How to add more than one shape with loop in plotly

Question

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()

Answer 1

Also you can use fig.add_{shape}:

fig = go.Figure()
    
fig.add_trace( 
    go.Scatter( ...)

for i in range( 1, len( vrect)):
    fig.add_vrect( 
        x0=vrect.start.iloc[ i-1], 
        x1=vrect.finish.iloc[ i-1], 
        fillcolor=vrect.color.iloc[ i-1]], 
        opacity=0.25, 
        line_width=0)  

fig.show()

Answer 2

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()