Question

我正在使用情节性离线Python 。我有一个 csv.dateset ，其中包括大学排名，其中包括许多大学的引文和教学排名。我想在一个数字中比较这两个因素，并且我使用了 plotly offline ，但是我遇到了一些无法解决的问题，任何人都可以帮助解决这个问题？

我的代码是这样的：

timesData = pd.read_csv('D:/Python/world_university_rankin/timesData.csv' ,encoding='utf-8')
edf=timesData.iloc[:100,:]
from plotly.offline import download_plotlyjs, init_notebook_mode, plot, ip`lot
import plotly.graph_objs as go
from plotly.plotly import iplot




plotly.offline.init_notebook_mode(connected=True)

# Creating trace1

#plotly.offline.iplot({
  #  "data": [go.Scatter(x=[1, 2, 3, 4], y=[4, 3, 2, 1])],
   # "layout": go.Layout(title="hello world")})
trace1 =plotly.offline.iplot([go.Scatter(
                    x = df.world_rank,
                    y = df.citations,
                    mode = "lines",
                    name = "citations",
                    marker = dict(color = 'rgba(16, 112, 2, 0.8)'),
                    text= df.university_name)])
# Creating trace2
trace2 = plotly.offline.iplot([go.Scatter(
                    x = df.world_rank,
                    y = df.teaching,
                    mode = "lines+markers",
                    name = "teaching",
                    marker = dict(color = 'rgba(80, 26, 80, 0.8)'),
                    text= df.university_name)])
data = [trace1, trace2]
layout = plotly.offline.iplot( [go.Layout( dict(title = 'Citation and Teaching vs World Rank of Top 100 Universities',
              xaxis= dict(title= 'World Rank',ticklen= 5,zeroline= False)))])



fig = plotly.offline.iplot( [dict(data = data, layout = layout)])

py.iplot(fig)

然后面临的问题是这个

ValueError                                Traceback (most recent call last)
<ipython-input-71-f5bacdda2f25> in <module>()
     28 data = [trace1, trace2]
     29 layout = plotly.offline.iplot( [go.Layout( dict(title = 'Citation and Teaching vs World Rank of Top 100 Universities',
---> 30               xaxis= dict(title= 'World Rank',ticklen= 5,zeroline= False)))])
     31 
     32 

C:\ProgramData\Anaconda3\lib\site-packages\plotly\offline\offline.py in iplot(figure_or_data, show_link, link_text, validate, image, filename, image_width, image_height, config)
    440     jconfig = _get_jconfig(config)
    441 
--> 442     figure = tools.return_figure_from_figure_or_data(figure_or_data, validate)
    443 
    444     # Though it can add quite a bit to the display-bundle size, we include

C:\ProgramData\Anaconda3\lib\site-packages\plotly\tools.py in return_figure_from_figure_or_data(figure_or_data, validate_figure)
   1506 
   1507         try:
-> 1508             figure = Figure(**figure).to_dict()
   1509         except exceptions.PlotlyError as err:
   1510             raise exceptions.PlotlyError("Invalid 'figure_or_data' argument. "

C:\ProgramData\Anaconda3\lib\site-packages\plotly\graph_objs\_figure.py in __init__(self, data, layout, frames, skip_invalid)
    409             is invalid AND skip_invalid is False
    410         """
--> 411         super(Figure, self).__init__(data, layout, frames, skip_invalid)
    412 
    413     def add_area(

C:\ProgramData\Anaconda3\lib\site-packages\plotly\basedatatypes.py in __init__(self, data, layout_plotly, frames, skip_invalid)
    139         # ### Import traces ###
    140         data = self._data_validator.validate_coerce(data,
--> 141                                                     skip_invalid=skip_invalid)
    142 
    143         # ### Save tuple of trace objects ###

C:\ProgramData\Anaconda3\lib\site-packages\_plotly_utils\basevalidators.py in validate_coerce(self, v, skip_invalid)
   2292 
   2293             if invalid_els:
-> 2294                 self.raise_invalid_elements(invalid_els)
   2295 
   2296             v = to_scalar_or_list(res)

C:\ProgramData\Anaconda3\lib\site-packages\_plotly_utils\basevalidators.py in raise_invalid_elements(self, invalid_els)
    264                 pname=self.parent_name,
    265                 invalid=invalid_els[:10],
--> 266                 valid_clr_desc=self.description()))
    267 
    268     def validate_coerce(self, v):

ValueError: 
    Invalid element(s) received for the 'data' property of 
        Invalid elements include: [Layout({
    'title': 'Citation and Teaching vs World Rank of Top 100 Universities',
    'xaxis': {'ticklen': 5, 'title': 'World Rank', 'zeroline': False}
})]

    The 'data' property is a tuple of trace instances
    that may be specified as:
      - A list or tuple of trace instances
        (e.g. [Scatter(...), Bar(...)])
      - A list or tuple of dicts of string/value properties where:
        - The 'type' property specifies the trace type
            One of: ['area', 'bar', 'barpolar', 'box',
                     'candlestick', 'carpet', 'choropleth', 'cone',
                     'contour', 'contourcarpet', 'heatmap',
                     'heatmapgl', 'histogram', 'histogram2d',
                     'histogram2dcontour', 'mesh3d', 'ohlc',
                     'parcats', 'parcoords', 'pie', 'pointcloud',
                     'sankey', 'scatter', 'scatter3d',
                     'scattercarpet', 'scattergeo', 'scattergl',
                     'scattermapbox', 'scatterpolar',
                     'scatterpolargl', 'scatterternary', 'splom',
                     'streamtube', 'surface', 'table', 'violin']

        - All remaining properties are passed to the constructor of
          the specified trace type

        (e.g. [{'type': 'scatter', ...}, {'type': 'bar, ...}])

数据链接在这里：https://www.kaggle.com/kanncaa1/plotly-tutorial-for-beginners/data

Answer 1

Yout回溯告诉您data变量中包含无效元素，因此在使用skip_invalid = True时尝试添加参数go.Layout：

只需替代

layout = plotly.offline.iplot( [go.Layout( dict(title = 'Citation and Teaching vs World Rank of Top 100 Universities',
              xaxis= dict(title= 'World Rank',ticklen= 5,zeroline= False)))])

使用

layout = plotly.offline.iplot( [go.Layout( dict(title = 'Citation and Teaching vsWorld Rank of Top 100 Universities', xaxis= dict(title= 'World Rank',ticklen= 5,zeroline= False) ), skip_invalid = True)])

在Python上使用plotly方法：离线散布方法可同时比较同一图中的两个因子

然后面临的问题是这个

1 个答案: