cmr | Project repo for Learning Category | 3D Printing library

I have a macro, which I would like after the last msgbox and after clicking "YES" to go next part of macro (open file), but when i clicked YES Macro stops working without error, as if I didn't know what to do next.

1. I'm trying to add an aggregate function to my choropleth. On the latter I had managed, thanks to @RobRaymond, to obtain an animation by year while displaying the countries with a missing value with their names.

On the Plotly site [https://plotly.com/python/aggregations/] I saw that we could obtain a mapping with aggregates.

I tried to add it to my code but I can't get my expected result. What did I miss?

My code:

I have this gradel.settings

I have a field called MER_DATA in a snowflake table having a value as shown below:

[43,44.25,44.5,42.75,44,44.25,42.75,43,42.5,42.5,36.75,42.25,42.75,43.25,43.25,43.25,42.75,43.5,42,43,43.75,43.75,43.25,41.75,43.25,42.5,43.25,42.75,43.25,43.5,43.25,43.25,43.75,...]

Each row has approximately 4k(This varies from row to row)numbers in them and the data type of the field is varchar(30000). The data is around 700k rows

Now I want to calculate the standard deviation of each row using the numbers present in the list shown above.

I have tried doing this in MySQL using the following query:

I have a problem with a macro, I have a sample file with a button that I would like to use to run two files in the background. One wb = this is a template and wbMe pli with data that I would like to copy to wbMe. However, when I run the code, I get subcprite out of range. Where I have an error, such a sheet exists + there is data there in the cell

I downloaded some tiles using NASA EARTHDATA for the NASADEM Slope and Curvation Global 1 arc second V001 data set. When I extracted the files, I saw the filenames followed the pattern: "TileLocation.Variable". For example, a tile with slope data located on the eastern Mediteranian is called: "n36e035.slope". I was surprised the file extension was ".slope" and not ".tif".

When I tried reading the file into R with r <- raster::raster("Filepath/n36e035.slope") I get an error, because the file structure is not a tif or geotiff. I want to read multiple tiles for each variable (slope, curvature, etc.), merge, crop to my study area, then write out the combined raster to my local device as a .tif file. That way the DEM file format and data structure will match the other rasters I have.

My preferred language is R, but if there's another open-source way to change the file format from this NASA-specific extension to a .tif then I can use that. I tried looking online, but all the tutorials used Google Earth Engine or Arc and didn't allow me to save the combined .tif files locally.

You can download the n36e35 zip here and the n35e35 zip here. You may need to log-in to NASA EARTHDATA to view and download the DEM tiles. The overview is here and the user guide is available here, but the user guide is more about how the data set was made, not how to read it in or change the data format. One strange note is that the DEM this data set is based off of has an .hgt file extension, which I can easily read into R with the raster::raster function.

I have 3 tables as follows:

DXBusinessPolicy_Policy

DXBusinessPolicy_Service

DXBusinessPolicy_PolicyService

Here is my stored procedure:

I have a dataset with about 50 columns (all indicators I got from World Bank), Country Code and Year. These 50 columns are not all complete, and I would like to fill in the missing values based on an lm fit for the column for that specific country. For example:

Doing this for a single country and a single column is absolutely fine when following these steps here: Filling NA using linear regression in R

However, I have over 180 different countries I want to do this to. And I want this to work for each indicator per country (so 50 columns total) So in a way, each country and each column would have its own linear regression model that fills out the missing values.

Here is how it looked after I did the steps above: This is the expected output for ONE column. I would like to do this for EVERY column by individual country groups.

However, the data looks like this:

There are numerous countries and columns that I want to perform this on just like the post above.

This is for a project I am working on for my data-mining / statistics class. Any help would be appreciated and thanks so much in advance!

EDIT

I tried this:

I have 50x49 matrix A that has 49 linearly independent columns. However, my software (octave) tells me its rank is 44:

1. Is it due to some computational error? If so, then how to prevent such errors?

2. If the software was able to correctly calculate rref(A), then why did it fail with rank(A)? Does it mean that calculating rank(A) is more error prone than calculating rref(A), or vice versa? I mean rref(A) actually tells you the rank, but here's a contradiction.

P.S. I've checked, Python makes the same error.

EDIT 1: Here is the matrix A itself. The first 9 columns were given. The rest was obtained with polynomial features.

EDIT 2: I was able to found a similar issue. Here is 10x10 matrix B of rank 10 (and octave calculates its rank correctly). However, octave says that rank(B * B) = 9 which is impossible.