Question

到目前为止，我已经尝试过：

import pandas as pd
import plotly.graph_objects as go

df = pd.read_csv('https://raw.githubusercontent.com/vyaduvanshi/helper-files/master/parallel_coordinates.csv')

dimensions = list([dict(range=[df['gm_Retail & Recreation'].min(),df['gm_Retail & Recreation'].max()],
                        label='Retail & Recreation', values=df['gm_Retail & Recreation']),
                  dict(range=[df['gm_Grocery & Pharmacy'].min(),df['gm_Grocery & Pharmacy'].max()],
                       label='Grocery & Pharmacy', values=df['gm_Grocery & Pharmacy']),
                  dict(range=[df['gm_Parks'].min(),df['gm_Parks'].max()],
                       label='Parks', values=df['gm_Parks']),
                  dict(range=[df['gm_Transit Stations'].min(),df['gm_Transit Stations'].max()],
                       label='Transit Stations', values=df['gm_Transit Stations']),
                  dict(range=[df['gm_Workplaces'].min(),df['gm_Workplaces'].max()],
                       label='Workplaces', values=df['gm_Workplaces']),
                  dict(range=[df['gm_Residential'].min(),df['gm_Residential'].max()],
                       label='Residential', values=df['gm_Residential']),])
#                   dict(range=[0,len(df)], values=df['country'],
#                       label='Country')])

fig = go.Figure(data=go.Parcoords(line = dict(color = '#ff0000',
                   colorscale = 'Electric',
                   showscale = True,
                   cmin = -4000,
                   cmax = -100), dimensions=dimensions))
fig.show()

它返回此：

json_serializable

我想要做的是将这些行分配给最后一列，即country列（类别）。（我的尝试在代码段中已注释掉）。我正在尝试思考如何将这些价值观与分类国家联系起来。索引可能是一种方法？我还想按国家/地区对行进行颜色编码，因此我猜想可以找到不同颜色的列表。我陷入困境，可以寻求帮助。

Answer 1

在您的情况下，您可以通过使虚拟变量代表df['country]中的每个唯一元素来实现此目的，此处具有长格式的数据集，因此您将获得重复的虚拟变量。但是不用担心，下面的代码将为您解决这些问题。然后，您可以将最后一个尺寸指定为：

dict(range=[0,df['dummy'].max()],
                   tickvals = dfg['dummy'], ticktext = dfg['country'],
                   label='Country', values=df['dummy']),

最后使用以下方法为线条分配颜色范围：

line = dict(color = df['dummy'],
                   colorscale = [[0,'rgba(200,0,0,0.1)'],[0.5,'rgba(0,200,0,0.1)'],[1,'rgba(0,0,200,0.1)']])

情节：

完整代码：

import pandas as pd
import plotly.graph_objects as go

df = pd.read_csv('https://raw.githubusercontent.com/vyaduvanshi/helper-files/master/parallel_coordinates.csv')
group_vars = df['country'].unique()
dfg = pd.DataFrame({'country':df['country'].unique()})
dfg['dummy'] = dfg.index
df = pd.merge(df, dfg, on = 'country', how='left')


dimensions = list([dict(range=[df['gm_Retail & Recreation'].min(),df['gm_Retail & Recreation'].max()],
                        label='Retail & Recreation', values=df['gm_Retail & Recreation']),
                  dict(range=[df['gm_Grocery & Pharmacy'].min(),df['gm_Grocery & Pharmacy'].max()],
                       label='Grocery & Pharmacy', values=df['gm_Grocery & Pharmacy']),
                  dict(range=[df['gm_Parks'].min(),df['gm_Parks'].max()],
                       label='Parks', values=df['gm_Parks']),
                  dict(range=[df['gm_Transit Stations'].min(),df['gm_Transit Stations'].max()],
                       label='Transit Stations', values=df['gm_Transit Stations']),
                  dict(range=[df['gm_Workplaces'].min(),df['gm_Workplaces'].max()],
                       label='Workplaces', values=df['gm_Workplaces']),
                  dict(range=[df['gm_Residential'].min(),df['gm_Residential'].max()],
                       label='Residential', values=df['gm_Residential']),
                   
                  dict(range=[0,df['dummy'].max()],
                       tickvals = dfg['dummy'], ticktext = dfg['country'],
                       label='Country', values=df['dummy']),
                  
                  ])

fig = go.Figure(data=go.Parcoords(line = dict(color = df['dummy'],
                   colorscale = [[0,'rgba(200,0,0,0.1)'],[0.5,'rgba(0,200,0,0.1)'],[1,'rgba(0,0,200,0.1)']]), dimensions=dimensions))
fig.show()

Answer 2

使用 df.infer_objects() 自动推断每一列的数据类型。

情节：如何将类别变量插入平行坐标图？

2 个答案:

情节：

完整代码：