Get my FREE cheat sheets for R programming and statistics (including transcripts of these lessons) here: www.learnmore365.com/pages/membership-r-programming-data-visualization-and-research-methods
I learned this in a course last semester, it was tough at the beginning but I managed to pass. But this video would’ve been extremely useful. Nice explanation 👍
Hello Dr. Greg Martin, The videos on R programming are very interesting. I have two questions. 1. How can I impute the missing values precipitation of different stations in the basin using Multivariate Imputation by Chained Equations? 2). How can I check the quality of the precipitation and temperature data using RClimDex 1.1?
Hi, thaks for the video! When I make the ggplot checking for interations between NA and varibels, I get a plot with circles in rows, both in the false and the true grahps. Is that because my data NA varibels are really not random ? Thanks in advance
Hello Dr. Greg Martin when i execute that same code for the relationship between Ozone and wind my histogram never shows. I am getting this error "Error in `mutate()`: ℹ In argument: `...
I got this same error originally. Did you close your parenthesis on the mutate() function? airquality %>% mutate( Missing_Ozone = factor(is.na(Ozone), # true or false condition, is Ozone missing? levels = c("TRUE","FALSE"), labels = c("Missing", "Not Missing"))) %>% ggplot(aes(x=Wind, fill = Missing_Ozone)) + geom_histogram() + labs( title = "Distribution of Wind Speeds for Missing vs Non-Missing Ozone Values", x = "Wind Speed", y = "Ozone Observations", fill = "Missingness") + theme_bw()
Get my FREE cheat sheets for R programming and statistics (including transcripts of these lessons) here: www.learnmore365.com/pages/membership-r-programming-data-visualization-and-research-methods
I learned this in a course last semester, it was tough at the beginning but I managed to pass. But this video would’ve been extremely useful. Nice explanation 👍
Thanks. Glad you liked it. Thanks for the feedback. 😀
very good tutorial, thanks !
thanks
Hello Dr. Greg Martin, The videos on R programming are very interesting. I have two questions. 1. How can I impute the missing values precipitation of different stations in the basin using Multivariate Imputation by Chained Equations? 2). How can I check the quality of the precipitation and temperature data using RClimDex 1.1?
Hi there. Can’t get into this in the comment section (too complicated) but will try to create a video about it.
@@RProgramming101 Thanks. How can I reach you?
Really amazing.
Thanks
Hi, thaks for the video! When I make the ggplot checking for interations between NA and varibels, I get a plot with circles in rows, both in the false and the true grahps. Is that because my data NA varibels are really not random ?
Thanks in advance
Hello Dr. Greg Martin when i execute that same code for the relationship between Ozone and wind my histogram never shows. I am getting this error
"Error in `mutate()`:
ℹ In argument: `...
I got this same error originally. Did you close your parenthesis on the mutate() function?
airquality %>%
mutate(
Missing_Ozone = factor(is.na(Ozone), # true or false condition, is Ozone missing?
levels = c("TRUE","FALSE"),
labels = c("Missing", "Not Missing"))) %>%
ggplot(aes(x=Wind, fill = Missing_Ozone)) +
geom_histogram() +
labs(
title = "Distribution of Wind Speeds for Missing vs Non-Missing Ozone Values",
x = "Wind Speed",
y = "Ozone Observations",
fill = "Missingness") +
theme_bw()
I think dlookr package is easier in handlig missing values and outliers
Will take a look. Thanks.
I need to be an expert in data analysis i need help
Here to help.
@@RProgramming101 how can I connect with you