绘图错误:参数'figure_or_data'无效



本 plotly 教程中的动画示例不适用于 Plotly 2.0.12。我将错误输出放在下面。有什么办法可以解决这个问题吗?我正在Jupyter笔记本上使用plotly。

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']

编辑:刚刚注意到链接已断开。以下是完整的代码:

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)

我不知道我是否必须降级版本(以及,以防万一,降级到哪个版本(,但我宁愿不降级。

我验证了您的代码并发现了一些错误。

  1. 在第 29 行你应该给

figure['layout']['sliders']而不是figure['layout']['slider']

  1. Plotly 离线的 iplot 函数有一个单独的参数来输入绘图的配置。

所以下面的一行

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

和线

iplot(figure)

实际上应该写成

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

iplot(figure, config=config)

所以最终的工作代码应该是

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)

我希望这可以帮助您解决问题,滑块看起来很棒:)

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