如何在绘图中通过循环添加多个形状 [英] How to add more than one shape with loop in plotly

问题描述

我使用plotly包在python上显示动态财务图表.但是，我没有设法将所有关键点线放在带有for循环的一张图表上.这是我的代码:

  fig.update_layout(对于范围(0，len(data))中的i:形状= [go.layout.Shape(输入="rect"，x0 = data ['Date'] [i]，y0 = data ['Max_alt'] [i]，x1 ='2019-12-31'，y1 = data ['Max_ust'] [i]，fillcolor ="LightSkyBlue"，不透明度= 0.5，layer ="below"，line_width = 0)])图show() 

我有一个类似下面的数据.它是基于时间序列的EURUSD平价金融数据集.我为本地最小"和最大"计算了两个等式.我想根据每个Min_alt/Min_ust和Max_alt/Max_range绘制矩形形状.我只能像下图那样绘制一个日期，但是我没有设法在同一个绘图图中显示所有范围.

这是

以下是添加行的解决方案:

 导入日期时间颜色= ["LightSkyBlue"，"RoyalBlue"，"forestgreen"，"lightseagreen"]ply_shapes = {}对于范围(0，len(data1))中的i:ply_shapes ['shape_'+ str(i)] = go.layout.Shape(type ="rect"，x0 = data1 ['Date'] [i] .strftime('％Y-％m-％d')，y0 = data1 ['Max_alt'] [i]，x1 ='2019-12-31'，y1 = data1 ['Max_ust'] [i]，fillcolor ="LightSkyBlue"，不透明度= 0.5，layer ="below")lst_shapes = list(ply_shapes.values())fig1.update_layout(shapes = lst_shapes)fig1.show() 

但是我仍然难以在这些行上添加跟踪.我的意思是文字属性.

这是我的代码:

  add_trace = {}对于范围(0，len(data1))中的i:add_trace ['scatter_'+ str(i)] = go.Scatter(x = ['2019-12-31']，y = [data1 ['Max_ust'] [i]]，text = [str(data ['Max_Label'] [i])]，mode ="text")lst_trace =列表(add_trace.values())fig2 = go.Figure(lst_trace)fig2.show() 

解决方案

答案:

要完全控制要插入的每个形状，可以遵循以下逻辑:

  fig = go.Figure()#[...]数据，痕迹等ply_shapes = {}对于范围(1，len(df))中的i:ply_shapes ['shape_'+ str(i)] = go.layout.Shape()lst_shapes = list(ply_shapes.values())fig.update_layout(shapes = lst_shapes)图show() 

详细信息:

我不确定您打算在这里做什么，但是下面的建议可以从字面上回答您有关以下问题的确切建议:

如何在绘图中添加多个带有循环的形状?

然后，您必须弄清楚有关以下内容的详细信息:

将所有关键点线放在一张图表上

情节:

该图本身很可能不是您要查找的，但是由于某种原因，由于您要根据数据的长度添加一个图，因此范围为(0，len(data)，我做到了:

代码:

此代码段将显示如何使用for循环处理所有所需的迹线和形状:

 #导入将熊猫作为pd导入#将matplotlib.pyplot导入为plt将numpy导入为np随地导入plotly.graph_objects#from plotly.offline导入download_plotlyjs，init_notebook_mode，plot，iplot#数据，随机样本说明股票np.random.seed(12345)行= 20x = pd.Series(np.random.randn(行)，index = pd.date_range('1/1/2020'，周期=行)).cumsum()y = pd.Series(x-np.random.randn(rows)* 5，index = pd.date_range('1/1/2020'，period = rows))df = pd.concat([y，x]，轴= 1)df.columns = ['StockA'，'StockB']#行df ['keyPoints1'] = np.random.randint(-5,5，len(df))df ['keyPoints2'] = df ['keyPoints1'] *-1#绘图痕迹无花果= go.Figure()股票= ['StockA'，'StockB']df [stocks] .tail()痕迹= {}对于i在范围(0，len(stock))中:traces ['trace_'+ str(i)] = go.Scatter(x = df.index，y = df [stocks [i]].values，名称=股票[i])数据=列表(traces.values())fig = go.Figure(数据)#形状更新颜色= ["LightSkyBlue"，"RoyalBlue"，"forestgreen"，"lightseagreen"]ply_shapes = {}对于范围(1，len(df))中的i:ply_shapes ['shape_'+ str(i)] = go.layout.Shape(type ="line"，x0 = df.index [i-1]，y0 = df ['keyPoints1'].iloc [i-1]，x1 = df.index [i]，y1 = df ['keyPoints2'].iloc [i-1]，线=字典(color = np.random.choice(colors，1)[0]，宽度= 30)，不透明度= 0.5，layer ="below")lst_shapes = list(ply_shapes.values())fig.update_layout(shapes = lst_shapes)图show() 

I use plotly package to show dynamic finance chart at python. However I didn't manage to put my all key points lines on one chart with for loop. Here is my code:

fig.update_layout(
    for i in range(0,len(data)):
        shapes=[
            go.layout.Shape(
            type="rect",
            x0=data['Date'][i],
            y0=data['Max_alt'][i],
            x1='2019-12-31',
            y1=data['Max_ust'][i],
            fillcolor="LightSkyBlue",
            opacity=0.5,
            layer="below",
            line_width=0)])
fig.show()

I have a data like below one. It is time series based EURUSD parity financial dataset. I calculated two constraits for both Local Min and Max. I wanted to draw rectangule shape to based on for each Min_alt / Min_ust and Max_alt / Max_range. I can draw for just one date like below image however I didn't manage to show all ranges in same plotly graph.

Here is the sample data set.

Here is the solution for added lines:

import datetime

colors = ["LightSkyBlue", "RoyalBlue", "forestgreen", "lightseagreen"]
ply_shapes = {}
for i in range(0, len(data1)):
    ply_shapes['shape_' + str(i)]=go.layout.Shape(type="rect",
                                                    x0=data1['Date'][i].strftime('%Y-%m-%d'),
                                                    y0=data1['Max_alt'][i],
                                                    x1='2019-12-31',
                                                    y1=data1['Max_ust'][i],
                                                    fillcolor="LightSkyBlue",
                                                    opacity=0.5,
                                                    layer="below"
                                                )
lst_shapes=list(ply_shapes.values())
fig1.update_layout(shapes=lst_shapes)
fig1.show()

However I have still problems to add traces to those lines. I mean text attribute.

Here is my code:

add_trace = {}
for i in range(0, len(data1)):
    add_trace['scatter_' + str(i)] =  go.Scatter(
                        x=['2019-12-31'],
                        y=[data1['Max_ust'][i]],
                        text=[str(data['Max_Label'][i])],
                        mode="text")

lst_trace = list(add_trace.values())

fig2=go.Figure(lst_trace)
fig2.show()

解决方案

The answer:

For full control of each and every shape you insert, you could follow this logic:

fig = go.Figure()

#[...] data, traces and such

ply_shapes = {}
    for i in range(1, len(df)):
    ply_shapes['shape_' + str(i)]=go.layout.Shape()

lst_shapes=list(ply_shapes.values())
fig.update_layout(shapes=lst_shapes)
fig.show()

The details:

I'm not 100% sure what you're aimin to do here, but the following suggestion will answer your question quite literally regarding:

How to add more than one shape with loop in plotly?

Then you'll have to figure out the details regarding:

manage to put my all key points lines on one chart

Plot:

The plot itself is most likely not what you're looking for, but since you for some reason are adding a plot by the length of your data for i in range(0,len(data), I've made this:

Code:

This snippet will show how to handle all desired traces and shapes with for loops:

# Imports
import pandas as pd
#import matplotlib.pyplot as plt
import numpy as np
import plotly.graph_objects as go
#from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot

# data, random sample to illustrate stocks
np.random.seed(12345)
rows = 20
x = pd.Series(np.random.randn(rows),index=pd.date_range('1/1/2020', periods=rows)).cumsum()
y = pd.Series(x-np.random.randn(rows)*5,index=pd.date_range('1/1/2020', periods=rows))
df = pd.concat([y,x], axis = 1)
df.columns = ['StockA', 'StockB']

# lines
df['keyPoints1']=np.random.randint(-5,5,len(df))
df['keyPoints2']=df['keyPoints1']*-1

# plotly traces
fig = go.Figure()
stocks = ['StockA', 'StockB']
df[stocks].tail()

traces = {}
for i in range(0, len(stocks)):
    traces['trace_' + str(i)]=go.Scatter(x=df.index,
                                         y=df[stocks[i]].values,
                                         name=stocks[i])
data=list(traces.values())  
fig=go.Figure(data)

# shapes update
colors = ["LightSkyBlue", "RoyalBlue", "forestgreen", "lightseagreen"]
ply_shapes = {}
for i in range(1, len(df)):
    ply_shapes['shape_' + str(i)]=go.layout.Shape(type="line",
                                                    x0=df.index[i-1],
                                                    y0=df['keyPoints1'].iloc[i-1],
                                                    x1=df.index[i],
                                                    y1=df['keyPoints2'].iloc[i-1],
                                                    line=dict(
                                                        color=np.random.choice(colors,1)[0],
                                                        width=30),
                                                    opacity=0.5,
                                                    layer="below"
                                                )
lst_shapes=list(ply_shapes.values())
fig.update_layout(shapes=lst_shapes)
fig.show()

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