[英]Add a line with its proper scale on an area chart with Plotly
I have the following code:我有以下代码:
import pandas as pd
import plotly.express as px
fig = px.area(df, x="Decade", y="Financial_Impact", color="Disaster_Type", title="Financial Impact, World, RCP = 2.6", color_discrete_sequence=["#FDB714", "#009CA7", "#F05023"])
fig.show()
Generating the following area chart:生成以下面积图:
Now I have a variable called C
providing a temperature (°C) for each decade.现在我有一个名为C
的变量,为每十年提供一个温度 (°C)。 How could I add a line showing C
, with a scale relative to C
on the right of the chart?如何添加一条显示C
的线,其比例相对于图表右侧的C
?
Here are the first five rows of the dataset:以下是数据集的前五行:
df.head()
import plotly.express as px
from plotly.subplots import make_subplots
subfig = make_subplots(specs=[[{"secondary_y": True}]])
fig = px.area(df, x="Decade", y="Financial_Impact", color="Disaster_Type", color_discrete_sequence=["#FDB714", "#009CA7", "#F05023"])
fig2 = px.line(df, x="Decade",y=df.C)
fig2.update_traces(yaxis="y2",showlegend=True,name='Temperature')
subfig.add_traces(fig.data + fig2.data)
subfig.layout.xaxis.title="Decades"
subfig.layout.yaxis.title="Financial Impact"
subfig.layout.yaxis2.title="°C"
subfig.layout.title="Financial Impact, World, RCP = 2.6"
subfig.show()
You will want to use graph_objects
instead of Plotly express, add your data as traces using go.Scatter
and the stackgroup
parameter to create overlapping area plots, and create a secondary y-axis.您将需要使用graph_objects
而不是 Plotly express,使用go.Scatter
和stackgroup
参数将数据添加为轨迹,以创建重叠区域图,并创建辅助 y 轴。 You can specify the secondary y-axis for your temperature data.您可以为温度数据指定辅助 y 轴。 I'll create a similar DataFrame as yours to illustrate my point.我将创建一个与您类似的 DataFrame 来说明我的观点。
import numpy as np
import pandas as pd
from plotly.subplots import make_subplots
import plotly.graph_objects as go
np.random.seed(42)
storm_data = np.repeat(3.5*10**9,21) + 10**8*np.random.normal(0,1,21)
flood_data = np.repeat(2*10**9,21) + 10**8*np.random.normal(0,1,21)
drought_data = np.repeat(1.4*10**9,21) + 10**8*np.random.normal(0,1,21)
df = pd.DataFrame({
'Decade':np.linspace(1900,2100,21),
'Storms':storm_data,
'Floods':flood_data,
'Droughts':drought_data,
'Temperature':np.random.normal(30,10,21)
})
## create a secondary y-axis
fig = make_subplots(specs=[[{"secondary_y": True}]])
## add your data using traces
fig.add_trace(go.Scatter(
x=df.Decade,
y=df.Storms,
name='Storms',
stackgroup='one'
))
fig.add_trace(go.Scatter(
x=df.Decade,
y=df.Floods,
name='Floods',
stackgroup='one'
))
fig.add_trace(go.Scatter(
x=df.Decade,
y=df.Droughts,
name='Droughts',
stackgroup='one'
))
## specify the secondary y_axis for temperature
fig.add_trace(go.Scatter(
x=df.Decade,
y=df.Temperature,
name='Temperature',
),
secondary_y=True
)
fig.show()
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