How to make binwidths wider in plotly?-CodePudding

I am trying to figure out how to fill the bin widths for a plotly dash dashboard. As it stands, I have a bunch of stock data in the dataset that can change the look of the charts.

When there are stock tickers with a wide X axis (strike), the data almost becomes invisible.

Zooming in, the bins seem to only occupy ~ 10% of the available space. I am assuming this is due to them being offset, but one step at a time.

How can I set the binwidths to take up the whole area?

I tried using

fig.update_traces(xbins=dict(
            start = 0.0,
            end = 60,
            size = 2))

and other variations but could not get it to work.

plotly / dash code below along with dataframe sample.

import dash
from dash import dcc
from dash import html
from dash.dependencies import Input, Output
import plotly.express as px


tickers = GEX['ticker'].unique()
pos_neg = GEX['pos_neg'].unique()

app = dash.Dash(__name__)

app.layout = html.Div([
    dcc.Dropdown(
        id="dropdown",
        options=[{"label": x, "value": x} for x in tickers],
        value=tickers[0],
        clearable=False,
    ),
    dcc.Graph(id="bar-chart", style = {'width': '90vh', 'height': '90vh'}),
])

@app.callback(
    Output("bar-chart", "figure"), 
    [Input("dropdown", "value")])
def gex_per_strike(ticker):
    mask = GEX['ticker'] == ticker
    fig = px.bar(GEX[mask], x="strike", y="net_GEX", 
                 color= 'pos_neg', 
                 barmode="group", 
                 title = ('Gamma Exposure for '   ticker),
                 color_discrete_sequence = ['#DC143C','#7FFF00'])
    '''fig.update_traces(xbins=dict(
            start = 0.0,
            end = 60,
            size = 2))'''

    return fig

app.run_server(debug=True, use_reloader = False)

Dataframe:

import numpy as np
import pandas as pd
import random

GEX = pd.DataFrame()

GEX['strike'] = range(0,200)
GEX['pos_GEX'] = np.random.randint(0, 1000000, GEX.shape[0])
GEX['neg_GEX'] = np.random.randint(-1000000, 0, GEX.shape[0])
GEX['net_GEX'] = GEX['pos_GEX']   GEX['neg_GEX']
GEX['pos_neg'] = GEX['net_GEX'].apply(lambda x: 1 if x > 0 else 0)
GEX['ticker'] = 'AAPL'

CodePudding user response：

You can change the bargap argument using fig.update_layout:

import numpy as np
import pandas as pd
import random

GEX = pd.DataFrame()

GEX['strike'] = range(0,200)
GEX['pos_GEX'] = np.random.randint(0, 1000000, GEX.shape[0])
GEX['neg_GEX'] = np.random.randint(-1000000, 0, GEX.shape[0])
GEX['net_GEX'] = GEX['pos_GEX']   GEX['neg_GEX']
GEX['pos_neg'] = GEX['net_GEX'].apply(lambda x: 1 if x > 0 else 0)
GEX['ticker'] = 'AAPL'

import dash
from dash import dcc
from dash import html
from dash.dependencies import Input, Output
import plotly.express as px


tickers = GEX['ticker'].unique()
pos_neg = GEX['pos_neg'].unique()

app = dash.Dash(__name__)

app.layout = html.Div([
    dcc.Dropdown(
        id="dropdown",
        options=[{"label": x, "value": x} for x in tickers],
        value=tickers[0],
        clearable=False,
    ),
    dcc.Graph(id="bar-chart", style = {'width': '90vb', 'height': '90vh'}),
])

@app.callback(
    Output("bar-chart", "figure"),
    [Input("dropdown", "value")])
def gex_per_strike(ticker):
    mask = GEX['ticker'] == ticker
    fig = px.bar(GEX[mask], x="strike", y="net_GEX",
                 color= 'pos_neg',
                 barmode="group",
                 # width=1,
                 title = ('Gamma Exposure for '   ticker),
                 color_discrete_sequence = ['#DC143C','#7FFF00'])
    fig.update_layout(
        bargap=0
    )
    '''fig.update_traces(xbins=dict(
            start = 0.0,
            end = 60,
            size = 2))'''

    return fig

app.run_server(debug=True, use_reloader = False)

Bar charts also have a width argument - but I guess that's not causing the issue here.