library(dplyr)
library(lubridate)

# Create a sample data frame with datetime series

data = read.csv('https://docs.google.com/spreadsheets/d/e/2PACX-1vQP0OK8q9x5XJa9T_DrOr2Hua_MRbW4WrdIRcZszYHtSodmMso5gFp3ieHp9nRjs2zGdnB9lwhpiBXp/pub?gid=388995206&single=true&output=csv')

#head(data)

data$DateTime = as.POSIXct(paste(data$Date, data$Time), format ="%d/%m/%Y %H:%M:%S")

head(data)

data = data[,c('DateTime','Name','Amount')]



#typeof(data$Date)

#data$Date = as.POSIXct(data$Date, format="%d/%m/%Y %H:%M:%S")
#
#typeof(data$Date)

head(data)

#df <- data.frame(
#  DateTime = as.POSIXct(c("2023-01-05 08:00:00", "2023-02-10 10:30:00", "2023-03-15 14:45:00", "2023-04-20 18:20:00")),
#  Value = c(10, 15, 20, 25)
#)

#typeof(df$Date)

# Define the target month and year

#data = subset(data,format(Date, "%m") == "09")

#print(data)

target_month <- 9  # February
target_year <- 2023

# Filter datetime values based on the target month and year
filtered_df <- data %>%
  filter(month(DateTime) == target_month, year(DateTime) == target_year)

# Print the filtered data frame
print(filtered_df)