Your viewer, or the website, has some problem with the fonts. Perhaps your browser does not get access to the defined fonts. Works for me, though, and this is how it should look:
Coordinates are expressed as degrees, minutes, and seconds. Try the file downloads https://www.legislation.gov.au/Details/F2012L01081/Download.
I have the same issue than you ...
It seems to be a problem with the website, and the intended rendering should be using the usual degrees, minutes and seconds symbols: °, ′, and ″. As noted by other users, different browsers and PDF readers behave differently.
If you look at the website's header, you can see that it explicitly claims that the page is UTF-8:
$ curl -v 'https://www.legislation....
Your data contains a few header lines that probably cause some problem. When importing, be sure to set the Number of header lines to discard to 5 (or as many lines there are before the actual data starst) and check the box near to First record has field names.
Check out the preview at the bottom of how your data are imported. Does it look similar? Each ...
Unfortunately I am not sure of the version of QGIS you are running, but this should apply to most QGIS 3.x versions.
When you add a map to the layout, you can access the map item properties.
From the screenshot provided, you seem to be accessing the "Map Grid Properties".
The item properties for your map will have icons under the map name - default ...
You can try BigDataCloud's reverse geocoding API: https://www.bigdatacloud.com/geocoding-apis/reverse-geocode-to-city-api
This API is based on the administrative/non-administrative boundary and provides the name of the smallest region which can be land or water.
You can easily get bounding box using fiona.
The minimum bounding rectangle (MBR) or bounds of the collection’s
records is obtained via a read-only bounds attribute.
shp_file = 'a_polygon_shapefile.shp'
c = fiona.open(shp_file)
c.bounds # Returns (minx, miny,...
May not be the most elegant solution but the file can be converted to CSV with the following python code:
import numpy as np
import pandas as pd
from netCDF4 import Dataset
You can use the select by location tool to select all points that fall inside the polygon. Set the points as input, select are within and the polygon as By comparing to the features from (see screenshot). You can than right click on the point layer / export / Save Selected Features As… and choose MS Office Open XML Table as output format to save only the ...