如何在plotly和python中使用make_subplot繪制多個圖表

Question

我正在嘗試使用plotly和make_subplot繪制多個圖表，我想在其中繪制使用迭代 for 循環創建的 5 個餅圖。 和 1 個條形圖，條形圖將采用colspan = 2

數據框示例：

eventtype_name    date    eventmohafaza_name   number       groups
watch movie     8/14/2020   loc1                 25         group1
stay at home    8/13/2020   loc2                 20         group2
swimming        8/13/2020   loc2                 25         group4
camping         8/13/2020   loc3                 20         group3
meeting         8/13/2020   loc4                 40         group5
meeting         8/13/2020   loc5                 20         group2
watch movie     8/14/2020   loc4                 25         group1
stay at home    8/13/2020   loc1                 20         group2
swimming        8/13/2020   loc5                 25         group4
camping         8/13/2020   loc4                 20         group3
meeting         8/13/2020   loc3                 30         group5
meeting         8/13/2020   loc5                 33         group2

問題在於當我分配行和列並嘗試使用規范參數時，系統崩潰並顯示以下錯誤。

This is the format of your plot grid:
[ (1,1)     ]  [ (1,2)     ]  [ (1,3)     ]
[ (2,1)     ]  [ (2,2)     ]  [ (2,3)     ]
[ (3,1)     ]  [ (3,2) x,y           -    ]

---------------------------------------------------------------------------
IndexError                                Traceback (most recent call last)
f:\aienv\lib\site-packages\plotly\subplots.py in _set_trace_grid_reference(trace, layout, grid_ref, row, col, secondary_y)
   1318     try:
-> 1319         subplot_refs = grid_ref[row - 1][col - 1]
   1320     except IndexError:

IndexError: list index out of range

During handling of the above exception, another exception occurred:

Exception                                 Traceback (most recent call last)
<ipython-input-108-831d326e87b8> in <module>
     59                          rotation=90),
     60      row=row,
---> 61      col=col
     62     )
     63 

f:\aienv\lib\site-packages\plotly\basedatatypes.py in add_trace(self, trace, row, col, secondary_y)
   1650             rows=[row] if row is not None else None,
   1651             cols=[col] if col is not None else None,
-> 1652             secondary_ys=[secondary_y] if secondary_y is not None else None,
   1653         )
   1654 

f:\aienv\lib\site-packages\plotly\basedatatypes.py in add_traces(self, data, rows, cols, secondary_ys)
   1764         if rows is not None:
   1765             for trace, row, col, secondary_y in zip(data, rows, cols, secondary_ys):
-> 1766                 self._set_trace_grid_position(trace, row, col, secondary_y)
   1767 
   1768         # Make deep copy of trace data (Optimize later if needed)

f:\aienv\lib\site-packages\plotly\basedatatypes.py in _set_trace_grid_position(self, trace, row, col, secondary_y)
   1847         grid_ref = self._validate_get_grid_ref()
   1848         return _set_trace_grid_reference(
-> 1849             trace, self.layout, grid_ref, row, col, secondary_y
   1850         )
   1851 

f:\aienv\lib\site-packages\plotly\subplots.py in _set_trace_grid_reference(trace, layout, grid_ref, row, col, secondary_y)
   1320     except IndexError:
   1321         raise Exception(
-> 1322             "The (row, col) pair sent is out of "
   1323             "range. Use Figure.print_grid to view the "
   1324             "subplot grid. "

Exception: The (row, col) pair sent is out of range. Use Figure.print_grid to view the subplot grid. 

代碼：

import plotly.graph_objs as go
from plotly.subplots import make_subplots
import plotly.express as px
import pandas as pd



df = pd.read_excel(file)
lst = list(df.groupby('eventmohafaza_name'))


rows = 3
cols = 3

subplot_titles = [l[0] for l in lst]


specs=[
           [{"type": "pie"},{"type": "pie"},{"type": "pie"}],
           [{"type": "pie"},{"type": "pie"},{"type": "pie"}],
           [{"type": "pie"},{"type": "bar",'colspan':2},None],
      ]

    
fig = make_subplots(
        rows=rows,
        cols=cols,
        subplot_titles=subplot_titles,
        specs=specs,
        
        print_grid=True
)

for i, l in enumerate(lst):
    row = i // cols + 1
    col = i % (rows + 1) + 1
    d = l[1]
   
    fig.add_trace(go.Pie(labels=d["eventtype_name"],
                         values = d["number"],
                         hovertemplate = "%{label}: <br>Value: %{value} ",
                         showlegend=True,
                         textposition='inside',
                         rotation=90),
     row=row,
     col=col    
    )
    
group_event_groups = df.groupby([df['eventmohafaza_name'],df['eventtype_name']]).size().unstack()    
for x in group_event_groups.columns: 
    fig.add_trace(go.Bar(name=str(x), x=group_event_groups.index, y=group_event_groups[x],showlegend=False), row=3, col=2)
    
fig.update_layout(height = 1000,
                  width = 900,
                  autosize = False,
                  title="Population by Continent", 
                  title_x=0.5)
fig.show()

預期結果是 5 個餅圖和 1 個條形圖

Answer 1

樣例數據增加了新的屬性數據，修改了行和列的計算邏輯。 此外，最后一個條形圖現在是單個圖，因為圖的數量與循環數據不匹配。

lst = list(df.groupby('eventmohafaza_name'))

rows = 3
cols = 3

subplot_titles = [l[0] for l in lst]

specs=[[{"type": "pie"},{"type": "pie"},{"type": "pie"}],
       [{"type": "pie"},{"type": "pie"},{"type": "pie"}],
       [{"type": "pie"},{"type": "bar",'colspan':2},None]]

fig = make_subplots(
        rows=rows,
        cols=cols,
        subplot_titles=subplot_titles,
        specs=specs,  
        print_grid=True
)

for i, l in enumerate(lst):
    row = i // cols + 1
    col = (i % rows) + 1
    d = l[1]
    fig.add_trace(go.Pie(labels=d["eventtype_name"],
                         values = d["number"],
                         hovertemplate = "%{label}: <br>Value: %{value} ",
                         showlegend=True,
                         textposition='inside',
                         rotation=90),
     row=row,
     col=col    
    )
    
group_event_groups = df.groupby([df['eventmohafaza_name'],df['eventtype_name']]).size().unstack()    
# for x in group_event_groups.columns: 
fig.add_trace(go.Bar(name='camping', x=group_event_groups.index, y=group_event_groups.columns, showlegend=False), row=3, col=2)
    
fig.update_layout(height = 1000,
                  width = 900,
                  autosize = False,
                  title="Population by Continent", 
                  title_x=0.5)
fig.show()