filter function in dplyr errors: object 'name' not found

It does seem like you are getting the stats::filter function and not the dplyr one. To make sure you get the right one, use the notation dplyr::filter.

d = data.frame(x=1:10,
 name=c("foo","bar","baz","bar","bar","baz","fnord","qar","qux","quux"))

filter(d, !grepl("ar|ux", name))
Error in grepl("ar|ux", name) : object 'name' not found

dplyr::filter(d, !grepl("ar|ux", name))
  x  name
1 1   foo
2 3   baz
3 6   baz
4 7 fnord

You don't even need to do library(dplyr) for this to work - you do need dplyr installed though.

This works for functions from any package.

What is causing 'object not found' error in filter() with the across() function?

Sorry for omitting this in my previous suggestion to you. Unfortunately, your original question was closed before I could post it as an answer:

If you want your function to resemble dplyr, here's a few
modifications you can make. Write your function header as
function(filename, opp, ...) verbatim. Then, replace !is.na(ID)
with across(..., ~ !is.na(.x)) verbatim. Now, you can call
extract_ids() and, just as you would with any dplyr verb, you can
specify any selection of columns you want to filter out NAs:
extract_ids(filename = "farmers.csv", opp = "farmers", rid, another_column_you_want_without_NAs).

Object Not Found

As MrFlick rightly suggests in their comment, you should wrap ... with c(), so everything you pass in ... is interpreted as the first argument to across(): a single tidy-selection of columns from df:

extract_ids <-  function(filename, opp, ...) {
  # ...

  # Filter and select
  df_id <- df %>%
    # This format is preferred for dplyr workflows with pipes (%>%).
    filter(across(c(...), ~ !is.na(.x)) & gc == 1) %>%
    select(...)

  # ...
}

Without this precaution, R interprets rid and cintid as multiple arguments to across(), rather than as simply columns named by the first argument (the tidy-selection).

Variable Names in the Filepath

To get those variable names within your filepath, use

extract_ids <-  function(filename, opp, ...) {
  # ...
  
  # Expand the '...' into a list of given variable names, which will get pasted.
  path <- c("/Users/stephenpoole/Downloads/", opp, "_", match.call(expand.dots = FALSE)$`...`, ".csv")

  # ...
}

though you might want to consider replacing match.call(expand.dots = FALSE)$`...`, which currently mushes together the variable names:

"/Users/stephenpoole/Downloads/farmers_ridcintid.csv"

In exactly the same place, you might use the expression paste(match.call(expand.dots = FALSE)$`...`, collapse = "-"), which will separate those variable names using -

"/Users/stephenpoole/Downloads/farmers_rid-cintid.csv"

or any other separator of your choice that gives a valid filename.

filter does not work properly in dplyr (Object not found)

In this line

df %>% select(Number) %>% filter(Letter == 'a')

The first call to select leaves you with a data table containing only one column (Number). Which is exactly why filter is complaining - you threw the Letter column away.

In the second call, you filter on Letter first, then throw the column away.

So, filter is working exactly as it should. There is no "general rule" for this beyond either "do things in a sensible order" or "garbage in garbage out"

object not found in filtering

As @Edward mentioned you are probably using stats::filter. We can reproduce the same error message using sample mtcars dataset.

stats::filter(mtcars, cyl > 12)

Error in stats::filter(mtcars, cyl > 12) : object 'cyl' not found

Use dplyr::filter and you don't need to specify four conditions separately. Use :

data_filtered <- dplyr::filter(data, !Item %in% c("INFUSION SET (L.E 15)",
                "INFUSION SET (L.E 4)","SYRINGE 3ML","CANNULA (22) BLUE"))

which is same as using subset in base R:

data_filtered <- subset(data, !Item %in% c("INFUSION SET (L.E 15)",
    "INFUSION SET (L.E 4)","SYRINGE 3ML","CANNULA (22) BLUE"))

Or

data_filtered <- data[!data$Item %in% c("INFUSION SET (L.E 15)",
           "INFUSION SET (L.E 4)","SYRINGE 3ML","CANNULA (22) BLUE"), ]

dplyr::select Object not found in self-made function

There are two issues with your function. The first error arises because calendario is no column of the df passed to the function. Simply remove the df$ when specifying the aesthetics. Second. Even when removing the df$ you set the y-aesthetic equal the string in variable dato, i.e. "indice_covid" in your example. That is for every date you have the same value "indice_covid". That's why you get a flat line. To tell ggplot2 that you want a the column datoof the df you have to convert it to a symbol using sym and the bang-bang-operator !!, i.e. !!sym(dato). Try this:

library(ggplot2)
library(dplyr)

plot_by_reg <- function(df, reg, dato) {

  df %>% 
    dplyr::filter(denominazione_regione == reg) %>%
    dplyr::mutate(calendario = format(as.Date(paste(mese,giorno , sep = "-" )  , format = "%m-%d" ), "%m-%d")) %>%
    dplyr::select(c(denominazione_regione, calendario, all_of(dato))) %>%
    #ggplot(aes(x=df$calendario, y=df$dato)) +
    ggplot(aes(x = calendario, y = !!sym(dato))) +
    geom_line(aes(group = 1)) +
    theme_dark()
}

plot_by_reg(df = data.moving, reg = "Toscana", dato = "indice_covid")

^{Created on 2020-05-25 by the reprex package (v0.3.0)}

My dplyr::filter function keeps displaying different errors

From the error message it seems AF2 is a matrix, you can change it to dataframe and then your code should work.

AF2_MAF <- AF2 %>% as.data.frame() %>% filter (Frequency>=0.1)

Alternatively, you can also subset the matrix.

AF2_MAF <- AF2[AF2[, "Frequency"] >= 0.1, ]

Is there something wrong with this Filter function code in R?

You need library(dplyr) after install.packages("dplyr").

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