I’m a R beginner and having difficulty with the bike sharing capstone project: I have the following code chunks:

[innocent_sky]

I can't figure out where the problem is, but i don't have values on my "MIN' and i still have "NA" on my graph after using some codes like na.mit() and drop_na, While going through other people's project i notice they have values on their "MIN", pictures and code chunks are slated below:

aggregate(all_trips_v2$ride_length ~ all_trips_v2$member_casual, FUN = mean)
aggregate(all_trips_v2$ride_length ~ all_trips_v2$member_casual, FUN = median)
aggregate(all_trips_v2$ride_length ~ all_trips_v2$member_casual, FUN = max)
aggregate(all_trips_v2$ride_length ~ all_trips_v2$member_casual, FUN = min)

all_trips_v2 %>% 
  mutate(weekday = wday(started_at, label = TRUE)) %>% 
  group_by(member_casual, weekday) %>% 
  summarise(number_of_rides = n(),average_duration = mean(ride_length)) %>% 
  arrange(member_casual,weekday)

[nirgrahamuk]

all 4 functions you mention have na.rm parameters ; which if set to TRUE would have them ignore NA values
or like you say you could na.omit() over your data.frame and then do the calculation; you've show no sign of having done this; so we can't comment on if you have done it incorrectly. If you did do it did you remember to assign the result back to a name with <-

[innocent_sky]

@innocent_sky

na.mit() and drop_na,

After that i tried with the codes: na.mit() and drop_na, and got same results.

[M_AcostaCH]

Hi @innocent_sky, try to put a reproducible example of data.

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.…

Maybe you could put the file in a drive or other type.

[nirgrahamuk]

@innocent_sky

na.mit()

its not na.mit() it would be na.omit()

[innocent_sky]

I am afraid i don't know how to load the data in here, however the datasets is very big, it's Cyclistic’s_Trips_Data data frame head (Cyclistic's_Trip_Data)#> ride_id, rideable_type, started_at, ended_at, start_station_name, start_station_id, end_station_name, end_station_id, member_casual, ride_length, day_of_week,#> 12 months data frame from 2022_01_01 to 2022_12_12.

[innocent_sky]

My bad it's typo error, na.omit() is what i did and the NAs are still there.