[ Python NLP: TypeError: not all arguments converted during string formatting ]
I tried the code on "Natural language processing with python", but a type error occurred.
import nltk
from nltk.corpus import brown
suffix_fdist = nltk.FreqDist()
for word in brown.words():
word = word.lower()
suffix_fdist.inc(word[-1:])
suffix_fdist.inc(word[-2:])
suffix_fdist.inc(word[-3:])
common_suffixes = suffix_fdist.items()[:100]
def pos_features(word):
features = {}
for suffix in common_suffixes:
features['endswith(%s)' % suffix] = word.lower().endswith(suffix)
return features
pos_features('people')
the error is below:
Traceback (most recent call last):
File "/home/wanglan/javadevelop/TestPython/src/FirstModule.py", line 323, in <module>
pos_features('people')
File "/home/wanglan/javadevelop/TestPython/src/FirstModule.py", line 321, in pos_features
features['endswith(%s)' % suffix] = word.lower().endswith(suffix)
TypeError: not all arguments converted during string formatting
Does anyone could help me find out where i am wrong?
Answer 1
suffix
is a tuple, because .items()
returns (key,value) tuples. When you use %, if the right hand side is a tuple, the values will be unpacked and substituted for each % format in order. The error you get is complaining that the tuple has more entries than % formats.
You probably want just the key (the actual suffix), in which case you should use suffix[0]
, or .keys()
to only retrieve the dictionary keys.