如何在 Plotly 中循环创建子图，每个子图上都有几条曲线？

Question

我已经在嵌套循环下面编写了成功生成 21 个图表（每个国家/地区一个图表，例如 german gasaustrian gas）

dfs 是一个以 21 个国家/地区名称为键，它们各自的气体存储 dfs 为值的字典

for country in list(dfs_storage.keys()):
    df_country=dfs_storage[country]
    month = list(set(df_country['month']))
    fig = go.Figure()
    for year in set(df_country['year']):
        workingGasVolume_peryear=df_country.loc[df_country['year']==year,'workingGasVolume']
        gasInStorage_peryear=df_country.loc[df_country['year']==year,'gasInStorage']
        # Create and style traces
        fig.add_trace(go.Scatter(x=month, y=workingGasVolume_peryear, name=f'workingGasVolume{year}',
                                 line=dict(width=4,dash='dash')))
        fig.add_trace(go.Scatter(x=month, y=gasInStorage_peryear, name=f'gasInStorage{year}',
                                 line = dict(width=4)))

    # Edit the layout
    fig.update_layout(title=f'{country} workingGasVolume gasInStorage',
                       xaxis_title='Month',
                       yaxis_title='Gas Volume')

    offline.plot({'data':fig},filename=f'{country} gas storage.html',auto_open=False)

现在我被要求将这 21 个图表放在一个 HTML 文件中而不更改每个图表，例如它们可以一个接一个垂直显示

我用下面的代码用 Plotly 尝试了“子图”，并修改了几次，但从来没有想要的图表，我得到了一个没有用的图表，我看不到任何值。有人可以帮助我吗？谢谢

countries=[]
for country in list(dfs_storage.keys()):
    countries.append(country)
fig = make_subplots(
    rows=len(list(dfs_storage.keys())),cols=1,
    subplot_titles=(countries))

for country in countries:
    df_country=dfs_storage[country]
    month = list(set(df_country['month']))
    for year in set(df_country['year']):
        workingGasVolume_peryear=df_country.loc[df_country['year']==year,'workingGasVolume']
        gasInStorage_peryear=df_country.loc[df_country['year']==year,'gasInStorage']
        # Create and style traces
        fig.add_trace(go.Scatter(x=month, y=workingGasVolume_peryear, name=f'workingGasVolume{year}',
                                 line=dict(width=4,dash='dash')))
        fig.add_trace(go.Scatter(x=month, y=gasInStorage_peryear, name=f'gasInStorage{year}',
                                 line = dict(width=4)))

    # Edit the layout
# fig.update_layout(title='workingGasVolume gasInStorage',
#                    xaxis_title='Month',
#                    yaxis_title='Gas Volume')

offline.plot({'data':fig},filename='gas storage.html',auto_open=False) 

6 月 7 日编辑：根据 jayveesea 的建议，我在 add_trace 下添加了 row 和 col 参数，代码如下但仍然有 Traceback：

countries=[]
for country in list(dfs_storage.keys()):
    countries.append(country)
fig = make_subplots(
    rows=len(list(dfs_storage.keys())),cols=1,
    subplot_titles=(countries))

for i in range(len(countries)):
    country=countries[i]
    df_country=dfs_storage[country]
    month = list(set(df_country['month']))
    for year in set(df_country['year']):
        workingGasVolume_peryear=df_country.loc[df_country['year']==year,'workingGasVolume']
        gasInStorage_peryear=df_country.loc[df_country['year']==year,'gasInStorage']
        # Create and style traces
        fig.add_trace(go.Scatter(x=month, y=workingGasVolume_peryear, name=f'workingGasVolume{year}',row=i,col=1,
                                 line=dict(width=4,dash='dash')))
        fig.add_trace(go.Scatter(x=month, y=gasInStorage_peryear, name=f'gasInStorage{year}',row=i,col=1,
                                 line = dict(width=4)))

    # Edit the layout
# fig.update_layout(title='workingGasVolume gasInStorage',
#                    xaxis_title='Month',
#                    yaxis_title='Gas Volume')

offline.plot({'data':fig},filename='gas storage.html',auto_open=False)

print('the Plotly charts are saved in the same folder as the Python code')

6 月 8 日编辑： 这是我现在正在运行的代码，从@jayveesea 的答案中复制而来，只修改了 df 的名称

countries=[]
for country in list(dfs_storage.keys()):
    countries.append(country)
# STEP 1
fig = make_subplots(
    rows=len(countries), cols=1,
    subplot_titles=(countries))

for i, country in enumerate(countries): #enumerate here to get access to i
    years = df_country.year[df_country.country==country].unique()
    for yrs in years:
        focus = (df_country.country==country) & (df_country.year==yrs)
        month = df_country.month[focus]
        workingGasVolume_peryear = df_country.workingGasVolume[focus]
        gasInStorage_peryear = df_country.gasInStorage[focus]

        # STEP 2, notice position of arguments!
        fig.add_trace(go.Scatter(x=month, 
                                 y=workingGasVolume_peryear, 
                                 name=f'workingGasVolume{yrs}',
                                 line=dict(width=4,dash='dash')),
                      row=i+1, #index for the subplot, i+1 because plotly starts with 1
                      col=1)
        fig.add_trace(go.Scatter(x=month, 
                                 y=gasInStorage_peryear, 
                                 name=f'gasInStorage{yrs}',
                                 line = dict(width=4)),
                      row=i+1,
                      col=1)      
fig.show()

但我仍然有 Traceback 消息

Traceback (most recent call last):

  File "<ipython-input-27-513826172e49>", line 43, in <module>
    line=dict(width=4,dash='dash')),

TypeError: 'dict' object is not callable

Answer 1

要在 plotly 中使用子图，您需要：

1. 使用make_subplots 来初始化指定row 和column 的布局
2. 然后使用row 和col 作为fig.add_trace 的参数。注意：子图行和列从 1（非零）开始

在您的情况下，第 2 步是您卡住的地方。最初这部分缺失（第一篇文章），但现在在您的更新中，它作为参数添加到 go.Scatter。仔细查看the examples here，因为区别只是逗号和括号以及它们的位置。

澄清一下：

fig.add_trace(go.Scatter(x=month, 
                         y=workingGasVolume_peryear, 
                         name=f'workingGasVolume{year}',
                         row=i,
                         col=1,
                         line=dict(width=4,dash='dash')))

应该是：

fig.add_trace(go.Scatter(x=month, 
                         y=workingGasVolume_peryear, 
                         name=f'workingGasVolume{year}',
                         line=dict(width=4,dash='dash')),
              row=i+1,
              col=1)

我在处理您的代码和数据时遇到了困难，这可能是因为我不使用这样的字典，但这是一个工作示例，您的数据在 csv 中并使用 pandas。另外，我把其中一年换到了另一个国家，这样会有另一个情节。

import pandas as pd
import plotly.graph_objects as go  
from plotly.subplots import make_subplots

df = pd.read_csv('someData.csv')
countries = df.country.unique()

# STEP 1
fig = make_subplots(
    rows=len(countries), cols=1,
    subplot_titles=(countries))

for i, country in enumerate(countries): #enumerate here to get access to i
    years = df.year[df.country==country].unique()
    for yrs in years:
        focus = (df.country==country) & (df.year==yrs)
        month = df.month[focus]
        workingGasVolume_peryear = df.workingGasVolume[focus]
        gasInStorage_peryear = df.gasInStorage[focus]

        # STEP 2, notice position of arguments!
        fig.add_trace(go.Scatter(x=month, 
                                 y=workingGasVolume_peryear, 
                                 name=f'workingGasVolume{yrs}',
                                 line=dict(width=4,dash='dash')
                                ),
                      row=i+1, #index for the subplot, i+1 because plotly starts with 1
                      col=1)
        fig.add_trace(go.Scatter(x=month, 
                                 y=gasInStorage_peryear, 
                                 name=f'gasInStorage{yrs}',
                                 line = dict(width=4)),
                      row=i+1,
                      col=1)      
fig.show()