4.08768
> 4 14.95139 14.01923
> 5 14.99517 15.91936
> 6 14.46359 14.07573
> 7 15.09702 13.94888
> 8 15.99967 14.97171
> 9 15.51924 15.59981
>
> A.K.
>
>
>
>
>
> - Original Message -
> From: Faz Jones
> To: r-help@r-project.org
> Cc:
> S
Thank you. It works great.
Sent from my iPhone
On Aug 5, 2012, at 9:08 PM, Jorge I Velez wrote:
> Hi Faz,
>
> Here is one way of doing it where "x" is your data frame:
>
> x[, colMeans(is.na(x)) <= .15]
>
> HTH,
> Jorge.-
>
>
> On Sun, Aug 5,
I have a dataframe of 10 different columns (length of each column is
the same). I want to eliminate any column that has 'NA' greater than
15% of the column length. Do i first need to make a function for
calculating the percentage of NA for each column and then make another
dataframe where i apply t
Hi,
I have attached a word document to explain the problem i am having
creating a for-loop in R with conditions to create a frequency table.
I am new to R so any help would be greatly appreciated.
Thanks
Jones
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