Hi
the output seems to me rather weird. Unles you have NaNs in input data frame
you should not get NaN as a result.
Anyway, your aggregate will give you NA or NaN even when there is only one NA
or NaN in your input data frame. So I suggest to use
sentiments_per_Category <- aggregate(relative_sentiment_frequencies,
by = list(Category = df$Case.Category), mean,
na.rm=TRUE)
This should strip all NAs before calculating mean in each category.
Complete cases removes all lines with at least one NA in your data frame, which
probably results to empty data frame.
Cheers
Petr
> -----Original Message-----
> From: R-help <r-help-boun...@r-project.org> On Behalf Of Shivi Bhatia
> Sent: Saturday, August 25, 2018 4:01 PM
> To: R-help <r-help@r-project.org>
> Subject: [R] NaN in Scoring Sentiment
>
> Hi All- I am running a sentiment scoring model and the code is as below:
> sentiments_per_Category <- aggregate(relative_sentiment_frequencies,
> by = list(Category = df$Case.Category),
> mean)
>
> while i run the head command most of the values are NaN. i then used
> complete.cases on my data frame df[complete.cases(df),] but it does not seems
> to work. Please advice if there is a way to handle NaN.
>
> Regards, Shivi
>
> [[alternative HTML version deleted]]
>
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