Overview

Dataset statistics

Number of variables14
Number of observations10000
Missing cells11804
Missing cells (%)8.4%
Duplicate rows2
Duplicate rows (%)< 0.1%
Total size in memory1.2 MiB
Average record size in memory124.0 B

Variable types

Categorical3
Text5
Numeric4
Boolean1
DateTime1

Alerts

Dataset has 2 (< 0.1%) duplicate rowsDuplicates
WGS84_위도 is highly overall correlated with 시군명High correlation
WGS84_경도 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with WGS84_위도 and 1 other fieldsHigh correlation
다중이용업소여부 is highly imbalanced (99.7%)Imbalance
소재지도로명주소 has 427 (4.3%) missing valuesMissing
WGS84_위도 has 139 (1.4%) missing valuesMissing
WGS84_경도 has 139 (1.4%) missing valuesMissing
폐업일자 has 6056 (60.6%) missing valuesMissing
소재지면적 has 2905 (29.0%) missing valuesMissing
년도 has 2054 (20.5%) missing valuesMissing
소재지면적 is highly skewed (γ1 = 69.73162845)Skewed
소재지면적 has 259 (2.6%) zerosZeros

Reproduction

Analysis started2023-12-10 22:27:01.642784
Analysis finished2023-12-10 22:27:06.718218
Duration5.08 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct32
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
용인시
845 
고양시
834 
성남시
795 
수원시
 
630
남양주시
 
542
Other values (27)
6354 

Length

Max length4
Median length3
Mean length3.0816
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row용인시
2nd row부천시
3rd row안양시
4th row성남시
5th row남양주시

Common Values

ValueCountFrequency (%)
용인시 845
 
8.5%
고양시 834
 
8.3%
성남시 795
 
8.0%
수원시 630
 
6.3%
남양주시 542
 
5.4%
화성시 540
 
5.4%
안산시 484
 
4.8%
부천시 450
 
4.5%
안양시 440
 
4.4%
광주시 428
 
4.3%
Other values (22) 4012
40.1%

Length

2023-12-11T07:27:06.777898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
용인시 845
 
8.5%
고양시 834
 
8.3%
성남시 795
 
8.0%
수원시 630
 
6.3%
남양주시 542
 
5.4%
화성시 540
 
5.4%
안산시 484
 
4.8%
부천시 450
 
4.5%
안양시 440
 
4.4%
광주시 428
 
4.3%
Other values (22) 4012
40.1%

사업장명
Text

Distinct8795
Distinct (%)87.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T07:27:07.037408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length28
Mean length7.6275
Min length2

Characters and Unicode

Total characters76275
Distinct characters921
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7910 ?
Unique (%)79.1%

Sample

1st row홈플러스익스프레스용인성복점
2nd row온누리식품(주)
3rd row지앤씨에프에스
4th row메디포스트(주)
5th row리치플러스
ValueCountFrequency (%)
주식회사 736
 
6.1%
농업회사법인 83
 
0.7%
주)이마트에브리데이 74
 
0.6%
노브랜드 47
 
0.4%
하나로마트 46
 
0.4%
롯데쇼핑(주)롯데슈퍼 43
 
0.4%
주 40
 
0.3%
진로마트 38
 
0.3%
주)지에스리테일 36
 
0.3%
롯데슈퍼 36
 
0.3%
Other values (9065) 10958
90.3%
2023-12-11T07:27:07.503768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 4771
 
6.3%
) 3962
 
5.2%
( 3907
 
5.1%
2143
 
2.8%
마 2086
 
2.7%
트 2061
 
2.7%
이 1965
 
2.6%
식 1709
 
2.2%
스 1619
 
2.1%
사 1484
 
1.9%
Other values (911) 50568
66.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 64068
84.0%
Close Punctuation 3963
 
5.2%
Open Punctuation 3908
 
5.1%
Space Separator 2143
 
2.8%
Uppercase Letter 1274
 
1.7%
Lowercase Letter 478
 
0.6%
Decimal Number 268
 
0.4%
Other Punctuation 132
 
0.2%
Dash Punctuation 38
 
< 0.1%
Other Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 4771
 
7.4%
마 2086
 
3.3%
트 2061
 
3.2%
이 1965
 
3.1%
식 1709
 
2.7%
스 1619
 
2.5%
사 1484
 
2.3%
회 1207
 
1.9%
에 1201
 
1.9%
점 1126
 
1.8%
Other values (839) 44839
70.0%
Uppercase Letter
ValueCountFrequency (%)
S 158
 
12.4%
F 125
 
9.8%
G 106
 
8.3%
B 83
 
6.5%
A 76
 
6.0%
C 74
 
5.8%
N 65
 
5.1%
K 65
 
5.1%
O 64
 
5.0%
E 56
 
4.4%
Other values (15) 402
31.6%
Lowercase Letter
ValueCountFrequency (%)
o 68
14.2%
e 53
11.1%
t 41
 
8.6%
r 36
 
7.5%
a 34
 
7.1%
n 32
 
6.7%
i 31
 
6.5%
s 26
 
5.4%
d 25
 
5.2%
l 20
 
4.2%
Other values (13) 112
23.4%
Decimal Number
ValueCountFrequency (%)
2 68
25.4%
1 53
19.8%
0 48
17.9%
3 26
 
9.7%
5 18
 
6.7%
4 12
 
4.5%
9 11
 
4.1%
6 11
 
4.1%
7 11
 
4.1%
8 10
 
3.7%
Other Punctuation
ValueCountFrequency (%)
& 72
54.5%
. 38
28.8%
, 7
 
5.3%
' 6
 
4.5%
/ 5
 
3.8%
＆ 2
 
1.5%
· 2
 
1.5%
Close Punctuation
ValueCountFrequency (%)
) 3962
> 99.9%
] 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 3907
> 99.9%
[ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
2143
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 64069
84.0%
Common 10452
 
13.7%
Latin 1752
 
2.3%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 4771
 
7.4%
마 2086
 
3.3%
트 2061
 
3.2%
이 1965
 
3.1%
식 1709
 
2.7%
스 1619
 
2.5%
사 1484
 
2.3%
회 1207
 
1.9%
에 1201
 
1.9%
점 1126
 
1.8%
Other values (838) 44840
70.0%
Latin
ValueCountFrequency (%)
S 158
 
9.0%
F 125
 
7.1%
G 106
 
6.1%
B 83
 
4.7%
A 76
 
4.3%
C 74
 
4.2%
o 68
 
3.9%
N 65
 
3.7%
K 65
 
3.7%
O 64
 
3.7%
Other values (38) 868
49.5%
Common
ValueCountFrequency (%)
) 3962
37.9%
( 3907
37.4%
2143
20.5%
& 72
 
0.7%
2 68
 
0.7%
1 53
 
0.5%
0 48
 
0.5%
. 38
 
0.4%
- 38
 
0.4%
3 26
 
0.2%
Other values (13) 97
 
0.9%
Han
ValueCountFrequency (%)
草 1
50.0%
愛 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 64066
84.0%
ASCII 12200
 
16.0%
None 7
 
< 0.1%
CJK 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 4771
 
7.4%
마 2086
 
3.3%
트 2061
 
3.2%
이 1965
 
3.1%
식 1709
 
2.7%
스 1619
 
2.5%
사 1484
 
2.3%
회 1207
 
1.9%
에 1201
 
1.9%
점 1126
 
1.8%
Other values (837) 44837
70.0%
ASCII
ValueCountFrequency (%)
) 3962
32.5%
( 3907
32.0%
2143
17.6%
S 158
 
1.3%
F 125
 
1.0%
G 106
 
0.9%
B 83
 
0.7%
A 76
 
0.6%
C 74
 
0.6%
& 72
 
0.6%
Other values (59) 1494
 
12.2%
None
ValueCountFrequency (%)
㈜ 3
42.9%
＆ 2
28.6%
· 2
28.6%
CJK
ValueCountFrequency (%)
草 1
50.0%
愛 1
50.0%

소재지우편번호
Text

Distinct2914
Distinct (%)29.2%
Missing5
Missing (%)< 0.1%
Memory size156.2 KiB
2023-12-11T07:27:07.831787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1185593
Min length5

Characters and Unicode

Total characters61155
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

Unique1141 ?
Unique (%)11.4%

Sample

1st row448831
2nd row14453
3rd row431812
4th row463400
5th row472935
ValueCountFrequency (%)
410837 84
 
0.8%
462807 55
 
0.6%
410835 50
 
0.5%
472501 33
 
0.3%
431815 32
 
0.3%
449853 31
 
0.3%
445160 28
 
0.3%
472861 27
 
0.3%
410-837 26
 
0.3%
411440 26
 
0.3%
Other values (2904) 9603
96.1%
2023-12-11T07:27:08.325223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 14550
23.8%
8 7906
12.9%
1 6703
11.0%
0 6130
10.0%
2 5233
 
8.6%
3 4731
 
7.7%
6 4252
 
7.0%
5 4249
 
6.9%
7 3193
 
5.2%
9 2394
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59341
97.0%
Dash Punctuation 1814
 
3.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 14550
24.5%
8 7906
13.3%
1 6703
11.3%
0 6130
10.3%
2 5233
 
8.8%
3 4731
 
8.0%
6 4252
 
7.2%
5 4249
 
7.2%
7 3193
 
5.4%
9 2394
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 1814
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 61155
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 14550
23.8%
8 7906
12.9%
1 6703
11.0%
0 6130
10.0%
2 5233
 
8.6%
3 4731
 
7.7%
6 4252
 
7.0%
5 4249
 
6.9%
7 3193
 
5.2%
9 2394
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 61155
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 14550
23.8%
8 7906
12.9%
1 6703
11.0%
0 6130
10.0%
2 5233
 
8.6%
3 4731
 
7.7%
6 4252
 
7.0%
5 4249
 
6.9%
7 3193
 
5.2%
9 2394
 
3.9%

소재지도로명주소
Text

MISSING 

Distinct8869
Distinct (%)92.6%
Missing427
Missing (%)4.3%
Memory size156.2 KiB
2023-12-11T07:27:08.654014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length88
Median length59
Mean length30.481772
Min length13

Characters and Unicode

Total characters291802
Distinct characters673
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8251 ?
Unique (%)86.2%

Sample

1st row경기도 용인시 수지구 성복1로 106 (성복동)
2nd row경기도 부천시 삼작로177번길 27
3rd row경기도 안양시 동안구 평촌대로 217 (호계동,한솔센트럴파크 1차 502호)
4th row경기도 성남시 분당구 대왕판교로644번길 21 (삼평동, 메디포스트 판교사옥 8층 일부)
5th row경기도 남양주시 경춘로1350번길 35 (평내동,리치플러스지하1층)
ValueCountFrequency (%)
경기도 9570
 
15.5%
1층 1656
 
2.7%
고양시 822
 
1.3%
용인시 813
 
1.3%
성남시 784
 
1.3%
수원시 609
 
1.0%
2층 569
 
0.9%
남양주시 531
 
0.9%
화성시 525
 
0.8%
분당구 448
 
0.7%
Other values (11202) 45590
73.6%
2023-12-11T07:27:09.112692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
52369
 
17.9%
1 12905
 
4.4%
기 10120
 
3.5%
시 10023
 
3.4%
도 9979
 
3.4%
경 9963
 
3.4%
동 8748
 
3.0%
로 8703
 
3.0%
, 7272
 
2.5%
2 7201
 
2.5%
Other values (663) 154519
53.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 165012
56.5%
Space Separator 52369
 
17.9%
Decimal Number 49677
 
17.0%
Other Punctuation 7330
 
2.5%
Open Punctuation 6713
 
2.3%
Close Punctuation 6713
 
2.3%
Dash Punctuation 2497
 
0.9%
Uppercase Letter 1267
 
0.4%
Math Symbol 127
 
< 0.1%
Lowercase Letter 83
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 10120
 
6.1%
시 10023
 
6.1%
도 9979
 
6.0%
경 9963
 
6.0%
동 8748
 
5.3%
로 8703
 
5.3%
길 4444
 
2.7%
구 4340
 
2.6%
층 4127
 
2.5%
호 3304
 
2.0%
Other values (591) 91261
55.3%
Uppercase Letter
ValueCountFrequency (%)
B 386
30.5%
A 219
17.3%
C 81
 
6.4%
I 69
 
5.4%
T 59
 
4.7%
E 47
 
3.7%
D 43
 
3.4%
S 43
 
3.4%
K 37
 
2.9%
L 33
 
2.6%
Other values (16) 250
19.7%
Lowercase Letter
ValueCountFrequency (%)
e 22
26.5%
a 11
13.3%
s 10
12.0%
t 10
12.0%
n 7
 
8.4%
k 6
 
7.2%
l 4
 
4.8%
c 3
 
3.6%
b 2
 
2.4%
r 2
 
2.4%
Other values (6) 6
 
7.2%
Decimal Number
ValueCountFrequency (%)
1 12905
26.0%
2 7201
14.5%
3 5087
 
10.2%
0 4817
 
9.7%
4 4164
 
8.4%
5 3731
 
7.5%
6 3416
 
6.9%
7 3066
 
6.2%
8 2680
 
5.4%
9 2610
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 7272
99.2%
. 37
 
0.5%
& 9
 
0.1%
: 4
 
0.1%
@ 3
 
< 0.1%
/ 2
 
< 0.1%
＆ 1
 
< 0.1%
' 1
 
< 0.1%
※ 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 124
97.6%
∼ 1
 
0.8%
∥ 1
 
0.8%
+ 1
 
0.8%
Letter Number
ValueCountFrequency (%)
Ⅱ 9
64.3%
Ⅲ 3
 
21.4%
Ⅰ 2
 
14.3%
Space Separator
ValueCountFrequency (%)
52369
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6713
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6713
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2497
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 165012
56.5%
Common 125426
43.0%
Latin 1364
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 10120
 
6.1%
시 10023
 
6.1%
도 9979
 
6.0%
경 9963
 
6.0%
동 8748
 
5.3%
로 8703
 
5.3%
길 4444
 
2.7%
구 4340
 
2.6%
층 4127
 
2.5%
호 3304
 
2.0%
Other values (591) 91261
55.3%
Latin
ValueCountFrequency (%)
B 386
28.3%
A 219
16.1%
C 81
 
5.9%
I 69
 
5.1%
T 59
 
4.3%
E 47
 
3.4%
D 43
 
3.2%
S 43
 
3.2%
K 37
 
2.7%
L 33
 
2.4%
Other values (35) 347
25.4%
Common
ValueCountFrequency (%)
52369
41.8%
1 12905
 
10.3%
, 7272
 
5.8%
2 7201
 
5.7%
( 6713
 
5.4%
) 6713
 
5.4%
3 5087
 
4.1%
0 4817
 
3.8%
4 4164
 
3.3%
5 3731
 
3.0%
Other values (17) 14454
 
11.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 165012
56.5%
ASCII 126772
43.4%
Number Forms 14
 
< 0.1%
Math Operators 2
 
< 0.1%
None 1
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
52369
41.3%
1 12905
 
10.2%
, 7272
 
5.7%
2 7201
 
5.7%
( 6713
 
5.3%
) 6713
 
5.3%
3 5087
 
4.0%
0 4817
 
3.8%
4 4164
 
3.3%
5 3731
 
2.9%
Other values (55) 15800
 
12.5%
Hangul
ValueCountFrequency (%)
기 10120
 
6.1%
시 10023
 
6.1%
도 9979
 
6.0%
경 9963
 
6.0%
동 8748
 
5.3%
로 8703
 
5.3%
길 4444
 
2.7%
구 4340
 
2.6%
층 4127
 
2.5%
호 3304
 
2.0%
Other values (591) 91261
55.3%
Number Forms
ValueCountFrequency (%)
Ⅱ 9
64.3%
Ⅲ 3
 
21.4%
Ⅰ 2
 
14.3%
None
ValueCountFrequency (%)
＆ 1
100.0%
Math Operators
ValueCountFrequency (%)
∼ 1
50.0%
∥ 1
50.0%
Punctuation
ValueCountFrequency (%)
※ 1
100.0%

소재지지번주소
Text

Distinct9580
Distinct (%)95.8%
Missing2
Missing (%)< 0.1%
Memory size156.2 KiB
2023-12-11T07:27:09.487973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length120
Median length63
Mean length26.947489
Min length14

Characters and Unicode

Total characters269421
Distinct characters625
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9226 ?
Unique (%)92.3%

Sample

1st row경기도 용인시 수지구 성복동 276-1번지
2nd row경기도 부천시 내동 182-18번지 (지상2층 일부)
3rd row경기도 안양시 동안구 호계동 1048-3번지 한솔센트럴파크 1차 502호
4th row경기도 성남시 분당구 삼평동 672-4번지 메디포스트 판교사옥 8층 일부
5th row경기도 남양주시 평내동 140번지 리치플러스지하1층
ValueCountFrequency (%)
경기도 9995
 
17.4%
1층 1185
 
2.1%
용인시 846
 
1.5%
고양시 834
 
1.5%
성남시 794
 
1.4%
수원시 629
 
1.1%
남양주시 542
 
0.9%
화성시 540
 
0.9%
안산시 484
 
0.8%
분당구 451
 
0.8%
Other values (11946) 41066
71.6%
2023-12-11T07:27:10.056696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
49116
 
18.2%
1 12643
 
4.7%
기 10427
 
3.9%
도 10357
 
3.8%
시 10334
 
3.8%
지 10085
 
3.7%
경 10057
 
3.7%
동 9694
 
3.6%
번 8056
 
3.0%
- 7798
 
2.9%
Other values (615) 130854
48.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 156906
58.2%
Decimal Number 51915
 
19.3%
Space Separator 49116
 
18.2%
Dash Punctuation 7798
 
2.9%
Uppercase Letter 1114
 
0.4%
Other Punctuation 904
 
0.3%
Open Punctuation 740
 
0.3%
Close Punctuation 740
 
0.3%
Math Symbol 107
 
< 0.1%
Lowercase Letter 68
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 10427
 
6.6%
도 10357
 
6.6%
시 10334
 
6.6%
지 10085
 
6.4%
경 10057
 
6.4%
동 9694
 
6.2%
번 8056
 
5.1%
구 4415
 
2.8%
양 3221
 
2.1%
리 3194
 
2.0%
Other values (546) 77066
49.1%
Uppercase Letter
ValueCountFrequency (%)
B 321
28.8%
A 189
17.0%
C 74
 
6.6%
I 72
 
6.5%
T 53
 
4.8%
E 47
 
4.2%
S 41
 
3.7%
D 39
 
3.5%
K 34
 
3.1%
L 30
 
2.7%
Other values (16) 214
19.2%
Lowercase Letter
ValueCountFrequency (%)
e 22
32.4%
a 8
 
11.8%
k 7
 
10.3%
n 6
 
8.8%
s 5
 
7.4%
t 4
 
5.9%
c 4
 
5.9%
l 3
 
4.4%
r 2
 
2.9%
y 2
 
2.9%
Other values (5) 5
 
7.4%
Decimal Number
ValueCountFrequency (%)
1 12643
24.4%
2 6805
13.1%
3 5460
10.5%
0 4748
 
9.1%
4 4535
 
8.7%
5 4210
 
8.1%
6 3906
 
7.5%
7 3540
 
6.8%
8 3225
 
6.2%
9 2843
 
5.5%
Other Punctuation
ValueCountFrequency (%)
, 834
92.3%
. 47
 
5.2%
& 10
 
1.1%
@ 5
 
0.6%
/ 3
 
0.3%
: 3
 
0.3%
· 1
 
0.1%
' 1
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 105
98.1%
+ 1
 
0.9%
∥ 1
 
0.9%
Letter Number
ValueCountFrequency (%)
Ⅱ 8
61.5%
Ⅲ 3
 
23.1%
Ⅰ 2
 
15.4%
Space Separator
ValueCountFrequency (%)
49116
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7798
100.0%
Open Punctuation
ValueCountFrequency (%)
( 740
100.0%
Close Punctuation
ValueCountFrequency (%)
) 740
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 156906
58.2%
Common 111320
41.3%
Latin 1195
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 10427
 
6.6%
도 10357
 
6.6%
시 10334
 
6.6%
지 10085
 
6.4%
경 10057
 
6.4%
동 9694
 
6.2%
번 8056
 
5.1%
구 4415
 
2.8%
양 3221
 
2.1%
리 3194
 
2.0%
Other values (546) 77066
49.1%
Latin
ValueCountFrequency (%)
B 321
26.9%
A 189
15.8%
C 74
 
6.2%
I 72
 
6.0%
T 53
 
4.4%
E 47
 
3.9%
S 41
 
3.4%
D 39
 
3.3%
K 34
 
2.8%
L 30
 
2.5%
Other values (34) 295
24.7%
Common
ValueCountFrequency (%)
49116
44.1%
1 12643
 
11.4%
- 7798
 
7.0%
2 6805
 
6.1%
3 5460
 
4.9%
0 4748
 
4.3%
4 4535
 
4.1%
5 4210
 
3.8%
6 3906
 
3.5%
7 3540
 
3.2%
Other values (15) 8559
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 156905
58.2%
ASCII 112500
41.8%
Number Forms 13
 
< 0.1%
Compat Jamo 1
 
< 0.1%
None 1
 
< 0.1%
Math Operators 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
49116
43.7%
1 12643
 
11.2%
- 7798
 
6.9%
2 6805
 
6.0%
3 5460
 
4.9%
0 4748
 
4.2%
4 4535
 
4.0%
5 4210
 
3.7%
6 3906
 
3.5%
7 3540
 
3.1%
Other values (54) 9739
 
8.7%
Hangul
ValueCountFrequency (%)
기 10427
 
6.6%
도 10357
 
6.6%
시 10334
 
6.6%
지 10085
 
6.4%
경 10057
 
6.4%
동 9694
 
6.2%
번 8056
 
5.1%
구 4415
 
2.8%
양 3221
 
2.1%
리 3194
 
2.0%
Other values (545) 77065
49.1%
Number Forms
ValueCountFrequency (%)
Ⅱ 8
61.5%
Ⅲ 3
 
23.1%
Ⅰ 2
 
15.4%
Compat Jamo
ValueCountFrequency (%)
ㅣ 1
100.0%
None
ValueCountFrequency (%)
· 1
100.0%
Math Operators
ValueCountFrequency (%)
∥ 1
100.0%

WGS84_위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct7782
Distinct (%)78.9%
Missing139
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean37.445579
Minimum36.491092
Maximum38.185224
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T07:27:10.192202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.491092
5-th percentile37.085762
Q137.29216
median37.402749
Q337.64018
95-th percentile37.814534
Maximum38.185224
Range1.6941318
Interquartile range (IQR)0.34801983

Descriptive statistics

Standard deviation0.21923117
Coefficient of variation (CV)0.0058546611
Kurtosis-0.50093913
Mean37.445579
Median Absolute Deviation (MAD)0.14638317
Skewness0.14892858
Sum369250.85
Variance0.048062307
MonotonicityNot monotonic
2023-12-11T07:27:10.321519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.3923317778 16
 
0.2%
37.6103315074 14
 
0.1%
37.3889401776 12
 
0.1%
37.3443549674 12
 
0.1%
37.3716127805 11
 
0.1%
37.6548220944 9
 
0.1%
37.2748617644 9
 
0.1%
37.2378906598 9
 
0.1%
37.436719428 8
 
0.1%
37.4399480135 8
 
0.1%
Other values (7772) 9753
97.5%
(Missing) 139
 
1.4%
ValueCountFrequency (%)
36.491091941 1
< 0.1%
36.9165803501 1
< 0.1%
36.9168961792 1
< 0.1%
36.938720379 1
< 0.1%
36.9402870569 2
< 0.1%
36.9439296295 1
< 0.1%
36.9443129561 1
< 0.1%
36.9448447964 1
< 0.1%
36.9463540043 1
< 0.1%
36.9469764639 1
< 0.1%
ValueCountFrequency (%)
38.1852237833 1
< 0.1%
38.1563638656 1
< 0.1%
38.1121625152 1
< 0.1%
38.1044947446 1
< 0.1%
38.099152433 1
< 0.1%
38.0904627858 1
< 0.1%
38.0901656506 1
< 0.1%
38.0898143955 1
< 0.1%
38.0898048968 1
< 0.1%
38.0857792983 1
< 0.1%

WGS84_경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct7782
Distinct (%)78.9%
Missing139
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean127.02154
Minimum126.52556
Maximum127.7562
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T07:27:10.737605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.52556
5-th percentile126.72342
Q1126.83715
median127.04094
Q3127.15294
95-th percentile127.38112
Maximum127.7562
Range1.2306471
Interquartile range (IQR)0.31579041

Descriptive statistics

Standard deviation0.20883862
Coefficient of variation (CV)0.0016441197
Kurtosis-0.056624418
Mean127.02154
Median Absolute Deviation (MAD)0.15393886
Skewness0.31716227
Sum1252559.4
Variance0.043613568
MonotonicityNot monotonic
2023-12-11T07:27:10.923871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9565123356 16
 
0.2%
127.1454453107 14
 
0.1%
127.122552825 12
 
0.1%
127.10510721 12
 
0.1%
126.9514327046 11
 
0.1%
126.7707679935 9
 
0.1%
127.0800687639 9
 
0.1%
127.1103081978 9
 
0.1%
127.1698572002 8
 
0.1%
127.1769873928 8
 
0.1%
Other values (7772) 9753
97.5%
(Missing) 139
 
1.4%
ValueCountFrequency (%)
126.5255574103 1
< 0.1%
126.5392340859 1
< 0.1%
126.5431591094 2
< 0.1%
126.5444458283 1
< 0.1%
126.5448899178 1
< 0.1%
126.5472916706 1
< 0.1%
126.5497387546 1
< 0.1%
126.5534964268 1
< 0.1%
126.5538438955 1
< 0.1%
126.553924773 1
< 0.1%
ValueCountFrequency (%)
127.7562044742 1
< 0.1%
127.7556986623 1
< 0.1%
127.7555835694 1
< 0.1%
127.7410826858 1
< 0.1%
127.7390928435 1
< 0.1%
127.7322701087 1
< 0.1%
127.7174001724 1
< 0.1%
127.7117391788 2
< 0.1%
127.7104484814 1
< 0.1%
127.7102109036 1
< 0.1%

인허가일자
Text

Distinct5083
Distinct (%)50.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T07:27:11.262290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.3948
Min length6

Characters and Unicode

Total characters83948
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

Unique2632 ?
Unique (%)26.3%

Sample

1st row20101014
2nd row20100804
3rd row20080219
4th row20170613
5th row20070226
ValueCountFrequency (%)
2023-05-11 13
 
0.1%
2023-10-05 13
 
0.1%
2023-10-11 12
 
0.1%
2023-04-21 11
 
0.1%
2023-07-21 11
 
0.1%
2023-04-11 10
 
0.1%
20150511 10
 
0.1%
20170220 10
 
0.1%
2023-09-11 10
 
0.1%
2023-04-07 10
 
0.1%
Other values (5073) 9890
98.9%
2023-12-11T07:27:11.724705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 25057
29.8%
2 17020
20.3%
1 14937
17.8%
9 3997
 
4.8%
- 3954
 
4.7%
3 3916
 
4.7%
6 3133
 
3.7%
7 3120
 
3.7%
8 3000
 
3.6%
5 2911
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 79994
95.3%
Dash Punctuation 3954
 
4.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 25057
31.3%
2 17020
21.3%
1 14937
18.7%
9 3997
 
5.0%
3 3916
 
4.9%
6 3133
 
3.9%
7 3120
 
3.9%
8 3000
 
3.8%
5 2911
 
3.6%
4 2903
 
3.6%
Dash Punctuation
ValueCountFrequency (%)
- 3954
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 83948
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 25057
29.8%
2 17020
20.3%
1 14937
17.8%
9 3997
 
4.8%
- 3954
 
4.7%
3 3916
 
4.7%
6 3133
 
3.7%
7 3120
 
3.7%
8 3000
 
3.6%
5 2911
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 83948
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 25057
29.8%
2 17020
20.3%
1 14937
17.8%
9 3997
 
4.8%
- 3954
 
4.7%
3 3916
 
4.7%
6 3133
 
3.7%
7 3120
 
3.7%
8 3000
 
3.6%
5 2911
 
3.5%

영업상태명
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
운영중
4486 
폐업 등
3537 
영업
1570 
폐업
 
407

Length

Max length4
Median length3
Mean length3.156
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row폐업 등
2nd row폐업 등
3rd row폐업 등
4th row운영중
5th row운영중

Common Values

ValueCountFrequency (%)
운영중 4486
44.9%
폐업 등 3537
35.4%
영업 1570
 
15.7%
폐업 407
 
4.1%

Length

2023-12-11T07:27:11.890224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:27:12.007890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운영중 4486
33.1%
폐업 3944
29.1%
등 3537
26.1%
영업 1570
 
11.6%

다중이용업소여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing77
Missing (%)0.8%
Memory size97.7 KiB
False
9921 
True
 
2
(Missing)
 
77
ValueCountFrequency (%)
False 9921
99.2%
True 2
 
< 0.1%
(Missing) 77
 
0.8%
2023-12-11T07:27:12.098191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

폐업일자
Date

MISSING 

Distinct2367
Distinct (%)60.0%
Missing6056
Missing (%)60.6%
Memory size156.2 KiB
Minimum1989-01-01 00:00:00
Maximum2023-12-06 00:00:00
2023-12-11T07:27:12.190829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:27:12.312565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업종명
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
유통전문판매업
6908 
식품판매업(기타)
2852 
식용얼음판매업
 
240

Length

Max length9
Median length7
Mean length7.5704
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row식품판매업(기타)
2nd row유통전문판매업
3rd row유통전문판매업
4th row유통전문판매업
5th row식품판매업(기타)

Common Values

ValueCountFrequency (%)
유통전문판매업 6908
69.1%
식품판매업(기타) 2852
28.5%
식용얼음판매업 240
 
2.4%

Length

2023-12-11T07:27:12.434984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:27:12.543165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통전문판매업 6908
69.1%
식품판매업(기타 2852
28.5%
식용얼음판매업 240
 
2.4%

소재지면적
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct4680
Distinct (%)66.0%
Missing2905
Missing (%)29.0%
Infinite0
Infinite (%)0.0%
Mean920.10152
Minimum0
Maximum2171817
Zeros259
Zeros (%)2.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T07:27:12.668725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5.76
Q133
median105.98
Q3456.695
95-th percentile1171.066
Maximum2171817
Range2171817
Interquartile range (IQR)423.695

Descriptive statistics

Standard deviation27978.304
Coefficient of variation (CV)30.407845
Kurtosis5216.4578
Mean920.10152
Median Absolute Deviation (MAD)92.3
Skewness69.731628
Sum6528120.3
Variance7.827855 × 108
MonotonicityNot monotonic
2023-12-11T07:27:12.795117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 259
 
2.6%
33.0 77
 
0.8%
198.0 58
 
0.6%
30.0 56
 
0.6%
20.0 50
 
0.5%
10.0 50
 
0.5%
15.0 38
 
0.4%
100.0 37
 
0.4%
16.5 31
 
0.3%
50.0 30
 
0.3%
Other values (4670) 6409
64.1%
(Missing) 2905
29.0%
ValueCountFrequency (%)
0.0 259
2.6%
1.0 2
 
< 0.1%
1.28 1
 
< 0.1%
2.41 1
 
< 0.1%
2.7 1
 
< 0.1%
2.86 1
 
< 0.1%
3.0 6
 
0.1%
3.06 1
 
< 0.1%
3.25 1
 
< 0.1%
3.3 17
 
0.2%
ValueCountFrequency (%)
2171817.0 1
< 0.1%
811361.0 1
< 0.1%
407347.0 1
< 0.1%
66114.13 1
< 0.1%
32543.36 1
< 0.1%
23260.0 1
< 0.1%
20579.0 1
< 0.1%
19889.2 1
< 0.1%
19149.17 1
< 0.1%
18639.95 1
< 0.1%

년도
Real number (ℝ)

MISSING 

Distinct41
Distinct (%)0.5%
Missing2054
Missing (%)20.5%
Infinite0
Infinite (%)0.0%
Mean2009.365
Minimum1882
Maximum2018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T07:27:12.916211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1882
5-th percentile1997
Q12004
median2011
Q32015
95-th percentile2018
Maximum2018
Range136
Interquartile range (IQR)11

Descriptive statistics

Standard deviation6.8771802
Coefficient of variation (CV)0.003422564
Kurtosis14.716449
Mean2009.365
Median Absolute Deviation (MAD)5
Skewness-1.4846377
Sum15966414
Variance47.295608
MonotonicityNot monotonic
2023-12-11T07:27:13.105427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
2017 684
 
6.8%
2015 639
 
6.4%
2016 613
 
6.1%
2014 544
 
5.4%
2018 450
 
4.5%
2013 437
 
4.4%
2012 365
 
3.6%
2010 336
 
3.4%
2011 335
 
3.4%
2008 335
 
3.4%
Other values (31) 3208
32.1%
(Missing) 2054
20.5%
ValueCountFrequency (%)
1882 1
 
< 0.1%
1971 2
 
< 0.1%
1974 1
 
< 0.1%
1976 4
< 0.1%
1979 2
 
< 0.1%
1980 2
 
< 0.1%
1981 2
 
< 0.1%
1985 3
< 0.1%
1986 6
0.1%
1987 2
 
< 0.1%
ValueCountFrequency (%)
2018 450
4.5%
2017 684
6.8%
2016 613
6.1%
2015 639
6.4%
2014 544
5.4%
2013 437
4.4%
2012 365
3.6%
2011 335
3.4%
2010 336
3.4%
2009 318
3.2%

Interactions

2023-12-11T07:27:05.617779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:27:04.305828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:27:04.703937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:27:05.154218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:27:05.731090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:27:04.414872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:27:04.836756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:27:05.252543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:27:05.864303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:27:04.511449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:27:04.955245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:27:05.352756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:27:05.976827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:27:04.605761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:27:05.056270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:27:05.464032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:27:13.266864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명WGS84_위도WGS84_경도영업상태명다중이용업소여부업종명소재지면적년도
시군명1.0000.9460.9270.2610.0000.2970.0000.207
WGS84_위도0.9461.0000.3860.0950.0000.1770.0000.123
WGS84_경도0.9270.3861.0000.1430.0000.1160.0000.057
영업상태명0.2610.0950.1431.0000.0440.1310.0140.424
다중이용업소여부0.0000.0000.0000.0441.0000.0000.0000.000
업종명0.2970.1770.1160.1310.0001.0000.0060.308
소재지면적0.0000.0000.0000.0140.0000.0061.0000.000
년도0.2070.1230.0570.4240.0000.3080.0001.000
2023-12-11T07:27:13.369875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명다중이용업소여부영업상태명시군명
업종명1.0000.0000.1240.156
다중이용업소여부0.0001.0000.0290.000
영업상태명0.1240.0291.0000.138
시군명0.1560.0000.1381.000
2023-12-11T07:27:13.452547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
WGS84_위도WGS84_경도소재지면적년도시군명영업상태명다중이용업소여부업종명
WGS84_위도1.000-0.229-0.0310.0180.7490.0610.0000.079
WGS84_경도-0.2291.0000.0080.0350.6640.0860.0000.069
소재지면적-0.0310.0081.000-0.1090.0000.0090.0000.005
년도0.0180.035-0.1091.0000.0940.2850.0000.300
시군명0.7490.6640.0000.0941.0000.1380.0000.156
영업상태명0.0610.0860.0090.2850.1381.0000.0290.124
다중이용업소여부0.0000.0000.0000.0000.0000.0291.0000.000
업종명0.0790.0690.0050.3000.1560.1240.0001.000

Missing values

2023-12-11T07:27:06.146847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:27:06.359145image/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.
2023-12-11T07:27:06.575225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

시군명사업장명소재지우편번호소재지도로명주소소재지지번주소WGS84_위도WGS84_경도인허가일자영업상태명다중이용업소여부폐업일자업종명소재지면적년도
8032용인시홈플러스익스프레스용인성복점448831경기도 용인시 수지구 성복1로 106 (성복동)경기도 용인시 수지구 성복동 276-1번지37.316806127.06825620101014폐업 등N20131002식품판매업(기타)324.02010
9948부천시온누리식품(주)14453경기도 부천시 삼작로177번길 27경기도 부천시 내동 182-18번지 (지상2층 일부)37.521415126.78091820100804폐업 등N20100811유통전문판매업<NA>2010
9730안양시지앤씨에프에스431812경기도 안양시 동안구 평촌대로 217 (호계동,한솔센트럴파크 1차 502호)경기도 안양시 동안구 호계동 1048-3번지 한솔센트럴파크 1차 502호37.39065126.95547420080219폐업 등N20151116유통전문판매업21.02008
4138성남시메디포스트(주)463400경기도 성남시 분당구 대왕판교로644번길 21 (삼평동, 메디포스트 판교사옥 8층 일부)경기도 성남시 분당구 삼평동 672-4번지 메디포스트 판교사옥 8층 일부37.400163127.10898420170613운영중N<NA>유통전문판매업567.02017
6237남양주시리치플러스472935경기도 남양주시 경춘로1350번길 35 (평내동,리치플러스지하1층)경기도 남양주시 평내동 140번지 리치플러스지하1층37.650343127.24321120070226운영중N<NA>식품판매업(기타)720.02007
10458수원시(주)씨티트레이딩441850<NA>경기도 수원시 권선구 오목천동 497-1번지37.243936126.96397620091109폐업 등N20091124유통전문판매업98.02009
2366남양주시(주)농서식품472865경기도 남양주시 진접읍 금강로 1588경기도 남양주시 진접읍 장현리 47-1번지37.731484127.19513120040628운영중N<NA>유통전문판매업25.22004
2634남양주시주식회사 쏘이마루472844경기도 남양주시 화도읍 경춘로2347번길 11, 1층경기도 남양주시 화도읍 답내리 227-6번지37.658816127.34703420120308운영중N<NA>유통전문판매업83.02012
6143수원시(주)이마트 트레이더스 수원점443390경기도 수원시 영통구 삼성로 2 (신동, 이마트 트레이더스 수원점)경기도 수원시 영통구 신동 507-1번지37.246109127.04864620140808운영중N<NA>식품판매업(기타)11886.482014
8545성남시덕산유통461820경기도 성남시 수정구 시민로241번길 13경기도 성남시 수정구 태평동 2591번지 (1층, 지층) (영장1길38)37.44877127.13869120050321폐업 등N20081218유통전문판매업19.142005
시군명사업장명소재지우편번호소재지도로명주소소재지지번주소WGS84_위도WGS84_경도인허가일자영업상태명다중이용업소여부폐업일자업종명소재지면적년도
8055용인시지스퀘어마켓448120경기도 용인시 수지구 동천로 109경기도 용인시 수지구 동천동 941-1번지 외3필지 지층,1층37.337975127.09232820110407폐업 등N20110427식품판매업(기타)1486.482011
3193용인시(주)동성식품449935경기도 용인시 처인구 유림로 135 (유방동,외 6필지)경기도 용인시 처인구 유방동 625번지 외 6필지37.259956127.19965820000407운영중N<NA>유통전문판매업<NA>2000
5361이천시(주)스마일467853경기도 이천시 대월면 사동로 164경기도 이천시 대월면 사동리 347-155번지37.243661127.49538920090608운영중N<NA>식품판매업(기타)818.652009
9047군포시농업회사법인쿱푸드시스템(주)435831경기도 군포시 경수대로 455 (당정동, 한솔테크노타운 301호,411호,701호)경기도 군포시 당정동 16-1번지 한솔테크노타운 301호,411호,701호37.363653126.95909120090507폐업 등N20120817유통전문판매업253.422009
4014남양주시DS푸드대왕472833경기도 남양주시 진건읍 진건오남로86번길 30, 가동 3호경기도 남양주시 진건읍 용정리 785-35번지37.658267127.18088520180326운영중N<NA>유통전문판매업33.02018
10493용인시(주)경원수산상사446904<NA>경기도 용인시 기흥구 보라동 539-2번지<NA><NA>20000327폐업 등N20060608유통전문판매업<NA>2000
2826파주시(주)아라리413841경기도 파주시 탄현면 평화로574번길 73-3, 1층 (일부)경기도 파주시 탄현면 갈현리 229번지 1층일부37.776246126.72131720160517운영중N<NA>유통전문판매업15.02016
351화성시(주)오렌지식자재마트445-891경기도 화성시 봉담읍 샘마을길 14, 1동경기도 화성시 봉담읍 상리 24-4 1동37.218412126.9493212023-05-11영업N<NA>식품판매업(기타)<NA><NA>
7394안양시에스마트(주)430823경기도 안양시 만안구 안양로 225, 2층 (안양동)경기도 안양시 만안구 안양동 445-1번지37.393258126.92543820111208폐업 등N20130205식품판매업(기타)<NA>2011
3454파주시늘푸른자활의집413907경기도 파주시 문산읍 바리골길 421, 다동경기도 파주시 문산읍 이천리 485-1번지 다동37.855033126.82737620050923운영중N<NA>유통전문판매업33.02005

Duplicate rows

Most frequently occurring

시군명사업장명소재지우편번호소재지도로명주소소재지지번주소WGS84_위도WGS84_경도인허가일자영업상태명다중이용업소여부폐업일자업종명소재지면적년도# duplicates
0오산시광고장수447-240경기도 오산시 독산성로270번길 141, 1층 (세교동)경기도 오산시 세교동 483-2 1층37.183894127.0368832021-04-22폐업N2023-05-10유통전문판매업<NA><NA>3
1화성시쿨마트445310경기도 화성시 효행로 237 (기안동)경기도 화성시 기안동 335-8번지37.226548126.97213320060711폐업 등N20130313식품판매업(기타)<NA>20062