app.py

import time
import streamlit as st

import pandas as pd
import plotly.express as px

import warnings
warnings.filterwarnings('ignore')

#Importing the cleaning file
from cleaning import *

################# PAGE SETUP

st.set_page_config(
    page_title="Renewable Dashboard",
    page_icon=":infinity:",
    layout="wide",
    initial_sidebar_state="expanded"
)

#Calling the merged_df
renw = EnergyProduction('./Data/Raw/EnergyProduction.csv')
gdp = CountriesGDP('./Data/Raw/CountriesGDP.csv')

#Merging Renewable and GDP
merged_df = pd.merge(renw,gdp, how='inner')\
    .sort_values('year')

#Ranking
df_ranking = renw[['cntry_name','value_ktoe']]
df_ranking = df_ranking.groupby(by=['cntry_name']).sum()\
    .sort_values('value_ktoe', ascending=False)
df_ranking['ranking'] = range(1, len(df_ranking['value_ktoe']) + 1)

################# SIDEBAR

#Sidebar config
st.sidebar.title('Select Country')

#Selecting the continent
merged_df = merged_df.sort_values('cntry_region')

cntry_reg = st.sidebar.selectbox("Continent:",merged_df['cntry_region'].unique())

df_c = merged_df.query(
    'cntry_region == @cntry_reg'
) 
df_c = df_c.sort_values('cntry_name')

#Selecting the country
cntry = st.sidebar.selectbox("Country:",df_c['cntry_name'].unique())

df_selection = df_c.query(
    'cntry_name == @cntry'
)
df_selection = df_selection.sort_values('year')

#Time Range
time_range = st.sidebar.slider(
    'Time range:',
    1990, 2015, (1990, 2015)
)

df_selection = df_selection[(df_selection['year'] >= time_range[0])&(df_selection['year'] <= time_range[1])]
renw = renw[(renw['year'] >= time_range[0])&(renw['year'] <= time_range[1])]

world_ranking = df_ranking.query(
    'cntry_name == @cntry'
)

#Convert the KToe units to GWh
on = st.sidebar.toggle('Convert to GWh')


################# DASHBOARD CONTENT

st.title(":bar_chart: Renewable Integration Dashboard")
st.markdown("###")

st.caption('Renewables include the primary energy equivalent of hydro (excluding pumped storage), geothermal, solar, wind, tide and wave sources. Energy derived from solid biofuels, biogasoline, biodiesels, other liquid biofuels, biogases and the renewable fraction of municipal waste are also included.\n This indicator is measured in thousand toe (tonne of oil equivalent) as well as in percentage of total primary energy supply.')

################# Section 1 - Metrics

sec_1 = st.container()
sec_1.subheader(cntry, divider='grey')
col1, col2, col3 = sec_1.columns(3, gap='large')

if on: #Units in GWh
    units_total = 'GWh'
    units_aver = 'GWh'
    df_selection = df_selection[['year','cntry_code','cntry_name','cntry_region','value_gwh','gdp']]\
        .rename(columns={'value_gwh':'value'})
    
else: #Units in Ktoe
    units_total = 'Ktoe'
    units_aver = 'Ktoe'
    df_selection = df_selection[['year','cntry_code','cntry_name','cntry_region','value_ktoe','gdp']]\
        .rename(columns={'value_ktoe':'value'})

#KPIs
total_renw = df_selection['value'].sum()
average_renw = df_selection['value'].mean()
std_renw = df_selection['value'].std()
delta_renw = round(std_renw / average_renw,2)

#Converting scale of units
if total_renw >= 1000:
    total_renw = total_renw/1000
    if on:
        units_total = 'TWh'
    else:
        units_total = 'Mtoe'


if average_renw >= 1000:
    average_renw = average_renw/1000
    if on:
        units_aver = 'TWh'
    else:
        units_aver = 'Mtoe'

#Printing KPI

col1.metric(
    label="Average Production:",
    value=f'{round(average_renw,1)} {units_aver}',
    delta=delta_renw,
)

col2.metric(
    label="Total Production:",
    value=f'{round(total_renw,1)} {units_total}',
)

col3.metric(
    label=":star2: World Ranking:",
    value=f"{world_ranking['ranking'].values[0]}º"
)


################# Section 2 - Charts

sec_2 = st.container()
col3, col4 = sec_2.columns(2, gap='large')

#Ploting the total production Year
fig_total = px.bar(
    df_selection, 
    x='year', 
    y='value',
    title=f'Renewable Production ({time_range[0]} - {time_range[1]})',
    labels={
        'year':'Year',
        'value':f'Energy Production ({units_total})'
    }
)

col3.plotly_chart(
    fig_total,
    use_container_width=True
)

#Ploting the total GDP Year
gdp_total = px.line(
    df_selection,
    x='year',
    y='gdp',
    title=f'GDP USD ({time_range[0]} - {time_range[1]}) ',
    labels={
        'year':'Year',
        'gdp':'GDP (USD)' 
    }
)
col4.plotly_chart(
    gdp_total,
    use_container_width=True
)

#################  RESET STREAMLIT
hide_st_style="""
            <style>
            #MainMenu {visibility:hidden;}
            footer {visibility: hidden;}
            header {visibility: hidden;}
            </style>
            """

st.markdown(hide_st_style, unsafe_allow_html=True)