import numpy as np
import pandas as pd
import holoviews as hv
hv.extension('bokeh', 'matplotlib')

diseases = pd.read_csv('../assets/diseases.csv.gz')
diseases.head()

vdims = [('measles', 'Measles Incidence'), ('pertussis', 'Pertussis Incidence')]
ds = hv.Dataset(diseases, ['Year', 'State'], vdims)

ds = ds.aggregate(function=np.mean)
ds

%%opts Curve [width=600 height=250] {+framewise}
(ds.to(hv.Curve, 'Year', 'measles') + ds.to(hv.Curve, 'Year', 'pertussis')).cols(1)

%%opts Bars [width=800 height=400 tools=['hover'] xrotation=90 show_legend=False]
states = ['New York', 'New Jersey', 'California', 'Texas']
ds.select(State=states, Year=(1980, 1990)).to(hv.Bars, ['Year', 'State'], 'measles').sort()

%%opts Curve [width=200] (color='indianred')
grouped = ds.select(State=states, Year=(1930, 2005)).to(hv.Curve, 'Year', 'measles')
grouped.grid('State')

%%opts Curve [width=600] (color=Cycle(values=['indianred', 'slateblue', 'lightseagreen', 'coral']))
grouped.overlay('State')

%%opts Curve [width=600]
agg = ds.aggregate('Year', function=np.mean, spreadfn=np.std)
(hv.Curve(agg) * hv.ErrorBars(agg,vdims=['measles', 'measles_std']).iloc[::2]).redim.range(measles=(0, None))