## Using sqldf to load subsets of data

-May 23, 2014

Like many sociolinguists, I have a lot of vowel formant data which is stored in separate files for each speaker. For example, I’ve organized my copy of the Philadelphia Neighborhood Corpus as follows:

Street_1/
Speaker_1/
Speaker_1_meas.txt
Speaker_2/
Speaker_2_meas.txt
Street_2/
Speaker_3/
Speaker_3_meas.txt
Speaker_4/
Speaker_4_meas.txt


It’s easy enough to load all of one speakers’ data into R.

df <- read.delim("Street_1/Speaker_1/Speaker_1_meas.txt")

It’s also easy enough, using plyr, to read in all of the data from all speakers by globbing for the measurement files.

library(plyr)
speakers <- Sys.glob("Street*/Speaker*/*_meas.txt")
df <- ldply(speakers, read.delim)

But with this plyr approach, I start facing two problems.

1. There are just about 1 million measurements in the whole PNC, and reading all of that into R’s memory can start making things a little bit wonky.
2. I don’t actually want or need all of the data anyway.I frequently only want some vowel data from some speakers, and sometimes the data I want is even narrower than that.

My previous solution to these problems has been pretty hacky and inflexible. But now, I think I’ve got something better going with sqldf. Briefly, the sqldf package, and its namesake function, sqldf(), allows you to read data from a delimited file using SQL queries. I’m totally new to SQL, but its Wikipedia page is surprisingly useful for learning how to use it.

First, you need to assign the file connection to the speaker’s data to a named variable.

speaker <- "Street_1/Speaker_1/Speaker_1_meas.txt"
fi <- file(speaker)

Now, you can use sqldf() to read in a specific data from the file connection using SQL queries. Here’s a simple one where I selected just the vowel /ow/. The bit that says plt_vclass is referring to a column called plt_vclass which exists in the data.

  library(sqldf)
df <- sqldf("select * from fi where plt_vclass == 'ow'",
file.format = list(header = TRUE, sep = "\t"))

# good practice to close the connection
close(fi)

table(df$plt_vclass) ## ## ow ## 145   summary(df$F2)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.
##     824    1130    1230    1240    1330    1640


I could’ve done something more fancy, where I select /uw/ and /ow/ with duration greater than 100ms.

  # re-open connection
fi <- file(speaker)

df <- sqldf("select * from fi where plt_vclass in ('ow', 'uw') and dur > 0.1",
file.format = list(header = TRUE, sep = "\t"))
close(fi)

table(df$plt_vclass) ## ## ow uw ## 52 10   ddply(df, .(plt_vclass), summarise, mean_F2 = mean(F2), min_dur = min(dur)) ## plt_vclass mean_F2 min_dur ## 1 ow 1254.2 0.101 ## 2 uw 912.5 0.101  The trick now is how to do this over and over again with a list of files, and with any arbitrary conditions. Here’s the function I’ve come up with. To use it, first get a list of speakers’ data files by globbing for them. speakers <- Sys.glob("Street*/Speaker*/*_meas.txt") Now, feed this vector of file names into ldply().  df <- ldply(speakers, sql_load, condition = "where plt_vclass in ('ow', 'uw') and dur > 0.1") table(df$plt_vclass)
##
##    ow    uw
## 11819  2539

  ddply(df, .(plt_vclass),
summarise,
mean_F2 = mean(F2),
min_dur = min(dur))
##   plt_vclass mean_F2 min_dur
## 1         ow    1267   0.101
## 2         uw    1151   0.101


posted by Joe at 17:50 (more or less).