sato sato - 1 month ago 11
Python Question

Plotly error: Invalid 'figure_or_data' argument

an animation example from this plotly tutorial is not working with Plotly 2.0.12. I put the error output below. Is there any way to solve the problem? I am using plotly on a Jupyter Notebook.

PlotlyError: Invalid 'figure_or_data' argument. Plotly will not be
able to properly parse the resulting JSON. If you want to send this
'figure_or_data' to Plotly anyway (not recommended), you can set
'validate=False' as a plot option.
Here's why you're seeing this error:

'slider' is not allowed in 'layout'

Path To Error: ['layout']['slider']

Valid attributes for 'layout' at path ['layout'] under parents
['figure']:

['angularaxis', 'annotations', 'autosize', 'bargap', 'bargroupgap',
'barmode', 'barnorm', 'boxgap', 'boxgroupgap', 'boxmode', 'calendar',
'direction', 'dragmode', 'font', 'geo', 'height', 'hiddenlabels',
'hiddenlabelssrc', 'hidesources', 'hoverlabel', 'hovermode',
'images',
'legend', 'mapbox', 'margin', 'orientation', 'paper_bgcolor',
'plot_bgcolor', 'radialaxis', 'scene', 'separators', 'shapes',
'showlegend', 'sliders', 'smith', 'ternary', 'title', 'titlefont',
'updatemenus', 'width', 'xaxis', 'yaxis']

Run `<layout-object>.help('attribute')` on any of the above.
'<layout-object>' is the object at ['layout']


EDIT: Just noticed the link is broken. Here is the full 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 = 'https://raw.githubusercontent.com/plotly/datasets/master/gapminderDataFiveYear.csv'
dataset = pd.read_csv(url)

years = ['1952', '1962', '1967', '1972', '1977', '1982', '1987', '1992', '1997', '2002', '2007']
# make list of continents
continents = []
for continent in dataset['continent']:
if continent not in continents:
continents.append(continent)
# make figure
figure = {
'data': [],
'layout': {},
'frames': [],
'config': {'scrollzoom': True}
}

# fill in most of layout
figure['layout']['xaxis'] = {'range': [30, 85], 'title': 'Life Expectancy'}
figure['layout']['yaxis'] = {'title': 'GDP per Capita', 'type': 'log'}
figure['layout']['hovermode'] = 'closest'
figure['layout']['slider'] = {
'args': [
'slider.value', {
'duration': 400,
'ease': 'cubic-in-out'
}
],
'initialValue': '1952',
'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
year = 1952
for continent in continents:
dataset_by_year = dataset[dataset['year'] == year]
dataset_by_year_and_cont =
dataset_by_year[dataset_by_year['continent'] == continent]

data_dict = {
'x': list(dataset_by_year_and_cont['lifeExp']),
'y': list(dataset_by_year_and_cont['gdpPercap']),
'mode': 'markers',
'text': list(dataset_by_year_and_cont['country']),
'marker': {
'sizemode': 'area',
'sizeref': 200000,
'size': list(dataset_by_year_and_cont['pop'])
},
'name': continent
}
figure['data'].append(data_dict)

# make frames
for year in years:
frame = {'data': [], 'name': str(year)}
for continent in continents:
dataset_by_year = dataset[dataset['year'] == int(year)]
dataset_by_year_and_cont =
dataset_by_year[dataset_by_year['continent'] == continent]

data_dict = {
'x': list(dataset_by_year_and_cont['lifeExp']),
'y': list(dataset_by_year_and_cont['gdpPercap']),
'mode': 'markers',
'text': list(dataset_by_year_and_cont['country']),
'marker': {
'sizemode': 'area',
'sizeref': 200000,
'size': list(dataset_by_year_and_cont['pop'])
},
'name': continent
}
frame['data'].append(data_dict)

figure['frames'].append(frame)
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)


I do not know if I have to downgrade the version (and, in case, to which one) but I'd rather not.

Answer Source

I validated your code and found some errors.

  1. On Line 29 you should have given

figure['layout']['sliders'] instead of figure['layout']['slider']

  1. Plotly offline's iplot function has a separate parameter of inputting config of the plot.

So the below line

# make figure
figure = {
    'data': [],
    'layout': {},
    'frames': [],
    'config': {'scrollzoom': True}
}

and the line

iplot(figure)

should actually be written as

# make figure
figure = {
    'data': [],
    'layout': {},
    'frames': []
}
config = {'scrollzoom': True}

and

iplot(figure, config=config)

So the final working code should be

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

import pandas as pd

init_notebook_mode(connected=True)

url = 'https://raw.githubusercontent.com/plotly/datasets/master/gapminderDataFiveYear.csv'
dataset = pd.read_csv(url)

years = ['1952', '1962', '1967', '1972', '1977', '1982', '1987', '1992', '1997', '2002', '2007']
# make list of continents
continents = []
for continent in dataset['continent']:
    if continent not in continents:
        continents.append(continent)
# make figure
figure = {
    'data': [],
    'layout': {},
    'frames': []
}
config = {'scrollzoom': True}

# fill in most of layout
figure['layout']['xaxis'] = {'range': [30, 85], 'title': 'Life Expectancy'}
figure['layout']['yaxis'] = {'title': 'GDP per Capita', 'type': 'log'}
figure['layout']['hovermode'] = 'closest'
figure['layout']['sliders'] = {
    'args': [
        'slider.value', {
            'duration': 400,
            'ease': 'cubic-in-out'
        }
    ],
    'initialValue': '1952',
    '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 
year = 1952
for continent in continents:
    dataset_by_year = dataset[dataset['year'] == year]
    dataset_by_year_and_cont=dataset_by_year[dataset_by_year['continent'] == continent]

    data_dict = {
        'x': list(dataset_by_year_and_cont['lifeExp']),
        'y': list(dataset_by_year_and_cont['gdpPercap']),
        'mode': 'markers',
        'text': list(dataset_by_year_and_cont['country']),
        'marker': {
            'sizemode': 'area',
            'sizeref': 200000,
            'size': list(dataset_by_year_and_cont['pop'])
        },
        'name': continent
    }
    figure['data'].append(data_dict)

# make frames
for year in years:
    frame = {'data': [], 'name': str(year)}
    for continent in continents:
        dataset_by_year = dataset[dataset['year'] == int(year)]

        dataset_by_year_and_cont=dataset_by_year[dataset_by_year['continent'] == continent]

        data_dict = {
            'x': list(dataset_by_year_and_cont['lifeExp']),
            'y': list(dataset_by_year_and_cont['gdpPercap']),
            'mode': 'markers',
            'text': list(dataset_by_year_and_cont['country']),
            'marker': {
                'sizemode': 'area',
                'sizeref': 200000,
                'size': list(dataset_by_year_and_cont['pop'])
            },
            'name': continent
        }
        frame['data'].append(data_dict)

    figure['frames'].append(frame)
    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)

I hope this helps you resolve your issue, the slider looks great :)