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ViewsHow to get the range of angles on Plotly polar plots
I'd like select the range on the angular axis at a Plotly polar plot, and I am wondering what's the easiest way to do it. Ideally, if I click-and-drag from 30 to 90 degree then I'd like to have the range from 30 to 90 degree; if I click-and-drag from 330 to 30 degree, then I'd like to have the range from 330 to 30 degree.
I don't know much about Plotly, but I wonder whether relayoutData is something that can be tapped into. Currently it only returns the range on the radial axis (see the range returned from relayoutData in pic). I wonder whether there is a parameter can be changed to make it to return the range of angular axis?
Here is the minimal code to generate the figure above
import json
import dash
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output
import plotly.express as px
import pandas as pd
app = dash.Dash(__name__)
df = px.data.wind()
fig = px.scatter_polar(df, r="frequency", theta="direction")
app.layout = html.Div([
dcc.Graph(
id='basic-interactions',
figure=fig
),
html.Div(className='row', children=[
html.Div([
dcc.Markdown("""
**Zoom and Relayout Data**
Click and drag on the graph to zoom or click on the zoom
buttons in the graph's menu bar.
Clicking on legend items will also fire
this event.
"""),
html.Pre(id='relayout-data'),
])
])
])
@app.callback(
Output('relayout-data', 'children'),
Input('basic-interactions', 'relayoutData'))
def display_relayout_data(relayoutData):
return json.dumps(relayoutData, indent=2)
if __name__ == '__main__':
app.run_server(debug=True)
·
Santiago Trujillo
1 answers
Answer question0
- similar idea, but lasso points that you are using. event is selectedData
- code plus decoding a compass direction to angle below
import json
import dash
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output, State
import plotly.express as px
import plotly.graph_objects as go
import pandas as pd
from jupyter_dash import JupyterDash
# Build App
app = JupyterDash(__name__)
# app = dash.Dash(__name__)
df = px.data.wind()
fig = px.scatter_polar(df, r="frequency", theta="direction")
# data to translate named direction to degrees
dfd = pd.read_html("http://snowfence.umn.edu/Components/winddirectionanddegrees.htm")[1]
dfd.columns = dfd.loc[0]
dfd = (
dfd.drop([0])
.dropna()
.set_index("Cardinal Direction")["Degree Direction"]
.apply(lambda v: pd.Series(v.split(" - ")).astype(float))
)
app.layout = html.Div(
[
dcc.Graph(id="basic-interactions", figure=fig),
html.Div(
className="row",
children=[
html.Div(
[
dcc.Markdown(
"""
**Selected points**
Use lasso to select points. Double-click de-select for reset
"""
),
html.Pre(id="relayout-data"),
]
)
],
),
]
)
@app.callback(
Output("relayout-data", "children"),
Input("basic-interactions", "selectedData"),
)
def display_relayout_data(selectedData):
global dfd
def degrees(wind_dir):
return dfd.loc[wind_dir, 0].min(), dfd.loc[wind_dir, 1].max()
if selectedData:
wind_dir = [p["theta"] for p in selectedData["points"]]
return f"{degrees(wind_dir)} {wind_dir}"
else:
raise dash.exceptions.PreventUpdate
if __name__ == "__main__":
# app.run_server(debug=True)
app.run_server(mode="inline")
·
Santiago Trujillo
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