conformal | Conformal prediction is a framework for providing accuracy | Machine Learning library

I am plotting an Indian map using plotly and geojson file. Now what I want to do is show static values on the Indian States. Currently those values are visible on hover, I want the values to be seen all the time.

This my code :

I have more than 1000 XML files that probably have the same structure. I want to create a database using data in all the files. I have never known how an XML file looked before yesterday. With the help of Google, I tried using the r-packages to load a single XML file in RStudio. But when I'm trying to convert that into a data frame, an error is occurring.

This is how file looks like: File A

I have been using the "Gridding METAR Observations" example code from MetPy Mondays #154 for some time without any issues. Up until recently, I passed the entire data set without restrictions (except to exclude stations near the South Pole, which were blowing up the Lambert Conformal transformation.)

Recently, I tried to restrict the domain of the METAR data I process to North America. At this point, MetPy's interpolate_to_grid function seems to be returning nan when it did not previously. Since my region of interest is far removed from the boundaries of the data set, I expected no effect on contours derived from the interpolated data; instead there is a profound effect (please see the example below.) I tried to interpolate over regions of missing data (nan) using SciPy's interp2d function, but there are too many nan to overcome with that "bandaid step".

Question: Is this expected behavior with interpolate_to_grid, or am I using it incorrectly? I can alway continue to use the entire data set, but that does slow things down a bit. Thanks for any help understanding this.

In the following example, I am using the 00Z.TXT file from https://tgftp.nws.noaa.gov/data/observations/metar/cycles/, but I am seeing this with METAR data from other sources.

I'm trying to plot data from a text file (organized with latitude, longitude, and pollen flux values) as a raster grid in Python. I'm using the code for Choropleth Map on https://autogis-site.readthedocs.io/en/latest/notebooks/L5/02_interactive-map-folium.html to try to display the data. My GeoPandas geodataframe has point geometries; however, it looks like the geometry of the points in the tutorial are already multipolygons, which I assume are the squares in the grid. How do I convert my data (assuming each latitude/longitude point is the center of a pixel in a grid) into gridded geopandas (geodataframe) data? The projection I'll be using is Lambert Conformal Conic projection.

To clarify what my geodataframe looks like, when doing gdf.head(10).to_dict(), it looks like this

I have two dataframes, df_points and df_polygon; I want to match based on points being within a given polygon. However, I am running into a few errors due to mismatch of CRS. This is what I have done:

First, I needed both of these to be sf class; I checked the classes / CRS and converted as follows (running with output):

I am new to geospatial data & trying to crop a tif file raster object using a shapefile by referring https://www.youtube.com/watch?v=UP2Za1TizOc.

I have tried below code by referring the above video & seems like there is a projection issue:

My goal here is to make a geodataframe from a couple of columns of coordinates in an existing dataframe, take those 1677 geographic points and add a buffer circle around each, then union the resulting polygons into a multipolygon. Where I keep getting wrapped around the axle is the .buffer() part of geopandas doesn't seem to be using the units of measure for the CRS I've selected.

I'm working on the joukowsky transformation for plotting airfoils and I'm trying to do so with python. The conformal mapping should be pretty straight forward but can't seem to find a guide on how to approach the problem on python.

by the math:

I am not an expert with maps and coordinate systems. I need to convert longitude and latitude coordinates into LCC (Lambert conformal conic projection). I have a list of city coordinates that I need to plot in a map. The problem is that the projection of the map is "+proj=lcc +lat_1=43 +lat_2=62 +lat_0=30 +lon_0=10 +x_0=0 +y_0=0 +ellps=intl +units=m +no_defs".

What can I do so that the longitude and latitude coordinates are converted into the projection of the map?

Below a tibble with the cities and the coordinates: