Animation using plotly

The code snippet below will produce a Plotly Dash app that animates a form of Random Walk. How that walk will appear will depend entirely on what kind of random nunbers you base it on. Here I'm using two accumulated processes for the X and Y axes based on np.random.uniform. But you can easily change that to whatever random process you prefer.

Dash App after 2500 runs

Dash App after 5000 runs

Complete code:

import pandas as pd
import numpy as np
import plotly.express as px
import plotly.graph_objects as go
from jupyter_dash import JupyterDash
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output

# data
np.random.seed(4)
Y = np.random.randint(low=-1, high=2, size=1).tolist()
X = np.random.randint(low=-1, high=2, size=1).tolist() 
df = pd.DataFrame({'X':X, 'Y':Y}, columns = ['X', 'Y'])
df.iloc[0]=0

# plotly app
app = JupyterDash(__name__)
app.layout = html.Div([
    html.H1("Random stumble"),
            dcc.Interval(
            id='interval-component',
            interval=1*1000, # in milliseconds
          
        ),
    dcc.Graph(id='graph'),
])

# Define callback to update graph
@app.callback(
    Output('graph', 'figure'),
    [Input('interval-component', "n_intervals")]
)
def streamFig(value):
    
    global df
   
    Y = np.random.randint(low=-1, high=2, size=1).tolist()
    X = np.random.randint(low=-1, high=2, size=1).tolist()  
    df2 = pd.DataFrame({'X':X, 'Y':Y}, columns = ['X', 'Y'])
    df = df.append(df2, ignore_index=True)#.reset_index()
    df3=df.copy()
    df3=df3.cumsum()
    fig = go.Figure(data=go.Scatter(x=df3['X'], y=df3['Y']))
    fig.update_layout(title = dict(text = 'x =' + str(X) + ', y ='+str(Y) + ', len = '+str(len(df))))
    #fig.update_layout(xaxis=dict(range=[-10,10]))
    #fig.update_layout(yaxis=dict(range=[-10,10]))
    return(fig)

app.run_server(mode='external', port = 8019, dev_tools_ui=True, debug=True,
              dev_tools_hot_reload =True, threaded=False)