如何在Plotly中循环创建子图，每个子图上有几条曲线？

Question

我已经写了下面的嵌套循环，成功地生成了21个图表（每个国家一个图表，例如 德国燃气 澳气)

dfs是一个以21个国家名称为键，以各自的天然气储存dfs为值的dict。

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，我被要求把这21个图表放在一个HTML文件中，而不改变每个图表，它们可以一个接一个地垂直出现，例如

我尝试用Plotly的 "子图 "与下面的代码和修改几次，但从来没有得到所需的图表，我得到一个单一的无用的图表，我看不到任何值...... 谁能帮帮我？有谁能帮帮我？

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：按照jayveesea的建议，我在add_trace下添加了row和col参数，代码如下，但还是有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: 这是我现在运行的代码 从@jayveesea的回答中复制过来的 只修改了df的名字。

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()

但我还是有回溯信息

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，你需要。

1. 使用 make_subplots 来初始化布局，并指定 row 和 column
2. 然后用 row 和 col 以此作为 fig.add_trace. 注：子图的行和列从 1 开始（不是零）。

在你的情况下，步骤2是你被卡住的地方。 最初这个部分是缺失的(第一篇文章)，但现在在你的更新中，它作为一个参数被添加到了 go.Scatter. 仔细看看 这里的例子 因为不同的只是逗号和括号及其位置。

澄清一下，这个。

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)

我对你的代码和数据有困难，这可能是我的问题，因为我没有使用这样的字典，但这里有一个工作的例子，你的数据在一个csv中，并使用 pandas. 另外，我把其中一个年份改成了不同的国家，这样就有了另一个情节。

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()