[SOLVED] Filtering my data frame is erasing my data frame despite correct number of rows

Filtering my data frame is erasing my data frame despite correct number of rows

I have a dataframe of transactions (roughly 76K rows). Each row has a column called START_DATE which is when the transaction started.

I am trying to filter down to transactions with START_DATE > 1/1/2023.

I am doing this:

str(A_23$START_DATE) ##IT STARTS OUT AS A CHR
A_23$START_DATE <- as.Date(A_23$START_DATE, format = "%Y-%m-%d")
str(A_23$START_DATE) ##THIS CONFIRMS IT IS A DATE
T_Date <- as.Date("2023-01-01", format = "%Y-%m-%d") ##USING A PLACEHOLDER VARIABLE TO VALIDATE STR()
str(T_Date) ##THIS CONFIRMS IT IS A DATE
A_23 <- A_23[A_23$START_DATE >= T_Date,] ##THIS CUTS THE DATAFRAME DOWN FROM 76K ROWS to 9K ROWS (IT WORKS)
head(A_23) ##EVERYTHING IS NA, THE ENTIRE FRAME

What am I doing wrong? Why is this causing all of my data to get erased but R knows how many rows?

Solution

Here is a possible solution:

library(dplyr)
library(lubridate)

    df <- data.frame(
      start_date = c("1/2/2021","5/11/2020","1/2/2021","5/11/2020"),
      item = c("A","B","C","D")
    )
    
    df <- df |> 
      mutate(start_date = as_date(dmy(start_date)))
    
    
    # filter date
    date_filter <- df |> 
      filter(!start_date %in% ymd("2021-02-01")) 

date_filter



  start_date item
1 2020-11-05    B
2 2020-11-05    D

Hope this helps!