I need help transalting an SQL statement regarding this dataset https://www.kaggle.com/datasets/hugomathien/soccer , into r code using dplyr. The SQL statement is : The r code that i have tried is: and i get this error : Error in dplyr::common_by(): ! by required, because the data sources have no common variables. Run rlang::last_error() to see where the error occurred. Run rlang::last_error()
Tag: dplyr
Creating a cumulative sum column with_order in R
I’m working alongside a SQL tutorial using queryparser and tidyquery in R. This has been going well until I was asked to do: Tidyquery reported that it did not support OVER functions so I am trying to replicate the OVER (PARTITION BY…) function with dplyr. This led me to with_order(order_by =… in dplyr. Now I’m struggling with getting the fun
R : x comparison (1) is possible only for atomic and list types
I am using R. In a previous post (R: Loop Producing the Following Error: Argument 1 must have names), I learned how to make a function (“create_data”) for my code. Now, I am trying to modify this function. First, I create some data to be used for this example: Here is the modified version of the function: The error results
sql to dplyr – nested select statements
I am trying to translate sql to R using the dplyr library, which I am new to. How would I do it for the following SQL? Answer
How can I translate this SQL code to R script using dplyr?
I’m currently working on a project and I want to summarize a column from a joined table twice. SQL code is this: …and the result is this: Database tables are as shown here: I hope that I have provided all the information needed. Question: How can I have the same result in R by only using dplyr library? Table names
How do you filter with a Dataframe, list, vector etc. to a table in a database in R?
I have a large set of id-s which is in a csv file. How could I filter on a database table using only that one-columned table in the csv file? For example in the ODBC database we have: TABLE 1 +–…