ggplot-Bellabeat

[Panagiotis_Emmanouil]

Hi all,
I have created the following tibble working with Bellabeat dataset:
daily_activity_summary_all<-
daily_activity%>%
select(-TrackerDistance,-VeryActiveDistance,-ModeratelyActiveDistance,-LightActiveDistance ,-VeryActiveMinutes,
-FairlyActiveMinutes,-LightlyActiveMinutes,-LoggedActivitiesDistance)%>%
mutate(ActiveDistance=(daily_activity$VeryActiveDistance+daily_activity$ModeratelyActiveDistance+
daily_activity$LightActiveDistance),
ActiveMinutes=(daily_activity$VeryActiveMinutes+daily_activity$FairlyActiveMinutes+
daily_activity$LightlyActiveMinutes))%>%
group_by(Id)
I want to create a point graph adding a trend line using the following function:
ggplot(data=daily_activity_summary_all)+
geom_smooth(mapping=aes(x=ActiveMinutes, y=Calories))+
geom_point(mapping=aes(x=ActiveMinutes, y=Calories))
Unfortunately the following error message is shown:
geom_smooth() using method = 'loess' and formula 'y ~ x'
Any idea what I am doing wrong?
Many thanks in advance
Panos

[M_AcostaCH]

@Panagiotis_Emmanouil

ggplot(data=daily_activity_summary_all)+
geom_smooth(mapping=aes(x=ActiveMinutes, y=Calories))+
geom_point(mapping=aes(x=ActiveMinutes, y=Calories))
Unfortunately the following error message is shown:
geom_smooth() using method = 'loess' and formula 'y ~ x'

Make sure that ActiveMinutes and Calories are the correct column names in your daily_activity_summary_all dataset.

For better help try to load 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.…

Other way is :

# paste the result of dput()
dput(daily_activity_summary_all[30 ,  ]) # for first 30 rows and all columns.

[EconProf]

@Panagiotis_Emmanouil

geom_smooth() using method = 'loess' and formula 'y ~ x'

This is information about the smoothing method used, not an error message. From the documentation for geom_smooth():

Smoothing method (function) to use, accepts either NULL or a character vector, e.g. "lm", "glm", "gam", "loess" or a function, e.g. MASS::rlm or mgcv::gam, stats::lm, or stats::loess. For method = NULL the smoothing method is chosen based on the size of the largest group (across all panels). stats::loess() is used for less than 1,000 observations; otherwise mgcv::gam() is used with formula = y ~ s(x, bs = "cs") with method = "REML".

Also, I would not get rid of variables just before calculating the totals of those variables.

daily_activity_summary_all <- daily_activity %>% 
  mutate(ActiveDistance = VeryActiveDistance + ModeratelyActiveDistance + LightActiveDistance,
         ActiveMinutes = VeryActiveMinutes + FairlyActiveMinutes + LightlyActiveMinutes
         ) %>%
  select(-c(TrackerDistance, VeryActiveDistance, ModeratelyActiveDistance, LightActiveDistance,
         VeryActiveMinutes, FairlyActiveMinutes, LightlyActiveMinutes, LoggedActivitiesDistance
         ) %>%
  group_by(Id)