“Got 1 columns instead of …” error in numpy

Question

I\'m working on the following code for performing Random Forest Classification on train and test sets;

from sklearn.ensemble import RandomForestClassifier
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Answer 1

An exception is raised if an inconsistency is detected in the number of columns.A number of reasons and solutions are possible.

1. Add invalid_raise = False to skip the offending lines.

   dataset = genfromtxt(open('data.csv','r'), delimiter='', invalid_raise = False)

2. If your data contains Names, make sure that the field name doesn’t contain any space or invalid character, or that it does not correspond to the name of a standard attribute (like size or shape), which would confuse the interpreter.

1. deletechars

   Gives a string combining all the characters that must be deleted from the name. By default, invalid characters are ~!@#$%^&*()-=+~\|]}[{';: /?.>,<.

2. excludelist

   Gives a list of the names to exclude, such as return, file, print… If one of the input name is part of this list, an underscore character ('_') will be appended to it.

3. case_sensitive

   Whether the names should be case-sensitive (case_sensitive=True), converted to upper case (case_sensitive=False or case_sensitive='upper') or to lower case (case_sensitive='lower').

data = np.genfromtxt("data.txt", dtype=None, names=True,\
       deletechars="~!@#$%^&*()-=+~\|]}[{';: /?.>,<.", case_sensitive=True)

Reference: numpy.genfromtxt