I am trying to read in a tab delimited text file that consists of a header or column names and decimal number data in the rows that follow. readr is however not parsing the data correctly - it sees the entire header as one long set of characters instead of columns so I end up with single column data - and I am not sure how to resolve this. Below is what the it looks like when I read in the data:
data <- read_tsv("data.txt")
Rows: 62893 Columns: 1
── Column specification ──────────────────────────────────────────────────────────────────────── Delimiter: "\t" chr (1): Lon Lat Col1 Col2 Col3...
ℹ Use
spec()to retrieve the full column specification for this data.
ℹ Specify the column types or set
show_col_types = FALSEto quiet this message.
When I print out the first few lines this what I get:
head(data)
# A tibble: 3 × 1
Lon Lat Col1 Col2 Col3
<chr>
1 "-123.25 38.25 0.000002 0.030371 0.000002"
2 "96.25 67.75 0.308539 0.063202 0.000019"
3 "-73.75 -15.75 0.018868 0.048092 0.013427"
# ℹ abbreviated name:
# ` Lon Lat Col1 Col2 Col3 `
Any ideas on how to get readr to pars this table correctly so so it sees the data as 3 rows and 5 columns instead of 3 rows and 1 column? And recognizes that the first row is a header column? (I tried using the col_names = TRUE attribute of the read_tsv() function and that did not work). It clearly sees each row a single long character string, including the first (header) row but shouldn't because the data is tab delimited.
I have just copy and paste the data from above:
data.txt
Lon Lat Col1 Col2 Col3
-123.25 38.25 0.000002 0.030371 0.000002
96.25 67.75 0.308539 0.063202 0.000019
-73.75 -15.75 0.018868 0.048092 0.013427
you can use read.csv and specify the sep parameter as space " ":
read.csv("data/data.txt", sep=" ")
# Lon Lat Col1 Col2 Col3
#1 -123.25 38.25 0.000002 0.030371 0.000002
#2 96.25 67.75 0.308539 0.063202 0.000019
#3 -73.75 -15.75 0.018868 0.048092 0.013427