Plotly与Pandas数据框在Jupyter笔记本中并排显示

huangapple go评论69阅读模式
英文:

Plotly with Pandas dataframe side by side in Jupyter notebook

问题

以下是翻译好的部分:

有关如何在Jupyter笔记本中并排创建两个Plotly图表的问题或如何在Jupyter笔记本中并排显示两个Pandas数据框的问题,有一些问题。但我想在Jupyter笔记本中将一个Plotly图与一个Pandas数据框并排显示。以下是一些用于图表和Pandas数据框的可重现代码:

import pandas as pd
import plotly.express as px

df = px.data.iris() 
fig = px.scatter(df, x="sepal_width", y="sepal_length")
fig.show()

# 简单的Pandas数据框
df[["sepal_length", "species"]].groupby("species").agg(['mean', 'count', 'median', 'min', 'max'])

输出:

Plotly与Pandas数据框在Jupyter笔记本中并排显示

现在输出是垂直排列的,但我想要它们并排显示。所以我想知道是否有人知道如何在Pandas数据框旁边并排显示一个Plotly图表?

英文:

There are some questions about how to create two plotly graphs side-by-side in Jupyter notebook or how to show two pandas dataframes side by side. But I would like to display a plotly graph with a pandas dataframe side by side in a Jupyter notebook. Here is some reproducible code for the graph and pandas dataframe:

import pandas as pd
import plotly.express as px

df = px.data.iris() 
fig = px.scatter(df, x="sepal_width", y="sepal_length")
fig.show()

# Simple pandas dataframe
df[["sepal_length", "species"]].groupby("species").agg(['mean', 'count', 'median', 'min', 'max'])

Output:

Plotly与Pandas数据框在Jupyter笔记本中并排显示

Now the output is below each other, but I would like to have them side by side. So I was wondering if anyone knows how to show a plotly graph side by side with a pandas dataframe?

答案1

得分: 3

你可以创建一个子图,并将表格视图放在第二列。这个示例应该可以运行:

import plotly.express as px
import plotly.graph_objects as go
from plotly.subplots import make_subplots

df = px.data.iris()

specs = [
    [{"type": "xy"}, {"type": "table"}]
]

fig = make_subplots(
    rows=1, 
    cols=2, 
    specs=specs, 
    subplot_titles=[
        "散点图", 
        "数据表格"
    ]
)
fig.add_trace(go.Scatter(
    x=df.index,
    y=df["petal_length"].values
),
row=1, col=1)

fig.add_trace(go.Table(
    header={"values": df.columns},
    cells={"values": (
        df
        .transpose()
        .values
        .tolist())}
),
row=1, col=2)
fig.update_layout(template="plotly_dark")
fig.show()

生成如下图所示:
Plotly与Pandas数据框在Jupyter笔记本中并排显示

英文:

You can make a subplot and place the table view on the second column. This example should run:

import plotly.express as px
import plotly.graph_objects as go
from plotly.subplots import make_subplots

df = px.data.iris()

specs = [
    [{"type": "xy"}, {"type": "table"}]
]

fig = make_subplots(
    rows=1, 
    cols=2, 
    specs=specs, 
    subplot_titles=[
        "A Scatter Plot", 
        "A DataFrame"
    ]
)
fig.add_trace(go.Scatter(
    x=df.index,
    y=df["petal_length"].values
),
row=1, col=1)

fig.add_trace(go.Table(
    header={"values": df.columns},
    cells={"values": (
        df
        .transpose()
        .values
        .tolist()}
    )
),
row=1, col=2)
fig.update_layout(template="plotly_dark")
fig.show()

Produces this:
Plotly与Pandas数据框在Jupyter笔记本中并排显示

答案2

得分: 0

我认为这里的原始帖子发布了一个更新的答案,使用make_subplots()来实现你正在寻找的功能:

https://stackoverflow.com/q/71296687/8508004

它做得比你需要的要多;但是,你应该能够根据你的代码进行修改以去掉多余的部分,并集成到你的代码中。

英文:

I think the original poster here posted an updated answer that does what you are looking for using make_subplots():

https://stackoverflow.com/q/71296687/8508004

It does more than you need; however, you should be able to adapt it to remove that and build in your code.

huangapple
  • 本文由 发表于 2023年7月3日 20:11:04
  • 转载请务必保留本文链接:https://go.coder-hub.com/76604620.html
匿名

发表评论

匿名网友

:?: :razz: :sad: :evil: :!: :smile: :oops: :grin: :eek: :shock: :???: :cool: :lol: :mad: :twisted: :roll: :wink: :idea: :arrow: :neutral: :cry: :mrgreen:

确定