import pandas as pd import numpy as np import plotly.express as px import streamlit as st st.set_page_config( page_title='Hydro Power Generation data Analysis', page_icon='📈', layout='wide' ) Years=['1971','1972','1973','1974','1975','1976','1977','1978','1979','1980','1981','1982','1983','1984', '1985','1986','1987','1988','1989','1990','1991','1992','1993','1994','1995','1996','1997','1998','1999', '2000','2001','2002','2003','2004','2005','2006','2007','2008','2009','2010'] @st.cache_data def load_data(): df=pd.read_csv('data/hydro_power_generation_per_person.csv') df.rename(columns={'geo':'Country'},inplace=True) df.set_index('Country',inplace=True) df.drop(['1960','1961','1962','1963','1964','1965','1966','1967','1968','1969','1970','2011'],axis=1,inplace=True) df['Total'] = df[Years].sum(axis=1) df['Avgrage']=df.mean(axis=1) df['Maximum']=df.max(axis=1) df['Minimum']=df.min(axis=1) df.sort_index(inplace=True) return df st.title('Hydro Power Generation Per Person') df = load_data() st.dataframe(df,use_container_width=True) countries= df.index.unique().tolist() Graphs = ['bar','pie','line','area','funnel'] c1,c2 = st.columns(2) country = c1.selectbox("Select a Country", countries) Graph = c2.selectbox("Select a Graph type", Graphs) st.header("Country wise visualization") cdf = df.loc[country,Years].reset_index() cdf.rename({'index':'Years'},axis=1, inplace=True) if Graph == Graphs[0]: fig = px.bar(cdf, 'Years',country, title=f'{country} hydro power generation per person') if Graph == Graphs[1]: fig = px.pie(cdf, 'Years',country, title=f'{country} hydro power generation per person') if Graph == Graphs[2]: fig = px.line(cdf, 'Years',country, title=f'{country} hydro power generation per person') if Graph == Graphs[3]: fig = px.area(cdf, 'Years',country, title=f'{country} hydro power generation per person') if Graph == Graphs[4]: fig = px.funnel(cdf, 'Years',country, title=f'{country} hydro power generation per person') st.plotly_chart(fig, use_container_width=True) st.header("Comparison of Countries") clist = st.multiselect("Select countries to compare", countries, default='India') cdf = df.loc[clist, Years].T # T to rotate the data in 90deg st.write(cdf) figc = px.line(cdf,cdf.index, clist, title=f'Comparing {", ".join(clist)}') st.plotly_chart(figc, use_container_width=True) df.sort_values(by='Total', ascending=False, inplace=True) fig1=px.bar(df, x=df.index, y='Total',title='Total hydro power generation per person') st.plotly_chart(fig1, use_container_width=True) dfavg = df.sort_values(by='Avgrage').reset_index() dfavg.rename({'index':'Country'},axis=1,inplace=True) fig2=px.bar(dfavg, 'Country', 'Avgrage', title="Avgrage hydro power generation") st.plotly_chart(fig2, use_container_width=True) dfmax=df.sort_values(by='Maximum').reset_index() dfmax.rename({'index':'Country'},axis=1,inplace=True) fig3=px.bar(dfmax,'Country','Maximum',title='Maximum hydro power generation by the Country') st.plotly_chart(fig3, use_container_width=True) dfmin=df.sort_values(by='Minimum').reset_index() dfmin.rename({'index':'Country'},axis=1,inplace=True) fig4=px.bar(dfmin,'Country','Minimum',title='Minimum hydro power generation by the Country' ) st.plotly_chart(fig4,use_container_width=True) dfcomp=df.sort_values(by='Country',ascending=False,inplace=True) fig5 = px.line(df, x=df.index, y='Maximum',title='Maximum and Minimum hydro power generation comparisons') fig5.add_scatter(x=df.index, y=df['Minimum'], mode='lines',) st.plotly_chart(fig5, use_container_width=True)