Plotly 动画气泡图：图中没有数据
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【中文标题】Plotly 动画气泡图：图中没有数据【英文标题】：Plotly animated bubble chart: no data in the plot 【发布时间】：2018-01-24 11:52:21 【问题描述】：我正在尝试将标准绘图动画气泡图调整为包含这些列的 csv 文件：
index,country,year,Country code,Total population (Gapminder),Life satisfaction in Cantril Ladder (World Happiness Report 2017),GDP per capita
62,Afghanistan,2008,AFG,29839994.0,3.723589897,1298.14315888
63,Afghanistan,2009,AFG,30577756.0,4.401778221,1531.17399272
64,Afghanistan,2010,AFG,31411743.0,4.75838089,1614.25500126
65,Afghanistan,2011,AFG,32358260.0,3.83171916,1660.73985618
66,Afghanistan,2012,AFG,33397058.0,3.782937527,1839.27357928
67,Afghanistan,2013,AFG,34499915.0,3.572100401,1814.15582533
167,Albania,2007,ALB,3169665.0,4.634251595,8447.88228539
169,Albania,2009,ALB,3192723.0,5.485469818,9524.60981095
170,Albania,2010,ALB,3204284.0,5.268936634,9927.13514733
171,Albania,2011,ALB,3215988.0,5.867421627,10207.7006745
172,Albania,2012,ALB,3227373.0,5.510124207,10369.7616592
173,Albania,2013,ALB,3238316.0,4.550647736,10504.0930888
242,Algeria,2010,DZA,35468208.0,5.46356678,12870.2162376
243,Algeria,2011,DZA,35980193.0,5.317194462,12989.9549601
244,Algeria,2012,DZA,36485828.0,5.604595661,13161.566464
451,Angola,2011,AGO,19618432.0,5.589000702,5911.25433387
452,Angola,2012,AGO,20162517.0,4.360249996,5998.63860099
453,Angola,2013,AGO,20714494.0,3.937106848,6185.0138292
数据点的大小将是人口的函数，我会将生活满意度绘制为国家 GDP 的函数。我在数据集上做了一些工作：
gdp=pd.read_csv('gdp-vs-happiness.csv')
gdp=gdp.ix[~(gdp['year'] < 2005)]
gdp=gdp.dropna()
dataset = gdp
然后是代码：
years = ['2005','2006', '2007','2008','2009','2010','2011','2012','2013','2014','2015','2016']
# make list of continents
countries = []
for country in dataset['country']:
countries.append(country)
# make figure
figure =
'data': [],
'layout': ,
'frames': []
config = 'scrollzoom': True
# fill in most of layout
figure['layout']['xaxis'] = 'title': 'GDP per Capita', 'type': 'log'
figure['layout']['yaxis'] = 'range': [0, 10], 'title': 'Life Satisfaction'
figure['layout']['hovermode'] = 'closest'
figure['layout']['sliders'] =
'args': [
'slider.value',
'duration': 400,
'ease': 'cubic-in-out'
],
'initialValue': '2005',
'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 = 2005
for country in countries:
dataset_by_year = dataset[dataset['year'] == year]
dataset_by_year_and_count = dataset_by_year[dataset_by_year['country'] == country]
data_dict =
'x': list(dataset_by_year_and_count['GDP per capita']),
'y': list(dataset_by_year_and_count['Life satisfaction in Cantril Ladder (World Happiness Report 2017)']),
'mode': 'markers',
'text': list(dataset_by_year_and_count['country']),
'marker':
'sizemode': 'area',
'sizeref': 200000,
'size': list(dataset_by_year_and_count['Total population (Gapminder)'])
,
'name': country
figure['data'].append(data_dict)
# make frames
for year in years:
frame = 'data': [], 'name': str(year)
for country in countries:
dataset_by_year = dataset[dataset['year'] == int(year)]
dataset_by_year_and_cont = dataset_by_year[dataset_by_year['country'] == country]
data_dict =
'x': list(dataset_by_year_and_count['GDP per capita']),
'y': list(dataset_by_year_and_count['Life satisfaction in Cantril Ladder (World Happiness Report 2017)']),
'mode': 'markers',
'text': list(dataset_by_year_and_count['country']),
'marker':
'sizemode': 'area',
'sizeref': 200000,
'size': list(dataset_by_year_and_count['Total population (Gapminder)'])
,
'name': country
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)
这里的问题是我得到一个空图（滑块、布局、轴标签动画正在工作），根本没有数据，也没有引发错误。所以老实说，我不知道问题出在哪里。这显然与脚本中的数据构建有关，但我不知道具体是什么。
【问题讨论】：
您能否在数据集中为每年提供 2 行的模型数据框，df = pd.DataFrame('county': ['Cochice', 'Pima', 'Santa Cruz', 'Maricopa', 'Yuma'], 'year': [2012, 2012, 2013, 2014, 2014], 'reports': [4, 24, 31, 2, 3])，请参考示例，但将一些示例数据和列与您的文件相同并将其添加到问题中
我刚刚编辑了这个问题，谢谢。通过查看该文件，我认为这可能取决于并非每个国家/地区都有所有指定年份的数据这一事实，但我不知道情节如何处理这个问题，以及如何让它发挥作用（对于例如，如果该年没有可用数据，则使国家/地区数据点消失）。
事实上，如果我将起始年份更改为 2008 年，则会填充图例（每个国家/地区，它在数据集中出现的每一年 - 这是我稍后将处理的内容）并出现一个数据点在情节中：津巴布韦 2008 年的情节。它在整个动画中都没有改变。所以这肯定取决于读取数据的方式。
【参考方案1】：
我使用了您提供的示例数据并对其进行了处理，我遇到了一些问题并在每一行添加了我的 cmets，主要原因在 cmets 部分指出，但您可以交叉检查我的代码和您的代码得到你需要的东西
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 = '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 = 2007
for 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 frames
for 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 traces
for 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)
输出：
【讨论】：
非常感谢您的帮助。它有效，并且通过一些细微的调整它将是完美的。我正在研究你所做的每一个改变，以理清你做了什么以及为什么这样做。今天，您在攀登我的情节学习曲线方面帮助了我很多:) 非常感谢！ @sato 很高兴为您提供帮助，Plotly 是一个很棒的库，我们只需要通过 reference guide 并习惯参数 :)以上是关于Plotly 动画气泡图：图中没有数据的主要内容，如果未能解决你的问题，请参考以下文章