Ploting in Jupyter Lab

[Geoffry Roberts]

Hi all,

Quick question asking: Is this possible?

I want to create a plot and have it appear in the output cell of Jupiter lab.  

I am using Julia and Plots.jl with the Plotly backend enabled.  My plot works peachy when run from a CL script. However, if I run the same in Jupiter,  a new browser tab is created for each plot but nothing displays.  Tab is empty. No errors show.  Output cell says "false".

Thanks

--

There are ways and there are ways, 

Geoffry Roberts

[Oliver Frank]

Hi Geoffry,

is it possible that you use another Environment? I had the same Problem. On the commandline the configfile .plotly/.credentials was used anderen under juyter another configfile was used.

[Oliver Frank]

Hi Geoffry,

an example which works for me in jupyter lab.

------------------------------------------------------------------------

import plotly.plotly as py
from plotly import tools
import plotly.offline as offline
import plotly.graph_objs as go


import pandas as pd
from datetime import datetime

df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv')[1:20]

# Date,AAPL.Open,AAPL.High,AAPL.Low,AAPL.Close,AAPL.Volume,AAPL.Adjusted,
# dn,mavg,up,direction

#print(df['AAPL.High'])
#print(df.Date)

trace1 = go.Scatter(name="AAPL.Open", x=df.Date, y=df['AAPL.Open'])
trace2 = go.Scatter(name="AAPL.Low",  x=df.Date, y=df['AAPL.Low'])
trace3 = go.Scatter(name="AAPL.High", x=df.Date, y=df['AAPL.High'])
trace4 = go.Scatter(name="dn", x=df.Date, y=df['dn'])
trace5 = go.Scatter(name="mavg", x=df.Date, y=df['mavg'])
trace6 = go.Scatter(name="direction", x=df.Date, y=df['direction'])

layout = go.Layout(
    xaxis=dict(
        title='X-AXIS TITLE',       
        autorange=True,
        showgrid=False,
        zeroline=False,
        showline=False,
        ticks='',
        showticklabels=False
    ),
    yaxis=dict(
        title='Y-AXIS TITLE',       
        autorange=True,
        showgrid=False,
        zeroline=False,
        showline=False,
        ticks='',
        showticklabels=False
    )
)

fig = tools.make_subplots(rows=3, cols=2, subplot_titles=('AAPL.Open',
                                                          'AAPL.Low',
                                                          'AAPL.High',
                                                          'dn',
                                                          'mavg',
                                                          'direction',
                                                         )
                         )

fig.append_trace(trace1, 1, 1)
fig.append_trace(trace2, 1, 2)
fig.append_trace(trace3, 2, 1)
fig.append_trace(trace4, 2, 2)
fig.append_trace(trace5, 3, 1)
fig.append_trace(trace6, 3, 2)


fig['layout'].update(layout)

# Result in a jupyter cell
py.iplot(fig, filename='make-subplots-multiple-with-titles')

# Result in an new Tab
# offline.plot(data, filename='time-series-simple.html')

------------------------------------------------------------------------

Oliver

[Geoffry Roberts]

Thanks Oliver.

Since I posted, I got it to work.  I am using Julia.

using Plots

plotlyjs()

# Aedge is an associative array.  Aedge.A is it's internal array.

scatter(Aedge.A, layout = 1, markersize=Aedge.A, marker=:hex, c=:red, fmt = :svg) 

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