Overview

Dataset statistics

Number of variables5
Number of observations22
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.0 KiB
Average record size in memory47.0 B

Variable types

Numeric1
Text4

Dataset

Description대전교통공사 대전도시철도 1호선 역명 및 도로명 주소 역명, 도로명 주소의 변경이 없어 기존 업데이트 정보와 변경 사항 없음 향후 역명 제개정 사유 발생시 신규 자료로 업데이트 예정임
URLhttps://www.data.go.kr/data/15083331/fileData.do

Alerts

역번호 has unique valuesUnique
주소 has unique valuesUnique
한 글 has unique valuesUnique
한 자 has unique valuesUnique
로 마 자 has unique valuesUnique

Reproduction

Analysis started2023-12-11 23:59:45.554980
Analysis finished2023-12-11 23:59:46.177103
Duration0.62 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

역번호
Real number (ℝ)

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean111.5
Minimum101
Maximum122
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-12T08:59:46.265784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile102.05
Q1106.25
median111.5
Q3116.75
95-th percentile120.95
Maximum122
Range21
Interquartile range (IQR)10.5

Descriptive statistics

Standard deviation6.4935866
Coefficient of variation (CV)0.058238445
Kurtosis-1.2
Mean111.5
Median Absolute Deviation (MAD)5.5
Skewness0
Sum2453
Variance42.166667
MonotonicityStrictly increasing
2023-12-12T08:59:46.390821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
101 1
 
4.5%
113 1
 
4.5%
122 1
 
4.5%
121 1
 
4.5%
120 1
 
4.5%
119 1
 
4.5%
118 1
 
4.5%
117 1
 
4.5%
116 1
 
4.5%
115 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
101 1
4.5%
102 1
4.5%
103 1
4.5%
104 1
4.5%
105 1
4.5%
106 1
4.5%
107 1
4.5%
108 1
4.5%
109 1
4.5%
110 1
4.5%
ValueCountFrequency (%)
122 1
4.5%
121 1
4.5%
120 1
4.5%
119 1
4.5%
118 1
4.5%
117 1
4.5%
116 1
4.5%
115 1
4.5%
114 1
4.5%
113 1
4.5%

주소
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-12T08:59:46.602654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length22
Mean length19.545455
Min length17

Characters and Unicode

Total characters430
Distinct characters67
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)100.0%

Sample

1st row동구 옥천로 지하162 (판암동)
2nd row동구 옥천로 지하 70 (판암동)
3rd row동구 계족로 지하 176 (대동)
4th row동구 중앙로 지하 218 (중동)
5th row중구 중앙로 지하 145 (은행동)
ValueCountFrequency (%)
지하 18
 
17.0%
유성구 7
 
6.6%
서구 7
 
6.6%
동구 4
 
3.8%
중구 4
 
3.8%
계룡로 4
 
3.8%
한밭대로 4
 
3.8%
중앙로 3
 
2.8%
지족동 2
 
1.9%
판암동 2
 
1.9%
Other values (46) 51
48.1%
2023-12-12T08:59:47.015519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
85
19.8%
동 26
 
6.0%
구 24
 
5.6%
) 22
 
5.1%
( 22
 
5.1%
로 22
 
5.1%
지 22
 
5.1%
하 20
 
4.7%
1 10
 
2.3%
유 9
 
2.1%
Other values (57) 168
39.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 237
55.1%
Space Separator 85
 
19.8%
Decimal Number 64
 
14.9%
Close Punctuation 22
 
5.1%
Open Punctuation 22
 
5.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 26
 
11.0%
구 24
 
10.1%
로 22
 
9.3%
지 22
 
9.3%
하 20
 
8.4%
유 9
 
3.8%
성 9
 
3.8%
중 9
 
3.8%
서 7
 
3.0%
대 7
 
3.0%
Other values (44) 82
34.6%
Decimal Number
ValueCountFrequency (%)
1 10
15.6%
5 9
14.1%
7 8
12.5%
4 7
10.9%
3 7
10.9%
6 7
10.9%
8 5
7.8%
9 5
7.8%
2 3
 
4.7%
0 3
 
4.7%
Space Separator
ValueCountFrequency (%)
85
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 237
55.1%
Common 193
44.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 26
 
11.0%
구 24
 
10.1%
로 22
 
9.3%
지 22
 
9.3%
하 20
 
8.4%
유 9
 
3.8%
성 9
 
3.8%
중 9
 
3.8%
서 7
 
3.0%
대 7
 
3.0%
Other values (44) 82
34.6%
Common
ValueCountFrequency (%)
85
44.0%
) 22
 
11.4%
( 22
 
11.4%
1 10
 
5.2%
5 9
 
4.7%
7 8
 
4.1%
4 7
 
3.6%
3 7
 
3.6%
6 7
 
3.6%
8 5
 
2.6%
Other values (3) 11
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 237
55.1%
ASCII 193
44.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
85
44.0%
) 22
 
11.4%
( 22
 
11.4%
1 10
 
5.2%
5 9
 
4.7%
7 8
 
4.1%
4 7
 
3.6%
3 7
 
3.6%
6 7
 
3.6%
8 5
 
2.6%
Other values (3) 11
 
5.7%
Hangul
ValueCountFrequency (%)
동 26
 
11.0%
구 24
 
10.1%
로 22
 
9.3%
지 22
 
9.3%
하 20
 
8.4%
유 9
 
3.8%
성 9
 
3.8%
중 9
 
3.8%
서 7
 
3.0%
대 7
 
3.0%
Other values (44) 82
34.6%

한 글
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-12T08:59:47.261220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length3
Mean length5.5454545
Min length3

Characters and Unicode

Total characters122
Distinct characters67
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)100.0%

Sample

1st row판암(대전대)
2nd row신 흥
3rd row대동(우송대)
4th row대 전
5th row중앙로
ValueCountFrequency (%)
판암(대전대 1
 
2.9%
구 1
 
2.9%
마 1
 
2.9%
월 1
 
2.9%
평(한국과학기술원 1
 
2.9%
갑 1
 
2.9%
천 1
 
2.9%
유성온천(충남대,목원대 1
 
2.9%
암 1
 
2.9%
신 1
 
2.9%
Other values (24) 24
70.6%
2023-12-12T08:59:47.678492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12
 
9.8%
대 11
 
9.0%
( 8
 
6.6%
) 8
 
6.6%
청 3
 
2.5%
전 3
 
2.5%
원 3
 
2.5%
월 2
 
1.6%
천 2
 
1.6%
한 2
 
1.6%
Other values (57) 68
55.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 93
76.2%
Space Separator 12
 
9.8%
Open Punctuation 8
 
6.6%
Close Punctuation 8
 
6.6%
Other Punctuation 1
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 11
 
11.8%
청 3
 
3.2%
전 3
 
3.2%
원 3
 
3.2%
월 2
 
2.2%
천 2
 
2.2%
한 2
 
2.2%
암 2
 
2.2%
성 2
 
2.2%
충 2
 
2.2%
Other values (53) 61
65.6%
Space Separator
ValueCountFrequency (%)
12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 93
76.2%
Common 29
 
23.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 11
 
11.8%
청 3
 
3.2%
전 3
 
3.2%
원 3
 
3.2%
월 2
 
2.2%
천 2
 
2.2%
한 2
 
2.2%
암 2
 
2.2%
성 2
 
2.2%
충 2
 
2.2%
Other values (53) 61
65.6%
Common
ValueCountFrequency (%)
12
41.4%
( 8
27.6%
) 8
27.6%
, 1
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 93
76.2%
ASCII 29
 
23.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12
41.4%
( 8
27.6%
) 8
27.6%
, 1
 
3.4%
Hangul
ValueCountFrequency (%)
대 11
 
11.8%
청 3
 
3.2%
전 3
 
3.2%
원 3
 
3.2%
월 2
 
2.2%
천 2
 
2.2%
한 2
 
2.2%
암 2
 
2.2%
성 2
 
2.2%
충 2
 
2.2%
Other values (53) 61
65.6%

한 자
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-12T08:59:47.907706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length5
Min length2

Characters and Unicode

Total characters110
Distinct characters75
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

Unique22 ?
Unique (%)100.0%

Sample

1st row板岩(大田大)
2nd row新興
3rd row大洞(又松大)
4th row大田
5th row中央路
ValueCountFrequency (%)
板岩(大田大 1
 
4.5%
新興 1
 
4.5%
智足(浸神大 1
 
4.5%
老隱 1
 
4.5%
월드컵競技場(老隱都賣市場 1
 
4.5%
顯忠院(한밭대 1
 
4.5%
九岩 1
 
4.5%
儒城溫泉(忠南大,牧園大 1
 
4.5%
甲川 1
 
4.5%
月坪(韓國科學技術院 1
 
4.5%
Other values (12) 12
54.5%
2023-12-12T08:59:48.290012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
大 9
 
8.2%
( 8
 
7.3%
) 8
 
7.3%
田 3
 
2.7%
廳 3
 
2.7%
忠 2
 
1.8%
中 2
 
1.8%
場 2
 
1.8%
市 2
 
1.8%
技 2
 
1.8%
Other values (65) 69
62.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 93
84.5%
Open Punctuation 8
 
7.3%
Close Punctuation 8
 
7.3%
Other Punctuation 1
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
大 9
 
9.7%
田 3
 
3.2%
廳 3
 
3.2%
忠 2
 
2.2%
中 2
 
2.2%
場 2
 
2.2%
市 2
 
2.2%
技 2
 
2.2%
岩 2
 
2.2%
隱 2
 
2.2%
Other values (62) 64
68.8%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 84
76.4%
Common 17
 
15.5%
Hangul 9
 
8.2%

Most frequent character per script

Han
ValueCountFrequency (%)
大 9
 
10.7%
田 3
 
3.6%
廳 3
 
3.6%
忠 2
 
2.4%
中 2
 
2.4%
場 2
 
2.4%
市 2
 
2.4%
技 2
 
2.4%
岩 2
 
2.4%
隱 2
 
2.4%
Other values (53) 55
65.5%
Hangul
ValueCountFrequency (%)
한 1
11.1%
밭 1
11.1%
대 1
11.1%
월 1
11.1%
드 1
11.1%
컵 1
11.1%
네 1
11.1%
거 1
11.1%
리 1
11.1%
Common
ValueCountFrequency (%)
( 8
47.1%
) 8
47.1%
, 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
CJK 81
73.6%
ASCII 17
 
15.5%
Hangul 9
 
8.2%
CJK Compat Ideographs 3
 
2.7%

Most frequent character per block

CJK
ValueCountFrequency (%)
大 9
 
11.1%
田 3
 
3.7%
廳 3
 
3.7%
忠 2
 
2.5%
中 2
 
2.5%
場 2
 
2.5%
市 2
 
2.5%
技 2
 
2.5%
岩 2
 
2.5%
隱 2
 
2.5%
Other values (51) 52
64.2%
ASCII
ValueCountFrequency (%)
( 8
47.1%
) 8
47.1%
, 1
 
5.9%
CJK Compat Ideographs
ValueCountFrequency (%)
老 2
66.7%
龍 1
33.3%
Hangul
ValueCountFrequency (%)
한 1
11.1%
밭 1
11.1%
대 1
11.1%
월 1
11.1%
드 1
11.1%
컵 1
11.1%
네 1
11.1%
거 1
11.1%
리 1
11.1%

로 마 자
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-12T08:59:48.495700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length23
Mean length16.181818
Min length4

Characters and Unicode

Total characters356
Distinct characters49
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)100.0%

Sample

1st rowPanam(Daejeon Univ.)
2nd rowSinheung
3rd rowDae-dong(Woosong Univ.)
4th rowDaejeon
5th rowJungangno
ValueCountFrequency (%)
univ 6
 
14.6%
daejeon 2
 
4.9%
nat'l 2
 
4.9%
cemetery(hanbat 1
 
2.4%
yuseong 1
 
2.4%
spa(chungnam 1
 
2.4%
mokwon 1
 
2.4%
guam 1
 
2.4%
national 1
 
2.4%
panam(daejeon 1
 
2.4%
Other values (24) 24
58.5%
2023-12-12T08:59:48.849164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 40
 
11.2%
e 30
 
8.4%
o 28
 
7.9%
a 28
 
7.9%
19
 
5.3%
i 16
 
4.5%
g 15
 
4.2%
u 13
 
3.7%
l 12
 
3.4%
m 10
 
2.8%
Other values (39) 145
40.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 257
72.2%
Uppercase Letter 53
 
14.9%
Space Separator 19
 
5.3%
Other Punctuation 9
 
2.5%
Close Punctuation 8
 
2.2%
Open Punctuation 8
 
2.2%
Dash Punctuation 2
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 40
15.6%
e 30
11.7%
o 28
10.9%
a 28
10.9%
i 16
 
6.2%
g 15
 
5.8%
u 13
 
5.1%
l 12
 
4.7%
m 10
 
3.9%
t 9
 
3.5%
Other values (14) 56
21.8%
Uppercase Letter
ValueCountFrequency (%)
C 7
13.2%
U 6
11.3%
S 5
9.4%
N 5
9.4%
G 4
 
7.5%
W 4
 
7.5%
D 4
 
7.5%
J 3
 
5.7%
Y 2
 
3.8%
T 2
 
3.8%
Other values (8) 11
20.8%
Other Punctuation
ValueCountFrequency (%)
. 6
66.7%
' 2
 
22.2%
, 1
 
11.1%
Space Separator
ValueCountFrequency (%)
19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 310
87.1%
Common 46
 
12.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 40
 
12.9%
e 30
 
9.7%
o 28
 
9.0%
a 28
 
9.0%
i 16
 
5.2%
g 15
 
4.8%
u 13
 
4.2%
l 12
 
3.9%
m 10
 
3.2%
t 9
 
2.9%
Other values (32) 109
35.2%
Common
ValueCountFrequency (%)
19
41.3%
) 8
17.4%
( 8
17.4%
. 6
 
13.0%
' 2
 
4.3%
- 2
 
4.3%
, 1
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 356
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 40
 
11.2%
e 30
 
8.4%
o 28
 
7.9%
a 28
 
7.9%
19
 
5.3%
i 16
 
4.5%
g 15
 
4.2%
u 13
 
3.7%
l 12
 
3.4%
m 10
 
2.8%
Other values (39) 145
40.7%

Interactions

2023-12-12T08:59:45.893025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:59:48.941500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
역번호주소한 글한 자로 마 자
역번호1.0001.0001.0001.0001.000
주소1.0001.0001.0001.0001.000
한 글1.0001.0001.0001.0001.000
한 자1.0001.0001.0001.0001.000
로 마 자1.0001.0001.0001.0001.000

Missing values

2023-12-12T08:59:46.016097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:59:46.130323image/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

역번호주소한 글한 자로 마 자
0101동구 옥천로 지하162 (판암동)판암(대전대)板岩(大田大)Panam(Daejeon Univ.)
1102동구 옥천로 지하 70 (판암동)신 흥新興Sinheung
2103동구 계족로 지하 176 (대동)대동(우송대)大洞(又松大)Dae-dong(Woosong Univ.)
3104동구 중앙로 지하 218 (중동)대 전大田Daejeon
4105중구 중앙로 지하 145 (은행동)중앙로中央路Jungangno
5106중구 중앙로 지하 71 (선화동)중구청中區廳Jung-gu Office
6107중구 계룡로 지하 889 (용두동)서대전네거리西大田네거리Seodaejeonnegeori
7108중구 계룡로 지하 793 (오류동)오 룡五龍Oryong
8109서구 계룡로 지하 644 (용문동)용 문龍汶Yongmun
9110서구 문정로48번길 지하 19 (탄방동)탄 방炭坊Tanbang
역번호주소한 글한 자로 마 자
12113서구 한밭대로 지하 666 (갈마동)갈 마葛馬Galma
13114서구 한밭대로 지하 595 (월평동)월 평(한국과학기술원)月坪(韓國科學技術院)Wolpyeong(KAIST)
14115서구 갑천도시고속도로 지하1833 (월평동)갑 천甲川Gapcheon
15116유성구 계룡로 지하 97 (봉명동)유성온천(충남대,목원대)儒城溫泉(忠南大,牧園大)Yuseong Spa(Chungnam Nat'l Univ., Mokwon Univ.)
16117유성구 유성대로 703 (구암동)구 암九岩Guam
17118유성구 현충원로 지하 455 (구암동)현충원(한밭대)顯忠院(한밭대)National Cemetery(Hanbat Nat'l Univ.)
18119유성구 한밭대로 지하 155 (노은동)월드컵경기장(노은도매시장)월드컵競技場(老隱都賣市場)World Cup Stadium(Noeun Wholesale Market)
19120유성구 노은로 지하 161 (지족동)노 은老隱Noeun
20121유성구 노은로 273 (지족동)지족(침신대)智足(浸神大)Jijok(Chimsin Univ.)
21122유성구 북유성대로 지하 303 (반석동)반 석(칠성대)盤石(七星臺)Banseok(Chilsungdae)