Overview

Dataset statistics

Number of variables44
Number of observations2815
Missing cells47509
Missing cells (%)38.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.0 MiB
Average record size in memory377.0 B

Variable types

Categorical12
Text8
DateTime4
Unsupported9
Numeric10
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
Author성북구
URLhttps://data.seoul.go.kr/dataList/OA-18084/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
남성종사자수 is highly imbalanced (67.4%)Imbalance
여성종사자수 is highly imbalanced (67.4%)Imbalance
급수시설구분명 is highly imbalanced (70.3%)Imbalance
총인원 is highly imbalanced (67.5%)Imbalance
다중이용업소여부 is highly imbalanced (99.4%)Imbalance
인허가취소일자 has 2815 (100.0%) missing valuesMissing
폐업일자 has 830 (29.5%) missing valuesMissing
휴업시작일자 has 2815 (100.0%) missing valuesMissing
휴업종료일자 has 2815 (100.0%) missing valuesMissing
재개업일자 has 2815 (100.0%) missing valuesMissing
전화번호 has 1563 (55.5%) missing valuesMissing
소재지면적 has 1299 (46.1%) missing valuesMissing
도로명주소 has 568 (20.2%) missing valuesMissing
도로명우편번호 has 619 (22.0%) missing valuesMissing
업태구분명 has 2815 (100.0%) missing valuesMissing
좌표정보(X) has 31 (1.1%) missing valuesMissing
좌표정보(Y) has 31 (1.1%) missing valuesMissing
영업장주변구분명 has 2815 (100.0%) missing valuesMissing
등급구분명 has 2815 (100.0%) missing valuesMissing
본사종업원수 has 2000 (71.0%) missing valuesMissing
공장사무직종업원수 has 2000 (71.0%) missing valuesMissing
공장판매직종업원수 has 2000 (71.0%) missing valuesMissing
공장생산직종업원수 has 2000 (71.0%) missing valuesMissing
보증액 has 2456 (87.2%) missing valuesMissing
월세액 has 2466 (87.6%) missing valuesMissing
다중이용업소여부 has 748 (26.6%) missing valuesMissing
시설총규모 has 748 (26.6%) missing valuesMissing
전통업소지정번호 has 2815 (100.0%) missing valuesMissing
전통업소주된음식 has 2815 (100.0%) missing valuesMissing
홈페이지 has 2783 (98.9%) missing valuesMissing
본사종업원수 is highly skewed (γ1 = 28.44165444)Skewed
시설총규모 is highly skewed (γ1 = 23.27576129)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
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
영업장주변구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
등급구분명 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
본사종업원수 has 803 (28.5%) zerosZeros
공장사무직종업원수 has 780 (27.7%) zerosZeros
공장판매직종업원수 has 696 (24.7%) zerosZeros
공장생산직종업원수 has 779 (27.7%) zerosZeros
보증액 has 271 (9.6%) zerosZeros
월세액 has 271 (9.6%) zerosZeros
시설총규모 has 2047 (72.7%) zerosZeros

Reproduction

Analysis started2024-05-11 06:45:45.803228
Analysis finished2024-05-11 06:45:47.962482
Duration2.16 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size22.1 KiB
3070000
2815 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3070000
2nd row3070000
3rd row3070000
4th row3070000
5th row3070000

Common Values

ValueCountFrequency (%)
3070000 2815
100.0%

Length

2024-05-11T15:45:48.044436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:45:48.174599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3070000 2815
100.0%

관리번호
Text

UNIQUE 

Distinct2815
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size22.1 KiB
2024-05-11T15:45:48.374099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters61930
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

Unique2815 ?
Unique (%)100.0%

Sample

1st row3070000-134-2004-00001
2nd row3070000-134-2004-00002
3rd row3070000-134-2004-00003
4th row3070000-134-2004-00004
5th row3070000-134-2004-00005
ValueCountFrequency (%)
3070000-134-2004-00001 1
 
< 0.1%
3070000-134-2019-00065 1
 
< 0.1%
3070000-134-2019-00067 1
 
< 0.1%
3070000-134-2019-00068 1
 
< 0.1%
3070000-134-2019-00069 1
 
< 0.1%
3070000-134-2019-00070 1
 
< 0.1%
3070000-134-2019-00071 1
 
< 0.1%
3070000-134-2019-00072 1
 
< 0.1%
3070000-134-2019-00073 1
 
< 0.1%
3070000-134-2019-00074 1
 
< 0.1%
Other values (2805) 2805
99.6%
2024-05-11T15:45:48.747258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 26191
42.3%
- 8445
 
13.6%
3 6589
 
10.6%
1 5672
 
9.2%
2 4842
 
7.8%
4 3843
 
6.2%
7 3492
 
5.6%
5 758
 
1.2%
9 731
 
1.2%
6 699
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 53485
86.4%
Dash Punctuation 8445
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 26191
49.0%
3 6589
 
12.3%
1 5672
 
10.6%
2 4842
 
9.1%
4 3843
 
7.2%
7 3492
 
6.5%
5 758
 
1.4%
9 731
 
1.4%
6 699
 
1.3%
8 668
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 8445
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 61930
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 26191
42.3%
- 8445
 
13.6%
3 6589
 
10.6%
1 5672
 
9.2%
2 4842
 
7.8%
4 3843
 
6.2%
7 3492
 
5.6%
5 758
 
1.2%
9 731
 
1.2%
6 699
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 61930
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 26191
42.3%
- 8445
 
13.6%
3 6589
 
10.6%
1 5672
 
9.2%
2 4842
 
7.8%
4 3843
 
6.2%
7 3492
 
5.6%
5 758
 
1.2%
9 731
 
1.2%
6 699
 
1.1%
Distinct1906
Distinct (%)67.7%
Missing0
Missing (%)0.0%
Memory size22.1 KiB
Minimum2004-04-02 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T15:45:48.914708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:45:49.075565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2815
Missing (%)100.0%
Memory size24.9 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.1 KiB
3
1985 
1
830 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 1985
70.5%
1 830
29.5%

Length

2024-05-11T15:45:49.238199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:45:49.357795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 1985
70.5%
1 830
29.5%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.1 KiB
폐업
1985 
영업/정상
830 

Length

Max length5
Median length2
Mean length2.8845471
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1985
70.5%
영업/정상 830
29.5%

Length

2024-05-11T15:45:49.482809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:45:49.633726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1985
70.5%
영업/정상 830
29.5%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.1 KiB
2
1985 
1
830 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 1985
70.5%
1 830
29.5%

Length

2024-05-11T15:45:49.842264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:45:49.987121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 1985
70.5%
1 830
29.5%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.1 KiB
폐업
1985 
영업
830 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1985
70.5%
영업 830
29.5%

Length

2024-05-11T15:45:50.125595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:45:50.253753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1985
70.5%
영업 830
29.5%

폐업일자
Date

MISSING 

Distinct1328
Distinct (%)66.9%
Missing830
Missing (%)29.5%
Memory size22.1 KiB
Minimum2004-09-14 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T15:45:50.405774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:45:50.599284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2815
Missing (%)100.0%
Memory size24.9 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2815
Missing (%)100.0%
Memory size24.9 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2815
Missing (%)100.0%
Memory size24.9 KiB

전화번호
Text

MISSING 

Distinct1208
Distinct (%)96.5%
Missing1563
Missing (%)55.5%
Memory size22.1 KiB
2024-05-11T15:45:51.052288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.88099
Min length2

Characters and Unicode

Total characters13623
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

Unique1171 ?
Unique (%)93.5%

Sample

1st row02 9161416
2nd row02 9110119
3rd row02 9132304
4th row0221171003
5th row02 9690887
ValueCountFrequency (%)
02 987
36.3%
070 69
 
2.5%
941 23
 
0.8%
909 17
 
0.6%
922 16
 
0.6%
929 16
 
0.6%
921 13
 
0.5%
942 12
 
0.4%
943 12
 
0.4%
924 12
 
0.4%
Other values (1323) 1545
56.8%
2024-05-11T15:45:51.741429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2300
16.9%
0 2120
15.6%
1993
14.6%
9 1521
11.2%
1 955
7.0%
7 903
 
6.6%
4 832
 
6.1%
3 792
 
5.8%
5 762
 
5.6%
8 725
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11630
85.4%
Space Separator 1993
 
14.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 2300
19.8%
0 2120
18.2%
9 1521
13.1%
1 955
8.2%
7 903
 
7.8%
4 832
 
7.2%
3 792
 
6.8%
5 762
 
6.6%
8 725
 
6.2%
6 720
 
6.2%
Space Separator
ValueCountFrequency (%)
1993
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13623
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 2300
16.9%
0 2120
15.6%
1993
14.6%
9 1521
11.2%
1 955
7.0%
7 903
 
6.6%
4 832
 
6.1%
3 792
 
5.8%
5 762
 
5.6%
8 725
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13623
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 2300
16.9%
0 2120
15.6%
1993
14.6%
9 1521
11.2%
1 955
7.0%
7 903
 
6.6%
4 832
 
6.1%
3 792
 
5.8%
5 762
 
5.6%
8 725
 
5.3%

소재지면적
Text

MISSING 

Distinct528
Distinct (%)34.8%
Missing1299
Missing (%)46.1%
Memory size22.1 KiB
2024-05-11T15:45:52.233044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length6
Mean length4.6022427
Min length3

Characters and Unicode

Total characters6977
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

Unique392 ?
Unique (%)25.9%

Sample

1st row36.90
2nd row23.57
3rd row51.87
4th row87.86
5th row165.00
ValueCountFrequency (%)
00 241
 
15.9%
3.30 103
 
6.8%
33.00 45
 
3.0%
6.60 30
 
2.0%
3.00 26
 
1.7%
2.00 25
 
1.6%
10.00 21
 
1.4%
15.00 19
 
1.3%
16.50 18
 
1.2%
18.00 16
 
1.1%
Other values (518) 972
64.1%
2024-05-11T15:45:52.860923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2389
34.2%
. 1516
21.7%
3 607
 
8.7%
1 518
 
7.4%
2 413
 
5.9%
6 360
 
5.2%
5 299
 
4.3%
4 263
 
3.8%
9 255
 
3.7%
8 181
 
2.6%
Other values (2) 176
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5460
78.3%
Other Punctuation 1517
 
21.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2389
43.8%
3 607
 
11.1%
1 518
 
9.5%
2 413
 
7.6%
6 360
 
6.6%
5 299
 
5.5%
4 263
 
4.8%
9 255
 
4.7%
8 181
 
3.3%
7 175
 
3.2%
Other Punctuation
ValueCountFrequency (%)
. 1516
99.9%
, 1
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 6977
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2389
34.2%
. 1516
21.7%
3 607
 
8.7%
1 518
 
7.4%
2 413
 
5.9%
6 360
 
5.2%
5 299
 
4.3%
4 263
 
3.8%
9 255
 
3.7%
8 181
 
2.6%
Other values (2) 176
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6977
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2389
34.2%
. 1516
21.7%
3 607
 
8.7%
1 518
 
7.4%
2 413
 
5.9%
6 360
 
5.2%
5 299
 
4.3%
4 263
 
3.8%
9 255
 
3.7%
8 181
 
2.6%
Other values (2) 176
 
2.5%
Distinct259
Distinct (%)9.3%
Missing16
Missing (%)0.6%
Memory size22.1 KiB
2024-05-11T15:45:53.387105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1825652
Min length6

Characters and Unicode

Total characters17305
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

Unique55 ?
Unique (%)2.0%

Sample

1st row136808
2nd row136110
3rd row136877
4th row136800
5th row136817
ValueCountFrequency (%)
136110 94
 
3.4%
136800 89
 
3.2%
136865 87
 
3.1%
136130 68
 
2.4%
136817 54
 
1.9%
136075 51
 
1.8%
136051 44
 
1.6%
136-110 44
 
1.6%
136045 43
 
1.5%
136060 43
 
1.5%
Other values (249) 2182
78.0%
2024-05-11T15:45:54.092708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3774
21.8%
3 3503
20.2%
6 3343
19.3%
8 1705
9.9%
0 1702
9.8%
5 801
 
4.6%
7 638
 
3.7%
4 614
 
3.5%
- 511
 
3.0%
2 439
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16794
97.0%
Dash Punctuation 511
 
3.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3774
22.5%
3 3503
20.9%
6 3343
19.9%
8 1705
10.2%
0 1702
10.1%
5 801
 
4.8%
7 638
 
3.8%
4 614
 
3.7%
2 439
 
2.6%
9 275
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 511
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17305
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3774
21.8%
3 3503
20.2%
6 3343
19.3%
8 1705
9.9%
0 1702
9.8%
5 801
 
4.6%
7 638
 
3.7%
4 614
 
3.5%
- 511
 
3.0%
2 439
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17305
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3774
21.8%
3 3503
20.2%
6 3343
19.3%
8 1705
9.9%
0 1702
9.8%
5 801
 
4.6%
7 638
 
3.7%
4 614
 
3.5%
- 511
 
3.0%
2 439
 
2.5%
Distinct1531
Distinct (%)54.7%
Missing16
Missing (%)0.6%
Memory size22.1 KiB
2024-05-11T15:45:54.583311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length79
Median length60
Mean length27.812076
Min length17

Characters and Unicode

Total characters77846
Distinct characters406
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1132 ?
Unique (%)40.4%

Sample

1st row서울특별시 성북구 길음동 ****-*번지 홍신빌딩 ***호
2nd row서울특별시 성북구 길음동 ****-**번지 길음뉴타운*단지래미안상가 지하*층 *호
3rd row서울특별시 성북구 정릉동 ***-**번지 B ***호
4th row서울특별시 성북구 길음동 **-*번지
5th row서울특별시 성북구 석관동 ***-*번지
ValueCountFrequency (%)
서울특별시 2799
20.1%
성북구 2799
20.1%
번지 1650
11.8%
1119
 
8.0%
385
 
2.8%
정릉동 378
 
2.7%
길음동 343
 
2.5%
장위동 295
 
2.1%
하월곡동 290
 
2.1%
지상*층 280
 
2.0%
Other values (866) 3621
25.9%
2024-05-11T15:45:55.263114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 14333
18.4%
12988
16.7%
3506
 
4.5%
2965
 
3.8%
2892
 
3.7%
2830
 
3.6%
2811
 
3.6%
2805
 
3.6%
2802
 
3.6%
2799
 
3.6%
Other values (396) 27115
34.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 45500
58.4%
Other Punctuation 14669
 
18.8%
Space Separator 12988
 
16.7%
Dash Punctuation 1972
 
2.5%
Lowercase Letter 1528
 
2.0%
Close Punctuation 448
 
0.6%
Open Punctuation 448
 
0.6%
Decimal Number 157
 
0.2%
Uppercase Letter 124
 
0.2%
Math Symbol 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3506
 
7.7%
2965
 
6.5%
2892
 
6.4%
2830
 
6.2%
2811
 
6.2%
2805
 
6.2%
2802
 
6.2%
2799
 
6.2%
2799
 
6.2%
2135
 
4.7%
Other values (328) 17156
37.7%
Lowercase Letter
ValueCountFrequency (%)
w 290
19.0%
o 165
10.8%
c 111
 
7.3%
e 104
 
6.8%
r 103
 
6.7%
a 82
 
5.4%
k 81
 
5.3%
m 81
 
5.3%
t 71
 
4.6%
n 71
 
4.6%
Other values (15) 369
24.1%
Uppercase Letter
ValueCountFrequency (%)
B 39
31.5%
A 16
12.9%
S 9
 
7.3%
K 9
 
7.3%
H 8
 
6.5%
W 8
 
6.5%
V 4
 
3.2%
D 4
 
3.2%
C 4
 
3.2%
J 3
 
2.4%
Other values (10) 20
16.1%
Decimal Number
ValueCountFrequency (%)
1 32
20.4%
2 24
15.3%
3 21
13.4%
4 17
10.8%
6 15
9.6%
5 14
8.9%
0 13
8.3%
8 9
 
5.7%
7 8
 
5.1%
9 4
 
2.5%
Other Punctuation
ValueCountFrequency (%)
* 14333
97.7%
. 259
 
1.8%
, 33
 
0.2%
/ 24
 
0.2%
: 12
 
0.1%
@ 4
 
< 0.1%
? 2
 
< 0.1%
& 2
 
< 0.1%
Space Separator
ValueCountFrequency (%)
12988
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1972
100.0%
Close Punctuation
ValueCountFrequency (%)
) 448
100.0%
Open Punctuation
ValueCountFrequency (%)
( 448
100.0%
Math Symbol
ValueCountFrequency (%)
~ 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 45500
58.4%
Common 30694
39.4%
Latin 1652
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3506
 
7.7%
2965
 
6.5%
2892
 
6.4%
2830
 
6.2%
2811
 
6.2%
2805
 
6.2%
2802
 
6.2%
2799
 
6.2%
2799
 
6.2%
2135
 
4.7%
Other values (328) 17156
37.7%
Latin
ValueCountFrequency (%)
w 290
17.6%
o 165
 
10.0%
c 111
 
6.7%
e 104
 
6.3%
r 103
 
6.2%
a 82
 
5.0%
k 81
 
4.9%
m 81
 
4.9%
t 71
 
4.3%
n 71
 
4.3%
Other values (35) 493
29.8%
Common
ValueCountFrequency (%)
* 14333
46.7%
12988
42.3%
- 1972
 
6.4%
) 448
 
1.5%
( 448
 
1.5%
. 259
 
0.8%
, 33
 
0.1%
1 32
 
0.1%
2 24
 
0.1%
/ 24
 
0.1%
Other values (13) 133
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 45500
58.4%
ASCII 32346
41.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 14333
44.3%
12988
40.2%
- 1972
 
6.1%
) 448
 
1.4%
( 448
 
1.4%
w 290
 
0.9%
. 259
 
0.8%
o 165
 
0.5%
c 111
 
0.3%
e 104
 
0.3%
Other values (58) 1228
 
3.8%
Hangul
ValueCountFrequency (%)
3506
 
7.7%
2965
 
6.5%
2892
 
6.4%
2830
 
6.2%
2811
 
6.2%
2805
 
6.2%
2802
 
6.2%
2799
 
6.2%
2799
 
6.2%
2135
 
4.7%
Other values (328) 17156
37.7%

도로명주소
Text

MISSING 

Distinct1644
Distinct (%)73.2%
Missing568
Missing (%)20.2%
Memory size22.1 KiB
2024-05-11T15:45:55.692560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length84
Median length64
Mean length36.852247
Min length22

Characters and Unicode

Total characters82807
Distinct characters407
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

Unique1352 ?
Unique (%)60.2%

Sample

1st row서울특별시 성북구 길음로*길 *, 지하*층 *호 (길음동, 길음뉴타운*단지래미안상가)
2nd row서울특별시 성북구 보국문로 ** (정릉동,B ***호)
3rd row서울특별시 성북구 동소문로 *** (길음동)
4th row서울특별시 성북구 동소문로 *** (동선동*가)
5th row서울특별시 성북구 보문로 *** (삼선동*가,윤홍B.D (*층))
ValueCountFrequency (%)
서울특별시 2247
14.9%
성북구 2247
14.9%
2228
14.8%
945
 
6.3%
673
 
4.5%
452
 
3.0%
정릉동 263
 
1.7%
길음동 238
 
1.6%
종암동 220
 
1.5%
하월곡동 208
 
1.4%
Other values (1141) 5328
35.4%
2024-05-11T15:45:56.297653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 13928
 
16.8%
12811
 
15.5%
3537
 
4.3%
, 2789
 
3.4%
2485
 
3.0%
2481
 
3.0%
( 2458
 
3.0%
) 2458
 
3.0%
2281
 
2.8%
2276
 
2.7%
Other values (397) 35303
42.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 45757
55.3%
Other Punctuation 16999
 
20.5%
Space Separator 12811
 
15.5%
Open Punctuation 2458
 
3.0%
Close Punctuation 2458
 
3.0%
Lowercase Letter 1446
 
1.7%
Dash Punctuation 428
 
0.5%
Decimal Number 285
 
0.3%
Uppercase Letter 159
 
0.2%
Math Symbol 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3537
 
7.7%
2485
 
5.4%
2481
 
5.4%
2281
 
5.0%
2276
 
5.0%
2256
 
4.9%
2250
 
4.9%
2247
 
4.9%
2247
 
4.9%
2220
 
4.9%
Other values (330) 21477
46.9%
Lowercase Letter
ValueCountFrequency (%)
w 231
16.0%
o 151
 
10.4%
r 116
 
8.0%
e 111
 
7.7%
c 104
 
7.2%
a 85
 
5.9%
m 73
 
5.0%
t 70
 
4.8%
k 65
 
4.5%
n 61
 
4.2%
Other values (16) 379
26.2%
Uppercase Letter
ValueCountFrequency (%)
B 69
43.4%
A 26
 
16.4%
S 12
 
7.5%
K 10
 
6.3%
H 9
 
5.7%
V 4
 
2.5%
D 4
 
2.5%
T 4
 
2.5%
L 3
 
1.9%
C 3
 
1.9%
Other values (8) 15
 
9.4%
Decimal Number
ValueCountFrequency (%)
1 73
25.6%
0 50
17.5%
2 40
14.0%
4 31
10.9%
3 26
 
9.1%
5 21
 
7.4%
7 13
 
4.6%
6 11
 
3.9%
8 11
 
3.9%
9 9
 
3.2%
Other Punctuation
ValueCountFrequency (%)
* 13928
81.9%
, 2789
 
16.4%
. 212
 
1.2%
/ 44
 
0.3%
: 17
 
0.1%
? 4
 
< 0.1%
@ 4
 
< 0.1%
; 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
12811
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2458
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2458
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 428
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 45756
55.3%
Common 35445
42.8%
Latin 1605
 
1.9%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3537
 
7.7%
2485
 
5.4%
2481
 
5.4%
2281
 
5.0%
2276
 
5.0%
2256
 
4.9%
2250
 
4.9%
2247
 
4.9%
2247
 
4.9%
2220
 
4.9%
Other values (329) 21476
46.9%
Latin
ValueCountFrequency (%)
w 231
14.4%
o 151
 
9.4%
r 116
 
7.2%
e 111
 
6.9%
c 104
 
6.5%
a 85
 
5.3%
m 73
 
4.5%
t 70
 
4.4%
B 69
 
4.3%
k 65
 
4.0%
Other values (34) 530
33.0%
Common
ValueCountFrequency (%)
* 13928
39.3%
12811
36.1%
, 2789
 
7.9%
( 2458
 
6.9%
) 2458
 
6.9%
- 428
 
1.2%
. 212
 
0.6%
1 73
 
0.2%
0 50
 
0.1%
/ 44
 
0.1%
Other values (13) 194
 
0.5%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 45756
55.3%
ASCII 37050
44.7%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 13928
37.6%
12811
34.6%
, 2789
 
7.5%
( 2458
 
6.6%
) 2458
 
6.6%
- 428
 
1.2%
w 231
 
0.6%
. 212
 
0.6%
o 151
 
0.4%
r 116
 
0.3%
Other values (57) 1468
 
4.0%
Hangul
ValueCountFrequency (%)
3537
 
7.7%
2485
 
5.4%
2481
 
5.4%
2281
 
5.0%
2276
 
5.0%
2256
 
4.9%
2250
 
4.9%
2247
 
4.9%
2247
 
4.9%
2220
 
4.9%
Other values (329) 21476
46.9%
CJK
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct170
Distinct (%)7.7%
Missing619
Missing (%)22.0%
Infinite0
Infinite (%)0.0%
Mean2788.2819
Minimum2700
Maximum2880
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.9 KiB
2024-05-11T15:45:56.509028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2700
5-th percentile2712
Q12740
median2791
Q32831
95-th percentile2866
Maximum2880
Range180
Interquartile range (IQR)91

Descriptive statistics

Standard deviation51.176823
Coefficient of variation (CV)0.01835425
Kurtosis-1.2486037
Mean2788.2819
Median Absolute Deviation (MAD)43
Skewness-0.010060953
Sum6123067
Variance2619.0672
MonotonicityNot monotonic
2024-05-11T15:45:56.789484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2730 66
 
2.3%
2751 64
 
2.3%
2831 47
 
1.7%
2829 47
 
1.7%
2845 40
 
1.4%
2717 39
 
1.4%
2797 37
 
1.3%
2781 36
 
1.3%
2860 32
 
1.1%
2830 32
 
1.1%
Other values (160) 1756
62.4%
(Missing) 619
 
22.0%
ValueCountFrequency (%)
2700 8
 
0.3%
2701 11
0.4%
2702 22
0.8%
2705 5
 
0.2%
2707 1
 
< 0.1%
2708 10
0.4%
2709 18
0.6%
2710 20
0.7%
2711 12
0.4%
2712 8
 
0.3%
ValueCountFrequency (%)
2880 20
0.7%
2879 5
 
0.2%
2877 4
 
0.1%
2876 1
 
< 0.1%
2875 4
 
0.1%
2874 23
0.8%
2873 14
0.5%
2872 13
0.5%
2871 10
0.4%
2870 3
 
0.1%
Distinct2625
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Memory size22.1 KiB
2024-05-11T15:45:57.133451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length41
Mean length7.0191829
Min length1

Characters and Unicode

Total characters19759
Distinct characters750
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2514 ?
Unique (%)89.3%

Sample

1st row달톤비알엠
2nd row준재활의학과
3rd row한국인삼공사정관장홍삼정릉점
4th row(주)현대백화점 미아점
5th row(주)미건뉴라이프
ValueCountFrequency (%)
주식회사 46
 
1.4%
세븐일레븐 24
 
0.7%
하이다이어트 17
 
0.5%
다이어트 12
 
0.4%
인셀덤 12
 
0.4%
허브다이어트 11
 
0.3%
씽킹빅 10
 
0.3%
gs25 9
 
0.3%
훼미리마트 9
 
0.3%
코리아 9
 
0.3%
Other values (2824) 3151
95.2%
2024-05-11T15:45:57.692051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
790
 
4.0%
514
 
2.6%
495
 
2.5%
) 469
 
2.4%
( 468
 
2.4%
383
 
1.9%
371
 
1.9%
320
 
1.6%
313
 
1.6%
299
 
1.5%
Other values (740) 15337
77.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16431
83.2%
Lowercase Letter 930
 
4.7%
Uppercase Letter 564
 
2.9%
Space Separator 495
 
2.5%
Close Punctuation 470
 
2.4%
Open Punctuation 469
 
2.4%
Decimal Number 274
 
1.4%
Other Punctuation 119
 
0.6%
Dash Punctuation 4
 
< 0.1%
Connector Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
790
 
4.8%
514
 
3.1%
383
 
2.3%
371
 
2.3%
320
 
1.9%
313
 
1.9%
299
 
1.8%
271
 
1.6%
239
 
1.5%
227
 
1.4%
Other values (664) 12704
77.3%
Uppercase Letter
ValueCountFrequency (%)
S 101
17.9%
G 91
16.1%
B 30
 
5.3%
H 28
 
5.0%
A 25
 
4.4%
C 24
 
4.3%
M 24
 
4.3%
K 23
 
4.1%
O 22
 
3.9%
L 21
 
3.7%
Other values (15) 175
31.0%
Lowercase Letter
ValueCountFrequency (%)
o 101
 
10.9%
e 99
 
10.6%
a 76
 
8.2%
r 73
 
7.8%
t 68
 
7.3%
l 54
 
5.8%
s 47
 
5.1%
n 45
 
4.8%
m 42
 
4.5%
i 39
 
4.2%
Other values (15) 286
30.8%
Decimal Number
ValueCountFrequency (%)
2 90
32.8%
5 84
30.7%
4 22
 
8.0%
0 19
 
6.9%
3 16
 
5.8%
1 15
 
5.5%
9 10
 
3.6%
6 10
 
3.6%
8 6
 
2.2%
7 2
 
0.7%
Other Punctuation
ValueCountFrequency (%)
. 60
50.4%
/ 27
22.7%
& 12
 
10.1%
: 7
 
5.9%
? 5
 
4.2%
, 5
 
4.2%
' 2
 
1.7%
! 1
 
0.8%
Close Punctuation
ValueCountFrequency (%)
) 469
99.8%
] 1
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 468
99.8%
[ 1
 
0.2%
Space Separator
ValueCountFrequency (%)
495
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16431
83.2%
Common 1834
 
9.3%
Latin 1494
 
7.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
790
 
4.8%
514
 
3.1%
383
 
2.3%
371
 
2.3%
320
 
1.9%
313
 
1.9%
299
 
1.8%
271
 
1.6%
239
 
1.5%
227
 
1.4%
Other values (664) 12704
77.3%
Latin
ValueCountFrequency (%)
S 101
 
6.8%
o 101
 
6.8%
e 99
 
6.6%
G 91
 
6.1%
a 76
 
5.1%
r 73
 
4.9%
t 68
 
4.6%
l 54
 
3.6%
s 47
 
3.1%
n 45
 
3.0%
Other values (40) 739
49.5%
Common
ValueCountFrequency (%)
495
27.0%
) 469
25.6%
( 468
25.5%
2 90
 
4.9%
5 84
 
4.6%
. 60
 
3.3%
/ 27
 
1.5%
4 22
 
1.2%
0 19
 
1.0%
3 16
 
0.9%
Other values (16) 84
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16431
83.2%
ASCII 3328
 
16.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
790
 
4.8%
514
 
3.1%
383
 
2.3%
371
 
2.3%
320
 
1.9%
313
 
1.9%
299
 
1.8%
271
 
1.6%
239
 
1.5%
227
 
1.4%
Other values (664) 12704
77.3%
ASCII
ValueCountFrequency (%)
495
 
14.9%
) 469
 
14.1%
( 468
 
14.1%
S 101
 
3.0%
o 101
 
3.0%
e 99
 
3.0%
G 91
 
2.7%
2 90
 
2.7%
5 84
 
2.5%
a 76
 
2.3%
Other values (66) 1254
37.7%
Distinct2692
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Memory size22.1 KiB
Minimum2004-04-30 00:00:00
Maximum2024-05-09 11:33:50
2024-05-11T15:45:57.846937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:45:58.035935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.1 KiB
I
1973 
U
842 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 1973
70.1%
U 842
29.9%

Length

2024-05-11T15:45:58.221007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:45:58.342468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1973
70.1%
u 842
29.9%
Distinct821
Distinct (%)29.2%
Missing0
Missing (%)0.0%
Memory size22.1 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T15:45:58.486965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:45:58.686461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2815
Missing (%)100.0%
Memory size24.9 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1592
Distinct (%)57.2%
Missing31
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean202403.77
Minimum199058.36
Maximum206112.46
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.9 KiB
2024-05-11T15:45:59.254104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum199058.36
5-th percentile200424.64
Q1201260.32
median202048.6
Q3203319.55
95-th percentile205288.24
Maximum206112.46
Range7054.1001
Interquartile range (IQR)2059.2271

Descriptive statistics

Standard deviation1505.0741
Coefficient of variation (CV)0.0074359986
Kurtosis-0.58865209
Mean202403.77
Median Absolute Deviation (MAD)1029.3323
Skewness0.53379232
Sum5.6349209 × 108
Variance2265248.2
MonotonicityNot monotonic
2024-05-11T15:45:59.460959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
200841.726990037 69
 
2.5%
202466.801104742 45
 
1.6%
203318.127254872 33
 
1.2%
203196.800963466 23
 
0.8%
203502.004139568 23
 
0.8%
202029.981799661 21
 
0.7%
205996.717928956 16
 
0.6%
201356.035379848 16
 
0.6%
201989.271689499 15
 
0.5%
200575.420521471 14
 
0.5%
Other values (1582) 2509
89.1%
(Missing) 31
 
1.1%
ValueCountFrequency (%)
199058.357470878 1
< 0.1%
199168.933415021 1
< 0.1%
199189.75153862 2
0.1%
199232.734942377 1
< 0.1%
199259.131263184 1
< 0.1%
199296.947862442 1
< 0.1%
199341.337774579 1
< 0.1%
199351.832787571 1
< 0.1%
199472.125987292 1
< 0.1%
199503.759472612 1
< 0.1%
ValueCountFrequency (%)
206112.457605113 1
 
< 0.1%
205996.717928956 16
0.6%
205818.852385165 5
 
0.2%
205812.674232907 1
 
< 0.1%
205811.749025593 1
 
< 0.1%
205780.478583532 1
 
< 0.1%
205771.272436364 1
 
< 0.1%
205764.586797298 1
 
< 0.1%
205741.721911974 1
 
< 0.1%
205738.912486727 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1592
Distinct (%)57.2%
Missing31
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean455492.74
Minimum452880.96
Maximum457988.51
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.9 KiB
2024-05-11T15:45:59.641461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum452880.96
5-th percentile453576.8
Q1454596.24
median455662.3
Q3456364.54
95-th percentile457110.02
Maximum457988.51
Range5107.5528
Interquartile range (IQR)1768.3019

Descriptive statistics

Standard deviation1108.3981
Coefficient of variation (CV)0.0024334045
Kurtosis-0.80255914
Mean455492.74
Median Absolute Deviation (MAD)855.1243
Skewness-0.28851601
Sum1.2680918 × 109
Variance1228546.3
MonotonicityNot monotonic
2024-05-11T15:45:59.822059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
454721.505180141 69
 
2.5%
456227.571665528 45
 
1.6%
456078.982123486 33
 
1.2%
455429.846270094 23
 
0.8%
455500.568972657 23
 
0.8%
455605.716911266 21
 
0.7%
456704.522324447 16
 
0.6%
456606.133621913 16
 
0.6%
455190.095862939 15
 
0.5%
457360.617372111 14
 
0.5%
Other values (1582) 2509
89.1%
(Missing) 31
 
1.1%
ValueCountFrequency (%)
452880.956723 1
 
< 0.1%
452903.25426846 1
 
< 0.1%
452935.221547454 2
0.1%
452939.911556 1
 
< 0.1%
452989.825481836 1
 
< 0.1%
452998.923564259 1
 
< 0.1%
453033.736082626 1
 
< 0.1%
453035.833489802 1
 
< 0.1%
453049.758964542 1
 
< 0.1%
453050.036188994 3
0.1%
ValueCountFrequency (%)
457988.509545404 1
 
< 0.1%
457873.129406188 1
 
< 0.1%
457844.348010616 14
0.5%
457726.529033725 1
 
< 0.1%
457726.528994544 1
 
< 0.1%
457583.354969729 1
 
< 0.1%
457581.254031821 1
 
< 0.1%
457579.21641655 4
 
0.1%
457566.403205181 1
 
< 0.1%
457548.670426757 1
 
< 0.1%

위생업태명
Categorical

Distinct10
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size22.1 KiB
영업장판매
1168 
<NA>
748 
전자상거래(통신판매업)
546 
다단계판매
154 
방문판매
133 
Other values (5)
 
66

Length

Max length14
Median length12
Mean length6.0468917
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업장판매 1168
41.5%
<NA> 748
26.6%
전자상거래(통신판매업) 546
19.4%
다단계판매 154
 
5.5%
방문판매 133
 
4.7%
통신판매 50
 
1.8%
전화권유판매 6
 
0.2%
도매업(유통) 4
 
0.1%
기타 건강기능식품일반판매업 4
 
0.1%
기타(복합 등) 2
 
0.1%

Length

2024-05-11T15:45:59.973104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:46:00.129082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업장판매 1168
41.4%
na 748
26.5%
전자상거래(통신판매업 546
19.4%
다단계판매 154
 
5.5%
방문판매 133
 
4.7%
통신판매 50
 
1.8%
전화권유판매 6
 
0.2%
도매업(유통 4
 
0.1%
기타 4
 
0.1%
건강기능식품일반판매업 4
 
0.1%
Other values (2) 4
 
0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.1 KiB
<NA>
2647 
0
 
168

Length

Max length4
Median length4
Mean length3.8209591
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> 2647
94.0%
0 168
 
6.0%

Length

2024-05-11T15:46:00.301304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:46:00.425759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2647
94.0%
0 168
 
6.0%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.1 KiB
<NA>
2647 
0
 
168

Length

Max length4
Median length4
Mean length3.8209591
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> 2647
94.0%
0 168
 
6.0%

Length

2024-05-11T15:46:00.574348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:46:00.704349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2647
94.0%
0 168
 
6.0%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2815
Missing (%)100.0%
Memory size24.9 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2815
Missing (%)100.0%
Memory size24.9 KiB

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.1 KiB
<NA>
2667 
상수도전용
 
148

Length

Max length5
Median length4
Mean length4.0525755
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2667
94.7%
상수도전용 148
 
5.3%

Length

2024-05-11T15:46:00.861040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:46:00.985974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2667
94.7%
상수도전용 148
 
5.3%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.1 KiB
<NA>
2648 
0
 
167

Length

Max length4
Median length4
Mean length3.8220249
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> 2648
94.1%
0 167
 
5.9%

Length

2024-05-11T15:46:01.142438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:46:01.344924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2648
94.1%
0 167
 
5.9%

본사종업원수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct8
Distinct (%)1.0%
Missing2000
Missing (%)71.0%
Infinite0
Infinite (%)0.0%
Mean0.41226994
Minimum0
Maximum300
Zeros803
Zeros (%)28.5%
Negative0
Negative (%)0.0%
Memory size24.9 KiB
2024-05-11T15:46:01.471929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum300
Range300
Interquartile range (IQR)0

Descriptive statistics

Standard deviation10.520337
Coefficient of variation (CV)25.518079
Kurtosis810.85944
Mean0.41226994
Median Absolute Deviation (MAD)0
Skewness28.441654
Sum336
Variance110.67749
MonotonicityNot monotonic
2024-05-11T15:46:01.679813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 803
28.5%
1 4
 
0.1%
2 3
 
0.1%
300 1
 
< 0.1%
3 1
 
< 0.1%
12 1
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
(Missing) 2000
71.0%
ValueCountFrequency (%)
0 803
28.5%
1 4
 
0.1%
2 3
 
0.1%
3 1
 
< 0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
12 1
 
< 0.1%
300 1
 
< 0.1%
ValueCountFrequency (%)
300 1
 
< 0.1%
12 1
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
3 1
 
< 0.1%
2 3
 
0.1%
1 4
 
0.1%
0 803
28.5%

공장사무직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)1.2%
Missing2000
Missing (%)71.0%
Infinite0
Infinite (%)0.0%
Mean0.16687117
Minimum0
Maximum30
Zeros780
Zeros (%)27.7%
Negative0
Negative (%)0.0%
Memory size24.9 KiB
2024-05-11T15:46:01.820552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum30
Range30
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.3973059
Coefficient of variation (CV)8.3735611
Kurtosis284.94536
Mean0.16687117
Median Absolute Deviation (MAD)0
Skewness15.279484
Sum136
Variance1.9524638
MonotonicityNot monotonic
2024-05-11T15:46:01.969304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 780
 
27.7%
1 14
 
0.5%
2 8
 
0.3%
5 4
 
0.1%
4 3
 
0.1%
3 2
 
0.1%
30 1
 
< 0.1%
12 1
 
< 0.1%
10 1
 
< 0.1%
16 1
 
< 0.1%
(Missing) 2000
71.0%
ValueCountFrequency (%)
0 780
27.7%
1 14
 
0.5%
2 8
 
0.3%
3 2
 
0.1%
4 3
 
0.1%
5 4
 
0.1%
10 1
 
< 0.1%
12 1
 
< 0.1%
16 1
 
< 0.1%
30 1
 
< 0.1%
ValueCountFrequency (%)
30 1
 
< 0.1%
16 1
 
< 0.1%
12 1
 
< 0.1%
10 1
 
< 0.1%
5 4
 
0.1%
4 3
 
0.1%
3 2
 
0.1%
2 8
 
0.3%
1 14
 
0.5%
0 780
27.7%

공장판매직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct20
Distinct (%)2.5%
Missing2000
Missing (%)71.0%
Infinite0
Infinite (%)0.0%
Mean0.73128834
Minimum0
Maximum77
Zeros696
Zeros (%)24.7%
Negative0
Negative (%)0.0%
Memory size24.9 KiB
2024-05-11T15:46:02.147087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum77
Range77
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.2284505
Coefficient of variation (CV)5.7821932
Kurtosis170.23054
Mean0.73128834
Median Absolute Deviation (MAD)0
Skewness11.666879
Sum596
Variance17.879794
MonotonicityNot monotonic
2024-05-11T15:46:02.346657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 696
 
24.7%
1 58
 
2.1%
2 21
 
0.7%
3 10
 
0.4%
4 6
 
0.2%
20 3
 
0.1%
12 3
 
0.1%
15 2
 
0.1%
10 2
 
0.1%
8 2
 
0.1%
Other values (10) 12
 
0.4%
(Missing) 2000
71.0%
ValueCountFrequency (%)
0 696
24.7%
1 58
 
2.1%
2 21
 
0.7%
3 10
 
0.4%
4 6
 
0.2%
5 2
 
0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
8 2
 
0.1%
10 2
 
0.1%
ValueCountFrequency (%)
77 1
 
< 0.1%
50 1
 
< 0.1%
44 1
 
< 0.1%
30 1
 
< 0.1%
21 1
 
< 0.1%
20 3
0.1%
15 2
0.1%
13 1
 
< 0.1%
12 3
0.1%
11 2
0.1%

공장생산직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)1.2%
Missing2000
Missing (%)71.0%
Infinite0
Infinite (%)0.0%
Mean0.1398773
Minimum0
Maximum15
Zeros779
Zeros (%)27.7%
Negative0
Negative (%)0.0%
Memory size24.9 KiB
2024-05-11T15:46:02.535684image/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 deviation0.98268423
Coefficient of variation (CV)7.0253302
Kurtosis121.09092
Mean0.1398773
Median Absolute Deviation (MAD)0
Skewness10.260131
Sum114
Variance0.96566829
MonotonicityNot monotonic
2024-05-11T15:46:02.703330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 779
 
27.7%
1 20
 
0.7%
4 4
 
0.1%
3 3
 
0.1%
2 2
 
0.1%
10 2
 
0.1%
5 2
 
0.1%
12 1
 
< 0.1%
8 1
 
< 0.1%
15 1
 
< 0.1%
(Missing) 2000
71.0%
ValueCountFrequency (%)
0 779
27.7%
1 20
 
0.7%
2 2
 
0.1%
3 3
 
0.1%
4 4
 
0.1%
5 2
 
0.1%
8 1
 
< 0.1%
10 2
 
0.1%
12 1
 
< 0.1%
15 1
 
< 0.1%
ValueCountFrequency (%)
15 1
 
< 0.1%
12 1
 
< 0.1%
10 2
 
0.1%
8 1
 
< 0.1%
5 2
 
0.1%
4 4
 
0.1%
3 3
 
0.1%
2 2
 
0.1%
1 20
 
0.7%
0 779
27.7%
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.1 KiB
<NA>
1546 
자가
952 
임대
317 

Length

Max length4
Median length4
Mean length3.0984014
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row임대
2nd row임대
3rd row임대
4th row자가
5th row임대

Common Values

ValueCountFrequency (%)
<NA> 1546
54.9%
자가 952
33.8%
임대 317
 
11.3%

Length

2024-05-11T15:46:02.899294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:46:03.063594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1546
54.9%
자가 952
33.8%
임대 317
 
11.3%

보증액
Real number (ℝ)

MISSING  ZEROS 

Distinct30
Distinct (%)8.4%
Missing2456
Missing (%)87.2%
Infinite0
Infinite (%)0.0%
Mean13070100
Minimum0
Maximum5.3 × 108
Zeros271
Zeros (%)9.6%
Negative0
Negative (%)0.0%
Memory size24.9 KiB
2024-05-11T15:46:03.208751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile67300000
Maximum5.3 × 108
Range5.3 × 108
Interquartile range (IQR)0

Descriptive statistics

Standard deviation46913738
Coefficient of variation (CV)3.5893938
Kurtosis63.613586
Mean13070100
Median Absolute Deviation (MAD)0
Skewness7.1136701
Sum4.692166 × 109
Variance2.2008988 × 1015
MonotonicityNot monotonic
2024-05-11T15:46:03.436776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 271
 
9.6%
50000000 14
 
0.5%
10000000 12
 
0.4%
20000000 9
 
0.3%
15000000 8
 
0.3%
5000000 6
 
0.2%
30000000 5
 
0.2%
100000000 4
 
0.1%
40000000 4
 
0.1%
80000000 2
 
0.1%
Other values (20) 24
 
0.9%
(Missing) 2456
87.2%
ValueCountFrequency (%)
0 271
9.6%
1000000 2
 
0.1%
2000000 1
 
< 0.1%
2100000 1
 
< 0.1%
3000000 2
 
0.1%
5000000 6
 
0.2%
10000000 12
 
0.4%
15000000 8
 
0.3%
17000000 1
 
< 0.1%
20000000 9
 
0.3%
ValueCountFrequency (%)
530000000 1
< 0.1%
440000000 1
< 0.1%
280000000 1
< 0.1%
200000000 1
< 0.1%
192000000 1
< 0.1%
158000000 1
< 0.1%
150000000 1
< 0.1%
145000000 1
< 0.1%
130000000 1
< 0.1%
105566000 1
< 0.1%

월세액
Real number (ℝ)

MISSING  ZEROS 

Distinct44
Distinct (%)12.6%
Missing2466
Missing (%)87.6%
Infinite0
Infinite (%)0.0%
Mean315457.02
Minimum0
Maximum6000000
Zeros271
Zeros (%)9.6%
Negative0
Negative (%)0.0%
Memory size24.9 KiB
2024-05-11T15:46:03.716743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1842000
Maximum6000000
Range6000000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation833120.57
Coefficient of variation (CV)2.6409955
Kurtosis21.120158
Mean315457.02
Median Absolute Deviation (MAD)0
Skewness4.1009635
Sum1.100945 × 108
Variance6.9408988 × 1011
MonotonicityNot monotonic
2024-05-11T15:46:03.928697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
0 271
 
9.6%
1500000 6
 
0.2%
1000000 6
 
0.2%
600000 5
 
0.2%
1200000 4
 
0.1%
200000 4
 
0.1%
500000 4
 
0.1%
1100000 3
 
0.1%
6000000 3
 
0.1%
700000 3
 
0.1%
Other values (34) 40
 
1.4%
(Missing) 2466
87.6%
ValueCountFrequency (%)
0 271
9.6%
400 1
 
< 0.1%
200000 4
 
0.1%
247500 1
 
< 0.1%
300000 2
 
0.1%
350000 1
 
< 0.1%
450000 2
 
0.1%
500000 4
 
0.1%
550000 1
 
< 0.1%
600000 5
 
0.2%
ValueCountFrequency (%)
6000000 3
0.1%
5000000 1
 
< 0.1%
3000000 1
 
< 0.1%
2970000 1
 
< 0.1%
2800000 1
 
< 0.1%
2700000 2
0.1%
2500000 2
0.1%
2400000 1
 
< 0.1%
2300000 1
 
< 0.1%
2200000 1
 
< 0.1%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.1%
Missing748
Missing (%)26.6%
Memory size5.6 KiB
False
2066 
True
 
1
(Missing)
748 
ValueCountFrequency (%)
False 2066
73.4%
True 1
 
< 0.1%
(Missing) 748
 
26.6%
2024-05-11T15:46:04.123731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct15
Distinct (%)0.7%
Missing748
Missing (%)26.6%
Infinite0
Infinite (%)0.0%
Mean0.31619739
Minimum0
Maximum162.89
Zeros2047
Zeros (%)72.7%
Negative0
Negative (%)0.0%
Memory size24.9 KiB
2024-05-11T15:46:04.289390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum162.89
Range162.89
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5.2716416
Coefficient of variation (CV)16.671996
Kurtosis613.58551
Mean0.31619739
Median Absolute Deviation (MAD)0
Skewness23.275761
Sum653.58
Variance27.790205
MonotonicityNot monotonic
2024-05-11T15:46:04.480981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0.0 2047
72.7%
3.3 3
 
0.1%
6.6 2
 
0.1%
30.0 2
 
0.1%
10.0 2
 
0.1%
3.0 2
 
0.1%
33.0 1
 
< 0.1%
122.0 1
 
< 0.1%
27.1 1
 
< 0.1%
34.55 1
 
< 0.1%
Other values (5) 5
 
0.2%
(Missing) 748
 
26.6%
ValueCountFrequency (%)
0.0 2047
72.7%
1.0 1
 
< 0.1%
3.0 2
 
0.1%
3.3 3
 
0.1%
6.6 2
 
0.1%
10.0 2
 
0.1%
18.18 1
 
< 0.1%
27.1 1
 
< 0.1%
30.0 2
 
0.1%
33.0 1
 
< 0.1%
ValueCountFrequency (%)
162.89 1
< 0.1%
122.0 1
< 0.1%
79.76 1
< 0.1%
66.0 1
< 0.1%
34.55 1
< 0.1%
33.0 1
< 0.1%
30.0 2
0.1%
27.1 1
< 0.1%
18.18 1
< 0.1%
10.0 2
0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2815
Missing (%)100.0%
Memory size24.9 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2815
Missing (%)100.0%
Memory size24.9 KiB

홈페이지
Text

MISSING 

Distinct32
Distinct (%)100.0%
Missing2783
Missing (%)98.9%
Memory size22.1 KiB
2024-05-11T15:46:04.823548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length21
Mean length17.9375
Min length11

Characters and Unicode

Total characters574
Distinct characters58
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)100.0%

Sample

1st rowwww.건강식품.org, 휴먼밸류.com
2nd rowwww.welllife99.co.kr
3rd rowcafe.daum.net/beeloveyou
4th rowwww.jungmall.co.kr
5th rowwww.cutcutprice.com
ValueCountFrequency (%)
www.건강식품.org 1
 
3.0%
www.goodmorninghealth.co.kr 1
 
3.0%
www.cscross.com 1
 
3.0%
www.dietld.com 1
 
3.0%
www.japanarenue.co.kr 1
 
3.0%
www.sinjjang.com 1
 
3.0%
www.petogen.co.kr 1
 
3.0%
www.kongjame.com 1
 
3.0%
www.wbholsagi.com 1
 
3.0%
www.barokoc.com 1
 
3.0%
Other values (23) 23
69.7%
2024-05-11T15:46:05.330792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
w 90
15.7%
. 76
13.2%
o 55
 
9.6%
c 42
 
7.3%
e 28
 
4.9%
m 27
 
4.7%
a 26
 
4.5%
r 25
 
4.4%
n 20
 
3.5%
l 18
 
3.1%
Other values (48) 167
29.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 458
79.8%
Other Punctuation 81
 
14.1%
Other Letter 16
 
2.8%
Uppercase Letter 15
 
2.6%
Decimal Number 3
 
0.5%
Space Separator 1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 90
19.7%
o 55
12.0%
c 42
 
9.2%
e 28
 
6.1%
m 27
 
5.9%
a 26
 
5.7%
r 25
 
5.5%
n 20
 
4.4%
l 18
 
3.9%
k 17
 
3.7%
Other values (13) 110
24.0%
Other Letter
ValueCountFrequency (%)
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
Other values (6) 6
37.5%
Uppercase Letter
ValueCountFrequency (%)
W 3
20.0%
U 2
13.3%
H 1
 
6.7%
T 1
 
6.7%
E 1
 
6.7%
S 1
 
6.7%
Y 1
 
6.7%
C 1
 
6.7%
B 1
 
6.7%
O 1
 
6.7%
Other values (2) 2
13.3%
Other Punctuation
ValueCountFrequency (%)
. 76
93.8%
/ 3
 
3.7%
: 1
 
1.2%
, 1
 
1.2%
Decimal Number
ValueCountFrequency (%)
9 2
66.7%
1 1
33.3%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 473
82.4%
Common 85
 
14.8%
Hangul 16
 
2.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 90
19.0%
o 55
11.6%
c 42
 
8.9%
e 28
 
5.9%
m 27
 
5.7%
a 26
 
5.5%
r 25
 
5.3%
n 20
 
4.2%
l 18
 
3.8%
k 17
 
3.6%
Other values (25) 125
26.4%
Hangul
ValueCountFrequency (%)
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
Other values (6) 6
37.5%
Common
ValueCountFrequency (%)
. 76
89.4%
/ 3
 
3.5%
9 2
 
2.4%
1 1
 
1.2%
: 1
 
1.2%
, 1
 
1.2%
1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 558
97.2%
Hangul 16
 
2.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w 90
16.1%
. 76
13.6%
o 55
 
9.9%
c 42
 
7.5%
e 28
 
5.0%
m 27
 
4.8%
a 26
 
4.7%
r 25
 
4.5%
n 20
 
3.6%
l 18
 
3.2%
Other values (32) 151
27.1%
Hangul
ValueCountFrequency (%)
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
Other values (6) 6
37.5%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030700003070000-134-2004-0000120040402<NA>3폐업2폐업20070605<NA><NA><NA>02 916141636.90136808서울특별시 성북구 길음동 ****-*번지 홍신빌딩 ***호<NA><NA>달톤비알엠2005-07-14 00:00:00I2018-08-31 23:59:59.0<NA>202029.72166455989.73388영업장판매<NA><NA><NA><NA>상수도전용<NA>0010임대3000000300000N0.0<NA><NA><NA>
130700003070000-134-2004-0000220040409<NA>1영업/정상1영업<NA><NA><NA><NA>02 911011923.57136110서울특별시 성북구 길음동 ****-**번지 길음뉴타운*단지래미안상가 지하*층 *호서울특별시 성북구 길음로*길 *, 지하*층 *호 (길음동, 길음뉴타운*단지래미안상가)2721준재활의학과2017-10-29 14:44:42I2018-08-31 23:59:59.0<NA>201912.435616455775.861032영업장판매<NA><NA><NA><NA><NA><NA>0010임대10000000247500N0.0<NA><NA><NA>
230700003070000-134-2004-0000320040414<NA>1영업/정상1영업<NA><NA><NA><NA>02 913230451.87136877서울특별시 성북구 정릉동 ***-**번지 B ***호서울특별시 성북구 보국문로 ** (정릉동,B ***호)2717한국인삼공사정관장홍삼정릉점2017-07-27 17:02:02I2018-08-31 23:59:59.0<NA>200824.604255456284.330878영업장판매<NA><NA><NA><NA>상수도전용<NA>0020임대1000000001900000N0.0<NA><NA><NA>
330700003070000-134-2004-0000420040424<NA>1영업/정상1영업<NA><NA><NA><NA>022117100387.86136800서울특별시 성북구 길음동 **-*번지서울특별시 성북구 동소문로 *** (길음동)2730(주)현대백화점 미아점2020-04-14 15:16:43U2020-04-16 02:40:00.0<NA>202466.801105456227.571666영업장판매<NA><NA><NA><NA>상수도전용<NA>0030자가<NA><NA>N0.0<NA><NA><NA>
430700003070000-134-2004-0000520040430<NA>3폐업2폐업20041129<NA><NA><NA>02 9690887165.00136817서울특별시 성북구 석관동 ***-*번지<NA><NA>(주)미건뉴라이프2004-04-30 00:00:00I2018-08-31 23:59:59.0<NA>205288.23944456677.726693영업장판매<NA><NA><NA><NA>상수도전용<NA>0000임대00N0.0<NA><NA><NA>
530700003070000-134-2004-0000620040511<NA>3폐업2폐업20121018<NA><NA><NA>02 9252055194.00136051서울특별시 성북구 동선동*가 ***-*번지서울특별시 성북구 동소문로 *** (동선동*가)2845코오롱웰케어(주)2009-07-13 11:33:49I2018-08-31 23:59:59.0<NA>201536.883549454556.210969영업장판매<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
630700003070000-134-2004-0000720040513<NA>3폐업2폐업20050124<NA><NA><NA>02 9223835198.00136860서울특별시 성북구 종암동 **-**번지<NA><NA>아모레보문점2004-05-13 00:00:00I2018-08-31 23:59:59.0<NA>203050.965165454804.168918방문판매<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA>
730700003070000-134-2004-0000820040514<NA>1영업/정상1영업<NA><NA><NA><NA>02 92306716.60136045서울특별시 성북구 삼선동*가 *** 윤홍B.D (*층)서울특별시 성북구 보문로 *** (삼선동*가,윤홍B.D (*층))2848아모레성북특약점2020-12-15 11:41:37U2020-12-17 02:40:00.0<NA>201494.411783454018.193574방문판매<NA><NA><NA><NA>상수도전용<NA>05770임대192000000<NA>N0.0<NA><NA><NA>
830700003070000-134-2004-0000920040514<NA>3폐업2폐업20221025<NA><NA><NA>02 961 6860248.52136818서울특별시 성북구 석관동 ***-*서울특별시 성북구 화랑로 *** (석관동)2783아모레드림특약점2022-10-25 14:38:45U2021-10-30 22:07:00.0<NA>205205.245652456629.619923<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
930700003070000-134-2004-0001020040518<NA>1영업/정상1영업<NA><NA><NA><NA>02 94223416.50136828서울특별시 성북구 장위동 **-***서울특별시 성북구 돌곶이로**길 **, ***호 (장위동)2770생그린한방화장품2021-04-22 16:12:53U2021-04-24 02:40:00.0<NA>204564.170445456497.589122방문판매<NA><NA><NA><NA>상수도전용<NA>0000임대10000000800000N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
280530700003070000-134-2024-000412024-04-15<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>136-719서울특별시 성북구 길음동 **-* 현대백화점미아점서울특별시 성북구 동소문로 ***, 현대백화점미아점 지하*층 (길음동)2730호랑이건강원에프앤비 주식회사2024-04-15 14:44:53I2023-12-03 23:07:00.0<NA>202466.801085456227.571721<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
280630700003070000-134-2024-000422024-04-15<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>136-824서울특별시 성북구 성북동 ***-*서울특별시 성북구 성북로**길 **, *층 (성북동)2879헤이밍2024-04-17 13:18:05I2023-12-03 23:09:00.0<NA>199472.125987454492.057879<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
280730700003070000-134-2024-000432024-04-17<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>136-832서울특별시 성북구 장위동 ***-* 석산빌딩서울특별시 성북구 한천로 ***, 석산빌딩 *층 ***호 (장위동)2759위루나(OuiLunar)2024-04-17 13:50:42I2023-12-03 23:09:00.0<NA>204481.191679457726.529034<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
280830700003070000-134-2024-000442024-04-23<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>136-090서울특별시 성북구 종암동 *** 래미안세레니티서울특별시 성북구 종암로**길 **, ***동 ****호 (종암동, 래미안세레니티)2804가든그로브2024-04-23 13:24:39I2023-12-03 22:05:00.0<NA>202672.454331455214.336583<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
280930700003070000-134-2024-000452024-04-24<NA>1영업/정상1영업<NA><NA><NA><NA><NA>12.00136-819서울특별시 성북구 석관동 ***-***서울특별시 성북구 돌곶이로 **, *층 (석관동)2788윤채네2024-04-24 10:20:39I2023-12-03 22:06:00.0<NA>205356.049058455981.897389<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
281030700003070000-134-2024-000462024-04-23<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>136-036서울특별시 성북구 동소문동*가 ***-* 기업은행서울특별시 성북구 아리랑로 *, 기업은행 *층 (동소문동*가)2830365엠씨2024-04-24 14:56:30I2023-12-03 22:06:00.0<NA>201358.388614454534.250494<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
281130700003070000-134-2024-000472024-04-25<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>136-052서울특별시 성북구 동선동*가 *** 패션빌딩서울특별시 성북구 보문로**길 **, 패션빌딩 *층 *호 (동선동*가)2849삼식이네2024-04-25 10:25:19I2023-12-03 22:07:00.0<NA>201646.590942454251.101589<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
281230700003070000-134-2024-000482024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>136-034서울특별시 성북구 동소문동*가 ***서울특별시 성북구 동소문로 **, *층 (동소문동*가)2832다비치안경 성북구청사거리점2024-04-30 14:21:15I2023-12-05 00:02:00.0<NA>201053.971934454391.194568<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
281330700003070000-134-2024-000492024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>136-090서울특별시 성북구 종암동 *** 아이파크 종암동서울특별시 성북구 종암로**길 ***, ***동 ***호 (종암동, 아이파크 종암동)2802헬시판다2024-05-07 09:16:37I2023-12-05 00:09:00.0<NA>202567.716727455579.463087<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
281430700003070000-134-2024-000502024-05-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>136-110서울특별시 성북구 길음동 **** 길음뉴타운서울특별시 성북구 길음로 ***, ***동 ****호 (길음동, 길음뉴타운)2723바로셀2024-05-09 09:39:03I2023-12-04 23:01:00.0<NA>201665.346471456637.258125<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>