landuse | Land use classification project using open source tools | Computer Vision library

I want to restructure my land use classification dataframe and add new rows and columns based on conditions of the dataframe. I've been using dplyr to try this, however the examples I have found tend to decrease the columns or rows and not increase the number of rows based off conditions. I have tried to loop through the dataset to add the rows, but want to know if there is a better way to do it in dplry? I'm open to using a different library as well but its a very large dataset of classifications and dplyr seems to work well with the dataframe?

Here is the code example of what my current dataframe looks like (df_old) and what I would like it to be in the end (df_new).

What I want to do, is everytime the Year1990-2015 changes it creates a new row. Example: ID 424, in 1990 it is 51, but in the Year 2000 it changes to 21 and remains 21 until present day. This means that the new dataframe for ID 424 should ahve two rows. One labeled Start_Year that represents the begining of the land use in 1990 as Forest (Landuse = 51) and remains Forest until it changes in 2000. Since in 2000 it is Pavement, we assume it was Forest still in 1999 and End_Year will be 1999 for the first row of ID 424. Than a new row appears for ID 424 where Start_Year is 2000 as it changed to Pavement (Landuse = 21) and remains 21 until End_year (Present day).

To add context, the dataset represents how an area changes in a city, where the numbers in Year1990-2015 are used to identify different landuse classifications( 21 = Pavement, 24 = Park, 25 = Residential, 51 = Forest, 41 = Agriculture).

I'm working on PostgreSQL in dbeaver. The database has a column addr:country and a column addr:city. The data has around 500 million rows so I have to do a ramdom sampling for testing. I intended to randomly select 1% of the data. However, the data itself could be highly biased (as there are big countries, and small countries, thus there are more rows for big countries, and less for smaller countries), and I'm thinking of a way to sample fairly. So I want to randomly select one or two rows from each city in each country.

The script I'm using is modified from someone else's query, and my script is:

I have a list of indices that I know I want to remove from my data frame.

Normally I can do this easily with just writing out the names but I don't understand why the following command works when I want to keep the rows I am deleting:

I would like to set x axis on a heatmap ggtree.

This is my code

In Gatling, I am using feeders to pass the values of the coordinates in a request, below is the code. I want on each repeat a new value from the feeder to be picked up. I am get the following error -- /mapping/v2/: Failed to build request: No attribute named 'map 30 (100.0%) x' is defined

Could someone please advice how this can be achieved. thanks.

I have a multi-column dataframe that can be divided into two categories: land use and water quality.

I would like to analyze the correlation only between water quality variables and land use variables, without there being a correlation between land use variables and a correlation between quality variables.

I am using package corrplot() spearmen method but i dont know how i can ignore correlation between categories.

Landuse = veg, wet, dry, water

Quality water = OD, DBO, DQO

I have results from a model that I extracted into a dataframe using this code: df1 <- coef(summary(mod1)). My dataframe with the model results has the estimates/model info that I want but the first column isn't registering as a column and is instead the labels for each row.

Q1) How do I make this first label column into an actual column that will show up when I try df1$?

Q2) Once I get this first column to register as a column, I'd like to separate the values at the colon so my dataframe looks like this:

I would like to calculate the shortest path between a list of destinations and an origin. But first I need to find the nodes closest to my destinations. I am getting the list of destinations from OSMNX function for a set of Points of Interests (geometries_from_place).

I'm using the helper function provided here with some modifications for distance and color. I tried it without my changes and it has the same result. I noticed if I used the 'natural' tag that water ways will extend past the figure but I'm not using it in these, only 'building'.

Code being used: