This is simple if you transform your Date variable into an actual date variable instead of a character variable.
library(dplyr)
library(lubridate)
# Sample data on a copy/paste friendly format
sample_df <- data.frame(
stringsAsFactors = FALSE,
Date = c("15-Nov-17","5-Apr-18",
"4-Apr-19","16-Nov-17","6-Apr-18","21-Jun-18","30-Aug-18",
"6-Dec-18","27-Mar-19","4-Apr-19","25-Jul-19",
"17-Oct-19","19-Nov-19","23-Oct-19","15-Nov-17","5-Apr-18",
"16-Nov-17","6-Apr-18","21-Jun-18","30-Aug-18",
"6-Dec-18","27-Mar-19","25-Jul-19","17-Oct-19","15-Nov-17",
"5-Apr-18","4-Apr-19","16-Nov-17","6-Apr-18",
"21-Jun-18","30-Aug-18","6-Dec-18","27-Mar-19","4-Apr-19",
"25-Jul-19","17-Oct-19","19-Nov-19","23-Oct-19"),
Parameter = c("nitrogen","nitrogen",
"nitrogen","nitrogen","nitrogen","nitrogen","nitrogen",
"nitrogen","nitrogen","nitrogen","nitrogen","nitrogen",
"nitrogen","nitrogen","nitrogen","nitrogen","nitrogen",
"nitrogen","nitrogen","nitrogen","nitrogen",
"nitrogen","nitrogen","nitrogen","nitrogen","nitrogen",
"nitrogen","nitrogen","nitrogen","nitrogen","nitrogen",
"nitrogen","nitrogen","nitrogen","nitrogen","nitrogen",
"nitrogen","nitrogen"),
Result = c(7.97,7.47,11.63,1.14,1,
0.992,1.1,1.2,1.12,1.124,1.24,1.25,1.528,1.217,0.17,
0.1,0.083,0.09,0.36,0.17,0.09,0.09,0.09,0.12,
8.14,7.56,11.785,1.14,1,0.99,1.27,1.2,1.12,1.173,
1.24,1.36,1.765,1.381)
)
sample_df %>%
mutate(Date = dmy(Date)) %>%
filter(month(Date) %in% 6:9)
#> Date Parameter Result
#> 1 2018-06-21 nitrogen 0.992
#> 2 2018-08-30 nitrogen 1.100
#> 3 2019-07-25 nitrogen 1.240
#> 4 2018-06-21 nitrogen 0.360
#> 5 2018-08-30 nitrogen 0.170
#> 6 2019-07-25 nitrogen 0.090
#> 7 2018-06-21 nitrogen 0.990
#> 8 2018-08-30 nitrogen 1.270
#> 9 2019-07-25 nitrogen 1.240
Created on 2020-05-15 by the reprex package (v0.3.0)