python-visualization / python-visualization/folium
FeatureGroupSubGroup: nth level subgroups
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Description
Describe the bug
I am using quite a few levels of recursion to generate a map that has subgroups within subgroups, and im not sure how to fix the issue, or if there is a better method.
To Reproduce
theres alot going on here... the repeated for loops are to keep the buttons ordered by hierarchy.
import folium
from folium import plugins
#####################################################################################
coord = df['Location'].apply(fetch_lat_lon)
df['Lat'] = coord.apply(lambda x: x[0] if isinstance(x, tuple) else None)
df['Long'] = coord.apply(lambda x: x[1] if isinstance(x, tuple) else None)
df['Result'] = (~df['Impounded'].isna().astype(int)).apply(lambda x: _results[x])
df['Interval'] = (datetime.now() - df.index).days
df['Weekday'] = df.index.weekday.map(lambda x: _days[x])
df['Time'] = df.index.hour
df = df[~df['ID'].isna()]
#####################################################################################
m = folium.Map(location=[0, 0], zoom_start=14)
results = {}
intervals = {}
days = {}
times = {}
_results = ['Complete', 'Canceled']
_intervals = [7, 30, 90, 365] ## days before now
_days = ['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday']
_times = range(24)
for result in _results:
results[result] = folium.FeatureGroup(name = result)
m.add_child(results[result])
for result in _results:
for interval in _intervals:
intervals[f'{result}_{interval}'] = plugins.FeatureGroupSubGroup(results[result], f'{interval} Days')
m.add_child(intervals[f'{result}_{interval}'])
for result in _results:
for interval in _intervals: ## days before now
for day in _days:
days[f'{result}_{interval}_{day}'] = plugins.FeatureGroupSubGroup(intervals[f'{result}_{interval}'], day)
m.add_child(days[f'{result}_{interval}_{day}'])
for result in _results:
for interval in _intervals: ## days before now
for day in _days:
for time in _times:
if time < 12:
if time !=0:
times[f'{result}_{interval}_{day}_{time}'] = plugins.FeatureGroupSubGroup(days[f'{result}_{interval}_{day}'], f'{time} AM')
m.add_child(times[f'{result}_{interval}_{day}_{time}'])
else:
times[f'{result}_{interval}_{day}_{time}'] = plugins.FeatureGroupSubGroup(days[f'{result}_{interval}_{day}'], f'{time + 12} AM')
m.add_child(times[f'{result}_{interval}_{day}_{time}'])
elif time > 12:
times[f'{result}_{interval}_{day}_{time}'] = plugins.FeatureGroupSubGroup(days[f'{result}_{interval}_{day}'], f'{time - 12} PM')
m.add_child(times[f'{result}_{interval}_{day}_{time}'])
else:
times[f'{result}_{interval}_{day}_{time}'] = plugins.FeatureGroupSubGroup(days[f'{result}_{interval}_{day}'], f'{time} PM')
m.add_child(times[f'{result}_{interval}_{day}_{time}'])
for result in _results:
for interval in _intervals: ## days before now
for day in _days:
for time in _times:
group = times[f'{result}_{interval}_{day}_{time}']
condition = ((df['Result'] == result) &
(df['Interval'] <= interval) &
(df['Weekday'] == day) &
(df['Time'] == time)
)
_df = df[condition].dropna()
for i in range(len(_df)):
lat = _df['Lat'].iloc[i] - _df['Lat'].mean()
long = _df['Long'].iloc[i] - _df['Long'].mean()
folium.Marker([lat, long]).add_to(group)
folium.LayerControl(collapsed=True).add_to(m)
m.save('TESTING.html')
Expected behavior
When all button conditions are met, points will display,
Environment (please complete the following information):
- chrome
- jupyter notebooks
- vs code
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with the provided FeatureGroupSubGroup construction and the generated TESTING.html in the Jupyter/VS Code reproduction; verify whether nested subgroups beyond one level are represented and toggled as expected. Define the desired nth-level behavior and confirm it with a minimal map reproduction, including the stated point-display condition.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- jupyter-notebook, python
- Domain
- data-visualization
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100