# Create a dict with unique values for each year of every country
years = [x for x in df.iyear.unique()]

data = []

scale = [
    [0.0, '#fcf2f2'],
    [0.2, '#f4b2b2'],
    [0.4, '#f47575'],
    [0.6, '#ef5f5f'],
    [0.8, '#f74747'],
    [1.0, '#ff0000']
]

# Create data for each year
for year in years:
    entry = dict (
    type = 'choropleth',
    colorscale = scale,
    locations = df[df.iyear == year].groupby('country_txt').nkill.sum().keys(),
    locationmode = 'country names',
    z = [int(x) for x in df[df.iyear == year].groupby('country_txt').nkill.sum().values]
    )
    data.append(entry)

map = go.Figure([data[0]])

steps = []
for i in range(len(data)):
    step = dict(
        method = 'restyle',
        args = ['visible', [False] * len(data)],
        label = 'year {}'.format(i + min(years) + 1)
    )
    step['args'][1][i] = True
    steps.append(step)

sliders = [dict(
    active = 10,
    currentvalue = {"prefix": "Number of kills: "},
    pad = {"t": 50},
    steps = steps
)]

layout = dict(sliders = sliders)
chorVis = dict(data = data, layout = layout)
iplot(chorVis, filename = 'Sine wave slider')