After converting data from string , it shows a values as NA.

[Avishkar]

#changing data type from string to date and time
calories$ActivityMinute <- as.POSIXct(calories$ActivityMinute, format="%Y/%m/%d %H:%M:%S", tz="UTC")
heart_rate$Time <- as.POSIXct(heart_rate$Time, format="%Y/%m/%d %H:%M:%S", tz="UTC")
steps$ActivityMinute <- as.POSIXct(steps$ActivityMinute, format="%Y/%m/%d %H:%M:%S", tz="UTC")
#check if changes has been made correctly
class(calories$ActivityMinute)
class(heart_rate$Time)
class(steps$ActivityMinute)

At first when i ran this on r markbook it worked perfectly fine but now it shows NA in that column.

sample of data Calories data set
ID TIME VALUE
|1|2022484408|4/12/2016 7:21:00 AM|97||
|2|2022484408|4/12/2016 7:21:05 AM|102||
|3|2022484408|4/12/2016 7:21:10 AM|105||
|4|2022484408|4/12/2016 7:21:20 AM|103||
|5|2022484408|4/12/2016 7:21:25 AM|101||
|6|2022484408|4/12/2016 7:22:05 AM|95||

[jrkrideau]

Welcome to the forum.

We need a reproducible example (reprex)

FAQ: How to do a minimal reproducible example ( reprex ) for beginners

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.…

[andresrcs]

@Avishkar

format="%Y/%m/%d %H:%M:%S",

The sample data you have posted has a %d/%m/%Y %H:%M:%S format, not %Y/%m/%d %H:%M:%S, If I change that everything works as expected.

# Sample data in a copy/paste friendly format, replace this with your own data frame
calories <- data.frame(
  stringsAsFactors = FALSE,
                ID = c(2022484408,2022484408,
                       2022484408,2022484408,2022484408,2022484408),
              TIME = c("4/12/2016 7:21:00 AM",
                       "4/12/2016 7:21:05 AM","4/12/2016 7:21:10 AM",
                       "4/12/2016 7:21:20 AM","4/12/2016 7:21:25 AM","4/12/2016 7:22:05 AM"),
             VALUE = c(97, 102, 105, 103, 101, 95)
)

# Relevant code
calories$TIME <- as.POSIXct(calories$TIME, format="%d/%m/%Y %H:%M:%S", tz="UTC")

calories
#>           ID                TIME VALUE
#> 1 2022484408 2016-12-04 07:21:00    97
#> 2 2022484408 2016-12-04 07:21:05   102
#> 3 2022484408 2016-12-04 07:21:10   105
#> 4 2022484408 2016-12-04 07:21:20   103
#> 5 2022484408 2016-12-04 07:21:25   101
#> 6 2022484408 2016-12-04 07:22:05    95

^{Created on 2022-01-18 by the reprex package (v2.0.1)}