Overview

Dataset statistics

Number of variables44
Number of observations786
Missing cells8771
Missing cells (%)25.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory289.5 KiB
Average record size in memory377.2 B

Variable types

Categorical19
Text7
DateTime4
Unsupported9
Numeric4
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
Author서초구
URLhttps://data.seoul.go.kr/dataList/OA-18073/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (65.3%)Imbalance
여성종사자수 is highly imbalanced (65.3%)Imbalance
급수시설구분명 is highly imbalanced (96.4%)Imbalance
총인원 is highly imbalanced (66.8%)Imbalance
인허가취소일자 has 786 (100.0%) missing valuesMissing
폐업일자 has 343 (43.6%) missing valuesMissing
휴업시작일자 has 786 (100.0%) missing valuesMissing
휴업종료일자 has 786 (100.0%) missing valuesMissing
재개업일자 has 786 (100.0%) missing valuesMissing
전화번호 has 302 (38.4%) missing valuesMissing
소재지면적 has 294 (37.4%) missing valuesMissing
도로명주소 has 91 (11.6%) missing valuesMissing
도로명우편번호 has 93 (11.8%) missing valuesMissing
영업장주변구분명 has 786 (100.0%) missing valuesMissing
등급구분명 has 786 (100.0%) missing valuesMissing
다중이용업소여부 has 282 (35.9%) missing valuesMissing
시설총규모 has 282 (35.9%) missing valuesMissing
전통업소지정번호 has 786 (100.0%) missing valuesMissing
전통업소주된음식 has 786 (100.0%) missing valuesMissing
홈페이지 has 786 (100.0%) missing valuesMissing
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
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
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
시설총규모 has 447 (56.9%) zerosZeros

Reproduction

Analysis started2024-05-11 00:49:08.218309
Analysis finished2024-05-11 00:49:10.440918
Duration2.22 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
3210000
786 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3210000
2nd row3210000
3rd row3210000
4th row3210000
5th row3210000

Common Values

ValueCountFrequency (%)
3210000 786
100.0%

Length

2024-05-11T00:49:10.606030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:49:10.919227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3210000 786
100.0%

관리번호
Text

UNIQUE 

Distinct786
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
2024-05-11T00:49:11.366661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters17292
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

Unique786 ?
Unique (%)100.0%

Sample

1st row3210000-135-2004-00001
2nd row3210000-135-2004-00002
3rd row3210000-135-2004-00003
4th row3210000-135-2004-00004
5th row3210000-135-2004-00005
ValueCountFrequency (%)
3210000-135-2004-00001 1
 
0.1%
3210000-135-2021-00007 1
 
0.1%
3210000-135-2020-00020 1
 
0.1%
3210000-135-2020-00030 1
 
0.1%
3210000-135-2020-00021 1
 
0.1%
3210000-135-2020-00022 1
 
0.1%
3210000-135-2020-00023 1
 
0.1%
3210000-135-2020-00024 1
 
0.1%
3210000-135-2020-00025 1
 
0.1%
3210000-135-2020-00026 1
 
0.1%
Other values (776) 776
98.7%
2024-05-11T00:49:12.353460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6829
39.5%
- 2358
 
13.6%
1 2311
 
13.4%
2 2187
 
12.6%
3 1827
 
10.6%
5 966
 
5.6%
4 240
 
1.4%
6 152
 
0.9%
8 144
 
0.8%
7 142
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14934
86.4%
Dash Punctuation 2358
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6829
45.7%
1 2311
 
15.5%
2 2187
 
14.6%
3 1827
 
12.2%
5 966
 
6.5%
4 240
 
1.6%
6 152
 
1.0%
8 144
 
1.0%
7 142
 
1.0%
9 136
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 2358
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17292
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6829
39.5%
- 2358
 
13.6%
1 2311
 
13.4%
2 2187
 
12.6%
3 1827
 
10.6%
5 966
 
5.6%
4 240
 
1.4%
6 152
 
0.9%
8 144
 
0.8%
7 142
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17292
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6829
39.5%
- 2358
 
13.6%
1 2311
 
13.4%
2 2187
 
12.6%
3 1827
 
10.6%
5 966
 
5.6%
4 240
 
1.4%
6 152
 
0.9%
8 144
 
0.8%
7 142
 
0.8%
Distinct684
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
Minimum2004-02-18 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T00:49:12.895699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:49:13.437263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing786
Missing (%)100.0%
Memory size7.0 KiB
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
3
443 
1
343 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 443
56.4%
1 343
43.6%

Length

2024-05-11T00:49:13.941826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:49:14.292826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 443
56.4%
1 343
43.6%

영업상태명
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
폐업
443 
영업/정상
343 

Length

Max length5
Median length2
Mean length3.3091603
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 443
56.4%
영업/정상 343
43.6%

Length

2024-05-11T00:49:14.655761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:49:15.116187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 443
56.4%
영업/정상 343
43.6%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
2
443 
1
343 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 443
56.4%
1 343
43.6%

Length

2024-05-11T00:49:15.791818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:49:16.277760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 443
56.4%
1 343
43.6%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
폐업
443 
영업
343 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 443
56.4%
영업 343
43.6%

Length

2024-05-11T00:49:16.675739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:49:17.058506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 443
56.4%
영업 343
43.6%

폐업일자
Date

MISSING 

Distinct360
Distinct (%)81.3%
Missing343
Missing (%)43.6%
Memory size6.3 KiB
Minimum2004-07-29 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T00:49:17.476948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:49:18.036432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing786
Missing (%)100.0%
Memory size7.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing786
Missing (%)100.0%
Memory size7.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing786
Missing (%)100.0%
Memory size7.0 KiB

전화번호
Text

MISSING 

Distinct471
Distinct (%)97.3%
Missing302
Missing (%)38.4%
Memory size6.3 KiB
2024-05-11T00:49:18.883602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.634298
Min length3

Characters and Unicode

Total characters5147
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

Unique458 ?
Unique (%)94.6%

Sample

1st row02 4421081
2nd row02 5882136
3rd row070 78608351
4th row02 5359670
5th row502
ValueCountFrequency (%)
02 230
 
24.7%
070 55
 
5.9%
031 8
 
0.9%
523 6
 
0.6%
529 5
 
0.5%
574 4
 
0.4%
533 4
 
0.4%
544 3
 
0.3%
525 3
 
0.3%
593 3
 
0.3%
Other values (554) 610
65.5%
2024-05-11T00:49:20.131488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 901
17.5%
2 692
13.4%
614
11.9%
5 527
10.2%
7 420
8.2%
1 384
7.5%
3 368
7.1%
8 365
7.1%
4 325
 
6.3%
6 321
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4533
88.1%
Space Separator 614
 
11.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 901
19.9%
2 692
15.3%
5 527
11.6%
7 420
9.3%
1 384
8.5%
3 368
8.1%
8 365
8.1%
4 325
 
7.2%
6 321
 
7.1%
9 230
 
5.1%
Space Separator
ValueCountFrequency (%)
614
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5147
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 901
17.5%
2 692
13.4%
614
11.9%
5 527
10.2%
7 420
8.2%
1 384
7.5%
3 368
7.1%
8 365
7.1%
4 325
 
6.3%
6 321
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5147
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 901
17.5%
2 692
13.4%
614
11.9%
5 527
10.2%
7 420
8.2%
1 384
7.5%
3 368
7.1%
8 365
7.1%
4 325
 
6.3%
6 321
 
6.2%

소재지면적
Text

MISSING 

Distinct287
Distinct (%)58.3%
Missing294
Missing (%)37.4%
Memory size6.3 KiB
2024-05-11T00:49:21.503720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length4.8719512
Min length3

Characters and Unicode

Total characters2397
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

Unique247 ?
Unique (%)50.2%

Sample

1st row100.00
2nd row171.60
3rd row141.00
4th row555.00
5th row70.00
ValueCountFrequency (%)
3.30 43
 
8.7%
00 42
 
8.5%
0.00 27
 
5.5%
33.00 13
 
2.6%
10.00 8
 
1.6%
50.00 7
 
1.4%
66.00 7
 
1.4%
20.00 6
 
1.2%
30.00 6
 
1.2%
60.00 6
 
1.2%
Other values (277) 327
66.5%
2024-05-11T00:49:23.145797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 688
28.7%
. 492
20.5%
3 244
 
10.2%
1 197
 
8.2%
2 147
 
6.1%
6 131
 
5.5%
5 124
 
5.2%
4 115
 
4.8%
8 96
 
4.0%
9 92
 
3.8%
Other values (2) 71
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1904
79.4%
Other Punctuation 493
 
20.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 688
36.1%
3 244
 
12.8%
1 197
 
10.3%
2 147
 
7.7%
6 131
 
6.9%
5 124
 
6.5%
4 115
 
6.0%
8 96
 
5.0%
9 92
 
4.8%
7 70
 
3.7%
Other Punctuation
ValueCountFrequency (%)
. 492
99.8%
, 1
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 2397
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 688
28.7%
. 492
20.5%
3 244
 
10.2%
1 197
 
8.2%
2 147
 
6.1%
6 131
 
5.5%
5 124
 
5.2%
4 115
 
4.8%
8 96
 
4.0%
9 92
 
3.8%
Other values (2) 71
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2397
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 688
28.7%
. 492
20.5%
3 244
 
10.2%
1 197
 
8.2%
2 147
 
6.1%
6 131
 
5.5%
5 124
 
5.2%
4 115
 
4.8%
8 96
 
4.0%
9 92
 
3.8%
Other values (2) 71
 
3.0%
Distinct182
Distinct (%)23.2%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
2024-05-11T00:49:24.073286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.2391858
Min length6

Characters and Unicode

Total characters4904
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

Unique56 ?
Unique (%)7.1%

Sample

1st row137850
2nd row137876
3rd row137863
4th row137839
5th row137130
ValueCountFrequency (%)
137860 33
 
4.2%
137858 23
 
2.9%
137863 23
 
2.9%
137130 15
 
1.9%
137902 15
 
1.9%
137890 15
 
1.9%
137888 14
 
1.8%
137887 13
 
1.7%
137875 13
 
1.7%
137862 13
 
1.7%
Other values (172) 609
77.5%
2024-05-11T00:49:25.363436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 971
19.8%
3 921
18.8%
1 900
18.4%
8 811
16.5%
0 270
 
5.5%
9 233
 
4.8%
6 203
 
4.1%
- 188
 
3.8%
5 169
 
3.4%
4 124
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4716
96.2%
Dash Punctuation 188
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 971
20.6%
3 921
19.5%
1 900
19.1%
8 811
17.2%
0 270
 
5.7%
9 233
 
4.9%
6 203
 
4.3%
5 169
 
3.6%
4 124
 
2.6%
2 114
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 188
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4904
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 971
19.8%
3 921
18.8%
1 900
18.4%
8 811
16.5%
0 270
 
5.5%
9 233
 
4.8%
6 203
 
4.1%
- 188
 
3.8%
5 169
 
3.4%
4 124
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4904
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 971
19.8%
3 921
18.8%
1 900
18.4%
8 811
16.5%
0 270
 
5.5%
9 233
 
4.8%
6 203
 
4.1%
- 188
 
3.8%
5 169
 
3.4%
4 124
 
2.5%
Distinct578
Distinct (%)73.5%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
2024-05-11T00:49:25.998739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length41
Mean length28.36514
Min length16

Characters and Unicode

Total characters22295
Distinct characters323
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique498 ?
Unique (%)63.4%

Sample

1st row서울특별시 서초구 방배동 ****-**번지 유신빌딩 *층
2nd row서울특별시 서초구 서초동 ****-* 르네상스오피스텔 ***호
3rd row서울특별시 서초구 서초동 ****-**번지 원효빌딩 ***호
4th row서울특별시 서초구 방배동 ***-**번지 정진빌딩 *층
5th row서울특별시 서초구 양재동 275
ValueCountFrequency (%)
서울특별시 786
18.0%
서초구 784
18.0%
415
9.5%
번지 361
8.3%
354
8.1%
서초동 350
8.0%
286
 
6.6%
양재동 168
 
3.8%
방배동 134
 
3.1%
잠원동 70
 
1.6%
Other values (418) 656
15.0%
2024-05-11T00:49:27.263777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 5028
22.6%
3959
17.8%
1948
 
8.7%
1150
 
5.2%
822
 
3.7%
790
 
3.5%
790
 
3.5%
787
 
3.5%
787
 
3.5%
786
 
3.5%
Other values (313) 5448
24.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12229
54.9%
Other Punctuation 5068
22.7%
Space Separator 3959
 
17.8%
Dash Punctuation 739
 
3.3%
Uppercase Letter 122
 
0.5%
Decimal Number 107
 
0.5%
Close Punctuation 26
 
0.1%
Open Punctuation 26
 
0.1%
Lowercase Letter 9
 
< 0.1%
Math Symbol 5
 
< 0.1%
Other values (2) 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1948
15.9%
1150
 
9.4%
822
 
6.7%
790
 
6.5%
790
 
6.5%
787
 
6.4%
787
 
6.4%
786
 
6.4%
421
 
3.4%
418
 
3.4%
Other values (265) 3530
28.9%
Uppercase Letter
ValueCountFrequency (%)
B 23
18.9%
A 12
9.8%
E 10
8.2%
T 10
8.2%
R 9
 
7.4%
O 9
 
7.4%
L 8
 
6.6%
K 8
 
6.6%
N 7
 
5.7%
W 5
 
4.1%
Other values (9) 21
17.2%
Decimal Number
ValueCountFrequency (%)
5 19
17.8%
2 17
15.9%
1 16
15.0%
3 13
12.1%
6 11
10.3%
8 10
9.3%
7 8
7.5%
9 5
 
4.7%
0 4
 
3.7%
4 4
 
3.7%
Other Punctuation
ValueCountFrequency (%)
* 5028
99.2%
, 31
 
0.6%
. 6
 
0.1%
& 1
 
< 0.1%
: 1
 
< 0.1%
/ 1
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
a 4
44.4%
r 1
 
11.1%
e 1
 
11.1%
w 1
 
11.1%
o 1
 
11.1%
b 1
 
11.1%
Space Separator
ValueCountFrequency (%)
3959
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 739
100.0%
Close Punctuation
ValueCountFrequency (%)
) 26
100.0%
Open Punctuation
ValueCountFrequency (%)
( 26
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%
Other Symbol
ValueCountFrequency (%)
4
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12229
54.9%
Common 9934
44.6%
Latin 132
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1948
15.9%
1150
 
9.4%
822
 
6.7%
790
 
6.5%
790
 
6.5%
787
 
6.4%
787
 
6.4%
786
 
6.4%
421
 
3.4%
418
 
3.4%
Other values (265) 3530
28.9%
Latin
ValueCountFrequency (%)
B 23
17.4%
A 12
 
9.1%
E 10
 
7.6%
T 10
 
7.6%
R 9
 
6.8%
O 9
 
6.8%
L 8
 
6.1%
K 8
 
6.1%
N 7
 
5.3%
W 5
 
3.8%
Other values (16) 31
23.5%
Common
ValueCountFrequency (%)
* 5028
50.6%
3959
39.9%
- 739
 
7.4%
, 31
 
0.3%
) 26
 
0.3%
( 26
 
0.3%
5 19
 
0.2%
2 17
 
0.2%
1 16
 
0.2%
3 13
 
0.1%
Other values (12) 60
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12229
54.9%
ASCII 10061
45.1%
CJK Compat 4
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 5028
50.0%
3959
39.3%
- 739
 
7.3%
, 31
 
0.3%
) 26
 
0.3%
( 26
 
0.3%
B 23
 
0.2%
5 19
 
0.2%
2 17
 
0.2%
1 16
 
0.2%
Other values (36) 177
 
1.8%
Hangul
ValueCountFrequency (%)
1948
15.9%
1150
 
9.4%
822
 
6.7%
790
 
6.5%
790
 
6.5%
787
 
6.4%
787
 
6.4%
786
 
6.4%
421
 
3.4%
418
 
3.4%
Other values (265) 3530
28.9%
CJK Compat
ValueCountFrequency (%)
4
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명주소
Text

MISSING 

Distinct588
Distinct (%)84.6%
Missing91
Missing (%)11.6%
Memory size6.3 KiB
2024-05-11T00:49:28.038817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length50
Mean length34.844604
Min length22

Characters and Unicode

Total characters24217
Distinct characters339
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique527 ?
Unique (%)75.8%

Sample

1st row서울특별시 서초구 서초중앙로 ** (서초동,르네상스오피스텔 ***호)
2nd row서울특별시 서초구 남부순환로 **** (서초동,원효빌딩 ***호)
3rd row서울특별시 서초구 마방로 68 (양재동)
4th row서울특별시 서초구 효령로**길 ** (서초동,서초이오빌 *층)
5th row서울특별시 서초구 남부순환로 **** (서초동,월림빌딩 *층)
ValueCountFrequency (%)
서울특별시 695
14.7%
서초구 693
14.7%
686
14.5%
424
 
9.0%
320
 
6.8%
서초동 276
 
5.8%
양재동 134
 
2.8%
방배동 104
 
2.2%
강남대로**길 74
 
1.6%
강남대로 64
 
1.4%
Other values (526) 1250
26.5%
2024-05-11T00:49:29.162449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4025
16.6%
* 3988
16.5%
1881
 
7.8%
1151
 
4.8%
, 860
 
3.6%
752
 
3.1%
) 702
 
2.9%
( 702
 
2.9%
699
 
2.9%
699
 
2.9%
Other values (329) 8758
36.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13604
56.2%
Other Punctuation 4851
 
20.0%
Space Separator 4025
 
16.6%
Close Punctuation 702
 
2.9%
Open Punctuation 702
 
2.9%
Dash Punctuation 112
 
0.5%
Uppercase Letter 110
 
0.5%
Decimal Number 104
 
0.4%
Letter Number 3
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1881
 
13.8%
1151
 
8.5%
752
 
5.5%
699
 
5.1%
699
 
5.1%
698
 
5.1%
696
 
5.1%
695
 
5.1%
686
 
5.0%
490
 
3.6%
Other values (287) 5157
37.9%
Uppercase Letter
ValueCountFrequency (%)
B 18
16.4%
A 15
13.6%
E 12
10.9%
T 10
9.1%
R 9
 
8.2%
W 5
 
4.5%
L 5
 
4.5%
O 5
 
4.5%
N 4
 
3.6%
D 4
 
3.6%
Other values (10) 23
20.9%
Decimal Number
ValueCountFrequency (%)
2 27
26.0%
1 21
20.2%
5 12
11.5%
0 9
 
8.7%
3 9
 
8.7%
9 8
 
7.7%
6 7
 
6.7%
7 4
 
3.8%
4 4
 
3.8%
8 3
 
2.9%
Other Punctuation
ValueCountFrequency (%)
* 3988
82.2%
, 860
 
17.7%
. 1
 
< 0.1%
& 1
 
< 0.1%
/ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
4025
100.0%
Close Punctuation
ValueCountFrequency (%)
) 702
100.0%
Open Punctuation
ValueCountFrequency (%)
( 702
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 112
100.0%
Letter Number
ValueCountFrequency (%)
3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
a 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13604
56.2%
Common 10498
43.3%
Latin 115
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1881
 
13.8%
1151
 
8.5%
752
 
5.5%
699
 
5.1%
699
 
5.1%
698
 
5.1%
696
 
5.1%
695
 
5.1%
686
 
5.0%
490
 
3.6%
Other values (287) 5157
37.9%
Latin
ValueCountFrequency (%)
B 18
15.7%
A 15
13.0%
E 12
10.4%
T 10
 
8.7%
R 9
 
7.8%
W 5
 
4.3%
L 5
 
4.3%
O 5
 
4.3%
N 4
 
3.5%
D 4
 
3.5%
Other values (12) 28
24.3%
Common
ValueCountFrequency (%)
4025
38.3%
* 3988
38.0%
, 860
 
8.2%
) 702
 
6.7%
( 702
 
6.7%
- 112
 
1.1%
2 27
 
0.3%
1 21
 
0.2%
5 12
 
0.1%
0 9
 
0.1%
Other values (10) 40
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13604
56.2%
ASCII 10610
43.8%
Number Forms 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4025
37.9%
* 3988
37.6%
, 860
 
8.1%
) 702
 
6.6%
( 702
 
6.6%
- 112
 
1.1%
2 27
 
0.3%
1 21
 
0.2%
B 18
 
0.2%
A 15
 
0.1%
Other values (31) 140
 
1.3%
Hangul
ValueCountFrequency (%)
1881
 
13.8%
1151
 
8.5%
752
 
5.5%
699
 
5.1%
699
 
5.1%
698
 
5.1%
696
 
5.1%
695
 
5.1%
686
 
5.0%
490
 
3.6%
Other values (287) 5157
37.9%
Number Forms
ValueCountFrequency (%)
3
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct190
Distinct (%)27.4%
Missing93
Missing (%)11.8%
Infinite0
Infinite (%)0.0%
Mean6659.6089
Minimum6035
Maximum8594
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.0 KiB
2024-05-11T00:49:29.606994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6035
5-th percentile6526
Q16600
median6649
Q36734
95-th percentile6778
Maximum8594
Range2559
Interquartile range (IQR)134

Descriptive statistics

Standard deviation111.56441
Coefficient of variation (CV)0.016752396
Kurtosis130.68145
Mean6659.6089
Median Absolute Deviation (MAD)71
Skewness7.2517878
Sum4615109
Variance12446.617
MonotonicityNot monotonic
2024-05-11T00:49:30.179302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6628 18
 
2.3%
6626 17
 
2.2%
6621 15
 
1.9%
6627 14
 
1.8%
6775 13
 
1.7%
6524 13
 
1.7%
6734 13
 
1.7%
6588 11
 
1.4%
6752 11
 
1.4%
6619 11
 
1.4%
Other values (180) 557
70.9%
(Missing) 93
 
11.8%
ValueCountFrequency (%)
6035 1
 
0.1%
6501 1
 
0.1%
6502 1
 
0.1%
6503 1
 
0.1%
6510 1
 
0.1%
6511 1
 
0.1%
6512 4
 
0.5%
6519 2
 
0.3%
6524 13
1.7%
6525 6
0.8%
ValueCountFrequency (%)
8594 1
 
0.1%
6806 1
 
0.1%
6802 4
0.5%
6800 2
0.3%
6793 1
 
0.1%
6792 1
 
0.1%
6789 1
 
0.1%
6787 2
0.3%
6786 1
 
0.1%
6784 1
 
0.1%
Distinct769
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
2024-05-11T00:49:30.888207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length19
Mean length8.5139949
Min length2

Characters and Unicode

Total characters6692
Distinct characters482
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique753 ?
Unique (%)95.8%

Sample

1st row(주)글로벌헬스케어
2nd row파맥스팜(주)
3rd row네-벤트리
4th row(주)오엔팜
5th row(주)동원F&B
ValueCountFrequency (%)
주식회사 189
 
18.0%
21
 
2.0%
유한회사 4
 
0.4%
주)일맥메디라이프 3
 
0.3%
주)퍼스트마인드 2
 
0.2%
트리즈코퍼레이션 2
 
0.2%
세레비 2
 
0.2%
강남점 2
 
0.2%
서울지점 2
 
0.2%
비티엔 2
 
0.2%
Other values (805) 820
78.2%
2024-05-11T00:49:32.260538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
610
 
9.1%
) 441
 
6.6%
( 440
 
6.6%
354
 
5.3%
263
 
3.9%
208
 
3.1%
199
 
3.0%
199
 
3.0%
197
 
2.9%
116
 
1.7%
Other values (472) 3665
54.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5366
80.2%
Close Punctuation 441
 
6.6%
Open Punctuation 440
 
6.6%
Space Separator 263
 
3.9%
Uppercase Letter 99
 
1.5%
Lowercase Letter 62
 
0.9%
Other Punctuation 12
 
0.2%
Decimal Number 7
 
0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
610
 
11.4%
354
 
6.6%
208
 
3.9%
199
 
3.7%
199
 
3.7%
197
 
3.7%
116
 
2.2%
110
 
2.0%
100
 
1.9%
96
 
1.8%
Other values (421) 3177
59.2%
Uppercase Letter
ValueCountFrequency (%)
H 11
 
11.1%
L 11
 
11.1%
B 9
 
9.1%
C 7
 
7.1%
N 7
 
7.1%
S 5
 
5.1%
P 5
 
5.1%
A 5
 
5.1%
I 4
 
4.0%
F 4
 
4.0%
Other values (13) 31
31.3%
Lowercase Letter
ValueCountFrequency (%)
e 10
16.1%
l 9
14.5%
a 6
9.7%
h 4
 
6.5%
t 4
 
6.5%
s 4
 
6.5%
m 3
 
4.8%
g 3
 
4.8%
o 3
 
4.8%
r 3
 
4.8%
Other values (8) 13
21.0%
Decimal Number
ValueCountFrequency (%)
2 3
42.9%
4 2
28.6%
0 1
 
14.3%
1 1
 
14.3%
Other Punctuation
ValueCountFrequency (%)
& 10
83.3%
. 2
 
16.7%
Close Punctuation
ValueCountFrequency (%)
) 441
100.0%
Open Punctuation
ValueCountFrequency (%)
( 440
100.0%
Space Separator
ValueCountFrequency (%)
263
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5366
80.2%
Common 1165
 
17.4%
Latin 161
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
610
 
11.4%
354
 
6.6%
208
 
3.9%
199
 
3.7%
199
 
3.7%
197
 
3.7%
116
 
2.2%
110
 
2.0%
100
 
1.9%
96
 
1.8%
Other values (421) 3177
59.2%
Latin
ValueCountFrequency (%)
H 11
 
6.8%
L 11
 
6.8%
e 10
 
6.2%
B 9
 
5.6%
l 9
 
5.6%
C 7
 
4.3%
N 7
 
4.3%
a 6
 
3.7%
S 5
 
3.1%
P 5
 
3.1%
Other values (31) 81
50.3%
Common
ValueCountFrequency (%)
) 441
37.9%
( 440
37.8%
263
22.6%
& 10
 
0.9%
2 3
 
0.3%
4 2
 
0.2%
. 2
 
0.2%
- 2
 
0.2%
0 1
 
0.1%
1 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5366
80.2%
ASCII 1326
 
19.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
610
 
11.4%
354
 
6.6%
208
 
3.9%
199
 
3.7%
199
 
3.7%
197
 
3.7%
116
 
2.2%
110
 
2.0%
100
 
1.9%
96
 
1.8%
Other values (421) 3177
59.2%
ASCII
ValueCountFrequency (%)
) 441
33.3%
( 440
33.2%
263
19.8%
H 11
 
0.8%
L 11
 
0.8%
e 10
 
0.8%
& 10
 
0.8%
B 9
 
0.7%
l 9
 
0.7%
C 7
 
0.5%
Other values (41) 115
 
8.7%
Distinct783
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
Minimum2004-03-26 00:00:00
Maximum2024-05-09 14:15:18
2024-05-11T00:49:32.999302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:49:33.562593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
I
421 
U
365 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 421
53.6%
U 365
46.4%

Length

2024-05-11T00:49:33.966150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:49:34.333273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 421
53.6%
u 365
46.4%
Distinct410
Distinct (%)52.2%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:05:00
2024-05-11T00:49:34.779264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:49:35.237688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
건강기능식품유통전문판매업
786 

Length

Max length13
Median length13
Mean length13
Min length13

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건강기능식품유통전문판매업 786
100.0%

Length

2024-05-11T00:49:35.842835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:49:36.422713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건강기능식품유통전문판매업 786
100.0%

좌표정보(X)
Real number (ℝ)

Distinct543
Distinct (%)69.5%
Missing5
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean201611.89
Minimum189920.53
Maximum205634.31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.0 KiB
2024-05-11T00:49:36.894725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189920.53
5-th percentile198660.62
Q1200792.24
median201680.91
Q3202677.86
95-th percentile203812.72
Maximum205634.31
Range15713.783
Interquartile range (IQR)1885.615

Descriptive statistics

Standard deviation1602.7746
Coefficient of variation (CV)0.0079498021
Kurtosis2.7601748
Mean201611.89
Median Absolute Deviation (MAD)961.62687
Skewness-0.80452854
Sum1.5745889 × 108
Variance2568886.4
MonotonicityNot monotonic
2024-05-11T00:49:37.447134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202623.297219041 12
 
1.5%
203204.755637424 8
 
1.0%
202407.97558606 8
 
1.0%
202152.435828986 8
 
1.0%
202481.661169413 7
 
0.9%
203576.547018477 6
 
0.8%
202524.096001449 6
 
0.8%
203392.793460583 6
 
0.8%
199197.79507181 6
 
0.8%
198432.354182494 5
 
0.6%
Other values (533) 709
90.2%
ValueCountFrequency (%)
189920.528610917 1
 
0.1%
198351.955 1
 
0.1%
198363.705516537 3
0.4%
198405.322905974 1
 
0.1%
198409.554742612 1
 
0.1%
198410.072816565 1
 
0.1%
198416.687503983 1
 
0.1%
198425.516282007 1
 
0.1%
198432.354182494 5
0.6%
198433.508570776 1
 
0.1%
ValueCountFrequency (%)
205634.311119598 1
0.1%
205203.899329664 1
0.1%
205065.965394024 2
0.3%
204969.365592873 1
0.1%
204947.859673929 1
0.1%
204923.553125008 1
0.1%
204561.886234256 1
0.1%
204223.120372772 1
0.1%
204158.349624217 1
0.1%
204140.82 1
0.1%

좌표정보(Y)
Real number (ℝ)

Distinct543
Distinct (%)69.5%
Missing5
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean442942.87
Minimum438012.13
Maximum446206.35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.0 KiB
2024-05-11T00:49:37.985865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum438012.13
5-th percentile440730.75
Q1442198.24
median442858.2
Q3443618.7
95-th percentile445676.17
Maximum446206.35
Range8194.2269
Interquartile range (IQR)1420.4657

Descriptive statistics

Standard deviation1375.9544
Coefficient of variation (CV)0.0031063926
Kurtosis0.75624806
Mean442942.87
Median Absolute Deviation (MAD)734.62666
Skewness0.083442795
Sum3.4593838 × 108
Variance1893250.6
MonotonicityNot monotonic
2024-05-11T00:49:38.579088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
443154.964346798 12
 
1.5%
440136.781183797 8
 
1.0%
443592.823707003 8
 
1.0%
443826.911881224 8
 
1.0%
442563.269271521 7
 
0.9%
441229.4333012 6
 
0.8%
443449.99298641 6
 
0.8%
440676.379919661 6
 
0.8%
442929.854461736 6
 
0.8%
442643.16392201 5
 
0.6%
Other values (533) 709
90.2%
ValueCountFrequency (%)
438012.1279662 1
0.1%
438089.937256048 2
0.3%
438278.235724516 1
0.1%
438293.331675201 1
0.1%
438769.485852873 1
0.1%
439407.27399616 1
0.1%
439459.307260772 1
0.1%
439551.025718835 1
0.1%
439960.533113874 2
0.3%
439981.934357936 1
0.1%
ValueCountFrequency (%)
446206.354902748 1
 
0.1%
446180.260965954 5
0.6%
446163.667153226 1
 
0.1%
446144.110278895 1
 
0.1%
446135.828367442 2
 
0.3%
446105.536208478 1
 
0.1%
446094.650854533 1
 
0.1%
446025.568423013 1
 
0.1%
446005.151564228 1
 
0.1%
445998.07382598 1
 
0.1%

위생업태명
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
건강기능식품유통전문판매업
504 
<NA>
282 

Length

Max length13
Median length13
Mean length9.7709924
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건강기능식품유통전문판매업 504
64.1%
<NA> 282
35.9%

Length

2024-05-11T00:49:39.151384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:49:39.571102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건강기능식품유통전문판매업 504
64.1%
na 282
35.9%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
<NA>
735 
0
 
51

Length

Max length4
Median length4
Mean length3.8053435
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> 735
93.5%
0 51
 
6.5%

Length

2024-05-11T00:49:39.967003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:49:40.377389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 735
93.5%
0 51
 
6.5%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
<NA>
735 
0
 
51

Length

Max length4
Median length4
Mean length3.8053435
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> 735
93.5%
0 51
 
6.5%

Length

2024-05-11T00:49:40.919148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:49:41.457928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 735
93.5%
0 51
 
6.5%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing786
Missing (%)100.0%
Memory size7.0 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing786
Missing (%)100.0%
Memory size7.0 KiB

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
<NA>
783 
상수도전용
 
3

Length

Max length5
Median length4
Mean length4.0038168
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> 783
99.6%
상수도전용 3
 
0.4%

Length

2024-05-11T00:49:41.883184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:49:42.427308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 783
99.6%
상수도전용 3
 
0.4%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
<NA>
738 
0
 
48

Length

Max length4
Median length4
Mean length3.8167939
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> 738
93.9%
0 48
 
6.1%

Length

2024-05-11T00:49:42.855283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:49:43.460667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 738
93.9%
0 48
 
6.1%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
<NA>
602 
0
184 

Length

Max length4
Median length4
Mean length3.2977099
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> 602
76.6%
0 184
 
23.4%

Length

2024-05-11T00:49:43.952059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:49:44.326371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 602
76.6%
0 184
 
23.4%
Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
<NA>
601 
0
184 
5
 
1

Length

Max length4
Median length4
Mean length3.2938931
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 601
76.5%
0 184
 
23.4%
5 1
 
0.1%

Length

2024-05-11T00:49:44.729848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:49:45.141023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 601
76.5%
0 184
 
23.4%
5 1
 
0.1%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
<NA>
602 
0
184 

Length

Max length4
Median length4
Mean length3.2977099
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> 602
76.6%
0 184
 
23.4%

Length

2024-05-11T00:49:45.553996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:49:46.000828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 602
76.6%
0 184
 
23.4%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
<NA>
602 
0
184 

Length

Max length4
Median length4
Mean length3.2977099
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> 602
76.6%
0 184
 
23.4%

Length

2024-05-11T00:49:46.595554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:49:47.025392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 602
76.6%
0 184
 
23.4%
Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
<NA>
436 
임대
248 
자가
102 

Length

Max length4
Median length4
Mean length3.1094148
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 436
55.5%
임대 248
31.6%
자가 102
 
13.0%

Length

2024-05-11T00:49:47.422064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:49:47.820028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 436
55.5%
임대 248
31.6%
자가 102
 
13.0%

보증액
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
<NA>
684 
0
102 

Length

Max length4
Median length4
Mean length3.610687
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> 684
87.0%
0 102
 
13.0%

Length

2024-05-11T00:49:48.228356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:49:48.722898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 684
87.0%
0 102
 
13.0%

월세액
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
<NA>
684 
0
102 

Length

Max length4
Median length4
Mean length3.610687
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> 684
87.0%
0 102
 
13.0%

Length

2024-05-11T00:49:49.101275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:49:49.428445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 684
87.0%
0 102
 
13.0%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing282
Missing (%)35.9%
Memory size1.7 KiB
False
504 
(Missing)
282 
ValueCountFrequency (%)
False 504
64.1%
(Missing) 282
35.9%
2024-05-11T00:49:49.721833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct31
Distinct (%)6.2%
Missing282
Missing (%)35.9%
Infinite0
Infinite (%)0.0%
Mean4.345754
Minimum0
Maximum537.13
Zeros447
Zeros (%)56.9%
Negative0
Negative (%)0.0%
Memory size7.0 KiB
2024-05-11T00:49:50.157332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5.85
Maximum537.13
Range537.13
Interquartile range (IQR)0

Descriptive statistics

Standard deviation30.773889
Coefficient of variation (CV)7.0813693
Kurtosis192.63843
Mean4.345754
Median Absolute Deviation (MAD)0
Skewness12.568954
Sum2190.26
Variance947.03222
MonotonicityNot monotonic
2024-05-11T00:49:50.678633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0.0 447
56.9%
3.3 24
 
3.1%
3.0 3
 
0.4%
2.0 2
 
0.3%
9.9 2
 
0.3%
1.44 1
 
0.1%
33.0 1
 
0.1%
15.0 1
 
0.1%
537.13 1
 
0.1%
27.1 1
 
0.1%
Other values (21) 21
 
2.7%
(Missing) 282
35.9%
ValueCountFrequency (%)
0.0 447
56.9%
1.44 1
 
0.1%
2.0 2
 
0.3%
3.0 3
 
0.4%
3.3 24
 
3.1%
5.0 1
 
0.1%
6.0 1
 
0.1%
7.5 1
 
0.1%
9.12 1
 
0.1%
9.9 2
 
0.3%
ValueCountFrequency (%)
537.13 1
0.1%
263.36 1
0.1%
181.43 1
0.1%
154.28 1
0.1%
138.18 1
0.1%
114.0 1
0.1%
108.64 1
0.1%
83.0 1
0.1%
60.0 1
0.1%
57.59 1
0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing786
Missing (%)100.0%
Memory size7.0 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing786
Missing (%)100.0%
Memory size7.0 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing786
Missing (%)100.0%
Memory size7.0 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
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개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
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77732100003210000-135-2024-000142024-03-14<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>137-887서울특별시 서초구 양재동 **-** *층서울특별시 서초구 남부순환로 ****-**, *층 (양재동)6737주식회사 휴바앤2024-03-14 15:27:12I2023-12-02 23:06:00.0건강기능식품유통전문판매업203145.785379442458.05229<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
77832100003210000-135-2024-000152024-03-25<NA>1영업/정상1영업<NA><NA><NA><NA><NA>0.00137-885서울특별시 서초구 서초동 ****-* *층 T***호서울특별시 서초구 서초대로 ***, *층 T***호 (서초동)6595위닉스제약2024-03-25 15:01:34I2023-12-02 22:07:00.0건강기능식품유통전문판매업200684.880873443355.310431<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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78032100003210000-135-2024-000172024-04-05<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>137-894서울특별시 서초구 양재동 ***-* 두성빌딩 *층서울특별시 서초구 마방로*길 **, 두성빌딩 *층 (양재동)6778비에이치바이오플러스 주식회사2024-04-05 10:27:40I2023-12-04 00:07:00.0건강기능식품유통전문판매업203576.547018441229.433301<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
78132100003210000-135-2024-000182024-04-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>137-857서울특별시 서초구 서초동 ****-** BNK디지털타워 ***호서울특별시 서초구 서초대로 ***, BNK디지털타워 ***호 (서초동)6619라운드포 주식회사2024-04-09 09:37:31I2023-12-03 23:01:00.0건강기능식품유통전문판매업202152.435829443826.911881<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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