CODEWITHSUNDEEP
pythonarraysnumpy
honeymoon
honeymoon

Reputation: 2520

NumPy loadtext()

I have a text file which I want to load into a NumPy array with loadtext(). The file is tab delimited and sometime I have a value after the last tab instead of empty:

Value1\tab\Value2\tab\value3\tab
Value4\tab\Value5\tab\value6\tab\value7
Value8\tab\Value9\tab\value10\tab
Value11\tab\Value12\tab\value13\tab

However, NumPy gives me an error with that line:

ValueError: Wrong number of columns

Is it possible to load such a data structure directly into a NumPy array (with None as a value)? Or do I have to open the file, insert a None if there is no value and load the manipulated text file in a NumPy array?

Thanks

Upvotes: 1

Views: 438

Answers (2)

Hackaholic
Hackaholic

Reputation: 19733

you can use np.genfromtxt:

import numpy as np
my_array = np.genfromtxt("myfile.txt", delimiter="\t")

Upvotes: 0

tmdavison
tmdavison

Reputation: 69066

neither numpy.genfromtxt or numpy.loadtxt can deal with an uneven number of columns in a file. If you have access to pandas, it can do what you need with pandas.read_table.

import pandas as pd
df = pd.read_table('myfile.txt',header=None,sep='\t')

# to get the data in a numpy ndarray:
myarray = df.values

By default missing values are assigned NaN, but you can change that with df.fillna(value)

Upvotes: 2

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