I want to change the dropdown button with an input box so I can search for the item by starting to type the name and then select. So far I have a drop down box where you can select either one item or all of them at the same time. However, I want the user to be able to start typing the name of the item and then click and select the item they want to display their graph.
As I am new to plotly, any suggestion is very welcome and appreciated :)
Here is what the plot looks like so far:
My code:
def interactive_multi_plot(actual, forecast_1, forecast_2, title, addAll = True):
fig = go.Figure()
for column in forecast_1.columns.to_list():
fig.add_trace(
go.Scatter(
x = forecast_1.index,
y = forecast_1[column],
name = "Forecast_SI"
)
)
button_all = dict(label = 'All',
method = 'update',
args = [{'visible': forecast_1.columns.isin(forecast_1.columns),
'title': 'All',
'showlegend':True}])
for column in forecast_2.columns.to_list():
fig.add_trace(
go.Scatter(
x = forecast_2.index,
y = forecast_2[column],
name = "Forecast_LSTM"
)
)
button_all = dict(label = 'All',
method = 'update',
args = [{'visible': forecast_2.columns.isin(forecast_2.columns),
'title': 'All',
'showlegend':True}])
for column in actual.columns.to_list():
fig.add_trace(
go.Scatter(
x = actual.index,
y = actual[column],
name = "True values"
)
)
button_all = dict(label = 'All',
method = 'update',
args = [{'visible': actual.columns.isin(actual.columns),
'title': 'All',
'showlegend':True}])
fig.layout.plot_bgcolor = '#010028'
fig.layout.paper_bgcolor = '#010028'
def create_layout_button(column):
return dict(label = column,
method = 'update',
args = [{'visible': actual.columns.isin([column]),
'title': column,
'showlegend': True}])
fig.update_layout(
updatemenus=[go.layout.Updatemenu(
active = 0,
buttons = ([button_all] * addAll) + list(actual.columns.map(lambda column: create_layout_button(column)))
)
]
)
# Update remaining layout properties
fig.update_layout(
title_text=title,
height=800,
font = dict(color='#fff', size=12)
)
fig.show()
This is the error I receive:
interactive_multi_plot()
.
add_trace()
add meta = column
for each of the scatter creationsreturn fig
instead of fig.show()
interactive_multi_plot()
. I have assumed all three data frames have the same columnsS = 100
C = 10
actual = pd.DataFrame(
{
c: np.sort(np.random.uniform(0, 600, S))
for c in [
f"{a}{b}-{c}"
for a, b, c in zip(
np.random.randint(100, 200, C),
np.random.choice(list("ABCDEF"), C),
np.random.randint(300, 400, C),
)
]
}
)
f1 = actual.assign(**{c:actual[c]*1.1 for c in actual.columns})
f2 = actual.assign(**{c:actual[c]*1.2 for c in actual.columns})
fig = interactive_multi_plot(actual, f1, f2, "Orders")
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output, State
from jupyter_dash import JupyterDash
# Build App
app = JupyterDash(__name__)
app.layout = html.Div(
[
dcc.Dropdown(
id="lines",
options=[{"label": c, "value": c} for c in ["All"] + actual.columns.tolist()],
value="All",
),
dcc.Graph(id="interactive-multiplot", figure=fig),
]
)
@app.callback(
Output("interactive-multiplot", "figure"),
Input("lines", "value"),
State("interactive-multiplot", "figure"),
)
def updateGraphCB(line, fig):
# filter traces...
fig = go.Figure(fig).update_traces(visible=False).update_traces(visible=True, selector={"meta":line} if line!="All" else {})
# syn button to dash drop down
fig = fig.update_layout(updatemenus=[{"active":0 if line=="All" else actual.columns.get_loc(line)+1}])
return fig
app.run_server(mode="inline")