Finished, added more plots, cleanup, demo, final changes (b54de6b4) · Commits · Terézia Slanináková / PV251-project

README.md

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		# project: Smoking, obesity and alcohol consumption
		# PV251 Project: Smoking, obesity and alcohol consumption
		## Info
		- Author: Terézia Slanináková (445526)
		- Date: 24.12.2019
		@@ -7,3 +7,13 @@
		- Prerequisite: python3 installed
		- `pip install -r requirements.txt` will install the dependencies
		- `python index.py` will launch the server on http://127.0.0.1:8050/

		## Description
		The data shows oecd healthrisk data of smoking, alcohol consumption and overweight/obese population throughout the world (and years). The data was published for [Health at a Glance](http://dx.doi.org/10.1787/19991312), original data may be found [here](https://data.oecd.org/healthrisk/daily-smokers.htm#indicator-chart).

		1. Percentage of daily smokers (15+ yrs) \| men-women-total \| 1960-2018
		2. Liters of alcohol / capita / year (15+ yrs) \| total \| 1960-2018
		3. Percentage of population (15+ yrs) \| measured-selfreported \| 1978-2018

		## Demo
		![demo](demo.gif)
		No newline at end of file

apps/main.py

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		import dash
		from dash.dependencies import *
		import dash_core_components as dcc
		import dash_html_components as html
		import pandas as pd
		@@ -7,64 +8,49 @@ import plotly.graph_objs as go
		from app import app

		df = pd.read_csv('data/oecd.csv')
		df_smokers = pd.read_csv("./data/oecd-smokers.csv")
		df_alc = pd.read_csv("./data/oecd-alc.csv")
		df_obese = pd.read_csv("./data/oecd-obese.csv")

		layout = html.Div([
		html.Div([
		html.H3("Smoking, obesity and alcohol consumption (1960-2017)")], style={'textAlign': "center", "padding-bottom": "30"}),
		html.Div([
		html.Span("Indicator to display: (e.g. Smoking)", className="six columns", style={"text-align": "right", "width": "40%", "padding-top": 10}),
		dcc.Dropdown(id="value-selected", value='lifeExp',
		options=[{'label': "Smoking", 'value': 'smoke'}, {'label': "Alcohol", 'value': 'alcohol'}, {'label': "Overweight/Obese", 'value': 'obese'}],
		style={"display": "block", "margin-left": "auto", "margin-right": "auto", "width": "70%"},
		className="six columns")
		],
		className="row"
		),
		html.Div([
		dcc.Graph(id="my-graph")],
		style={'width': '100vh', 'display': 'inline-block', 'vertical-align': 'center'}),
		html.Div([
		html.Div([dcc.Graph(id="my-graph2", animate=False)], style={'width': '50%', 'display': 'inline-block', 'vertical-align': 'left', 'float':'left', 'overflowY': 'scroll', 'height': 500}),
		html.Div([dcc.Graph(id="my-graph3")], style={'width': '50%', 'display': 'inline-block', 'vertical-align': 'right', 'overflow': 'hidden'})
		])
		], style={'width': '100vh'}, className="container")


		@app.callback(
		[dash.dependencies.Output("my-graph", "figure"), dash.dependencies.Output("my-graph2", "figure"), dash.dependencies.Output("my-graph3", "figure")],
		[dash.dependencies.Input("value-selected", "value")]
		)
		def update_figure(selected):
		fig = go.Figure()
		horBarChart1 = go.Figure()
		def get_labels_for_countries():
		locations = df["LOCATION"].unique()
		loc_dicts = []
		for l in locations:
		loc_dicts.append({"label": l, "value": l})
		return loc_dicts

		df_smoke = df[(df["INDICATOR"] == "SMOKERS") & (df["SUBJECT"] == "TOT")]
		df_alc = df[(df["INDICATOR"] == "ALCOHOL") & (df["SUBJECT"] == "TOT")]
		df_overobese = df[(df["INDICATOR"] == "OVEROBESE")]
		def title(text):
		if text == "smoke":
		return "% of population (15+) smoking"
		elif text == "alcohol":
		return "Pure alcohol consumption per capita (liters)"
		def get_title_indicator(selected_indicator):
		title = ""
		if selected_indicator == "smoke":
		title = "% of population (15+) smoking"
		elif selected_indicator == "obese":
		title = "% of population being Overweight or obese"
		else:
		return "% of population being Overweight or obese"
		if selected == "smoke":
		df_to_use = df_smoke
		elif selected == "alcohol":
		df_to_use = df_alc
		title = "Pure alcohol consumption per capita (liters)"
		return title

		def get_title(selected_indicator, selected_gender, selected_obese):
		title = get_title_indicator(selected_indicator)
		if selected_indicator == "smoke":
		if selected_gender == "women":
		title += " (Women)"
		elif selected_gender == "men":
		title += " (Men)"
		else:
		df_to_use = df_overobese
		title += " (Men+Women)"
		elif selected_indicator == "obese":
		if selected_obese == "measured":
		title += " (Measured)"
		elif selected_obese == "reported":
		title += " (Self-reported)"

		make_visible = False
		for year in range(df_to_use["TIME"].min(), df_to_use["TIME"].max(), 1):
		df_to_use_per_year = df_to_use[df_to_use["TIME"] == year]
		if year == df_to_use["TIME"].max()-1:
		make_visible = True
		fig.add_trace(
		go.Choropleth(
		locations=df_to_use_per_year['LOCATION'],
		z=df_to_use_per_year["Value"],
		text=df_to_use_per_year['LOCATION'],
		return title

		def create_choropleth(locations, values, make_visible):
		return go.Choropleth(
		locations=locations,
		z=values,
		text=locations,
		autocolorscale=False,
		reversescale = True,
		colorscale = [
		@@ -78,47 +64,143 @@ def update_figure(selected):
		marker={'line': {'color': 'rgb(0,0,0)','width': 0.5}},
		colorbar={"thickness": 20,"len": 0.3,"x": 0,"y": 0.4},
		visible=make_visible)
		)
		sorted_df = df_to_use_per_year.sort_values(by='Value', ascending=False)
		horBarChart1.add_trace(go.Bar(
		x=sorted_df["Value"],
		y=sorted_df["LOCATION"],
		orientation='h'))

		def create_slider(df_years, choropleth_data):
		steps = []
		for i in range(df_to_use["TIME"].min(), df_to_use["TIME"].max(), 1):
		step = dict(
		method="restyle",
		args=["visible", [False] * len(fig.data)],
		label=i
		)
		step["args"][1][i-df_to_use["TIME"].min()] = True
		for i in range(df_years.min(), df_years.max(), 1):
		step = dict(method="restyle", args=["visible", [False] * len(choropleth_data)], label=i)
		step["args"][1][i-df_years.min()] = True
		steps.append(step)

		sliders = [dict(
		slider = [dict(
		active=len(steps)-1,
		currentvalue={"prefix": "Year: "},
		steps=steps
		)]
		return slider

		layout = html.Div([
		html.Div([
		html.H3("Smoking, obesity and alcohol consumption (1960-2017)")], style={'textAlign': "center", "padding-left": 30}),
		html.Div([
		html.Span("Indicator to display: (e.g. Alcohol)", className="six columns", style={"text-align": "right", "width": "50%", "padding-top": 10, "padding-left": "10%"}),
		dcc.Dropdown(id="value-selected-indicator", value='alcohol',
		options=[{'label': "Smoking", 'value': 'smoke'}, {'label': "Alcohol", 'value': 'alcohol'}, {'label': "Overweight/Obese", 'value': 'obese'}],
		style={"display": "block", "margin-left": "auto", "margin-right": "auto", "width": "70%"})
		],
		className="row"
		),
		html.Div([
		html.Div([
		html.Span("Gender (Relevant to smoking)", className="six columns", style={"text-align": "right", "width": "40%", "padding-left": 70}),
		dcc.Dropdown(id="value-selected-gender", value='total',
		options=[{'label': "Women", 'value': 'women'}, {'label': "Men", 'value': 'men'}, {'label': "Both", 'value': 'total'}],
		style={"display": "block", "margin-left": "auto", "margin-right": "0", "width": "70%", "padding-left": 70})
		],
		className="row", style={'font-size': '0.7em', 'float':'left', 'width': '50%'}
		),
		html.Div([
		html.Span("Measured/self-reported (Relevant to overweight/obese)", className="six columns", style={"text-align": "right", "width": "40%", "padding-left": 70}),
		dcc.Dropdown(id="value-selected-obese", value='both',
		options=[{'label': "Measured", 'value': 'measured'}, {'label': "Self-reported", 'value': 'reported'}, {'label': "Both", 'value': 'both'}],
		style={"display": "block", "margin-left": "auto", "margin-right": "auto", "width": "70%", "padding-left": 90},
		className="six columns")
		],
		className="row", style={'font-size': '0.7em', 'float':'right', 'width': '50%'}
		)
		], style={'overflow': 'hidden', 'width': '100%', 'padding-top': 10, 'padding-bottom': '10%'}),
		html.Div([
		dcc.Graph(id="choropleth")],
		style={'width': '100vh', 'display': 'inline-block', 'vertical-align': 'center'}),
		html.Div([dcc.Graph(id="horizontal-bar", animate=False)], style={'vertical-align': 'center', 'padding-bottom': '10%'}),
		html.Div([
		html.Span("Pick a country", className="six columns", style={"padding-top": 20, "padding-left": 70}),
		dcc.Dropdown(id="value-selected-country", value='AUS',
		options=get_labels_for_countries(),
		style={'width': '20vh', "padding-left": 70},
		className="six columns")],
		className="row-2", style={'padding-left': '30%'}
		),
		html.Div([
		html.Div([
		dcc.Graph(id="obesity-line")],
		style={'float':'left', 'width': '33%'}),
		html.Div([
		dcc.Graph(id="smoke-line")],
		style={'float':'left', 'width': '33%'}),
		html.Div([
		dcc.Graph(id="alc-consumption-line")],
		style={'overflow': 'hidden', 'width': '34%'}),
		], style={'overflow': 'hidden', 'width': '100%', 'padding-top': 10} )
		], className="container")

		fig3 = go.Figure(go.Bar(
		x=[20, 14, 23],
		y=['giraffes', 'orangutans', 'monkeys'],
		orientation='h'))

		@app.callback(
		[Output("choropleth", "figure"), Output("horizontal-bar", "figure"), Output("obesity-line", "figure"),
		Output("smoke-line", "figure"), Output("alc-consumption-line", "figure")],
		[Input("value-selected-indicator", "value"), Input("value-selected-country", "value"),
		Input("value-selected-gender", "value"), Input("value-selected-obese", "value")]
		)

		def update_figures(selected_indicator, selected_country, selected_gender, selected_obese):
		choropleth = go.Figure()
		horBarChart1 = go.Figure()

		if selected_indicator == "smoke": df_ind = df_smokers
		elif selected_indicator == "alcohol": df_ind = df_alc
		else: df_ind = df_obese
		df_ind_sel = df_ind

		if selected_indicator == "smoke":
		if selected_gender == "women":
		df_ind_sel = df_ind[df_ind["SUBJECT"] == "WOMEN"]
		elif selected_gender == "men":
		df_ind_sel = df_ind[df_ind["SUBJECT"] == "MEN"]
		else:
		df_ind_sel = df_ind[df_ind["SUBJECT"] == "TOT"]
		elif selected_indicator == "obese":
		if selected_obese == "measured":
		df_ind_sel = df_ind[df_ind["SUBJECT"] == "MEASURED"]
		elif selected_obese == "reported":
		df_ind_sel = df_ind[df_ind["SUBJECT"] == "SELFREPORTED"]

		make_visible = False
		for year in range(df_ind_sel["TIME"].min(), df_ind_sel["TIME"].max(), 1):
		df_to_use_per_year = df_ind_sel[df_ind_sel["TIME"] == year]
		if year == df_ind_sel["TIME"].max()-1:
		make_visible = True
		# --- Choropleth -- #
		choropleth.add_trace(create_choropleth(df_to_use_per_year['LOCATION'], df_to_use_per_year['Value'], make_visible))

		# --- Horizontal bar chart -- #
		df_dropped = df_to_use_per_year.drop_duplicates(["LOCATION"])
		df_dropped = df_dropped.sort_values(by=['Value'])
		horBarChart1.add_trace(go.Bar(x=df_dropped["Value"], y=df_dropped["LOCATION"], orientation='h', visible=make_visible))
		horBarChart1.update_layout(autosize=False, width=500, height=500, margin=go.layout.Margin(l=50, r=50, b=100, t=100, pad=4))

		sliders = create_slider(df_ind_sel["TIME"], choropleth.data)

		# --- 3 Line charts per country -- #
		df_ = df[df["LOCATION"] == selected_country]
		x1 = df_[(df_["INDICATOR"] == "OVEROBESE")].drop_duplicates(["TIME"]).sort_values(by=["TIME"])
		x2 = df_[(df_["INDICATOR"] == "SMOKERS") & (df_["SUBJECT"] == "TOT")]
		x3 = df_[(df_["INDICATOR"] == "ALCOHOL")]
		fig3 = go.Figure(go.Scatter(x=x1["TIME"], y=x1["Value"], marker_color='royalblue'))
		fig4 = go.Figure(go.Scatter(x=x2["TIME"], y=x2["Value"], marker_color='lightsalmon'))
		fig5 = go.Figure(go.Scatter(x=x3["TIME"], y=x3["Value"], marker_color='lightseagreen'))

		return [
		{"data": fig.data,
		{"data": choropleth.data,
		"layout": go.Layout(
		title=title(selected),height=800,
		geo={
		'showframe': False,
		'showcoastlines': True,
		'showcountries': True,
		'countrycolor': 'gray'
		},
		sliders=sliders)},
		title=get_title(selected_indicator, selected_gender, selected_obese),height=800,
		geo={'showframe': False, 'showcoastlines': True, 'showcountries': True, 'countrycolor': 'gray' }, sliders=sliders)},
		{"data": horBarChart1.data,
		"layout": go.Layout(title="Comparison of countries", yaxis=dict(title="y", tickmode="linear"), sliders=sliders)
		"layout": go.Layout(title=get_title_indicator(selected_indicator) + " \| Sorted country comparison", xaxis=dict(title="Year"), yaxis=dict(title="Country"), sliders=sliders)
		},
		{"data": fig3.data,
		"layout": go.Layout(title="random")}]
		"layout": go.Layout(title=f"Obesity in {selected_country}", xaxis=dict(title="Year"), yaxis=dict(title=get_title_indicator("obese")))},
		{"data": fig4.data,
		"layout": go.Layout(title=f"Smoking in {selected_country}", xaxis=dict(title="Year"), yaxis=dict(title=get_title_indicator("smoke")))},
		{"data": fig5.data,
		"layout": go.Layout(title=f"Alcohol consumption in {selected_country}", xaxis=dict(title="Year"), yaxis=dict(title=get_title_indicator("alcohol")))},
		]

data/oecd-alc.csv

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data/oecd-obese.csv

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data/oecd-smokers.csv

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