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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='Income per Person GDP data Analysis', | |
| page_icon='📈', | |
| layout='wide' | |
| ) | |
| Years=['1800','1801','1802','1803','1804','1805','1806','1807','1808','1809','1810','1811','1812','1813', | |
| '1814','1815','1816','1817','1818','1819','1820','1821','1822','1823','1824','1825','1826','1827','1828', | |
| '1829','1830','1831','1832','1833','1834','1835','1836','1837','1838','1839','1840','1841','1842','1843', | |
| '1844','1845','1846','1847','1848','1849','1850','1851','1852','1853','1854','1855','1856','1857','1858', | |
| '1859','1860','1861','1862','1863','1864','1865','1866','1867','1868','1869','1870','1871','1872','1873', | |
| '1874','1875','1876','1877','1878','1879','1880','1881','1882','1883','1884','1885','1886','1887','1888', | |
| '1889','1890','1891','1892','1893','1894','1895','1896','1897','1898','1899','1900','1901','1902','1903', | |
| '1904','1905','1906','1907','1908','1909','1910','1911','1912','1913','1914','1915','1916','1917','1918', | |
| '1919','1920','1921','1922','1923','1924','1925','1926','1927','1928','1929','1930','1931','1932','1933', | |
| '1934','1935','1936','1937','1938','1939','1940','1941','1942','1943','1944','1945','1946','1947','1948', | |
| '1949','1950','1951','1952','1953','1954','1955','1956','1957','1958','1959','1960','1961','1962','1963', | |
| '1964','1965','1966','1967','1968','1969','1970','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','2011','2012','2013','2014','2015','2016','2017','2018'] | |
| def load_data(): | |
| df=pd.read_csv('data/income_per_person_gdppercapita_ppp_inflation_adjusted.csv') | |
| df.rename(columns={'geo':'Country'},inplace=True) | |
| df.set_index('Country',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('Income per Person GDP per Capital ppp Inflation Adjusted') | |
| 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} Income per Person GDP per Capital ppp Inflation Adjusted') | |
| if Graph == Graphs[1]: | |
| fig = px.pie(cdf, 'Years',country, title=f'{country} Income per Person GDP per Capital ppp Inflation Adjusted') | |
| if Graph == Graphs[2]: | |
| fig = px.line(cdf, 'Years',country, title=f'{country} Income per Person GDP per Capital ppp Inflation Adjusted') | |
| if Graph == Graphs[3]: | |
| fig = px.area(cdf, 'Years',country, title=f'{country} Income per Person GDP per Capital ppp Inflation Adjusted') | |
| if Graph == Graphs[4]: | |
| fig = px.funnel(cdf, 'Years',country, title=f'{country} Income per Person GDP per Capital ppp Inflation Adjusted') | |
| 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 Income per Person GDP per Capital ppp Inflation Adjusted') | |
| 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 Income per Person GDP per Capital ppp Inflation Adjusted by Country") | |
| 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 Income per Person GDP per Capital ppp Inflation Adjusted 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 Income per Person GDP per Capital ppp Inflation Adjusted 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 Income per Person GDP per Capital ppp Inflation Adjusted comparisons') | |
| fig5.add_scatter(x=df.index, y=df['Minimum'], mode='lines',) | |
| st.plotly_chart(fig5, use_container_width=True) |