Hi there,
I would like to use go.Scattergl() instead of px.scatter() but I’m not sure how to enter the variables now. Simply replacing didn’t work and it seems like the data sets have to be addressed differently?
I want to separate columns (indicated by signals) by color and devices (by shape or whatever).
Thanks a lot in advance!
At the moment I have
fig_general = px.scatter(df3
, x = "time"
, y = 'value'
, color = 'Device'
, symbol = 'variable'
, hover_name = "Device"
, template = 'plotly_dark'
#, marginal_y="rug"
).update_layout(
transition_duration = 500
, autosize = True
, height = 700
)
which I would like to replace with go.Scattergl(). I tried
fig_general = go.Figure()
fig_general.add_trace(
go.Scattergl(
x = df3["time"]
, y = df3['value']
, fill = df3['Device']
, template = 'plotly_dark'
)
)
which results in
self["fill"] = _v
(...)
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
edit: I figured out that
fig_general = go.Figure()
fig_general.add_trace(
go.Scattergl(
x = df3["time"]
, y = df3['value']
)
)
generates at least a plot. But it doesn’t distinguish between the selected columns, probably because of the missing fill = command or the like. But it doesn’t work as in px.scatter(). Any idea?
Here is the entire code:
df2 = df.melt(id_vars=['Device','time'], value_vars=['V+','V-','I_A', 'I_fil'])
external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']
app = dash.Dash(__name__, title='Dashboard', external_stylesheets=external_stylesheets)
colors = {
'background': '#000000',
'text': '#f3ff00'
}
app.layout = html.Div(children = [
html.Div([
html.H4('Dauertest'),
html.Div(children = ""),
dcc.Graph(id = 'General'
, figure={}
),
]),
dcc.Checklist(
id="signals",
options = ['V+', 'V-', 'I_A', 'I_fil'],
value = ['V+', 'V-'],
inline=True
),
html.Br(),
html.Br(),
html.Div([
html.Div([
dcc.Graph(id = 'shared'
, figure={}
),
], className='twelve columns'),
], className='row')
])
@app.callback(
Output("General", "figure"),
Output("shared", "figure"),
Input("signals", "value")
)
def update_line_chart(signals):
df3=df2[df2['variable'].isin(signals)]
fig_general = go.Figure()
fig_general.add_trace(
go.Scattergl(
data = df3
, x = "time"
, y = 'value'
, color = 'Device'
, symbol = 'variable'
, hover_name = "Device"
, template = 'plotly_dark'
#, marginal_y="rug"
)
)
fig_shared = make_subplots(rows = 4
, cols = 1
, shared_xaxes=True
, vertical_spacing=0.05
)
fig_shared.add_trace(go.Scattergl(
x = all_df['time']
, y = all_df['V+']
, mode = "markers"
, name="V+"
, connectgaps = False
, marker=dict(
symbol = "circle"
)
)
, row=4
, col=1
)
fig_shared.add_trace(go.Scattergl(
x = all_df['time']
, y = all_df['V-']
, name="V-"
, mode = "markers"
, marker=dict(
symbol = "star"
)
)
, row=3
, col=1
)
fig_shared.add_trace(go.Scattergl(
x = all_df['time']
, y = all_df['I_A']
, name="I_A"
, mode = "markers"
, marker=dict(
symbol = "diamond"
)
)
, row=2
, col=1
)
fig_shared.add_trace(go.Scattergl(
x = all_df['time']
, y = all_df['I_fil']
, name="I_fil"
, mode = "markers"
, marker=dict(
symbol = "x"
)
)
, row=1
, col=1
)
fig_shared.update_layout(
height= 1000
, width = 1900
, title_text = ""
, template = 'plotly_dark'
)
fig_shared.show()
fig_shared['layout']['yaxis']['title'] = 'I_fil / A'
fig_shared['layout']['yaxis2']['title'] = 'I_A / A'
fig_shared['layout']['yaxis3']['title'] = 'V- / V'
fig_shared['layout']['yaxis4']['title'] = 'V+ / V'
return [fig_general, fig_shared]
if __name__ == "__main__":
app.run_server(
debug=False
, port=8050
)
I hope I didn’t remove anything necessary… Here is the data set: Filebin | pag2dnsixti4ce9a
I stumbled over How to add categorical color legend for scatter plot created by graph_objects - #4 by ljam which looks alike but I can’t adjust it to my needs.
