R：eval（predvars，data，env）中的错误：找不到对象'x'

Question

I am quite new to R, so this might seem like a really simple question. However I don't know specifically what to search for because I don't really know what is causing the problem. Both CSV-files mentioned below are formatted in the same way, which is the reason I don't know what is causing the trouble. However the CSV that is returning the error mentioned below has many more rows than the other.

I have a certain dataset I want to run a linear model on (lm in R). I imported it into R from a CSV using this code in R:

rawData=read.csv("dataset.csv", header=T)

When requesting an output of the ten top rows by we get:

> head(rawData, 10)
   ï..x   y
1     1 0.0
2     2 0.0
3     3 0.0
4     4 0.0
5     5 0.0
6     6 0.5
7     7 0.0
8     8 0.0
9     9 0.1
10   10 0.0

From the above output we see that the top row display as follows:

ï..x   y

Running a linear model on the last one returns an error messages:

simple.fit = lm(x~y, data=dataset)
summary(simple.fit)

The error message returned is:

Error in eval(predvars, data, env) : object 'x' not found

How can this be solved?

As we can see below the output from an import of another CSV file (I just used for testing linear regression) in R the output is as follows:

> rawData=read.csv("testing.csv", header=T)
> head(rawData, 10)
             x          y
1  82.58321982 134.907414
2  73.92246618 134.085180
3  34.88744536         NA
4  61.83998269 114.530638
5  16.77594025  31.376437
6   0.01673734   8.764634
7  44.45764646  73.285341
8  10.34490930  18.859865
9  42.76713229  72.946609
10 20.85663802  28.637286

Here we see the top row have simply:

x          y

Running a linear model on the last one returns no error messages and gives an output simple.fit = lm(x~y, data=testing) summary(simple.fit)

Answer 1

对于这种情况，您可以尝试使用 library janitor中的clean_names() 。