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How to make a plotly graph wider and higher? [duplicate]

I have made a scatter plot using matplotlib and Plotly. I want the height, width and the markers to be scatter as in matplotlib plot. Please see the attached plots.
I used the following code in Plotly
import plotly
import plotly.plotly as py
from plotly.graph_objs import Scatter
import plotly.graph_objs as go
trace1 = go.Scatter(
x=x1_tsne, # x-coordinates of trace
y=y1_tsne, # y-coordinates of trace
mode='markers ', # scatter mode (more in UG section 1)
text = label3,
opacity = 1,
textposition='top center',
marker = dict(size = 25, color = color_4, symbol = marker_list_2, line=dict(width=0.5)),
textfont=dict(
color='black',
size=18, #can change the size of font here
family='Times New Roman'
)
)
layout = {
'xaxis': {
'showticklabels': False,
'showgrid': False,
'zeroline': False,
'linecolor':'black',
'linewidth':2,
'mirror':True,
'autorange':False,
'range':[-40, 40][![enter image description here][1]][1]
},
'yaxis': {
'showticklabels': False,
'showgrid': False,
'zeroline': False,
'linecolor':'black',
'linewidth':2,
'mirror':True,
'autorange':False,
'range':[-40, 40]
}
}
data = [trace1]
fig = go.Figure(
data= data,
layout= layout)
py.iplot(fig)
I try to tune the range but did not help. In addition, I use Autorange that did not help. Could you please help me with this.
I want the image as
##update: This can be done by the following code. I am updating this in the question:
trace1 = go.Scatter(
x=x1_tsne, # x-coordinates of trace
y=y1_tsne, # y-coordinates of trace
mode='markers +text ', # scatter mode (more in UG section 1)
text = label3,
opacity = 1,
textposition='top center',
marker = dict(size = 25, color = color_4, symbol = marker_list_2, line=dict(width=0.5)),
textfont=dict(
color='black',
size=18, #can change the size of font here
family='Times New Roman'
)
)
data = [trace1]
layout = go.Layout(
autosize=False,
width=1000,
height=1000,
xaxis= go.layout.XAxis(linecolor = 'black',
linewidth = 1,
mirror = True),
yaxis= go.layout.YAxis(linecolor = 'black',
linewidth = 1,
mirror = True),
margin=go.layout.Margin(
l=50,
r=50,
b=100,
t=100,
pad = 4
)
)
fig = go.Figure(data=data, layout=layout)
py.iplot(fig, filename='size-margins')

Have you considered to use
fig.update_layout(
autosize=False,
width=800,
height=800,)
and eventually reduce the size of your marker?
UPDATE
Full Code
import plotly.graph_objs as go
trace1 = go.Scatter(
x=x1_tsne, # x-coordinates of trace
y=y1_tsne, # y-coordinates of trace
mode='markers +text ', # scatter mode (more in UG section 1)
text = label3,
opacity = 1,
textposition='top center',
marker = dict(size = 12, color = color_4, symbol = marker_list_2, line=dict(width=0.5)),
textfont=dict(
color='black',
size=18, #can change the size of font here
family='Times New Roman'
)
)
data = [trace1]
layout = go.Layout(
autosize=False,
width=1000,
height=1000,
xaxis= go.layout.XAxis(linecolor = 'black',
linewidth = 1,
mirror = True),
yaxis= go.layout.YAxis(linecolor = 'black',
linewidth = 1,
mirror = True),
margin=go.layout.Margin(
l=50,
r=50,
b=100,
t=100,
pad = 4
)
)
fig = go.Figure(data=data, layout=layout)

Dash+Plotly Synchronize zoom and pan between two plots using imshow

I try to synchronize zoom and pan between two graphs in a dashboard (dash + plotly). I obtain strange behavior when I zoom on a graph, the second graph does not update. I need to zoom on the second graph to make both graphs update but not with the same zoom nor the same location on the graphs. Furthermore the shapes of the two graphs change.
Below is the code I am in. I do not see I am doing wrong.
import os
from dash import Dash, html, dcc, Input, Output, State
import plotly.express as px
import numpy as np
import rasterio as rio
app2 = Dash(__name__)
data_folder = r'.\data'
store = {}
for filename in os.listdir(data_folder):
if os.path.isfile(os.path.join(data_folder, filename)):
band_name = filename.replace('.', '_').split(sep='_')[-2]
with rio.open(os.path.join(data_folder, filename)) as dataset:
nb_band = dataset.count
if nb_band == 1:
data = dataset.read(1)
else:
data = dataset.read(tuple(range(1, nb_band + 1)))
if band_name == 'triband':
data = np.swapaxes(data, 2, 0)
data = np.swapaxes(data, 0, 1)
store[band_name] = data.astype(float)
else:
store[f'B{band_name}'] = data.astype(float)
fig1 = px.imshow(store['triband'])
fig1.update_xaxes(showticklabels=False, showgrid=False, zeroline=False)
fig1.update_yaxes(showticklabels=False, showgrid=False, zeroline=False)
fig1.update_layout(
margin=dict(l=0, r=0, t=0, b=0),
plot_bgcolor='rgba(0, 0, 0, 0)',
paper_bgcolor='rgba(0, 0, 0, 0)',
)
# Application structure and content
app2.layout = html.Div(className='main', children=[
html.H1(children='Hello Dash', style={'padding': 10}),
html.Div(children=[
html.Div(children=[
dcc.Graph(
id='graph1',
figure=fig1,
responsive=True
)
], style={'padding': 5, 'flex': 1}),
html.Div(children=[
dcc.Graph(
id='graph2',
figure=fig1,
responsive=True
)
], style={'padding': 5, 'flex': 1})
], style={'display': 'flex', 'flex-direction': 'row'}),
])
#app2.callback(Output('graph2', 'figure'),
Input('graph1', 'relayoutData'),
State('graph2', 'figure'))
def graph_event1(select_data, fig):
if select_data is not None:
try:
fig['layout']['xaxis']['range'] = [select_data['xaxis.range[0]'], select_data['xaxis.range[1]']],
fig['layout']['yaxis']['range'] = [select_data['yaxis.range[0]'], select_data['yaxis.range[1]']]
except KeyError:
pass
return fig
#app2.callback(Output('graph1', 'figure'),
Input('graph2', 'relayoutData'),
State('graph1', 'figure'))
def graph_event2(select_data, fig):
if select_data is not None:
try:
fig['layout']['xaxis']['range'] = [select_data['xaxis.range[0]'], select_data['xaxis.range[1]']],
fig['layout']['yaxis']['range'] = [select_data['yaxis.range[0]'], select_data['yaxis.range[1]']]
except KeyError:
pass
return fig
if __name__ == '__main__':
app2.run_server(debug=True)

I found a solution : rather than creating two graphs, I created a graph with several subplots and force zoom and pan between subplots.
fig = make_subplots(rows=1, cols=3, shared_xaxes=True, shared_yaxes=True)
fig.add_trace(
px.imshow(store['triband']).data[0],
row=1, col=1
)
fig.add_trace(
px.imshow(index_store['NDVI']).data[0],
row=1, col=2
)
fig.add_trace(
px.imshow(np.where(index_store['NDVI'] >= np.median(index_store['NDVI']),
0.8 * np.max(index_store['NDVI']),
0.8 * np.min(index_store['NDVI']))
).data[0],
row=1, col=3
)
fig.update_xaxes(matches='x', showticklabels=False, showgrid=False, zeroline=False)
fig.update_yaxes(matches='y', showticklabels=False, showgrid=False, zeroline=False)

Changing line color based on other line's index

I have a out dataframe containing two columns, Actual_Values and Predicted_Values.
I am trying to create a graph:
import pandas as pd
import plotly.graph_objects as go
x_data = out.index
trace1 = go.Scatter(
x=x_data,
y=out['Actual_Values'],
name="Actual Values"
)
trace2 = go.Scatter(
x=x_data,
y=out['Predicted_Values'],
name="Predictions"
)
traces = [trace1, trace2]
layout = go.Layout(
xaxis=dict(
autorange=True
),
yaxis=dict(
autorange=True
)
)
fig = go.Figure(data=traces, layout=layout)
plot(fig, include_plotlyjs=True)
which gives:
however, I need a graph, in which the blue line's changes to some other color from the start of the red line.

Does this help you?
import pandas as pd
import numpy as np
import plotly.graph_objects as go
# Data
n = 150
n_pred = 10
df1 = pd.DataFrame(
{"x": np.arange(n),
"actual_value": np.random.randint(0, 100, n)})
df2 = pd.DataFrame(
{"x": np.arange(n-n_pred, n),
"predicted_value": np.random.randint(0, 100, n_pred)})
# You need Outer join when prediction range is
# larger than actual value one.
df = pd.merge(df1, df2, on="x", how="outer")
idx_min = df[df["predicted_value"].notnull()].index[0]
# Plot
trace1 = go.Scatter(
x=df["x"][:idx_min+1],
y=df['actual_value'][:idx_min+1],
name="Actual Values",
line=dict(color="blue")
)
trace2 = go.Scatter(
x=df["x"][idx_min:],
y=df['actual_value'][idx_min:],
name="Actual Values",
mode="lines",
line=dict(color="green"),
showlegend=False
)
trace3 = go.Scatter(
x=df["x"],
y=df['predicted_value'],
name="Predicted Values",
line=dict(color="red")
)
traces = [trace1, trace2, trace3]
layout = go.Layout(
xaxis=dict(
autorange=True
),
yaxis=dict(
autorange=True
)
)
fig = go.Figure(data=traces, layout=layout)
fig.show()

Python plotly - add horizontal line to legend

I would like to add a horizontal line to the below charts so it will appear in the legend as well.
The goal is to allow to make the line appear\disappear per user choice by clicking on the legend.
Any ideas?
import plotly.graph_objects as go
tips = px.data.tips()
fig = make_subplots(rows=2, cols=2, shared_xaxes=False, vertical_spacing=0.3,horizontal_spacing=0.05)
#Scatter plot
fig.append_trace(go.Scatter(
x=tips['total_bill'],
y=tips['tip'],
mode = 'markers',
marker=dict( size=7),
showlegend = True),
row=1, col=1)
#Box plot
fig.add_trace(go.Box(
y=tips['tip'],
x = tips['sex'],
boxpoints='all',jitter=0.5,whiskerwidth=0.2,marker_size=5,line_width=2),
row=1, col=2)
#Add horizontal lines
shapes = [
{'type': 'line','x0': 5,'y0': 5,
'x1': 50,'y1' : 5,'xref': 'x1',
'yref': 'y1','line': {'color': 'red','width': 4, 'dash':'dashdot'}},
{'type': 'line','x0': 'Female','y0': 5,
'x1': 'Male','y1' : 5,'xref': 'x2',
'yref': 'y2','line': {'color': 'red','width': 4, 'dash':'dashdot'}},
]
fig['layout'].update(shapes=shapes)
fig.show()

Store all your traces in a list. Then add each of your plots to the list.
fig = go.Figure()
data = []
data.append(go.Scatter(
x=tips['total_bill'],
y=tips['tip'],
mode = 'markers',
marker=dict( size=7))
data.append(
go.Scatter(
x=(5,5),
y=(50,5),
mode='lines',
name='trace 0',
yaxis='y1'
))
layout = go.Layout(title='Some Title',showlegend=True)
fig = go.Figure(data=data, layout=layout)
fig.show()

Share all x-axes of a subplot (rows and columns)

I try to share all x-axes of a subplot structure with several columns, but I can't get the solution. With 'share_xaxes=True' only the x-axes of the same row are linked, and I am not able to change the 'xaxis' paramater from the figures in the subplot. Any idea?

In the Plotly documentation you can see that the axes have an attribute called scaleanchor (see https://plot.ly/python/reference/#layout-xaxis-scaleanchor). You can use it to connect as many axes as you like. I tested it out on a simple subplot with 2 rows and 2 columns where all x-axes are connected:
import plotly.plotly as py
import plotly.graph_objs as go
# -*- coding: utf-8 -*-
import dash
import dash_core_components as dcc
import dash_html_components as html
external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']
app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
def create_figure():
trace1 = go.Scatter(
x=[1, 2, 3],
y=[2, 3, 4]
)
trace2 = go.Scatter(
x=[1, 2, 3],
y=[5, 5, 5],
xaxis='x2',
yaxis='y2'
)
trace3 = go.Scatter(
x=[1, 2, 3],
y=[600, 700, 800],
xaxis='x3',
yaxis='y3'
)
trace4 = go.Scatter(
x=[1, 2, 3],
y=[7000, 8000, 9000],
xaxis='x4',
yaxis='y4'
)
data = [trace1, trace2, trace3, trace4]
layout = go.Layout(
xaxis=dict(
domain=[0, 0.45],
anchor='y'
),
xaxis2=dict(
domain=[0.55, 1],
anchor='y2',
scaleanchor='x'
),
xaxis3=dict(
domain=[0, 0.45],
anchor='y3',
scaleanchor='x'
),
xaxis4=dict(
domain=[0.55, 1],
anchor='y4',
scaleanchor='x'
),
yaxis=dict(
domain=[0, 0.45],
anchor='x'
),
yaxis2=dict(
domain=[0, 0.45],
anchor='x2'
),
yaxis3=dict(
domain=[0.55, 1],
anchor='x3'
),
yaxis4=dict(
domain=[0.55, 1],
anchor='x4'
)
)
fig = go.Figure(data=data, layout=layout)
return fig
app.layout = html.Div(children=[
html.H1(children='Hello Dash'),
html.Div(children='''
Dash: A web application framework for Python.
'''),
dcc.Graph(
id='example-graph',
figure=create_figure()
)
])
if __name__ == '__main__':
app.run_server(debug=True)

I know this post is old, but maybe this can help someone else:
Just use the option shared_xaxes = 'all' when you create subplots with make_subplots() and all x-axes will be shared.