Overview

Dataset statistics

Number of variables44
Number of observations7053
Missing cells74140
Missing cells (%)23.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 MiB
Average record size in memory377.0 B

Variable types

Categorical19
Text6
DateTime4
Unsupported7
Numeric7
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author영등포구
URLhttps://data.seoul.go.kr/dataList/OA-18695/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
영업장주변구분명 is highly imbalanced (59.8%)Imbalance
등급구분명 is highly imbalanced (56.8%)Imbalance
총인원 is highly imbalanced (77.2%)Imbalance
본사종업원수 is highly imbalanced (77.0%)Imbalance
공장사무직종업원수 is highly imbalanced (77.0%)Imbalance
공장판매직종업원수 is highly imbalanced (77.0%)Imbalance
공장생산직종업원수 is highly imbalanced (77.0%)Imbalance
보증액 is highly imbalanced (77.0%)Imbalance
월세액 is highly imbalanced (77.0%)Imbalance
다중이용업소여부 is highly imbalanced (89.3%)Imbalance
전통업소주된음식 is highly imbalanced (99.8%)Imbalance
인허가취소일자 has 7053 (100.0%) missing valuesMissing
폐업일자 has 2104 (29.8%) missing valuesMissing
휴업시작일자 has 7053 (100.0%) missing valuesMissing
휴업종료일자 has 7053 (100.0%) missing valuesMissing
재개업일자 has 7053 (100.0%) missing valuesMissing
전화번호 has 3823 (54.2%) missing valuesMissing
소재지면적 has 346 (4.9%) missing valuesMissing
도로명주소 has 2378 (33.7%) missing valuesMissing
도로명우편번호 has 2472 (35.0%) missing valuesMissing
좌표정보(X) has 273 (3.9%) missing valuesMissing
좌표정보(Y) has 273 (3.9%) missing valuesMissing
남성종사자수 has 4964 (70.4%) missing valuesMissing
여성종사자수 has 4946 (70.1%) missing valuesMissing
건물소유구분명 has 7053 (100.0%) missing valuesMissing
다중이용업소여부 has 1553 (22.0%) missing valuesMissing
시설총규모 has 1553 (22.0%) missing valuesMissing
전통업소지정번호 has 7053 (100.0%) missing valuesMissing
홈페이지 has 7053 (100.0%) missing valuesMissing
도로명우편번호 is highly skewed (γ1 = 60.37873814)Skewed
남성종사자수 is highly skewed (γ1 = 22.85783445)Skewed
여성종사자수 is highly skewed (γ1 = 28.22291517)Skewed
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물소유구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
남성종사자수 has 1766 (25.0%) zerosZeros
여성종사자수 has 1180 (16.7%) zerosZeros
시설총규모 has 338 (4.8%) zerosZeros

Reproduction

Analysis started2024-05-11 06:14:17.539393
Analysis finished2024-05-11 06:14:20.471629
Duration2.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.2 KiB
3180000
7053 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3180000
2nd row3180000
3rd row3180000
4th row3180000
5th row3180000

Common Values

ValueCountFrequency (%)
3180000 7053
100.0%

Length

2024-05-11T15:14:20.605059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:20.772518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3180000 7053
100.0%

관리번호
Text

UNIQUE 

Distinct7053
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size55.2 KiB
2024-05-11T15:14:21.048937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters155166
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

Unique7053 ?
Unique (%)100.0%

Sample

1st row3180000-104-1913-01275
2nd row3180000-104-1933-01958
3rd row3180000-104-1934-00386
4th row3180000-104-1966-00957
5th row3180000-104-1967-00912
ValueCountFrequency (%)
3180000-104-1913-01275 1
 
< 0.1%
3180000-104-2017-00110 1
 
< 0.1%
3180000-104-2017-00121 1
 
< 0.1%
3180000-104-2017-00120 1
 
< 0.1%
3180000-104-2017-00119 1
 
< 0.1%
3180000-104-2017-00118 1
 
< 0.1%
3180000-104-2017-00117 1
 
< 0.1%
3180000-104-2017-00116 1
 
< 0.1%
3180000-104-2017-00115 1
 
< 0.1%
3180000-104-2017-00114 1
 
< 0.1%
Other values (7043) 7043
99.9%
2024-05-11T15:14:21.471810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 59254
38.2%
1 23705
15.3%
- 21159
 
13.6%
2 10256
 
6.6%
3 10096
 
6.5%
8 9764
 
6.3%
4 9486
 
6.1%
9 4750
 
3.1%
7 2322
 
1.5%
6 2312
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 134007
86.4%
Dash Punctuation 21159
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 59254
44.2%
1 23705
17.7%
2 10256
 
7.7%
3 10096
 
7.5%
8 9764
 
7.3%
4 9486
 
7.1%
9 4750
 
3.5%
7 2322
 
1.7%
6 2312
 
1.7%
5 2062
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 21159
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 155166
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 59254
38.2%
1 23705
15.3%
- 21159
 
13.6%
2 10256
 
6.6%
3 10096
 
6.5%
8 9764
 
6.3%
4 9486
 
6.1%
9 4750
 
3.1%
7 2322
 
1.5%
6 2312
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 155166
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 59254
38.2%
1 23705
15.3%
- 21159
 
13.6%
2 10256
 
6.6%
3 10096
 
6.5%
8 9764
 
6.3%
4 9486
 
6.1%
9 4750
 
3.1%
7 2322
 
1.5%
6 2312
 
1.5%

인허가일자
Date

Distinct4504
Distinct (%)63.9%
Missing0
Missing (%)0.0%
Memory size55.2 KiB
Minimum1913-09-16 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T15:14:21.618912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:14:21.795423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7053
Missing (%)100.0%
Memory size62.1 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.2 KiB
3
4949 
1
2104 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 4949
70.2%
1 2104
29.8%

Length

2024-05-11T15:14:22.037579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:22.225149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 4949
70.2%
1 2104
29.8%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.2 KiB
폐업
4949 
영업/정상
2104 

Length

Max length5
Median length2
Mean length2.8949383
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업/정상
2nd row폐업
3rd row폐업
4th row폐업
5th row폐업

Common Values

ValueCountFrequency (%)
폐업 4949
70.2%
영업/정상 2104
29.8%

Length

2024-05-11T15:14:22.404369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:22.567412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 4949
70.2%
영업/정상 2104
29.8%

상세영업상태코드
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.2 KiB
2
4949 
1
2104 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 4949
70.2%
1 2104
29.8%

Length

2024-05-11T15:14:22.731595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:22.937682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 4949
70.2%
1 2104
29.8%

상세영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.2 KiB
폐업
4949 
영업
2104 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업
2nd row폐업
3rd row폐업
4th row폐업
5th row폐업

Common Values

ValueCountFrequency (%)
폐업 4949
70.2%
영업 2104
29.8%

Length

2024-05-11T15:14:23.100230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:23.289139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 4949
70.2%
영업 2104
29.8%

폐업일자
Date

MISSING 

Distinct3264
Distinct (%)66.0%
Missing2104
Missing (%)29.8%
Memory size55.2 KiB
Minimum1983-02-23 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T15:14:23.823771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:14:24.174526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7053
Missing (%)100.0%
Memory size62.1 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7053
Missing (%)100.0%
Memory size62.1 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7053
Missing (%)100.0%
Memory size62.1 KiB

전화번호
Text

MISSING 

Distinct2715
Distinct (%)84.1%
Missing3823
Missing (%)54.2%
Memory size55.2 KiB
2024-05-11T15:14:24.583411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.5931889
Min length2

Characters and Unicode

Total characters30986
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2587 ?
Unique (%)80.1%

Sample

1st row0207834877
2nd row0207802673
3rd row0206306000
4th row0226785003
5th row0226354329
ValueCountFrequency (%)
02 1330
28.7%
070 43
 
0.9%
0200000000 33
 
0.7%
031 21
 
0.5%
0206306000 17
 
0.4%
0206708000 16
 
0.3%
34681052 15
 
0.3%
780 14
 
0.3%
831 12
 
0.3%
053 11
 
0.2%
Other values (2816) 3116
67.3%
2024-05-11T15:14:25.418487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6385
20.6%
2 5313
17.1%
6 2863
9.2%
7 2694
8.7%
8 2632
8.5%
3 2606
8.4%
4 1885
 
6.1%
1841
 
5.9%
1 1810
 
5.8%
5 1731
 
5.6%
Other values (2) 1226
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 29142
94.0%
Space Separator 1841
 
5.9%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6385
21.9%
2 5313
18.2%
6 2863
9.8%
7 2694
9.2%
8 2632
9.0%
3 2606
8.9%
4 1885
 
6.5%
1 1810
 
6.2%
5 1731
 
5.9%
9 1223
 
4.2%
Space Separator
ValueCountFrequency (%)
1841
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 30986
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6385
20.6%
2 5313
17.1%
6 2863
9.2%
7 2694
8.7%
8 2632
8.5%
3 2606
8.4%
4 1885
 
6.1%
1841
 
5.9%
1 1810
 
5.8%
5 1731
 
5.6%
Other values (2) 1226
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30986
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6385
20.6%
2 5313
17.1%
6 2863
9.2%
7 2694
8.7%
8 2632
8.5%
3 2606
8.4%
4 1885
 
6.1%
1841
 
5.9%
1 1810
 
5.8%
5 1731
 
5.6%
Other values (2) 1226
 
4.0%

소재지면적
Real number (ℝ)

MISSING 

Distinct3044
Distinct (%)45.4%
Missing346
Missing (%)4.9%
Infinite0
Infinite (%)0.0%
Mean45.539764
Minimum0
Maximum810.95
Zeros30
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size62.1 KiB
2024-05-11T15:14:25.701887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.3
Q110
median28.08
Q359.9
95-th percentile140.061
Maximum810.95
Range810.95
Interquartile range (IQR)49.9

Descriptive statistics

Standard deviation56.911432
Coefficient of variation (CV)1.2497085
Kurtosis26.695536
Mean45.539764
Median Absolute Deviation (MAD)20.5
Skewness3.9049199
Sum305435.2
Variance3238.9111
MonotonicityNot monotonic
2024-05-11T15:14:26.047197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.6 346
 
4.9%
9.0 261
 
3.7%
3.3 258
 
3.7%
5.0 196
 
2.8%
9.9 85
 
1.2%
10.0 81
 
1.1%
33.0 70
 
1.0%
20.0 60
 
0.9%
16.5 57
 
0.8%
4.0 52
 
0.7%
Other values (3034) 5241
74.3%
(Missing) 346
 
4.9%
ValueCountFrequency (%)
0.0 30
0.4%
0.66 1
 
< 0.1%
1.0 3
 
< 0.1%
1.13 1
 
< 0.1%
1.19 1
 
< 0.1%
1.2 1
 
< 0.1%
1.4 1
 
< 0.1%
1.6 2
 
< 0.1%
1.61 1
 
< 0.1%
1.7 1
 
< 0.1%
ValueCountFrequency (%)
810.95 1
< 0.1%
770.0 2
< 0.1%
591.9 1
< 0.1%
580.0 1
< 0.1%
562.3 1
< 0.1%
552.15 1
< 0.1%
546.66 1
< 0.1%
546.45 1
< 0.1%
519.75 1
< 0.1%
495.94 1
< 0.1%

소재지우편번호
Text

Distinct336
Distinct (%)4.8%
Missing42
Missing (%)0.6%
Memory size55.2 KiB
2024-05-11T15:14:26.759055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1603195
Min length6

Characters and Unicode

Total characters43190
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

Unique59 ?
Unique (%)0.8%

Sample

1st row150877
2nd row150010
3rd row150034
4th row150034
5th row150036
ValueCountFrequency (%)
150034 309
 
4.4%
150899 297
 
4.2%
150010 268
 
3.8%
150033 233
 
3.3%
150985 205
 
2.9%
150835 143
 
2.0%
150875 138
 
2.0%
150841 136
 
1.9%
150-875 110
 
1.6%
150103 108
 
1.5%
Other values (326) 5064
72.2%
2024-05-11T15:14:27.564441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10905
25.2%
1 8580
19.9%
5 8553
19.8%
8 4875
11.3%
3 2360
 
5.5%
9 2350
 
5.4%
7 1387
 
3.2%
4 1326
 
3.1%
- 1124
 
2.6%
6 1017
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 42066
97.4%
Dash Punctuation 1124
 
2.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10905
25.9%
1 8580
20.4%
5 8553
20.3%
8 4875
11.6%
3 2360
 
5.6%
9 2350
 
5.6%
7 1387
 
3.3%
4 1326
 
3.2%
6 1017
 
2.4%
2 713
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 1124
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 43190
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10905
25.2%
1 8580
19.9%
5 8553
19.8%
8 4875
11.3%
3 2360
 
5.5%
9 2350
 
5.4%
7 1387
 
3.2%
4 1326
 
3.1%
- 1124
 
2.6%
6 1017
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 43190
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10905
25.2%
1 8580
19.9%
5 8553
19.8%
8 4875
11.3%
3 2360
 
5.5%
9 2350
 
5.4%
7 1387
 
3.2%
4 1326
 
3.1%
- 1124
 
2.6%
6 1017
 
2.4%

지번주소
Text

Distinct5293
Distinct (%)75.5%
Missing42
Missing (%)0.6%
Memory size55.2 KiB
2024-05-11T15:14:27.978130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length81
Median length58
Mean length29.614178
Min length18

Characters and Unicode

Total characters207625
Distinct characters512
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4698 ?
Unique (%)67.0%

Sample

1st row서울특별시 영등포구 여의도동 24-2번지 102호
2nd row서울특별시 영등포구 여의도동 1-140번지
3rd row서울특별시 영등포구 영등포동4가 441-21번지
4th row서울특별시 영등포구 영등포동4가 426-71번지 지하1층
5th row서울특별시 영등포구 영등포동6가 79-0번지 지하1층
ValueCountFrequency (%)
서울특별시 7010
19.1%
영등포구 7010
19.1%
여의도동 1795
 
4.9%
1층 907
 
2.5%
신길동 801
 
2.2%
영등포동4가 697
 
1.9%
대림동 515
 
1.4%
지하1층 508
 
1.4%
영등포동 398
 
1.1%
지상1층 295
 
0.8%
Other values (5084) 16733
45.6%
2024-05-11T15:14:28.776901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
35054
 
16.9%
영 9261
 
4.5%
포 9238
 
4.4%
등 9199
 
4.4%
1 8495
 
4.1%
동 7422
 
3.6%
시 7237
 
3.5%
서 7137
 
3.4%
울 7105
 
3.4%
구 7067
 
3.4%
Other values (502) 100410
48.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 130186
62.7%
Decimal Number 35384
 
17.0%
Space Separator 35054
 
16.9%
Dash Punctuation 5337
 
2.6%
Uppercase Letter 634
 
0.3%
Open Punctuation 334
 
0.2%
Close Punctuation 334
 
0.2%
Other Punctuation 217
 
0.1%
Lowercase Letter 94
 
< 0.1%
Math Symbol 50
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 9261
 
7.1%
포 9238
 
7.1%
등 9199
 
7.1%
동 7422
 
5.7%
시 7237
 
5.6%
서 7137
 
5.5%
울 7105
 
5.5%
구 7067
 
5.4%
별 7027
 
5.4%
특 7016
 
5.4%
Other values (437) 52477
40.3%
Uppercase Letter
ValueCountFrequency (%)
B 107
16.9%
S 84
13.2%
C 66
10.4%
K 64
10.1%
A 44
 
6.9%
I 38
 
6.0%
F 37
 
5.8%
E 34
 
5.4%
L 24
 
3.8%
G 21
 
3.3%
Other values (14) 115
18.1%
Lowercase Letter
ValueCountFrequency (%)
e 26
27.7%
n 12
12.8%
c 12
12.8%
r 11
11.7%
t 7
 
7.4%
s 4
 
4.3%
l 3
 
3.2%
o 3
 
3.2%
x 3
 
3.2%
a 2
 
2.1%
Other values (7) 11
11.7%
Decimal Number
ValueCountFrequency (%)
1 8495
24.0%
4 4897
13.8%
2 4534
12.8%
3 4208
11.9%
5 2755
 
7.8%
6 2577
 
7.3%
0 2476
 
7.0%
8 2046
 
5.8%
9 1717
 
4.9%
7 1679
 
4.7%
Other Punctuation
ValueCountFrequency (%)
, 189
87.1%
? 15
 
6.9%
. 8
 
3.7%
& 2
 
0.9%
/ 2
 
0.9%
@ 1
 
0.5%
Open Punctuation
ValueCountFrequency (%)
( 333
99.7%
[ 1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 333
99.7%
] 1
 
0.3%
Space Separator
ValueCountFrequency (%)
35054
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5337
100.0%
Math Symbol
ValueCountFrequency (%)
~ 50
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 130184
62.7%
Common 76711
36.9%
Latin 728
 
0.4%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 9261
 
7.1%
포 9238
 
7.1%
등 9199
 
7.1%
동 7422
 
5.7%
시 7237
 
5.6%
서 7137
 
5.5%
울 7105
 
5.5%
구 7067
 
5.4%
별 7027
 
5.4%
특 7016
 
5.4%
Other values (435) 52475
40.3%
Latin
ValueCountFrequency (%)
B 107
14.7%
S 84
11.5%
C 66
 
9.1%
K 64
 
8.8%
A 44
 
6.0%
I 38
 
5.2%
F 37
 
5.1%
E 34
 
4.7%
e 26
 
3.6%
L 24
 
3.3%
Other values (31) 204
28.0%
Common
ValueCountFrequency (%)
35054
45.7%
1 8495
 
11.1%
- 5337
 
7.0%
4 4897
 
6.4%
2 4534
 
5.9%
3 4208
 
5.5%
5 2755
 
3.6%
6 2577
 
3.4%
0 2476
 
3.2%
8 2046
 
2.7%
Other values (14) 4332
 
5.6%
Han
ValueCountFrequency (%)
貪 1
50.0%
箸 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 130181
62.7%
ASCII 77439
37.3%
Compat Jamo 3
 
< 0.1%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
35054
45.3%
1 8495
 
11.0%
- 5337
 
6.9%
4 4897
 
6.3%
2 4534
 
5.9%
3 4208
 
5.4%
5 2755
 
3.6%
6 2577
 
3.3%
0 2476
 
3.2%
8 2046
 
2.6%
Other values (55) 5060
 
6.5%
Hangul
ValueCountFrequency (%)
영 9261
 
7.1%
포 9238
 
7.1%
등 9199
 
7.1%
동 7422
 
5.7%
시 7237
 
5.6%
서 7137
 
5.5%
울 7105
 
5.5%
구 7067
 
5.4%
별 7027
 
5.4%
특 7016
 
5.4%
Other values (432) 52472
40.3%
Compat Jamo
ValueCountFrequency (%)
ㄱ 1
33.3%
ㅖ 1
33.3%
ㅣ 1
33.3%
CJK
ValueCountFrequency (%)
貪 1
50.0%
箸 1
50.0%

도로명주소
Text

MISSING 

Distinct3806
Distinct (%)81.4%
Missing2378
Missing (%)33.7%
Memory size55.2 KiB
2024-05-11T15:14:29.284278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length76
Median length62
Mean length38.525775
Min length22

Characters and Unicode

Total characters180108
Distinct characters503
Distinct categories11 ?
Distinct scripts5 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3564 ?
Unique (%)76.2%

Sample

1st row서울특별시 영등포구 여의나루로 77-1 (여의도동,102호)
2nd row서울특별시 영등포구 영등포로 253 (영등포동2가)
3rd row서울특별시 영등포구 영중로 65 (영등포동6가)
4th row서울특별시 영등포구 영등포로 255 (영등포동2가)
5th row서울특별시 영등포구 선유로 106 (양평동1가)
ValueCountFrequency (%)
영등포구 4675
 
14.3%
서울특별시 4674
 
14.3%
1층 1840
 
5.6%
여의도동 1191
 
3.6%
지하1층 879
 
2.7%
영중로 557
 
1.7%
신길동 438
 
1.3%
영등포동4가 408
 
1.2%
9 294
 
0.9%
여의동로 281
 
0.9%
Other values (3307) 17544
53.5%
2024-05-11T15:14:29.967096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
28138
 
15.6%
1 8434
 
4.7%
영 7142
 
4.0%
포 6416
 
3.6%
등 6381
 
3.5%
동 5447
 
3.0%
, 5251
 
2.9%
서 5033
 
2.8%
( 4986
 
2.8%
) 4986
 
2.8%
Other values (493) 97894
54.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 109422
60.8%
Space Separator 28138
 
15.6%
Decimal Number 25898
 
14.4%
Other Punctuation 5268
 
2.9%
Open Punctuation 4989
 
2.8%
Close Punctuation 4989
 
2.8%
Uppercase Letter 713
 
0.4%
Dash Punctuation 543
 
0.3%
Lowercase Letter 96
 
0.1%
Math Symbol 51
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 7142
 
6.5%
포 6416
 
5.9%
등 6381
 
5.8%
동 5447
 
5.0%
서 5033
 
4.6%
울 4948
 
4.5%
시 4926
 
4.5%
구 4716
 
4.3%
로 4715
 
4.3%
별 4684
 
4.3%
Other values (427) 55014
50.3%
Uppercase Letter
ValueCountFrequency (%)
B 161
22.6%
S 88
12.3%
C 67
9.4%
K 57
 
8.0%
A 52
 
7.3%
I 49
 
6.9%
F 40
 
5.6%
E 33
 
4.6%
L 23
 
3.2%
G 21
 
2.9%
Other values (14) 122
17.1%
Lowercase Letter
ValueCountFrequency (%)
e 28
29.2%
n 13
13.5%
r 12
12.5%
c 10
 
10.4%
t 8
 
8.3%
s 4
 
4.2%
l 3
 
3.1%
u 2
 
2.1%
i 2
 
2.1%
g 2
 
2.1%
Other values (9) 12
12.5%
Decimal Number
ValueCountFrequency (%)
1 8434
32.6%
2 2908
 
11.2%
3 2812
 
10.9%
0 2444
 
9.4%
4 2235
 
8.6%
5 1581
 
6.1%
8 1577
 
6.1%
6 1517
 
5.9%
7 1268
 
4.9%
9 1122
 
4.3%
Other Punctuation
ValueCountFrequency (%)
, 5251
99.7%
. 6
 
0.1%
? 6
 
0.1%
/ 3
 
0.1%
& 2
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 4986
99.9%
[ 3
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 4986
99.9%
] 3
 
0.1%
Space Separator
ValueCountFrequency (%)
28138
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 543
100.0%
Math Symbol
ValueCountFrequency (%)
~ 51
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 109419
60.8%
Common 69877
38.8%
Latin 809
 
0.4%
Han 2
 
< 0.1%
Hiragana 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 7142
 
6.5%
포 6416
 
5.9%
등 6381
 
5.8%
동 5447
 
5.0%
서 5033
 
4.6%
울 4948
 
4.5%
시 4926
 
4.5%
구 4716
 
4.3%
로 4715
 
4.3%
별 4684
 
4.3%
Other values (424) 55011
50.3%
Latin
ValueCountFrequency (%)
B 161
19.9%
S 88
10.9%
C 67
 
8.3%
K 57
 
7.0%
A 52
 
6.4%
I 49
 
6.1%
F 40
 
4.9%
E 33
 
4.1%
e 28
 
3.5%
L 23
 
2.8%
Other values (33) 211
26.1%
Common
ValueCountFrequency (%)
28138
40.3%
1 8434
 
12.1%
, 5251
 
7.5%
( 4986
 
7.1%
) 4986
 
7.1%
2 2908
 
4.2%
3 2812
 
4.0%
0 2444
 
3.5%
4 2235
 
3.2%
5 1581
 
2.3%
Other values (13) 6102
 
8.7%
Han
ValueCountFrequency (%)
殆 1
50.0%
箸 1
50.0%
Hiragana
ValueCountFrequency (%)
せ 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 109419
60.8%
ASCII 70686
39.2%
CJK 2
 
< 0.1%
Hiragana 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
28138
39.8%
1 8434
 
11.9%
, 5251
 
7.4%
( 4986
 
7.1%
) 4986
 
7.1%
2 2908
 
4.1%
3 2812
 
4.0%
0 2444
 
3.5%
4 2235
 
3.2%
5 1581
 
2.2%
Other values (56) 6911
 
9.8%
Hangul
ValueCountFrequency (%)
영 7142
 
6.5%
포 6416
 
5.9%
등 6381
 
5.8%
동 5447
 
5.0%
서 5033
 
4.6%
울 4948
 
4.5%
시 4926
 
4.5%
구 4716
 
4.3%
로 4715
 
4.3%
별 4684
 
4.3%
Other values (424) 55011
50.3%
Hiragana
ValueCountFrequency (%)
せ 1
100.0%
CJK
ValueCountFrequency (%)
殆 1
50.0%
箸 1
50.0%

도로명우편번호
Real number (ℝ)

MISSING  SKEWED 

Distinct239
Distinct (%)5.2%
Missing2472
Missing (%)35.0%
Infinite0
Infinite (%)0.0%
Mean7309.1074
Minimum7200
Maximum21349
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size62.1 KiB
2024-05-11T15:14:30.271329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7200
5-th percentile7213
Q17257
median7305
Q37337
95-th percentile7419
Maximum21349
Range14149
Interquartile range (IQR)80

Descriptive statistics

Standard deviation215.5339
Coefficient of variation (CV)0.029488402
Kurtosis3933.3855
Mean7309.1074
Median Absolute Deviation (MAD)35
Skewness60.378738
Sum33483021
Variance46454.861
MonotonicityNot monotonic
2024-05-11T15:14:30.530944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7305 465
 
6.6%
7337 228
 
3.2%
7306 209
 
3.0%
7335 206
 
2.9%
7333 108
 
1.5%
7238 71
 
1.0%
7255 64
 
0.9%
7236 61
 
0.9%
7297 55
 
0.8%
7326 53
 
0.8%
Other values (229) 3061
43.4%
(Missing) 2472
35.0%
ValueCountFrequency (%)
7200 9
 
0.1%
7201 7
 
0.1%
7202 5
 
0.1%
7203 3
 
< 0.1%
7204 14
 
0.2%
7205 31
0.4%
7206 36
0.5%
7207 22
0.3%
7208 34
0.5%
7209 15
0.2%
ValueCountFrequency (%)
21349 1
 
< 0.1%
7448 3
 
< 0.1%
7447 3
 
< 0.1%
7446 6
 
0.1%
7445 13
0.2%
7444 11
0.2%
7443 3
 
< 0.1%
7442 27
0.4%
7441 4
 
0.1%
7440 13
0.2%

사업장명
Text

Distinct6192
Distinct (%)87.8%
Missing0
Missing (%)0.0%
Memory size55.2 KiB
2024-05-11T15:14:30.931120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length35
Mean length7.661846
Min length1

Characters and Unicode

Total characters54039
Distinct characters987
Distinct categories12 ?
Distinct scripts5 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5674 ?
Unique (%)80.4%

Sample

1st row린네스가든
2nd row뉴욕제과
3rd row휠라휘프
4th row희
5th row궁전
ValueCountFrequency (%)
coffee 74
 
0.8%
영등포점 54
 
0.6%
세븐일레븐 45
 
0.5%
씨유 40
 
0.5%
여의도점 32
 
0.4%
카페 29
 
0.3%
주식회사 29
 
0.3%
메가엠지씨커피 29
 
0.3%
gs25 29
 
0.3%
cafe 27
 
0.3%
Other values (6655) 8326
95.5%
2024-05-11T15:14:31.532422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 2016
 
3.7%
1664
 
3.1%
스 1596
 
3.0%
) 1243
 
2.3%
( 1239
 
2.3%
이 1057
 
2.0%
피 926
 
1.7%
리 902
 
1.7%
커 798
 
1.5%
도 635
 
1.2%
Other values (977) 41963
77.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 42152
78.0%
Uppercase Letter 4183
 
7.7%
Lowercase Letter 2202
 
4.1%
Space Separator 1664
 
3.1%
Close Punctuation 1244
 
2.3%
Open Punctuation 1240
 
2.3%
Decimal Number 1175
 
2.2%
Other Punctuation 158
 
0.3%
Dash Punctuation 13
 
< 0.1%
Math Symbol 3
 
< 0.1%
Other values (2) 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 2016
 
4.8%
스 1596
 
3.8%
이 1057
 
2.5%
피 926
 
2.2%
리 902
 
2.1%
커 798
 
1.9%
도 635
 
1.5%
영 627
 
1.5%
포 582
 
1.4%
의 537
 
1.3%
Other values (895) 32476
77.0%
Uppercase Letter
ValueCountFrequency (%)
S 459
 
11.0%
E 451
 
10.8%
C 379
 
9.1%
G 307
 
7.3%
F 297
 
7.1%
O 289
 
6.9%
A 261
 
6.2%
I 176
 
4.2%
B 172
 
4.1%
L 156
 
3.7%
Other values (16) 1236
29.5%
Lowercase Letter
ValueCountFrequency (%)
e 388
17.6%
a 218
 
9.9%
o 182
 
8.3%
f 174
 
7.9%
n 136
 
6.2%
i 130
 
5.9%
c 124
 
5.6%
s 121
 
5.5%
t 100
 
4.5%
r 81
 
3.7%
Other values (16) 548
24.9%
Other Punctuation
ValueCountFrequency (%)
& 47
29.7%
' 33
20.9%
. 24
15.2%
, 16
 
10.1%
/ 9
 
5.7%
? 8
 
5.1%
# 7
 
4.4%
! 6
 
3.8%
？ 4
 
2.5%
: 3
 
1.9%
Decimal Number
ValueCountFrequency (%)
2 429
36.5%
5 318
27.1%
1 109
 
9.3%
3 79
 
6.7%
4 73
 
6.2%
9 39
 
3.3%
0 39
 
3.3%
6 35
 
3.0%
8 31
 
2.6%
7 23
 
2.0%
Close Punctuation
ValueCountFrequency (%)
) 1243
99.9%
] 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 1239
99.9%
[ 1
 
0.1%
Space Separator
ValueCountFrequency (%)
1664
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Math Symbol
ValueCountFrequency (%)
+ 3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 42132
78.0%
Latin 6385
 
11.8%
Common 5502
 
10.2%
Han 17
 
< 0.1%
Hiragana 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 2016
 
4.8%
스 1596
 
3.8%
이 1057
 
2.5%
피 926
 
2.2%
리 902
 
2.1%
커 798
 
1.9%
도 635
 
1.5%
영 627
 
1.5%
포 582
 
1.4%
의 537
 
1.3%
Other values (875) 32456
77.0%
Latin
ValueCountFrequency (%)
S 459
 
7.2%
E 451
 
7.1%
e 388
 
6.1%
C 379
 
5.9%
G 307
 
4.8%
F 297
 
4.7%
O 289
 
4.5%
A 261
 
4.1%
a 218
 
3.4%
o 182
 
2.9%
Other values (42) 3154
49.4%
Common
ValueCountFrequency (%)
1664
30.2%
) 1243
22.6%
( 1239
22.5%
2 429
 
7.8%
5 318
 
5.8%
1 109
 
2.0%
3 79
 
1.4%
4 73
 
1.3%
& 47
 
0.9%
9 39
 
0.7%
Other values (20) 262
 
4.8%
Han
ValueCountFrequency (%)
情 1
 
5.9%
安 1
 
5.9%
母 1
 
5.9%
夢 1
 
5.9%
喫 1
 
5.9%
茶 1
 
5.9%
秀 1
 
5.9%
過 1
 
5.9%
橋 1
 
5.9%
米 1
 
5.9%
Other values (7) 7
41.2%
Hiragana
ValueCountFrequency (%)
こ 1
33.3%
ぐ 1
33.3%
ま 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 42129
78.0%
ASCII 11883
 
22.0%
CJK 16
 
< 0.1%
None 4
 
< 0.1%
Compat Jamo 3
 
< 0.1%
Hiragana 3
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 2016
 
4.8%
스 1596
 
3.8%
이 1057
 
2.5%
피 926
 
2.2%
리 902
 
2.1%
커 798
 
1.9%
도 635
 
1.5%
영 627
 
1.5%
포 582
 
1.4%
의 537
 
1.3%
Other values (873) 32453
77.0%
ASCII
ValueCountFrequency (%)
1664
 
14.0%
) 1243
 
10.5%
( 1239
 
10.4%
S 459
 
3.9%
E 451
 
3.8%
2 429
 
3.6%
e 388
 
3.3%
C 379
 
3.2%
5 318
 
2.7%
G 307
 
2.6%
Other values (71) 5006
42.1%
None
ValueCountFrequency (%)
？ 4
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅋ 2
66.7%
ㅌ 1
33.3%
CJK
ValueCountFrequency (%)
情 1
 
6.2%
安 1
 
6.2%
母 1
 
6.2%
夢 1
 
6.2%
喫 1
 
6.2%
茶 1
 
6.2%
秀 1
 
6.2%
過 1
 
6.2%
橋 1
 
6.2%
米 1
 
6.2%
Other values (6) 6
37.5%
Hiragana
ValueCountFrequency (%)
こ 1
33.3%
ぐ 1
33.3%
ま 1
33.3%
CJK Compat Ideographs
ValueCountFrequency (%)
良 1
100.0%

최종수정일자
Date

Distinct5724
Distinct (%)81.2%
Missing0
Missing (%)0.0%
Memory size55.2 KiB
Minimum1999-02-10 00:00:00
Maximum2024-05-09 16:31:55
2024-05-11T15:14:31.733252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:14:31.982027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.2 KiB
I
4685 
U
2367 
D
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowU
2nd rowI
3rd rowI
4th rowI
5th rowI

Common Values

ValueCountFrequency (%)
I 4685
66.4%
U 2367
33.6%
D 1
 
< 0.1%

Length

2024-05-11T15:14:32.291018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:32.492934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 4685
66.4%
u 2367
33.6%
d 1
 
< 0.1%

데이터갱신일자
Date

Distinct1339
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Memory size55.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T15:14:32.716931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:14:32.960062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size55.2 KiB
커피숍
1751 
다방
1226 
일반조리판매
961 
기타 휴게음식점
741 
편의점
663 
Other values (12)
1711 

Length

Max length8
Median length6
Mean length3.9258472
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row다방
2nd row과자점
3rd row백화점
4th row다방
5th row다방

Common Values

ValueCountFrequency (%)
커피숍 1751
24.8%
다방 1226
17.4%
일반조리판매 961
13.6%
기타 휴게음식점 741
10.5%
편의점 663
 
9.4%
과자점 497
 
7.0%
백화점 443
 
6.3%
패스트푸드 351
 
5.0%
푸드트럭 285
 
4.0%
철도역구내 48
 
0.7%
Other values (7) 87
 
1.2%

Length

2024-05-11T15:14:33.208967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
커피숍 1751
22.5%
다방 1226
15.7%
일반조리판매 961
12.3%
기타 741
9.5%
휴게음식점 741
9.5%
편의점 663
 
8.5%
과자점 497
 
6.4%
백화점 443
 
5.7%
패스트푸드 351
 
4.5%
푸드트럭 285
 
3.7%
Other values (8) 135
 
1.7%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct2476
Distinct (%)36.5%
Missing273
Missing (%)3.9%
Infinite0
Infinite (%)0.0%
Mean191890.62
Minimum176792.47
Maximum194794.06
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size62.1 KiB
2024-05-11T15:14:33.487684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum176792.47
5-th percentile190258.46
Q1190996.36
median191661.12
Q3192875.23
95-th percentile193839.05
Maximum194794.06
Range18001.589
Interquartile range (IQR)1878.872

Descriptive statistics

Standard deviation1159.5149
Coefficient of variation (CV)0.0060425826
Kurtosis3.4415291
Mean191890.62
Median Absolute Deviation (MAD)867.75552
Skewness0.032707881
Sum1.3010184 × 109
Variance1344474.8
MonotonicityNot monotonic
2024-05-11T15:14:33.783406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
191741.345847708 284
 
4.0%
191581.500265536 272
 
3.9%
192875.229282664 242
 
3.4%
193592.000380036 206
 
2.9%
191385.057392247 172
 
2.4%
190729.506453391 79
 
1.1%
193209.283508484 53
 
0.8%
193326.931018911 50
 
0.7%
190352.321686588 49
 
0.7%
191527.685753464 46
 
0.7%
Other values (2466) 5327
75.5%
(Missing) 273
 
3.9%
ValueCountFrequency (%)
176792.467792121 1
 
< 0.1%
189455.788632983 3
< 0.1%
189570.401236233 2
< 0.1%
189574.962072527 4
0.1%
189602.767582543 1
 
< 0.1%
189607.598899153 3
< 0.1%
189614.372793612 1
 
< 0.1%
189641.475801911 3
< 0.1%
189651.877011522 1
 
< 0.1%
189653.829218246 2
< 0.1%
ValueCountFrequency (%)
194794.056976261 21
0.3%
194632.526367463 33
0.5%
194599.854707059 3
 
< 0.1%
194592.276750438 5
 
0.1%
194561.746032498 20
0.3%
194530.535390096 10
 
0.1%
194504.656267957 12
 
0.2%
194475.664839714 1
 
< 0.1%
194422.414881513 3
 
< 0.1%
194385.660555095 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct2476
Distinct (%)36.5%
Missing273
Missing (%)3.9%
Infinite0
Infinite (%)0.0%
Mean446306.52
Minimum442605.7
Maximum449612.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size62.1 KiB
2024-05-11T15:14:33.998816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum442605.7
5-th percentile443755.66
Q1445970.31
median446401.93
Q3447092.63
95-th percentile448022.07
Maximum449612.2
Range7006.4918
Interquartile range (IQR)1122.3218

Descriptive statistics

Standard deviation1180.9018
Coefficient of variation (CV)0.0026459434
Kurtosis0.62187066
Mean446306.52
Median Absolute Deviation (MAD)631.94695
Skewness-0.76827778
Sum3.0259582 × 109
Variance1394529
MonotonicityNot monotonic
2024-05-11T15:14:34.192775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
445970.307641467 284
 
4.0%
446108.807192753 272
 
3.9%
447481.699112003 242
 
3.4%
447092.629432527 206
 
2.9%
446098.555926507 172
 
2.4%
446227.07504062 79
 
1.1%
446474.956573488 53
 
0.8%
446973.914570276 50
 
0.7%
447095.641206789 49
 
0.7%
446151.006265911 46
 
0.7%
Other values (2466) 5327
75.5%
(Missing) 273
 
3.9%
ValueCountFrequency (%)
442605.70463744 1
 
< 0.1%
442621.787911877 2
 
< 0.1%
442663.748373343 2
 
< 0.1%
442710.662421803 3
< 0.1%
442715.677609564 1
 
< 0.1%
442717.639571997 2
 
< 0.1%
442756.531513655 5
0.1%
442809.244656606 1
 
< 0.1%
442829.231926853 1
 
< 0.1%
442829.909245325 1
 
< 0.1%
ValueCountFrequency (%)
449612.196451455 3
< 0.1%
449199.038668984 1
 
< 0.1%
449105.000294519 6
0.1%
449045.705457074 4
0.1%
449039.941340036 1
 
< 0.1%
449033.097215692 2
 
< 0.1%
449021.440559054 1
 
< 0.1%
448990.816559516 1
 
< 0.1%
448936.418388404 1
 
< 0.1%
448924.017990949 1
 
< 0.1%

위생업태명
Categorical

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size55.2 KiB
<NA>
1553 
다방
1205 
커피숍
1178 
일반조리판매
836 
과자점
490 
Other values (12)
1791 

Length

Max length8
Median length6
Mean length3.830285
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row다방
2nd row과자점
3rd row백화점
4th row다방
5th row다방

Common Values

ValueCountFrequency (%)
<NA> 1553
22.0%
다방 1205
17.1%
커피숍 1178
16.7%
일반조리판매 836
11.9%
과자점 490
 
6.9%
편의점 459
 
6.5%
기타 휴게음식점 401
 
5.7%
패스트푸드 308
 
4.4%
백화점 284
 
4.0%
푸드트럭 255
 
3.6%
Other values (7) 84
 
1.2%

Length

2024-05-11T15:14:34.466504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1553
20.8%
다방 1205
16.2%
커피숍 1178
15.8%
일반조리판매 836
11.2%
과자점 490
 
6.6%
편의점 459
 
6.2%
기타 401
 
5.4%
휴게음식점 401
 
5.4%
패스트푸드 308
 
4.1%
백화점 284
 
3.8%
Other values (8) 339
 
4.5%

남성종사자수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct10
Distinct (%)0.5%
Missing4964
Missing (%)70.4%
Infinite0
Infinite (%)0.0%
Mean0.42077549
Minimum0
Maximum93
Zeros1766
Zeros (%)25.0%
Negative0
Negative (%)0.0%
Memory size62.1 KiB
2024-05-11T15:14:34.674649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum93
Range93
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.7124324
Coefficient of variation (CV)8.8228342
Kurtosis558.44797
Mean0.42077549
Median Absolute Deviation (MAD)0
Skewness22.857834
Sum879
Variance13.782154
MonotonicityNot monotonic
2024-05-11T15:14:35.239848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 1766
 
25.0%
1 157
 
2.2%
2 127
 
1.8%
3 25
 
0.4%
4 7
 
0.1%
93 3
 
< 0.1%
24 1
 
< 0.1%
7 1
 
< 0.1%
22 1
 
< 0.1%
33 1
 
< 0.1%
(Missing) 4964
70.4%
ValueCountFrequency (%)
0 1766
25.0%
1 157
 
2.2%
2 127
 
1.8%
3 25
 
0.4%
4 7
 
0.1%
7 1
 
< 0.1%
22 1
 
< 0.1%
24 1
 
< 0.1%
33 1
 
< 0.1%
93 3
 
< 0.1%
ValueCountFrequency (%)
93 3
 
< 0.1%
33 1
 
< 0.1%
24 1
 
< 0.1%
22 1
 
< 0.1%
7 1
 
< 0.1%
4 7
 
0.1%
3 25
 
0.4%
2 127
 
1.8%
1 157
 
2.2%
0 1766
25.0%

여성종사자수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct8
Distinct (%)0.4%
Missing4946
Missing (%)70.1%
Infinite0
Infinite (%)0.0%
Mean1.0294257
Minimum0
Maximum95
Zeros1180
Zeros (%)16.7%
Negative0
Negative (%)0.0%
Memory size62.1 KiB
2024-05-11T15:14:35.413188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile3
Maximum95
Range95
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.4141652
Coefficient of variation (CV)2.3451572
Kurtosis1090.843
Mean1.0294257
Median Absolute Deviation (MAD)0
Skewness28.222915
Sum2169
Variance5.8281935
MonotonicityNot monotonic
2024-05-11T15:14:35.584184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 1180
 
16.7%
2 410
 
5.8%
3 285
 
4.0%
1 183
 
2.6%
4 34
 
0.5%
5 13
 
0.2%
95 1
 
< 0.1%
15 1
 
< 0.1%
(Missing) 4946
70.1%
ValueCountFrequency (%)
0 1180
16.7%
1 183
 
2.6%
2 410
 
5.8%
3 285
 
4.0%
4 34
 
0.5%
5 13
 
0.2%
15 1
 
< 0.1%
95 1
 
< 0.1%
ValueCountFrequency (%)
95 1
 
< 0.1%
15 1
 
< 0.1%
5 13
 
0.2%
4 34
 
0.5%
3 285
 
4.0%
2 410
 
5.8%
1 183
 
2.6%
0 1180
16.7%

영업장주변구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.2 KiB
<NA>
5287 
기타
1129 
주택가주변
 
328
유흥업소밀집지역
 
170
아파트지역
 
100
Other values (3)
 
39

Length

Max length8
Median length4
Mean length3.8552389
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기타
2nd row아파트지역
3rd row기타
4th row유흥업소밀집지역
5th row기타

Common Values

ValueCountFrequency (%)
<NA> 5287
75.0%
기타 1129
 
16.0%
주택가주변 328
 
4.7%
유흥업소밀집지역 170
 
2.4%
아파트지역 100
 
1.4%
결혼예식장주변 27
 
0.4%
학교정화(상대) 7
 
0.1%
학교정화(절대) 5
 
0.1%

Length

2024-05-11T15:14:35.806377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:36.052197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5287
75.0%
기타 1129
 
16.0%
주택가주변 328
 
4.7%
유흥업소밀집지역 170
 
2.4%
아파트지역 100
 
1.4%
결혼예식장주변 27
 
0.4%
학교정화(상대 7
 
0.1%
학교정화(절대 5
 
0.1%

등급구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.2 KiB
<NA>
5309 
지도
747 
기타
 
438
자율
 
339
을
 
178
Other values (3)
 
42

Length

Max length4
Median length4
Mean length3.4756841
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row지도
2nd row지도
3rd row기타
4th row지도
5th row지도

Common Values

ValueCountFrequency (%)
<NA> 5309
75.3%
지도 747
 
10.6%
기타 438
 
6.2%
자율 339
 
4.8%
을 178
 
2.5%
갑 32
 
0.5%
우수 8
 
0.1%
관리 2
 
< 0.1%

Length

2024-05-11T15:14:36.363548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:36.626689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5309
75.3%
지도 747
 
10.6%
기타 438
 
6.2%
자율 339
 
4.8%
을 178
 
2.5%
갑 32
 
0.5%
우수 8
 
0.1%
관리 2
 
< 0.1%

급수시설구분명
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.2 KiB
<NA>
5018 
상수도전용
2011 
상수도(음용)지하수(주방용)겸용
 
24

Length

Max length17
Median length4
Mean length4.3293634
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5018
71.1%
상수도전용 2011
28.5%
상수도(음용)지하수(주방용)겸용 24
 
0.3%

Length

2024-05-11T15:14:36.881007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:37.107164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5018
71.1%
상수도전용 2011
28.5%
상수도(음용)지하수(주방용)겸용 24
 
0.3%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.2 KiB
<NA>
6792 
0
 
261

Length

Max length4
Median length4
Mean length3.8889834
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 6792
96.3%
0 261
 
3.7%

Length

2024-05-11T15:14:37.328876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:37.517521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6792
96.3%
0 261
 
3.7%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.2 KiB
<NA>
6790 
0
 
263

Length

Max length4
Median length4
Mean length3.8881327
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 6790
96.3%
0 263
 
3.7%

Length

2024-05-11T15:14:37.695645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:37.883712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6790
96.3%
0 263
 
3.7%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.2 KiB
<NA>
6790 
0
 
263

Length

Max length4
Median length4
Mean length3.8881327
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 6790
96.3%
0 263
 
3.7%

Length

2024-05-11T15:14:38.087076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:38.312798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6790
96.3%
0 263
 
3.7%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.2 KiB
<NA>
6790 
0
 
263

Length

Max length4
Median length4
Mean length3.8881327
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 6790
96.3%
0 263
 
3.7%

Length

2024-05-11T15:14:38.527759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:38.715397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6790
96.3%
0 263
 
3.7%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.2 KiB
<NA>
6790 
0
 
263

Length

Max length4
Median length4
Mean length3.8881327
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 6790
96.3%
0 263
 
3.7%

Length

2024-05-11T15:14:38.911808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:39.142422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6790
96.3%
0 263
 
3.7%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7053
Missing (%)100.0%
Memory size62.1 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.2 KiB
<NA>
6790 
0
 
263

Length

Max length4
Median length4
Mean length3.8881327
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 6790
96.3%
0 263
 
3.7%

Length

2024-05-11T15:14:39.386798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:39.559169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6790
96.3%
0 263
 
3.7%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.2 KiB
<NA>
6790 
0
 
263

Length

Max length4
Median length4
Mean length3.8881327
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 6790
96.3%
0 263
 
3.7%

Length

2024-05-11T15:14:39.730613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:39.919115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6790
96.3%
0 263
 
3.7%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1553
Missing (%)22.0%
Memory size13.9 KiB
False
5422 
True
 
78
(Missing)
1553 
ValueCountFrequency (%)
False 5422
76.9%
True 78
 
1.1%
(Missing) 1553
 
22.0%
2024-05-11T15:14:40.063852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct2629
Distinct (%)47.8%
Missing1553
Missing (%)22.0%
Infinite0
Infinite (%)0.0%
Mean43.672409
Minimum0
Maximum770
Zeros338
Zeros (%)4.8%
Negative0
Negative (%)0.0%
Memory size62.1 KiB
2024-05-11T15:14:40.295324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q19
median27.2
Q360.49
95-th percentile132.2485
Maximum770
Range770
Interquartile range (IQR)51.49

Descriptive statistics

Standard deviation53.251779
Coefficient of variation (CV)1.219346
Kurtosis27.026436
Mean43.672409
Median Absolute Deviation (MAD)20.6
Skewness3.7520571
Sum240198.25
Variance2835.7519
MonotonicityNot monotonic
2024-05-11T15:14:40.598685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 338
 
4.8%
9.0 235
 
3.3%
3.3 153
 
2.2%
6.6 134
 
1.9%
5.0 134
 
1.9%
9.9 70
 
1.0%
33.0 54
 
0.8%
4.0 49
 
0.7%
20.0 48
 
0.7%
10.0 48
 
0.7%
Other values (2619) 4237
60.1%
(Missing) 1553
 
22.0%
ValueCountFrequency (%)
0.0 338
4.8%
1.0 3
 
< 0.1%
1.13 1
 
< 0.1%
1.19 1
 
< 0.1%
1.2 1
 
< 0.1%
1.4 1
 
< 0.1%
1.6 2
 
< 0.1%
1.61 1
 
< 0.1%
1.7 1
 
< 0.1%
1.71 15
 
0.2%
ValueCountFrequency (%)
770.0 2
< 0.1%
591.9 1
< 0.1%
580.0 1
< 0.1%
562.3 1
< 0.1%
552.15 1
< 0.1%
495.94 1
< 0.1%
441.95 1
< 0.1%
431.98 1
< 0.1%
406.34 1
< 0.1%
403.3 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7053
Missing (%)100.0%
Memory size62.1 KiB

전통업소주된음식
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.2 KiB
<NA>
7052 
0
 
1

Length

Max length4
Median length4
Mean length3.9995746
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 7052
> 99.9%
0 1
 
< 0.1%

Length

2024-05-11T15:14:40.898425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:41.094363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7052
> 99.9%
0 1
 
< 0.1%

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7053
Missing (%)100.0%
Memory size62.1 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031800003180000-104-1913-0127519130916<NA>1영업/정상1영업<NA><NA><NA><NA>0207834877114.03150877서울특별시 영등포구 여의도동 24-2번지 102호서울특별시 영등포구 여의나루로 77-1 (여의도동,102호)7327린네스가든2019-06-14 14:22:12U2019-06-16 02:40:00.0다방193488.889001446902.521593다방05기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N114.03<NA><NA><NA>
131800003180000-104-1933-0195819330413<NA>3폐업2폐업19990825<NA><NA><NA>020780267332.37150010서울특별시 영등포구 여의도동 1-140번지<NA><NA>뉴욕제과2001-08-02 00:00:00I2018-08-31 23:59:59.0과자점<NA><NA>과자점34아파트지역지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N32.37<NA><NA><NA>
231800003180000-104-1934-0038619340826<NA>3폐업2폐업20091216<NA><NA><NA>020630600017.92150034서울특별시 영등포구 영등포동4가 441-21번지<NA><NA>휠라휘프2009-12-16 20:41:21I2018-08-31 23:59:59.0백화점<NA><NA>백화점00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N17.92<NA><NA><NA>
331800003180000-104-1966-0095719661227<NA>3폐업2폐업20160121<NA><NA><NA>0226785003116.55150034서울특별시 영등포구 영등포동4가 426-71번지 지하1층<NA><NA>희2009-08-26 14:31:05I2018-08-31 23:59:59.0다방191517.978667445999.559667다방22유흥업소밀집지역지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N116.55<NA><NA><NA>
431800003180000-104-1967-0091219670330<NA>3폐업2폐업20101227<NA><NA><NA>022635432943.38150036서울특별시 영등포구 영등포동6가 79-0번지 지하1층<NA><NA>궁전2009-08-17 14:56:19I2018-08-31 23:59:59.0다방191408.295152446472.146787다방02기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N43.38<NA><NA><NA>
531800003180000-104-1967-0134519670915<NA>3폐업2폐업19971126<NA><NA><NA>020678201868.26150033서울특별시 영등포구 영등포동3가 3-2번지<NA><NA>한성2001-08-02 00:00:00I2018-08-31 23:59:59.0다방191827.66199446313.399531다방03유흥업소밀집지역지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N68.26<NA><NA><NA>
631800003180000-104-1967-0162619671115<NA>3폐업2폐업19950208<NA><NA><NA>020677604640.16150035서울특별시 영등포구 영등포동5가 6-0번지<NA><NA>영2001-08-02 00:00:00I2018-08-31 23:59:59.0다방191747.252214446393.375935다방03기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N40.16<NA><NA><NA>
731800003180000-104-1968-0084619680430<NA>3폐업2폐업19960719<NA><NA><NA>020634532775.73150036서울특별시 영등포구 영등포동6가 79-6번지<NA><NA>뉴욕2001-08-02 00:00:00I2018-08-31 23:59:59.0다방<NA><NA>다방02기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N75.73<NA><NA><NA>
831800003180000-104-1968-0097819681004<NA>3폐업2폐업20170220<NA><NA><NA>0206764825110.43150903서울특별시 영등포구 영등포동2가 175-0번지서울특별시 영등포구 영등포로 253 (영등포동2가)7252경원블루2017-02-21 10:10:57I2018-08-31 23:59:59.0다방191952.897387446340.637133다방22기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N110.43<NA><NA><NA>
931800003180000-104-1968-0167119680513<NA>3폐업2폐업19950208<NA><NA><NA>0206338477126.17150903서울특별시 영등포구 영등포동2가 143-0번지<NA><NA>로타리다방2001-08-02 00:00:00I2018-08-31 23:59:59.0다방192152.344661446311.597773다방03기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N126.17<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
704331800003180000-104-2024-001322024-05-01<NA>3폐업2폐업2024-05-08<NA><NA><NA><NA>15.0150-875서울특별시 영등포구 여의도동 22 파크원서울특별시 영등포구 여의대로 108, 더현대서울 지하2층 (여의도동)7335톤즈(TONES)2024-05-09 04:15:09U2023-12-04 23:01:00.0기타 휴게음식점193592.00038447092.629433<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
704431800003180000-104-2024-001332024-05-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>6.6150-875서울특별시 영등포구 여의도동 22 파크원서울특별시 영등포구 여의대로 108, 더현대서울 지하1층 (여의도동)7335더블스윗2024-05-03 11:25:45I2023-12-05 00:05:00.0기타 휴게음식점193592.00038447092.629433<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
704531800003180000-104-2024-001342024-05-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.0150-875서울특별시 영등포구 여의도동 22 파크원서울특별시 영등포구 여의대로 108, 더현대서울 지하1층 (여의도동)7335드링크스토어 더현대여의도점2024-05-03 15:50:54I2023-12-05 00:05:00.0기타 휴게음식점193592.00038447092.629433<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
704631800003180000-104-2024-001352024-05-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.09150-985서울특별시 영등포구 영등포동4가 434-5 신세계백화점서울특별시 영등포구 영중로 9, 신세계백화점 타임스퀘어점 지하1층 (영등포동4가)7305모구야미2024-05-03 17:13:47I2023-12-05 00:05:00.0기타 휴게음식점191581.500266446108.807193<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
704731800003180000-104-2024-001362024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>29.38150-874서울특별시 영등포구 여의도동 17-16서울특별시 영등포구 국회대로62길 11, 1층 101호 (여의도동)7236커피나인KBS(coffeenine KBS)2024-05-07 11:08:46I2023-12-05 00:09:00.0기타 휴게음식점192562.603704447240.55433<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
704831800003180000-104-2024-001372024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>6.6150-798서울특별시 영등포구 영등포동4가 442 타임스퀘어서울특별시 영등포구 영중로 15, 타임스퀘어 지하1층 (영등포동4가)7305감동푸드2024-05-07 16:25:09I2023-12-05 00:09:00.0기타 휴게음식점191385.057392446098.555927<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
704931800003180000-104-2024-001382024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>47.55150-050서울특별시 영등포구 신길동 4969 힐스테이트 클래시안서울특별시 영등포구 신길로28길 9, 지하2층 134호 (신길동, 힐스테이트 클래시안)7388카페 요아정 신길점2024-05-07 17:26:20I2023-12-05 00:09:00.0커피숍192143.319862444660.996604<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
705031800003180000-104-2024-001392024-05-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA>6.6150-985서울특별시 영등포구 영등포동4가 434-5 신세계백화점서울특별시 영등포구 영중로 9, 신세계백화점 타임스퀘어점 지하1층 (영등포동4가)7305글라스 빈2024-05-09 09:12:25I2023-12-04 23:01:00.0기타 휴게음식점191581.500266446108.807193<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
705131800003180000-104-2024-001402024-05-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA>6.6150-985서울특별시 영등포구 영등포동4가 434-5 신세계백화점서울특별시 영등포구 영중로 9, 신세계백화점 타임스퀘어점 지하1층 (영등포동4가)7305팥붕슈붕2024-05-09 13:11:03I2023-12-04 23:01:00.0기타 휴게음식점191581.500266446108.807193<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
705231800003180000-104-2024-001412024-05-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA>9.0150-899서울특별시 영등포구 영등포동 618-496 영등포 민자역사서울특별시 영등포구 경인로 846, 영등포 민자역사 지하1층 (영등포동)7306영준목장2024-05-09 16:31:55I2023-12-04 23:01:00.0기타 휴게음식점191741.345848445970.307641<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>