Overview

Dataset statistics

Number of variables6
Number of observations44
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 KiB
Average record size in memory51.0 B

Variable types

Text6

Dataset

Description역명(한글),역명(영문),역명(로마자),역명(일본어),역명(중국어간체),역명(중국어번체) 등의 정보를 제공
URLhttps://www.data.go.kr/data/15064040/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

Reproduction

Analysis started2023-12-12 15:08:49.385732
Analysis finished2023-12-12 15:08:50.245527
Duration0.86 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

역명
Text

UNIQUE 

Distinct44
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size484.0 B
2023-12-13T00:08:50.418033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length2
Mean length3.25
Min length2

Characters and Unicode

Total characters143
Distinct characters92
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)100.0%

Sample

1st row대화
2nd row주엽
3rd row정발산
4th row마두
5th row백석
ValueCountFrequency (%)
대화 1
 
2.3%
주엽 1
 
2.3%
남부터미널(예술의전당 1
 
2.3%
약수 1
 
2.3%
금호 1
 
2.3%
옥수 1
 
2.3%
압구정 1
 
2.3%
신사 1
 
2.3%
잠원 1
 
2.3%
고속터미널 1
 
2.3%
Other values (34) 34
77.3%
2023-12-13T00:08:50.835081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 6
 
4.2%
원 6
 
4.2%
정 4
 
2.8%
구 4
 
2.8%
( 4
 
2.8%
) 4
 
2.8%
청 4
 
2.8%
가 3
 
2.1%
서 3
 
2.1%
수 3
 
2.1%
Other values (82) 102
71.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 132
92.3%
Open Punctuation 4
 
2.8%
Close Punctuation 4
 
2.8%
Decimal Number 2
 
1.4%
Other Punctuation 1
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 6
 
4.5%
원 6
 
4.5%
정 4
 
3.0%
구 4
 
3.0%
청 4
 
3.0%
가 3
 
2.3%
서 3
 
2.3%
수 3
 
2.3%
로 3
 
2.3%
미 2
 
1.5%
Other values (78) 94
71.2%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Decimal Number
ValueCountFrequency (%)
3 2
100.0%
Other Punctuation
ValueCountFrequency (%)
· 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 132
92.3%
Common 11
 
7.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 6
 
4.5%
원 6
 
4.5%
정 4
 
3.0%
구 4
 
3.0%
청 4
 
3.0%
가 3
 
2.3%
서 3
 
2.3%
수 3
 
2.3%
로 3
 
2.3%
미 2
 
1.5%
Other values (78) 94
71.2%
Common
ValueCountFrequency (%)
( 4
36.4%
) 4
36.4%
3 2
18.2%
· 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 132
92.3%
ASCII 10
 
7.0%
None 1
 
0.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 6
 
4.5%
원 6
 
4.5%
정 4
 
3.0%
구 4
 
3.0%
청 4
 
3.0%
가 3
 
2.3%
서 3
 
2.3%
수 3
 
2.3%
로 3
 
2.3%
미 2
 
1.5%
Other values (78) 94
71.2%
ASCII
ValueCountFrequency (%)
( 4
40.0%
) 4
40.0%
3 2
20.0%
None
ValueCountFrequency (%)
· 1
100.0%

역명(영문)
Text

UNIQUE 

Distinct44
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size484.0 B
2023-12-13T00:08:51.084623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length26
Mean length11.454545
Min length4

Characters and Unicode

Total characters504
Distinct characters50
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

Unique44 ?
Unique (%)100.0%

Sample

1st rowDaehwa
2nd rowJuyeop
3rd rowJeongbalsan
4th rowMadu
5th rowBaekseok
ValueCountFrequency (%)
office 2
 
2.9%
seoul 2
 
2.9%
terminal 2
 
2.9%
bus 2
 
2.9%
univ 2
 
2.9%
3(sam)ga 2
 
2.9%
of 1
 
1.4%
1
 
1.4%
court 1
 
1.4%
education 1
 
1.4%
Other values (54) 54
77.1%
2023-12-13T00:08:51.444251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 45
 
8.9%
n 42
 
8.3%
e 41
 
8.1%
a 40
 
7.9%
u 32
 
6.3%
g 29
 
5.8%
26
 
5.2%
s 18
 
3.6%
i 17
 
3.4%
l 16
 
3.2%
Other values (40) 198
39.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 390
77.4%
Uppercase Letter 67
 
13.3%
Space Separator 26
 
5.2%
Close Punctuation 6
 
1.2%
Open Punctuation 6
 
1.2%
Other Punctuation 5
 
1.0%
Dash Punctuation 2
 
0.4%
Decimal Number 2
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 45
11.5%
n 42
10.8%
e 41
10.5%
a 40
10.3%
u 32
 
8.2%
g 29
 
7.4%
s 18
 
4.6%
i 17
 
4.4%
l 16
 
4.1%
r 14
 
3.6%
Other values (14) 96
24.6%
Uppercase Letter
ValueCountFrequency (%)
S 7
 
10.4%
D 7
 
10.4%
J 5
 
7.5%
G 5
 
7.5%
O 4
 
6.0%
C 4
 
6.0%
N 4
 
6.0%
M 4
 
6.0%
B 4
 
6.0%
H 4
 
6.0%
Other values (8) 19
28.4%
Other Punctuation
ValueCountFrequency (%)
. 2
40.0%
' 2
40.0%
& 1
20.0%
Space Separator
ValueCountFrequency (%)
26
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Decimal Number
ValueCountFrequency (%)
3 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 457
90.7%
Common 47
 
9.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 45
 
9.8%
n 42
 
9.2%
e 41
 
9.0%
a 40
 
8.8%
u 32
 
7.0%
g 29
 
6.3%
s 18
 
3.9%
i 17
 
3.7%
l 16
 
3.5%
r 14
 
3.1%
Other values (32) 163
35.7%
Common
ValueCountFrequency (%)
26
55.3%
) 6
 
12.8%
( 6
 
12.8%
- 2
 
4.3%
3 2
 
4.3%
. 2
 
4.3%
' 2
 
4.3%
& 1
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 504
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 45
 
8.9%
n 42
 
8.3%
e 41
 
8.1%
a 40
 
7.9%
u 32
 
6.3%
g 29
 
5.8%
26
 
5.2%
s 18
 
3.6%
i 17
 
3.4%
l 16
 
3.2%
Other values (40) 198
39.3%

역명(로마자)
Text

UNIQUE 

Distinct44
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size484.0 B
2023-12-13T00:08:51.674653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length24
Mean length11.068182
Min length4

Characters and Unicode

Total characters487
Distinct characters50
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

Unique44 ?
Unique (%)100.0%

Sample

1st rowDaehwa
2nd rowJuyeop
3rd rowJeongbalsan
4th rowMadu
5th rowBaekseok
ValueCountFrequency (%)
terminal 2
 
3.1%
bus 2
 
3.1%
univ 2
 
3.1%
3(sam)-ga 2
 
3.1%
daehwa 1
 
1.6%
yangjae 1
 
1.6%
apgujeong 1
 
1.6%
sinsa 1
 
1.6%
jamwon 1
 
1.6%
express 1
 
1.6%
Other values (50) 50
78.1%
2023-12-13T00:08:52.012112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 45
 
9.2%
o 45
 
9.2%
a 44
 
9.0%
e 39
 
8.0%
g 33
 
6.8%
u 30
 
6.2%
21
 
4.3%
s 18
 
3.7%
i 16
 
3.3%
k 14
 
2.9%
Other values (40) 182
37.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 384
78.9%
Uppercase Letter 59
 
12.1%
Space Separator 21
 
4.3%
Open Punctuation 6
 
1.2%
Close Punctuation 6
 
1.2%
Dash Punctuation 5
 
1.0%
Other Punctuation 4
 
0.8%
Decimal Number 2
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 45
11.7%
o 45
11.7%
a 44
11.5%
e 39
10.2%
g 33
 
8.6%
u 30
 
7.8%
s 18
 
4.7%
i 16
 
4.2%
k 14
 
3.6%
m 13
 
3.4%
Other values (14) 87
22.7%
Uppercase Letter
ValueCountFrequency (%)
D 7
11.9%
J 6
10.2%
B 5
 
8.5%
G 5
 
8.5%
N 4
 
6.8%
Y 4
 
6.8%
S 4
 
6.8%
H 4
 
6.8%
M 4
 
6.8%
E 3
 
5.1%
Other values (8) 13
22.0%
Other Punctuation
ValueCountFrequency (%)
. 2
50.0%
' 1
25.0%
& 1
25.0%
Space Separator
ValueCountFrequency (%)
21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Decimal Number
ValueCountFrequency (%)
3 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 443
91.0%
Common 44
 
9.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 45
 
10.2%
o 45
 
10.2%
a 44
 
9.9%
e 39
 
8.8%
g 33
 
7.4%
u 30
 
6.8%
s 18
 
4.1%
i 16
 
3.6%
k 14
 
3.2%
m 13
 
2.9%
Other values (32) 146
33.0%
Common
ValueCountFrequency (%)
21
47.7%
( 6
 
13.6%
) 6
 
13.6%
- 5
 
11.4%
3 2
 
4.5%
. 2
 
4.5%
' 1
 
2.3%
& 1
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 487
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 45
 
9.2%
o 45
 
9.2%
a 44
 
9.0%
e 39
 
8.0%
g 33
 
6.8%
u 30
 
6.2%
21
 
4.3%
s 18
 
3.7%
i 16
 
3.3%
k 14
 
2.9%
Other values (40) 182
37.4%

역명(일본어)
Text

UNIQUE 

Distinct44
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size484.0 B
2023-12-13T00:08:52.222864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length7
Mean length4.8409091
Min length2

Characters and Unicode

Total characters213
Distinct characters63
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)100.0%

Sample

1st rowテファ
2nd rowチュヨプ
3rd rowチョンバルサン
4th rowマドゥ
5th rowペッソク
ValueCountFrequency (%)
テファ 1
 
2.3%
チュヨプ 1
 
2.3%
ナンブターミナル 1
 
2.3%
ヤッス 1
 
2.3%
クムホ 1
 
2.3%
オッス 1
 
2.3%
アックジョン 1
 
2.3%
シンサ 1
 
2.3%
チャムォン 1
 
2.3%
コソクターミナル 1
 
2.3%
Other values (34) 34
77.3%
2023-12-13T00:08:52.547124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
ン 34
 
16.0%
ク 13
 
6.1%
チ 12
 
5.6%
ョ 10
 
4.7%
ム 9
 
4.2%
ル 9
 
4.2%
ッ 7
 
3.3%
サ 5
 
2.3%
ォ 5
 
2.3%
ウ 5
 
2.3%
Other values (53) 104
48.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 207
97.2%
Other Punctuation 2
 
0.9%
Modifier Letter 2
 
0.9%
Open Punctuation 1
 
0.5%
Close Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
ン 34
 
16.4%
ク 13
 
6.3%
チ 12
 
5.8%
ョ 10
 
4.8%
ム 9
 
4.3%
ル 9
 
4.3%
ッ 7
 
3.4%
サ 5
 
2.4%
ォ 5
 
2.4%
ウ 5
 
2.4%
Other values (49) 98
47.3%
Other Punctuation
ValueCountFrequency (%)
· 2
100.0%
Modifier Letter
ValueCountFrequency (%)
ー 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Katakana 205
96.2%
Common 6
 
2.8%
Han 2
 
0.9%

Most frequent character per script

Katakana
ValueCountFrequency (%)
ン 34
 
16.6%
ク 13
 
6.3%
チ 12
 
5.9%
ョ 10
 
4.9%
ム 9
 
4.4%
ル 9
 
4.4%
ッ 7
 
3.4%
サ 5
 
2.4%
ォ 5
 
2.4%
ウ 5
 
2.4%
Other values (47) 96
46.8%
Common
ValueCountFrequency (%)
· 2
33.3%
ー 2
33.3%
( 1
16.7%
) 1
16.7%
Han
ValueCountFrequency (%)
三 1
50.0%
松 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Katakana 207
97.2%
None 2
 
0.9%
ASCII 2
 
0.9%
CJK 2
 
0.9%

Most frequent character per block

Katakana
ValueCountFrequency (%)
ン 34
 
16.4%
ク 13
 
6.3%
チ 12
 
5.8%
ョ 10
 
4.8%
ム 9
 
4.3%
ル 9
 
4.3%
ッ 7
 
3.4%
サ 5
 
2.4%
ォ 5
 
2.4%
ウ 5
 
2.4%
Other values (48) 98
47.3%
None
ValueCountFrequency (%)
· 2
100.0%
ASCII
ValueCountFrequency (%)
( 1
50.0%
) 1
50.0%
CJK
ValueCountFrequency (%)
三 1
50.0%
松 1
50.0%

역명(중국어 간체)
Text

UNIQUE 

Distinct44
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size484.0 B
2023-12-13T00:08:52.763162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length2
Mean length2.7045455
Min length2

Characters and Unicode

Total characters119
Distinct characters97
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)100.0%

Sample

1st row大化
2nd row注叶
3rd row鼎鉢山
4th row马头
5th row白石
ValueCountFrequency (%)
大化 1
 
2.3%
注叶 1
 
2.3%
南部客运站 1
 
2.3%
药水 1
 
2.3%
金湖 1
 
2.3%
玉水 1
 
2.3%
狎鸥亭 1
 
2.3%
新沙 1
 
2.3%
蚕院 1
 
2.3%
高速巴士客运站 1
 
2.3%
Other values (34) 34
77.3%
2023-12-13T00:08:53.076426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
大 6
 
5.0%
水 3
 
2.5%
院 3
 
2.5%
路 3
 
2.5%
三 3
 
2.5%
谷 2
 
1.7%
客 2
 
1.7%
运 2
 
1.7%
站 2
 
1.7%
国 2
 
1.7%
Other values (87) 91
76.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 119
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
大 6
 
5.0%
水 3
 
2.5%
院 3
 
2.5%
路 3
 
2.5%
三 3
 
2.5%
谷 2
 
1.7%
客 2
 
1.7%
运 2
 
1.7%
站 2
 
1.7%
国 2
 
1.7%
Other values (87) 91
76.5%

Most occurring scripts

ValueCountFrequency (%)
Han 119
100.0%

Most frequent character per script

Han
ValueCountFrequency (%)
大 6
 
5.0%
水 3
 
2.5%
院 3
 
2.5%
路 3
 
2.5%
三 3
 
2.5%
谷 2
 
1.7%
客 2
 
1.7%
运 2
 
1.7%
站 2
 
1.7%
国 2
 
1.7%
Other values (87) 91
76.5%

Most occurring blocks

ValueCountFrequency (%)
CJK 119
100.0%

Most frequent character per block

CJK
ValueCountFrequency (%)
大 6
 
5.0%
水 3
 
2.5%
院 3
 
2.5%
路 3
 
2.5%
三 3
 
2.5%
谷 2
 
1.7%
客 2
 
1.7%
运 2
 
1.7%
站 2
 
1.7%
国 2
 
1.7%
Other values (87) 91
76.5%

역명(중국어 번체)
Text

Distinct42
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Memory size484.0 B
2023-12-13T00:08:53.294445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length2
Mean length3.1590909
Min length1

Characters and Unicode

Total characters139
Distinct characters108
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)93.2%

Sample

1st row大化
2nd row注葉
3rd row鼎鉢山
4th row馬頭
5th row白石
ValueCountFrequency (%)
3
 
6.8%
高速터미널 1
 
2.3%
警察病院 1
 
2.3%
敎大(法院·檢察廳 1
 
2.3%
藥水 1
 
2.3%
金湖 1
 
2.3%
玉水 1
 
2.3%
狎鷗亭 1
 
2.3%
新沙 1
 
2.3%
蠶院 1
 
2.3%
Other values (32) 32
72.7%
2023-12-13T00:08:53.603539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
大 5
 
3.6%
院 4
 
2.9%
( 4
 
2.9%
) 4
 
2.9%
- 3
 
2.2%
水 3
 
2.2%
廳 3
 
2.2%
路 3
 
2.2%
울 2
 
1.4%
谷 2
 
1.4%
Other values (98) 106
76.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 125
89.9%
Open Punctuation 4
 
2.9%
Close Punctuation 4
 
2.9%
Dash Punctuation 3
 
2.2%
Decimal Number 2
 
1.4%
Other Punctuation 1
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
大 5
 
4.0%
院 4
 
3.2%
水 3
 
2.4%
廳 3
 
2.4%
路 3
 
2.4%
울 2
 
1.6%
谷 2
 
1.6%
터 2
 
1.6%
察 2
 
1.6%
堂 2
 
1.6%
Other values (93) 97
77.6%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Decimal Number
ValueCountFrequency (%)
3 2
100.0%
Other Punctuation
ValueCountFrequency (%)
· 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 113
81.3%
Common 14
 
10.1%
Hangul 12
 
8.6%

Most frequent character per script

Han
ValueCountFrequency (%)
大 5
 
4.4%
院 4
 
3.5%
水 3
 
2.7%
廳 3
 
2.7%
路 3
 
2.7%
谷 2
 
1.8%
察 2
 
1.8%
堂 2
 
1.8%
元 2
 
1.8%
街 2
 
1.8%
Other values (85) 85
75.2%
Hangul
ValueCountFrequency (%)
울 2
16.7%
터 2
16.7%
미 2
16.7%
널 2
16.7%
여 1
8.3%
의 1
8.3%
서 1
8.3%
재 1
8.3%
Common
ValueCountFrequency (%)
( 4
28.6%
) 4
28.6%
- 3
21.4%
3 2
14.3%
· 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
CJK 110
79.1%
ASCII 13
 
9.4%
Hangul 12
 
8.6%
CJK Compat Ideographs 3
 
2.2%
None 1
 
0.7%

Most frequent character per block

CJK
ValueCountFrequency (%)
大 5
 
4.5%
院 4
 
3.6%
水 3
 
2.7%
廳 3
 
2.7%
路 3
 
2.7%
谷 2
 
1.8%
察 2
 
1.8%
堂 2
 
1.8%
元 2
 
1.8%
街 2
 
1.8%
Other values (82) 82
74.5%
ASCII
ValueCountFrequency (%)
( 4
30.8%
) 4
30.8%
- 3
23.1%
3 2
15.4%
Hangul
ValueCountFrequency (%)
울 2
16.7%
터 2
16.7%
미 2
16.7%
널 2
16.7%
여 1
8.3%
의 1
8.3%
서 1
8.3%
재 1
8.3%
None
ValueCountFrequency (%)
· 1
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
良 1
33.3%
碌 1
33.3%
磻 1
33.3%

Correlations

2023-12-13T00:08:53.703259image/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

2023-12-13T00:08:50.106485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:08:50.198279image/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)
0대화DaehwaDaehwaテファ大化大化
1주엽JuyeopJuyeopチュヨプ注叶注葉
2정발산JeongbalsanJeongbalsanチョンバルサン鼎鉢山鼎鉢山
3마두MaduMaduマドゥ马头馬頭
4백석BaekseokBaekseokペッソク白石白石
5대곡DaegokDaegokテゴク大谷大谷
6화정HwajeongHwajeongファジョン花井花井
7원당WondangWondangウォンダン元堂元堂
8원흥WonheungWonheungウォンフン元兴元興
9삼송SamsongSamsongサムソン(三松)三松三松
역명역명(영문)역명(로마자)역명(일본어)역명(중국어 간체)역명(중국어 번체)
34매봉MaebongMaebongメボン梅峰-
35도곡DogokDogokトゴク道谷道谷
36대치DaechiDaechiテチ大峙大峙
37학여울HangnyeoulHangnyeoulハギョウル鹤滩鶴여울
38대청DaecheongDaecheongテチョン大厅-
39일원IrwonIrwonイルォン逸院逸院
40수서SuseoSuseoスソ水西水西
41가락시장Garak MarketGarak Marketカラク·シジャン可乐市场可樂市場
42경찰병원National Police HospitalNational Police Hospitalキョンチャル·ピョンウォン警察医院警察病院
43오금OgeumOgeumオグム梧琴梧琴