Overview

Dataset statistics

Number of variables44
Number of observations10000
Missing cells95300
Missing cells (%)21.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 MiB
Average record size in memory383.0 B

Variable types

Categorical20
Text8
Unsupported7
DateTime3
Numeric5
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-18450/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 is highly imbalanced (97.6%)Imbalance
위생업태명 is highly imbalanced (56.3%)Imbalance
남성종사자수 is highly imbalanced (61.5%)Imbalance
여성종사자수 is highly imbalanced (69.9%)Imbalance
영업장주변구분명 is highly imbalanced (74.6%)Imbalance
등급구분명 is highly imbalanced (75.5%)Imbalance
급수시설구분명 is highly imbalanced (79.7%)Imbalance
총인원 is highly imbalanced (67.5%)Imbalance
공장사무직종업원수 is highly imbalanced (52.7%)Imbalance
공장판매직종업원수 is highly imbalanced (67.4%)Imbalance
공장생산직종업원수 is highly imbalanced (52.7%)Imbalance
보증액 is highly imbalanced (75.1%)Imbalance
월세액 is highly imbalanced (75.1%)Imbalance
다중이용업소여부 is highly imbalanced (99.8%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 1486 (14.9%) 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 6499 (65.0%) missing valuesMissing
소재지면적 has 1391 (13.9%) missing valuesMissing
도로명주소 has 2026 (20.3%) missing valuesMissing
도로명우편번호 has 2048 (20.5%) missing valuesMissing
좌표정보(X) has 255 (2.5%) missing valuesMissing
좌표정보(Y) has 255 (2.5%) missing valuesMissing
본사종업원수 has 7834 (78.3%) missing valuesMissing
다중이용업소여부 has 1750 (17.5%) missing valuesMissing
시설총규모 has 1750 (17.5%) missing valuesMissing
전통업소지정번호 has 10000 (100.0%) missing valuesMissing
전통업소주된음식 has 10000 (100.0%) missing valuesMissing
홈페이지 has 10000 (100.0%) missing valuesMissing
도로명우편번호 is highly skewed (γ1 = 50.51496525)Skewed
좌표정보(X) is highly skewed (γ1 = 34.6665713)Skewed
시설총규모 is highly skewed (γ1 = 43.70537895)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
전통업소지정번호 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
본사종업원수 has 2134 (21.3%) zerosZeros
시설총규모 has 8238 (82.4%) zerosZeros

Reproduction

Analysis started2024-05-11 07:01:59.827411
Analysis finished2024-05-11 07:02:03.639242
Duration3.81 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

2024-05-11T16:02:03.741501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:02:03.893410image/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
2024-05-11T16:02:04.224623image/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 row3230000-107-2016-00289
2nd row3230000-107-2018-00218
3rd row3230000-107-2019-00019
4th row3230000-107-2019-00697
5th row3230000-107-2023-00088
ValueCountFrequency (%)
3230000-107-2016-00289 1
 
< 0.1%
3230000-107-2020-01046 1
 
< 0.1%
3230000-107-2009-00053 1
 
< 0.1%
3230000-107-2018-00047 1
 
< 0.1%
3230000-107-2019-00544 1
 
< 0.1%
3230000-107-2018-00119 1
 
< 0.1%
3230000-107-2021-00107 1
 
< 0.1%
3230000-107-2022-00207 1
 
< 0.1%
3230000-107-2009-00090 1
 
< 0.1%
3230000-107-1988-00447 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-05-11T16:02:04.885980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 86342
39.2%
- 30000
 
13.6%
2 27366
 
12.4%
3 24191
 
11.0%
1 20249
 
9.2%
7 13414
 
6.1%
9 4729
 
2.1%
8 3711
 
1.7%
4 3468
 
1.6%
6 3292
 
1.5%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 86342
45.4%
2 27366
 
14.4%
3 24191
 
12.7%
1 20249
 
10.7%
7 13414
 
7.1%
9 4729
 
2.5%
8 3711
 
2.0%
4 3468
 
1.8%
6 3292
 
1.7%
5 3238
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 86342
39.2%
- 30000
 
13.6%
2 27366
 
12.4%
3 24191
 
11.0%
1 20249
 
9.2%
7 13414
 
6.1%
9 4729
 
2.1%
8 3711
 
1.7%
4 3468
 
1.6%
6 3292
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 86342
39.2%
- 30000
 
13.6%
2 27366
 
12.4%
3 24191
 
11.0%
1 20249
 
9.2%
7 13414
 
6.1%
9 4729
 
2.1%
8 3711
 
1.7%
4 3468
 
1.6%
6 3292
 
1.5%
Distinct4629
Distinct (%)46.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T16:02:05.359894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.2214
Min length8

Characters and Unicode

Total characters82214
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

Unique2399 ?
Unique (%)24.0%

Sample

1st row20161018
2nd row20180423
3rd row20190110
4th row20190819
5th row2023-02-27
ValueCountFrequency (%)
20010818 31
 
0.3%
20000714 18
 
0.2%
20200818 15
 
0.1%
20170605 13
 
0.1%
20200204 13
 
0.1%
20181001 13
 
0.1%
20010820 13
 
0.1%
20070822 13
 
0.1%
19991119 13
 
0.1%
20180319 11
 
0.1%
Other values (4619) 9847
98.5%
2024-05-11T16:02:06.066989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 25071
30.5%
2 19529
23.8%
1 14590
17.7%
9 4231
 
5.1%
8 3301
 
4.0%
3 3211
 
3.9%
7 2943
 
3.6%
4 2463
 
3.0%
6 2447
 
3.0%
- 2214
 
2.7%
Other values (2) 2214
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 79996
97.3%
Dash Punctuation 2214
 
2.7%
Space Separator 4
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 25071
31.3%
2 19529
24.4%
1 14590
18.2%
9 4231
 
5.3%
8 3301
 
4.1%
3 3211
 
4.0%
7 2943
 
3.7%
4 2463
 
3.1%
6 2447
 
3.1%
5 2210
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 2214
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 82214
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 25071
30.5%
2 19529
23.8%
1 14590
17.7%
9 4231
 
5.1%
8 3301
 
4.0%
3 3211
 
3.9%
7 2943
 
3.6%
4 2463
 
3.0%
6 2447
 
3.0%
- 2214
 
2.7%
Other values (2) 2214
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 82214
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 25071
30.5%
2 19529
23.8%
1 14590
17.7%
9 4231
 
5.1%
8 3301
 
4.0%
3 3211
 
3.9%
7 2943
 
3.6%
4 2463
 
3.0%
6 2447
 
3.0%
- 2214
 
2.7%
Other values (2) 2214
 
2.7%

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
8514 
1
1486 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 8514
85.1%
1 1486
 
14.9%

Length

2024-05-11T16:02:06.314632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:02:06.468987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 8514
85.1%
1 1486
 
14.9%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
8514 
영업/정상
1486 

Length

Max length5
Median length2
Mean length2.4458
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 8514
85.1%
영업/정상 1486
 
14.9%

Length

2024-05-11T16:02:06.683883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:02:06.845707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 8514
85.1%
영업/정상 1486
 
14.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
8514 
1
1486 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 8514
85.1%
1 1486
 
14.9%

Length

2024-05-11T16:02:07.032039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:02:07.186476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 8514
85.1%
1 1486
 
14.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
8514 
영업
1486 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 8514
85.1%
영업 1486
 
14.9%

Length

2024-05-11T16:02:07.373082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:02:07.531202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 8514
85.1%
영업 1486
 
14.9%

폐업일자
Date

MISSING 

Distinct3899
Distinct (%)45.8%
Missing1486
Missing (%)14.9%
Memory size156.2 KiB
Minimum1990-04-30 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T16:02:07.708922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:02:07.926370image/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 

Distinct2337
Distinct (%)66.8%
Missing6499
Missing (%)65.0%
Memory size156.2 KiB
2024-05-11T16:02:08.409369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length10.839474
Min length2

Characters and Unicode

Total characters37949
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

Unique2047 ?
Unique (%)58.5%

Sample

1st row02 5939351
2nd row02 411 3001
3rd row02 4228675
4th row064 796 9000
5th row032 672 7707
ValueCountFrequency (%)
02 2218
28.7%
031 396
 
5.1%
070 241
 
3.1%
032 122
 
1.6%
43009589 81
 
1.0%
81588727 48
 
0.6%
4358 46
 
0.6%
845 46
 
0.6%
7910 36
 
0.5%
426 35
 
0.5%
Other values (2514) 4448
57.6%
2024-05-11T16:02:09.149987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7071
18.6%
2 5514
14.5%
5297
14.0%
4 3954
10.4%
1 2964
7.8%
3 2891
7.6%
7 2375
 
6.3%
8 2164
 
5.7%
5 2090
 
5.5%
9 1840
 
4.8%
Other values (2) 1789
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 32649
86.0%
Space Separator 5297
 
14.0%
Other Punctuation 3
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7071
21.7%
2 5514
16.9%
4 3954
12.1%
1 2964
9.1%
3 2891
8.9%
7 2375
 
7.3%
8 2164
 
6.6%
5 2090
 
6.4%
9 1840
 
5.6%
6 1786
 
5.5%
Space Separator
ValueCountFrequency (%)
5297
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 37949
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7071
18.6%
2 5514
14.5%
5297
14.0%
4 3954
10.4%
1 2964
7.8%
3 2891
7.6%
7 2375
 
6.3%
8 2164
 
5.7%
5 2090
 
5.5%
9 1840
 
4.8%
Other values (2) 1789
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 37949
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7071
18.6%
2 5514
14.5%
5297
14.0%
4 3954
10.4%
1 2964
7.8%
3 2891
7.6%
7 2375
 
6.3%
8 2164
 
5.7%
5 2090
 
5.5%
9 1840
 
4.8%
Other values (2) 1789
 
4.7%

소재지면적
Text

MISSING 

Distinct1249
Distinct (%)14.5%
Missing1391
Missing (%)13.9%
Memory size156.2 KiB
2024-05-11T16:02:09.630493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length4
Mean length4.431409
Min length3

Characters and Unicode

Total characters38150
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

Unique859 ?
Unique (%)10.0%

Sample

1st row3.30
2nd row3.30
3rd row3.30
4th row.00
5th row6.50
ValueCountFrequency (%)
3.30 3238
37.6%
00 382
 
4.4%
3.00 247
 
2.9%
6.60 244
 
2.8%
33.00 228
 
2.6%
6.00 208
 
2.4%
10.00 172
 
2.0%
1,126.58 165
 
1.9%
5.00 95
 
1.1%
9.90 95
 
1.1%
Other values (1239) 3535
41.1%
2024-05-11T16:02:10.296401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10887
28.5%
. 8609
22.6%
3 8185
21.5%
1 2134
 
5.6%
2 1881
 
4.9%
6 1786
 
4.7%
5 1280
 
3.4%
4 954
 
2.5%
8 837
 
2.2%
9 820
 
2.1%
Other values (2) 777
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 29369
77.0%
Other Punctuation 8781
 
23.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10887
37.1%
3 8185
27.9%
1 2134
 
7.3%
2 1881
 
6.4%
6 1786
 
6.1%
5 1280
 
4.4%
4 954
 
3.2%
8 837
 
2.8%
9 820
 
2.8%
7 605
 
2.1%
Other Punctuation
ValueCountFrequency (%)
. 8609
98.0%
, 172
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
Common 38150
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10887
28.5%
. 8609
22.6%
3 8185
21.5%
1 2134
 
5.6%
2 1881
 
4.9%
6 1786
 
4.7%
5 1280
 
3.4%
4 954
 
2.5%
8 837
 
2.2%
9 820
 
2.1%
Other values (2) 777
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38150
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10887
28.5%
. 8609
22.6%
3 8185
21.5%
1 2134
 
5.6%
2 1881
 
4.9%
6 1786
 
4.7%
5 1280
 
3.4%
4 954
 
2.5%
8 837
 
2.2%
9 820
 
2.1%
Other values (2) 777
 
2.0%
Distinct227
Distinct (%)2.3%
Missing4
Missing (%)< 0.1%
Memory size156.2 KiB
2024-05-11T16:02:10.781963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1106443
Min length6

Characters and Unicode

Total characters61082
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

Unique31 ?
Unique (%)0.3%

Sample

1st row138829
2nd row138960
3rd row138721
4th row138721
5th row138-885
ValueCountFrequency (%)
138960 820
 
8.2%
138721 786
 
7.9%
138915 769
 
7.7%
138885 613
 
6.1%
138934 612
 
6.1%
138888 431
 
4.3%
138962 330
 
3.3%
138829 282
 
2.8%
138881 261
 
2.6%
138736 225
 
2.3%
Other values (217) 4867
48.7%
2024-05-11T16:02:11.568269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 17304
28.3%
1 13317
21.8%
3 12031
19.7%
9 3858
 
6.3%
2 2693
 
4.4%
0 2436
 
4.0%
6 2379
 
3.9%
5 2149
 
3.5%
7 1933
 
3.2%
4 1876
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59976
98.2%
Dash Punctuation 1106
 
1.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 17304
28.9%
1 13317
22.2%
3 12031
20.1%
9 3858
 
6.4%
2 2693
 
4.5%
0 2436
 
4.1%
6 2379
 
4.0%
5 2149
 
3.6%
7 1933
 
3.2%
4 1876
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 1106
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 61082
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 17304
28.3%
1 13317
21.8%
3 12031
19.7%
9 3858
 
6.3%
2 2693
 
4.4%
0 2436
 
4.0%
6 2379
 
3.9%
5 2149
 
3.5%
7 1933
 
3.2%
4 1876
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 61082
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 17304
28.3%
1 13317
21.8%
3 12031
19.7%
9 3858
 
6.3%
2 2693
 
4.4%
0 2436
 
4.0%
6 2379
 
3.9%
5 2149
 
3.5%
7 1933
 
3.2%
4 1876
 
3.1%
Distinct3730
Distinct (%)37.3%
Missing2
Missing (%)< 0.1%
Memory size156.2 KiB
2024-05-11T16:02:12.074930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length43
Mean length25.434487
Min length6

Characters and Unicode

Total characters254294
Distinct characters421
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3158 ?
Unique (%)31.6%

Sample

1st row서울특별시 송파구 방이동 89-11
2nd row서울특별시 송파구 문정동 634 가든파이브라이프
3rd row서울특별시 송파구 잠실동 40-1 롯데월드
4th row서울특별시 송파구 잠실동 40-1 롯데월드
5th row서울특별시 송파구 문정동 150-2 문정프라자
ValueCountFrequency (%)
서울특별시 9994
19.9%
송파구 9994
19.9%
문정동 2563
 
5.1%
잠실동 2410
 
4.8%
40-1 1599
 
3.2%
신천동 979
 
2.0%
가락동 945
 
1.9%
634 917
 
1.8%
롯데월드 879
 
1.8%
가든파이브라이프 842
 
1.7%
Other values (3490) 19030
37.9%
2024-05-11T16:02:12.759038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
48209
19.0%
12526
 
4.9%
10614
 
4.2%
10450
 
4.1%
10311
 
4.1%
10247
 
4.0%
10244
 
4.0%
9999
 
3.9%
9996
 
3.9%
9995
 
3.9%
Other values (411) 111703
43.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 157541
62.0%
Space Separator 48209
 
19.0%
Decimal Number 37144
 
14.6%
Dash Punctuation 6972
 
2.7%
Uppercase Letter 3448
 
1.4%
Close Punctuation 435
 
0.2%
Open Punctuation 433
 
0.2%
Other Punctuation 93
 
< 0.1%
Lowercase Letter 14
 
< 0.1%
Math Symbol 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12526
 
8.0%
10614
 
6.7%
10450
 
6.6%
10311
 
6.5%
10247
 
6.5%
10244
 
6.5%
9999
 
6.3%
9996
 
6.3%
9995
 
6.3%
2881
 
1.8%
Other values (355) 60278
38.3%
Uppercase Letter
ValueCountFrequency (%)
S 525
15.2%
G 421
12.2%
N 393
11.4%
A 384
11.1%
U 306
8.9%
T 158
 
4.6%
D 156
 
4.5%
I 156
 
4.5%
M 156
 
4.5%
O 155
 
4.5%
Other values (14) 638
18.5%
Lowercase Letter
ValueCountFrequency (%)
l 2
14.3%
s 2
14.3%
g 2
14.3%
a 1
7.1%
b 1
7.1%
r 1
7.1%
i 1
7.1%
c 1
7.1%
t 1
7.1%
n 1
7.1%
Decimal Number
ValueCountFrequency (%)
1 9602
25.9%
0 4664
12.6%
2 4639
12.5%
4 3887
10.5%
6 3492
 
9.4%
8 2956
 
8.0%
3 2565
 
6.9%
5 2056
 
5.5%
9 1648
 
4.4%
7 1635
 
4.4%
Other Punctuation
ValueCountFrequency (%)
, 65
69.9%
/ 19
 
20.4%
. 6
 
6.5%
? 1
 
1.1%
@ 1
 
1.1%
& 1
 
1.1%
Space Separator
ValueCountFrequency (%)
48209
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6972
100.0%
Close Punctuation
ValueCountFrequency (%)
) 435
100.0%
Open Punctuation
ValueCountFrequency (%)
( 433
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 157536
62.0%
Common 93291
36.7%
Latin 3462
 
1.4%
Han 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12526
 
8.0%
10614
 
6.7%
10450
 
6.6%
10311
 
6.5%
10247
 
6.5%
10244
 
6.5%
9999
 
6.3%
9996
 
6.3%
9995
 
6.3%
2881
 
1.8%
Other values (353) 60273
38.3%
Latin
ValueCountFrequency (%)
S 525
15.2%
G 421
12.2%
N 393
11.4%
A 384
11.1%
U 306
8.8%
T 158
 
4.6%
D 156
 
4.5%
I 156
 
4.5%
M 156
 
4.5%
O 155
 
4.5%
Other values (25) 652
18.8%
Common
ValueCountFrequency (%)
48209
51.7%
1 9602
 
10.3%
- 6972
 
7.5%
0 4664
 
5.0%
2 4639
 
5.0%
4 3887
 
4.2%
6 3492
 
3.7%
8 2956
 
3.2%
3 2565
 
2.7%
5 2056
 
2.2%
Other values (11) 4249
 
4.6%
Han
ValueCountFrequency (%)
4
80.0%
1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 157536
62.0%
ASCII 96753
38.0%
CJK 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
48209
49.8%
1 9602
 
9.9%
- 6972
 
7.2%
0 4664
 
4.8%
2 4639
 
4.8%
4 3887
 
4.0%
6 3492
 
3.6%
8 2956
 
3.1%
3 2565
 
2.7%
5 2056
 
2.1%
Other values (46) 7711
 
8.0%
Hangul
ValueCountFrequency (%)
12526
 
8.0%
10614
 
6.7%
10450
 
6.6%
10311
 
6.5%
10247
 
6.5%
10244
 
6.5%
9999
 
6.3%
9996
 
6.3%
9995
 
6.3%
2881
 
1.8%
Other values (353) 60273
38.3%
CJK
ValueCountFrequency (%)
4
80.0%
1
 
20.0%

도로명주소
Text

MISSING 

Distinct4434
Distinct (%)55.6%
Missing2026
Missing (%)20.3%
Memory size156.2 KiB
2024-05-11T16:02:13.428518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length76
Median length63
Mean length38.342112
Min length22

Characters and Unicode

Total characters305740
Distinct characters439
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3799 ?
Unique (%)47.6%

Sample

1st row서울특별시 송파구 양재대로 1222 (방이동, 에브리데이올림픽점)
2nd row서울특별시 송파구 충민로 66, 가든파이브라이프 1층 (문정동)
3rd row서울특별시 송파구 올림픽로 240, 롯데월드 롯데마트 잠실점 (잠실동)
4th row서울특별시 송파구 올림픽로 240, 롯데마트 잠실점 지하1층 (잠실동)
5th row서울특별시 송파구 중대로 80, 롯데마트 (문정동)
ValueCountFrequency (%)
서울특별시 7971
 
13.5%
송파구 7971
 
13.5%
지하1층 2749
 
4.7%
문정동 2163
 
3.7%
올림픽로 1975
 
3.4%
잠실동 1675
 
2.8%
1층 1498
 
2.5%
충민로 1412
 
2.4%
240 1251
 
2.1%
66 936
 
1.6%
Other values (3011) 29321
49.8%
2024-05-11T16:02:14.132129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
51192
 
16.7%
11115
 
3.6%
1 10709
 
3.5%
9467
 
3.1%
, 9207
 
3.0%
8927
 
2.9%
8588
 
2.8%
8365
 
2.7%
8235
 
2.7%
) 8202
 
2.7%
Other values (429) 171733
56.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 189999
62.1%
Space Separator 51192
 
16.7%
Decimal Number 35544
 
11.6%
Other Punctuation 9225
 
3.0%
Close Punctuation 8202
 
2.7%
Open Punctuation 8201
 
2.7%
Uppercase Letter 2260
 
0.7%
Dash Punctuation 614
 
0.2%
Math Symbol 264
 
0.1%
Lowercase Letter 239
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
11115
 
5.9%
9467
 
5.0%
8927
 
4.7%
8588
 
4.5%
8365
 
4.4%
8235
 
4.3%
8043
 
4.2%
7973
 
4.2%
7972
 
4.2%
7972
 
4.2%
Other values (372) 103342
54.4%
Uppercase Letter
ValueCountFrequency (%)
B 336
14.9%
N 297
13.1%
A 269
11.9%
S 243
10.8%
H 238
10.5%
G 221
9.8%
C 186
8.2%
U 78
 
3.5%
F 58
 
2.6%
D 50
 
2.2%
Other values (13) 284
12.6%
Lowercase Letter
ValueCountFrequency (%)
c 32
13.4%
s 30
12.6%
g 30
12.6%
n 30
12.6%
h 23
9.6%
r 22
9.2%
t 20
8.4%
a 20
8.4%
m 19
7.9%
e 6
 
2.5%
Other values (3) 7
 
2.9%
Decimal Number
ValueCountFrequency (%)
1 10709
30.1%
2 5523
15.5%
0 4154
 
11.7%
6 3516
 
9.9%
4 3213
 
9.0%
3 3184
 
9.0%
8 1768
 
5.0%
5 1686
 
4.7%
9 978
 
2.8%
7 813
 
2.3%
Other Punctuation
ValueCountFrequency (%)
, 9207
99.8%
/ 12
 
0.1%
. 3
 
< 0.1%
? 1
 
< 0.1%
' 1
 
< 0.1%
& 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
51192
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8202
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8201
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 614
100.0%
Math Symbol
ValueCountFrequency (%)
~ 264
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 189994
62.1%
Common 113242
37.0%
Latin 2499
 
0.8%
Han 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
11115
 
5.9%
9467
 
5.0%
8927
 
4.7%
8588
 
4.5%
8365
 
4.4%
8235
 
4.3%
8043
 
4.2%
7973
 
4.2%
7972
 
4.2%
7972
 
4.2%
Other values (370) 103337
54.4%
Latin
ValueCountFrequency (%)
B 336
13.4%
N 297
11.9%
A 269
10.8%
S 243
9.7%
H 238
9.5%
G 221
8.8%
C 186
 
7.4%
U 78
 
3.1%
F 58
 
2.3%
D 50
 
2.0%
Other values (26) 523
20.9%
Common
ValueCountFrequency (%)
51192
45.2%
1 10709
 
9.5%
, 9207
 
8.1%
) 8202
 
7.2%
( 8201
 
7.2%
2 5523
 
4.9%
0 4154
 
3.7%
6 3516
 
3.1%
4 3213
 
2.8%
3 3184
 
2.8%
Other values (11) 6141
 
5.4%
Han
ValueCountFrequency (%)
4
80.0%
1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 189989
62.1%
ASCII 115741
37.9%
CJK 5
 
< 0.1%
Compat Jamo 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
51192
44.2%
1 10709
 
9.3%
, 9207
 
8.0%
) 8202
 
7.1%
( 8201
 
7.1%
2 5523
 
4.8%
0 4154
 
3.6%
6 3516
 
3.0%
4 3213
 
2.8%
3 3184
 
2.8%
Other values (47) 8640
 
7.5%
Hangul
ValueCountFrequency (%)
11115
 
5.9%
9467
 
5.0%
8927
 
4.7%
8588
 
4.5%
8365
 
4.4%
8235
 
4.3%
8043
 
4.2%
7973
 
4.2%
7972
 
4.2%
7972
 
4.2%
Other values (367) 103332
54.4%
CJK
ValueCountFrequency (%)
4
80.0%
1
 
20.0%
Compat Jamo
ValueCountFrequency (%)
3
60.0%
1
 
20.0%
1
 
20.0%

도로명우편번호
Real number (ℝ)

MISSING  SKEWED 

Distinct308
Distinct (%)3.9%
Missing2048
Missing (%)20.5%
Infinite0
Infinite (%)0.0%
Mean5675.9028
Minimum5501
Maximum25348
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T16:02:14.345359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5501
5-th percentile5505
Q15554
median5652
Q35833
95-th percentile5840
Maximum25348
Range19847
Interquartile range (IQR)279

Descriptive statistics

Standard deviation271.24218
Coefficient of variation (CV)0.047788377
Kurtosis3535.6613
Mean5675.9028
Median Absolute Deviation (MAD)101
Skewness50.514965
Sum45134779
Variance73572.321
MonotonicityNot monotonic
2024-05-11T16:02:14.551481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5554 1254
 
12.5%
5838 935
 
9.3%
5840 467
 
4.7%
5833 385
 
3.9%
5510 367
 
3.7%
5505 287
 
2.9%
5551 276
 
2.8%
5614 267
 
2.7%
5699 239
 
2.4%
5648 228
 
2.3%
Other values (298) 3247
32.5%
(Missing) 2048
20.5%
ValueCountFrequency (%)
5501 160
1.6%
5502 42
 
0.4%
5503 77
 
0.8%
5504 50
 
0.5%
5505 287
2.9%
5507 99
 
1.0%
5508 3
 
< 0.1%
5509 4
 
< 0.1%
5510 367
3.7%
5511 1
 
< 0.1%
ValueCountFrequency (%)
25348 1
 
< 0.1%
12217 1
 
< 0.1%
10595 1
 
< 0.1%
5855 99
1.0%
5854 28
 
0.3%
5852 59
0.6%
5850 1
 
< 0.1%
5849 52
0.5%
5846 2
 
< 0.1%
5841 12
 
0.1%
Distinct5412
Distinct (%)54.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T16:02:14.896716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length27
Mean length6.5906
Min length1

Characters and Unicode

Total characters65906
Distinct characters923
Distinct categories13 ?
Distinct scripts5 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4498 ?
Unique (%)45.0%

Sample

1st row행복생활건강
2nd row주식회사 에벤에셀
3rd row선우어묵
4th row다봉상사
5th row주식회사 씨스코컴퍼니
ValueCountFrequency (%)
주식회사 656
 
5.3%
명류당티에프 114
 
0.9%
더프리미엄 109
 
0.9%
한가람 88
 
0.7%
주)햇살드림 87
 
0.7%
엠엔에이치(m&h 86
 
0.7%
주)참살이유통 80
 
0.6%
씨스코컴퍼니 67
 
0.5%
월드푸드 65
 
0.5%
주)행복생활건강 64
 
0.5%
Other values (5895) 10933
88.5%
2024-05-11T16:02:15.431370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3223
 
4.9%
) 2834
 
4.3%
( 2787
 
4.2%
2369
 
3.6%
1496
 
2.3%
1355
 
2.1%
1225
 
1.9%
1168
 
1.8%
1111
 
1.7%
967
 
1.5%
Other values (913) 47371
71.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 55292
83.9%
Close Punctuation 2836
 
4.3%
Open Punctuation 2789
 
4.2%
Space Separator 2369
 
3.6%
Lowercase Letter 1107
 
1.7%
Uppercase Letter 1070
 
1.6%
Other Punctuation 272
 
0.4%
Decimal Number 159
 
0.2%
Dash Punctuation 8
 
< 0.1%
Modifier Symbol 1
 
< 0.1%
Other values (3) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3223
 
5.8%
1496
 
2.7%
1355
 
2.5%
1225
 
2.2%
1168
 
2.1%
1111
 
2.0%
967
 
1.7%
967
 
1.7%
889
 
1.6%
861
 
1.6%
Other values (829) 42030
76.0%
Lowercase Letter
ValueCountFrequency (%)
e 157
14.2%
a 103
 
9.3%
o 96
 
8.7%
m 78
 
7.0%
h 76
 
6.9%
i 63
 
5.7%
n 62
 
5.6%
t 57
 
5.1%
s 55
 
5.0%
l 52
 
4.7%
Other values (16) 308
27.8%
Uppercase Letter
ValueCountFrequency (%)
M 107
 
10.0%
H 105
 
9.8%
A 76
 
7.1%
F 73
 
6.8%
E 71
 
6.6%
C 69
 
6.4%
S 67
 
6.3%
B 66
 
6.2%
O 57
 
5.3%
K 40
 
3.7%
Other values (15) 339
31.7%
Other Punctuation
ValueCountFrequency (%)
& 173
63.6%
. 42
 
15.4%
, 27
 
9.9%
? 11
 
4.0%
/ 6
 
2.2%
: 4
 
1.5%
' 4
 
1.5%
! 2
 
0.7%
; 1
 
0.4%
* 1
 
0.4%
Decimal Number
ValueCountFrequency (%)
1 37
23.3%
2 28
17.6%
3 20
12.6%
9 19
11.9%
5 18
11.3%
0 14
 
8.8%
4 9
 
5.7%
8 5
 
3.1%
6 5
 
3.1%
7 4
 
2.5%
Close Punctuation
ValueCountFrequency (%)
) 2834
99.9%
] 1
 
< 0.1%
1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 2787
99.9%
[ 1
 
< 0.1%
1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
2369
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 55281
83.9%
Common 8436
 
12.8%
Latin 2177
 
3.3%
Han 11
 
< 0.1%
Greek 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3223
 
5.8%
1496
 
2.7%
1355
 
2.5%
1225
 
2.2%
1168
 
2.1%
1111
 
2.0%
967
 
1.7%
967
 
1.7%
889
 
1.6%
861
 
1.6%
Other values (820) 42019
76.0%
Latin
ValueCountFrequency (%)
e 157
 
7.2%
M 107
 
4.9%
H 105
 
4.8%
a 103
 
4.7%
o 96
 
4.4%
m 78
 
3.6%
A 76
 
3.5%
h 76
 
3.5%
F 73
 
3.4%
E 71
 
3.3%
Other values (41) 1235
56.7%
Common
ValueCountFrequency (%)
) 2834
33.6%
( 2787
33.0%
2369
28.1%
& 173
 
2.1%
. 42
 
0.5%
1 37
 
0.4%
2 28
 
0.3%
, 27
 
0.3%
3 20
 
0.2%
9 19
 
0.2%
Other values (22) 100
 
1.2%
Han
ValueCountFrequency (%)
3
27.3%
1
 
9.1%
1
 
9.1%
1
 
9.1%
1
 
9.1%
1
 
9.1%
1
 
9.1%
1
 
9.1%
1
 
9.1%
Greek
ValueCountFrequency (%)
Χ 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 55277
83.9%
ASCII 10609
 
16.1%
CJK 10
 
< 0.1%
Compat Jamo 4
 
< 0.1%
None 4
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
3223
 
5.8%
1496
 
2.7%
1355
 
2.5%
1225
 
2.2%
1168
 
2.1%
1111
 
2.0%
967
 
1.7%
967
 
1.7%
889
 
1.6%
861
 
1.6%
Other values (817) 42015
76.0%
ASCII
ValueCountFrequency (%)
) 2834
26.7%
( 2787
26.3%
2369
22.3%
& 173
 
1.6%
e 157
 
1.5%
M 107
 
1.0%
H 105
 
1.0%
a 103
 
1.0%
o 96
 
0.9%
m 78
 
0.7%
Other values (69) 1800
17.0%
CJK
ValueCountFrequency (%)
3
30.0%
1
 
10.0%
1
 
10.0%
1
 
10.0%
1
 
10.0%
1
 
10.0%
1
 
10.0%
1
 
10.0%
Compat Jamo
ValueCountFrequency (%)
2
50.0%
1
25.0%
1
25.0%
None
ValueCountFrequency (%)
1
25.0%
1
25.0%
Χ 1
25.0%
1
25.0%
CJK Compat Ideographs
ValueCountFrequency (%)
1
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%
Distinct6646
Distinct (%)66.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1999-01-05 00:00:00
Maximum2024-05-09 14:01:02
2024-05-11T16:02:15.630848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:02:15.872863image/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
5288 
U
4712 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 5288
52.9%
U 4712
47.1%

Length

2024-05-11T16:02:16.126710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:02:16.252072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 5288
52.9%
u 4712
47.1%
Distinct1789
Distinct (%)17.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T16:02:16.404208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:02:16.567044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
즉석판매제조가공업
9976 
기타
 
24

Length

Max length9
Median length9
Mean length8.9832
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
즉석판매제조가공업 9976
99.8%
기타 24
 
0.2%

Length

2024-05-11T16:02:16.741728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:02:16.873683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
즉석판매제조가공업 9976
99.8%
기타 24
 
0.2%

좌표정보(X)
Real number (ℝ)

MISSING  SKEWED 

Distinct1736
Distinct (%)17.8%
Missing255
Missing (%)2.5%
Infinite0
Infinite (%)0.0%
Mean209918.99
Minimum190950
Maximum349854.42
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T16:02:17.024131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum190950
5-th percentile207564.04
Q1208589.36
median209908.01
Q3210986.46
95-th percentile212573
Maximum349854.42
Range158904.42
Interquartile range (IQR)2397.0974

Descriptive statistics

Standard deviation2009.6736
Coefficient of variation (CV)0.0095735675
Kurtosis2412.5519
Mean209918.99
Median Absolute Deviation (MAD)1078.4483
Skewness34.666571
Sum2.0456606 × 109
Variance4038788.1
MonotonicityNot monotonic
2024-05-11T16:02:17.185049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
208589.363343145 1596
 
16.0%
210986.460698452 918
 
9.2%
210343.699256005 613
 
6.1%
210480.282018702 454
 
4.5%
209039.148023482 337
 
3.4%
209607.590372037 289
 
2.9%
209790.959909032 286
 
2.9%
209074.900840074 276
 
2.8%
211619.368009793 263
 
2.6%
208865.513376106 260
 
2.6%
Other values (1726) 4453
44.5%
(Missing) 255
 
2.5%
ValueCountFrequency (%)
190950.0 1
 
< 0.1%
206383.829438022 2
 
< 0.1%
206397.34797252 19
0.2%
206487.800145227 1
 
< 0.1%
206531.147433206 1
 
< 0.1%
206726.499021996 7
 
0.1%
206731.192156063 2
 
< 0.1%
206869.238000307 1
 
< 0.1%
206900.84547168 1
 
< 0.1%
206932.357872339 4
 
< 0.1%
ValueCountFrequency (%)
349854.419682047 1
< 0.1%
220661.109741495 1
< 0.1%
213999.956783491 1
< 0.1%
213873.895223193 2
< 0.1%
213873.675372176 1
< 0.1%
213862.955350277 1
< 0.1%
213843.762365507 1
< 0.1%
213842.444758266 1
< 0.1%
213792.427290891 1
< 0.1%
213791.304800814 1
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1736
Distinct (%)17.8%
Missing255
Missing (%)2.5%
Infinite0
Infinite (%)0.0%
Mean444449.6
Minimum441406.98
Maximum463575.63
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T16:02:17.354043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum441406.98
5-th percentile441725.29
Q1443288.28
median444905.13
Q3445455.9
95-th percentile446588.74
Maximum463575.63
Range22168.644
Interquartile range (IQR)2167.6191

Descriptive statistics

Standard deviation1616.6035
Coefficient of variation (CV)0.0036373156
Kurtosis3.3590267
Mean444449.6
Median Absolute Deviation (MAD)964.83568
Skewness0.084899452
Sum4.3311613 × 109
Variance2613406.7
MonotonicityNot monotonic
2024-05-11T16:02:17.505237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
445455.90405262 1596
 
16.0%
441725.293491662 918
 
9.2%
443288.284974717 613
 
6.1%
441833.16323518 454
 
4.5%
446007.966801057 337
 
3.4%
447120.577229325 289
 
2.9%
443481.212174317 286
 
2.9%
445657.80932984 276
 
2.8%
445963.384875409 263
 
2.6%
444574.099815107 260
 
2.6%
Other values (1726) 4453
44.5%
(Missing) 255
 
2.5%
ValueCountFrequency (%)
441406.981434166 2
 
< 0.1%
441411.906445707 1
 
< 0.1%
441412.0 8
 
0.1%
441426.0 6
 
0.1%
441586.029967716 2
 
< 0.1%
441590.062253247 8
 
0.1%
441602.0 20
0.2%
441632.0 12
0.1%
441680.580139573 11
0.1%
441703.846676865 2
 
< 0.1%
ValueCountFrequency (%)
463575.625064377 1
< 0.1%
460897.765414263 1
< 0.1%
460718.0 1
< 0.1%
448596.610120879 1
< 0.1%
448571.39753402 1
< 0.1%
448439.202290106 1
< 0.1%
448437.083161462 1
< 0.1%
448435.73123223 1
< 0.1%
448427.153396127 1
< 0.1%
448417.803499032 2
< 0.1%

위생업태명
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
즉석판매제조가공업
8226 
<NA>
1750 
기타
 
24

Length

Max length9
Median length9
Mean length8.1082
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
즉석판매제조가공업 8226
82.3%
<NA> 1750
 
17.5%
기타 24
 
0.2%

Length

2024-05-11T16:02:17.656973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:02:17.784828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
즉석판매제조가공업 8226
82.3%
na 1750
 
17.5%
기타 24
 
0.2%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8786 
0
1021 
1
 
193

Length

Max length4
Median length4
Mean length3.6358
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> 8786
87.9%
0 1021
 
10.2%
1 193
 
1.9%

Length

2024-05-11T16:02:17.907594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:02:18.034765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8786
87.9%
0 1021
 
10.2%
1 193
 
1.9%

여성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8783 
0
1060 
1
 
156
2
 
1

Length

Max length4
Median length4
Mean length3.6349
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> 8783
87.8%
0 1060
 
10.6%
1 156
 
1.6%
2 1
 
< 0.1%

Length

2024-05-11T16:02:18.187017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:02:18.353243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8783
87.8%
0 1060
 
10.6%
1 156
 
1.6%
2 1
 
< 0.1%

영업장주변구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8979 
기타
 
602
주택가주변
 
393
아파트지역
 
24
유흥업소밀집지역
 
2

Length

Max length8
Median length4
Mean length3.9221
Min length2

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> 8979
89.8%
기타 602
 
6.0%
주택가주변 393
 
3.9%
아파트지역 24
 
0.2%
유흥업소밀집지역 2
 
< 0.1%

Length

2024-05-11T16:02:18.508727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:02:18.640346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8979
89.8%
기타 602
 
6.0%
주택가주변 393
 
3.9%
아파트지역 24
 
0.2%
유흥업소밀집지역 2
 
< 0.1%

등급구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8979 
기타
 
625
우수
 
196
자율
 
131
 
68

Length

Max length4
Median length4
Mean length3.789
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> 8979
89.8%
기타 625
 
6.2%
우수 196
 
2.0%
자율 131
 
1.3%
68
 
0.7%
관리 1
 
< 0.1%

Length

2024-05-11T16:02:18.778085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:02:18.936253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8979
89.8%
기타 625
 
6.2%
우수 196
 
2.0%
자율 131
 
1.3%
68
 
0.7%
관리 1
 
< 0.1%

급수시설구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9193 
상수도전용
 
805
상수도(음용)지하수(주방용)겸용
 
1
간이상수도
 
1

Length

Max length17
Median length4
Mean length4.0819
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9193
91.9%
상수도전용 805
 
8.1%
상수도(음용)지하수(주방용)겸용 1
 
< 0.1%
간이상수도 1
 
< 0.1%

Length

2024-05-11T16:02:19.100580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:02:19.234052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9193
91.9%
상수도전용 805
 
8.1%
상수도(음용)지하수(주방용)겸용 1
 
< 0.1%
간이상수도 1
 
< 0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9407 
0
 
593

Length

Max length4
Median length4
Mean length3.8221
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> 9407
94.1%
0 593
 
5.9%

Length

2024-05-11T16:02:19.394610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:02:19.513176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9407
94.1%
0 593
 
5.9%

본사종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)0.4%
Missing7834
Missing (%)78.3%
Infinite0
Infinite (%)0.0%
Mean0.048014774
Minimum0
Maximum15
Zeros2134
Zeros (%)21.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T16:02:19.605013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum15
Range15
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.55422228
Coefficient of variation (CV)11.542745
Kurtosis426.40552
Mean0.048014774
Median Absolute Deviation (MAD)0
Skewness18.80927
Sum104
Variance0.30716234
MonotonicityNot monotonic
2024-05-11T16:02:19.739126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 2134
 
21.3%
2 19
 
0.2%
1 4
 
< 0.1%
3 3
 
< 0.1%
8 2
 
< 0.1%
13 1
 
< 0.1%
15 1
 
< 0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%
(Missing) 7834
78.3%
ValueCountFrequency (%)
0 2134
21.3%
1 4
 
< 0.1%
2 19
 
0.2%
3 3
 
< 0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%
8 2
 
< 0.1%
13 1
 
< 0.1%
15 1
 
< 0.1%
ValueCountFrequency (%)
15 1
 
< 0.1%
13 1
 
< 0.1%
8 2
 
< 0.1%
5 1
 
< 0.1%
4 1
 
< 0.1%
3 3
 
< 0.1%
2 19
 
0.2%
1 4
 
< 0.1%
0 2134
21.3%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7864 
0
2135 
3
 
1

Length

Max length4
Median length4
Mean length3.3592
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> 7864
78.6%
0 2135
 
21.3%
3 1
 
< 0.1%

Length

2024-05-11T16:02:19.899306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:02:20.041116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7864
78.6%
0 2135
 
21.3%
3 1
 
< 0.1%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7859 
0
2134 
1
 
5
2
 
1
7
 
1

Length

Max length4
Median length4
Mean length3.3577
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7859
78.6%
0 2134
 
21.3%
1 5
 
0.1%
2 1
 
< 0.1%
7 1
 
< 0.1%

Length

2024-05-11T16:02:20.191570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:02:20.332100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7859
78.6%
0 2134
 
21.3%
1 5
 
< 0.1%
2 1
 
< 0.1%
7 1
 
< 0.1%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7864 
0
2135 
1
 
1

Length

Max length4
Median length4
Mean length3.3592
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> 7864
78.6%
0 2135
 
21.3%
1 1
 
< 0.1%

Length

2024-05-11T16:02:20.513194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:02:20.663432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7864
78.6%
0 2135
 
21.3%
1 1
 
< 0.1%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
임대
3827 
<NA>
3470 
자가
2703 

Length

Max length4
Median length2
Mean length2.694
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
임대 3827
38.3%
<NA> 3470
34.7%
자가 2703
27.0%

Length

2024-05-11T16:02:20.839397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:02:21.001570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
임대 3827
38.3%
na 3470
34.7%
자가 2703
27.0%

보증액
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8635 
0
1362 
30000000
 
1
5000000
 
1
10000000
 
1

Length

Max length8
Median length4
Mean length3.5925
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8635
86.4%
0 1362
 
13.6%
30000000 1
 
< 0.1%
5000000 1
 
< 0.1%
10000000 1
 
< 0.1%

Length

2024-05-11T16:02:21.163716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:02:21.613948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8635
86.4%
0 1362
 
13.6%
30000000 1
 
< 0.1%
5000000 1
 
< 0.1%
10000000 1
 
< 0.1%

월세액
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8635 
0
1362 
1400000
 
1
600000
 
1
400000
 
1

Length

Max length7
Median length4
Mean length3.5921
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8635
86.4%
0 1362
 
13.6%
1400000 1
 
< 0.1%
600000 1
 
< 0.1%
400000 1
 
< 0.1%

Length

2024-05-11T16:02:21.752535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:02:21.878521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8635
86.4%
0 1362
 
13.6%
1400000 1
 
< 0.1%
600000 1
 
< 0.1%
400000 1
 
< 0.1%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1750
Missing (%)17.5%
Memory size97.7 KiB
False
8249 
True
 
1
(Missing)
1750 
ValueCountFrequency (%)
False 8249
82.5%
True 1
 
< 0.1%
(Missing) 1750
 
17.5%
2024-05-11T16:02:21.974709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct11
Distinct (%)0.1%
Missing1750
Missing (%)17.5%
Infinite0
Infinite (%)0.0%
Mean0.027940606
Minimum0
Maximum59.4
Zeros8238
Zeros (%)82.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T16:02:22.081589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum59.4
Range59.4
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.95504822
Coefficient of variation (CV)34.181371
Kurtosis2226.266
Mean0.027940606
Median Absolute Deviation (MAD)0
Skewness43.705379
Sum230.51
Variance0.91211709
MonotonicityNot monotonic
2024-05-11T16:02:22.188617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0.0 8238
82.4%
3.3 2
 
< 0.1%
30.0 2
 
< 0.1%
22.0 1
 
< 0.1%
6.0 1
 
< 0.1%
25.92 1
 
< 0.1%
12.59 1
 
< 0.1%
59.4 1
 
< 0.1%
10.0 1
 
< 0.1%
27.0 1
 
< 0.1%
(Missing) 1750
 
17.5%
ValueCountFrequency (%)
0.0 8238
82.4%
1.0 1
 
< 0.1%
3.3 2
 
< 0.1%
6.0 1
 
< 0.1%
10.0 1
 
< 0.1%
12.59 1
 
< 0.1%
22.0 1
 
< 0.1%
25.92 1
 
< 0.1%
27.0 1
 
< 0.1%
30.0 2
 
< 0.1%
ValueCountFrequency (%)
59.4 1
< 0.1%
30.0 2
< 0.1%
27.0 1
< 0.1%
25.92 1
< 0.1%
22.0 1
< 0.1%
12.59 1
< 0.1%
10.0 1
< 0.1%
6.0 1
< 0.1%
3.3 2
< 0.1%
1.0 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

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
388332300003230000-107-2016-0028920161018<NA>3폐업2폐업20161118<NA><NA><NA><NA>3.30138829서울특별시 송파구 방이동 89-11서울특별시 송파구 양재대로 1222 (방이동, 에브리데이올림픽점)5648행복생활건강2016-11-19 04:15:27I2018-08-31 23:59:59.0즉석판매제조가공업211619.36801445963.384875즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA>
487232300003230000-107-2018-0021820180423<NA>3폐업2폐업20180508<NA><NA><NA><NA>3.30138960서울특별시 송파구 문정동 634 가든파이브라이프서울특별시 송파구 충민로 66, 가든파이브라이프 1층 (문정동)5838주식회사 에벤에셀2018-05-09 04:16:07I2018-08-31 23:59:59.0즉석판매제조가공업210986.460698441725.293492즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA>
558632300003230000-107-2019-0001920190110<NA>3폐업2폐업20190212<NA><NA><NA><NA>3.30138721서울특별시 송파구 잠실동 40-1 롯데월드서울특별시 송파구 올림픽로 240, 롯데월드 롯데마트 잠실점 (잠실동)5554선우어묵2019-02-13 04:15:09U2019-02-15 02:40:00.0즉석판매제조가공업208589.363343445455.904053즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>임대<NA><NA>N0.0<NA><NA><NA>
626432300003230000-107-2019-0069720190819<NA>3폐업2폐업20190921<NA><NA><NA><NA>.00138721서울특별시 송파구 잠실동 40-1 롯데월드서울특별시 송파구 올림픽로 240, 롯데마트 잠실점 지하1층 (잠실동)5554다봉상사2019-09-22 04:15:09U2019-09-24 02:40:00.0즉석판매제조가공업208589.363343445455.904053즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>임대<NA><NA>N0.0<NA><NA><NA>
938132300003230000-107-2023-000882023-02-27<NA>3폐업2폐업2023-03-31<NA><NA><NA><NA><NA>138-885서울특별시 송파구 문정동 150-2 문정프라자서울특별시 송파구 중대로 80, 롯데마트 (문정동)5833주식회사 씨스코컴퍼니2023-04-01 04:15:10U2022-12-04 00:03:00.0즉석판매제조가공업210343.699256443288.284975<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
436832300003230000-107-2017-0036320170728<NA>1영업/정상1영업<NA><NA><NA><NA><NA>6.50138881서울특별시 송파구 가락동 600서울특별시 송파구 양재대로 932, 판매동 1층 041-1호 (가락동, 가락몰 수산부류)5699강남 홍어2017-07-28 10:32:50I2018-08-31 23:59:59.0즉석판매제조가공업209790.959909443481.212174즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA>
485532300003230000-107-2018-0020120180417<NA>3폐업2폐업20180502<NA><NA><NA><NA>3.30138885서울특별시 송파구 문정동 150-2 문정프라자서울특별시 송파구 중대로 80, 롯데마트 송파점 지하2층 (문정동)5833(주)신풍특산2018-05-03 04:16:02I2018-08-31 23:59:59.0즉석판매제조가공업210343.699256443288.284975즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA>
89432300003230000-107-2001-0300620010618<NA>3폐업2폐업20010823<NA><NA><NA>02 59393516.60138915서울특별시 송파구 잠실동 40-1 (롯데백화점지하1층)<NA><NA>(주)히코코2001-08-23 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업208589.363343445455.904053즉석판매제조가공업<NA><NA>기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
403432300003230000-107-2017-0002820170123<NA>3폐업2폐업20170222<NA><NA><NA><NA>3.30138915서울특별시 송파구 잠실동 40-1서울특별시 송파구 올림픽로 240, 지하1층 (잠실동, 롯데마트 잠실점)5554신풍특산2017-02-23 04:15:33I2018-08-31 23:59:59.0즉석판매제조가공업208589.363343445455.904053즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA>
275632300003230000-107-2010-0019520100916<NA>3폐업2폐업20101008<NA><NA><NA><NA>3.00138240서울특별시 송파구 신천동 20-6 GS잠실파크리온점<NA><NA>황태세상2010-09-16 09:45:34I2018-08-31 23:59:59.0즉석판매제조가공업209933.823276446455.526716즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
749232300003230000-107-2020-0085320201029<NA>3폐업2폐업20221212<NA><NA><NA><NA>160.90138862서울특별시 송파구 잠실동 207-3서울특별시 송파구 백제고분로15길 44, 지하1층 (잠실동)5559라이스푸드설화2022-12-12 16:02:24U2021-11-01 23:04:00.0즉석판매제조가공업207431.905944445237.060567<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
98532300003230000-107-2001-0320620010921<NA>3폐업2폐업20020603<NA><NA><NA>024.90138885서울특별시 송파구 문정동 150-0 (LG수퍼마켓훼미리점)<NA><NA>평화식품2002-06-03 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업210045.748264442930.687285즉석판매제조가공업<NA><NA>기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
325732300003230000-107-2013-0003020130319<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.74138881서울특별시 송파구 가락동 600 가락시장 수산물시장동 지상1층 688호서울특별시 송파구 양재대로 932, 지상1층 688호 (가락동, 가락시장 수산물시장동)5699유한회사 하늘지에스2013-03-19 10:18:35I2018-08-31 23:59:59.0즉석판매제조가공업209790.959909443481.212174즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
635632300003230000-107-2019-0078920190927<NA>3폐업2폐업20191011<NA><NA><NA><NA>3.30138721서울특별시 송파구 잠실동 40-1 롯데월드서울특별시 송파구 올림픽로 240, 롯데백화점 잠실점 지하1층 (잠실동)5554에프앤푸드2019-10-12 04:15:10U2019-10-15 02:40:00.0즉석판매제조가공업208589.363343445455.904053즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>임대<NA><NA>N0.0<NA><NA><NA>
272732300003230000-107-2010-0016620100726<NA>3폐업2폐업20100802<NA><NA><NA>02 346880003.30138934서울특별시 송파구 신천동 7-12 홈플러스잠실점<NA><NA>우리찬2010-07-26 16:03:47I2018-08-31 23:59:59.0즉석판매제조가공업209039.148023446007.966801즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>임대<NA><NA>N0.0<NA><NA><NA>
532132300003230000-107-2018-0066720181002<NA>3폐업2폐업20181110<NA><NA><NA>070 430095863.30138721서울특별시 송파구 잠실동 40-1 롯데월드서울특별시 송파구 올림픽로 240, 롯데마트 잠실점 (잠실동)5554명륜당티에프2018-11-11 04:15:09U2018-11-13 02:35:58.0즉석판매제조가공업208589.363343445455.904053즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>임대<NA><NA>N0.0<NA><NA><NA>
544932300003230000-107-2018-0079520181121<NA>3폐업2폐업20181129<NA><NA><NA>042 936 30403.30138721서울특별시 송파구 잠실동 40-1 롯데월드서울특별시 송파구 올림픽로 240, 롯데백화점 잠실점 지하1층 (잠실동)5554주)미림푸드2018-11-30 04:15:09U2018-12-02 02:40:00.0즉석판매제조가공업208589.363343445455.904053즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>임대<NA><NA>N0.0<NA><NA><NA>
999732300003230000-107-2024-001662024-04-24<NA>3폐업2폐업2024-05-01<NA><NA><NA><NA><NA>138-829서울특별시 송파구 방이동 89-11 올림픽프라자서울특별시 송파구 양재대로 1222, 올림픽프라자 이마트에브리데이 올림픽점 1층 (방이동)5648더원씨푸드 주식회사2024-05-02 04:15:05U2023-12-05 00:04:00.0즉석판매제조가공업211619.36801445963.384875<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
402432300003230000-107-2017-0001820170111<NA>3폐업2폐업20170214<NA><NA><NA><NA>3.30138885서울특별시 송파구 문정동 150-2서울특별시 송파구 중대로 80, 2층 (문정동, 롯데마트 송파점)5833(주)경주식품케이제이푸드2017-02-15 04:15:31I2018-08-31 23:59:59.0즉석판매제조가공업210343.699256443288.284975즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA>
108232300003230000-107-2002-0343220020329<NA>3폐업2폐업20020508<NA><NA><NA>02 67143016.00138885서울특별시 송파구 문정동 150-2 (LG마트지하1층)<NA><NA>경주전통식품2002-05-08 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업210343.699256443288.284975즉석판매제조가공업<NA><NA>기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>