Overview

Dataset statistics

Number of variables10
Number of observations32
Missing cells1
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.7 KiB
Average record size in memory85.1 B

Variable types

Categorical2
Text6
Boolean1
Numeric1

Dataset

Description대구1호선에 포함된 도시광역철도역들의 철도운영기관명, 선명, 역명, 영어명, 로마자, 일본어, 중국어간체, 중국어번체, 환승역여부, 신설일자의 데이터가 있습니다.
Author국가철도공단
URLhttps://www.data.go.kr/data/15041043/fileData.do

Alerts

철도운영기관명 has constant value ""Constant
선명 has constant value ""Constant
환승역여부 is highly imbalanced (66.3%)Imbalance
중국어 번체 has 1 (3.1%) missing valuesMissing
역명 has unique valuesUnique
영어명 has unique valuesUnique
로마자 has unique valuesUnique
일본어 has unique valuesUnique
중국어 간체 has unique valuesUnique

Reproduction

Analysis started2023-12-12 23:31:10.419192
Analysis finished2023-12-12 23:31:11.097943
Duration0.68 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

철도운영기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size388.0 B
대구교통공사
32 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대구교통공사
2nd row대구교통공사
3rd row대구교통공사
4th row대구교통공사
5th row대구교통공사

Common Values

ValueCountFrequency (%)
대구교통공사 32
100.0%

Length

2023-12-13T08:31:11.161348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:31:11.240845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구교통공사 32
100.0%

선명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size388.0 B
1호선
32 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1호선
2nd row1호선
3rd row1호선
4th row1호선
5th row1호선

Common Values

ValueCountFrequency (%)
1호선 32
100.0%

Length

2023-12-13T08:31:11.319911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:31:11.393000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1호선 32
100.0%

역명
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-13T08:31:11.548620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13
Mean length4.1875
Min length2

Characters and Unicode

Total characters134
Distinct characters79
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

Unique32 ?
Unique (%)100.0%

Sample

1st row각산
2nd row교대
3rd row대곡(정부대구청사)
4th row대구역
5th row대명
ValueCountFrequency (%)
각산 1
 
3.1%
교대 1
 
3.1%
현충로 1
 
3.1%
해안 1
 
3.1%
동구청(큰고개 1
 
3.1%
칠성시장 1
 
3.1%
진천 1
 
3.1%
중앙로 1
 
3.1%
율하 1
 
3.1%
월촌 1
 
3.1%
Other values (22) 22
68.8%
2023-12-13T08:31:11.864814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 8
 
6.0%
( 6
 
4.5%
) 6
 
4.5%
구 5
 
3.7%
월 4
 
3.0%
동 4
 
3.0%
촌 3
 
2.2%
장 3
 
2.2%
시 3
 
2.2%
안 3
 
2.2%
Other values (69) 89
66.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 117
87.3%
Open Punctuation 6
 
4.5%
Close Punctuation 6
 
4.5%
Decimal Number 3
 
2.2%
Other Punctuation 2
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 8
 
6.8%
구 5
 
4.3%
월 4
 
3.4%
동 4
 
3.4%
촌 3
 
2.6%
장 3
 
2.6%
시 3
 
2.6%
안 3
 
2.6%
신 3
 
2.6%
명 3
 
2.6%
Other values (63) 78
66.7%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
8 1
33.3%
Other Punctuation
ValueCountFrequency (%)
· 1
50.0%
. 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 117
87.3%
Common 17
 
12.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 8
 
6.8%
구 5
 
4.3%
월 4
 
3.4%
동 4
 
3.4%
촌 3
 
2.6%
장 3
 
2.6%
시 3
 
2.6%
안 3
 
2.6%
신 3
 
2.6%
명 3
 
2.6%
Other values (63) 78
66.7%
Common
ValueCountFrequency (%)
( 6
35.3%
) 6
35.3%
2 2
 
11.8%
· 1
 
5.9%
. 1
 
5.9%
8 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 117
87.3%
ASCII 16
 
11.9%
None 1
 
0.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 8
 
6.8%
구 5
 
4.3%
월 4
 
3.4%
동 4
 
3.4%
촌 3
 
2.6%
장 3
 
2.6%
시 3
 
2.6%
안 3
 
2.6%
신 3
 
2.6%
명 3
 
2.6%
Other values (63) 78
66.7%
ASCII
ValueCountFrequency (%)
( 6
37.5%
) 6
37.5%
2 2
 
12.5%
. 1
 
6.2%
8 1
 
6.2%
None
ValueCountFrequency (%)
· 1
100.0%

영어명
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-13T08:31:12.065259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length31
Mean length17.25
Min length5

Characters and Unicode

Total characters552
Distinct characters54
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

Unique32 ?
Unique (%)100.0%

Sample

1st rowGaksan
2nd rowNational University Of Education
3rd rowDaegok(Central Gov't Office-Daegu)
4th rowDaegu Station
5th rowDaemyeong
ValueCountFrequency (%)
station 4
 
6.3%
market 2
 
3.2%
university 2
 
3.2%
daegu 2
 
3.2%
yeungnam 1
 
1.6%
nat'l 1
 
1.6%
univ 1
 
1.6%
ayanggyo 1
 
1.6%
int'l 1
 
1.6%
airport 1
 
1.6%
Other values (47) 47
74.6%
2023-12-13T08:31:12.382411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 61
 
11.1%
o 50
 
9.1%
a 42
 
7.6%
e 40
 
7.2%
g 33
 
6.0%
31
 
5.6%
i 28
 
5.1%
t 25
 
4.5%
u 17
 
3.1%
c 15
 
2.7%
Other values (44) 210
38.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 424
76.8%
Uppercase Letter 67
 
12.1%
Space Separator 31
 
5.6%
Open Punctuation 8
 
1.4%
Close Punctuation 8
 
1.4%
Other Punctuation 7
 
1.3%
Dash Punctuation 3
 
0.5%
Decimal Number 3
 
0.5%
Control 1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 61
14.4%
o 50
11.8%
a 42
9.9%
e 40
9.4%
g 33
 
7.8%
i 28
 
6.6%
t 25
 
5.9%
u 17
 
4.0%
c 15
 
3.5%
l 15
 
3.5%
Other values (14) 98
23.1%
Uppercase Letter
ValueCountFrequency (%)
D 10
14.9%
S 9
13.4%
M 6
 
9.0%
H 5
 
7.5%
A 4
 
6.0%
B 4
 
6.0%
Y 3
 
4.5%
G 3
 
4.5%
U 3
 
4.5%
C 3
 
4.5%
Other values (9) 17
25.4%
Other Punctuation
ValueCountFrequency (%)
' 3
42.9%
· 2
28.6%
. 1
 
14.3%
‧ 1
 
14.3%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
8 1
33.3%
Space Separator
ValueCountFrequency (%)
31
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 491
88.9%
Common 61
 
11.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 61
 
12.4%
o 50
 
10.2%
a 42
 
8.6%
e 40
 
8.1%
g 33
 
6.7%
i 28
 
5.7%
t 25
 
5.1%
u 17
 
3.5%
c 15
 
3.1%
l 15
 
3.1%
Other values (33) 165
33.6%
Common
ValueCountFrequency (%)
31
50.8%
( 8
 
13.1%
) 8
 
13.1%
- 3
 
4.9%
' 3
 
4.9%
2 2
 
3.3%
· 2
 
3.3%
1
 
1.6%
. 1
 
1.6%
8 1
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 549
99.5%
None 2
 
0.4%
Punctuation 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 61
 
11.1%
o 50
 
9.1%
a 42
 
7.7%
e 40
 
7.3%
g 33
 
6.0%
31
 
5.6%
i 28
 
5.1%
t 25
 
4.6%
u 17
 
3.1%
c 15
 
2.7%
Other values (42) 207
37.7%
None
ValueCountFrequency (%)
· 2
100.0%
Punctuation
ValueCountFrequency (%)
‧ 1
100.0%

로마자
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-13T08:31:12.820014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length26
Mean length13.21875
Min length5

Characters and Unicode

Total characters423
Distinct characters48
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)100.0%

Sample

1st rowGaksan
2nd rowNat'l Univ. of Education
3rd rowDaegok(Jeongbudaegucheongsa)
4th rowDaegu Station
5th rowDaemyeong
ValueCountFrequency (%)
station 2
 
5.0%
gaksan 1
 
2.5%
yulha 1
 
2.5%
ansim(hyeoksindositpcheombokdanji 1
 
2.5%
anjirang 1
 
2.5%
yeongdae 1
 
2.5%
hospital 1
 
2.5%
yonggye 1
 
2.5%
wolbae 1
 
2.5%
wolchon 1
 
2.5%
Other values (29) 29
72.5%
2023-12-13T08:31:13.133703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 53
 
12.5%
o 47
 
11.1%
g 38
 
9.0%
a 35
 
8.3%
e 33
 
7.8%
i 20
 
4.7%
u 14
 
3.3%
h 13
 
3.1%
y 12
 
2.8%
d 11
 
2.6%
Other values (38) 147
34.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 349
82.5%
Uppercase Letter 45
 
10.6%
Space Separator 8
 
1.9%
Open Punctuation 5
 
1.2%
Close Punctuation 5
 
1.2%
Dash Punctuation 4
 
0.9%
Other Punctuation 4
 
0.9%
Decimal Number 3
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 53
15.2%
o 47
13.5%
g 38
10.9%
a 35
10.0%
e 33
9.5%
i 20
 
5.7%
u 14
 
4.0%
h 13
 
3.7%
y 12
 
3.4%
d 11
 
3.2%
Other values (13) 73
20.9%
Uppercase Letter
ValueCountFrequency (%)
S 8
17.8%
D 6
13.3%
H 5
11.1%
M 4
8.9%
B 3
 
6.7%
J 3
 
6.7%
A 3
 
6.7%
Y 3
 
6.7%
W 2
 
4.4%
G 2
 
4.4%
Other values (6) 6
13.3%
Other Punctuation
ValueCountFrequency (%)
. 2
50.0%
· 1
25.0%
' 1
25.0%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
8 1
33.3%
Space Separator
ValueCountFrequency (%)
8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 394
93.1%
Common 29
 
6.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 53
13.5%
o 47
 
11.9%
g 38
 
9.6%
a 35
 
8.9%
e 33
 
8.4%
i 20
 
5.1%
u 14
 
3.6%
h 13
 
3.3%
y 12
 
3.0%
d 11
 
2.8%
Other values (29) 118
29.9%
Common
ValueCountFrequency (%)
8
27.6%
( 5
17.2%
) 5
17.2%
- 4
13.8%
2 2
 
6.9%
. 2
 
6.9%
8 1
 
3.4%
· 1
 
3.4%
' 1
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 422
99.8%
None 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 53
 
12.6%
o 47
 
11.1%
g 38
 
9.0%
a 35
 
8.3%
e 33
 
7.8%
i 20
 
4.7%
u 14
 
3.3%
h 13
 
3.1%
y 12
 
2.8%
d 11
 
2.6%
Other values (37) 146
34.6%
None
ValueCountFrequency (%)
· 1
100.0%

일본어
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-13T08:31:13.322496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length2
Mean length4.3125
Min length2

Characters and Unicode

Total characters138
Distinct characters84
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)100.0%

Sample

1st row角山
2nd row敎大
3rd row大谷
4th row大邱驛
5th row大明
ValueCountFrequency (%)
角山 1
 
3.0%
アヤンギョ 1
 
3.0%
顯忠路 1
 
3.0%
解顔 1
 
3.0%
トングチョン(クンゴゲ 1
 
3.0%
チルソンシジャン 1
 
3.0%
辰泉 1
 
3.0%
中央路 1
 
3.0%
栗下 1
 
3.0%
月村 1
 
3.0%
Other values (23) 23
69.7%
2023-12-13T08:31:13.623489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
ン 13
 
9.4%
大 7
 
5.1%
( 4
 
2.9%
ョ 4
 
2.9%
) 4
 
2.9%
月 4
 
2.9%
ジ 4
 
2.9%
ソ 3
 
2.2%
ク 3
 
2.2%
村 3
 
2.2%
Other values (74) 89
64.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 129
93.5%
Open Punctuation 4
 
2.9%
Close Punctuation 4
 
2.9%
Space Separator 1
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
ン 13
 
10.1%
大 7
 
5.4%
ョ 4
 
3.1%
月 4
 
3.1%
ジ 4
 
3.1%
ソ 3
 
2.3%
ク 3
 
2.3%
村 3
 
2.3%
ゴ 2
 
1.6%
半 2
 
1.6%
Other values (71) 84
65.1%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 72
52.2%
Katakana 57
41.3%
Common 9
 
6.5%

Most frequent character per script

Han
ValueCountFrequency (%)
大 7
 
9.7%
月 4
 
5.6%
村 3
 
4.2%
半 2
 
2.8%
路 2
 
2.8%
新 2
 
2.8%
明 2
 
2.8%
邱 2
 
2.8%
入 2
 
2.8%
口 2
 
2.8%
Other values (44) 44
61.1%
Katakana
ValueCountFrequency (%)
ン 13
22.8%
ョ 4
 
7.0%
ジ 4
 
7.0%
ソ 3
 
5.3%
ク 3
 
5.3%
ゴ 2
 
3.5%
ャ 2
 
3.5%
チ 2
 
3.5%
ル 2
 
3.5%
ァ 2
 
3.5%
Other values (17) 20
35.1%
Common
ValueCountFrequency (%)
( 4
44.4%
) 4
44.4%
1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
CJK 69
50.0%
Katakana 57
41.3%
ASCII 9
 
6.5%
CJK Compat Ideographs 3
 
2.2%

Most frequent character per block

Katakana
ValueCountFrequency (%)
ン 13
22.8%
ョ 4
 
7.0%
ジ 4
 
7.0%
ソ 3
 
5.3%
ク 3
 
5.3%
ゴ 2
 
3.5%
ャ 2
 
3.5%
チ 2
 
3.5%
ル 2
 
3.5%
ァ 2
 
3.5%
Other values (17) 20
35.1%
CJK
ValueCountFrequency (%)
大 7
 
10.1%
月 4
 
5.8%
村 3
 
4.3%
半 2
 
2.9%
路 2
 
2.9%
新 2
 
2.9%
明 2
 
2.9%
邱 2
 
2.9%
入 2
 
2.9%
口 2
 
2.9%
Other values (41) 41
59.4%
ASCII
ValueCountFrequency (%)
( 4
44.4%
) 4
44.4%
1
 
11.1%
CJK Compat Ideographs
ValueCountFrequency (%)
龍 1
33.3%
嶺 1
33.3%
栗 1
33.3%

중국어 간체
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-13T08:31:13.801490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length2
Mean length3.8125
Min length2

Characters and Unicode

Total characters122
Distinct characters80
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)100.0%

Sample

1st row角山
2nd row敎大
3rd row大谷
4th row大邱站
5th row大明
ValueCountFrequency (%)
角山 1
 
2.8%
敎大 1
 
2.8%
峨洋桥 1
 
2.8%
大邱国际机场门口 1
 
2.8%
安心 1
 
2.8%
安吉朗 1
 
2.8%
嶺大病院 1
 
2.8%
龍溪 1
 
2.8%
月背 1
 
2.8%
月村 1
 
2.8%
Other values (26) 26
72.2%
2023-12-13T08:31:14.071172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
大 8
 
6.6%
) 5
 
4.1%
( 5
 
4.1%
东 4
 
3.3%
村 4
 
3.3%
4
 
3.3%
月 4
 
3.3%
邱 3
 
2.5%
站 3
 
2.5%
场 3
 
2.5%
Other values (70) 79
64.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 108
88.5%
Close Punctuation 5
 
4.1%
Open Punctuation 5
 
4.1%
Space Separator 4
 
3.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
大 8
 
7.4%
东 4
 
3.7%
村 4
 
3.7%
月 4
 
3.7%
邱 3
 
2.8%
站 3
 
2.8%
场 3
 
2.8%
半 2
 
1.9%
路 2
 
1.9%
市 2
 
1.9%
Other values (67) 73
67.6%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 108
88.5%
Common 14
 
11.5%

Most frequent character per script

Han
ValueCountFrequency (%)
大 8
 
7.4%
东 4
 
3.7%
村 4
 
3.7%
月 4
 
3.7%
邱 3
 
2.8%
站 3
 
2.8%
场 3
 
2.8%
半 2
 
1.9%
路 2
 
1.9%
市 2
 
1.9%
Other values (67) 73
67.6%
Common
ValueCountFrequency (%)
) 5
35.7%
( 5
35.7%
4
28.6%

Most occurring blocks

ValueCountFrequency (%)
CJK 105
86.1%
ASCII 14
 
11.5%
CJK Compat Ideographs 3
 
2.5%

Most frequent character per block

CJK
ValueCountFrequency (%)
大 8
 
7.6%
东 4
 
3.8%
村 4
 
3.8%
月 4
 
3.8%
邱 3
 
2.9%
站 3
 
2.9%
场 3
 
2.9%
半 2
 
1.9%
路 2
 
1.9%
市 2
 
1.9%
Other values (64) 70
66.7%
ASCII
ValueCountFrequency (%)
) 5
35.7%
( 5
35.7%
4
28.6%
CJK Compat Ideographs
ValueCountFrequency (%)
嶺 1
33.3%
龍 1
33.3%
栗 1
33.3%

중국어 번체
Text

MISSING 

Distinct31
Distinct (%)100.0%
Missing1
Missing (%)3.1%
Memory size388.0 B
2023-12-13T08:31:14.252841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length4.9032258
Min length2

Characters and Unicode

Total characters152
Distinct characters96
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)100.0%

Sample

1st row角山
2nd row敎大
3rd row大谷(政府大邱廳舍)
4th row大邱驛
5th row大明
ValueCountFrequency (%)
角山 1
 
2.9%
月村 1
 
2.9%
峨洋橋 1
 
2.9%
大邱國際空港入口 1
 
2.9%
安心(革新都市·尖複團地驛 1
 
2.9%
嶺大病院 1
 
2.9%
龍溪 1
 
2.9%
月背 1
 
2.9%
栗下 1
 
2.9%
新川 1
 
2.9%
Other values (25) 25
71.4%
2023-12-13T08:31:14.564331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
大 9
 
5.9%
( 7
 
4.6%
) 7
 
4.6%
5
 
3.3%
驛 4
 
2.6%
月 4
 
2.6%
村 4
 
2.6%
東 4
 
2.6%
邱 4
 
2.6%
新 3
 
2.0%
Other values (86) 101
66.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 126
82.9%
Open Punctuation 7
 
4.6%
Close Punctuation 7
 
4.6%
Space Separator 5
 
3.3%
Decimal Number 3
 
2.0%
Control 2
 
1.3%
Other Punctuation 2
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
大 9
 
7.1%
驛 4
 
3.2%
月 4
 
3.2%
村 4
 
3.2%
東 4
 
3.2%
邱 4
 
3.2%
新 3
 
2.4%
市 3
 
2.4%
場 2
 
1.6%
入 2
 
1.6%
Other values (78) 87
69.0%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
8 1
33.3%
Other Punctuation
ValueCountFrequency (%)
· 1
50.0%
‧ 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Control
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 126
82.9%
Common 26
 
17.1%

Most frequent character per script

Han
ValueCountFrequency (%)
大 9
 
7.1%
驛 4
 
3.2%
月 4
 
3.2%
村 4
 
3.2%
東 4
 
3.2%
邱 4
 
3.2%
新 3
 
2.4%
市 3
 
2.4%
場 2
 
1.6%
入 2
 
1.6%
Other values (78) 87
69.0%
Common
ValueCountFrequency (%)
( 7
26.9%
) 7
26.9%
5
19.2%
2 2
 
7.7%
2
 
7.7%
· 1
 
3.8%
8 1
 
3.8%
‧ 1
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
CJK 126
82.9%
ASCII 24
 
15.8%
None 1
 
0.7%
Punctuation 1
 
0.7%

Most frequent character per block

CJK
ValueCountFrequency (%)
大 9
 
7.1%
驛 4
 
3.2%
月 4
 
3.2%
村 4
 
3.2%
東 4
 
3.2%
邱 4
 
3.2%
新 3
 
2.4%
市 3
 
2.4%
場 2
 
1.6%
入 2
 
1.6%
Other values (78) 87
69.0%
ASCII
ValueCountFrequency (%)
( 7
29.2%
) 7
29.2%
5
20.8%
2 2
 
8.3%
2
 
8.3%
8 1
 
4.2%
None
ValueCountFrequency (%)
· 1
100.0%
Punctuation
ValueCountFrequency (%)
‧ 1
100.0%

환승역여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size164.0 B
False
30 
True
 
2
ValueCountFrequency (%)
False 30
93.8%
True 2
 
6.2%
2023-12-13T08:31:14.657013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

신설일자
Real number (ℝ)

Distinct10
Distinct (%)31.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19985791
Minimum19880502
Maximum20160908
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-13T08:31:14.721324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19880502
5-th percentile19971126
Q119971126
median19980331
Q319980502
95-th percentile20083755
Maximum20160908
Range280406
Interquartile range (IQR)9376

Descriptive statistics

Standard deviation49850.856
Coefficient of variation (CV)0.0024943149
Kurtosis9.4031499
Mean19985791
Median Absolute Deviation (MAD)9201
Skewness2.6577543
Sum6.3954533 × 108
Variance2.4851079 × 109
MonotonicityNot monotonic
2023-12-13T08:31:14.814671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
19971126 11
34.4%
19980502 7
21.9%
19980331 4
 
12.5%
19971130 3
 
9.4%
20160908 2
 
6.2%
20020630 1
 
3.1%
19980413 1
 
3.1%
19980521 1
 
3.1%
19880502 1
 
3.1%
19980830 1
 
3.1%
ValueCountFrequency (%)
19880502 1
 
3.1%
19971126 11
34.4%
19971130 3
 
9.4%
19980331 4
 
12.5%
19980413 1
 
3.1%
19980502 7
21.9%
19980521 1
 
3.1%
19980830 1
 
3.1%
20020630 1
 
3.1%
20160908 2
 
6.2%
ValueCountFrequency (%)
20160908 2
 
6.2%
20020630 1
 
3.1%
19980830 1
 
3.1%
19980521 1
 
3.1%
19980502 7
21.9%
19980413 1
 
3.1%
19980331 4
 
12.5%
19971130 3
 
9.4%
19971126 11
34.4%
19880502 1
 
3.1%

Interactions

2023-12-13T08:31:10.835230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:31:14.885172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
역명영어명로마자일본어중국어 간체중국어 번체환승역여부신설일자
역명1.0001.0001.0001.0001.0001.0001.0001.000
영어명1.0001.0001.0001.0001.0001.0001.0001.000
로마자1.0001.0001.0001.0001.0001.0001.0001.000
일본어1.0001.0001.0001.0001.0001.0001.0001.000
중국어 간체1.0001.0001.0001.0001.0001.0001.0001.000
중국어 번체1.0001.0001.0001.0001.0001.0001.0001.000
환승역여부1.0001.0001.0001.0001.0001.0001.0000.000
신설일자1.0001.0001.0001.0001.0001.0000.0001.000
2023-12-13T08:31:14.968686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
신설일자환승역여부
신설일자1.0000.000
환승역여부0.0001.000

Missing values

2023-12-13T08:31:10.921931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:31:11.040519image/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

철도운영기관명선명역명영어명로마자일본어중국어 간체중국어 번체환승역여부신설일자
0대구교통공사1호선각산GaksanGaksan角山角山角山N19980331
1대구교통공사1호선교대National University Of EducationNat'l Univ. of Education敎大敎大敎大N19971126
2대구교통공사1호선대곡(정부대구청사)Daegok(Central Gov't Office-Daegu)Daegok(Jeongbudaegucheongsa)大谷大谷大谷(政府大邱廳舍)N20020630
3대구교통공사1호선대구역Daegu StationDaegu Station大邱驛大邱站大邱驛N19980502
4대구교통공사1호선대명DaemyeongDaemyeong大明大明大明N19971126
5대구교통공사1호선동대구역Dongdaegu StationDongdaegu Stationトンデグヨク东大邱站東大邱驛N19971130
6대구교통공사1호선동촌Dongchon(Dongchon Resort)Dongchon東村东村 (东村游园地)東村 (東村遊園地)N19980502
7대구교통공사1호선명덕(2.28민주운동기념회관)Myeongdeok(The 2‧28 Movement for Democracy museum)Myeongdeok(2.28Minjuundongginyeomhoegwan)明德明德明德(2‧28 民主運動紀念會館)Y19971130
8대구교통공사1호선반야월BanyawolBanyawol半夜月半夜月半夜月N19980413
9대구교통공사1호선반월당BanwoldangBanwoldang半月堂半月堂半月堂Y19971126
철도운영기관명선명역명영어명로마자일본어중국어 간체중국어 번체환승역여부신설일자
22대구교통공사1호선월배WolbaeWolbae月背月背月背N19971126
23대구교통공사1호선월촌WolchonWolchon月村月村月村N19971126
24대구교통공사1호선율하YulhaYulha栗下栗下栗下N19980331
25대구교통공사1호선중앙로Jungangno StationJungang-ro中央路中央路中央路驛N19971126
26대구교통공사1호선진천JincheonJincheon辰泉辰泉辰泉N19971126
27대구교통공사1호선칠성시장Chilseong MarketChilseong Marketチルソンシジャン七星市场七星市場N19880502
28대구교통공사1호선동구청(큰고개)Dong-gu Office(Keungogae)Dong-gu Office(Keungogae)トングチョン(クンゴゲ)东区厅(肯高盖)東區廳N19980502
29대구교통공사1호선해안HaeanHaean解顔解顔解顔N19980830
30대구교통공사1호선현충로Hyeonchungno stationHyeonchung-ro顯忠路显忠路顯忠路N19971126
31대구교통공사1호선화원HwawonHwawonファウォン花園花園N20160908