Pandas: parse columns from csv

Question

I have data in csv file without header. I need to parse some columns.

A part of data:

-1.0,-0.0246259814315,1174.60023796
 1.0,-0.978057706084,1083.19880269
-1.0,0.314271994507,-1472.97760911
-1.0,0.179751565771,231.017267343
1.0,-1.26254374278,-778.271726463
-1.0,0.249969939456,-52.8014826538
1.0,-1.87039747875,-324.235348241

I need to load only second and third columns. I use train_X = pd.read_csv("perceptron-train.csv", sep=',', parse_dates=[1], usecols=[2, 3]) but it returns IndexError: list index out of range

you need to enclose square brackets: train_X = pd.read_csv("perception-train.csv", parse_dates=[1]) also for usecols you should pass a list of either the names or ordinal positions of the columns — EdChum
– EdChum, Commented Aug 5, 2016 at 13:22
Use parse_dates=[1] and keep in mind that the column-indices are zero-based. — albert
– albert, Commented Aug 5, 2016 at 13:23
@EdChum if I want to scecify two columns I should use two brakets? — NineWasps
– NineWasps, Commented Aug 5, 2016 at 13:26
@ldevyataykina no this is a list. You separate them by a comma — Ivaylo Strandjev
– Ivaylo Strandjev, Commented Aug 5, 2016 at 13:26
Please can you edit your question with raw data, your code and the desired output, I and others have repeatedly asked you to do this for the majority of your questions, also the data you posted doesn't look like a datetime string so I don't see what you're trying to do here — EdChum
– EdChum, Commented Aug 5, 2016 at 13:41

EdChum · Accepted Answer · 2016-08-05 14:57:38Z

1

IIUC indices are zero-based so you need:

train_X = pd.read_csv("perceptron-train.csv", sep=',', parse_dates=[1], usecols=[1, 2])

Also I don't know if this also means you need to change your date col:

train_X = pd.read_csv("perceptron-train.csv", sep=',', parse_dates=[0], usecols=[1, 2])

However, looking at your data I don't understand how to interpret the first or second column as a datetime as they look weird

answered Aug 5, 2016 at 14:57

EdChum

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