Overview

Dataset statistics

Number of variables5
Number of observations1180
Missing cells1
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory47.4 KiB
Average record size in memory41.1 B

Variable types

Numeric1
Text4

Dataset

Description서울특별시 중구 관내 담배소매인 현황입니다.
Author서울특별시 중구
URLhttps://www.data.go.kr/data/3078655/fileData.do

Alerts

번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 05:40:53.279799
Analysis finished2023-12-12 05:40:54.329407
Duration1.05 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct1180
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean590.5
Minimum1
Maximum1180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.5 KiB
2023-12-12T14:40:54.418674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile59.95
Q1295.75
median590.5
Q3885.25
95-th percentile1121.05
Maximum1180
Range1179
Interquartile range (IQR)589.5

Descriptive statistics

Standard deviation340.78097
Coefficient of variation (CV)0.57710578
Kurtosis-1.2
Mean590.5
Median Absolute Deviation (MAD)295
Skewness0
Sum696790
Variance116131.67
MonotonicityStrictly increasing
2023-12-12T14:40:54.601677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
777 1
 
0.1%
793 1
 
0.1%
792 1
 
0.1%
791 1
 
0.1%
790 1
 
0.1%
789 1
 
0.1%
788 1
 
0.1%
787 1
 
0.1%
786 1
 
0.1%
Other values (1170) 1170
99.2%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1180 1
0.1%
1179 1
0.1%
1178 1
0.1%
1177 1
0.1%
1176 1
0.1%
1175 1
0.1%
1174 1
0.1%
1173 1
0.1%
1172 1
0.1%
1171 1
0.1%

업소명
Text

Distinct899
Distinct (%)76.2%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
2023-12-12T14:40:54.936606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length22
Mean length6.3694915
Min length1

Characters and Unicode

Total characters7516
Distinct characters480
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique873 ?
Unique (%)74.0%

Sample

1st rowGS25 충무로햇살점
2nd row명동스테이
3rd row(주)코리아세븐 시그니처타워점
4th row더블유매점
5th row씨유 중구해성점
ValueCountFrequency (%)
무 206
 
13.2%
씨유 78
 
5.0%
gs25 50
 
3.2%
세븐일레븐 48
 
3.1%
주)코리아세븐 33
 
2.1%
매점 20
 
1.3%
이마트24 19
 
1.2%
가로판매대 10
 
0.6%
전자담배 9
 
0.6%
주식회사 8
 
0.5%
Other values (970) 1078
69.1%
2023-12-12T14:40:55.471960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 454
 
6.0%
450
 
6.0%
무 241
 
3.2%
2 163
 
2.2%
븐 147
 
2.0%
동 132
 
1.8%
매 124
 
1.6%
5 124
 
1.6%
로 120
 
1.6%
대 116
 
1.5%
Other values (470) 5445
72.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6109
81.3%
Space Separator 450
 
6.0%
Decimal Number 431
 
5.7%
Uppercase Letter 303
 
4.0%
Open Punctuation 93
 
1.2%
Close Punctuation 93
 
1.2%
Lowercase Letter 18
 
0.2%
Other Punctuation 13
 
0.2%
Dash Punctuation 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 454
 
7.4%
무 241
 
3.9%
븐 147
 
2.4%
동 132
 
2.2%
매 124
 
2.0%
로 120
 
2.0%
대 116
 
1.9%
이 108
 
1.8%
트 106
 
1.7%
세 105
 
1.7%
Other values (418) 4456
72.9%
Uppercase Letter
ValueCountFrequency (%)
G 103
34.0%
S 103
34.0%
C 14
 
4.6%
U 13
 
4.3%
A 8
 
2.6%
K 7
 
2.3%
D 6
 
2.0%
N 6
 
2.0%
L 5
 
1.7%
R 5
 
1.7%
Other values (14) 33
 
10.9%
Lowercase Letter
ValueCountFrequency (%)
e 5
27.8%
t 2
 
11.1%
a 2
 
11.1%
f 2
 
11.1%
s 1
 
5.6%
k 1
 
5.6%
o 1
 
5.6%
i 1
 
5.6%
g 1
 
5.6%
r 1
 
5.6%
Decimal Number
ValueCountFrequency (%)
2 163
37.8%
5 124
28.8%
4 41
 
9.5%
1 30
 
7.0%
3 22
 
5.1%
7 14
 
3.2%
6 14
 
3.2%
0 12
 
2.8%
9 6
 
1.4%
8 5
 
1.2%
Other Punctuation
ValueCountFrequency (%)
. 9
69.2%
/ 2
 
15.4%
& 2
 
15.4%
Space Separator
ValueCountFrequency (%)
450
100.0%
Open Punctuation
ValueCountFrequency (%)
( 93
100.0%
Close Punctuation
ValueCountFrequency (%)
) 93
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6109
81.3%
Common 1086
 
14.4%
Latin 321
 
4.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 454
 
7.4%
무 241
 
3.9%
븐 147
 
2.4%
동 132
 
2.2%
매 124
 
2.0%
로 120
 
2.0%
대 116
 
1.9%
이 108
 
1.8%
트 106
 
1.7%
세 105
 
1.7%
Other values (418) 4456
72.9%
Latin
ValueCountFrequency (%)
G 103
32.1%
S 103
32.1%
C 14
 
4.4%
U 13
 
4.0%
A 8
 
2.5%
K 7
 
2.2%
D 6
 
1.9%
N 6
 
1.9%
e 5
 
1.6%
L 5
 
1.6%
Other values (25) 51
15.9%
Common
ValueCountFrequency (%)
450
41.4%
2 163
 
15.0%
5 124
 
11.4%
( 93
 
8.6%
) 93
 
8.6%
4 41
 
3.8%
1 30
 
2.8%
3 22
 
2.0%
7 14
 
1.3%
6 14
 
1.3%
Other values (7) 42
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6109
81.3%
ASCII 1407
 
18.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 454
 
7.4%
무 241
 
3.9%
븐 147
 
2.4%
동 132
 
2.2%
매 124
 
2.0%
로 120
 
2.0%
대 116
 
1.9%
이 108
 
1.8%
트 106
 
1.7%
세 105
 
1.7%
Other values (418) 4456
72.9%
ASCII
ValueCountFrequency (%)
450
32.0%
2 163
 
11.6%
5 124
 
8.8%
G 103
 
7.3%
S 103
 
7.3%
( 93
 
6.6%
) 93
 
6.6%
4 41
 
2.9%
1 30
 
2.1%
3 22
 
1.6%
Other values (42) 185
13.1%

업소지번주소
Text

Distinct1076
Distinct (%)91.3%
Missing1
Missing (%)0.1%
Memory size9.3 KiB
2023-12-12T14:40:55.867046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length43
Mean length24.514843
Min length1

Characters and Unicode

Total characters28903
Distinct characters339
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1062 ?
Unique (%)90.1%

Sample

1st row서울특별시 중구 필동1가 46번지 1호
2nd row서울특별시 중구 남산동3가 31번지 1호
3rd row서울특별시 중구 수표동 99번지 시그니쳐타워
4th row서울특별시 중구 신당동 213번지 8호 STUDIO W
5th row서울특별시 중구 남대문로4가 17번지 19호
ValueCountFrequency (%)
서울특별시 1088
 
17.5%
중구 1084
 
17.5%
호 221
 
3.6%
신당동 153
 
2.5%
1호 117
 
1.9%
1층 108
 
1.7%
을지로6가 65
 
1.0%
2호 51
 
0.8%
18번지 46
 
0.7%
1 44
 
0.7%
Other values (1148) 3233
52.1%
2023-12-12T14:40:56.518284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6466
22.4%
1 1435
 
5.0%
지 1210
 
4.2%
서 1131
 
3.9%
시 1121
 
3.9%
중 1116
 
3.9%
구 1106
 
3.8%
울 1101
 
3.8%
특 1091
 
3.8%
별 1091
 
3.8%
Other values (329) 12035
41.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16985
58.8%
Space Separator 6466
 
22.4%
Decimal Number 5266
 
18.2%
Uppercase Letter 77
 
0.3%
Dash Punctuation 39
 
0.1%
Lowercase Letter 24
 
0.1%
Other Punctuation 23
 
0.1%
Close Punctuation 11
 
< 0.1%
Open Punctuation 10
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 1210
 
7.1%
서 1131
 
6.7%
시 1121
 
6.6%
중 1116
 
6.6%
구 1106
 
6.5%
울 1101
 
6.5%
특 1091
 
6.4%
별 1091
 
6.4%
호 1073
 
6.3%
번 945
 
5.6%
Other values (279) 6000
35.3%
Uppercase Letter
ValueCountFrequency (%)
B 13
16.9%
A 8
10.4%
K 8
10.4%
C 8
10.4%
S 7
9.1%
T 5
 
6.5%
D 5
 
6.5%
I 5
 
6.5%
M 3
 
3.9%
X 3
 
3.9%
Other values (9) 12
15.6%
Lowercase Letter
ValueCountFrequency (%)
o 4
16.7%
e 3
12.5%
g 2
8.3%
n 2
8.3%
r 2
8.3%
a 2
8.3%
s 2
8.3%
w 1
 
4.2%
d 1
 
4.2%
y 1
 
4.2%
Other values (4) 4
16.7%
Decimal Number
ValueCountFrequency (%)
1 1435
27.3%
2 875
16.6%
3 529
 
10.0%
4 420
 
8.0%
5 417
 
7.9%
6 367
 
7.0%
0 347
 
6.6%
7 307
 
5.8%
9 288
 
5.5%
8 281
 
5.3%
Other Punctuation
ValueCountFrequency (%)
. 20
87.0%
/ 3
 
13.0%
Space Separator
ValueCountFrequency (%)
6466
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 39
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16985
58.8%
Common 11817
40.9%
Latin 101
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 1210
 
7.1%
서 1131
 
6.7%
시 1121
 
6.6%
중 1116
 
6.6%
구 1106
 
6.5%
울 1101
 
6.5%
특 1091
 
6.4%
별 1091
 
6.4%
호 1073
 
6.3%
번 945
 
5.6%
Other values (279) 6000
35.3%
Latin
ValueCountFrequency (%)
B 13
 
12.9%
A 8
 
7.9%
K 8
 
7.9%
C 8
 
7.9%
S 7
 
6.9%
T 5
 
5.0%
D 5
 
5.0%
I 5
 
5.0%
o 4
 
4.0%
e 3
 
3.0%
Other values (23) 35
34.7%
Common
ValueCountFrequency (%)
6466
54.7%
1 1435
 
12.1%
2 875
 
7.4%
3 529
 
4.5%
4 420
 
3.6%
5 417
 
3.5%
6 367
 
3.1%
0 347
 
2.9%
7 307
 
2.6%
9 288
 
2.4%
Other values (7) 366
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16984
58.8%
ASCII 11918
41.2%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6466
54.3%
1 1435
 
12.0%
2 875
 
7.3%
3 529
 
4.4%
4 420
 
3.5%
5 417
 
3.5%
6 367
 
3.1%
0 347
 
2.9%
7 307
 
2.6%
9 288
 
2.4%
Other values (40) 467
 
3.9%
Hangul
ValueCountFrequency (%)
지 1210
 
7.1%
서 1131
 
6.7%
시 1121
 
6.6%
중 1116
 
6.6%
구 1106
 
6.5%
울 1101
 
6.5%
특 1091
 
6.4%
별 1091
 
6.4%
호 1073
 
6.3%
번 945
 
5.6%
Other values (278) 5999
35.3%
Compat Jamo
ValueCountFrequency (%)
ㅎ 1
100.0%

업소도로명주소
Text

Distinct1048
Distinct (%)88.8%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
2023-12-12T14:40:56.882752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length51
Mean length28.344068
Min length1

Characters and Unicode

Total characters33446
Distinct characters370
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1038 ?
Unique (%)88.0%

Sample

1st row서울특별시 중구 충무로 10. 1층 (필동1가)
2nd row서울특별시 중구 퇴계로24길 13-8. 지하1층 (남산동3가)
3rd row서울특별시 중구 청계천로 100. 시그니쳐타워 지하1층 (수표동)
4th row서울특별시 중구 마장로1길 22. STUDIO W 4층 401-1호 (신당동)
5th row서울특별시 중구 세종대로12길 12. 1층 102호 (남대문로4가)
ValueCountFrequency (%)
서울특별시 1058
 
16.3%
중구 1055
 
16.3%
1층 292
 
4.5%
신당동 171
 
2.6%
퇴계로 83
 
1.3%
을지로 57
 
0.9%
지하1층 50
 
0.8%
장충단로 50
 
0.8%
청계천로 45
 
0.7%
다산로 45
 
0.7%
Other values (1414) 3570
55.1%
2023-12-12T14:40:57.425102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5973
 
17.9%
1 1520
 
4.5%
로 1327
 
4.0%
서 1139
 
3.4%
시 1113
 
3.3%
중 1098
 
3.3%
구 1092
 
3.3%
울 1079
 
3.2%
) 1066
 
3.2%
( 1065
 
3.2%
Other values (360) 16974
50.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18873
56.4%
Space Separator 5973
 
17.9%
Decimal Number 5184
 
15.5%
Close Punctuation 1066
 
3.2%
Open Punctuation 1065
 
3.2%
Other Punctuation 918
 
2.7%
Dash Punctuation 182
 
0.5%
Uppercase Letter 154
 
0.5%
Lowercase Letter 22
 
0.1%
Math Symbol 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 1327
 
7.0%
서 1139
 
6.0%
시 1113
 
5.9%
중 1098
 
5.8%
구 1092
 
5.8%
울 1079
 
5.7%
별 1064
 
5.6%
특 1060
 
5.6%
동 962
 
5.1%
가 661
 
3.5%
Other values (302) 8278
43.9%
Uppercase Letter
ValueCountFrequency (%)
B 29
18.8%
A 13
 
8.4%
C 13
 
8.4%
S 9
 
5.8%
K 9
 
5.8%
E 9
 
5.8%
D 8
 
5.2%
T 7
 
4.5%
G 6
 
3.9%
P 6
 
3.9%
Other values (13) 45
29.2%
Lowercase Letter
ValueCountFrequency (%)
o 3
13.6%
e 3
13.6%
g 2
9.1%
n 2
9.1%
t 2
9.1%
a 2
9.1%
r 1
 
4.5%
k 1
 
4.5%
l 1
 
4.5%
h 1
 
4.5%
Other values (4) 4
18.2%
Decimal Number
ValueCountFrequency (%)
1 1520
29.3%
2 905
17.5%
3 533
 
10.3%
4 429
 
8.3%
0 376
 
7.3%
5 355
 
6.8%
6 332
 
6.4%
7 272
 
5.2%
8 249
 
4.8%
9 213
 
4.1%
Other Punctuation
ValueCountFrequency (%)
. 911
99.2%
/ 3
 
0.3%
, 2
 
0.2%
& 1
 
0.1%
# 1
 
0.1%
Space Separator
ValueCountFrequency (%)
5973
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1066
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1065
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 182
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18873
56.4%
Common 14395
43.0%
Latin 178
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 1327
 
7.0%
서 1139
 
6.0%
시 1113
 
5.9%
중 1098
 
5.8%
구 1092
 
5.8%
울 1079
 
5.7%
별 1064
 
5.6%
특 1060
 
5.6%
동 962
 
5.1%
가 661
 
3.5%
Other values (302) 8278
43.9%
Latin
ValueCountFrequency (%)
B 29
16.3%
A 13
 
7.3%
C 13
 
7.3%
S 9
 
5.1%
K 9
 
5.1%
E 9
 
5.1%
D 8
 
4.5%
T 7
 
3.9%
G 6
 
3.4%
P 6
 
3.4%
Other values (28) 69
38.8%
Common
ValueCountFrequency (%)
5973
41.5%
1 1520
 
10.6%
) 1066
 
7.4%
( 1065
 
7.4%
. 911
 
6.3%
2 905
 
6.3%
3 533
 
3.7%
4 429
 
3.0%
0 376
 
2.6%
5 355
 
2.5%
Other values (10) 1262
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18872
56.4%
ASCII 14571
43.6%
Number Forms 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5973
41.0%
1 1520
 
10.4%
) 1066
 
7.3%
( 1065
 
7.3%
. 911
 
6.3%
2 905
 
6.2%
3 533
 
3.7%
4 429
 
2.9%
0 376
 
2.6%
5 355
 
2.4%
Other values (47) 1438
 
9.9%
Hangul
ValueCountFrequency (%)
로 1327
 
7.0%
서 1139
 
6.0%
시 1113
 
5.9%
중 1098
 
5.8%
구 1092
 
5.8%
울 1079
 
5.7%
별 1064
 
5.6%
특 1060
 
5.6%
동 962
 
5.1%
가 661
 
3.5%
Other values (301) 8277
43.9%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅎ 1
100.0%

지정일자
Text

Distinct904
Distinct (%)76.6%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
2023-12-12T14:40:57.733157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters11800
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique735 ?
Unique (%)62.3%

Sample

1st row2019-05-03
2nd row2019-04-30
3rd row2019-04-29
4th row2019-04-25
5th row2019-04-22
ValueCountFrequency (%)
1999-01-01 45
 
3.8%
0000-00-00 8
 
0.7%
1998-11-28 5
 
0.4%
1998-12-14 5
 
0.4%
1998-12-16 5
 
0.4%
1998-12-09 5
 
0.4%
2000-01-01 4
 
0.3%
2001-09-28 4
 
0.3%
1998-12-05 4
 
0.3%
2009-09-18 4
 
0.3%
Other values (894) 1091
92.5%
2023-12-12T14:40:58.232382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2867
24.3%
- 2360
20.0%
1 2064
17.5%
2 1704
14.4%
9 778
 
6.6%
8 407
 
3.4%
3 373
 
3.2%
7 350
 
3.0%
6 326
 
2.8%
5 300
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9440
80.0%
Dash Punctuation 2360
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2867
30.4%
1 2064
21.9%
2 1704
18.1%
9 778
 
8.2%
8 407
 
4.3%
3 373
 
4.0%
7 350
 
3.7%
6 326
 
3.5%
5 300
 
3.2%
4 271
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 2360
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11800
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2867
24.3%
- 2360
20.0%
1 2064
17.5%
2 1704
14.4%
9 778
 
6.6%
8 407
 
3.4%
3 373
 
3.2%
7 350
 
3.0%
6 326
 
2.8%
5 300
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11800
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2867
24.3%
- 2360
20.0%
1 2064
17.5%
2 1704
14.4%
9 778
 
6.6%
8 407
 
3.4%
3 373
 
3.2%
7 350
 
3.0%
6 326
 
2.8%
5 300
 
2.5%

Interactions

2023-12-12T14:40:54.021899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-12T14:40:54.178402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:40:54.288066image/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

번호업소명업소지번주소업소도로명주소지정일자
01GS25 충무로햇살점서울특별시 중구 필동1가 46번지 1호서울특별시 중구 충무로 10. 1층 (필동1가)2019-05-03
12명동스테이서울특별시 중구 남산동3가 31번지 1호서울특별시 중구 퇴계로24길 13-8. 지하1층 (남산동3가)2019-04-30
23(주)코리아세븐 시그니처타워점서울특별시 중구 수표동 99번지 시그니쳐타워서울특별시 중구 청계천로 100. 시그니쳐타워 지하1층 (수표동)2019-04-29
34더블유매점서울특별시 중구 신당동 213번지 8호 STUDIO W서울특별시 중구 마장로1길 22. STUDIO W 4층 401-1호 (신당동)2019-04-25
45씨유 중구해성점서울특별시 중구 남대문로4가 17번지 19호서울특별시 중구 세종대로12길 12. 1층 102호 (남대문로4가)2019-04-22
56박사공인중개사사무소서울특별시 중구 황학동 1719번지서울특별시 중구 난계로23길 27. B01호 (황학동)2019-04-19
67이마트24 중구광희문점서울특별시 중구 신당동 398번지 1호 인영빌딩서울특별시 중구 청구로 109-1. 인영빌딩 1층 (신당동)2019-04-11
781층매점서울특별시 중구 신당동 251번지 7호 유어스(서울패션센터)서울특별시 중구 마장로 22. 유어스(서울패션센터) 1층 (신당동)2019-04-10
89중앙식품서울특별시 중구 중림동 156번지 118호서울특별시 중구 중림로5길 21 (중림동)2019-04-10
910없음서울특별시 중구 을지로3가 326번지 상지빌딩서울특별시 중구 을지로 114-10. 상지빌딩 1층 107호 (을지로3가)2019-04-08
번호업소명업소지번주소업소도로명주소지정일자
11701171가자시청점서울특별시 중구 필동2가 12호1999-01-01
11711172무서울특별시 중구 태평로1가 61번지 1 호 코리아나호텔 지ㅎ 1층 구내매점서울특별시 중구 세종대로 135 (태평로1가.코리아나호텔 지ㅎ 1층 구내매점)1998-12-09
11721173무서울특별시 중구 태평로1가 31번지 20 호서울특별시 중구 무교로 17-27 (태평로1가)1993-01-13
11731174무서울특별시 중구 다동 53호0000-00-00
11741175무서울특별시 중구 다동 120호서울특별시 중구 을지로3길 20 (다동)0000-00-00
11751176남일식품서울특별시 중구 남대문로5가 18번지 1호서울특별시 중구 세종대로2나길 30 (남대문로5가)1998-12-15
11761177무서울특별시 중구 장충동2가 197호서울특별시 중구 동호로 257-10 (장충동2가)1995-02-02
11771178차돌슈퍼서울특별시 중구 신당동 432번지 178호서울특별시 중구 동호로15가길 20. 1층 (신당동)1989-07-01
11781179창흥상회서울특별시 중구 남대문로3가 85번지 1호 2통 4반서울특별시 중구 남대문로 17-1 (남대문로3가)1989-07-01
11791180가로판매대53서울특별시 중구 남대문로2가 140번지 1호 가판점1989-12-19