combine | Visual programming environment inspired by https | Frontend Framework library

I have a function on a Google Sheet that combines 3 different ImportRange tables from 3 different sheets, and queries them so that any missing data/empty lines are cut out. The problem I'm having is that I want to add a column at the start of the list that specifies which sheet each row originated from, but I'm not sure how to do this, as I am unable to edit each source sheet.

This is my function so far:

I have a dataset that was recorded by observation(each observation has its own row of data). I am looking to combine/condense these rows by the plant they were found on - currently a character variable. All other columns are numerical vales.

EX:

This is the raw data |Sci_Name|Honeybee_count|Other_bee_Obsevrved|Stem_count| |---|---|---|---| |Zizia aurea|1|5|10| |Asclepias viridiflora|15|1|3| |Viola unknown|0|0|4| |Zizia aurea|0|2|6| |Zizia aurea|3|6|3| |Asclepias viridiflora|8|2|17|

and I want:

I am currently pulling this data from a CSV already in table form. I have been attempting to create a new table/data frame with one entry of each plant species, and blanks/0s for each other variable, which I can then use to c-binding the two together. This, however, has been clunky at best and I am having trouble figuring out how to have each row check itself. I am open to any approach, let me know what you think!

Thanks :D

So I have dataframe (result of bad joining I suppose) which looks like this:

And I want to squeeze it such that same column names align having only one column each as in:

It is guaranteed that there will be only one non-nan value for each row and column combination which I checked using a couple of notna() checks. There are infact a large number of columns and a large number of indices. I just posted a sample dataframe for simple problem reproduction. I tried looking at squeeze() and now trying to combine them via splitting and joining but far from an ideal solution

I have a dataset with the name of Danish ministers and their position from 1990 to 2020 (data comes from dataset called WhoGovern; https://politicscentre.nuffield.ox.ac.uk/whogov-dataset/). The dataset consists of the ministers name, the ministers position, the prestige of that position, and the year in which the minister had that given position.

My problem is that some ministers are counted twice in the same year (i.e., the rows aren't unique in terms of name and year). See the example in the picture below, where "Bertel Haarder" was both Minister of Health and Minister of Interior Affairs in 2010 and 2021.

I want to create a dataset, where all the rows are unique combinations of name and year. However, I do not want to remove any information from the dataset. Instead, I want to use the information in the prestige column to combine the duplicated rows into one. The observations with the highest prestige should be the main observations, where the other information should be added in a new column, e.g., position2 and prestige2. In the example with Bertel Haarder the data should look like this:

(PS: Sorry for bad presenting of the tables, but didn't know how to create a nice looking table...)

Here's the dataset for creating a reproducible example with observations from 2010-2020:

I have a table which stores student admission details and the admission date. Admission Date is bifurcated into multiple rows and I would like to combine the values from the three rows into a single row.

I wish to move a large set of files from an AWS S3 bucket in one AWS account (source), having systematic filenames following this pattern:

I have a dataframe where I want to group rows based on a column. Some of the columns in the rows I want to sum up and the others I want to aggregate as a list.

I have a data frame with the name of the objects, the values of each one, and another column with the type of the object ('A', 'B', 'C'). Something like that (I can't put here my data because the data frame is too large, but this example may help)

I want to plot the boxplot of all the objects (this means A, B and C together), and the objects of the type 'A' and 'B'. Three boxplots in total. But doing :

ggplot(data, aes(x=type, y= values))+ geom_boxplot()

I get the boxplots of the types A, B, and C, obviously, but what I want is have a boxplot with all the objects, another with the objects type A and another with the object type B.

And when I try to do it in another way I get the error:

I am trying to run a simple parallel program on a SLURM cluster (4x raspberry Pi 3) but I have no success. I have been reading about it, but I just cannot get it to work. The problem is as follows:

I have a Python program named remove_duplicates_in_scraped_data.py. This program is executed on a single node (node=1xraspberry pi) and inside the program there is a multiprocessing loop section that looks something like: