Table of Stop Words

Three sources hyperlinked in column names.1

Translations by Google, except where noted.

idx words 01a_stop2 02_ranks_nl 03_dutch-stop-words translation BD count
0 aan 1 1 1 to 213
1 af 0 1 1 down 19
2 al 1 1 1 already 82
3 alles 1 0 1 all 9
4 als 1 1 1 as 97
5 altijd 1 0 1 always 10
6 andere 1 0 1 other 37
7 ben 1 0 1 am 14
8 bij 1 1 1 at 175
9 daar 1 0 1 over there 43
10 dan 1 1 1 than 64
11 dat 1 1 1 it 403
12 de 1 0 1 the 2481
13 der 1 0 1 of 29
14 deze 1 0 1 this 66
15 die 1 1 1 that 245
16 dit 1 1 1 this 68
17 doch 1 0 1 but  
18 doen 1 0 1 do 25
19 door 1 0 1 by 125
20 dus 1 0 1 so 20
21 een 1 1 1 a 923
22 eens 1 0 1 once 14
23 en 1 1 1 and 615
24 er 1 1 1 there 239
25 ge 1 0 1 ‘thou’3  
26 geen 1 0 1 no 69
27 geweest 1 0 1 been 7
28 haar 1 0 1 its 35
29 had 1 1 1 had 43
30 heb 1 1 1 have 10
31 hebben 1 0 1 have 107
32 heeft 1 0 1 has 149
33 hem 1 1 1 him 31
34 het 1 1 1 the 1063
35 hier 1 0 1 here 15
36 hij 1 1 1 he 141
37 hoe 1 1 1 how 21
38 hun 1 1 1 their 40
39 iemand 1 0 1 someone 2
40 iets 1 0 1 something 13
41 ik 1 1 1 I 66
42 in 1 1 1 in 861
43 is 1 1 1 is 435
44 ja 1 0 1 yes 3
45 je 1 1 1 you 57
46 kan 1 1 1 can 59
47 kon 1 0 1 could 20
48 kunnen 1 0 1 can 47
49 maar 1 0 1 but 150
50 me 1 1 1 me 10
51 meer 1 0 1 (1) more 101
52 men 1 1 1 one  
53 met 1 1 1 with 316
54 mij 1 1 1 me 8
55 mijn 1 0 1 my 16
56 moet 1 0 1 must 42
57 na 1 0 1 after 62
58 naar 1 0 1 to 153
59 niet 1 0 1 not 226
60 niets 1 0 1 nothing 6
61 nog 1 1 1 yet 156
62 nu 1 1 1 now 43
63 of 1 1 1 whether 61
64 om 1 0 1 to 218
65 omdat 1 0 1 because 27
66 onder 1 0 0 below 67
67 ons 1 1 1 us / our 16
68 ook 1 1 1 also 149
69 op 1 0 1 on 544
70 over 1 0 1 about 140
71 reeds 1 0 1 already  
72 te 1 1 1 too 324
73 tegen 1 0 1 against 46
74 toch 1 0 1 nevertheless 17
75 toen 1 0 1 when 38
76 tot 1 1 1 until 85
77 u 1 0 1 you 9
78 uit 1 1 1 from 158
79 uw 1 0 1 your 2
80 van 1 1 1 from 1078
81 veel 1 0 1 many 42
82 voor 1 0 1 in front of 278
83 want 1 0 1 because 13
84 waren 1 0 1 goods 53
85 was 1 1 1 was 133
86 wat 1 1 1 what 46
87 we 0 1 1 we 39
88 wel 0 1 1 well 59
89 werd 1 0 1 became 99
90 wezen 1 0 1 being  
91 wie 1 0 1 who 13
92 wij 0 1 1 we 19
93 wil 1 0 1 want 33
94 worden 1 0 1 be 94
95 wordt 1 0 0 is 82
96 zal 1 1 1 shall 28
97 ze 1 1 1 she 90
98 zei 0 1 1 said 13
99 zelf 1 0 1 self 12
100 zich 1 0 1 himself 73
101 zij 1 1 1 they 40
102 zijn 1 0 1 his 304
103 zo 1 1 1 so 45
104 zonder 1 0 1 without 14
105 zou 1 1 1 would 67


Code

import pandas as pd
import os

stop_files = os.listdir('stopwords/')
stop_files.pop(1)
stop_files

Out:

[‘01a_stop.txt’, ‘02_ranks_nl.txt’, ‘03_dutch-stop-words.txt’]

stop_list = []
stopwords = []

for stop in stop_files:
    with open('stopwords/'+stop, 'r') as f:
        temp_list = []
        for line in f:
            temp_list.append(line.strip())
            stopwords.append(line.strip())
        temp_dict = {'file': stop, 'words': temp_list}
        stop_list.append(temp_dict)
        
print [len(d['words']) for d in stop_list]
print len(stopwords)
print len(set(stopwords))

Out:

[101, 48, 104]

253

106

stopwords_idx = pd.DataFrame(list(set(stopwords)))
print stopwords_idx.shape
stopwords_idx.columns = ['words']
stopwords_idx.head()

Out:

(106, 1)

words
0 andere
1 deze
2 over
3 zei
4 zal 
stopwords_full = stopwords_idx
print stopwords_full.shape

for i in range(len(stop_list)):
    df = pd.DataFrame(stop_list[i]['words'], columns=['words'])
    df[stop_list[i]['file'].replace('.txt', '')] = 1
    stopwords_temp = pd.merge(stopwords_idx, df, on='words')
    stopwords_full = pd.merge(stopwords_full, stopwords_temp, on='words', how='outer')

print stopwords_full.shape
stopwords_full = stopwords_full.fillna(0)
stopwords_full = stopwords_full.sort(columns='words', axis=0)
stopwords_full = stopwords_full.reset_index(drop=True)
stopwords_full.head()

Out:

(106, 1)

(106, 4)

words 01a_stop 02_ranks_nl 03_dutch-stop-words
0 aan 1 1 1
1 af 0 1 1
2 al 1 1 1
3 alles 1 0 1
4 als 1 1 1 
stopwords_full.to_csv('stopwords/stopwords_table.csv', encoding='utf8')


Notes

1 And listed below with identified contacts:

  1. http://snowball.tartarus.org/algorithms/dutch/stop.txt; http://www.patrickmileswriter.co.uk/ \ mail@patrickmiles.co.uk
  2. http://www.ranks.nl/stopwords/dutch; damian@ranks.nl
  3. http://www.damienvanholten.com/blog/dutch-stop-words/; http://twitter.com/damienvanholten ↩

2 Modified to remove provided translations. ↩
3 According to http://snowball.tartarus.org/algorithms/dutch/stop.txt: “‘thou’, still used in Belgium and south Netherlands” ↩