverlabel=dict(bgcolor="white", font_size=16),
template=stylepick,
hovermode='closest',
height=800,
autosize=True),
}
''''filling bar figure with data and layout'''
bar = {
'data':
traces3,
'layout':
go.Layout(title='% population from groups {} in the year {} '.format(
grouppicker, yearpick),
xaxis={'title': 'year'},
yaxis={'title': '% of population'},
template=stylepick,
hoverlabel=dict(bgcolor="white", font_size=16),
hovermode='closest',
height=800)
}
# save figures in a dictionary for sending to the dcc.Store
return {"pie": pie, "scatter": scatter, "bar": bar}
import dash_bootstrap_components as dbc
import dash_core_components as dcc
import dash_html_components as html
import numpy as np
import plotly.express as px
import plotly.graph_objs as go
from dash.dependencies import Input, Output, State
import dash_table as dt
from apps.eurostatapi import popAgeGroup
from app import app
from apps.navbar import Navbar
nav = Navbar()
'''used to create dropdown menues'''
year_options = []
for time in popAgeGroup()['time'].unique():
year_options.append({'label': str(time), 'value': time})
group_options = []
for group in popAgeGroup()['indic_de'].unique():
group_options.append({'label': str(group), 'value': group})
country_options = []
for country in popAgeGroup()['geo'].unique():
country_options.append({'label': str(country), 'value': country})
features = popAgeGroup().columns
body = dbc.Container(
[
dcc.Store(id="store"),