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import pandas as pd
import numpy as np
import plotly.express as px
import streamlit as st
st.set_page_config(
page_title=' Forest Coverage data Analysis',
page_icon='📈',
layout='wide'
)
Years=['1990','1991','1992','1993','1994','1995','1996','1997','1998','1999',
'2000','2001','2002','2003','2004','2005','2006','2007','2008','2009','2010','2011','2012','2013','2014','2015']
@st.cache_data
def load_data():
df=pd.read_csv('data/forest_coverage_percent.csv')
df.rename({'geo':'Country'},axis=1,inplace=True)
df.set_index('Country',inplace=True)
df.sort_values('Country',inplace=True)
df['Total']=df[Years].sum(axis=1)
df['Average']=df.mean(axis=1)
df['Minimum']=df.min(axis=1)
df['Maximum']=df.max(axis=1)
return df
st.title('Forest Coverage Percentage')
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} forest coverage percentage')
if Graph == Graphs[1]:
fig = px.pie(cdf, 'Years',country, title=f'{country} forest coverage percentage')
if Graph == Graphs[2]:
fig = px.line(cdf, 'Years',country, title=f'{country} forest coverage percentage')
if Graph == Graphs[3]:
fig = px.area(cdf, 'Years',country, title=f'{country} forest coverage percentage')
if Graph == Graphs[4]:
fig = px.funnel(cdf, 'Years',country, title=f'{country} forest coverage percentage')
st.plotly_chart(fig, use_container_width=True)
st.header('Comparison of Country')
clist = st.multiselect("Select countries to compare", countries, default='India')
cdf = df.loc[clist, Years].T # T to rotate the data in 90deg
cdf.rename({'index':'Years'},axis=1,inplace=True)
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 forest coverage percent')
st.plotly_chart(fig1,use_container_width=True)
dfavg = df.sort_values(by='Average').reset_index()
dfavg.rename({'index':'Country'},axis=1,inplace=True)
fig2=px.bar(dfavg, 'Country', 'Average', title="Average percent of forest coverage by Country")
st.plotly_chart(fig2,use_container_width=True)
dfmin=df.sort_values(by='Minimum').reset_index()
dfmin.rename({'index':'Country'},axis=1,inplace=True)
fig3=px.bar(dfmin,'Country','Minimum',title='Minimum forest coverage by the Country' )
st.plotly_chart(fig3,use_container_width=True)
dfmax=df.sort_values(by='Maximum').reset_index()
dfmax.rename({'index':'Country'},axis=1,inplace=True)
fig4=px.bar(dfmax,'Country','Maximum',title='Maximum forest coverage 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 forest coverage by Country comparison')
fig5.add_scatter(x=df.index, y=df['Minimum'], mode='lines',)
st.plotly_chart(fig5,use_container_width=True)
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