Plotly Animated Bubble Chart: No Data In The Plot

I am trying to adapt the standard plotly animated bubble chart to a csv file with these columns: index,country,year,Country code,Total population (Gapminder),Life satisfaction in C

Solution 1:

I used the sample data you gave and worked on it, i've encounted few issues and added my comments on each line, the main reasons were pointed out in the comments section, but you can cross check my code with yours and get what you need

Code:

from plotly.offline import init_notebook_mode, iplot
from IPython.display import display, HTML

import pandas as pd

init_notebook_mode(connected=True)

url = 'testing.csv'
dataset = pd.read_csv(url)
# instead of hardcoding you can use unique() function to get the years present in the file, then convert to list and sort based on years# years = dataset['year'].unique().tolist()# years.sort()
years = ['2007','2008','2009','2010','2011','2012','2013'] # try to provide years that contain data in the data set# make list of continents
countries = []
for country in dataset['country'].unique():
    countries.append(country)
# make figure
figure = {
    'data': [],
    'layout': {},
    'frames': []
}
config = {'scrollzoom': True}

# fill in most of layout# there is a small ranging issue, where some points go out of the plot so try this code if you notice it#figure['layout']['xaxis'] = {'title': 'GDP per Capita',  'autorange': False, 'range': [int(dataset['GDP per capita'].min()), int(dataset['GDP per capita'].max())]} #was not set properly#figure['layout']['yaxis'] = {'title': 'Life Expectancy', 'autorange': False, #                             'range': [int(dataset['Life satisfaction in Cantril Ladder (World Happiness Report 2017)'].min()), #                                    int(dataset['Life satisfaction in Cantril Ladder (World Happiness Report 2017)'].max())]} #was not set properly


figure['layout']['xaxis'] = {'title': 'GDP per Capita', 'type': 'log', 'autorange': True} #was not set properly
figure['layout']['yaxis'] = {'title': 'Life Expectancy', 'autorange': True} #was not set properly
figure['layout']['hovermode'] = 'closest'
figure['layout']['showlegend'] = True
figure['layout']['sliders'] = {
    'args': [
        'slider.value', {
            'duration': 400,
            'ease': 'cubic-in-out'
        }
    ],
    'initialValue': '2007',
    'plotlycommand': 'animate',
    'values': years,
    'visible': True
}
figure['layout']['updatemenus'] = [
    {
        'buttons': [
            {
                'args': [None, {'frame': {'duration': 500, 'redraw': False},
                         'fromcurrent': True, 'transition': {'duration': 300, 'easing': 'quadratic-in-out'}}],
                'label': 'Play',
                'method': 'animate'
            },
            {
                'args': [[None], {'frame': {'duration': 0, 'redraw': False}, 'mode': 'immediate',
                'transition': {'duration': 0}}],
                'label': 'Pause',
                'method': 'animate'
            }
        ],
        'direction': 'left',
        'pad': {'r': 10, 't': 87},
        'showactive': False,
        'type': 'buttons',
        'x': 0.1,
        'xanchor': 'right',
        'y': 0,
        'yanchor': 'top'
    }
]

sliders_dict = {
    'active': 0,
    'yanchor': 'top',
    'xanchor': 'left',
    'currentvalue': {
        'font': {'size': 20},
        'prefix': 'Year:',
        'visible': True,
        'xanchor': 'right'
    },
    'transition': {'duration': 300, 'easing': 'cubic-in-out'},
    'pad': {'b': 10, 't': 50},
    'len': 0.9,
    'x': 0.1,
    'y': 0,
    'steps': []
}

# make data -  here you need to specify the year being used as starting point, important to change
year = 2007for country in countries:
    dataset_by_year = dataset[dataset['year'] == year]
    dataset_by_year_and_cont=dataset_by_year[dataset_by_year['country'] == country]

    data_dict = {
        'x': list(dataset_by_year_and_cont['GDP per capita']),
        'y': list(dataset_by_year_and_cont['Life satisfaction in Cantril Ladder (World Happiness Report 2017)']),
        'mode': 'markers',
        'text': [country], # since there is only one country we do not need to provide the list for text -  #Suggestion: No need to have this'marker': {
            'sizemode': 'area',
            'sizeref': 200000,
            'size': list(dataset_by_year_and_cont['Total population (Gapminder)'])
        },
        'name': country
    }
    figure['data'].append(data_dict)

# make framesfor year in years:
    frame = {'data': [], 'name': str(year)}
    dataset_by_year = dataset[dataset['year'] == int(year)] # here this has been moved because if the country # is not present for that particular year there is no need to plot those tracesfor country in dataset_by_year['country']:

        dataset_by_year_and_cont=dataset_by_year[dataset_by_year['country'] == country]

        data_dict = {
            'x': list(dataset_by_year_and_cont['GDP per capita']),
            'y': list(dataset_by_year_and_cont['Life satisfaction in Cantril Ladder (World Happiness Report 2017)']),
            'mode': 'markers',
            'text': [country], # since there is only one country we do not need to provide the list for text - #Suggestion: No need to have this'marker': {
                'sizemode': 'area',
                'sizeref': 200000,
                'size': list(dataset_by_year_and_cont['Total population (Gapminder)'])
            },
            'name': country,
            'type': 'scatter',
            'showlegend': True
        }
        frame['data'].append(data_dict)

    figure['frames'].append(frame) #this block was indented and should not have been.
    slider_step = {'args': [
        [year],
        {'frame': {'duration': 300, 'redraw': False},
         'mode': 'immediate',
       'transition': {'duration': 300}}
     ],
     'label': year,
     'method': 'animate'}
    sliders_dict['steps'].append(slider_step)


figure['layout']['sliders'] = [sliders_dict]

iplot(figure, config=config)

Output: