Overview

Dataset statistics

Number of variables44
Number of observations4690
Missing cells80109
Missing cells (%)38.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 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
Author마포구
URLhttps://data.seoul.go.kr/dataList/OA-18090/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
홈페이지 has constant value ""Constant
남성종사자수 is highly imbalanced (69.2%)Imbalance
여성종사자수 is highly imbalanced (69.2%)Imbalance
급수시설구분명 is highly imbalanced (70.2%)Imbalance
총인원 is highly imbalanced (69.2%)Imbalance
인허가취소일자 has 4690 (100.0%) missing valuesMissing
폐업일자 has 1357 (28.9%) missing valuesMissing
휴업시작일자 has 4690 (100.0%) missing valuesMissing
휴업종료일자 has 4690 (100.0%) missing valuesMissing
재개업일자 has 4690 (100.0%) missing valuesMissing
전화번호 has 2405 (51.3%) missing valuesMissing
소재지면적 has 2740 (58.4%) missing valuesMissing
소재지우편번호 has 57 (1.2%) missing valuesMissing
지번주소 has 57 (1.2%) missing valuesMissing
도로명주소 has 798 (17.0%) missing valuesMissing
도로명우편번호 has 810 (17.3%) missing valuesMissing
업태구분명 has 4690 (100.0%) missing valuesMissing
좌표정보(X) has 86 (1.8%) missing valuesMissing
좌표정보(Y) has 86 (1.8%) missing valuesMissing
영업장주변구분명 has 4690 (100.0%) missing valuesMissing
등급구분명 has 4690 (100.0%) missing valuesMissing
본사종업원수 has 3534 (75.4%) missing valuesMissing
공장사무직종업원수 has 3519 (75.0%) missing valuesMissing
공장판매직종업원수 has 3559 (75.9%) missing valuesMissing
공장생산직종업원수 has 3608 (76.9%) missing valuesMissing
보증액 has 3620 (77.2%) missing valuesMissing
월세액 has 3628 (77.4%) missing valuesMissing
다중이용업소여부 has 1673 (35.7%) missing valuesMissing
시설총규모 has 1673 (35.7%) missing valuesMissing
전통업소지정번호 has 4690 (100.0%) missing valuesMissing
전통업소주된음식 has 4690 (100.0%) missing valuesMissing
홈페이지 has 4689 (> 99.9%) missing valuesMissing
도로명우편번호 is highly skewed (γ1 = 48.37927517)Skewed
시설총규모 is highly skewed (γ1 = 54.22716941)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 1002 (21.4%) zerosZeros
공장사무직종업원수 has 742 (15.8%) zerosZeros
공장판매직종업원수 has 768 (16.4%) zerosZeros
공장생산직종업원수 has 1058 (22.6%) zerosZeros
보증액 has 461 (9.8%) zerosZeros
월세액 has 448 (9.6%) zerosZeros
시설총규모 has 2977 (63.5%) zerosZeros

Reproduction

Analysis started2024-05-11 07:23:21.352077
Analysis finished2024-05-11 07:23:24.672586
Duration3.32 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size36.8 KiB
3130000
4690 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3130000
2nd row3130000
3rd row3130000
4th row3130000
5th row3130000

Common Values

ValueCountFrequency (%)
3130000 4690
100.0%

Length

2024-05-11T07:23:24.892434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:23:25.236813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3130000 4690
100.0%

관리번호
Text

UNIQUE 

Distinct4690
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size36.8 KiB
2024-05-11T07:23:25.802329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters103180
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

Unique4690 ?
Unique (%)100.0%

Sample

1st row3130000-134-1998-00001
2nd row3130000-134-2004-00001
3rd row3130000-134-2004-00002
4th row3130000-134-2004-00003
5th row3130000-134-2004-00004
ValueCountFrequency (%)
3130000-134-1998-00001 1
 
< 0.1%
3130000-134-2020-00118 1
 
< 0.1%
3130000-134-2020-00170 1
 
< 0.1%
3130000-134-2020-00169 1
 
< 0.1%
3130000-134-2020-00168 1
 
< 0.1%
3130000-134-2020-00167 1
 
< 0.1%
3130000-134-2020-00166 1
 
< 0.1%
3130000-134-2020-00172 1
 
< 0.1%
3130000-134-2020-00165 1
 
< 0.1%
3130000-134-2020-00163 1
 
< 0.1%
Other values (4680) 4680
99.8%
2024-05-11T07:23:26.701382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 37582
36.4%
3 16114
15.6%
1 14310
 
13.9%
- 14070
 
13.6%
2 8598
 
8.3%
4 6494
 
6.3%
5 1285
 
1.2%
6 1249
 
1.2%
9 1195
 
1.2%
7 1166
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 89110
86.4%
Dash Punctuation 14070
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 37582
42.2%
3 16114
18.1%
1 14310
 
16.1%
2 8598
 
9.6%
4 6494
 
7.3%
5 1285
 
1.4%
6 1249
 
1.4%
9 1195
 
1.3%
7 1166
 
1.3%
8 1117
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 14070
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 103180
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 37582
36.4%
3 16114
15.6%
1 14310
 
13.9%
- 14070
 
13.6%
2 8598
 
8.3%
4 6494
 
6.3%
5 1285
 
1.2%
6 1249
 
1.2%
9 1195
 
1.2%
7 1166
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 103180
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 37582
36.4%
3 16114
15.6%
1 14310
 
13.9%
- 14070
 
13.6%
2 8598
 
8.3%
4 6494
 
6.3%
5 1285
 
1.2%
6 1249
 
1.2%
9 1195
 
1.2%
7 1166
 
1.1%
Distinct2574
Distinct (%)54.9%
Missing0
Missing (%)0.0%
Memory size36.8 KiB
Minimum1998-02-12 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T07:23:27.116752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T07:23:27.506208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4690
Missing (%)100.0%
Memory size41.3 KiB
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size36.8 KiB
3
3333 
1
1357 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 3333
71.1%
1 1357
28.9%

Length

2024-05-11T07:23:27.919751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:23:28.219010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 3333
71.1%
1 1357
28.9%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size36.8 KiB
폐업
3333 
영업/정상
1357 

Length

Max length5
Median length2
Mean length2.8680171
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 3333
71.1%
영업/정상 1357
28.9%

Length

2024-05-11T07:23:28.662616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:23:28.976903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3333
71.1%
영업/정상 1357
28.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size36.8 KiB
2
3333 
1
1357 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 3333
71.1%
1 1357
28.9%

Length

2024-05-11T07:23:29.260239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:23:29.523561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 3333
71.1%
1 1357
28.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size36.8 KiB
폐업
3333 
영업
1357 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 3333
71.1%
영업 1357
28.9%

Length

2024-05-11T07:23:29.892884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:23:30.222534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3333
71.1%
영업 1357
28.9%

폐업일자
Date

MISSING 

Distinct1880
Distinct (%)56.4%
Missing1357
Missing (%)28.9%
Memory size36.8 KiB
Minimum2004-05-07 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T07:23:30.542609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T07:23:30.966268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4690
Missing (%)100.0%
Memory size41.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4690
Missing (%)100.0%
Memory size41.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4690
Missing (%)100.0%
Memory size41.3 KiB

전화번호
Text

MISSING 

Distinct2192
Distinct (%)95.9%
Missing2405
Missing (%)51.3%
Memory size36.8 KiB
2024-05-11T07:23:31.650212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.574179
Min length2

Characters and Unicode

Total characters24162
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

Unique2117 ?
Unique (%)92.6%

Sample

1st row000203376881
2nd row02 3356661
3rd row0231431116
4th row02 7171926
5th row02 3382904
ValueCountFrequency (%)
02 1396
31.7%
070 126
 
2.9%
322 36
 
0.8%
031 21
 
0.5%
323 21
 
0.5%
332 21
 
0.5%
325 20
 
0.5%
333 19
 
0.4%
701 14
 
0.3%
715 14
 
0.3%
Other values (2341) 2715
61.7%
2024-05-11T07:23:32.884177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3966
16.4%
2 3790
15.7%
3 2951
12.2%
2912
12.1%
7 2122
8.8%
1 1785
7.4%
5 1478
 
6.1%
8 1415
 
5.9%
4 1379
 
5.7%
6 1338
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21250
87.9%
Space Separator 2912
 
12.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3966
18.7%
2 3790
17.8%
3 2951
13.9%
7 2122
10.0%
1 1785
8.4%
5 1478
 
7.0%
8 1415
 
6.7%
4 1379
 
6.5%
6 1338
 
6.3%
9 1026
 
4.8%
Space Separator
ValueCountFrequency (%)
2912
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24162
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3966
16.4%
2 3790
15.7%
3 2951
12.2%
2912
12.1%
7 2122
8.8%
1 1785
7.4%
5 1478
 
6.1%
8 1415
 
5.9%
4 1379
 
5.7%
6 1338
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24162
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3966
16.4%
2 3790
15.7%
3 2951
12.2%
2912
12.1%
7 2122
8.8%
1 1785
7.4%
5 1478
 
6.1%
8 1415
 
5.9%
4 1379
 
5.7%
6 1338
 
5.5%

소재지면적
Text

MISSING 

Distinct937
Distinct (%)48.1%
Missing2740
Missing (%)58.4%
Memory size36.8 KiB
2024-05-11T07:23:33.927172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.9138462
Min length3

Characters and Unicode

Total characters9582
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

Unique745 ?
Unique (%)38.2%

Sample

1st row64.48
2nd row6.40
3rd row161.34
4th row198.00
5th row146.36
ValueCountFrequency (%)
00 133
 
6.8%
3.30 75
 
3.8%
10.00 50
 
2.6%
6.60 37
 
1.9%
66.00 35
 
1.8%
33.00 33
 
1.7%
20.00 25
 
1.3%
3.00 25
 
1.3%
0.00 24
 
1.2%
30.00 24
 
1.2%
Other values (927) 1489
76.4%
2024-05-11T07:23:35.414679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2665
27.8%
. 1950
20.4%
1 783
 
8.2%
3 751
 
7.8%
2 614
 
6.4%
6 583
 
6.1%
5 545
 
5.7%
4 470
 
4.9%
9 452
 
4.7%
8 428
 
4.5%
Other values (2) 341
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7626
79.6%
Other Punctuation 1956
 
20.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2665
34.9%
1 783
 
10.3%
3 751
 
9.8%
2 614
 
8.1%
6 583
 
7.6%
5 545
 
7.1%
4 470
 
6.2%
9 452
 
5.9%
8 428
 
5.6%
7 335
 
4.4%
Other Punctuation
ValueCountFrequency (%)
. 1950
99.7%
, 6
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 9582
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2665
27.8%
. 1950
20.4%
1 783
 
8.2%
3 751
 
7.8%
2 614
 
6.4%
6 583
 
6.1%
5 545
 
5.7%
4 470
 
4.9%
9 452
 
4.7%
8 428
 
4.5%
Other values (2) 341
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9582
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2665
27.8%
. 1950
20.4%
1 783
 
8.2%
3 751
 
7.8%
2 614
 
6.4%
6 583
 
6.1%
5 545
 
5.7%
4 470
 
4.9%
9 452
 
4.7%
8 428
 
4.5%
Other values (2) 341
 
3.6%

소재지우편번호
Text

MISSING 

Distinct326
Distinct (%)7.0%
Missing57
Missing (%)1.2%
Memory size36.8 KiB
2024-05-11T07:23:36.398446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.2326786
Min length6

Characters and Unicode

Total characters28876
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

Unique49 ?
Unique (%)1.1%

Sample

1st row121862
2nd row121827
3rd row121849
4th row121827
5th row121869
ValueCountFrequency (%)
121805 106
 
2.3%
121856 103
 
2.2%
121904 93
 
2.0%
121812 81
 
1.7%
121815 79
 
1.7%
121884 75
 
1.6%
121807 75
 
1.6%
121893 66
 
1.4%
121821 58
 
1.3%
121839 56
 
1.2%
Other values (316) 3841
82.9%
2024-05-11T07:23:37.980194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 10268
35.6%
2 5451
18.9%
8 4525
15.7%
0 1524
 
5.3%
9 1245
 
4.3%
4 1154
 
4.0%
7 1123
 
3.9%
- 1078
 
3.7%
5 998
 
3.5%
6 789
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 27798
96.3%
Dash Punctuation 1078
 
3.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 10268
36.9%
2 5451
19.6%
8 4525
16.3%
0 1524
 
5.5%
9 1245
 
4.5%
4 1154
 
4.2%
7 1123
 
4.0%
5 998
 
3.6%
6 789
 
2.8%
3 721
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 1078
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 28876
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 10268
35.6%
2 5451
18.9%
8 4525
15.7%
0 1524
 
5.3%
9 1245
 
4.3%
4 1154
 
4.0%
7 1123
 
3.9%
- 1078
 
3.7%
5 998
 
3.5%
6 789
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28876
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 10268
35.6%
2 5451
18.9%
8 4525
15.7%
0 1524
 
5.3%
9 1245
 
4.3%
4 1154
 
4.0%
7 1123
 
3.9%
- 1078
 
3.7%
5 998
 
3.5%
6 789
 
2.7%

지번주소
Text

MISSING 

Distinct2695
Distinct (%)58.2%
Missing57
Missing (%)1.2%
Memory size36.8 KiB
2024-05-11T07:23:38.685331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length44
Mean length27.692856
Min length16

Characters and Unicode

Total characters128301
Distinct characters470
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2117 ?
Unique (%)45.7%

Sample

1st row서울특별시 마포구 아현동 ***-** 건우약국 *층
2nd row서울특별시 마포구 망원동 ***-**번지 *층
3rd row서울특별시 마포구 성산동 ***-*번지 다농마트내
4th row서울특별시 마포구 망원동 ***-*번지 리츠아파트 B***호
5th row서울특별시 마포구 연남동 ***-**번지 지남빌딩 ***호
ValueCountFrequency (%)
서울특별시 4631
18.8%
마포구 4630
18.8%
번지 2318
 
9.4%
2237
 
9.1%
1387
 
5.6%
803
 
3.3%
서교동 653
 
2.6%
성산동 475
 
1.9%
망원동 406
 
1.6%
도화동 388
 
1.6%
Other values (1566) 6765
27.4%
2024-05-11T07:23:39.710574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 25590
19.9%
22571
17.6%
5528
 
4.3%
5413
 
4.2%
4997
 
3.9%
4944
 
3.9%
4711
 
3.7%
4682
 
3.6%
4668
 
3.6%
4649
 
3.6%
Other values (460) 40548
31.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 74517
58.1%
Other Punctuation 25680
 
20.0%
Space Separator 22571
 
17.6%
Dash Punctuation 3409
 
2.7%
Decimal Number 721
 
0.6%
Uppercase Letter 702
 
0.5%
Open Punctuation 268
 
0.2%
Close Punctuation 268
 
0.2%
Lowercase Letter 146
 
0.1%
Letter Number 17
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5528
 
7.4%
5413
 
7.3%
4997
 
6.7%
4944
 
6.6%
4711
 
6.3%
4682
 
6.3%
4668
 
6.3%
4649
 
6.2%
4638
 
6.2%
2761
 
3.7%
Other values (387) 27526
36.9%
Uppercase Letter
ValueCountFrequency (%)
B 113
16.1%
C 62
 
8.8%
S 48
 
6.8%
T 47
 
6.7%
A 46
 
6.6%
D 45
 
6.4%
L 45
 
6.4%
G 44
 
6.3%
P 40
 
5.7%
M 38
 
5.4%
Other values (14) 174
24.8%
Lowercase Letter
ValueCountFrequency (%)
e 25
17.1%
b 22
15.1%
s 12
8.2%
i 11
 
7.5%
t 11
 
7.5%
o 9
 
6.2%
u 8
 
5.5%
r 8
 
5.5%
l 6
 
4.1%
y 5
 
3.4%
Other values (13) 29
19.9%
Decimal Number
ValueCountFrequency (%)
1 117
16.2%
4 103
14.3%
2 89
12.3%
5 78
10.8%
0 76
10.5%
3 68
9.4%
8 52
7.2%
7 51
7.1%
9 49
6.8%
6 38
 
5.3%
Other Punctuation
ValueCountFrequency (%)
* 25590
99.6%
, 65
 
0.3%
@ 8
 
< 0.1%
. 5
 
< 0.1%
& 5
 
< 0.1%
/ 5
 
< 0.1%
? 1
 
< 0.1%
; 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 267
99.6%
[ 1
 
0.4%
Close Punctuation
ValueCountFrequency (%)
) 267
99.6%
] 1
 
0.4%
Space Separator
ValueCountFrequency (%)
22571
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3409
100.0%
Letter Number
ValueCountFrequency (%)
17
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 74513
58.1%
Common 52919
41.2%
Latin 865
 
0.7%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5528
 
7.4%
5413
 
7.3%
4997
 
6.7%
4944
 
6.6%
4711
 
6.3%
4682
 
6.3%
4668
 
6.3%
4649
 
6.2%
4638
 
6.2%
2761
 
3.7%
Other values (385) 27522
36.9%
Latin
ValueCountFrequency (%)
B 113
 
13.1%
C 62
 
7.2%
S 48
 
5.5%
T 47
 
5.4%
A 46
 
5.3%
D 45
 
5.2%
L 45
 
5.2%
G 44
 
5.1%
P 40
 
4.6%
M 38
 
4.4%
Other values (38) 337
39.0%
Common
ValueCountFrequency (%)
* 25590
48.4%
22571
42.7%
- 3409
 
6.4%
( 267
 
0.5%
) 267
 
0.5%
1 117
 
0.2%
4 103
 
0.2%
2 89
 
0.2%
5 78
 
0.1%
0 76
 
0.1%
Other values (15) 352
 
0.7%
Han
ValueCountFrequency (%)
2
50.0%
2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 74512
58.1%
ASCII 53767
41.9%
Number Forms 17
 
< 0.1%
CJK 4
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 25590
47.6%
22571
42.0%
- 3409
 
6.3%
( 267
 
0.5%
) 267
 
0.5%
1 117
 
0.2%
B 113
 
0.2%
4 103
 
0.2%
2 89
 
0.2%
5 78
 
0.1%
Other values (62) 1163
 
2.2%
Hangul
ValueCountFrequency (%)
5528
 
7.4%
5413
 
7.3%
4997
 
6.7%
4944
 
6.6%
4711
 
6.3%
4682
 
6.3%
4668
 
6.3%
4649
 
6.2%
4638
 
6.2%
2761
 
3.7%
Other values (384) 27521
36.9%
Number Forms
ValueCountFrequency (%)
17
100.0%
CJK
ValueCountFrequency (%)
2
50.0%
2
50.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

도로명주소
Text

MISSING 

Distinct2870
Distinct (%)73.7%
Missing798
Missing (%)17.0%
Memory size36.8 KiB
2024-05-11T07:23:40.373038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length55
Mean length36.518756
Min length22

Characters and Unicode

Total characters142131
Distinct characters482
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2395 ?
Unique (%)61.5%

Sample

1st row서울특별시 마포구 마포대로 ***-*, 건우약국 *층 (아현동)
2nd row서울특별시 마포구 월드컵로**길 ** (망원동, *층)
3rd row서울특별시 마포구 월드컵로**길 **, B***호 (망원동, 리츠아파트)
4th row서울특별시 마포구 월드컵북로 *** (성산동, 제*상가 *호)
5th row서울특별시 마포구 동교로**길 * (동교동, 석진빌딩*층)
ValueCountFrequency (%)
서울특별시 3890
 
14.1%
마포구 3889
 
14.1%
3861
 
14.0%
2060
 
7.5%
1600
 
5.8%
서교동 566
 
2.1%
478
 
1.7%
성산동 390
 
1.4%
망원동 354
 
1.3%
마포대로 339
 
1.2%
Other values (1840) 10164
36.8%
2024-05-11T07:23:41.632988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
23707
16.7%
* 23082
 
16.2%
5155
 
3.6%
, 5061
 
3.6%
4723
 
3.3%
4681
 
3.3%
4635
 
3.3%
) 4162
 
2.9%
( 4162
 
2.9%
4019
 
2.8%
Other values (472) 58744
41.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 79238
55.7%
Other Punctuation 28163
 
19.8%
Space Separator 23707
 
16.7%
Close Punctuation 4163
 
2.9%
Open Punctuation 4163
 
2.9%
Decimal Number 916
 
0.6%
Uppercase Letter 837
 
0.6%
Dash Punctuation 745
 
0.5%
Lowercase Letter 159
 
0.1%
Math Symbol 20
 
< 0.1%
Other values (2) 20
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5155
 
6.5%
4723
 
6.0%
4681
 
5.9%
4635
 
5.8%
4019
 
5.1%
3974
 
5.0%
3940
 
5.0%
3912
 
4.9%
3895
 
4.9%
3784
 
4.8%
Other values (402) 36520
46.1%
Uppercase Letter
ValueCountFrequency (%)
B 194
23.2%
C 82
9.8%
A 73
 
8.7%
D 53
 
6.3%
S 53
 
6.3%
M 50
 
6.0%
T 46
 
5.5%
L 42
 
5.0%
P 41
 
4.9%
G 36
 
4.3%
Other values (14) 167
20.0%
Lowercase Letter
ValueCountFrequency (%)
b 44
27.7%
e 23
14.5%
s 11
 
6.9%
t 11
 
6.9%
i 10
 
6.3%
r 8
 
5.0%
o 8
 
5.0%
u 7
 
4.4%
l 7
 
4.4%
y 5
 
3.1%
Other values (11) 25
15.7%
Decimal Number
ValueCountFrequency (%)
1 226
24.7%
2 148
16.2%
0 142
15.5%
3 96
10.5%
4 66
 
7.2%
5 64
 
7.0%
8 54
 
5.9%
6 49
 
5.3%
9 41
 
4.5%
7 30
 
3.3%
Other Punctuation
ValueCountFrequency (%)
* 23082
82.0%
, 5061
 
18.0%
. 10
 
< 0.1%
& 4
 
< 0.1%
@ 4
 
< 0.1%
/ 2
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 4162
> 99.9%
] 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 4162
> 99.9%
[ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
23707
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 745
100.0%
Math Symbol
ValueCountFrequency (%)
~ 20
100.0%
Letter Number
ValueCountFrequency (%)
16
100.0%
Other Symbol
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 79234
55.7%
Common 61881
43.5%
Latin 1012
 
0.7%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5155
 
6.5%
4723
 
6.0%
4681
 
5.9%
4635
 
5.8%
4019
 
5.1%
3974
 
5.0%
3940
 
5.0%
3912
 
4.9%
3895
 
4.9%
3784
 
4.8%
Other values (400) 36516
46.1%
Latin
ValueCountFrequency (%)
B 194
19.2%
C 82
 
8.1%
A 73
 
7.2%
D 53
 
5.2%
S 53
 
5.2%
M 50
 
4.9%
T 46
 
4.5%
b 44
 
4.3%
L 42
 
4.2%
P 41
 
4.1%
Other values (36) 334
33.0%
Common
ValueCountFrequency (%)
23707
38.3%
* 23082
37.3%
, 5061
 
8.2%
) 4162
 
6.7%
( 4162
 
6.7%
- 745
 
1.2%
1 226
 
0.4%
2 148
 
0.2%
0 142
 
0.2%
3 96
 
0.2%
Other values (14) 350
 
0.6%
Han
ValueCountFrequency (%)
2
50.0%
2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 79234
55.7%
ASCII 62873
44.2%
Number Forms 16
 
< 0.1%
CJK Compat 4
 
< 0.1%
CJK 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
23707
37.7%
* 23082
36.7%
, 5061
 
8.0%
) 4162
 
6.6%
( 4162
 
6.6%
- 745
 
1.2%
1 226
 
0.4%
B 194
 
0.3%
2 148
 
0.2%
0 142
 
0.2%
Other values (58) 1244
 
2.0%
Hangul
ValueCountFrequency (%)
5155
 
6.5%
4723
 
6.0%
4681
 
5.9%
4635
 
5.8%
4019
 
5.1%
3974
 
5.0%
3940
 
5.0%
3912
 
4.9%
3895
 
4.9%
3784
 
4.8%
Other values (400) 36516
46.1%
Number Forms
ValueCountFrequency (%)
16
100.0%
CJK Compat
ValueCountFrequency (%)
4
100.0%
CJK
ValueCountFrequency (%)
2
50.0%
2
50.0%

도로명우편번호
Real number (ℝ)

MISSING  SKEWED 

Distinct302
Distinct (%)7.8%
Missing810
Missing (%)17.3%
Infinite0
Infinite (%)0.0%
Mean4063.3049
Minimum3901
Maximum26429
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size41.3 KiB
2024-05-11T07:23:42.231664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3901
5-th percentile3925
Q13991
median4049.5
Q34127
95-th percentile4195
Maximum26429
Range22528
Interquartile range (IQR)136

Descriptive statistics

Standard deviation401.82167
Coefficient of variation (CV)0.098890357
Kurtosis2571.8656
Mean4063.3049
Median Absolute Deviation (MAD)63.5
Skewness48.379275
Sum15765623
Variance161460.66
MonotonicityNot monotonic
2024-05-11T07:23:42.744959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4089 103
 
2.2%
4072 93
 
2.0%
4057 75
 
1.6%
4168 67
 
1.4%
4031 62
 
1.3%
4017 62
 
1.3%
4050 53
 
1.1%
4167 48
 
1.0%
3925 42
 
0.9%
3938 40
 
0.9%
Other values (292) 3235
69.0%
(Missing) 810
 
17.3%
ValueCountFrequency (%)
3901 3
 
0.1%
3902 19
0.4%
3903 4
 
0.1%
3904 1
 
< 0.1%
3905 14
0.3%
3906 3
 
0.1%
3907 8
0.2%
3908 16
0.3%
3909 15
0.3%
3911 14
0.3%
ValueCountFrequency (%)
26429 1
 
< 0.1%
14001 1
 
< 0.1%
4516 1
 
< 0.1%
4214 12
0.3%
4213 13
0.3%
4212 5
 
0.1%
4211 7
 
0.1%
4210 2
 
< 0.1%
4209 18
0.4%
4208 15
0.3%
Distinct4489
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size36.8 KiB
2024-05-11T07:23:43.419107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length30
Mean length7.3110874
Min length2

Characters and Unicode

Total characters34289
Distinct characters855
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4343 ?
Unique (%)92.6%

Sample

1st row건우약국
2nd row솔고헬스케어
3rd row고려인삼코너
4th row(주)페드넷
5th row(주)헬쓰웨이인터내셔날
ValueCountFrequency (%)
주식회사 313
 
5.2%
세븐일레븐 45
 
0.7%
씨제이올리브영(주 27
 
0.4%
마포점 26
 
0.4%
훼미리마트 25
 
0.4%
홍대점 20
 
0.3%
gs25 17
 
0.3%
아리따움 16
 
0.3%
인셀덤 16
 
0.3%
신촌점 15
 
0.2%
Other values (4779) 5541
91.4%
2024-05-11T07:23:44.719475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1379
 
4.0%
1371
 
4.0%
1194
 
3.5%
1084
 
3.2%
) 1080
 
3.1%
( 1064
 
3.1%
705
 
2.1%
571
 
1.7%
520
 
1.5%
491
 
1.4%
Other values (845) 24830
72.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 28621
83.5%
Space Separator 1371
 
4.0%
Close Punctuation 1080
 
3.1%
Open Punctuation 1064
 
3.1%
Uppercase Letter 930
 
2.7%
Lowercase Letter 700
 
2.0%
Decimal Number 441
 
1.3%
Other Punctuation 65
 
0.2%
Dash Punctuation 13
 
< 0.1%
Math Symbol 2
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1379
 
4.8%
1194
 
4.2%
1084
 
3.8%
705
 
2.5%
571
 
2.0%
520
 
1.8%
491
 
1.7%
482
 
1.7%
465
 
1.6%
438
 
1.5%
Other values (770) 21292
74.4%
Uppercase Letter
ValueCountFrequency (%)
S 107
 
11.5%
G 79
 
8.5%
C 75
 
8.1%
A 61
 
6.6%
N 55
 
5.9%
O 52
 
5.6%
I 45
 
4.8%
M 43
 
4.6%
H 41
 
4.4%
B 40
 
4.3%
Other values (16) 332
35.7%
Lowercase Letter
ValueCountFrequency (%)
e 86
12.3%
o 72
 
10.3%
a 61
 
8.7%
n 58
 
8.3%
i 54
 
7.7%
r 40
 
5.7%
t 39
 
5.6%
l 36
 
5.1%
h 31
 
4.4%
u 29
 
4.1%
Other values (16) 194
27.7%
Decimal Number
ValueCountFrequency (%)
2 156
35.4%
5 129
29.3%
1 43
 
9.8%
9 25
 
5.7%
0 22
 
5.0%
3 20
 
4.5%
6 16
 
3.6%
7 15
 
3.4%
4 11
 
2.5%
8 4
 
0.9%
Other Punctuation
ValueCountFrequency (%)
. 36
55.4%
& 15
23.1%
? 7
 
10.8%
, 4
 
6.2%
' 2
 
3.1%
/ 1
 
1.5%
Space Separator
ValueCountFrequency (%)
1371
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1080
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1064
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 28618
83.5%
Common 4038
 
11.8%
Latin 1630
 
4.8%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1379
 
4.8%
1194
 
4.2%
1084
 
3.8%
705
 
2.5%
571
 
2.0%
520
 
1.8%
491
 
1.7%
482
 
1.7%
465
 
1.6%
438
 
1.5%
Other values (767) 21289
74.4%
Latin
ValueCountFrequency (%)
S 107
 
6.6%
e 86
 
5.3%
G 79
 
4.8%
C 75
 
4.6%
o 72
 
4.4%
a 61
 
3.7%
A 61
 
3.7%
n 58
 
3.6%
N 55
 
3.4%
i 54
 
3.3%
Other values (42) 922
56.6%
Common
ValueCountFrequency (%)
1371
34.0%
) 1080
26.7%
( 1064
26.3%
2 156
 
3.9%
5 129
 
3.2%
1 43
 
1.1%
. 36
 
0.9%
9 25
 
0.6%
0 22
 
0.5%
3 20
 
0.5%
Other values (13) 92
 
2.3%
Han
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 28618
83.5%
ASCII 5667
 
16.5%
CJK 3
 
< 0.1%
CJK Compat 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1379
 
4.8%
1194
 
4.2%
1084
 
3.8%
705
 
2.5%
571
 
2.0%
520
 
1.8%
491
 
1.7%
482
 
1.7%
465
 
1.6%
438
 
1.5%
Other values (767) 21289
74.4%
ASCII
ValueCountFrequency (%)
1371
24.2%
) 1080
19.1%
( 1064
18.8%
2 156
 
2.8%
5 129
 
2.3%
S 107
 
1.9%
e 86
 
1.5%
G 79
 
1.4%
C 75
 
1.3%
o 72
 
1.3%
Other values (64) 1448
25.6%
CJK Compat
ValueCountFrequency (%)
1
100.0%
CJK
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Distinct4425
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Memory size36.8 KiB
Minimum2004-03-30 00:00:00
Maximum2024-05-09 15:18:11
2024-05-11T07:23:45.219193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T07:23:45.606936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size36.8 KiB
I
2919 
U
1770 
D
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
I 2919
62.2%
U 1770
37.7%
D 1
 
< 0.1%

Length

2024-05-11T07:23:46.126598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:23:46.431205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2919
62.2%
u 1770
37.7%
d 1
 
< 0.1%
Distinct1048
Distinct (%)22.3%
Missing0
Missing (%)0.0%
Memory size36.8 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:05:00
2024-05-11T07:23:46.789713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T07:23:47.310030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4690
Missing (%)100.0%
Memory size41.3 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct2187
Distinct (%)47.5%
Missing86
Missing (%)1.8%
Infinite0
Infinite (%)0.0%
Mean193366.6
Minimum189212.71
Maximum284484.96
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size41.3 KiB
2024-05-11T07:23:47.761724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189212.71
5-th percentile190657.12
Q1192085.99
median193104.7
Q3194999.82
95-th percentile195936.77
Maximum284484.96
Range95272.25
Interquartile range (IQR)2913.8286

Descriptive statistics

Standard deviation2160.9039
Coefficient of variation (CV)0.011175166
Kurtosis685.50423
Mean193366.6
Median Absolute Deviation (MAD)1331.331
Skewness16.27768
Sum8.9025981 × 108
Variance4669505.6
MonotonicityNot monotonic
2024-05-11T07:23:48.221249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
194301.304865904 102
 
2.2%
192652.282023976 75
 
1.6%
193166.430144679 43
 
0.9%
192730.376890748 40
 
0.9%
195703.425296812 40
 
0.9%
191578.189539451 35
 
0.7%
193870.417173466 35
 
0.7%
193260.779825462 30
 
0.6%
195764.944565229 28
 
0.6%
191263.451931121 26
 
0.6%
Other values (2177) 4150
88.5%
(Missing) 86
 
1.8%
ValueCountFrequency (%)
189212.708916184 3
 
0.1%
189212.737535822 12
0.3%
189286.651086068 1
 
< 0.1%
189315.310470024 2
 
< 0.1%
189315.370584751 4
 
0.1%
189333.237397304 1
 
< 0.1%
189343.04418441 1
 
< 0.1%
189372.962506695 1
 
< 0.1%
189392.975995366 5
0.1%
189409.319972063 1
 
< 0.1%
ValueCountFrequency (%)
284484.959261583 1
< 0.1%
197143.10408516 1
< 0.1%
196717.946323293 1
< 0.1%
196717.811595364 1
< 0.1%
196700.29270525 1
< 0.1%
196625.816432336 1
< 0.1%
196607.625984913 1
< 0.1%
196604.277736784 1
< 0.1%
196589.972583452 1
< 0.1%
196587.461456239 1
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct2187
Distinct (%)47.5%
Missing86
Missing (%)1.8%
Infinite0
Infinite (%)0.0%
Mean450165.04
Minimum427479.8
Maximum453923.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size41.3 KiB
2024-05-11T07:23:48.647796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum427479.8
5-th percentile448616.47
Q1449388.05
median450130.09
Q3450662.58
95-th percentile452647.98
Maximum453923.2
Range26443.4
Interquartile range (IQR)1274.5284

Descriptive statistics

Standard deviation1184.9434
Coefficient of variation (CV)0.0026322421
Kurtosis38.96721
Mean450165.04
Median Absolute Deviation (MAD)658.707
Skewness-1.4955913
Sum2.0725599 × 109
Variance1404090.8
MonotonicityNot monotonic
2024-05-11T07:23:49.103254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
449388.053900946 102
 
2.2%
449483.723207355 75
 
1.6%
450425.852790862 43
 
0.9%
450187.395198752 40
 
0.9%
449330.800717721 40
 
0.9%
450099.587238227 35
 
0.7%
450441.587738525 35
 
0.7%
450395.053477987 30
 
0.6%
449028.002731859 28
 
0.6%
452207.500653521 26
 
0.6%
Other values (2177) 4150
88.5%
(Missing) 86
 
1.8%
ValueCountFrequency (%)
427479.800413061 1
 
< 0.1%
432877.040153499 1
 
< 0.1%
448116.639953919 2
 
< 0.1%
448201.92884513 3
 
0.1%
448206.301166714 1
 
< 0.1%
448229.063825491 22
0.5%
448236.655548283 15
0.3%
448248.442978398 1
 
< 0.1%
448276.965250949 11
0.2%
448281.815199671 1
 
< 0.1%
ValueCountFrequency (%)
453923.20042427 1
 
< 0.1%
453923.18626299 2
< 0.1%
453872.42578746 3
0.1%
453872.3993323 1
 
< 0.1%
453797.138339588 1
 
< 0.1%
453685.545865753 4
0.1%
453685.460423342 2
< 0.1%
453647.349314742 4
0.1%
453647.190988422 2
< 0.1%
453624.945221014 1
 
< 0.1%

위생업태명
Categorical

Distinct11
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size36.8 KiB
<NA>
1673 
영업장판매
1174 
전자상거래(통신판매업)
821 
통신판매
465 
방문판매
250 
Other values (6)
307 

Length

Max length14
Median length4
Mean length5.8260128
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row영업장판매
3rd row영업장판매
4th row전자상거래(통신판매업)
5th row방문판매

Common Values

ValueCountFrequency (%)
<NA> 1673
35.7%
영업장판매 1174
25.0%
전자상거래(통신판매업) 821
17.5%
통신판매 465
 
9.9%
방문판매 250
 
5.3%
다단계판매 172
 
3.7%
기타(복합 등) 51
 
1.1%
도매업(유통) 37
 
0.8%
기타 건강기능식품일반판매업 30
 
0.6%
전화권유판매 16
 
0.3%

Length

2024-05-11T07:23:49.599807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1673
35.1%
영업장판매 1174
24.6%
전자상거래(통신판매업 821
17.2%
통신판매 465
 
9.7%
방문판매 250
 
5.2%
다단계판매 172
 
3.6%
기타(복합 51
 
1.1%
51
 
1.1%
도매업(유통 37
 
0.8%
기타 30
 
0.6%
Other values (3) 47
 
1.0%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size36.8 KiB
<NA>
4431 
0
 
259

Length

Max length4
Median length4
Mean length3.8343284
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> 4431
94.5%
0 259
 
5.5%

Length

2024-05-11T07:23:50.005909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:23:50.337865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4431
94.5%
0 259
 
5.5%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size36.8 KiB
<NA>
4431 
0
 
259

Length

Max length4
Median length4
Mean length3.8343284
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> 4431
94.5%
0 259
 
5.5%

Length

2024-05-11T07:23:50.691434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:23:51.017138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4431
94.5%
0 259
 
5.5%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4690
Missing (%)100.0%
Memory size41.3 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4690
Missing (%)100.0%
Memory size41.3 KiB

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size36.8 KiB
<NA>
4443 
상수도전용
 
247

Length

Max length5
Median length4
Mean length4.0526652
Min length4

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> 4443
94.7%
상수도전용 247
 
5.3%

Length

2024-05-11T07:23:51.345566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:23:51.645397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4443
94.7%
상수도전용 247
 
5.3%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size36.8 KiB
<NA>
4431 
0
 
259

Length

Max length4
Median length4
Mean length3.8343284
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> 4431
94.5%
0 259
 
5.5%

Length

2024-05-11T07:23:51.984039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:23:52.309287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4431
94.5%
0 259
 
5.5%

본사종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct26
Distinct (%)2.2%
Missing3534
Missing (%)75.4%
Infinite0
Infinite (%)0.0%
Mean0.91262976
Minimum0
Maximum101
Zeros1002
Zeros (%)21.4%
Negative0
Negative (%)0.0%
Memory size41.3 KiB
2024-05-11T07:23:52.657717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum101
Range101
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5.8431279
Coefficient of variation (CV)6.4025174
Kurtosis166.67314
Mean0.91262976
Median Absolute Deviation (MAD)0
Skewness12.013731
Sum1055
Variance34.142143
MonotonicityNot monotonic
2024-05-11T07:23:53.085766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 1002
 
21.4%
1 48
 
1.0%
2 33
 
0.7%
3 25
 
0.5%
4 8
 
0.2%
5 5
 
0.1%
10 4
 
0.1%
7 4
 
0.1%
11 3
 
0.1%
6 3
 
0.1%
Other values (16) 21
 
0.4%
(Missing) 3534
75.4%
ValueCountFrequency (%)
0 1002
21.4%
1 48
 
1.0%
2 33
 
0.7%
3 25
 
0.5%
4 8
 
0.2%
5 5
 
0.1%
6 3
 
0.1%
7 4
 
0.1%
8 2
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
101 1
< 0.1%
85 1
< 0.1%
84 1
< 0.1%
58 2
< 0.1%
50 1
< 0.1%
30 1
< 0.1%
25 1
< 0.1%
24 1
< 0.1%
23 2
< 0.1%
20 1
< 0.1%

공장사무직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct23
Distinct (%)2.0%
Missing3519
Missing (%)75.0%
Infinite0
Infinite (%)0.0%
Mean1.1033305
Minimum0
Maximum33
Zeros742
Zeros (%)15.8%
Negative0
Negative (%)0.0%
Memory size41.3 KiB
2024-05-11T07:23:53.453627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile5
Maximum33
Range33
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.8429696
Coefficient of variation (CV)2.5767162
Kurtosis48.008998
Mean1.1033305
Median Absolute Deviation (MAD)0
Skewness5.9872042
Sum1292
Variance8.0824761
MonotonicityNot monotonic
2024-05-11T07:23:53.820297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 742
 
15.8%
1 196
 
4.2%
2 89
 
1.9%
3 43
 
0.9%
4 32
 
0.7%
5 22
 
0.5%
6 12
 
0.3%
7 8
 
0.2%
10 5
 
0.1%
12 4
 
0.1%
Other values (13) 18
 
0.4%
(Missing) 3519
75.0%
ValueCountFrequency (%)
0 742
15.8%
1 196
 
4.2%
2 89
 
1.9%
3 43
 
0.9%
4 32
 
0.7%
5 22
 
0.5%
6 12
 
0.3%
7 8
 
0.2%
8 2
 
< 0.1%
9 3
 
0.1%
ValueCountFrequency (%)
33 1
< 0.1%
32 1
< 0.1%
28 1
< 0.1%
25 1
< 0.1%
24 1
< 0.1%
22 1
< 0.1%
20 1
< 0.1%
19 2
< 0.1%
16 2
< 0.1%
15 1
< 0.1%

공장판매직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct24
Distinct (%)2.1%
Missing3559
Missing (%)75.9%
Infinite0
Infinite (%)0.0%
Mean1.3757737
Minimum0
Maximum90
Zeros768
Zeros (%)16.4%
Negative0
Negative (%)0.0%
Memory size41.3 KiB
2024-05-11T07:23:54.226944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile5
Maximum90
Range90
Interquartile range (IQR)1

Descriptive statistics

Standard deviation5.2981293
Coefficient of variation (CV)3.8510181
Kurtosis147.60816
Mean1.3757737
Median Absolute Deviation (MAD)0
Skewness10.847098
Sum1556
Variance28.070174
MonotonicityNot monotonic
2024-05-11T07:23:54.614679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 768
 
16.4%
1 124
 
2.6%
2 77
 
1.6%
3 50
 
1.1%
4 38
 
0.8%
5 21
 
0.4%
6 13
 
0.3%
7 7
 
0.1%
8 6
 
0.1%
20 4
 
0.1%
Other values (14) 23
 
0.5%
(Missing) 3559
75.9%
ValueCountFrequency (%)
0 768
16.4%
1 124
 
2.6%
2 77
 
1.6%
3 50
 
1.1%
4 38
 
0.8%
5 21
 
0.4%
6 13
 
0.3%
7 7
 
0.1%
8 6
 
0.1%
10 3
 
0.1%
ValueCountFrequency (%)
90 1
 
< 0.1%
80 1
 
< 0.1%
70 1
 
< 0.1%
45 1
 
< 0.1%
44 1
 
< 0.1%
42 1
 
< 0.1%
30 1
 
< 0.1%
21 1
 
< 0.1%
20 4
0.1%
18 1
 
< 0.1%

공장생산직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.6%
Missing3608
Missing (%)76.9%
Infinite0
Infinite (%)0.0%
Mean0.044362292
Minimum0
Maximum8
Zeros1058
Zeros (%)22.6%
Negative0
Negative (%)0.0%
Memory size41.3 KiB
2024-05-11T07:23:54.953518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum8
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.38934777
Coefficient of variation (CV)8.7765476
Kurtosis211.84402
Mean0.044362292
Median Absolute Deviation (MAD)0
Skewness13.128683
Sum48
Variance0.15159168
MonotonicityNot monotonic
2024-05-11T07:23:55.328382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 1058
 
22.6%
1 15
 
0.3%
2 3
 
0.1%
3 2
 
< 0.1%
4 2
 
< 0.1%
5 1
 
< 0.1%
8 1
 
< 0.1%
(Missing) 3608
76.9%
ValueCountFrequency (%)
0 1058
22.6%
1 15
 
0.3%
2 3
 
0.1%
3 2
 
< 0.1%
4 2
 
< 0.1%
5 1
 
< 0.1%
8 1
 
< 0.1%
ValueCountFrequency (%)
8 1
 
< 0.1%
5 1
 
< 0.1%
4 2
 
< 0.1%
3 2
 
< 0.1%
2 3
 
0.1%
1 15
 
0.3%
0 1058
22.6%
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size36.8 KiB
<NA>
3000 
임대
1325 
자가
365 

Length

Max length4
Median length4
Mean length3.2793177
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3000
64.0%
임대 1325
28.3%
자가 365
 
7.8%

Length

2024-05-11T07:23:55.798154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:23:56.253071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3000
64.0%
임대 1325
28.3%
자가 365
 
7.8%

보증액
Real number (ℝ)

MISSING  ZEROS 

Distinct77
Distinct (%)7.2%
Missing3620
Missing (%)77.2%
Infinite0
Infinite (%)0.0%
Mean23000744
Minimum0
Maximum2.1 × 109
Zeros461
Zeros (%)9.8%
Negative0
Negative (%)0.0%
Memory size41.3 KiB
2024-05-11T07:23:56.625050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5000000
Q315000000
95-th percentile80000000
Maximum2.1 × 109
Range2.1 × 109
Interquartile range (IQR)15000000

Descriptive statistics

Standard deviation97164390
Coefficient of variation (CV)4.224402
Kurtosis235.5011
Mean23000744
Median Absolute Deviation (MAD)5000000
Skewness13.413621
Sum2.4610796 × 1010
Variance9.4409186 × 1015
MonotonicityNot monotonic
2024-05-11T07:23:57.069345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 461
 
9.8%
10000000 142
 
3.0%
5000000 78
 
1.7%
20000000 68
 
1.4%
30000000 42
 
0.9%
50000000 34
 
0.7%
15000000 34
 
0.7%
1000000 17
 
0.4%
2000000 14
 
0.3%
3000000 12
 
0.3%
Other values (67) 168
 
3.6%
(Missing) 3620
77.2%
ValueCountFrequency (%)
0 461
9.8%
200000 1
 
< 0.1%
300000 3
 
0.1%
350000 1
 
< 0.1%
500000 4
 
0.1%
1000000 17
 
0.4%
1100000 1
 
< 0.1%
1400000 2
 
< 0.1%
2000000 14
 
0.3%
2500000 1
 
< 0.1%
ValueCountFrequency (%)
2100000000 1
< 0.1%
1162000000 1
< 0.1%
1055000000 1
< 0.1%
1000000000 1
< 0.1%
590000000 1
< 0.1%
500000000 1
< 0.1%
400000000 1
< 0.1%
350000000 2
< 0.1%
340209000 1
< 0.1%
340000000 1
< 0.1%

월세액
Real number (ℝ)

MISSING  ZEROS 

Distinct139
Distinct (%)13.1%
Missing3628
Missing (%)77.4%
Infinite0
Infinite (%)0.0%
Mean955086.37
Minimum0
Maximum38557020
Zeros448
Zeros (%)9.6%
Negative0
Negative (%)0.0%
Memory size41.3 KiB
2024-05-11T07:23:57.506487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median400000
Q31100000
95-th percentile3595000
Maximum38557020
Range38557020
Interquartile range (IQR)1100000

Descriptive statistics

Standard deviation2077021.3
Coefficient of variation (CV)2.1746948
Kurtosis115.18689
Mean955086.37
Median Absolute Deviation (MAD)400000
Skewness8.2437026
Sum1.0143017 × 109
Variance4.3140177 × 1012
MonotonicityNot monotonic
2024-05-11T07:23:58.205583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 448
 
9.6%
1000000 48
 
1.0%
500000 41
 
0.9%
600000 31
 
0.7%
700000 30
 
0.6%
1500000 26
 
0.6%
2000000 25
 
0.5%
900000 23
 
0.5%
300000 22
 
0.5%
400000 19
 
0.4%
Other values (129) 349
 
7.4%
(Missing) 3628
77.4%
ValueCountFrequency (%)
0 448
9.6%
50000 1
 
< 0.1%
100000 10
 
0.2%
110000 1
 
< 0.1%
120000 1
 
< 0.1%
143000 1
 
< 0.1%
150000 1
 
< 0.1%
170000 1
 
< 0.1%
200000 17
 
0.4%
250000 9
 
0.2%
ValueCountFrequency (%)
38557020 1
< 0.1%
19000000 1
< 0.1%
17180000 1
< 0.1%
16000000 1
< 0.1%
13545000 1
< 0.1%
11600000 1
< 0.1%
10000000 1
< 0.1%
9200000 1
< 0.1%
9000000 1
< 0.1%
8760000 1
< 0.1%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing1673
Missing (%)35.7%
Memory size9.3 KiB
False
3017 
(Missing)
1673 
ValueCountFrequency (%)
False 3017
64.3%
(Missing) 1673
35.7%
2024-05-11T07:23:58.578302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct32
Distinct (%)1.1%
Missing1673
Missing (%)35.7%
Infinite0
Infinite (%)0.0%
Mean1.6380709
Minimum0
Maximum3504.05
Zeros2977
Zeros (%)63.5%
Negative0
Negative (%)0.0%
Memory size41.3 KiB
2024-05-11T07:23:58.997640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum3504.05
Range3504.05
Interquartile range (IQR)0

Descriptive statistics

Standard deviation64.065047
Coefficient of variation (CV)39.110056
Kurtosis2964.7118
Mean1.6380709
Median Absolute Deviation (MAD)0
Skewness54.227169
Sum4942.06
Variance4104.3302
MonotonicityNot monotonic
2024-05-11T07:23:59.414040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0.0 2977
63.5%
3.3 4
 
0.1%
16.5 3
 
0.1%
20.0 2
 
< 0.1%
30.0 2
 
< 0.1%
35.9 2
 
< 0.1%
9.0 2
 
< 0.1%
20.7 1
 
< 0.1%
99.0 1
 
< 0.1%
92.4 1
 
< 0.1%
Other values (22) 22
 
0.5%
(Missing) 1673
35.7%
ValueCountFrequency (%)
0.0 2977
63.5%
3.3 4
 
0.1%
4.0 1
 
< 0.1%
5.0 1
 
< 0.1%
6.0 1
 
< 0.1%
6.6 1
 
< 0.1%
9.0 2
 
< 0.1%
14.65 1
 
< 0.1%
16.5 3
 
0.1%
20.0 2
 
< 0.1%
ValueCountFrequency (%)
3504.05 1
< 0.1%
195.44 1
< 0.1%
99.0 1
< 0.1%
98.91 1
< 0.1%
92.4 1
< 0.1%
89.09 1
< 0.1%
78.88 1
< 0.1%
69.66 1
< 0.1%
60.0 1
< 0.1%
51.79 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4690
Missing (%)100.0%
Memory size41.3 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4690
Missing (%)100.0%
Memory size41.3 KiB

홈페이지
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing4689
Missing (%)> 99.9%
Memory size36.8 KiB
2024-05-11T07:23:59.984820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length43
Mean length43
Min length43

Characters and Unicode

Total characters43
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowhttps://smartstore.naver.com/health_shares2
ValueCountFrequency (%)
https://smartstore.naver.com/health_shares2 1
100.0%
2024-05-11T07:24:00.854259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 5
11.6%
t 5
11.6%
h 4
9.3%
r 4
9.3%
e 4
9.3%
a 4
9.3%
/ 3
 
7.0%
. 2
 
4.7%
o 2
 
4.7%
m 2
 
4.7%
Other values (8) 8
18.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 35
81.4%
Other Punctuation 6
 
14.0%
Connector Punctuation 1
 
2.3%
Decimal Number 1
 
2.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 5
14.3%
t 5
14.3%
h 4
11.4%
r 4
11.4%
e 4
11.4%
a 4
11.4%
o 2
 
5.7%
m 2
 
5.7%
p 1
 
2.9%
n 1
 
2.9%
Other values (3) 3
8.6%
Other Punctuation
ValueCountFrequency (%)
/ 3
50.0%
. 2
33.3%
: 1
 
16.7%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 35
81.4%
Common 8
 
18.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 5
14.3%
t 5
14.3%
h 4
11.4%
r 4
11.4%
e 4
11.4%
a 4
11.4%
o 2
 
5.7%
m 2
 
5.7%
p 1
 
2.9%
n 1
 
2.9%
Other values (3) 3
8.6%
Common
ValueCountFrequency (%)
/ 3
37.5%
. 2
25.0%
: 1
 
12.5%
_ 1
 
12.5%
2 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 43
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 5
11.6%
t 5
11.6%
h 4
9.3%
r 4
9.3%
e 4
9.3%
a 4
9.3%
/ 3
 
7.0%
. 2
 
4.7%
o 2
 
4.7%
m 2
 
4.7%
Other values (8) 8
18.6%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031300003130000-134-1998-0000119980212<NA>3폐업2폐업20220824<NA><NA><NA><NA><NA>121862서울특별시 마포구 아현동 ***-** 건우약국 *층서울특별시 마포구 마포대로 ***-*, 건우약국 *층 (아현동)4117건우약국2022-08-26 10:47:48I2021-12-07 22:08:00.0<NA>196034.54787450031.784279<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
131300003130000-134-2004-0000120040310<NA>3폐업2폐업20120925<NA><NA><NA>00020337688164.48121827서울특별시 마포구 망원동 ***-**번지 *층서울특별시 마포구 월드컵로**길 ** (망원동, *층)3964솔고헬스케어2011-10-30 13:26:25I2018-08-31 23:59:59.0<NA>191539.04284450647.376283영업장판매<NA><NA><NA><NA><NA><NA>0100임대100000001500000N0.0<NA><NA><NA>
231300003130000-134-2004-0000220040312<NA>3폐업2폐업20070402<NA><NA><NA><NA>6.40121849서울특별시 마포구 성산동 ***-*번지 다농마트내<NA><NA>고려인삼코너2006-06-05 00:00:00I2018-08-31 23:59:59.0<NA>190931.000876451427.722145영업장판매<NA><NA><NA><NA><NA><NA>0010임대1000000560000N0.0<NA><NA><NA>
331300003130000-134-2004-0000320040315<NA>1영업/정상1영업<NA><NA><NA><NA>02 3356661161.34121827서울특별시 마포구 망원동 ***-*번지 리츠아파트 B***호서울특별시 마포구 월드컵로**길 **, B***호 (망원동, 리츠아파트)3964(주)페드넷2013-08-26 13:19:33I2018-08-31 23:59:59.0<NA>191692.980564450656.710828전자상거래(통신판매업)<NA><NA><NA><NA><NA><NA>0600임대200000001200000N0.0<NA><NA><NA>
431300003130000-134-2004-0000420040317<NA>3폐업2폐업20110823<NA><NA><NA>0231431116198.00121869서울특별시 마포구 연남동 ***-**번지 지남빌딩 ***호<NA><NA>(주)헬쓰웨이인터내셔날2004-12-24 00:00:00I2018-08-31 23:59:59.0<NA>192937.736221450878.984951방문판매<NA><NA><NA><NA><NA><NA>0400임대700000006600000N0.0<NA><NA><NA>
531300003130000-134-2004-0000520040319<NA>3폐업2폐업20070112<NA><NA><NA>02 7171926146.36121811서울특별시 마포구 대흥동 ***-*번지 신영빌딩 *층<NA><NA>주식회사 아이허브2004-11-01 00:00:00I2018-08-31 23:59:59.0<NA>194834.929798449298.894966통신판매<NA><NA><NA><NA><NA><NA>5000임대300000002200000N0.0<NA><NA><NA>
631300003130000-134-2004-0000620040323<NA>3폐업2폐업20060614<NA><NA><NA>02 338290417.35121816서울특별시 마포구 동교동 ***-*번지 마젤란** ***호<NA><NA>주식회사 씨케이바이오2005-08-18 00:00:00I2018-08-31 23:59:59.0<NA>193248.820008450611.763042영업장판매<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
731300003130000-134-2004-0000720040323<NA>3폐업2폐업20041122<NA><NA><NA>02 711519292.40121050서울특별시 마포구 마포동 ***번지 강변한신코아 ****호<NA><NA>주식회사 보령라인2004-11-01 00:00:00I2018-08-31 23:59:59.0<NA>194974.587674448229.063825통신판매<NA><NA><NA><NA><NA><NA>0000임대10000000750000N0.0<NA><NA><NA>
831300003130000-134-2004-000082004-03-29<NA>1영업/정상1영업<NA><NA><NA><NA>02 30434481281.60121-850서울특별시 마포구 성산동 *** ***,***번지 제*상가 *호서울특별시 마포구 월드컵북로 *** (성산동, 제*상가 *호)3936(주)농협유통 하나로마트 성산점2024-04-08 15:33:17U2023-12-03 23:01:00.0<NA>191263.451931452207.500654<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
931300003130000-134-2004-0000920040330<NA>3폐업2폐업20040507<NA><NA><NA>02 7161734165.00121875서울특별시 마포구 용강동 ***-**번지 *층<NA><NA>한솔2004-03-30 00:00:00I2018-08-31 23:59:59.0<NA>194818.840187448772.43154영업장판매<NA><NA><NA><NA><NA><NA>5140임대4000000<NA>N0.0<NA><NA><NA>
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