silt | progress | Functional Programming library

How do I make this more efficient? I feel like I should be able to do this without looping through the entire dataframe. Basically I have to split the column CollectType, into multiple columns depending on the the value in column SSampleCode.

I have recreated a common geoscientific plot using Matplotlib. It shows the grain size distribution of a soil sample and is used for soil classification.

Basically, a soil sample is placed in a stack of sieves, which is then shaked for a certain amount of time, and the remaining weight of each grain fraction is then plotted onto the diagram (see attached image below).

An important use for this type of diagram, is to determine two parameters known as D60 and D10, which is the grain size at 60 and 10 percent passing, respectively (see orange dots in diagram). I have interpolated these values with a function using np.interp, but oddly enough these points fall outside of the line plotted by Matplotlib. Can anyone give me a hint where I'm going wrong with this? They should intersect the line where y = 10 and y = 60 exactly.

The data looks like this:

In Matlab, creating an empty vector that will later be filled looks like this:

I have a dataframe of many variables (soil properties) for 11 legumes in 2 different locations. first few columns of the data is shown below.

i have a dataframe of variables for 11 species of plants recorded in 2 locations. for each specie, I am attempting to compare the mean of variables between two different locations using a t.test(or wilcoxon test).

Here is the first few rows of my data

I'm a beginner in r and I've been trying to find how I can plot this graphic.

I have 4 variables (% of gravel, % of sand, % of silt in five places). I'm trying to plot the percentages of these 3 types of sediment (y) in each station (x). So it's five groups in x axis and 3 bars per group.

I've got a data set that has many observations for a given location. Each observation (defined by a site which has multiple columns of descriptors) contains a measurement (also defined by multiple columns of descriptors). As a pared down example:

I'm getting an error in my code that (the first in the main if and the main if else) value of tn in the if statement is never used, although the other assigned value with above it is okay, and other tn values are okay, and I used tn at the end as in a textview. so the application skips it and uses the next tn value..

I've got three global soil texture rasters (sand, clay and silt). I want to merge these rasters into one raster with two categories (coarse and fine) based on relative percentages of sand, clay and silt. I've done this before when working with dataframe in this way: