Overview

Dataset statistics

Number of variables44
Number of observations10000
Missing cells108204
Missing cells (%)24.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 MiB
Average record size in memory383.0 B

Variable types

Categorical18
Text8
DateTime4
Unsupported7
Numeric6
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
Author송파구
URLhttps://data.seoul.go.kr/dataList/OA-18675/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
급수시설구분명 is highly imbalanced (50.3%)Imbalance
총인원 is highly imbalanced (87.1%)Imbalance
본사종업원수 is highly imbalanced (86.9%)Imbalance
공장사무직종업원수 is highly imbalanced (86.9%)Imbalance
공장판매직종업원수 is highly imbalanced (86.9%)Imbalance
공장생산직종업원수 is highly imbalanced (86.9%)Imbalance
보증액 is highly imbalanced (86.9%)Imbalance
월세액 is highly imbalanced (86.9%)Imbalance
다중이용업소여부 is highly imbalanced (92.2%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 1890 (18.9%) missing valuesMissing
휴업시작일자 has 10000 (100.0%) missing valuesMissing
휴업종료일자 has 10000 (100.0%) missing valuesMissing
재개업일자 has 10000 (100.0%) missing valuesMissing
전화번호 has 3250 (32.5%) missing valuesMissing
도로명주소 has 5332 (53.3%) missing valuesMissing
도로명우편번호 has 5407 (54.1%) missing valuesMissing
좌표정보(X) has 468 (4.7%) missing valuesMissing
좌표정보(Y) has 468 (4.7%) missing valuesMissing
남성종사자수 has 4686 (46.9%) missing valuesMissing
여성종사자수 has 4650 (46.5%) missing valuesMissing
건물소유구분명 has 10000 (100.0%) missing valuesMissing
다중이용업소여부 has 994 (9.9%) missing valuesMissing
시설총규모 has 994 (9.9%) missing valuesMissing
전통업소지정번호 has 9998 (> 99.9%) missing valuesMissing
전통업소주된음식 has 10000 (100.0%) missing valuesMissing
홈페이지 has 10000 (100.0%) missing valuesMissing
도로명우편번호 is highly skewed (γ1 = 25.12713654)Skewed
남성종사자수 is highly skewed (γ1 = 37.70500958)Skewed
여성종사자수 is highly skewed (γ1 = 38.09785622)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
전통업소주된음식 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 4019 (40.2%) zerosZeros
여성종사자수 has 3495 (34.9%) zerosZeros

Reproduction

Analysis started2024-05-11 03:24:26.317813
Analysis finished2024-05-11 03:24:33.538565
Duration7.22 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3230000
10000 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3230000
2nd row3230000
3rd row3230000
4th row3230000
5th row3230000

Common Values

ValueCountFrequency (%)
3230000 10000
100.0%

Length

2024-05-11T03:24:33.692228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:24:34.032342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3230000 10000
100.0%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T03:24:34.537516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters220000
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

Unique10000 ?
Unique (%)100.0%

Sample

1st row3230000-101-2002-17702
2nd row3230000-101-1998-04022
3rd row3230000-101-1996-11149
4th row3230000-101-2007-00052
5th row3230000-101-2007-00169
ValueCountFrequency (%)
3230000-101-2002-17702 1
 
< 0.1%
3230000-101-1989-13205 1
 
< 0.1%
3230000-101-1999-00861 1
 
< 0.1%
3230000-101-2009-00020 1
 
< 0.1%
3230000-101-1993-13157 1
 
< 0.1%
3230000-101-1995-11410 1
 
< 0.1%
3230000-101-1997-04197 1
 
< 0.1%
3230000-101-2003-00327 1
 
< 0.1%
3230000-101-1996-04719 1
 
< 0.1%
3230000-101-1994-09665 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-05-11T03:24:35.490883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 75878
34.5%
1 34117
15.5%
- 30000
 
13.6%
3 24745
 
11.2%
2 20580
 
9.4%
9 11610
 
5.3%
4 4944
 
2.2%
5 4612
 
2.1%
8 4589
 
2.1%
7 4539
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 190000
86.4%
Dash Punctuation 30000
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 75878
39.9%
1 34117
18.0%
3 24745
 
13.0%
2 20580
 
10.8%
9 11610
 
6.1%
4 4944
 
2.6%
5 4612
 
2.4%
8 4589
 
2.4%
7 4539
 
2.4%
6 4386
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 75878
34.5%
1 34117
15.5%
- 30000
 
13.6%
3 24745
 
11.2%
2 20580
 
9.4%
9 11610
 
5.3%
4 4944
 
2.2%
5 4612
 
2.1%
8 4589
 
2.1%
7 4539
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 75878
34.5%
1 34117
15.5%
- 30000
 
13.6%
3 24745
 
11.2%
2 20580
 
9.4%
9 11610
 
5.3%
4 4944
 
2.2%
5 4612
 
2.1%
8 4589
 
2.1%
7 4539
 
2.1%
Distinct5856
Distinct (%)58.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1904-08-08 00:00:00
Maximum2020-11-16 00:00:00
2024-05-11T03:24:35.971019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:24:36.427635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3
8110 
1
1890 

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 8110
81.1%
1 1890
 
18.9%

Length

2024-05-11T03:24:37.019238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:24:37.425808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 8110
81.1%
1 1890
 
18.9%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
8110 
영업/정상
1890 

Length

Max length5
Median length2
Mean length2.567
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 8110
81.1%
영업/정상 1890
 
18.9%

Length

2024-05-11T03:24:37.860910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:24:38.220316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 8110
81.1%
영업/정상 1890
 
18.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
8110 
1
1890 

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 8110
81.1%
1 1890
 
18.9%

Length

2024-05-11T03:24:38.738035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:24:39.036628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 8110
81.1%
1 1890
 
18.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
8110 
영업
1890 

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 8110
81.1%
영업 1890
 
18.9%

Length

2024-05-11T03:24:39.395229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:24:39.703317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 8110
81.1%
영업 1890
 
18.9%

폐업일자
Date

MISSING 

Distinct4586
Distinct (%)56.5%
Missing1890
Missing (%)18.9%
Memory size156.2 KiB
Minimum1989-03-17 00:00:00
Maximum2024-05-07 00:00:00
2024-05-11T03:24:40.076509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:24:40.545439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

전화번호
Text

MISSING 

Distinct6121
Distinct (%)90.7%
Missing3250
Missing (%)32.5%
Memory size156.2 KiB
2024-05-11T03:24:41.502852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.041778
Min length2

Characters and Unicode

Total characters67782
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5900 ?
Unique (%)87.4%

Sample

1st row02 5628513
2nd row02 4162943
3rd row02 2038602
4th row02 4776236
5th row02 4232003
ValueCountFrequency (%)
02 5637
43.4%
0200000000 89
 
0.7%
00000 78
 
0.6%
400 36
 
0.3%
070 31
 
0.2%
402 31
 
0.2%
422 29
 
0.2%
424 29
 
0.2%
417 29
 
0.2%
412 27
 
0.2%
Other values (6185) 6958
53.6%
2024-05-11T03:24:42.857109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13822
20.4%
2 11969
17.7%
4 9367
13.8%
7317
10.8%
1 4974
 
7.3%
3 4482
 
6.6%
8 3309
 
4.9%
9 3253
 
4.8%
7 3157
 
4.7%
5 3109
 
4.6%
Other values (3) 3023
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60453
89.2%
Space Separator 7317
 
10.8%
Other Punctuation 11
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13822
22.9%
2 11969
19.8%
4 9367
15.5%
1 4974
 
8.2%
3 4482
 
7.4%
8 3309
 
5.5%
9 3253
 
5.4%
7 3157
 
5.2%
5 3109
 
5.1%
6 3011
 
5.0%
Space Separator
ValueCountFrequency (%)
7317
100.0%
Other Punctuation
ValueCountFrequency (%)
. 11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 67782
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13822
20.4%
2 11969
17.7%
4 9367
13.8%
7317
10.8%
1 4974
 
7.3%
3 4482
 
6.6%
8 3309
 
4.9%
9 3253
 
4.8%
7 3157
 
4.7%
5 3109
 
4.6%
Other values (3) 3023
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 67782
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13822
20.4%
2 11969
17.7%
4 9367
13.8%
7317
10.8%
1 4974
 
7.3%
3 4482
 
6.6%
8 3309
 
4.9%
9 3253
 
4.8%
7 3157
 
4.7%
5 3109
 
4.6%
Other values (3) 3023
 
4.5%
Distinct4527
Distinct (%)45.6%
Missing63
Missing (%)0.6%
Memory size156.2 KiB
2024-05-11T03:24:43.777930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.1811412
Min length3

Characters and Unicode

Total characters51485
Distinct characters12
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

Unique3222 ?
Unique (%)32.4%

Sample

1st row41.50
2nd row167.44
3rd row63.50
4th row30.00
5th row26.40
ValueCountFrequency (%)
26.40 244
 
2.5%
33.00 189
 
1.9%
29.70 156
 
1.6%
30.00 140
 
1.4%
66.00 116
 
1.2%
23.10 112
 
1.1%
49.50 95
 
1.0%
19.80 84
 
0.8%
26.00 70
 
0.7%
99.00 66
 
0.7%
Other values (4517) 8665
87.2%
2024-05-11T03:24:45.536001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9937
19.3%
0 8986
17.5%
2 5550
10.8%
1 4354
8.5%
3 3866
 
7.5%
4 3601
 
7.0%
6 3485
 
6.8%
5 3463
 
6.7%
9 2957
 
5.7%
8 2865
 
5.6%
Other values (2) 2421
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 41533
80.7%
Other Punctuation 9952
 
19.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8986
21.6%
2 5550
13.4%
1 4354
10.5%
3 3866
9.3%
4 3601
8.7%
6 3485
 
8.4%
5 3463
 
8.3%
9 2957
 
7.1%
8 2865
 
6.9%
7 2406
 
5.8%
Other Punctuation
ValueCountFrequency (%)
. 9937
99.8%
, 15
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 51485
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9937
19.3%
0 8986
17.5%
2 5550
10.8%
1 4354
8.5%
3 3866
 
7.5%
4 3601
 
7.0%
6 3485
 
6.8%
5 3463
 
6.7%
9 2957
 
5.7%
8 2865
 
5.6%
Other values (2) 2421
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 51485
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9937
19.3%
0 8986
17.5%
2 5550
10.8%
1 4354
8.5%
3 3866
 
7.5%
4 3601
 
7.0%
6 3485
 
6.8%
5 3463
 
6.7%
9 2957
 
5.7%
8 2865
 
5.6%
Other values (2) 2421
 
4.7%
Distinct234
Distinct (%)2.3%
Missing2
Missing (%)< 0.1%
Memory size156.2 KiB
2024-05-11T03:24:46.515803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0660132
Min length6

Characters and Unicode

Total characters60648
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

Unique39 ?
Unique (%)0.4%

Sample

1st row138934
2nd row138861
3rd row138838
4th row138859
5th row138839
ValueCountFrequency (%)
138862 379
 
3.8%
138861 317
 
3.2%
138888 299
 
3.0%
138934 297
 
3.0%
138200 290
 
2.9%
138842 235
 
2.4%
138837 221
 
2.2%
138803 206
 
2.1%
138847 204
 
2.0%
138854 190
 
1.9%
Other values (224) 7360
73.6%
2024-05-11T03:24:47.970220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 20212
33.3%
1 12440
20.5%
3 12090
19.9%
0 2915
 
4.8%
4 2887
 
4.8%
2 2700
 
4.5%
5 1951
 
3.2%
6 1878
 
3.1%
9 1535
 
2.5%
7 1380
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59988
98.9%
Dash Punctuation 660
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 20212
33.7%
1 12440
20.7%
3 12090
20.2%
0 2915
 
4.9%
4 2887
 
4.8%
2 2700
 
4.5%
5 1951
 
3.3%
6 1878
 
3.1%
9 1535
 
2.6%
7 1380
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 660
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 60648
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 20212
33.3%
1 12440
20.5%
3 12090
19.9%
0 2915
 
4.8%
4 2887
 
4.8%
2 2700
 
4.5%
5 1951
 
3.2%
6 1878
 
3.1%
9 1535
 
2.5%
7 1380
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60648
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 20212
33.3%
1 12440
20.5%
3 12090
19.9%
0 2915
 
4.8%
4 2887
 
4.8%
2 2700
 
4.5%
5 1951
 
3.2%
6 1878
 
3.1%
9 1535
 
2.5%
7 1380
 
2.3%
Distinct7442
Distinct (%)74.4%
Missing2
Missing (%)< 0.1%
Memory size156.2 KiB
2024-05-11T03:24:48.790300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length51
Mean length24.40058
Min length14

Characters and Unicode

Total characters243957
Distinct characters422
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

Unique5987 ?
Unique (%)59.9%

Sample

1st row서울특별시 송파구 신천동 7번지 장미A상가 2동 112,113,114호
2nd row서울특별시 송파구 잠실동 176-7번지 동진빌딩 2층동
3rd row서울특별시 송파구 삼전동 67-6번지
4th row서울특별시 송파구 오금동 129-11번지
5th row서울특별시 송파구 삼전동 97-7번지
ValueCountFrequency (%)
서울특별시 9997
21.8%
송파구 9997
21.8%
잠실동 1468
 
3.2%
가락동 1454
 
3.2%
지상1층 1158
 
2.5%
방이동 1114
 
2.4%
문정동 1024
 
2.2%
석촌동 1003
 
2.2%
송파동 801
 
1.7%
마천동 589
 
1.3%
Other values (5911) 17238
37.6%
2024-05-11T03:24:50.174489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
44577
18.3%
1 12249
 
5.0%
11179
 
4.6%
10892
 
4.5%
10569
 
4.3%
10343
 
4.2%
10128
 
4.2%
10009
 
4.1%
10004
 
4.1%
10001
 
4.1%
Other values (412) 104006
42.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 145145
59.5%
Space Separator 44577
 
18.3%
Decimal Number 43617
 
17.9%
Dash Punctuation 9009
 
3.7%
Uppercase Letter 434
 
0.2%
Other Punctuation 419
 
0.2%
Close Punctuation 351
 
0.1%
Open Punctuation 349
 
0.1%
Lowercase Letter 30
 
< 0.1%
Math Symbol 23
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
11179
 
7.7%
10892
 
7.5%
10569
 
7.3%
10343
 
7.1%
10128
 
7.0%
10009
 
6.9%
10004
 
6.9%
10001
 
6.9%
9997
 
6.9%
9997
 
6.9%
Other values (350) 42026
29.0%
Uppercase Letter
ValueCountFrequency (%)
B 143
32.9%
A 98
22.6%
C 24
 
5.5%
F 23
 
5.3%
S 18
 
4.1%
T 17
 
3.9%
I 16
 
3.7%
Y 14
 
3.2%
N 13
 
3.0%
G 11
 
2.5%
Other values (14) 57
 
13.1%
Lowercase Letter
ValueCountFrequency (%)
c 5
16.7%
e 4
13.3%
a 3
10.0%
s 3
10.0%
l 2
 
6.7%
i 2
 
6.7%
t 2
 
6.7%
u 2
 
6.7%
w 1
 
3.3%
k 1
 
3.3%
Other values (5) 5
16.7%
Decimal Number
ValueCountFrequency (%)
1 12249
28.1%
2 6212
14.2%
0 4129
 
9.5%
3 3467
 
7.9%
4 3394
 
7.8%
8 3024
 
6.9%
7 2822
 
6.5%
5 2800
 
6.4%
9 2779
 
6.4%
6 2741
 
6.3%
Other Punctuation
ValueCountFrequency (%)
, 386
92.1%
. 15
 
3.6%
/ 7
 
1.7%
? 7
 
1.7%
& 3
 
0.7%
@ 1
 
0.2%
Letter Number
ValueCountFrequency (%)
2
66.7%
1
33.3%
Space Separator
ValueCountFrequency (%)
44577
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9009
100.0%
Close Punctuation
ValueCountFrequency (%)
) 351
100.0%
Open Punctuation
ValueCountFrequency (%)
( 349
100.0%
Math Symbol
ValueCountFrequency (%)
~ 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 145145
59.5%
Common 98345
40.3%
Latin 467
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
11179
 
7.7%
10892
 
7.5%
10569
 
7.3%
10343
 
7.1%
10128
 
7.0%
10009
 
6.9%
10004
 
6.9%
10001
 
6.9%
9997
 
6.9%
9997
 
6.9%
Other values (350) 42026
29.0%
Latin
ValueCountFrequency (%)
B 143
30.6%
A 98
21.0%
C 24
 
5.1%
F 23
 
4.9%
S 18
 
3.9%
T 17
 
3.6%
I 16
 
3.4%
Y 14
 
3.0%
N 13
 
2.8%
G 11
 
2.4%
Other values (31) 90
19.3%
Common
ValueCountFrequency (%)
44577
45.3%
1 12249
 
12.5%
- 9009
 
9.2%
2 6212
 
6.3%
0 4129
 
4.2%
3 3467
 
3.5%
4 3394
 
3.5%
8 3024
 
3.1%
7 2822
 
2.9%
5 2800
 
2.8%
Other values (11) 6662
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 145144
59.5%
ASCII 98809
40.5%
Number Forms 3
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
44577
45.1%
1 12249
 
12.4%
- 9009
 
9.1%
2 6212
 
6.3%
0 4129
 
4.2%
3 3467
 
3.5%
4 3394
 
3.4%
8 3024
 
3.1%
7 2822
 
2.9%
5 2800
 
2.8%
Other values (50) 7126
 
7.2%
Hangul
ValueCountFrequency (%)
11179
 
7.7%
10892
 
7.5%
10569
 
7.3%
10343
 
7.1%
10128
 
7.0%
10009
 
6.9%
10004
 
6.9%
10001
 
6.9%
9997
 
6.9%
9997
 
6.9%
Other values (349) 42025
29.0%
Number Forms
ValueCountFrequency (%)
2
66.7%
1
33.3%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

도로명주소
Text

MISSING 

Distinct4416
Distinct (%)94.6%
Missing5332
Missing (%)53.3%
Memory size156.2 KiB
2024-05-11T03:24:50.996547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length79
Median length66
Mean length34.447301
Min length21

Characters and Unicode

Total characters160800
Distinct characters416
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4206 ?
Unique (%)90.1%

Sample

1st row서울특별시 송파구 올림픽로35길 124 (신천동, 장미A상가 2동 112,113,114호)
2nd row서울특별시 송파구 올림픽로45길 19 (풍납동,풍성빌딩 101호 102호)
3rd row서울특별시 송파구 가락로16길 3-12, 지상1층 (석촌동)
4th row서울특별시 송파구 백제고분로7길 8-16, 2층 (잠실동)
5th row서울특별시 송파구 양재대로66길 44, 지상1층 (가락동)
ValueCountFrequency (%)
서울특별시 4667
 
15.3%
송파구 4667
 
15.3%
1층 1113
 
3.6%
지상1층 974
 
3.2%
문정동 647
 
2.1%
잠실동 593
 
1.9%
가락동 542
 
1.8%
지하1층 499
 
1.6%
방이동 478
 
1.6%
석촌동 349
 
1.1%
Other values (2875) 15999
52.4%
2024-05-11T03:24:52.240547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25892
 
16.1%
1 8971
 
5.6%
5880
 
3.7%
5692
 
3.5%
5418
 
3.4%
, 5282
 
3.3%
4828
 
3.0%
) 4739
 
2.9%
( 4739
 
2.9%
4689
 
2.9%
Other values (406) 84670
52.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 92408
57.5%
Decimal Number 25904
 
16.1%
Space Separator 25892
 
16.1%
Other Punctuation 5301
 
3.3%
Close Punctuation 4740
 
2.9%
Open Punctuation 4740
 
2.9%
Dash Punctuation 980
 
0.6%
Uppercase Letter 768
 
0.5%
Math Symbol 37
 
< 0.1%
Lowercase Letter 29
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5880
 
6.4%
5692
 
6.2%
5418
 
5.9%
4828
 
5.2%
4689
 
5.1%
4674
 
5.1%
4673
 
5.1%
4672
 
5.1%
4667
 
5.1%
4667
 
5.1%
Other values (345) 42548
46.0%
Uppercase Letter
ValueCountFrequency (%)
B 289
37.6%
A 174
22.7%
C 75
 
9.8%
G 49
 
6.4%
E 45
 
5.9%
F 25
 
3.3%
Y 23
 
3.0%
T 16
 
2.1%
S 13
 
1.7%
N 11
 
1.4%
Other values (14) 48
 
6.2%
Lowercase Letter
ValueCountFrequency (%)
c 11
37.9%
e 3
 
10.3%
l 2
 
6.9%
b 2
 
6.9%
a 2
 
6.9%
s 2
 
6.9%
w 1
 
3.4%
x 1
 
3.4%
y 1
 
3.4%
k 1
 
3.4%
Other values (3) 3
 
10.3%
Decimal Number
ValueCountFrequency (%)
1 8971
34.6%
2 4022
15.5%
0 2404
 
9.3%
3 2358
 
9.1%
4 2039
 
7.9%
5 1548
 
6.0%
6 1332
 
5.1%
7 1147
 
4.4%
8 1057
 
4.1%
9 1026
 
4.0%
Other Punctuation
ValueCountFrequency (%)
, 5282
99.6%
. 9
 
0.2%
/ 3
 
0.1%
? 3
 
0.1%
& 3
 
0.1%
* 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 4739
> 99.9%
] 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 4739
> 99.9%
[ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
25892
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 980
100.0%
Math Symbol
ValueCountFrequency (%)
~ 37
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 92408
57.5%
Common 67594
42.0%
Latin 798
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5880
 
6.4%
5692
 
6.2%
5418
 
5.9%
4828
 
5.2%
4689
 
5.1%
4674
 
5.1%
4673
 
5.1%
4672
 
5.1%
4667
 
5.1%
4667
 
5.1%
Other values (345) 42548
46.0%
Latin
ValueCountFrequency (%)
B 289
36.2%
A 174
21.8%
C 75
 
9.4%
G 49
 
6.1%
E 45
 
5.6%
F 25
 
3.1%
Y 23
 
2.9%
T 16
 
2.0%
S 13
 
1.6%
c 11
 
1.4%
Other values (28) 78
 
9.8%
Common
ValueCountFrequency (%)
25892
38.3%
1 8971
 
13.3%
, 5282
 
7.8%
) 4739
 
7.0%
( 4739
 
7.0%
2 4022
 
6.0%
0 2404
 
3.6%
3 2358
 
3.5%
4 2039
 
3.0%
5 1548
 
2.3%
Other values (13) 5600
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 92408
57.5%
ASCII 68391
42.5%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25892
37.9%
1 8971
 
13.1%
, 5282
 
7.7%
) 4739
 
6.9%
( 4739
 
6.9%
2 4022
 
5.9%
0 2404
 
3.5%
3 2358
 
3.4%
4 2039
 
3.0%
5 1548
 
2.3%
Other values (50) 6397
 
9.4%
Hangul
ValueCountFrequency (%)
5880
 
6.4%
5692
 
6.2%
5418
 
5.9%
4828
 
5.2%
4689
 
5.1%
4674
 
5.1%
4673
 
5.1%
4672
 
5.1%
4667
 
5.1%
4667
 
5.1%
Other values (345) 42548
46.0%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Real number (ℝ)

MISSING  SKEWED 

Distinct312
Distinct (%)6.8%
Missing5407
Missing (%)54.1%
Infinite0
Infinite (%)0.0%
Mean5672.8156
Minimum5500
Maximum13141
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T03:24:52.686872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5500
5-th percentile5510
Q15563
median5663
Q35758
95-th percentile5849
Maximum13141
Range7641
Interquartile range (IQR)195

Descriptive statistics

Standard deviation153.52103
Coefficient of variation (CV)0.02706258
Kurtosis1218.5278
Mean5672.8156
Median Absolute Deviation (MAD)98
Skewness25.127137
Sum26055242
Variance23568.706
MonotonicityNot monotonic
2024-05-11T03:24:53.130518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5554 118
 
1.2%
5559 108
 
1.1%
5510 90
 
0.9%
5836 90
 
0.9%
5854 87
 
0.9%
5855 86
 
0.9%
5548 69
 
0.7%
5560 59
 
0.6%
5699 59
 
0.6%
5551 59
 
0.6%
Other values (302) 3768
37.7%
(Missing) 5407
54.1%
ValueCountFrequency (%)
5500 7
 
0.1%
5501 16
 
0.2%
5502 23
 
0.2%
5503 13
 
0.1%
5504 56
0.6%
5505 1
 
< 0.1%
5507 23
 
0.2%
5509 5
 
0.1%
5510 90
0.9%
5511 10
 
0.1%
ValueCountFrequency (%)
13141 1
 
< 0.1%
5855 86
0.9%
5854 87
0.9%
5852 53
0.5%
5849 36
0.4%
5841 37
0.4%
5840 11
 
0.1%
5839 16
 
0.2%
5838 56
0.6%
5837 31
 
0.3%
Distinct8665
Distinct (%)86.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T03:24:53.762890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length32
Mean length5.4505
Min length1

Characters and Unicode

Total characters54505
Distinct characters1086
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7862 ?
Unique (%)78.6%

Sample

1st row새벽집
2nd row프로야구
3rd row대부정
4th row가정식당
5th row새참방
ValueCountFrequency (%)
잠실점 63
 
0.5%
송파점 51
 
0.4%
문정점 40
 
0.3%
카페 35
 
0.3%
방이점 30
 
0.2%
투다리 26
 
0.2%
떡볶이 22
 
0.2%
전주식당 21
 
0.2%
가락점 21
 
0.2%
신천점 19
 
0.2%
Other values (9404) 12087
97.4%
2024-05-11T03:24:54.716511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2419
 
4.4%
1155
 
2.1%
1132
 
2.1%
949
 
1.7%
911
 
1.7%
803
 
1.5%
795
 
1.5%
702
 
1.3%
592
 
1.1%
588
 
1.1%
Other values (1076) 44459
81.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 47838
87.8%
Space Separator 2419
 
4.4%
Lowercase Letter 1228
 
2.3%
Uppercase Letter 1173
 
2.2%
Decimal Number 578
 
1.1%
Close Punctuation 528
 
1.0%
Open Punctuation 527
 
1.0%
Other Punctuation 187
 
0.3%
Dash Punctuation 17
 
< 0.1%
Connector Punctuation 5
 
< 0.1%
Other values (3) 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1155
 
2.4%
1132
 
2.4%
949
 
2.0%
911
 
1.9%
803
 
1.7%
795
 
1.7%
702
 
1.5%
592
 
1.2%
588
 
1.2%
475
 
1.0%
Other values (994) 39736
83.1%
Uppercase Letter
ValueCountFrequency (%)
A 109
 
9.3%
B 100
 
8.5%
E 95
 
8.1%
C 91
 
7.8%
O 90
 
7.7%
S 68
 
5.8%
R 60
 
5.1%
T 58
 
4.9%
F 52
 
4.4%
L 48
 
4.1%
Other values (16) 402
34.3%
Lowercase Letter
ValueCountFrequency (%)
e 185
15.1%
o 125
 
10.2%
a 123
 
10.0%
n 80
 
6.5%
i 74
 
6.0%
l 71
 
5.8%
r 69
 
5.6%
f 48
 
3.9%
c 46
 
3.7%
s 46
 
3.7%
Other values (15) 361
29.4%
Other Punctuation
ValueCountFrequency (%)
. 66
35.3%
& 57
30.5%
, 20
 
10.7%
' 14
 
7.5%
? 13
 
7.0%
! 7
 
3.7%
/ 2
 
1.1%
: 2
 
1.1%
# 2
 
1.1%
% 2
 
1.1%
Other values (2) 2
 
1.1%
Decimal Number
ValueCountFrequency (%)
1 104
18.0%
2 99
17.1%
0 85
14.7%
7 50
8.7%
9 45
7.8%
5 45
7.8%
8 44
7.6%
3 43
7.4%
4 37
 
6.4%
6 26
 
4.5%
Math Symbol
ValueCountFrequency (%)
+ 1
50.0%
~ 1
50.0%
Space Separator
ValueCountFrequency (%)
2419
100.0%
Close Punctuation
ValueCountFrequency (%)
) 528
100.0%
Open Punctuation
ValueCountFrequency (%)
( 527
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%
Other Symbol
ValueCountFrequency (%)
2
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 47812
87.7%
Common 4266
 
7.8%
Latin 2401
 
4.4%
Han 26
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1155
 
2.4%
1132
 
2.4%
949
 
2.0%
911
 
1.9%
803
 
1.7%
795
 
1.7%
702
 
1.5%
592
 
1.2%
588
 
1.2%
475
 
1.0%
Other values (972) 39710
83.1%
Latin
ValueCountFrequency (%)
e 185
 
7.7%
o 125
 
5.2%
a 123
 
5.1%
A 109
 
4.5%
B 100
 
4.2%
E 95
 
4.0%
C 91
 
3.8%
O 90
 
3.7%
n 80
 
3.3%
i 74
 
3.1%
Other values (41) 1329
55.4%
Common
ValueCountFrequency (%)
2419
56.7%
) 528
 
12.4%
( 527
 
12.4%
1 104
 
2.4%
2 99
 
2.3%
0 85
 
2.0%
. 66
 
1.5%
& 57
 
1.3%
7 50
 
1.2%
9 45
 
1.1%
Other values (21) 286
 
6.7%
Han
ValueCountFrequency (%)
2
 
7.7%
2
 
7.7%
2
 
7.7%
2
 
7.7%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
Other values (12) 12
46.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 47812
87.7%
ASCII 6665
 
12.2%
CJK 25
 
< 0.1%
Letterlike Symbols 2
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2419
36.3%
) 528
 
7.9%
( 527
 
7.9%
e 185
 
2.8%
o 125
 
1.9%
a 123
 
1.8%
A 109
 
1.6%
1 104
 
1.6%
B 100
 
1.5%
2 99
 
1.5%
Other values (71) 2346
35.2%
Hangul
ValueCountFrequency (%)
1155
 
2.4%
1132
 
2.4%
949
 
2.0%
911
 
1.9%
803
 
1.7%
795
 
1.7%
702
 
1.5%
592
 
1.2%
588
 
1.2%
475
 
1.0%
Other values (972) 39710
83.1%
CJK
ValueCountFrequency (%)
2
 
8.0%
2
 
8.0%
2
 
8.0%
2
 
8.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
Other values (11) 11
44.0%
Letterlike Symbols
ValueCountFrequency (%)
2
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
1
100.0%
Distinct6259
Distinct (%)62.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1999-04-15 00:00:00
Maximum2024-05-09 13:02:10
2024-05-11T03:24:55.114723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:24:55.552588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
7549 
U
2451 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 7549
75.5%
U 2451
 
24.5%

Length

2024-05-11T03:24:55.928093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:24:56.096453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 7549
75.5%
u 2451
 
24.5%
Distinct1231
Distinct (%)12.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T03:24:56.303678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:24:56.708292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct26
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
한식
4916 
분식
1553 
기타
1076 
경양식
699 
호프/통닭
 
491
Other values (21)
1265 

Length

Max length15
Median length2
Mean length2.5061
Min length2

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row분식
2nd row분식
3rd row한식
4th row한식
5th row한식

Common Values

ValueCountFrequency (%)
한식 4916
49.2%
분식 1553
 
15.5%
기타 1076
 
10.8%
경양식 699
 
7.0%
호프/통닭 491
 
4.9%
일식 334
 
3.3%
중국식 237
 
2.4%
통닭(치킨) 194
 
1.9%
정종/대포집/소주방 161
 
1.6%
까페 148
 
1.5%
Other values (16) 191
 
1.9%

Length

2024-05-11T03:24:57.380439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 4916
49.2%
분식 1553
 
15.5%
기타 1076
 
10.8%
경양식 699
 
7.0%
호프/통닭 491
 
4.9%
일식 334
 
3.3%
중국식 237
 
2.4%
통닭(치킨 194
 
1.9%
정종/대포집/소주방 161
 
1.6%
까페 148
 
1.5%
Other values (16) 191
 
1.9%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct4080
Distinct (%)42.8%
Missing468
Missing (%)4.7%
Infinite0
Infinite (%)0.0%
Mean210030.93
Minimum206223.14
Maximum214116.81
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T03:24:57.714245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum206223.14
5-th percentile207204.15
Q1208707.09
median210128.39
Q3211049.55
95-th percentile213089.94
Maximum214116.81
Range7893.669
Interquartile range (IQR)2342.4628

Descriptive statistics

Standard deviation1709.2175
Coefficient of variation (CV)0.0081379324
Kurtosis-0.64530326
Mean210030.93
Median Absolute Deviation (MAD)1077.4815
Skewness0.091197924
Sum2.0020148 × 109
Variance2921424.5
MonotonicityNot monotonic
2024-05-11T03:24:58.235175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
208589.363343145 168
 
1.7%
208707.089897534 108
 
1.1%
209790.959909032 73
 
0.7%
209074.900840074 59
 
0.6%
210580.683290918 49
 
0.5%
210558.0 44
 
0.4%
210986.460698452 43
 
0.4%
210868.397496689 31
 
0.3%
210749.0 30
 
0.3%
211619.368009793 26
 
0.3%
Other values (4070) 8901
89.0%
(Missing) 468
 
4.7%
ValueCountFrequency (%)
206223.136110141 1
 
< 0.1%
206322.970067697 1
 
< 0.1%
206383.829438022 4
< 0.1%
206397.34797252 5
0.1%
206425.501600423 3
< 0.1%
206487.800145227 1
 
< 0.1%
206597.102072932 2
 
< 0.1%
206684.903140953 1
 
< 0.1%
206726.499021996 5
0.1%
206731.192156063 3
< 0.1%
ValueCountFrequency (%)
214116.805129503 1
 
< 0.1%
213926.029560738 1
 
< 0.1%
213886.824622785 2
< 0.1%
213880.072396674 1
 
< 0.1%
213873.675372176 1
 
< 0.1%
213862.955350277 1
 
< 0.1%
213860.660598816 3
< 0.1%
213859.070843691 1
 
< 0.1%
213854.731189463 1
 
< 0.1%
213849.121019057 3
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct4079
Distinct (%)42.8%
Missing468
Missing (%)4.7%
Infinite0
Infinite (%)0.0%
Mean444617.59
Minimum439236.86
Maximum448596.61
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T03:24:58.704680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum439236.86
5-th percentile442553
Q1443842.81
median444659.05
Q3445336.43
95-th percentile446299.35
Maximum448596.61
Range9359.7454
Interquartile range (IQR)1493.6225

Descriptive statistics

Standard deviation1222.1368
Coefficient of variation (CV)0.0027487369
Kurtosis1.1344214
Mean444617.59
Median Absolute Deviation (MAD)730.07271
Skewness0.31738041
Sum4.2380948 × 109
Variance1493618.3
MonotonicityNot monotonic
2024-05-11T03:24:59.254685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
445455.90405262 168
 
1.7%
446299.352775446 108
 
1.1%
443481.212174317 73
 
0.7%
445657.80932984 59
 
0.6%
443657.71204579 49
 
0.5%
442587.0 44
 
0.4%
441725.293491662 43
 
0.4%
442053.227933005 31
 
0.3%
442560.0 30
 
0.3%
445963.384875409 26
 
0.3%
Other values (4069) 8901
89.0%
(Missing) 468
 
4.7%
ValueCountFrequency (%)
439236.864712055 1
 
< 0.1%
441093.234429209 1
 
< 0.1%
441197.665004971 1
 
< 0.1%
441406.981434166 3
 
< 0.1%
441411.906445707 4
 
< 0.1%
441412.0 7
0.1%
441426.0 10
0.1%
441460.547970063 1
 
< 0.1%
441479.512244612 2
 
< 0.1%
441586.029967716 2
 
< 0.1%
ValueCountFrequency (%)
448596.610120879 1
< 0.1%
448571.39753402 1
< 0.1%
448548.80270079 1
< 0.1%
448472.581253344 2
< 0.1%
448461.082353287 1
< 0.1%
448439.202290106 2
< 0.1%
448437.083161462 1
< 0.1%
448435.73123223 1
< 0.1%
448425.885637954 2
< 0.1%
448422.080740097 1
< 0.1%

위생업태명
Categorical

Distinct26
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
한식
4491 
분식
1489 
<NA>
994 
기타
855 
경양식
647 
Other values (21)
1524 

Length

Max length15
Median length2
Mean length2.6479
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row분식
2nd row분식
3rd row한식
4th row한식
5th row한식

Common Values

ValueCountFrequency (%)
한식 4491
44.9%
분식 1489
 
14.9%
<NA> 994
 
9.9%
기타 855
 
8.6%
경양식 647
 
6.5%
호프/통닭 418
 
4.2%
일식 276
 
2.8%
중국식 206
 
2.1%
통닭(치킨) 180
 
1.8%
정종/대포집/소주방 151
 
1.5%
Other values (16) 293
 
2.9%

Length

2024-05-11T03:24:59.648886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 4491
44.9%
분식 1489
 
14.9%
na 994
 
9.9%
기타 855
 
8.6%
경양식 647
 
6.5%
호프/통닭 418
 
4.2%
일식 276
 
2.8%
중국식 206
 
2.1%
통닭(치킨 180
 
1.8%
정종/대포집/소주방 151
 
1.5%
Other values (16) 293
 
2.9%

남성종사자수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct13
Distinct (%)0.2%
Missing4686
Missing (%)46.9%
Infinite0
Infinite (%)0.0%
Mean0.37786978
Minimum0
Maximum93
Zeros4019
Zeros (%)40.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T03:25:00.019480image/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 deviation2.0263295
Coefficient of variation (CV)5.3625074
Kurtosis1673.4438
Mean0.37786978
Median Absolute Deviation (MAD)0
Skewness37.70501
Sum2008
Variance4.1060112
MonotonicityNot monotonic
2024-05-11T03:25:00.366751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 4019
40.2%
1 1002
 
10.0%
2 181
 
1.8%
3 62
 
0.6%
4 28
 
0.3%
5 13
 
0.1%
8 2
 
< 0.1%
93 2
 
< 0.1%
7 1
 
< 0.1%
41 1
 
< 0.1%
Other values (3) 3
 
< 0.1%
(Missing) 4686
46.9%
ValueCountFrequency (%)
0 4019
40.2%
1 1002
 
10.0%
2 181
 
1.8%
3 62
 
0.6%
4 28
 
0.3%
5 13
 
0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
8 2
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
93 2
 
< 0.1%
41 1
 
< 0.1%
15 1
 
< 0.1%
10 1
 
< 0.1%
8 2
 
< 0.1%
7 1
 
< 0.1%
6 1
 
< 0.1%
5 13
 
0.1%
4 28
0.3%
3 62
0.6%

여성종사자수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct11
Distinct (%)0.2%
Missing4650
Missing (%)46.5%
Infinite0
Infinite (%)0.0%
Mean0.52448598
Minimum0
Maximum94
Zeros3495
Zeros (%)34.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T03:25:01.051142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum94
Range94
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.0105486
Coefficient of variation (CV)3.8333695
Kurtosis1750.5396
Mean0.52448598
Median Absolute Deviation (MAD)0
Skewness38.097856
Sum2806
Variance4.0423055
MonotonicityNot monotonic
2024-05-11T03:25:01.397135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 3495
34.9%
1 1307
 
13.1%
2 424
 
4.2%
3 82
 
0.8%
4 25
 
0.2%
5 6
 
0.1%
6 3
 
< 0.1%
10 3
 
< 0.1%
7 2
 
< 0.1%
94 2
 
< 0.1%
(Missing) 4650
46.5%
ValueCountFrequency (%)
0 3495
34.9%
1 1307
 
13.1%
2 424
 
4.2%
3 82
 
0.8%
4 25
 
0.2%
5 6
 
0.1%
6 3
 
< 0.1%
7 2
 
< 0.1%
10 3
 
< 0.1%
25 1
 
< 0.1%
ValueCountFrequency (%)
94 2
 
< 0.1%
25 1
 
< 0.1%
10 3
 
< 0.1%
7 2
 
< 0.1%
6 3
 
< 0.1%
5 6
 
0.1%
4 25
 
0.2%
3 82
 
0.8%
2 424
 
4.2%
1 1307
13.1%
Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5176 
주택가주변
3080 
기타
1346 
유흥업소밀집지역
 
198
아파트지역
 
179
Other values (3)
 
21

Length

Max length8
Median length4
Mean length4.144
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5176
51.8%
주택가주변 3080
30.8%
기타 1346
 
13.5%
유흥업소밀집지역 198
 
2.0%
아파트지역 179
 
1.8%
학교정화(상대) 13
 
0.1%
학교정화(절대) 5
 
0.1%
결혼예식장주변 3
 
< 0.1%

Length

2024-05-11T03:25:01.803344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:25:02.116426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5176
51.8%
주택가주변 3080
30.8%
기타 1346
 
13.5%
유흥업소밀집지역 198
 
2.0%
아파트지역 179
 
1.8%
학교정화(상대 13
 
0.1%
학교정화(절대 5
 
< 0.1%
결혼예식장주변 3
 
< 0.1%

등급구분명
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5180 
기타
2304 
837 
우수
730 
지도
 
483
Other values (3)
 
466

Length

Max length4
Median length4
Mean length2.9417
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5180
51.8%
기타 2304
23.0%
837
 
8.4%
우수 730
 
7.3%
지도 483
 
4.8%
자율 358
 
3.6%
106
 
1.1%
관리 2
 
< 0.1%

Length

2024-05-11T03:25:02.547412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:25:02.956509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5180
51.8%
기타 2304
23.0%
837
 
8.4%
우수 730
 
7.3%
지도 483
 
4.8%
자율 358
 
3.6%
106
 
1.1%
관리 2
 
< 0.1%

급수시설구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5883 
상수도전용
4100 
상수도(음용)지하수(주방용)겸용
 
16
지하수전용
 
1

Length

Max length17
Median length4
Mean length4.4309
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5883
58.8%
상수도전용 4100
41.0%
상수도(음용)지하수(주방용)겸용 16
 
0.2%
지하수전용 1
 
< 0.1%

Length

2024-05-11T03:25:03.414266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:25:03.748093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5883
58.8%
상수도전용 4100
41.0%
상수도(음용)지하수(주방용)겸용 16
 
0.2%
지하수전용 1
 
< 0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9821 
0
 
179

Length

Max length4
Median length4
Mean length3.9463
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> 9821
98.2%
0 179
 
1.8%

Length

2024-05-11T03:25:04.157692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:25:04.485680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9821
98.2%
0 179
 
1.8%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9819 
0
 
181

Length

Max length4
Median length4
Mean length3.9457
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> 9819
98.2%
0 181
 
1.8%

Length

2024-05-11T03:25:04.852683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:25:05.172151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9819
98.2%
0 181
 
1.8%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9819 
0
 
181

Length

Max length4
Median length4
Mean length3.9457
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> 9819
98.2%
0 181
 
1.8%

Length

2024-05-11T03:25:05.451498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:25:05.636041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9819
98.2%
0 181
 
1.8%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9819 
0
 
181

Length

Max length4
Median length4
Mean length3.9457
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> 9819
98.2%
0 181
 
1.8%

Length

2024-05-11T03:25:05.841536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:25:06.020681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9819
98.2%
0 181
 
1.8%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9819 
0
 
181

Length

Max length4
Median length4
Mean length3.9457
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> 9819
98.2%
0 181
 
1.8%

Length

2024-05-11T03:25:06.325281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:25:06.639572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9819
98.2%
0 181
 
1.8%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9819 
0
 
181

Length

Max length4
Median length4
Mean length3.9457
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> 9819
98.2%
0 181
 
1.8%

Length

2024-05-11T03:25:06.962339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:25:07.271330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9819
98.2%
0 181
 
1.8%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9819 
0
 
181

Length

Max length4
Median length4
Mean length3.9457
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> 9819
98.2%
0 181
 
1.8%

Length

2024-05-11T03:25:07.604797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:25:07.909978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9819
98.2%
0 181
 
1.8%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing994
Missing (%)9.9%
Memory size97.7 KiB
False
8920 
True
 
86
(Missing)
994 
ValueCountFrequency (%)
False 8920
89.2%
True 86
 
0.9%
(Missing) 994
 
9.9%
2024-05-11T03:25:08.049762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING 

Distinct4146
Distinct (%)46.0%
Missing994
Missing (%)9.9%
Infinite0
Infinite (%)0.0%
Mean72.589483
Minimum0
Maximum5735
Zeros80
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T03:25:08.284478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile16.5
Q126.4
median40
Q383.81
95-th percentile204.09
Maximum5735
Range5735
Interquartile range (IQR)57.41

Descriptive statistics

Standard deviation119.91744
Coefficient of variation (CV)1.6519946
Kurtosis610.8687
Mean72.589483
Median Absolute Deviation (MAD)18.755
Skewness16.77895
Sum653740.88
Variance14380.191
MonotonicityNot monotonic
2024-05-11T03:25:08.686968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
26.4 235
 
2.4%
33.0 165
 
1.7%
29.7 147
 
1.5%
30.0 122
 
1.2%
23.1 110
 
1.1%
66.0 104
 
1.0%
49.5 91
 
0.9%
19.8 80
 
0.8%
0.0 80
 
0.8%
26.0 66
 
0.7%
Other values (4136) 7806
78.1%
(Missing) 994
 
9.9%
ValueCountFrequency (%)
0.0 80
0.8%
1.0 1
 
< 0.1%
2.25 2
 
< 0.1%
3.3 2
 
< 0.1%
4.2 1
 
< 0.1%
4.48 1
 
< 0.1%
5.46 1
 
< 0.1%
5.56 1
 
< 0.1%
5.75 1
 
< 0.1%
5.85 1
 
< 0.1%
ValueCountFrequency (%)
5735.0 1
< 0.1%
2343.28 1
< 0.1%
2305.36 1
< 0.1%
2145.0 1
< 0.1%
1642.14 1
< 0.1%
1518.04 1
< 0.1%
1491.5 1
< 0.1%
1431.4 1
< 0.1%
1320.0 1
< 0.1%
1246.0 1
< 0.1%
Distinct2
Distinct (%)100.0%
Missing9998
Missing (%)> 99.9%
Memory size156.2 KiB
2024-05-11T03:25:09.041308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length2.5
Mean length2.5
Min length1

Characters and Unicode

Total characters5
Distinct characters5
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

Unique2 ?
Unique (%)100.0%

Sample

1st row9286
2nd row
ValueCountFrequency (%)
9286 1
100.0%
2024-05-11T03:25:09.733337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 1
20.0%
2 1
20.0%
8 1
20.0%
6 1
20.0%
1
20.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4
80.0%
Space Separator 1
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 1
25.0%
2 1
25.0%
8 1
25.0%
6 1
25.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
9 1
20.0%
2 1
20.0%
8 1
20.0%
6 1
20.0%
1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 1
20.0%
2 1
20.0%
8 1
20.0%
6 1
20.0%
1
20.0%

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
1290232300003230000-101-2002-1770220020830<NA>1영업/정상1영업<NA><NA><NA><NA>02 562851341.50138934서울특별시 송파구 신천동 7번지 장미A상가 2동 112,113,114호서울특별시 송파구 올림픽로35길 124 (신천동, 장미A상가 2동 112,113,114호)5504새벽집2012-11-06 16:09:44I2018-08-31 23:59:59.0분식208707.089898446299.352775분식<NA><NA>기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N41.5<NA><NA><NA>
864332300003230000-101-1998-0402219980623<NA>3폐업2폐업20030313<NA><NA><NA>02 4162943167.44138861서울특별시 송파구 잠실동 176-7번지 동진빌딩 2층동<NA><NA>프로야구2003-07-16 00:00:00I2018-08-31 23:59:59.0분식206964.414977445386.914519분식<NA><NA>주택가주변우수상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N167.44<NA><NA><NA>
723532300003230000-101-1996-1114919960715<NA>3폐업2폐업20090716<NA><NA><NA>02 203860263.50138838서울특별시 송파구 삼전동 67-6번지<NA><NA>대부정2005-02-07 00:00:00I2018-08-31 23:59:59.0한식207990.709796444191.167225한식00주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N63.5<NA><NA><NA>
1612032300003230000-101-2007-0005220070213<NA>3폐업2폐업20130523<NA><NA><NA><NA>30.00138859서울특별시 송파구 오금동 129-11번지<NA><NA>가정식당2007-02-13 00:00:00I2018-08-31 23:59:59.0한식212168.871495444442.593446한식00<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N30.0<NA><NA><NA>
1623532300003230000-101-2007-0016920070511<NA>3폐업2폐업20100224<NA><NA><NA><NA>26.40138839서울특별시 송파구 삼전동 97-7번지<NA><NA>새참방2007-09-05 13:44:50I2018-08-31 23:59:59.0한식208160.122532444727.371708한식00<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N26.4<NA><NA><NA>
1204332300003230000-101-2001-1675420010904<NA>3폐업2폐업20020730<NA><NA><NA>02 477623623.10138832서울특별시 송파구 방이동 156-8번지<NA><NA>패밀리언2003-07-25 00:00:00I2018-08-31 23:59:59.0한식210381.992146445662.59141한식<NA><NA>기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N23.1<NA><NA><NA>
436232300003230000-101-1994-0372519940507<NA>3폐업2폐업19990408<NA><NA><NA>02 4232003223.20138050서울특별시 송파구 방이동 산 167-8번지<NA><NA>박옥란출장파티2003-06-20 00:00:00I2018-08-31 23:59:59.0출장조리<NA><NA>출장조리34주택가주변상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N223.2<NA><NA><NA>
1730532300003230000-101-2009-0025920090608<NA>3폐업2폐업20170222<NA><NA><NA><NA>83.64138878서울특별시 송파구 풍납동 392-2번지 풍성빌딩 101호 102호서울특별시 송파구 올림픽로45길 19 (풍납동,풍성빌딩 101호 102호)5537우야동동2017-03-06 10:12:18I2018-08-31 23:59:59.0한식210171.723445447214.905374한식<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N83.64<NA><NA><NA>
1732132300003230000-101-2009-0027520090615<NA>3폐업2폐업20180207<NA><NA><NA>02 2043200886.00138847서울특별시 송파구 석촌동 297-2번지 지상1층서울특별시 송파구 가락로16길 3-12, 지상1층 (석촌동)5697해마당2018-02-07 10:46:25I2018-08-31 23:59:59.0한식209588.877485444335.22373한식<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N86.0<NA><NA><NA>
1898432300003230000-101-2011-0063020111227<NA>3폐업2폐업20220831<NA><NA><NA>02 423 5292210.00138862서울특별시 송파구 잠실동 195-9서울특별시 송파구 백제고분로7길 8-16, 2층 (잠실동)5561대나무집2022-08-31 09:34:00U2021-12-09 00:03:00.0한식206985.109464445276.185152<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
1411532300003230000-101-2004-0006920040220<NA>3폐업2폐업20170222<NA><NA><NA><NA>88.00138130서울특별시 송파구 오금동 28-0번지 ,1,2오금동스포츠센타서울특별시 송파구 위례성대로22길 27-22 (오금동,,1,2오금동스포츠센타)5655서울레저스포츠 파워텍2017-03-02 17:58:02I2018-08-31 23:59:59.0분식211565.077399445013.127578분식00<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N88.0<NA><NA><NA>
110432300003230000-101-1989-0653919890504<NA>3폐업2폐업20020322<NA><NA><NA>023431071530.24138829서울특별시 송파구 방이동 89-11번지 (중심상가2층26호)<NA><NA>삼장벽제갈비2003-06-23 00:00:00I2018-08-31 23:59:59.0한식211619.36801445963.384875한식00아파트지역상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N30.24<NA><NA><NA>
184932300003230000-101-1990-1419219930729<NA>3폐업2폐업20160509<NA><NA><NA>02 406491870.18138818서울특별시 송파구 마천동 34-7번지서울특별시 송파구 마천로37길 5 (마천동)5734마천삼계탕2004-04-02 00:00:00I2018-08-31 23:59:59.0한식212854.262095444082.162827한식00기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N70.18<NA><NA><NA>
2495932300003230000-101-2019-0091320191211<NA>1영업/정상1영업<NA><NA><NA><NA>02 419 3001245.22138844서울특별시 송파구 석촌동 183-9번지서울특별시 송파구 석촌호수로 240, 2층 (석촌동)5609나리식당2019-12-11 11:19:02I2019-12-13 00:23:26.0한식209068.283749445090.212414한식<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>Y245.22<NA><NA><NA>
82132300003230000-101-1988-0918319881231<NA>3폐업2폐업20120921<NA><NA><NA>0204132046159.41138842서울특별시 송파구 석촌동 24-11번지<NA><NA>군산오징어집2004-04-27 00:00:00I2018-08-31 23:59:59.0경양식208681.402224444879.056734경양식31주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N159.41<NA><NA><NA>
381632300003230000-101-1993-0984719931105<NA>3폐업2폐업19961231<NA><NA><NA>02 4123459157.86138844서울특별시 송파구 석촌동 158-17번지<NA><NA>레인보우2003-06-13 00:00:00I2018-08-31 23:59:59.0경양식<NA><NA>경양식12주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N157.86<NA><NA><NA>
35032300003230000-101-1985-1315819850319<NA>3폐업2폐업19981105<NA><NA><NA>02 417585450.89138861서울특별시 송파구 잠실동 176-3번지<NA><NA>2003-06-23 00:00:00I2018-08-31 23:59:59.0한식206945.449732445393.130028한식02주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N50.89<NA><NA><NA>
1102032300003230000-101-2000-1550920000724<NA>3폐업2폐업20020709<NA><NA><NA>02 43152068.10138815서울특별시 송파구 거여동 580-0번지<NA><NA>골목집2003-07-23 00:00:00I2018-08-31 23:59:59.0한식213854.731189443117.51303한식00주택가주변자율<NA><NA><NA><NA><NA><NA><NA><NA><NA>N8.1<NA><NA><NA>
964932300003230000-101-1999-0052319990430<NA>3폐업2폐업20101029<NA><NA><NA>02 406918239.78138803서울특별시 송파구 가락동 84-6번지<NA><NA>에뜨랑제2010-02-17 14:16:40I2018-08-31 23:59:59.0분식210536.379532443748.684431분식00기타우수상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N39.78<NA><NA><NA>
877732300003230000-101-1998-0416319980109<NA>3폐업2폐업20170222<NA><NA><NA>02 4435733203.17138855서울특별시 송파구 오금동 17-16번지 지상2층서울특별시 송파구 위례성대로20길 22, 지상2층 (오금동)5657삼천포수산2017-03-02 17:34:26I2018-08-31 23:59:59.0한식211189.563607445248.966867한식00주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N203.17<NA><NA><NA>