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Interactive Xarray dataset raster visualisation app using Panel and hvplot

I am trying to replicate the Glaciers Demo using an Xarray of geospatial data. I am able to create pretty much exactly what I want but I am trying to create a Panel app that allows the user to select the data_vars, each of which has different dimensions that I want make interactable, and visualize on an interactive map with at least the continents contour. Here is what my Xarray Dataset looks like :
def plot(field):
return xds[field].hvplot.image().opts(cmap='jet',height=650,width=1300,data_aspect=1)
interact(plot, field = list(xds.data_vars))
and here is what the code above produces in a notebook :
I would like to integrate the selector for the data_vars and then depending on its dimensions have interactive maps with controls for all its dimensions (ES has (time, pres1, lat, lon) while P0 has only (time, lat, lon)) and I would like to have the controls in the sidebar and the plots in the main of the following template :
from turtle import width
from matplotlib.pyplot import title
import panel as pn
import numpy as np
import holoviews as hv
from panel.template import DefaultTheme
from pathlib import Path
import fstd2nc
import hvplot.xarray
import xarray as xr
from unicodedata import name
import hvplot
import param
from panel.interact import interact
pn.extension(sizing_mode='stretch_width')
bootstrap = pn.template.MaterialTemplate(title='Material Template', theme=DefaultTheme, )
glob_path = Path(r"C:\Users\spart\Documents\Anaconda-Work-Dir")
file_list = [str(pp).split('\\')[-1] for pp in glob_path.glob("2022*")]
phase = pn.widgets.FloatSlider(name="Phase", start=0, end=np.pi)
fileSel = pn.widgets.Select(name='Select File', options=file_list)
#pn.depends(fileSel=fileSel)
def selectedFile(fileSel):
base_path = r"C:\Users\spart\Documents\Anaconda-Work-Dir\{}".format(fileSel)
return pn.widgets.StaticText(name='Selected', value=base_path)
#pn.depends(fileSel=fileSel)
def dataXArray(fileSel):
base_path = r"C:\Users\spart\Documents\Anaconda-Work-Dir\{}".format(fileSel)
xds = fstd2nc.Buffer(base_path).to_xarray()
return xds.ES.hvplot( width=500)
bootstrap.sidebar.append(fileSel)
bootstrap.sidebar.append(selectedFile)
bootstrap.main.append(
pn.Row(
pn.Card(hv.DynamicMap(dataXArray), title='Plot'),
)
)
bootstrap.show()
EDIT : Here is a link to an example dataset which can be loaded with the following code
xds = fstd2nc.Buffer(PATH_TO_FILE).to_xarray()

Without the data file I can't easily run the code, but some observations:
If using bare functions like this rather than classes, I'd recommend using pn.bind rather than pn.depends; it really helps get the code organized better.
For a simple application like this, I'd use hvPlot .interactive: https://hvplot.holoviz.org/user_guide/Interactive.html
I can't seem to find this in the docs, but you can pull out the widgets from the result of dataXArray (or any other hvplot or holoviews object) using .widgets(), and you can then put that in the sidebar. You can then pull out just the plot using .panel(), and put that in the main area.
If that helps you get it done, then great; if not please post a sample data file or two so that it's runnable, and I can look into it further. And please submit a PR to the docs once you get it working so that future users have less trouble!

PyQGIS changing basemap crs when importing a csv

I am using PyQGIS to import a csv file with a lat and long, when doing this I am using the appropriate crs of EPSG:4326.
I'm plotting this onto Google Maps.
I load my basemap, then import my CSV. The issue is that my basemap projection then changes to 4326 and I need it to remain on 3857.
I've tried importing the basemap after the CSV and moving it down in the layers, however this still changes the projections.
import requests
from PyQt5.QtGui import *
from PyQt5.QtCore import *
from qgis.core import *
from qgis.utils import iface
from qgis import core
#Use Google Street Map as QGIS basemap.
service_url = "mt1.google.com/vt/lyrs=m&x={x}&y={y}&z={z}"
service_uri = "type=xyz&zmin=0&zmax=21&url=https://"+requests.utils.quote(service_url)
tms_layer = iface.addRasterLayer(service_uri, "GoogleSat", "wms")
#Import CSV and plot.
uri = 'file:///home/user/fred.csv?type=csv&xField=%s&yField=%s&crs=%s' % ("Site Longitude", "Site Latitude", "EPSG:4326")
layer_csv = QgsVectorLayer(uri, 'fred', 'delimitedtext')
layer_csv.isValid()
QgsProject.instance().addMapLayer(layer_csv)
I'll be the first to admit I'm a novice with QGIS!

It seems this has something to do with the application not refreshing properly as mentioned in this answer on gis stack. You may want to look into it for details.
To answer your question in brief, you can add QApplication.instance().processEvents() after QgsProject.instance().addMapLayer(layer_csv) and then use setCrs() to set your basemap CRS to whatever value you need. It will hold.
proj = QgsProject.instance()
proj.addMapLayer(layer_csv)
# This line makes the difference
QApplication.instance().processEvents()
# This sets the project CRS back to 3857
proj.setCrs(QgsCoordinateReferenceSystem(3857))

Plotting polygons onto folium with a gdf frame error

I have an issue i made a fairly simple code I just create my file then create the map and the plot it but I get an error. I want to be plotting the polygons from the file onto the map.
import pandas as pd
import folium
import geopandas as gpd
input_map = "CLUSTERS.TAB"
gdf = gpd.read_file(input_map, driver="MapInfo File")
maploc = folium.Map(location=[42.377157,-71.236088],zoom_start=11,tiles="Stamen Toner")
folium.GeoJson(gdf).add_to(maploc)
The error I get is
builtins.RuntimeError: b'no arguments in initialization list'
I have no idea what this means or how to fix it. Any input helps, Thanks.

Find all intersecting polygons in a shape file

I am trying to find out all the polygons in a shapefile through QGIS Algorithm Extract By Location and it gives me perfect results but takes too much time, around 25 hours. Now, I want it to be done by other libraries like geopandas or other libraries if possible. Can anyone suggest me which library can help?
This is what am doing in geopandas:
import itertools
import geopandas as gpd
gi = gpd.GeoDataFrame.from_file("D:\Shape_file_uploader\qgis\laneGroup.shp")
geoms = gi['geometry'].tolist()
intersection_iter = gpd.GeoDataFrame(gpd.GeoSeries([poly[0].intersection(poly[1]) for poly in itertools.combinations(geoms, 2)

I did this some time ago and if I remember correctly I used the geopandas overlay method. So the 'pseudo' code to handle this ...
from geopandas import GeoDataFrame, overlay
first_shape_gdf = GeoDataFrame.from_file('D:\Shape_file_uploader\qgis\laneGroup.shp')
second_shape_gdf = GeoDataFrame.from_file('another.shp')
intersection_gdf = overlay(first_shape_gdf, second_shape_gdf, how='intersection')
Have a look at Set-Operations with Overlay

Python mapping: plotting an electoral boundary over a street map?

I would have thought this would be so simple it would be almost example 1 in any mapping documentation. But it seems not... I want to map the boundary of an electorate over a street map, using cartopy. I can download the GIS data of the electorates in either MapInfo or ShapeFile form. When I tried to do this a year ago, the only way I could find to do it was to extract the lat/long coordinates of the MapInfo polygon, and plot them with matplotlib.
I'm trying to be a bit more elegant this year. With the MapInfo file, I can isolate my particular electorate with
import geopandas as gpd
v = gpd.read_file('VicMaps/vic-july-2018-mid-mif/E_VIC18.MIF')
cg = v.loc[7].geometry
My efforts to extract a particular single boundary from a shapefile are given below.
The other issue is that when I try to run this in jupyter, attempts at plotting a map causes the kernel (python 3.4) to crash.
There must be examples of this somewhere, but so far I haven't found an example which works with my data. This is what I have so far, cobbled together from various helpful answers to other people's questions:
import matplotlib.pyplot as plt
import cartopy.crs as ccrs
from cartopy.io.shapereader import Reader
from cartopy.io.img_tiles import OSM
shp = Reader('VicMaps/E_AUGFN3_region.shp')
fig = plt.figure(figsize=(16,16))
tiler = OSM()
ax = plt.axes(projection=tiler.crs)
ax.set_extent([144.956158, 145.085398, -37.813662, -37.690999])
for r, g in zip(shp.records(), shp.geometries()):
if r.attributes['Elect_div'] == 'Cooper':
ax.add_geometries(g, ccrs.Geodetic())
plt.show()
But what happens is that the kernel just dies "unexpectedly".
If anybody could point me in the direction of a solution, I'd be delighted! Also: I'm not wedded to cartopy; if there's a better package I'll use it.
Thanks!