Error nas introduced by coercion

Как исправить в R: NA, представленные Coercion

Одно распространенное предупреждающее сообщение, с которым вы можете столкнуться в R:

Это предупреждающее сообщение появляется, когда вы используете as.numeric() для преобразования вектора в R в числовой вектор, а в исходном векторе есть нечисловые значения.

Чтобы было ясно, вам не нужно ничего делать, чтобы «исправить» это предупреждающее сообщение. R просто предупреждает вас о том, что некоторые значения в исходном векторе были преобразованы в NA, потому что их нельзя преобразовать в числовые значения.

Однако в этом руководстве описаны точные шаги, которые вы можете использовать, если вы вообще не хотите, чтобы это предупреждающее сообщение отображалось.

Как воспроизвести предупреждающее сообщение

Следующий код преобразует вектор символов в числовой вектор:

R преобразует вектор символов в числовой вектор, но отображает предупреждающее сообщение NAs, введенное принуждением, поскольку два значения в исходном векторе не могут быть преобразованы в числовые значения.

Метод № 1: подавить предупреждения

Один из способов справиться с этим предупреждающим сообщением состоит в том, чтобы просто подавить его с помощью функции submitWarnings() при преобразовании вектора символов в числовой вектор:

R успешно преобразует вектор символов в числовой вектор без отображения каких-либо предупреждающих сообщений.

Способ № 2: заменить нечисловые значения

Один из способов избежать предупреждающего сообщения — заменить нечисловые значения в исходном векторе пробелами с помощью функции gsub() :

R успешно преобразует вектор символов в числовой вектор без отображения каких-либо предупреждающих сообщений.

Дополнительные ресурсы

В следующих руководствах объясняется, как устранять другие распространенные ошибки в R:

Источник

R Warning Message: NAs Introduced by Coercion (Example)

This article explains how to debug the warning message “NAs introduced by coercion” in the R programming language.

The content of the post is structured as follows:

Let’s dive into it…

Creation of Example Data

First, I’ll have to create some example data.

vec Example 1: Reproduce the Warning Message: NAs Introduced by Coercion

In this example, I’ll show how to replicate the warning message “NAs introduced by coercion” when using the as.numeric function in R. Let’s apply the as.numeric function to our example vector:

as.numeric(vec) # Applying as.numeric function # [1] 50 200 NA 10 1200 NA # Warning message: # NAs introduced by coercion

As you can see, the warning message “NAs introduced by coercion” is returned and some output values are NA (i.e. missing data or not available data).

The reason for this is that some of the character strings are not properly formatted numbers and hence cannot be converted to the numeric class.

The next example shows how to solve this problem in R.

Example 2: Modify Data to Avoid Warning Message Using gsub() Function

In Example 2, I’ll illustrate how to handle the as.numeric() warning message “NAs introduced by coercion”.

As explained before, some of our input values are not formatted properly, because they contain commas (i.e. ,) between the numbers. We can remove these commas by using the gsub function:

vec_new Example 3: Suppress Warning Message Using suppressWarnings() Function

Sometimes you might not want to convert non-number values to numeric. In this case, you can simply ignore the warning message “NAs introduced by coercion” by wrapping the suppressWarnings function around the as.numeric function:

suppressWarnings(as.numeric(vec)) # Applying suppressWarnings function # [1] 50 200 NA 10 1200 NA

The output is the same as in Example 1, but this time without printing the warning message to the RStudio console.

Video, Further Resources & Summary

Do you want to know more about warnings and errors in R? Then I can recommend watching the following video of my YouTube channel. In the video, I’m explaining the R programming codes of this tutorial in a live programming session.

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In addition, you might have a look at the related articles of my homepage. You can find some tutorials about warning and error messages below.

Summary: In this post, I explained how to get rid of the warning “NAs introduced by coercion” when converting a character or factor variable to numeric in the R programming language.

In case you have further questions, don’t hesitate to let me know in the comments section. Furthermore, please subscribe to my email newsletter in order to get updates on new tutorials.

Hi Joachim, thanks for this tutorial and your help in advance!
I am having the error NAs introduced by coercion. In my case however I am trying to reformat the string characters (e.g. green, blue, red) from two specific columns so that the characters (e.g. green) is represented by a numeric number (e.g. 1) I’ve been trying a long while now so that I can use the data as part of a neural network but cannot get past this error. Can you help me with this?

Thank you for the very kind words and your interesting question. A simple solution might be the following:

Hi Joachim,
Your blog has been a godsend! and I’m hoping you can solve this: My character vector (“1”, “2”, “3”) has zero-width non printing spaces (‘u200b’)in it (I rvested some Covid data online). I managed to remove most of them with str_remove and then convert the characters into numbers. But it still spits out this message “NAs introduced by coercion” and I don’t know what to look for! Would appreciate any guidance. Thank you!

Thanks a lot for this amazing feedback! 🙂

You could use the following code to identify all data cells that are converted to NA:

Thanks Joachim. The problem was figuring 1) the “invisible” mystery character that was creating the issue. Since I tend to glimpse() at my data rather than head() it, I couldn’t see anything wrong. Till I used head(). 2) The culprit was a zero-width non-printing space that was seemingly immune to str_remove() in its original form “”. But 48 hours later, a good learning experience.

Glad you found a solution Angi, and thanks for sharing it here! I’m sure others will have similar problems and will benefit from your explanation. 🙂

Hi Joachim, thank you but this function gsub(“,”, “”, vec) remove all the comma’s. But what if we had values with comma for example when our vector is like vec Joachim

In this case, you would have to replace the comma by a point. Have a look at the example code below:

Hi Joachim, thank you very much this does work but i have another problem. I try to change a data frame with several columns where the elements are saved as character elements: It looks like this: BAYER DAIMLER DBANK SIEMENS VONOVIA
[1,] “65,24” “47” “6,809” “89,073” “46,34”
[2,] “65,79” “46,91” “6,839” “89,29” “46,6”
[3,] “66,59” “47,92” “7,079” “90,056” “47,69”

If i use this function as.numeric(gsub(“,”, “.”, vec) it does change the character elements in numerical but i loose the structure of this data frame and get a vector with only one column which looks like this:
[1] 65.24 65.79 66.59 66.22 65.78 64.99

Do you how i can change the character elements into numerical but dont loose the complete structure of the data frame?

Please have a look at the following example code. I assume this works for your data as well:

My code for ANOVA also showed this message, for each row of the dataframe:
There were 22 warnings (use warnings() to see them)
>
> warnings()
Warning messages:
1: In FUN(newX[, i], …) : NAs introduced by coercion
2: In FUN(newX[, i], …) : NAs introduced by coercion
3: In FUN(newX[, i], …) : NAs introduced by coercion
4: In FUN(newX[, i], …) : NAs introduced by coercion
5: In FUN(newX[, i], …) : NAs introduced by coercion
6: In FUN(newX[, i], …) : NAs introduced by coercion
7: In FUN(newX[, i], …) : NAs introduced by coercion
8: In FUN(newX[, i], …) : NAs introduced by coercion
9: In FUN(newX[, i], …) : NAs introduced by coercion
10: In FUN(newX[, i], …) : NAs introduced by coercion
11: In FUN(newX[, i], …) : NAs introduced by coercion
12: In FUN(newX[, i], …) : NAs introduced by coercion
13: In FUN(newX[, i], …) : NAs introduced by coercion
14: In FUN(newX[, i], …) : NAs introduced by coercion
15: In FUN(newX[, i], …) : NAs introduced by coercion
16: In FUN(newX[, i], …) : NAs introduced by coercion
17: In FUN(newX[, i], …) : NAs introduced by coercion
18: In FUN(newX[, i], …) : NAs introduced by coercion
19: In FUN(newX[, i], …) : NAs introduced by coercion
20: In FUN(newX[, i], …) : NAs introduced by coercion
21: In FUN(newX[, i], …) : NAs introduced by coercion
22: In FUN(newX[, i], …) : NAs introduced by coercion

#assigning X vector #obtain classifications for samples

It seems like your variables Control, Sarcoidosis, and TB are not formatted properly. Could you illustrate how these variables look like?

Hi Joachim, ur blog is amazing!
I’m hoping that you can solve this: My character factor W is in the data set of XYZ.
W has value such as “1”, “2”, “3”, “101-200”, “101-200″,”101-200”,NA, NA. I have tried: as.integer(as.factor(XYZ$W)) and also
as.integer(as.factor(W))

However, when I determine if I have changed the W character to integer, so I check it with both:
as.integer(W) –> TRUE
as.integer(XYZ$W) –> FALSE

But, when i type in: str(XYZ), it shows the W is still in character form.

Could you help me look over how to change the factor to integer?
I would really appreciate if you can help me with this. Thank you!

First of all, thanks a lot for the very kind words! Glad you like my tutorials! 🙂

Regarding your question, please have a look at the code below. First we have to create some example data:

Hi Joachim, first I’ll like to thank you so much for the help and amazing work you’re doing right here. I’ll need you to please help convert a column from my dataset containing time duration in format “hms” to numeric. Here’s a view of the column

glimpse(Annual_Trips$ride_length)
‘hms’ num [1:5595063] 00:10:25 00:04:04 00:01:20 00:11:42 …
– attr(*, “units”)= chr “secs”

Tried applying the gsub function and taught of replacing the ‘,’ with the ‘:’ but still got a column full of NAs.
Thanks in advance

Thank you so much for the great feedback, glad you like my tutorials! 🙂

Also, thanks for the interesting question. It has inspired me top create a new tutorial on how to convert hours, minutes, and seconds to a numeric seconds object.

I hope that helps!

Hi Joachim thanks for this tutorial.
Followed the steps and it worked perfectly. Thank you very much

You are very welcome, glad it worked! 🙂

Hi Joachim,
I’m new here so I will be very happy if you can help me with my data.

I try to convert my variable “Year”, that is a character to numeric. This is my complete code:

FD2 %
pivot_longer(cols = 4:72, names_to = “Year”, values_to = “Catch”) %>%
mutate(Year = as.numeric(“Year”))

But as a result I get a collum “Year” with all NAs…
What am I doing wrong?

Could you please share some example values that are contained in the Year column?

Hi Joachim,
Thank you so much for your tutorials! Hope you can help me with my problem!
I have pH values from some samples – but a lot of NA’s as well. I would like to tell R that it is numeric values, but when I use the as.numeric function I get the warning: nas introduced by coercion. I loos all the numbers as it convert it to NA’s

[1] NA NA NA 6.51 6.18 NA 6.43 6.73 NA 6.56 6.02 NA NA 7.31 NA 6.56 6.17 NA 7.31 6.78
[21] NA 5.25 5.44 NA NA NA

Thank you very much for the kind feedback, glad you like my tutorials!

Regarding your question, I can convert the values you have posted above to numeric without having any problems. See the example code below:

thank you for your work and all of your tutorials, they always help a lot.
I am currently experiencing the same problem with the NA introduced by coercion in my dataset.
I already figured out that there must be a problem with the format of the negative values in my dataset, however, I haven’t found a solution yet to solve this issue.
This is a little example of the values:
EBIT_dax$`2020`
[1] “739000.00” “10603000.00” “-1055000.00” “5481000.00” “-15692000.00” “-772500.00”

And this is how I tried to solve the issue (which didn’t end up working):
EBIT_dax[ ,9] Joachim

Thank you for the kind comment, glad you find the tutorials on Statistics Globe useful!

Regarding your question, you may convert all the columns in your data set to numeric as shown in the following example:

Thank you very much for this tutorial! My script finally is running properly!

Источник

Solving R’s “NAs introduced by coercion”

In this blog post, I will elaborate on a specific warning, the contexts in which it occurs and how you can solve or prevent it. It’s definitely in my top three of generic warnings that I bump into:

Apparently, some NAs were added to my data because of something that is called coercion. What is coercion? Let’s look it up in Joseph Adler’s R in a Nutshell — pdf available here.

When you call a function with an argument of the wrong type,
R will try to coerce values to a different type so that the function will work.

Joseph Adler, R in a Nutshell (2 ed.), p56

When you receive the warning that NAs were introduced by coercion, R has coerced values to a different type, but warns us that it wasn’t able to coerce all of them. The following example is straightforward: I try to convert strings to numeric and it fails.

But the error might show while trying to execute other functions.

In the following example, I’m using data.table’s shift() function and I get the same error. As you can see, I’m trying to create a leading variable from a vector of integers. By using the parameter fill, I’m also trying to insert ‘NO VALUE’ where the leading variable is NA. This is a bad idea, as the vector x is of type integer. Funny thing: even if no NAs were added to the output, you will still get the warning.

Here’s another one I found online. In the following example, I’m trying to create a distance matrix (although it’s a silly example) from a data frame using the dist() function. In order to succeed, R eliminates the character column by coercing all these values to NAs.

Here’s another silly example. I’m trying to extract everything after the fifth character using the substring() function. Because I pass a character, not an integer, the function returns NA and I get the warning. However, passing ‘5’ as a character will work, because the coercion succeeds. Finally, because TRUE is treated as 1, it will also work.

By the way, if you’re having trouble understanding some of the code and concepts, I can highly recommend “An Introduction to Statistical Learning: with Applications in R”, which is the must-have data science bible. If you simply need an introduction into R, and less into the Data Science part, I can absolutely recommend this book by Richard Cotton. Hope it helps!

Источник

I’ve been classifying events using the KNN algorithm but that has not led to high accuracies of classification. I’ve been told by some collegues that the tree () function in R (from the tree package) could help with this.

Here’s a sample of my data. I’m trying to classify different events (I have 8 different classes of events), based on the values from the first two columns "ACTIVITY_X" and "ACTIVITY_Y":

> print(dataset)
     ACTIVITY_X ACTIVITY_Y     Event
  1:         19         21 Vigilance
  2:         20         14 Vigilance
  3:         34         35 Vigilance
  4:         18          5 Vigilance
  5:         23         27 Vigilance
 ---                                
426:          9         25 Vigilance
427:          0          0   Head-up
428:          0          0   Head-up
429:          3          3   Head-up
430:          0          0 Vigilance

Ideally, I would like to find different threshold values between the different classes (Head-up, Vigilance etc..) which should help classifying them when "Event" data is not available and I only have "ACTIVITY_X" and "ACTIVITY_Y" data. I guess I should be using the tree() function as:

xtree <- tree(Head-up~ACTIVITY_X+ACTIVITY_Y,data=dataset)
plot(xtree)
title("Head_up")
text(xtree)

xtree <- tree(Vigilance~ACTIVITY_X+ACTIVITY_Y,data=dataset)
plot(xtree)
title("Vigilance")
text(xtree)

etc..

However, I’m having different errors when running the analysis, main one being "NAs introduced by coercion". These errors are unexistant when I’m using the rpart() function, which is also a classifying algorithm.

> xtree <- tree(Vigilance~ACTIVITY_X+ACTIVITY_Y,data=dataset)
Warning message:
In tree(Vigilance ~ ACTIVITY_X + ACTIVITY_Y, data = dataset) :
  NAs introduced by coercion
> plot(xtree)
Error in plot.tree(xtree) : cannot plot singlenode tree
> title("Vigilance")
Error in title("Vigilance") : plot.new has not been called yet
> text(xtree)
Error in text.tree(xtree) : cannot plot singlenode tree

Any help would be appreciated. I’m very new to R so I hope this question is still of interest to other users.

This warning occurs when you try to convert a vector containing non-numeric values to a numeric vector.

As this is a warning, you do not need to solve anything. However, you can replace non-numeric values or suppress the warning using suppressWarnings().

This tutorial will go through the warning and what to do to stop the warning.

Example

Consider the following example where we have a vector of type character. Some of the values have commas between numbers.

vec <- c("10", "1,250", "34", "4,500", "20")
class(vec)
vec

[1] "character"
[1] "10"    "1,250" "34"    "4,500" "20"   

Let’s attempt to convert the character vector to a numeric vector using as.numeric().

vec_new <- as.numeric(vec)
vec_new

Let’s run the code to see the result:

Warning message:
NAs introduced by coercion 

[1] 10 NA 34 NA 20

The warning occurs because R could not convert the two values “1,250” and “4,500” to numeric.

Solution #1: Substitute Non-numeric values

If the data is corrupt, we can replace part or all of the values in the vector so R can convert them to numeric. In this case, we can remove the commas in the values using gsub. Let’s look at the revised code.

vec <- gsub(",", "", vec)
vec_new <- as.numeric(vec)
vec_new

Let’s run the code to see the result:

[1]   10 1250   34 4500   20

We successfully converted the character vector to a numeric vector without displaying the warning message,

Solution #2

We may not want to convert the non-numeric values, in which case we can suppress the warning message using the suppressWarnings() built-in function. Let’s look at the revised code:

vec <- c("10", "1,250", "34", "4,500", "20")
suppressWarnings(vec_new <- as.numeric(vec))
vec_new

Let’s run the code to see the result:

[1] 10 NA 34 NA 20

We successfully converted the character vector to a numeric vector without the warning message.

Summary

Congratulations on reading to the end of this tutorial!

For further reading on R related errors, go to the articles: 

• How to Solve R Error in sort.int(x, na.last = na.last, decreasing = decreasing, …) : ‘x’ must be atomic
• How to Solve R Error: attempt to use zero-length variable name

Go to the online courses page on R to learn more about coding in R for data science and machine learning.

Have fun and happy researching!