hi all,
what’s the most efficient / preferred python way of parsing tab separated data into arrays? for example if i have a file containing two columns one corresponding to names the other numbers:
col1 \t col 2
joe \t 12.3
jane \t 155.0
i’d like to parse into an array() such that i can do: mydata[:, 0] and mydata[:, 1] to easily access all the columns.
right now i can iterate through the file, parse it manually using the split(’\t’) command and construct a list out of it, then convert it to arrays. but there must be a better way?
also, my first column is just a name, and so it is variable in length – is there still a way to store it as an array so i can access: mydata[:, 0] to get all the names (as a list)?
thank you.
per freem wrote:
hi all,
what's the most efficient / preferred python way of parsing tab separated data into arrays? for example if i have a file containing two
Check out the python csv module. Documentation at
JLS
Try matplotlib.mlab.csv2rec or numpy.loadtxt
Ryan
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On Fri, Mar 13, 2009 at 5:18 PM, per freem <perfreem@…287…> wrote:
hi all,
what’s the most efficient / preferred python way of parsing tab separated data into arrays? for example if i have a file containing two columns one corresponding to names the other numbers:
col1 \t col 2
joe \t 12.3
jane \t 155.0
i’d like to parse into an array() such that i can do: mydata[:, 0] and mydata[:, 1] to easily access all the columns.
right now i can iterate through the file, parse it manually using the split(‘\t’) command and construct a list out of it, then convert it to arrays. but there must be a better way?
also, my first column is just a name, and so it is variable in length – is there still a way to store it as an array so i can access: mydata[:, 0] to get all the names (as a list)?
–
Ryan May
Graduate Research Assistant
School of Meteorology
University of Oklahoma
Sent from: Norman Oklahoma United States.