r: Error in mutate_impl(.data, dots) : Evaluation error: object '72L' not found

Question

I am trying to run frame_calendar for my univariate time series data in r. When I try to compute the calendar layout for the data frame, I am getting the following error.

Error in mutate_impl(.data, dots) : Evaluation error: object '72L' not found.

From similar threads, I see the evaluation error: object ' ' not found is usually for an object the users have input in the code. However, in my case, I am not referring to any '72L' in my code. And it is not in my data set as well. Can you please help me figure out how to fix this error? Any help is much appreciated.

Here is a part of my data.

Date_Time   Time    Date    Year    Month   Mdate   Day Hours_Time  Hourly_Counts
1/1/2015 0:00   0:00:00 2015-01-01  2015    January 1   Thursday    1   72
1/1/2015 1:00   1:00:00 2015-01-01  2015    January 1   Thursday    2   48
1/1/2015 2:00   2:00:00 2015-01-01  2015    January 1   Thursday    3   53
1/1/2015 3:00   3:00:00 2015-01-01  2015    January 1   Thursday    4   84
1/1/2015 4:00   4:00:00 2015-01-01  2015    January 1   Thursday    5   68

Here's my code.

newdata <- read.csv("D:/NEWDATA.csv")
attach(newdata)
View(newdata)

newdata[,3] <- as.Date(Date, origin = "1/1/2000")
attach(newdata)
View(newdata)


library(dplyr)
# compute the calendar layout for the data frame
calendar_df <- newdata %>%
  filter(Year == 2015) %>%
  frame_calendar(x = Time, y = Hourly_Counts, date = Date)

Answer 1

The main problem here is that when you attach() your data frame first you mask a number of objects that you need. Generally, don't use attach . If you want to work with an attached data set, use it inside a call to with , and certainly don't combine this with dplyr or other tidyverse functions.

With a clean environment (no data or namespaces attached), use dplyr methods throughout, like this. Other than not attaching, notice the two other changes to your code. (1) use mutate to set the Date column within the dplyr pipe. (2) x = Hours_Time , rather than Time . If you've previously run attach(new_data) , do detach(new_data) first, UNTIL you have a clean environment. If you've run it multiple times, you're going to have to detach multiple times.

library(dplyr)
library(sugrrants)
new_data %>%
  mutate(Date = as.Date(Date, origin = "1/1/2000")) %>%
  frame_calendar(x = Hours_Time, y = Hourly_Counts, date = Date)
#       Date_Time    Time Year   Month Mdate      Day Hours_Time Hourly_Counts       Date
# 1 1/1/2015 0:00 0:00:00 2015 January     1 Thursday          1            72 2015-01-01
# 2 1/1/2015 1:00 1:00:00 2015 January     1 Thursday          2            48 2015-01-01
# 3 1/1/2015 2:00 2:00:00 2015 January     1 Thursday          3            53 2015-01-01
# 4 1/1/2015 3:00 3:00:00 2015 January     1 Thursday          4            84 2015-01-01
# 5 1/1/2015 4:00 4:00:00 2015 January     1 Thursday          5            68 2015-01-01
#   .Hours_Time .Hourly_Counts
# 1    1.454167      0.6833333
# 2    1.691667      0.0500000
# 3    1.929167      0.1819444
# 4    2.166667      1.0000000
# 5    2.404167      0.5777778

Data:

new_data <- read.table(text = "Date_Time   Time    Date    Year    Month   Mdate   Day Hours_Time  Hourly_Counts
'1/1/2015 0:00'   0:00:00 2015-01-01  2015    January 1   Thursday    1   72
                       '1/1/2015 1:00'   1:00:00 2015-01-01  2015    January 1   Thursday    2   48
                       '1/1/2015 2:00'   2:00:00 2015-01-01  2015    January 1   Thursday    3   53
                       '1/1/2015 3:00'   3:00:00 2015-01-01  2015    January 1   Thursday    4   84
                       '1/1/2015 4:00'   4:00:00 2015-01-01  2015    January 1   Thursday    5   68", header = TRUE, stringsAsFactors = FALSE)