Overview

Dataset statistics

Number of variables44
Number of observations10000
Missing cells106261
Missing cells (%)24.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 MiB
Average record size in memory384.0 B

Variable types

Categorical19
Text7
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
Author종로구
URLhttps://data.seoul.go.kr/dataList/OA-18652/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
영업장주변구분명 is highly imbalanced (50.7%)Imbalance
총인원 is highly imbalanced (79.5%)Imbalance
본사종업원수 is highly imbalanced (79.5%)Imbalance
공장사무직종업원수 is highly imbalanced (79.5%)Imbalance
공장판매직종업원수 is highly imbalanced (79.5%)Imbalance
공장생산직종업원수 is highly imbalanced (79.5%)Imbalance
보증액 is highly imbalanced (79.5%)Imbalance
월세액 is highly imbalanced (79.5%)Imbalance
다중이용업소여부 is highly imbalanced (90.3%)Imbalance
전통업소지정번호 is highly imbalanced (99.9%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 3475 (34.8%) 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 3531 (35.3%) missing valuesMissing
소재지면적 has 6694 (66.9%) missing valuesMissing
도로명주소 has 4478 (44.8%) missing valuesMissing
도로명우편번호 has 4616 (46.2%) missing valuesMissing
좌표정보(X) has 798 (8.0%) missing valuesMissing
좌표정보(Y) has 798 (8.0%) missing valuesMissing
남성종사자수 has 4211 (42.1%) missing valuesMissing
여성종사자수 has 4180 (41.8%) missing valuesMissing
건물소유구분명 has 10000 (100.0%) missing valuesMissing
다중이용업소여부 has 1733 (17.3%) missing valuesMissing
시설총규모 has 1733 (17.3%) missing valuesMissing
전통업소주된음식 has 10000 (100.0%) missing valuesMissing
홈페이지 has 10000 (100.0%) missing valuesMissing
시설총규모 is highly skewed (γ1 = 79.71245087)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 3704 (37.0%) zerosZeros
여성종사자수 has 3327 (33.3%) zerosZeros
시설총규모 has 118 (1.2%) zerosZeros

Reproduction

Analysis started2024-05-11 08:08:13.019693
Analysis finished2024-05-11 08:08:15.028738
Duration2.01 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
3000000
10000 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3000000
2nd row3000000
3rd row3000000
4th row3000000
5th row3000000

Common Values

ValueCountFrequency (%)
3000000 10000
100.0%

Length

2024-05-11T17:08:15.092324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:08:15.208199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3000000 10000
100.0%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T17:08:15.371868image/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 row3000000-101-1996-11227
2nd row3000000-101-2000-11382
3rd row3000000-101-1997-02842
4th row3000000-101-2013-00263
5th row3000000-101-1988-06743
ValueCountFrequency (%)
3000000-101-1996-11227 1
 
< 0.1%
3000000-101-1995-05128 1
 
< 0.1%
3000000-101-1993-00195 1
 
< 0.1%
3000000-101-2016-00251 1
 
< 0.1%
3000000-101-2023-00326 1
 
< 0.1%
3000000-101-1982-04142 1
 
< 0.1%
3000000-101-1986-03067 1
 
< 0.1%
3000000-101-1999-00060 1
 
< 0.1%
3000000-101-1996-05372 1
 
< 0.1%
3000000-101-2023-00029 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-05-11T17:08:15.869775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 96743
44.0%
1 33527
 
15.2%
- 30000
 
13.6%
3 15204
 
6.9%
2 11872
 
5.4%
9 10989
 
5.0%
8 5119
 
2.3%
4 4487
 
2.0%
7 4085
 
1.9%
6 3994
 
1.8%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 96743
50.9%
1 33527
 
17.6%
3 15204
 
8.0%
2 11872
 
6.2%
9 10989
 
5.8%
8 5119
 
2.7%
4 4487
 
2.4%
7 4085
 
2.1%
6 3994
 
2.1%
5 3980
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 96743
44.0%
1 33527
 
15.2%
- 30000
 
13.6%
3 15204
 
6.9%
2 11872
 
5.4%
9 10989
 
5.0%
8 5119
 
2.3%
4 4487
 
2.0%
7 4085
 
1.9%
6 3994
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 96743
44.0%
1 33527
 
15.2%
- 30000
 
13.6%
3 15204
 
6.9%
2 11872
 
5.4%
9 10989
 
5.0%
8 5119
 
2.3%
4 4487
 
2.0%
7 4085
 
1.9%
6 3994
 
1.8%
Distinct6508
Distinct (%)65.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1921-02-28 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T17:08:16.022043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:08:16.168772image/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
6525 
1
3475 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 6525
65.2%
1 3475
34.8%

Length

2024-05-11T17:08:16.305137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:08:16.397094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 6525
65.2%
1 3475
34.8%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
6525 
영업/정상
3475 

Length

Max length5
Median length2
Mean length3.0425
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 6525
65.2%
영업/정상 3475
34.8%

Length

2024-05-11T17:08:16.501989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:08:16.604546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 6525
65.2%
영업/정상 3475
34.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
6525 
1
3475 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 6525
65.2%
1 3475
34.8%

Length

2024-05-11T17:08:16.733209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:08:16.834994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 6525
65.2%
1 3475
34.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
6525 
영업
3475 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 6525
65.2%
영업 3475
34.8%

Length

2024-05-11T17:08:16.946746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:08:17.049719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 6525
65.2%
영업 3475
34.8%

폐업일자
Date

MISSING 

Distinct3980
Distinct (%)61.0%
Missing3475
Missing (%)34.8%
Memory size156.2 KiB
Minimum1989-12-26 00:00:00
Maximum2024-05-10 00:00:00
2024-05-11T17:08:17.163810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:08:17.321057image/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 

Distinct6055
Distinct (%)93.6%
Missing3531
Missing (%)35.3%
Memory size156.2 KiB
2024-05-11T17:08:17.675099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.169887
Min length2

Characters and Unicode

Total characters65789
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

Unique5859 ?
Unique (%)90.6%

Sample

1st row02 7207144
2nd row02 7385280
3rd row0207425334
4th row02 7307377
5th row0207325850
ValueCountFrequency (%)
02 3967
35.7%
0200000000 81
 
0.7%
722 56
 
0.5%
733 38
 
0.3%
070 32
 
0.3%
0 31
 
0.3%
720 29
 
0.3%
747 28
 
0.3%
737 28
 
0.3%
730 26
 
0.2%
Other values (6134) 6811
61.2%
2024-05-11T17:08:18.114828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12201
18.5%
2 11656
17.7%
7 8373
12.7%
3 6165
9.4%
5537
8.4%
6 4526
 
6.9%
4 4341
 
6.6%
5 3983
 
6.1%
9 3086
 
4.7%
1 3053
 
4.6%
Other values (2) 2868
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60251
91.6%
Space Separator 5537
 
8.4%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12201
20.3%
2 11656
19.3%
7 8373
13.9%
3 6165
10.2%
6 4526
 
7.5%
4 4341
 
7.2%
5 3983
 
6.6%
9 3086
 
5.1%
1 3053
 
5.1%
8 2867
 
4.8%
Space Separator
ValueCountFrequency (%)
5537
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 65789
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12201
18.5%
2 11656
17.7%
7 8373
12.7%
3 6165
9.4%
5537
8.4%
6 4526
 
6.9%
4 4341
 
6.6%
5 3983
 
6.1%
9 3086
 
4.7%
1 3053
 
4.6%
Other values (2) 2868
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 65789
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12201
18.5%
2 11656
17.7%
7 8373
12.7%
3 6165
9.4%
5537
8.4%
6 4526
 
6.9%
4 4341
 
6.6%
5 3983
 
6.1%
9 3086
 
4.7%
1 3053
 
4.6%
Other values (2) 2868
 
4.4%

소재지면적
Text

MISSING 

Distinct2341
Distinct (%)70.8%
Missing6694
Missing (%)66.9%
Memory size156.2 KiB
2024-05-11T17:08:18.426764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.2141561
Min length4

Characters and Unicode

Total characters17238
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

Unique1943 ?
Unique (%)58.8%

Sample

1st row82.77
2nd row10.00
3rd row185.66
4th row58.74
5th row40.02
ValueCountFrequency (%)
30.00 24
 
0.7%
33.00 22
 
0.7%
66.00 20
 
0.6%
20.00 20
 
0.6%
60.00 17
 
0.5%
16.50 15
 
0.5%
18.00 15
 
0.5%
40.00 14
 
0.4%
19.80 14
 
0.4%
50.00 14
 
0.4%
Other values (2331) 3131
94.7%
2024-05-11T17:08:18.889715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 3306
19.2%
0 2539
14.7%
1 1623
9.4%
2 1556
9.0%
4 1327
7.7%
3 1274
 
7.4%
5 1235
 
7.2%
6 1194
 
6.9%
8 1142
 
6.6%
9 1066
 
6.2%
Other values (2) 976
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13926
80.8%
Other Punctuation 3312
 
19.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2539
18.2%
1 1623
11.7%
2 1556
11.2%
4 1327
9.5%
3 1274
9.1%
5 1235
8.9%
6 1194
8.6%
8 1142
8.2%
9 1066
7.7%
7 970
 
7.0%
Other Punctuation
ValueCountFrequency (%)
. 3306
99.8%
, 6
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 17238
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 3306
19.2%
0 2539
14.7%
1 1623
9.4%
2 1556
9.0%
4 1327
7.7%
3 1274
 
7.4%
5 1235
 
7.2%
6 1194
 
6.9%
8 1142
 
6.6%
9 1066
 
6.2%
Other values (2) 976
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17238
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 3306
19.2%
0 2539
14.7%
1 1623
9.4%
2 1556
9.0%
4 1327
7.7%
3 1274
 
7.4%
5 1235
 
7.2%
6 1194
 
6.9%
8 1142
 
6.6%
9 1066
 
6.2%
Other values (2) 976
 
5.7%
Distinct322
Distinct (%)3.2%
Missing7
Missing (%)0.1%
Memory size156.2 KiB
2024-05-11T17:08:19.276890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1222856
Min length6

Characters and Unicode

Total characters61180
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

Unique54 ?
Unique (%)0.5%

Sample

1st row110100
2nd row110300
3rd row110460
4th row110850
5th row110801
ValueCountFrequency (%)
110111 387
 
3.9%
110522 316
 
3.2%
110130 286
 
2.9%
110809 267
 
2.7%
110320 254
 
2.5%
110524 232
 
2.3%
110836 187
 
1.9%
110530 174
 
1.7%
110300 172
 
1.7%
110290 169
 
1.7%
Other values (312) 7549
75.5%
2024-05-11T17:08:19.770784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 24229
39.6%
0 16993
27.8%
2 3967
 
6.5%
8 3473
 
5.7%
3 2994
 
4.9%
4 2709
 
4.4%
5 2308
 
3.8%
6 1317
 
2.2%
- 1222
 
2.0%
7 1127
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59958
98.0%
Dash Punctuation 1222
 
2.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 24229
40.4%
0 16993
28.3%
2 3967
 
6.6%
8 3473
 
5.8%
3 2994
 
5.0%
4 2709
 
4.5%
5 2308
 
3.8%
6 1317
 
2.2%
7 1127
 
1.9%
9 841
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 1222
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 61180
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 24229
39.6%
0 16993
27.8%
2 3967
 
6.5%
8 3473
 
5.7%
3 2994
 
4.9%
4 2709
 
4.4%
5 2308
 
3.8%
6 1317
 
2.2%
- 1222
 
2.0%
7 1127
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 61180
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 24229
39.6%
0 16993
27.8%
2 3967
 
6.5%
8 3473
 
5.7%
3 2994
 
4.9%
4 2709
 
4.4%
5 2308
 
3.8%
6 1317
 
2.2%
- 1222
 
2.0%
7 1127
 
1.8%
Distinct8222
Distinct (%)82.3%
Missing7
Missing (%)0.1%
Memory size156.2 KiB
2024-05-11T17:08:20.034641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length78
Median length57
Mean length23.410988
Min length14

Characters and Unicode

Total characters233946
Distinct characters380
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7069 ?
Unique (%)70.7%

Sample

1st row서울특별시 종로구 교남동 786-0번지 지상1층
2nd row서울특별시 종로구 관훈동 100-2번지
3rd row서울특별시 종로구 연건동 93-15번지
4th row서울특별시 종로구 효제동 226-2번지
5th row서울특별시 종로구 계동 148-1번지
ValueCountFrequency (%)
서울특별시 9993
22.1%
종로구 9992
22.1%
지상1층 776
 
1.7%
창신동 708
 
1.6%
1층 662
 
1.5%
숭인동 546
 
1.2%
관철동 467
 
1.0%
지하1층 386
 
0.9%
명륜2가 362
 
0.8%
동숭동 342
 
0.8%
Other values (5438) 20902
46.3%
2024-05-11T17:08:20.474232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
43315
18.5%
1 12188
 
5.2%
11235
 
4.8%
10973
 
4.7%
10145
 
4.3%
10118
 
4.3%
10051
 
4.3%
10021
 
4.3%
9994
 
4.3%
9993
 
4.3%
Other values (370) 95913
41.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 138424
59.2%
Space Separator 43315
 
18.5%
Decimal Number 42354
 
18.1%
Dash Punctuation 7951
 
3.4%
Open Punctuation 506
 
0.2%
Close Punctuation 506
 
0.2%
Other Punctuation 447
 
0.2%
Uppercase Letter 289
 
0.1%
Lowercase Letter 91
 
< 0.1%
Math Symbol 61
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
11235
 
8.1%
10973
 
7.9%
10145
 
7.3%
10118
 
7.3%
10051
 
7.3%
10021
 
7.2%
9994
 
7.2%
9993
 
7.2%
9693
 
7.0%
8719
 
6.3%
Other values (311) 37482
27.1%
Uppercase Letter
ValueCountFrequency (%)
B 150
51.9%
D 46
 
15.9%
A 19
 
6.6%
S 11
 
3.8%
T 9
 
3.1%
G 9
 
3.1%
L 8
 
2.8%
K 6
 
2.1%
E 5
 
1.7%
M 4
 
1.4%
Other values (10) 22
 
7.6%
Lowercase Letter
ValueCountFrequency (%)
o 14
15.4%
r 10
11.0%
b 9
9.9%
e 8
8.8%
c 8
8.8%
d 8
8.8%
n 8
8.8%
a 6
6.6%
i 6
6.6%
w 5
 
5.5%
Other values (6) 9
9.9%
Decimal Number
ValueCountFrequency (%)
1 12188
28.8%
2 6455
15.2%
3 4008
 
9.5%
0 3978
 
9.4%
4 3412
 
8.1%
5 3155
 
7.4%
6 2558
 
6.0%
8 2469
 
5.8%
7 2111
 
5.0%
9 2020
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 373
83.4%
. 44
 
9.8%
/ 24
 
5.4%
? 4
 
0.9%
& 1
 
0.2%
1
 
0.2%
Space Separator
ValueCountFrequency (%)
43315
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7951
100.0%
Open Punctuation
ValueCountFrequency (%)
( 506
100.0%
Close Punctuation
ValueCountFrequency (%)
) 506
100.0%
Math Symbol
ValueCountFrequency (%)
~ 61
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 138424
59.2%
Common 95141
40.7%
Latin 381
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
11235
 
8.1%
10973
 
7.9%
10145
 
7.3%
10118
 
7.3%
10051
 
7.3%
10021
 
7.2%
9994
 
7.2%
9993
 
7.2%
9693
 
7.0%
8719
 
6.3%
Other values (311) 37482
27.1%
Latin
ValueCountFrequency (%)
B 150
39.4%
D 46
 
12.1%
A 19
 
5.0%
o 14
 
3.7%
S 11
 
2.9%
r 10
 
2.6%
T 9
 
2.4%
G 9
 
2.4%
b 9
 
2.4%
e 8
 
2.1%
Other values (27) 96
25.2%
Common
ValueCountFrequency (%)
43315
45.5%
1 12188
 
12.8%
- 7951
 
8.4%
2 6455
 
6.8%
3 4008
 
4.2%
0 3978
 
4.2%
4 3412
 
3.6%
5 3155
 
3.3%
6 2558
 
2.7%
8 2469
 
2.6%
Other values (12) 5652
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 138424
59.2%
ASCII 95520
40.8%
Punctuation 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
43315
45.3%
1 12188
 
12.8%
- 7951
 
8.3%
2 6455
 
6.8%
3 4008
 
4.2%
0 3978
 
4.2%
4 3412
 
3.6%
5 3155
 
3.3%
6 2558
 
2.7%
8 2469
 
2.6%
Other values (47) 6031
 
6.3%
Hangul
ValueCountFrequency (%)
11235
 
8.1%
10973
 
7.9%
10145
 
7.3%
10118
 
7.3%
10051
 
7.3%
10021
 
7.2%
9994
 
7.2%
9993
 
7.2%
9693
 
7.0%
8719
 
6.3%
Other values (311) 37482
27.1%
Punctuation
ValueCountFrequency (%)
1
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명주소
Text

MISSING 

Distinct5166
Distinct (%)93.6%
Missing4478
Missing (%)44.8%
Memory size156.2 KiB
2024-05-11T17:08:20.770047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length71
Median length65
Mean length30.303332
Min length20

Characters and Unicode

Total characters167335
Distinct characters380
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

Unique4861 ?
Unique (%)88.0%

Sample

1st row서울특별시 종로구 대학로5길 12 (연건동)
2nd row서울특별시 종로구 종로35길 21-6, 1층 (효제동)
3rd row서울특별시 종로구 우정국로 4-1 (관철동,1층)
4th row서울특별시 종로구 난계로29길 72 (숭인동)
5th row서울특별시 종로구 수표로22길 30 (돈의동)
ValueCountFrequency (%)
서울특별시 5522
 
16.9%
종로구 5521
 
16.9%
1층 1408
 
4.3%
종로 476
 
1.5%
지하1층 397
 
1.2%
2층 355
 
1.1%
창신동 257
 
0.8%
관철동 233
 
0.7%
숭인동 180
 
0.5%
동숭동 170
 
0.5%
Other values (3221) 18222
55.7%
2024-05-11T17:08:21.197508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
27241
 
16.3%
10855
 
6.5%
1 8582
 
5.1%
7292
 
4.4%
( 5890
 
3.5%
) 5889
 
3.5%
5664
 
3.4%
5584
 
3.3%
5580
 
3.3%
5554
 
3.3%
Other values (370) 79204
47.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 95507
57.1%
Space Separator 27241
 
16.3%
Decimal Number 25972
 
15.5%
Open Punctuation 5890
 
3.5%
Close Punctuation 5889
 
3.5%
Other Punctuation 4840
 
2.9%
Dash Punctuation 1481
 
0.9%
Uppercase Letter 314
 
0.2%
Math Symbol 103
 
0.1%
Lowercase Letter 97
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10855
 
11.4%
7292
 
7.6%
5664
 
5.9%
5584
 
5.8%
5580
 
5.8%
5554
 
5.8%
5523
 
5.8%
5522
 
5.8%
5288
 
5.5%
3924
 
4.1%
Other values (310) 34721
36.4%
Uppercase Letter
ValueCountFrequency (%)
B 180
57.3%
D 29
 
9.2%
A 27
 
8.6%
S 12
 
3.8%
G 9
 
2.9%
T 9
 
2.9%
L 8
 
2.5%
R 6
 
1.9%
K 6
 
1.9%
E 5
 
1.6%
Other values (12) 23
 
7.3%
Lowercase Letter
ValueCountFrequency (%)
o 14
14.4%
e 10
10.3%
r 10
10.3%
a 9
9.3%
n 8
8.2%
i 8
8.2%
c 8
8.2%
b 8
8.2%
w 5
 
5.2%
l 5
 
5.2%
Other values (6) 12
12.4%
Decimal Number
ValueCountFrequency (%)
1 8582
33.0%
2 4160
16.0%
3 2898
 
11.2%
4 2143
 
8.3%
5 1909
 
7.4%
0 1619
 
6.2%
6 1360
 
5.2%
9 1138
 
4.4%
8 1129
 
4.3%
7 1034
 
4.0%
Other Punctuation
ValueCountFrequency (%)
, 4777
98.7%
. 54
 
1.1%
/ 5
 
0.1%
? 2
 
< 0.1%
1
 
< 0.1%
& 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
27241
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5890
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5889
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1481
100.0%
Math Symbol
ValueCountFrequency (%)
~ 103
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 95507
57.1%
Common 71416
42.7%
Latin 412
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10855
 
11.4%
7292
 
7.6%
5664
 
5.9%
5584
 
5.8%
5580
 
5.8%
5554
 
5.8%
5523
 
5.8%
5522
 
5.8%
5288
 
5.5%
3924
 
4.1%
Other values (310) 34721
36.4%
Latin
ValueCountFrequency (%)
B 180
43.7%
D 29
 
7.0%
A 27
 
6.6%
o 14
 
3.4%
S 12
 
2.9%
e 10
 
2.4%
r 10
 
2.4%
G 9
 
2.2%
T 9
 
2.2%
a 9
 
2.2%
Other values (29) 103
25.0%
Common
ValueCountFrequency (%)
27241
38.1%
1 8582
 
12.0%
( 5890
 
8.2%
) 5889
 
8.2%
, 4777
 
6.7%
2 4160
 
5.8%
3 2898
 
4.1%
4 2143
 
3.0%
5 1909
 
2.7%
0 1619
 
2.3%
Other values (11) 6308
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 95507
57.1%
ASCII 71826
42.9%
Punctuation 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
27241
37.9%
1 8582
 
11.9%
( 5890
 
8.2%
) 5889
 
8.2%
, 4777
 
6.7%
2 4160
 
5.8%
3 2898
 
4.0%
4 2143
 
3.0%
5 1909
 
2.7%
0 1619
 
2.3%
Other values (48) 6718
 
9.4%
Hangul
ValueCountFrequency (%)
10855
 
11.4%
7292
 
7.6%
5664
 
5.9%
5584
 
5.8%
5580
 
5.8%
5554
 
5.8%
5523
 
5.8%
5522
 
5.8%
5288
 
5.5%
3924
 
4.1%
Other values (310) 34721
36.4%
Punctuation
ValueCountFrequency (%)
1
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct183
Distinct (%)3.4%
Missing4616
Missing (%)46.2%
Infinite0
Infinite (%)0.0%
Mean3117.3822
Minimum3000
Maximum3330
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T17:08:21.353844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000
5-th percentile3029
Q13074
median3127
Q33163
95-th percentile3191
Maximum3330
Range330
Interquartile range (IQR)89

Descriptive statistics

Standard deviation53.810805
Coefficient of variation (CV)0.017261536
Kurtosis-1.040468
Mean3117.3822
Median Absolute Deviation (MAD)46
Skewness-0.26858948
Sum16783986
Variance2895.6027
MonotonicityNot monotonic
2024-05-11T17:08:21.484587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3133 177
 
1.8%
3190 148
 
1.5%
3086 133
 
1.3%
3189 133
 
1.3%
3173 124
 
1.2%
3139 120
 
1.2%
3157 114
 
1.1%
3079 86
 
0.9%
3041 84
 
0.8%
3129 81
 
0.8%
Other values (173) 4184
41.8%
(Missing) 4616
46.2%
ValueCountFrequency (%)
3000 5
 
0.1%
3001 5
 
0.1%
3003 2
 
< 0.1%
3004 5
 
0.1%
3006 1
 
< 0.1%
3007 24
0.2%
3008 21
0.2%
3009 17
0.2%
3010 7
 
0.1%
3011 13
0.1%
ValueCountFrequency (%)
3330 1
 
< 0.1%
3198 25
 
0.2%
3197 59
 
0.6%
3196 18
 
0.2%
3195 50
 
0.5%
3194 14
 
0.1%
3193 35
 
0.4%
3192 65
0.7%
3191 59
 
0.6%
3190 148
1.5%
Distinct8751
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T17:08:21.785980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length37
Mean length5.4294
Min length1

Characters and Unicode

Total characters54294
Distinct characters1143
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7963 ?
Unique (%)79.6%

Sample

1st row고기잔치
2nd row전주식당
3rd row수제비와 보리밥 세상
4th row옛토성
5th row현대호프
ValueCountFrequency (%)
대학로점 86
 
0.7%
광화문점 62
 
0.5%
종로점 61
 
0.5%
카페 54
 
0.4%
광화문 39
 
0.3%
종로 30
 
0.2%
27
 
0.2%
주식회사 25
 
0.2%
cafe 21
 
0.2%
커피 19
 
0.1%
Other values (9612) 12260
96.7%
2024-05-11T17:08:22.262174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2690
 
5.0%
1056
 
1.9%
960
 
1.8%
937
 
1.7%
823
 
1.5%
766
 
1.4%
765
 
1.4%
) 700
 
1.3%
( 698
 
1.3%
661
 
1.2%
Other values (1133) 44238
81.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 45532
83.9%
Space Separator 2690
 
5.0%
Lowercase Letter 2012
 
3.7%
Uppercase Letter 1691
 
3.1%
Decimal Number 757
 
1.4%
Close Punctuation 702
 
1.3%
Open Punctuation 700
 
1.3%
Other Punctuation 159
 
0.3%
Dash Punctuation 24
 
< 0.1%
Letter Number 19
 
< 0.1%
Other values (2) 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1056
 
2.3%
960
 
2.1%
937
 
2.1%
823
 
1.8%
766
 
1.7%
765
 
1.7%
661
 
1.5%
602
 
1.3%
578
 
1.3%
513
 
1.1%
Other values (1049) 37871
83.2%
Uppercase Letter
ValueCountFrequency (%)
A 161
 
9.5%
O 134
 
7.9%
E 128
 
7.6%
B 104
 
6.2%
T 99
 
5.9%
N 94
 
5.6%
S 93
 
5.5%
C 91
 
5.4%
M 79
 
4.7%
H 75
 
4.4%
Other values (16) 633
37.4%
Lowercase Letter
ValueCountFrequency (%)
e 268
13.3%
a 231
11.5%
o 179
 
8.9%
i 143
 
7.1%
n 121
 
6.0%
l 115
 
5.7%
r 111
 
5.5%
t 106
 
5.3%
c 102
 
5.1%
s 94
 
4.7%
Other values (15) 542
26.9%
Other Punctuation
ValueCountFrequency (%)
. 56
35.2%
& 47
29.6%
, 23
14.5%
' 16
 
10.1%
? 5
 
3.1%
/ 3
 
1.9%
! 3
 
1.9%
# 2
 
1.3%
: 2
 
1.3%
1
 
0.6%
Decimal Number
ValueCountFrequency (%)
1 166
21.9%
2 128
16.9%
0 87
11.5%
3 85
11.2%
5 64
 
8.5%
4 58
 
7.7%
9 50
 
6.6%
8 48
 
6.3%
6 37
 
4.9%
7 34
 
4.5%
Math Symbol
ValueCountFrequency (%)
+ 4
66.7%
~ 1
 
16.7%
1
 
16.7%
Close Punctuation
ValueCountFrequency (%)
) 700
99.7%
] 2
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 698
99.7%
[ 2
 
0.3%
Letter Number
ValueCountFrequency (%)
16
84.2%
3
 
15.8%
Space Separator
ValueCountFrequency (%)
2690
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 45464
83.7%
Common 5040
 
9.3%
Latin 3722
 
6.9%
Han 68
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1056
 
2.3%
960
 
2.1%
937
 
2.1%
823
 
1.8%
766
 
1.7%
765
 
1.7%
661
 
1.5%
602
 
1.3%
578
 
1.3%
513
 
1.1%
Other values (994) 37803
83.1%
Han
ValueCountFrequency (%)
3
 
4.4%
3
 
4.4%
2
 
2.9%
2
 
2.9%
2
 
2.9%
2
 
2.9%
2
 
2.9%
2
 
2.9%
2
 
2.9%
2
 
2.9%
Other values (45) 46
67.6%
Latin
ValueCountFrequency (%)
e 268
 
7.2%
a 231
 
6.2%
o 179
 
4.8%
A 161
 
4.3%
i 143
 
3.8%
O 134
 
3.6%
E 128
 
3.4%
n 121
 
3.3%
l 115
 
3.1%
r 111
 
3.0%
Other values (43) 2131
57.3%
Common
ValueCountFrequency (%)
2690
53.4%
) 700
 
13.9%
( 698
 
13.8%
1 166
 
3.3%
2 128
 
2.5%
0 87
 
1.7%
3 85
 
1.7%
5 64
 
1.3%
4 58
 
1.2%
. 56
 
1.1%
Other values (21) 308
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 45461
83.7%
ASCII 8741
 
16.1%
CJK 64
 
0.1%
Number Forms 19
 
< 0.1%
CJK Compat Ideographs 4
 
< 0.1%
Compat Jamo 3
 
< 0.1%
None 1
 
< 0.1%
Math Operators 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2690
30.8%
) 700
 
8.0%
( 698
 
8.0%
e 268
 
3.1%
a 231
 
2.6%
o 179
 
2.0%
1 166
 
1.9%
A 161
 
1.8%
i 143
 
1.6%
O 134
 
1.5%
Other values (70) 3371
38.6%
Hangul
ValueCountFrequency (%)
1056
 
2.3%
960
 
2.1%
937
 
2.1%
823
 
1.8%
766
 
1.7%
765
 
1.7%
661
 
1.5%
602
 
1.3%
578
 
1.3%
513
 
1.1%
Other values (991) 37800
83.1%
Number Forms
ValueCountFrequency (%)
16
84.2%
3
 
15.8%
CJK
ValueCountFrequency (%)
3
 
4.7%
3
 
4.7%
2
 
3.1%
2
 
3.1%
2
 
3.1%
2
 
3.1%
2
 
3.1%
2
 
3.1%
2
 
3.1%
2
 
3.1%
Other values (42) 42
65.6%
CJK Compat Ideographs
ValueCountFrequency (%)
2
50.0%
1
25.0%
1
25.0%
None
ValueCountFrequency (%)
1
100.0%
Compat Jamo
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Math Operators
ValueCountFrequency (%)
1
100.0%
Distinct7159
Distinct (%)71.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1998-12-29 00:00:00
Maximum2024-05-09 18:31:56
2024-05-11T17:08:22.393966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:08:22.537731image/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
7153 
U
2847 

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 7153
71.5%
U 2847
 
28.5%

Length

2024-05-11T17:08:22.662186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:08:22.745980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 7153
71.5%
u 2847
 
28.5%
Distinct1342
Distinct (%)13.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T17:08:22.840258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:08:22.970952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
한식
3951 
분식
1738 
경양식
1718 
기타
1298 
일식
 
316
Other values (20)
979 

Length

Max length15
Median length2
Mean length2.5417
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
한식 3951
39.5%
분식 1738
17.4%
경양식 1718
17.2%
기타 1298
 
13.0%
일식 316
 
3.2%
중국식 255
 
2.5%
호프/통닭 222
 
2.2%
정종/대포집/소주방 116
 
1.2%
외국음식전문점(인도,태국등) 100
 
1.0%
까페 93
 
0.9%
Other values (15) 193
 
1.9%

Length

2024-05-11T17:08:23.098622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 3951
39.5%
분식 1738
17.4%
경양식 1718
17.2%
기타 1298
 
13.0%
일식 316
 
3.2%
중국식 255
 
2.5%
호프/통닭 222
 
2.2%
정종/대포집/소주방 116
 
1.2%
외국음식전문점(인도,태국등 100
 
1.0%
까페 93
 
0.9%
Other values (15) 193
 
1.9%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct4638
Distinct (%)50.4%
Missing798
Missing (%)8.0%
Infinite0
Infinite (%)0.0%
Mean198990.22
Minimum192828.05
Maximum201962.63
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T17:08:23.220722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum192828.05
5-th percentile196662.19
Q1197775.32
median198928.78
Q3200075.36
95-th percentile201341.79
Maximum201962.63
Range9134.5752
Interquartile range (IQR)2300.0386

Descriptive statistics

Standard deviation1423.0684
Coefficient of variation (CV)0.0071514491
Kurtosis-0.75093631
Mean198990.22
Median Absolute Deviation (MAD)1147.4082
Skewness0.03363817
Sum1.831108 × 109
Variance2025123.8
MonotonicityNot monotonic
2024-05-11T17:08:23.661569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
198150.300374121 100
 
1.0%
198324.653631679 48
 
0.5%
197650.653736722 42
 
0.4%
197181.393301659 38
 
0.4%
197567.849954354 35
 
0.4%
197583.394691008 32
 
0.3%
198068.926781947 31
 
0.3%
198286.311784052 31
 
0.3%
199045.043602772 30
 
0.3%
198504.772723631 30
 
0.3%
Other values (4628) 8785
87.8%
(Missing) 798
 
8.0%
ValueCountFrequency (%)
192828.053794717 1
 
< 0.1%
195877.645568351 1
 
< 0.1%
195998.140762432 1
 
< 0.1%
196010.602015955 1
 
< 0.1%
196022.700306348 1
 
< 0.1%
196023.58999141 1
 
< 0.1%
196036.761890225 3
< 0.1%
196045.610971552 1
 
< 0.1%
196047.812876606 1
 
< 0.1%
196048.515964041 2
< 0.1%
ValueCountFrequency (%)
201962.62904341 1
 
< 0.1%
201962.375901875 1
 
< 0.1%
201959.524603547 4
< 0.1%
201958.489788275 1
 
< 0.1%
201957.720140045 2
< 0.1%
201956.111584613 1
 
< 0.1%
201955.261272616 1
 
< 0.1%
201954.453030707 1
 
< 0.1%
201952.144470289 1
 
< 0.1%
201949.750623535 3
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct4638
Distinct (%)50.4%
Missing798
Missing (%)8.0%
Infinite0
Infinite (%)0.0%
Mean452701.49
Minimum451580.2
Maximum457530.76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T17:08:23.798897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum451580.2
5-th percentile451885.73
Q1452117.33
median452396.83
Q3453033.08
95-th percentile454659.12
Maximum457530.76
Range5950.562
Interquartile range (IQR)915.754

Descriptive statistics

Standard deviation909.52302
Coefficient of variation (CV)0.002009101
Kurtosis5.2250715
Mean452701.49
Median Absolute Deviation (MAD)356.79905
Skewness2.1592804
Sum4.1657591 × 109
Variance827232.12
MonotonicityNot monotonic
2024-05-11T17:08:23.919156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
452019.212642931 100
 
1.0%
452252.812389497 48
 
0.5%
452368.519288991 42
 
0.4%
452458.826651573 38
 
0.4%
452567.159554494 35
 
0.4%
452513.612017871 32
 
0.3%
452087.030190231 31
 
0.3%
452091.444332546 31
 
0.3%
451939.677286976 30
 
0.3%
452018.161511911 30
 
0.3%
Other values (4628) 8785
87.8%
(Missing) 798
 
8.0%
ValueCountFrequency (%)
451580.195594285 1
 
< 0.1%
451580.22699738 1
 
< 0.1%
451596.900364676 2
 
< 0.1%
451621.50036997 6
0.1%
451647.659357433 3
< 0.1%
451658.76871749 2
 
< 0.1%
451663.113055146 1
 
< 0.1%
451673.763505869 1
 
< 0.1%
451678.787536538 1
 
< 0.1%
451682.186997114 2
 
< 0.1%
ValueCountFrequency (%)
457530.757592514 1
< 0.1%
457064.384905993 1
< 0.1%
457039.439720457 1
< 0.1%
456956.051784209 1
< 0.1%
456938.519833034 2
< 0.1%
456775.899204411 1
< 0.1%
456670.79610764 1
< 0.1%
456667.78577584 2
< 0.1%
456584.627065144 1
< 0.1%
456582.534430668 1
< 0.1%

위생업태명
Categorical

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
한식
3314 
<NA>
1735 
분식
1612 
경양식
1505 
기타
830 
Other values (20)
1004 

Length

Max length15
Median length2
Mean length2.7791
Min length2

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
한식 3314
33.1%
<NA> 1735
17.3%
분식 1612
16.1%
경양식 1505
15.0%
기타 830
 
8.3%
일식 237
 
2.4%
중국식 200
 
2.0%
호프/통닭 151
 
1.5%
정종/대포집/소주방 111
 
1.1%
까페 81
 
0.8%
Other values (15) 224
 
2.2%

Length

2024-05-11T17:08:24.049102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 3314
33.1%
na 1735
17.3%
분식 1612
16.1%
경양식 1505
15.0%
기타 830
 
8.3%
일식 237
 
2.4%
중국식 200
 
2.0%
호프/통닭 151
 
1.5%
정종/대포집/소주방 111
 
1.1%
까페 81
 
0.8%
Other values (15) 224
 
2.2%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)0.2%
Missing4211
Missing (%)42.1%
Infinite0
Infinite (%)0.0%
Mean0.55259976
Minimum0
Maximum15
Zeros3704
Zeros (%)37.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T17:08:24.144258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum15
Range15
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.92452133
Coefficient of variation (CV)1.6730397
Kurtosis17.09699
Mean0.55259976
Median Absolute Deviation (MAD)0
Skewness2.7537062
Sum3199
Variance0.8547397
MonotonicityNot monotonic
2024-05-11T17:08:24.248349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 3704
37.0%
1 1348
 
13.5%
2 481
 
4.8%
3 190
 
1.9%
4 43
 
0.4%
6 9
 
0.1%
5 8
 
0.1%
7 4
 
< 0.1%
15 1
 
< 0.1%
10 1
 
< 0.1%
(Missing) 4211
42.1%
ValueCountFrequency (%)
0 3704
37.0%
1 1348
 
13.5%
2 481
 
4.8%
3 190
 
1.9%
4 43
 
0.4%
5 8
 
0.1%
6 9
 
0.1%
7 4
 
< 0.1%
10 1
 
< 0.1%
15 1
 
< 0.1%
ValueCountFrequency (%)
15 1
 
< 0.1%
10 1
 
< 0.1%
7 4
 
< 0.1%
6 9
 
0.1%
5 8
 
0.1%
4 43
 
0.4%
3 190
 
1.9%
2 481
 
4.8%
1 1348
 
13.5%
0 3704
37.0%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)0.2%
Missing4180
Missing (%)41.8%
Infinite0
Infinite (%)0.0%
Mean0.7185567
Minimum0
Maximum13
Zeros3327
Zeros (%)33.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T17:08:24.358330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum13
Range13
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.0394352
Coefficient of variation (CV)1.4465597
Kurtosis7.92393
Mean0.7185567
Median Absolute Deviation (MAD)0
Skewness2.0163313
Sum4182
Variance1.0804255
MonotonicityNot monotonic
2024-05-11T17:08:24.454560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 3327
33.3%
1 1341
 
13.4%
2 785
 
7.8%
3 268
 
2.7%
4 65
 
0.7%
5 18
 
0.2%
6 7
 
0.1%
7 4
 
< 0.1%
8 3
 
< 0.1%
10 1
 
< 0.1%
(Missing) 4180
41.8%
ValueCountFrequency (%)
0 3327
33.3%
1 1341
13.4%
2 785
 
7.8%
3 268
 
2.7%
4 65
 
0.7%
5 18
 
0.2%
6 7
 
0.1%
7 4
 
< 0.1%
8 3
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
13 1
 
< 0.1%
10 1
 
< 0.1%
8 3
 
< 0.1%
7 4
 
< 0.1%
6 7
 
0.1%
5 18
 
0.2%
4 65
 
0.7%
3 268
 
2.7%
2 785
7.8%
1 1341
13.4%

영업장주변구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
4737 
기타
4333 
주택가주변
 
464
유흥업소밀집지역
 
411
학교정화(상대)
 
24
Other values (3)
 
31

Length

Max length8
Median length7
Mean length3.36
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4737
47.4%
기타 4333
43.3%
주택가주변 464
 
4.6%
유흥업소밀집지역 411
 
4.1%
학교정화(상대) 24
 
0.2%
아파트지역 17
 
0.2%
결혼예식장주변 11
 
0.1%
학교정화(절대) 3
 
< 0.1%

Length

2024-05-11T17:08:24.573917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:08:24.679929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4737
47.4%
기타 4333
43.3%
주택가주변 464
 
4.6%
유흥업소밀집지역 411
 
4.1%
학교정화(상대 24
 
0.2%
아파트지역 17
 
0.2%
결혼예식장주변 11
 
0.1%
학교정화(절대 3
 
< 0.1%

등급구분명
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5085 
기타
2470 
1162 
678 
자율
 
356
Other values (3)
 
249

Length

Max length4
Median length4
Mean length2.833
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5085
50.8%
기타 2470
24.7%
1162
 
11.6%
678
 
6.8%
자율 356
 
3.6%
지도 157
 
1.6%
관리 51
 
0.5%
우수 41
 
0.4%

Length

2024-05-11T17:08:24.816310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:08:24.931802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5085
50.8%
기타 2470
24.7%
1162
 
11.6%
678
 
6.8%
자율 356
 
3.6%
지도 157
 
1.6%
관리 51
 
0.5%
우수 41
 
0.4%
Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
상수도전용
5592 
<NA>
4376 
상수도(음용)지하수(주방용)겸용
 
31
간이상수도
 
1

Length

Max length17
Median length5
Mean length4.5996
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 5592
55.9%
<NA> 4376
43.8%
상수도(음용)지하수(주방용)겸용 31
 
0.3%
간이상수도 1
 
< 0.1%

Length

2024-05-11T17:08:25.066911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:08:25.167450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 5592
55.9%
na 4376
43.8%
상수도(음용)지하수(주방용)겸용 31
 
0.3%
간이상수도 1
 
< 0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9679 
0
 
321

Length

Max length4
Median length4
Mean length3.9037
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> 9679
96.8%
0 321
 
3.2%

Length

2024-05-11T17:08:25.295972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:08:25.386816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9679
96.8%
0 321
 
3.2%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9678 
0
 
322

Length

Max length4
Median length4
Mean length3.9034
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> 9678
96.8%
0 322
 
3.2%

Length

2024-05-11T17:08:25.494766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:08:25.623881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9678
96.8%
0 322
 
3.2%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9678 
0
 
322

Length

Max length4
Median length4
Mean length3.9034
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> 9678
96.8%
0 322
 
3.2%

Length

2024-05-11T17:08:25.857637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:08:26.116010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9678
96.8%
0 322
 
3.2%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9678 
0
 
322

Length

Max length4
Median length4
Mean length3.9034
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> 9678
96.8%
0 322
 
3.2%

Length

2024-05-11T17:08:26.215595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:08:26.309179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9678
96.8%
0 322
 
3.2%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9678 
0
 
322

Length

Max length4
Median length4
Mean length3.9034
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> 9678
96.8%
0 322
 
3.2%

Length

2024-05-11T17:08:26.424785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:08:26.539889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9678
96.8%
0 322
 
3.2%

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>
9678 
0
 
322

Length

Max length4
Median length4
Mean length3.9034
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> 9678
96.8%
0 322
 
3.2%

Length

2024-05-11T17:08:26.659222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:08:26.765262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9678
96.8%
0 322
 
3.2%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9678 
0
 
322

Length

Max length4
Median length4
Mean length3.9034
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> 9678
96.8%
0 322
 
3.2%

Length

2024-05-11T17:08:26.874138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:08:26.968121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9678
96.8%
0 322
 
3.2%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1733
Missing (%)17.3%
Memory size97.7 KiB
False
8164 
True
 
103
(Missing)
1733 
ValueCountFrequency (%)
False 8164
81.6%
True 103
 
1.0%
(Missing) 1733
 
17.3%
2024-05-11T17:08:27.051148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct5071
Distinct (%)61.3%
Missing1733
Missing (%)17.3%
Infinite0
Infinite (%)0.0%
Mean77.392446
Minimum0
Maximum30707.06
Zeros118
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T17:08:27.160644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile11.909
Q125.16
median45.47
Q384.385
95-th percentile216.071
Maximum30707.06
Range30707.06
Interquartile range (IQR)59.225

Descriptive statistics

Standard deviation352.30801
Coefficient of variation (CV)4.5522274
Kurtosis6914.6381
Mean77.392446
Median Absolute Deviation (MAD)24.67
Skewness79.712451
Sum639803.35
Variance124120.93
MonotonicityNot monotonic
2024-05-11T17:08:27.292658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 118
 
1.2%
30.0 51
 
0.5%
16.5 36
 
0.4%
20.0 34
 
0.3%
33.0 33
 
0.3%
19.8 28
 
0.3%
24.0 27
 
0.3%
18.0 25
 
0.2%
26.4 22
 
0.2%
15.0 22
 
0.2%
Other values (5061) 7871
78.7%
(Missing) 1733
 
17.3%
ValueCountFrequency (%)
0.0 118
1.2%
1.0 2
 
< 0.1%
1.09 1
 
< 0.1%
2.54 1
 
< 0.1%
3.25 2
 
< 0.1%
3.3 4
 
< 0.1%
3.48 1
 
< 0.1%
3.75 1
 
< 0.1%
3.83 1
 
< 0.1%
3.85 1
 
< 0.1%
ValueCountFrequency (%)
30707.06 1
< 0.1%
2768.5 1
< 0.1%
2569.0 1
< 0.1%
1444.17 1
< 0.1%
1293.47 1
< 0.1%
1281.17 1
< 0.1%
1219.61 1
< 0.1%
1104.95 1
< 0.1%
1090.0 1
< 0.1%
1087.65 1
< 0.1%

전통업소지정번호
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9999 
4078
 
1

Length

Max length4
Median length4
Mean length4
Min length4

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> 9999
> 99.9%
4078 1
 
< 0.1%

Length

2024-05-11T17:08:27.416174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:08:27.506156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9999
> 99.9%
4078 1
 
< 0.1%

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
703630000003000000-101-1996-1122719960302<NA>1영업/정상1영업<NA><NA><NA><NA>02 7207144<NA>110100서울특별시 종로구 교남동 786-0번지 지상1층<NA><NA>고기잔치2008-07-16 09:37:39I2018-08-31 23:59:59.0한식<NA><NA>한식00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N15.99<NA><NA><NA>
920030000003000000-101-2000-1138220000703<NA>3폐업2폐업20090203<NA><NA><NA>02 7385280<NA>110300서울특별시 종로구 관훈동 100-2번지<NA><NA>전주식당2008-07-23 09:32:32I2018-08-31 23:59:59.0한식198542.046479452515.147334한식00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N92.12<NA><NA><NA>
711930000003000000-101-1997-0284219970825<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>110460서울특별시 종로구 연건동 93-15번지서울특별시 종로구 대학로5길 12 (연건동)3082수제비와 보리밥 세상2015-08-20 13:39:45I2018-08-31 23:59:59.0한식200056.482517452898.127465한식02유흥업소밀집지역지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N64.0<NA><NA><NA>
1509430000003000000-101-2013-0026320131010<NA>3폐업2폐업20151124<NA><NA><NA><NA><NA>110850서울특별시 종로구 효제동 226-2번지서울특별시 종로구 종로35길 21-6, 1층 (효제동)3126옛토성2015-12-02 10:45:39I2018-08-31 23:59:59.0한식200252.303687452205.707697한식<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N31.9<NA><NA><NA>
317430000003000000-101-1988-0674319880203<NA>3폐업2폐업20010918<NA><NA><NA>0207425334<NA>110801서울특별시 종로구 계동 148-1번지<NA><NA>현대호프2003-02-25 00:00:00I2018-08-31 23:59:59.0한식<NA><NA>한식24기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N173.25<NA><NA><NA>
820730000003000000-101-1999-0574119991123<NA>3폐업2폐업20080125<NA><NA><NA>02 7307377<NA>110070서울특별시 종로구 내수동 35-0번지<NA><NA>우리집 보쌈1999-11-23 00:00:00I2018-08-31 23:59:59.0일식<NA><NA>일식11기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N54.67<NA><NA><NA>
1154030000003000000-101-2004-0046520041119<NA>1영업/정상1영업<NA><NA><NA><NA><NA>82.77110111서울특별시 종로구 관철동 263번지 1층서울특별시 종로구 우정국로 4-1 (관철동,1층)3189토속정2020-01-09 15:10:18U2020-01-11 02:40:00.0한식198454.588762451879.773068한식00<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N82.77<NA><NA><NA>
425730000003000000-101-1992-0042319920424<NA>3폐업2폐업19940809<NA><NA><NA>0207325850<NA>110110서울특별시 종로구 서린동 127-0번지<NA><NA>무교동낙지2001-11-20 00:00:00I2018-08-31 23:59:59.0한식198119.936679451902.693235한식00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N53.35<NA><NA><NA>
1240130000003000000-101-2006-0032920061204<NA>3폐업2폐업20070626<NA><NA><NA><NA><NA>110863서울특별시 종로구 숭인동 190-1번지 1층<NA><NA>대박주막골2007-07-03 00:00:00I2018-08-31 23:59:59.0호프/통닭201772.180262452545.382897호프/통닭00<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N20.0<NA><NA><NA>
1394430000003000000-101-2010-0023920100809<NA>3폐업2폐업20110530<NA><NA><NA>02 738 7851<NA>110805서울특별시 종로구 누하동 56-1번지<NA><NA>esola(에소라)2010-08-09 11:50:02I2018-08-31 23:59:59.0경양식197154.70982453020.240843경양식<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N35.9<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
24030000003000000-101-1974-0133419740410<NA>1영업/정상1영업<NA><NA><NA><NA>02 734285528.30110123서울특별시 종로구 종로3가 116-3서울특별시 종로구 수표로20길 17 (종로3가)3192라우드 플레이 리스트(LOUD Play list)2022-04-11 10:44:25U2021-12-03 23:03:00.0한식199088.081995451967.732854<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
82330000003000000-101-1982-0182419821020<NA>1영업/정상1영업<NA><NA><NA><NA>02 742133951.39110410서울특별시 종로구 인의동 25서울특별시 종로구 창경궁로16길 6-12, 2층 (인의동)3128영재식당2022-08-17 15:37:58U2021-12-07 22:00:00.0한식199664.158242452482.9789<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
704930000003000000-101-1997-0277019970217<NA>3폐업2폐업20041119<NA><NA><NA>02 7417448<NA>110845서울특별시 종로구 충신동 104-1번지<NA><NA>찌게마을2001-11-20 00:00:00I2018-08-31 23:59:59.0한식200240.392972452458.263705한식02기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N48.07<NA><NA><NA>
453230000003000000-101-1992-0522519920716<NA>3폐업2폐업19930824<NA><NA><NA>0200000000<NA>110061서울특별시 종로구 신문로1가 18-1번지<NA><NA>십이월이십오일2001-09-29 00:00:00I2018-08-31 23:59:59.0경양식<NA><NA>경양식00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N35.01<NA><NA><NA>
1640530000003000000-101-2016-0028920160812<NA>1영업/정상1영업<NA><NA><NA><NA><NA>151.00110880서울특별시 종로구 숭인동 310 대우디오빌2층206호서울특별시 종로구 종로 344, 2층 206호 (숭인동)3114홍콩반점0410 동묘역점2021-09-28 16:22:53U2021-09-30 02:40:00.0중국식201350.473376452279.74426중국식<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N151.0<NA><NA><NA>
149830000003000000-101-1984-0619019840822<NA>3폐업2폐업20190628<NA><NA><NA>02 737356540.30110290서울특별시 종로구 인사동 173번지서울특별시 종로구 인사동5길 7, 1층 (인사동)3162인사동국밥2019-06-28 10:43:39U2019-06-30 02:40:00.0분식198690.082041452266.198268분식12기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N40.3<NA><NA><NA>
695630000003000000-101-1996-0743319960904<NA>3폐업2폐업20031229<NA><NA><NA>02 7205562<NA>110130서울특별시 종로구 청진동 258-1번지<NA><NA>패스호프2000-03-09 00:00:00I2018-08-31 23:59:59.0분식<NA><NA>분식02유흥업소밀집지역우수상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N76.77<NA><NA><NA>
692430000003000000-101-1996-0739519960705<NA>3폐업2폐업19990913<NA><NA><NA>02 7388951<NA>110035서울특별시 종로구 옥인동 37-0번지<NA><NA>윤가네만두2001-09-29 00:00:00I2018-08-31 23:59:59.0분식197151.855973453243.785159분식<NA><NA>기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N15.11<NA><NA><NA>
88830000003000000-101-1982-0484719820603<NA>3폐업2폐업19941227<NA><NA><NA>0207443672<NA>110340서울특별시 종로구 익선동 158-3번지<NA><NA>리베라2001-11-20 00:00:00I2018-08-31 23:59:59.0경양식199120.386055452366.057156경양식11기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N43.3<NA><NA><NA>
1000930000003000000-101-2001-1235520011214<NA>1영업/정상1영업<NA><NA><NA><NA>22023321<NA>110160서울특별시 종로구 공평동 42-2번지서울특별시 종로구 우정국로 30-30 (공평동)<NA>김명자굴국밥2007-08-23 09:49:20I2018-08-31 23:59:59.0한식198495.143454452138.704732한식00<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N42.12<NA><NA><NA>