Overview

Dataset statistics

Number of variables6
Number of observations30
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory52.4 B

Variable types

Text6

Dataset

Description대구3호선에 포함된 도시광역철도역들의 역명,역명(영문),역명(로마자),역명(일본어),역명(중국어간체),역명(중국어번체) 등의 정보 입니다.
Author국가철도공단
URLhttps://www.data.go.kr/data/15068944/fileData.do

Alerts

역명 has unique valuesUnique
역명(영문) has unique valuesUnique
역명(로마자) has unique valuesUnique
역명(일본어) has unique valuesUnique
역명(중국어 간체) has unique valuesUnique
역명(중국어 번체) has unique valuesUnique

Reproduction

Analysis started2023-12-12 19:32:03.921661
Analysis finished2023-12-12 19:32:04.440055
Duration0.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

역명
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-13T04:32:04.576406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13
Mean length4.2333333
Min length2

Characters and Unicode

Total characters127
Distinct characters73
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row칠곡경대병원
2nd row학정
3rd row팔거(국립농관원·통계청)
4th row동천
5th row칠곡운암
ValueCountFrequency (%)
칠곡경대병원 1
 
3.3%
학정 1
 
3.3%
범물 1
 
3.3%
지산 1
 
3.3%
수성못(tbc 1
 
3.3%
황금 1
 
3.3%
어린이회관 1
 
3.3%
수성구민운동장 1
 
3.3%
수성시장 1
 
3.3%
대봉교 1
 
3.3%
Other values (20) 20
66.7%
2023-12-13T04:32:05.037363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 5
 
3.9%
장 5
 
3.9%
성 4
 
3.1%
시 4
 
3.1%
동 4
 
3.1%
) 4
 
3.1%
( 4
 
3.1%
관 3
 
2.4%
운 3
 
2.4%
천 3
 
2.4%
Other values (63) 88
69.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 111
87.4%
Close Punctuation 4
 
3.1%
Open Punctuation 4
 
3.1%
Decimal Number 3
 
2.4%
Uppercase Letter 3
 
2.4%
Other Punctuation 2
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 5
 
4.5%
장 5
 
4.5%
성 4
 
3.6%
시 4
 
3.6%
동 4
 
3.6%
관 3
 
2.7%
운 3
 
2.7%
천 3
 
2.7%
청 3
 
2.7%
달 3
 
2.7%
Other values (54) 74
66.7%
Uppercase Letter
ValueCountFrequency (%)
T 1
33.3%
B 1
33.3%
C 1
33.3%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
8 1
33.3%
Other Punctuation
ValueCountFrequency (%)
· 1
50.0%
. 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 111
87.4%
Common 13
 
10.2%
Latin 3
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 5
 
4.5%
장 5
 
4.5%
성 4
 
3.6%
시 4
 
3.6%
동 4
 
3.6%
관 3
 
2.7%
운 3
 
2.7%
천 3
 
2.7%
청 3
 
2.7%
달 3
 
2.7%
Other values (54) 74
66.7%
Common
ValueCountFrequency (%)
) 4
30.8%
( 4
30.8%
2 2
15.4%
· 1
 
7.7%
. 1
 
7.7%
8 1
 
7.7%
Latin
ValueCountFrequency (%)
T 1
33.3%
B 1
33.3%
C 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 111
87.4%
ASCII 15
 
11.8%
None 1
 
0.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 5
 
4.5%
장 5
 
4.5%
성 4
 
3.6%
시 4
 
3.6%
동 4
 
3.6%
관 3
 
2.7%
운 3
 
2.7%
천 3
 
2.7%
청 3
 
2.7%
달 3
 
2.7%
Other values (54) 74
66.7%
ASCII
ValueCountFrequency (%)
) 4
26.7%
( 4
26.7%
2 2
13.3%
T 1
 
6.7%
B 1
 
6.7%
C 1
 
6.7%
. 1
 
6.7%
8 1
 
6.7%
None
ValueCountFrequency (%)
· 1
100.0%

역명(영문)
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-13T04:32:05.295050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length24
Mean length16.3
Min length5

Characters and Unicode

Total characters489
Distinct characters51
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st rowChilgok Kyungpook Nat‘l Univ.Medical Center
2nd rowHakjeong
3rd rowPalgeo(NAQS · KOSTAT)
4th rowDongcheon
5th rowChilgok·Unam
ValueCountFrequency (%)
market 3
 
5.4%
park 2
 
3.6%
paldal 2
 
3.6%
suseong 2
 
3.6%
maecheon 2
 
3.6%
hall 2
 
3.6%
myeongdeok(2·28democracy 1
 
1.8%
dalseong 1
 
1.8%
seomun 1
 
1.8%
market(dongsan 1
 
1.8%
Other values (39) 39
69.6%
2023-12-13T04:32:05.703607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 48
 
9.8%
a 42
 
8.6%
n 40
 
8.2%
o 35
 
7.2%
g 27
 
5.5%
26
 
5.3%
l 23
 
4.7%
i 18
 
3.7%
u 15
 
3.1%
k 13
 
2.7%
Other values (41) 202
41.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 357
73.0%
Uppercase Letter 78
 
16.0%
Space Separator 26
 
5.3%
Open Punctuation 8
 
1.6%
Close Punctuation 8
 
1.6%
Other Punctuation 7
 
1.4%
Decimal Number 3
 
0.6%
Dash Punctuation 1
 
0.2%
Initial Punctuation 1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 48
13.4%
a 42
11.8%
n 40
11.2%
o 35
9.8%
g 27
 
7.6%
l 23
 
6.4%
i 18
 
5.0%
u 15
 
4.2%
k 13
 
3.6%
m 13
 
3.6%
Other values (13) 83
23.2%
Uppercase Letter
ValueCountFrequency (%)
M 10
12.8%
S 9
11.5%
D 9
11.5%
C 7
9.0%
H 7
9.0%
B 5
 
6.4%
P 5
 
6.4%
T 5
 
6.4%
G 5
 
6.4%
U 3
 
3.8%
Other values (8) 13
16.7%
Other Punctuation
ValueCountFrequency (%)
· 4
57.1%
. 2
28.6%
' 1
 
14.3%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
8 1
33.3%
Space Separator
ValueCountFrequency (%)
26
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 435
89.0%
Common 54
 
11.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 48
 
11.0%
a 42
 
9.7%
n 40
 
9.2%
o 35
 
8.0%
g 27
 
6.2%
l 23
 
5.3%
i 18
 
4.1%
u 15
 
3.4%
k 13
 
3.0%
m 13
 
3.0%
Other values (31) 161
37.0%
Common
ValueCountFrequency (%)
26
48.1%
( 8
 
14.8%
) 8
 
14.8%
· 4
 
7.4%
2 2
 
3.7%
. 2
 
3.7%
- 1
 
1.9%
‘ 1
 
1.9%
8 1
 
1.9%
' 1
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 484
99.0%
None 4
 
0.8%
Punctuation 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 48
 
9.9%
a 42
 
8.7%
n 40
 
8.3%
o 35
 
7.2%
g 27
 
5.6%
26
 
5.4%
l 23
 
4.8%
i 18
 
3.7%
u 15
 
3.1%
k 13
 
2.7%
Other values (39) 197
40.7%
None
ValueCountFrequency (%)
· 4
100.0%
Punctuation
ValueCountFrequency (%)
‘ 1
100.0%

역명(로마자)
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-13T04:32:05.899783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length20
Mean length13.233333
Min length4

Characters and Unicode

Total characters397
Distinct characters44
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st rowChilgokgyeongdae Hospital
2nd rowHakjeong
3rd rowPalgeo(GungnimnonggwanwonTonggyecheong)
4th rowDongcheon
5th rowChilgogunam
ValueCountFrequency (%)
market 3
 
7.7%
paldal 2
 
5.1%
hospital 2
 
5.1%
maecheon 2
 
5.1%
namsan 1
 
2.6%
myeongdeok(2.28minjuundongginyeomhoegwan 1
 
2.6%
geondeulbawi 1
 
2.6%
daebonggyo 1
 
2.6%
suseong 1
 
2.6%
suseonggumin 1
 
2.6%
Other values (24) 24
61.5%
2023-12-13T04:32:06.289586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 46
 
11.6%
o 41
 
10.3%
e 38
 
9.6%
a 35
 
8.8%
g 34
 
8.6%
u 16
 
4.0%
i 15
 
3.8%
m 12
 
3.0%
l 12
 
3.0%
k 10
 
2.5%
Other values (34) 138
34.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 330
83.1%
Uppercase Letter 45
 
11.3%
Space Separator 9
 
2.3%
Close Punctuation 4
 
1.0%
Open Punctuation 4
 
1.0%
Decimal Number 3
 
0.8%
Dash Punctuation 1
 
0.3%
Other Punctuation 1
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 46
13.9%
o 41
12.4%
e 38
11.5%
a 35
10.6%
g 34
10.3%
u 16
 
4.8%
i 15
 
4.5%
m 12
 
3.6%
l 12
 
3.6%
k 10
 
3.0%
Other values (12) 71
21.5%
Uppercase Letter
ValueCountFrequency (%)
M 9
20.0%
S 5
11.1%
D 4
8.9%
C 4
8.9%
G 4
8.9%
H 4
8.9%
T 3
 
6.7%
P 3
 
6.7%
B 3
 
6.7%
O 1
 
2.2%
Other values (5) 5
11.1%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
8 1
33.3%
Space Separator
ValueCountFrequency (%)
9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 375
94.5%
Common 22
 
5.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 46
 
12.3%
o 41
 
10.9%
e 38
 
10.1%
a 35
 
9.3%
g 34
 
9.1%
u 16
 
4.3%
i 15
 
4.0%
m 12
 
3.2%
l 12
 
3.2%
k 10
 
2.7%
Other values (27) 116
30.9%
Common
ValueCountFrequency (%)
9
40.9%
) 4
18.2%
( 4
18.2%
2 2
 
9.1%
- 1
 
4.5%
. 1
 
4.5%
8 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 397
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 46
 
11.6%
o 41
 
10.3%
e 38
 
9.6%
a 35
 
8.8%
g 34
 
8.6%
u 16
 
4.0%
i 15
 
3.8%
m 12
 
3.0%
l 12
 
3.0%
k 10
 
2.5%
Other values (34) 138
34.8%

역명(일본어)
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-13T04:32:06.543342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length15
Mean length7
Min length2

Characters and Unicode

Total characters210
Distinct characters103
Distinct categories6 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row漆谷慶大病院
2nd row鶴亭
3rd row八莒 (国立農管院·統計庁)
4th row東川
5th row漆谷雲岩
ValueCountFrequency (%)
漆谷慶大病院 1
 
3.1%
鶴亭 1
 
3.1%
凡勿 1
 
3.1%
池山 1
 
3.1%
寿城池(スソンモッ 1
 
3.1%
黃金 1
 
3.1%
こども会館 1
 
3.1%
寿城区民運動場(スソングミウンドンジャン 1
 
3.1%
壽城市場 1
 
3.1%
大鳳橋 1
 
3.1%
Other values (22) 22
68.8%
2023-12-13T04:32:06.950729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
ン 20
 
9.5%
( 12
 
5.7%
) 12
 
5.7%
ル 6
 
2.9%
場 5
 
2.4%
城 5
 
2.4%
市 4
 
1.9%
達 4
 
1.9%
ソ 4
 
1.9%
岩 3
 
1.4%
Other values (93) 135
64.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 179
85.2%
Open Punctuation 12
 
5.7%
Close Punctuation 12
 
5.7%
Decimal Number 3
 
1.4%
Space Separator 2
 
1.0%
Other Punctuation 2
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
ン 20
 
11.2%
ル 6
 
3.4%
場 5
 
2.8%
城 5
 
2.8%
市 4
 
2.2%
達 4
 
2.2%
ソ 4
 
2.2%
岩 3
 
1.7%
川 3
 
1.7%
ジ 3
 
1.7%
Other values (87) 122
68.2%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
8 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Punctuation
ValueCountFrequency (%)
· 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 101
48.1%
Katakana 72
34.3%
Common 31
 
14.8%
Hiragana 6
 
2.9%

Most frequent character per script

Han
ValueCountFrequency (%)
場 5
 
5.0%
城 5
 
5.0%
市 4
 
4.0%
達 4
 
4.0%
岩 3
 
3.0%
川 3
 
3.0%
院 3
 
3.0%
池 3
 
3.0%
八 3
 
3.0%
会 2
 
2.0%
Other values (54) 66
65.3%
Katakana
ValueCountFrequency (%)
ン 20
27.8%
ル 6
 
8.3%
ソ 4
 
5.6%
ジ 3
 
4.2%
ャ 3
 
4.2%
ダ 3
 
4.2%
ド 3
 
4.2%
ョ 3
 
4.2%
ナ 2
 
2.8%
ミ 2
 
2.8%
Other values (17) 23
31.9%
Common
ValueCountFrequency (%)
( 12
38.7%
) 12
38.7%
2 2
 
6.5%
2
 
6.5%
· 2
 
6.5%
8 1
 
3.2%
Hiragana
ValueCountFrequency (%)
も 1
16.7%
こ 1
16.7%
ど 1
16.7%
か 1
16.7%
お 1
16.7%
の 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
CJK 100
47.6%
Katakana 72
34.3%
ASCII 29
 
13.8%
Hiragana 6
 
2.9%
None 2
 
1.0%
CJK Compat Ideographs 1
 
0.5%

Most frequent character per block

Katakana
ValueCountFrequency (%)
ン 20
27.8%
ル 6
 
8.3%
ソ 4
 
5.6%
ジ 3
 
4.2%
ャ 3
 
4.2%
ダ 3
 
4.2%
ド 3
 
4.2%
ョ 3
 
4.2%
ナ 2
 
2.8%
ミ 2
 
2.8%
Other values (17) 23
31.9%
ASCII
ValueCountFrequency (%)
( 12
41.4%
) 12
41.4%
2 2
 
6.9%
2
 
6.9%
8 1
 
3.4%
CJK
ValueCountFrequency (%)
場 5
 
5.0%
城 5
 
5.0%
市 4
 
4.0%
達 4
 
4.0%
岩 3
 
3.0%
川 3
 
3.0%
院 3
 
3.0%
池 3
 
3.0%
八 3
 
3.0%
会 2
 
2.0%
Other values (53) 65
65.0%
None
ValueCountFrequency (%)
· 2
100.0%
Hiragana
ValueCountFrequency (%)
も 1
16.7%
こ 1
16.7%
ど 1
16.7%
か 1
16.7%
お 1
16.7%
の 1
16.7%
CJK Compat Ideographs
ValueCountFrequency (%)
龍 1
100.0%

역명(중국어 간체)
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-13T04:32:07.239550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length4.5333333
Min length2

Characters and Unicode

Total characters136
Distinct characters80
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row漆谷庆大医院
2nd row鹤亭
3rd row八莒 (国立农管院·统计厅)
4th row东川
5th row漆谷云岩
ValueCountFrequency (%)
漆谷庆大医院 1
 
2.9%
大凤桥 1
 
2.9%
新南 1
 
2.9%
南山 1
 
2.9%
启明十字路口 1
 
2.9%
明德 1
 
2.9%
2·28民主运动纪念会馆 1
 
2.9%
斗笠岩 1
 
2.9%
寿城市场 1
 
2.9%
东山医院 1
 
2.9%
Other values (25) 25
71.4%
2023-12-13T04:32:08.040860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5
 
3.7%
) 5
 
3.7%
( 5
 
3.7%
场 5
 
3.7%
市 4
 
2.9%
院 4
 
2.9%
城 4
 
2.9%
岩 3
 
2.2%
寿 3
 
2.2%
八 3
 
2.2%
Other values (70) 95
69.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 116
85.3%
Space Separator 5
 
3.7%
Close Punctuation 5
 
3.7%
Open Punctuation 5
 
3.7%
Decimal Number 3
 
2.2%
Other Punctuation 2
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
场 5
 
4.3%
市 4
 
3.4%
院 4
 
3.4%
城 4
 
3.4%
岩 3
 
2.6%
寿 3
 
2.6%
八 3
 
2.6%
池 3
 
2.6%
川 3
 
2.6%
山 3
 
2.6%
Other values (64) 81
69.8%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
8 1
33.3%
Space Separator
ValueCountFrequency (%)
5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Other Punctuation
ValueCountFrequency (%)
· 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 116
85.3%
Common 20
 
14.7%

Most frequent character per script

Han
ValueCountFrequency (%)
场 5
 
4.3%
市 4
 
3.4%
院 4
 
3.4%
城 4
 
3.4%
岩 3
 
2.6%
寿 3
 
2.6%
八 3
 
2.6%
池 3
 
2.6%
川 3
 
2.6%
山 3
 
2.6%
Other values (64) 81
69.8%
Common
ValueCountFrequency (%)
5
25.0%
) 5
25.0%
( 5
25.0%
2 2
 
10.0%
· 2
 
10.0%
8 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
CJK 115
84.6%
ASCII 18
 
13.2%
None 2
 
1.5%
CJK Compat Ideographs 1
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5
27.8%
) 5
27.8%
( 5
27.8%
2 2
 
11.1%
8 1
 
5.6%
CJK
ValueCountFrequency (%)
场 5
 
4.3%
市 4
 
3.5%
院 4
 
3.5%
城 4
 
3.5%
岩 3
 
2.6%
寿 3
 
2.6%
八 3
 
2.6%
池 3
 
2.6%
川 3
 
2.6%
山 3
 
2.6%
Other values (63) 80
69.6%
None
ValueCountFrequency (%)
· 2
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
龍 1
100.0%

역명(중국어 번체)
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-13T04:32:08.331102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16
Mean length4.9
Min length1

Characters and Unicode

Total characters147
Distinct characters92
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row漆谷 慶大病院
2nd row鶴亭
3rd row八莒(國立農管院統計廳)
4th row東川
5th row漆谷雲岩
ValueCountFrequency (%)
漆谷 1
 
3.1%
慶大病院 1
 
3.1%
凡勿 1
 
3.1%
池山 1
 
3.1%
壽城못 1
 
3.1%
黃金 1
 
3.1%
어린이會館 1
 
3.1%
壽城區民運動場 1
 
3.1%
壽城市場 1
 
3.1%
大鳳橋 1
 
3.1%
Other values (22) 22
68.8%
2023-12-13T04:32:08.764408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 6
 
4.1%
) 6
 
4.1%
大 5
 
3.4%
場 5
 
3.4%
院 4
 
2.7%
市 4
 
2.7%
城 4
 
2.7%
八 3
 
2.0%
達 3
 
2.0%
壽 3
 
2.0%
Other values (82) 104
70.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 120
81.6%
Open Punctuation 6
 
4.1%
Close Punctuation 6
 
4.1%
Uppercase Letter 4
 
2.7%
Decimal Number 3
 
2.0%
Lowercase Letter 3
 
2.0%
Other Punctuation 2
 
1.4%
Space Separator 2
 
1.4%
Dash Punctuation 1
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
大 5
 
4.2%
場 5
 
4.2%
院 4
 
3.3%
市 4
 
3.3%
城 4
 
3.3%
八 3
 
2.5%
達 3
 
2.5%
壽 3
 
2.5%
山 3
 
2.5%
川 3
 
2.5%
Other values (68) 83
69.2%
Uppercase Letter
ValueCountFrequency (%)
G 1
25.0%
D 1
25.0%
P 1
25.0%
B 1
25.0%
Lowercase Letter
ValueCountFrequency (%)
k 1
33.3%
r 1
33.3%
a 1
33.3%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
8 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Other Punctuation
ValueCountFrequency (%)
· 2
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 116
78.9%
Common 20
 
13.6%
Latin 7
 
4.8%
Hangul 4
 
2.7%

Most frequent character per script

Han
ValueCountFrequency (%)
大 5
 
4.3%
場 5
 
4.3%
院 4
 
3.4%
市 4
 
3.4%
城 4
 
3.4%
八 3
 
2.6%
達 3
 
2.6%
壽 3
 
2.6%
山 3
 
2.6%
川 3
 
2.6%
Other values (64) 79
68.1%
Common
ValueCountFrequency (%)
( 6
30.0%
) 6
30.0%
2 2
 
10.0%
· 2
 
10.0%
2
 
10.0%
8 1
 
5.0%
- 1
 
5.0%
Latin
ValueCountFrequency (%)
G 1
14.3%
k 1
14.3%
r 1
14.3%
D 1
14.3%
a 1
14.3%
P 1
14.3%
B 1
14.3%
Hangul
ValueCountFrequency (%)
못 1
25.0%
이 1
25.0%
린 1
25.0%
어 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
CJK 115
78.2%
ASCII 25
 
17.0%
Hangul 4
 
2.7%
None 2
 
1.4%
CJK Compat Ideographs 1
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 6
24.0%
) 6
24.0%
2 2
 
8.0%
2
 
8.0%
8 1
 
4.0%
- 1
 
4.0%
G 1
 
4.0%
k 1
 
4.0%
r 1
 
4.0%
D 1
 
4.0%
Other values (3) 3
12.0%
CJK
ValueCountFrequency (%)
大 5
 
4.3%
場 5
 
4.3%
院 4
 
3.5%
市 4
 
3.5%
城 4
 
3.5%
八 3
 
2.6%
達 3
 
2.6%
壽 3
 
2.6%
山 3
 
2.6%
川 3
 
2.6%
Other values (63) 78
67.8%
None
ValueCountFrequency (%)
· 2
100.0%
Hangul
ValueCountFrequency (%)
못 1
25.0%
이 1
25.0%
린 1
25.0%
어 1
25.0%
CJK Compat Ideographs
ValueCountFrequency (%)
龍 1
100.0%

Correlations

2023-12-13T04:32:08.895524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
역명역명(영문)역명(로마자)역명(일본어)역명(중국어 간체)역명(중국어 번체)
역명1.0001.0001.0001.0001.0001.000
역명(영문)1.0001.0001.0001.0001.0001.000
역명(로마자)1.0001.0001.0001.0001.0001.000
역명(일본어)1.0001.0001.0001.0001.0001.000
역명(중국어 간체)1.0001.0001.0001.0001.0001.000
역명(중국어 번체)1.0001.0001.0001.0001.0001.000

Missing values

2023-12-13T04:32:04.297698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:32:04.400257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

역명역명(영문)역명(로마자)역명(일본어)역명(중국어 간체)역명(중국어 번체)
0칠곡경대병원Chilgok Kyungpook Nat‘l Univ.Medical CenterChilgokgyeongdae Hospital漆谷慶大病院漆谷庆大医院漆谷 慶大病院
1학정HakjeongHakjeong鶴亭鹤亭鶴亭
2팔거(국립농관원·통계청)Palgeo(NAQS · KOSTAT)Palgeo(GungnimnonggwanwonTonggyecheong)八莒 (国立農管院·統計庁)八莒 (国立农管院·统计厅)八莒(國立農管院統計廳)
3동천DongcheonDongcheon東川东川東川
4칠곡운암Chilgok·UnamChilgogunam漆谷雲岩漆谷云岩漆谷雲岩
5구암Guam(Taegu Science Univ.·Daegu Health College)Guam鳩岩鸠岩鳩岩(科學大·保健大入口)
6태전TaejeonTaejeon太田太田太田
7매천MaecheonMaecheon梅川梅川梅川
8매천시장Maecheon MarketMaecheon Market梅川市場梅川市场梅川市場
9팔달PaldalPaldal八達(パルダル)八达八達
역명역명(영문)역명(로마자)역명(일본어)역명(중국어 간체)역명(중국어 번체)
20건들바위GeondeulbawiGeondeulbawiコンドゥル岩斗笠岩-
21대봉교DaebonggyoDaebonggyo大鳳橋大凤桥大鳳橋
22수성시장Suseong MarketSuseong Market壽城市場寿城市场壽城市場
23수성구민운동장Suseong District StadiumSuseonggumin Stadium寿城区民運動場(スソングミウンドンジャン)寿城区民运动场壽城區民運動場
24어린이회관Children's HallEorinihoegwanこども会館儿童会馆어린이會館
25황금HwanggeumHwanggeum黃金黄金黃金
26수성못(TBC)Suseongmot(TBC)Suseongmot(TBC)寿城池(スソンモッ)寿城池壽城못
27지산JisanJisan池山池山池山
28범물BeommulBeommul凡勿凡勿凡勿
29용지YongjiYongji龍池龍池龍池