mirror of
https://github.com/aykhans/AzSuicideDataVisualization.git
synced 2025-04-19 01:49:43 +00:00
150 lines
5.6 KiB
Python
150 lines
5.6 KiB
Python
import pandas as pd
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import plotly.express as px
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import streamlit as st
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import os
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import numpy as np
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data_location = os.path.realpath(
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os.path.join(os.getcwd(), 'data'))
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st.set_page_config(page_title='Azerbaijan Suicide Data',
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page_icon=':bar_chart:',
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layout='wide')
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####################################### Data by Year #######################################
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data_year = pd.read_excel(os.path.join(data_location, 'azerbaijan_suicide_data.xlsx'), sheet_name='year')
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st.sidebar.header('Data by Year:')
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data_year_filter_year = st.sidebar.multiselect(
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'Select Year:',
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options = data_year['Year'].unique(),
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default = data_year['Year'].unique()
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)
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data_year_selection = data_year.query(
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'Year == @data_year_filter_year'
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)
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both_sexes = [float(d[:d.find(' ')]) for d in data_year_selection.Both_sexes]
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both_sexes_len = len(both_sexes)
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average_both_sexes_year = sum(both_sexes) / (both_sexes_len if both_sexes_len else 1)
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male = [float(d[:d.find(' ')]) for d in data_year_selection.Male]
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male_len = len(male)
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average_male_year = sum(male) / (male_len if male_len else 1)
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female = [float(d[:d.find(' ')]) for d in data_year_selection.Female]
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female_len = len(female)
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average_female_year = sum(female) / (female_len if female_len else 1)
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df_line_graph = pd.DataFrame(
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{'Year': data_year_selection.Year, 'Both Sexes': both_sexes, 'Male': male, 'Female': female})
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st.title('<h5>Azerbaijan Suicide Data by Year(2000-2019)</h5>', 1)
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st.dataframe(data_year_selection)
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st.title('<h1>Dashboard by Year</h1>', 1)
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dashboard_column1, dashboard_column2 = st.columns([1, 2])
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with dashboard_column1:
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st.subheader('Averages by Years')
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st.markdown(f'#### Average of Both Sexes: _{round(average_both_sexes_year, 2)}_')
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st.markdown(f'#### Average of Male: _{round(average_male_year, 2)}_')
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st.markdown(f'#### Average of Female: _{round(average_female_year, 2)}_')
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with dashboard_column2:
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if average_both_sexes_year > 0:
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bar_graph = px.bar(x=['Both Sexes', 'Male', 'Female'], y=[average_both_sexes_year, average_male_year, average_female_year])
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st.plotly_chart(bar_graph)
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if len(df_line_graph) > 1:
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st.title('<h1>Gender Line Graph by Year</h1>', 1)
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line_graph_column1, line_graph_column2 = st.columns([1, 7])
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with line_graph_column1:
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column_list = []
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st.markdown(' ')
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both_sexes_check_box_year = st.checkbox('Both Sexes', value=1, key='both_sexes_check_box_year')
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male_check_box_year = st.checkbox('Male', value=1, key='male_check_box_year')
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female_check_box_year = st.checkbox('Female', value=1, key='female_check_box_year')
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if both_sexes_check_box_year: column_list.append('Both Sexes')
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if male_check_box_year: column_list.append('Male')
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if female_check_box_year: column_list.append('Female')
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with line_graph_column2:
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if column_list:
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line_graph = px.line(df_line_graph, x='Year', y=column_list)
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st.plotly_chart(line_graph)
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####################################### Data by Age #######################################
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st.title('<h5>Azerbaijan Suicide Data by Age (2019)</h5>', 1)
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data_age = pd.read_excel(os.path.join(data_location, 'azerbaijan_suicide_data.xlsx'), sheet_name='age')\
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.loc[::-1].reset_index(drop=True)
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st.sidebar.header('Data by Age:')
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data_age_filter_age = st.sidebar.multiselect(
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'Select Age:',
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options = data_age['Age'].unique(),
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default = data_age['Age'].unique()
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)
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data_age_selection = data_age.query(
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'Age == @data_age_filter_age'
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)
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average_both_sexes_age = np.average(data_age_selection.Both_sexes)
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average_male_age = np.average(data_age_selection.Male)
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average_female_age = np.average(data_age_selection.Female)
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st.dataframe(data_age_selection)
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st.title('<h1>Dashboard by Age</h1>', 1)
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dashboard_column1, dashboard_column2 = st.columns([1, 2])
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with dashboard_column1:
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st.subheader('Averages by Age')
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st.markdown(f'#### Average of Both Sexes: _{round(average_both_sexes_age, 2)}_')
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st.markdown(f'#### Average of Male: _{round(average_male_age, 2)}_')
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st.markdown(f'#### Average of Female: _{round(average_female_age, 2)}_')
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with dashboard_column2:
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if average_both_sexes_age > 0:
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bar_graph = px.bar(x=['Both Sexes', 'Male', 'Female'], y=[average_both_sexes_age, average_male_age, average_female_age])
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st.plotly_chart(bar_graph)
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if 1:
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st.title('<h1>Gender Line Graph by Age</h1>', 1)
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line_graph_column1, line_graph_column2 = st.columns([1, 7])
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with line_graph_column1:
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column_list = []
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st.markdown(' ')
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both_sexes_check_box_age = st.checkbox('Both Sexes', value=1, key='both_sexes_check_box_age')
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male_check_box_age = st.checkbox('Male', value=1, key='male_check_box_age')
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female_check_box_age = st.checkbox('Female', value=1, key='female_check_box_age')
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if both_sexes_check_box_age: column_list.append('Both Sexes')
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if male_check_box_age: column_list.append('Male')
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if female_check_box_age: column_list.append('Female')
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with line_graph_column2:
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if column_list:
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data_age_line_graph = data_age.copy()
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data_age_line_graph.columns = ['Age', 'Both Sexes', 'Male', 'Female']
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line_graph = px.line(data_age_line_graph, x='Age', y=column_list)
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st.plotly_chart(line_graph)
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st.markdown('***')
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st.markdown('###### Data Source: https://www.who.int/data/gho/data/themes/mental-health/suicide-rates')
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hide_st_style = """
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<style>
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#MainMenu {visibility: hidden;}
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footer {visibility: hidden;}
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header {visibility: hidden;}
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</style>
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"""
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st.markdown(hide_st_style, unsafe_allow_html=True)
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