automating-gis-processes / csc18 Goto Github PK

Hi!

This Script has a limit on how many files it can merge and is dependant on the size of your RAM.

How would you incorporate the ability for the script to not do everything in memory, but create a virtual dataset?

Thanks so much!

When applying the user defined function nearest() to the GeoDataFrame df1 you get the below error:

AttributeError: 'Series' object has no attribute 'get_values'

This is caused by this line in the function:

value = df2[nearest][src_column].get_values()[0]

And that's because pandas.DataFrame.get_values() was deprecated in Pandas since version 0.25.0 (I'm using Pandas v1.0.4 and Geopandas v0.7.0).

The below code works:

value = df2[nearest][src_column].values[0]

This is the first time the shapefile addresses_epsg3879.shp has been mentioned.

To go ahead with the course, I referred to the shapefile addresses.shp we created back in Lesson 3 from addresses.txt

The following code:

# Replace No Data values (-1) with large number (999)
grid = grid.replace(-1, 999)

Fails with the below error:

TypeError: Value should be either a BaseGeometry or None, got 999

Replaced with the below code, which limits the change to the first 14 columns (i.e. geometry column excluded):

for col in grid.columns[:14]:
    grid[col].replace(-1, 999, inplace=True)

Starting in v0.20.0, the .ix indexer is deprecated, in favor of the more strict .iloc and .loc indexers.

The ix indexer was completely removed in v1.0.0.

The below command:

classifier = ps.Natural_Breaks.make(k=n_classes)

Fails with the below error:

module 'pysal' has no attribute 'Natural_Breaks'

I had to use the following apporach instead (i.e. mapclassify instead of pysal):

import mapclassify as mc
classifier = mc.NaturalBreaks(y=acc[['pt_r_tt']], k=n_classes)

Hello,
first of all I would like to express my greatest respect and gratitude. The course is wonderful, I've been looking for it for a long time.
But I have a request: It would be nice if you could add more examples for visualization. It would be especially nice if the visualization could be done directly in the Jupyter notebook. I would like to be able to display points and polygons and all analyses graphically.

Thanks in advance

The tif files that are downloaded in the Automatize data download Tutorial are no longer available. A 404 error occurs if you try to open the download links.

The below command:

buildings = ox.buildings_from_place(place_name)

Is failing with the below error:

module 'osmnx' has no attribute 'buildings_from_place'

I had to use this instead:

buildings = ox.footprints_from_place(place_name)

NOTE: it seems .buildings_from_place() was removed in v10.

Hi,
Thanks for putting such a great material.
I have a question.
Is there any way to analyze the DEM or (.tif files), visually as we do in our GIS softwares?
I am looking for a functionality like:
Suppose I have a tif file. It is a DEM. So I want to select a polygon using mouse clicks and extract the information of it.