過去38年間の10カ国のGDP per Capitaの推移をplotlyで視覚化

import pandas as pd

imf = pd.read_csv('WEOApr2019all.xls',encoding='latin1',sep='\t', thousands=',', na_values=['n/a', '--'])

imf1 = imf[imf['WEO Subject Code'] == 'NGDPDPC']
imf1[['Country','2018']].tail(10)

imf1 = imf1.fillna(0)
for i in range(9,55):
    imf1.iloc[:, i] = round(imf1.iloc[:, i],0).apply(pd.to_numeric, errors="coerce").astype(int)

variables = ['NGDPDPC']
countries = ['SGP', 'DEU', 'FRA', 'CHE', 'USA', 'JPN', 'CAN' ,'GBR','AUS','QAT']
GDP = imf1[imf1['ISO'].isin(countries) & imf1['WEO Subject Code'].isin(variables)]
GDP = GDP.set_index('Country').T.dropna()

import plotly.graph_objs as go
from plotly.offline import plot,iplot

year = list(range(1980,2019))

trace0 = go.Scatter(
    x = year,
    y = GDP[8:47]['Japan'],
    name = 'Japan',
    line = dict(
        color = ('mediumvioletred'),
        width = 4)
)

trace1 = go.Scatter(
    x = year,
    y = GDP[8:47]['Canada'],
    name = 'Canada',
    line = dict(
        color = ('green'),
        width = 4)
)

trace2 = go.Scatter(
    x = year,
    y = GDP[8:47]['France'],
    name = 'France',
    line = dict(
        color = ('magenta'),
        width = 4)
)

trace3 = go.Scatter(
    x = year,
    y = GDP[8:47]['Germany'],
    name = 'Germany',
    line = dict(
        color = ('blue'),
        width = 4)
)

trace4 = go.Scatter(
    x = year,
    y = GDP[8:47]['Singapore'],
    name = 'Singapore',
    line = dict(
        color = ('purple'),
        width = 4)
)

trace5 = go.Scatter(
    x = year,
    y = GDP[8:47]['Switzerland'],
    name = 'Switzerland',
    line = dict(
        color = ('deeppink'),
        width = 4)
)

trace6 = go.Scatter(
    x = year,
    y = GDP[8:47]['United Kingdom'],
    name = 'United Kingdom',
    line = dict(
        color = ('black'),
        width = 4)
)

trace7 = go.Scatter(
    x = year,
    y = GDP[8:47]['United States'],
    name = 'United States',
    line = dict(
        color = ('deepskyblue'),
        width = 4)
)

trace8 = go.Scatter(
    x = year,
    y = GDP[8:47]['Australia'],
    name = 'Australia',
    line = dict(
        color = ('teal'),
        width = 4)
)

trace9 = go.Scatter(
    x = year,
    y = GDP[8:47]['Qatar'],
    name = 'Qatar',
    line = dict(
        color = ('palegreen'),
        width = 4)
)

data = [trace0,trace1,trace2,trace3,trace4,trace5,trace6,trace7,trace8,trace9]
layout = dict(title = 'GDP Per Capita by Country',
    title_font=dict(size=24, family='Courier', color='black'),
    yaxis=dict(title='一人当たりのGDP',title_font=dict(size=22)
                ,tickfont=dict(size=20)),
    xaxis=dict(title='年',title_font=dict(size=22),tickfont=dict(size=20)),
    autosize=False,width=800, height=640,
    hovermode= 'x',
    hoverlabel=dict(font=dict(size=24)),
    legend=dict(x=-.001,y=1,font=dict(size=21,color='black'),bgcolor='rgba(0,0,0,0)'),
    legend_orientation="v"
              )
fig = dict(data=data, layout=layout)
plot(fig,show_link=False,filename="c.html",include_plotlyjs=False)