Overview

Dataset statistics

Number of variables44
Number of observations360
Missing cells4114
Missing cells (%)26.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory132.7 KiB
Average record size in memory377.4 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
Author영등포구
URLhttps://data.seoul.go.kr/dataList/OA-18070/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
급수시설구분명 is highly imbalanced (86.2%)Imbalance
본사종업원수 is highly imbalanced (51.6%)Imbalance
공장사무직종업원수 is highly imbalanced (50.6%)Imbalance
공장판매직종업원수 is highly imbalanced (51.6%)Imbalance
보증액 is highly imbalanced (57.2%)Imbalance
월세액 is highly imbalanced (57.2%)Imbalance
인허가취소일자 has 360 (100.0%) missing valuesMissing
폐업일자 has 157 (43.6%) missing valuesMissing
휴업시작일자 has 360 (100.0%) missing valuesMissing
휴업종료일자 has 360 (100.0%) missing valuesMissing
재개업일자 has 360 (100.0%) missing valuesMissing
전화번호 has 158 (43.9%) missing valuesMissing
소재지면적 has 233 (64.7%) missing valuesMissing
도로명주소 has 40 (11.1%) missing valuesMissing
도로명우편번호 has 40 (11.1%) missing valuesMissing
영업장주변구분명 has 360 (100.0%) missing valuesMissing
등급구분명 has 360 (100.0%) missing valuesMissing
다중이용업소여부 has 119 (33.1%) missing valuesMissing
시설총규모 has 119 (33.1%) missing valuesMissing
전통업소지정번호 has 360 (100.0%) missing valuesMissing
전통업소주된음식 has 360 (100.0%) missing valuesMissing
홈페이지 has 360 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
최종수정일자 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 235 (65.3%) zerosZeros

Reproduction

Analysis started2024-05-11 06:20:39.775915
Analysis finished2024-05-11 06:20:41.062002
Duration1.29 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
3180000
360 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3180000
2nd row3180000
3rd row3180000
4th row3180000
5th row3180000

Common Values

ValueCountFrequency (%)
3180000 360
100.0%

Length

2024-05-11T15:20:41.191246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:41.372734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3180000 360
100.0%

관리번호
Text

UNIQUE 

Distinct360
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
2024-05-11T15:20:41.691347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters7920
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

Unique360 ?
Unique (%)100.0%

Sample

1st row3180000-135-2004-00002
2nd row3180000-135-2004-00003
3rd row3180000-135-2004-00004
4th row3180000-135-2004-00005
5th row3180000-135-2004-00006
ValueCountFrequency (%)
3180000-135-2004-00002 1
 
0.3%
3180000-135-2020-00008 1
 
0.3%
3180000-135-2020-00006 1
 
0.3%
3180000-135-2020-00005 1
 
0.3%
3180000-135-2020-00004 1
 
0.3%
3180000-135-2020-00003 1
 
0.3%
3180000-135-2020-00002 1
 
0.3%
3180000-135-2020-00001 1
 
0.3%
3180000-135-2019-00021 1
 
0.3%
3180000-135-2019-00020 1
 
0.3%
Other values (350) 350
97.2%
2024-05-11T15:20:42.560878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3223
40.7%
1 1090
 
13.8%
- 1080
 
13.6%
3 804
 
10.2%
2 607
 
7.7%
8 433
 
5.5%
5 425
 
5.4%
4 88
 
1.1%
9 61
 
0.8%
7 55
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6840
86.4%
Dash Punctuation 1080
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3223
47.1%
1 1090
 
15.9%
3 804
 
11.8%
2 607
 
8.9%
8 433
 
6.3%
5 425
 
6.2%
4 88
 
1.3%
9 61
 
0.9%
7 55
 
0.8%
6 54
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
- 1080
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3223
40.7%
1 1090
 
13.8%
- 1080
 
13.6%
3 804
 
10.2%
2 607
 
7.7%
8 433
 
5.5%
5 425
 
5.4%
4 88
 
1.1%
9 61
 
0.8%
7 55
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3223
40.7%
1 1090
 
13.8%
- 1080
 
13.6%
3 804
 
10.2%
2 607
 
7.7%
8 433
 
5.5%
5 425
 
5.4%
4 88
 
1.1%
9 61
 
0.8%
7 55
 
0.7%
Distinct342
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
Minimum2004-04-02 00:00:00
Maximum2024-05-02 00:00:00
2024-05-11T15:20:42.791242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:20:43.014278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing360
Missing (%)100.0%
Memory size3.3 KiB
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
3
203 
1
157 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 203
56.4%
1 157
43.6%

Length

2024-05-11T15:20:43.224420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:43.362056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 203
56.4%
1 157
43.6%

영업상태명
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
폐업
203 
영업/정상
157 

Length

Max length5
Median length2
Mean length3.3083333
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 203
56.4%
영업/정상 157
43.6%

Length

2024-05-11T15:20:43.486777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:43.617144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 203
56.4%
영업/정상 157
43.6%
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
2
203 
1
157 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 203
56.4%
1 157
43.6%

Length

2024-05-11T15:20:43.780204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:43.926688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 203
56.4%
1 157
43.6%
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
폐업
203 
영업
157 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 203
56.4%
영업 157
43.6%

Length

2024-05-11T15:20:44.080246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:44.204487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 203
56.4%
영업 157
43.6%

폐업일자
Date

MISSING 

Distinct163
Distinct (%)80.3%
Missing157
Missing (%)43.6%
Memory size2.9 KiB
Minimum2004-12-22 00:00:00
Maximum2024-04-26 00:00:00
2024-05-11T15:20:44.347098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:20:44.521803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing360
Missing (%)100.0%
Memory size3.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing360
Missing (%)100.0%
Memory size3.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing360
Missing (%)100.0%
Memory size3.3 KiB

전화번호
Text

MISSING 

Distinct196
Distinct (%)97.0%
Missing158
Missing (%)43.9%
Memory size2.9 KiB
2024-05-11T15:20:44.875778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.475248
Min length7

Characters and Unicode

Total characters2116
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

Unique190 ?
Unique (%)94.1%

Sample

1st row02 8359007
2nd row0226706653
3rd row0226380161
4th row0226327002
5th row02 7822165
ValueCountFrequency (%)
02 89
27.1%
070 9
 
2.7%
031 4
 
1.2%
780 4
 
1.2%
07040364555 2
 
0.6%
784 2
 
0.6%
0269681133 2
 
0.6%
0221664100 2
 
0.6%
8324000 2
 
0.6%
34527311 2
 
0.6%
Other values (209) 210
64.0%
2024-05-11T15:20:45.353160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 381
18.0%
2 339
16.0%
7 192
9.1%
8 183
8.6%
6 175
8.3%
175
8.3%
3 157
7.4%
5 154
7.3%
1 128
 
6.0%
4 125
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1941
91.7%
Space Separator 175
 
8.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 381
19.6%
2 339
17.5%
7 192
9.9%
8 183
9.4%
6 175
9.0%
3 157
8.1%
5 154
7.9%
1 128
 
6.6%
4 125
 
6.4%
9 107
 
5.5%
Space Separator
ValueCountFrequency (%)
175
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2116
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 381
18.0%
2 339
16.0%
7 192
9.1%
8 183
8.6%
6 175
8.3%
175
8.3%
3 157
7.4%
5 154
7.3%
1 128
 
6.0%
4 125
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2116
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 381
18.0%
2 339
16.0%
7 192
9.1%
8 183
8.6%
6 175
8.3%
175
8.3%
3 157
7.4%
5 154
7.3%
1 128
 
6.0%
4 125
 
5.9%

소재지면적
Text

MISSING 

Distinct97
Distinct (%)76.4%
Missing233
Missing (%)64.7%
Memory size2.9 KiB
2024-05-11T15:20:45.760202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5
Min length3

Characters and Unicode

Total characters635
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

Unique86 ?
Unique (%)67.7%

Sample

1st row.00
2nd row251.13
3rd row84.00
4th row130.00
5th row224.40
ValueCountFrequency (%)
3.30 7
 
5.5%
10.00 6
 
4.7%
30.00 5
 
3.9%
2.00 4
 
3.1%
33.00 4
 
3.1%
6.60 3
 
2.4%
0.00 3
 
2.4%
3.00 3
 
2.4%
53.00 2
 
1.6%
100.00 2
 
1.6%
Other values (87) 88
69.3%
2024-05-11T15:20:46.413372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 196
30.9%
. 127
20.0%
3 61
 
9.6%
1 52
 
8.2%
2 40
 
6.3%
6 40
 
6.3%
4 31
 
4.9%
5 27
 
4.3%
8 22
 
3.5%
7 20
 
3.1%
Other values (2) 19
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 507
79.8%
Other Punctuation 128
 
20.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 196
38.7%
3 61
 
12.0%
1 52
 
10.3%
2 40
 
7.9%
6 40
 
7.9%
4 31
 
6.1%
5 27
 
5.3%
8 22
 
4.3%
7 20
 
3.9%
9 18
 
3.6%
Other Punctuation
ValueCountFrequency (%)
. 127
99.2%
, 1
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
Common 635
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 196
30.9%
. 127
20.0%
3 61
 
9.6%
1 52
 
8.2%
2 40
 
6.3%
6 40
 
6.3%
4 31
 
4.9%
5 27
 
4.3%
8 22
 
3.5%
7 20
 
3.1%
Other values (2) 19
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 635
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 196
30.9%
. 127
20.0%
3 61
 
9.6%
1 52
 
8.2%
2 40
 
6.3%
6 40
 
6.3%
4 31
 
4.9%
5 27
 
4.3%
8 22
 
3.5%
7 20
 
3.1%
Other values (2) 19
 
3.0%
Distinct124
Distinct (%)34.5%
Missing1
Missing (%)0.3%
Memory size2.9 KiB
2024-05-11T15:20:46.966186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.2479109
Min length6

Characters and Unicode

Total characters2243
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

Unique44 ?
Unique (%)12.3%

Sample

1st row150830
2nd row150-866
3rd row150042
4th row150040
5th row150871
ValueCountFrequency (%)
150870 17
 
4.7%
150809 11
 
3.1%
150103 10
 
2.8%
150105 9
 
2.5%
150804 9
 
2.5%
150866 8
 
2.2%
150871 8
 
2.2%
150-867 7
 
1.9%
150837 6
 
1.7%
150-835 6
 
1.7%
Other values (114) 268
74.7%
2024-05-11T15:20:47.774087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 552
24.6%
1 450
20.1%
5 415
18.5%
8 275
12.3%
3 102
 
4.5%
7 99
 
4.4%
- 89
 
4.0%
9 84
 
3.7%
6 81
 
3.6%
4 56
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2154
96.0%
Dash Punctuation 89
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 552
25.6%
1 450
20.9%
5 415
19.3%
8 275
12.8%
3 102
 
4.7%
7 99
 
4.6%
9 84
 
3.9%
6 81
 
3.8%
4 56
 
2.6%
2 40
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 89
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2243
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 552
24.6%
1 450
20.1%
5 415
18.5%
8 275
12.3%
3 102
 
4.5%
7 99
 
4.4%
- 89
 
4.0%
9 84
 
3.7%
6 81
 
3.6%
4 56
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2243
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 552
24.6%
1 450
20.1%
5 415
18.5%
8 275
12.3%
3 102
 
4.5%
7 99
 
4.4%
- 89
 
4.0%
9 84
 
3.7%
6 81
 
3.6%
4 56
 
2.5%
Distinct303
Distinct (%)84.4%
Missing1
Missing (%)0.3%
Memory size2.9 KiB
2024-05-11T15:20:48.157739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length37
Mean length29.554318
Min length19

Characters and Unicode

Total characters10610
Distinct characters247
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique266 ?
Unique (%)74.1%

Sample

1st row서울특별시 영등포구 도림동 ***-**번지 유미빌딩 *층
2nd row서울특별시 영등포구 양평동*가 **
3rd row서울특별시 영등포구 당산동*가 **-*번지
4th row서울특별시 영등포구 당산동 ***-***번지
5th row서울특별시 영등포구 여의도동 **-*번지 아크로폴리스 ***호
ValueCountFrequency (%)
서울특별시 359
18.8%
영등포구 358
18.7%
179
9.4%
번지 178
9.3%
여의도동 107
 
5.6%
92
 
4.8%
당산동*가 61
 
3.2%
양평동*가 52
 
2.7%
51
 
2.7%
문래동*가 40
 
2.1%
Other values (221) 434
22.7%
2024-05-11T15:20:48.819543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 1791
16.9%
1741
16.4%
401
 
3.8%
396
 
3.7%
394
 
3.7%
384
 
3.6%
372
 
3.5%
364
 
3.4%
361
 
3.4%
359
 
3.4%
Other values (237) 4047
38.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6723
63.4%
Other Punctuation 1797
 
16.9%
Space Separator 1741
 
16.4%
Dash Punctuation 266
 
2.5%
Uppercase Letter 26
 
0.2%
Decimal Number 22
 
0.2%
Lowercase Letter 15
 
0.1%
Close Punctuation 9
 
0.1%
Open Punctuation 9
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
401
 
6.0%
396
 
5.9%
394
 
5.9%
384
 
5.7%
372
 
5.5%
364
 
5.4%
361
 
5.4%
359
 
5.3%
359
 
5.3%
359
 
5.3%
Other values (200) 2974
44.2%
Uppercase Letter
ValueCountFrequency (%)
K 5
19.2%
S 4
15.4%
C 2
 
7.7%
V 2
 
7.7%
A 2
 
7.7%
T 2
 
7.7%
G 2
 
7.7%
W 2
 
7.7%
Y 1
 
3.8%
E 1
 
3.8%
Other values (3) 3
11.5%
Decimal Number
ValueCountFrequency (%)
2 8
36.4%
3 3
 
13.6%
6 3
 
13.6%
7 2
 
9.1%
0 2
 
9.1%
4 2
 
9.1%
8 1
 
4.5%
1 1
 
4.5%
Lowercase Letter
ValueCountFrequency (%)
e 4
26.7%
n 3
20.0%
t 2
13.3%
c 2
13.3%
r 2
13.3%
k 1
 
6.7%
s 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
* 1791
99.7%
, 4
 
0.2%
. 1
 
0.1%
? 1
 
0.1%
Space Separator
ValueCountFrequency (%)
1741
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 266
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6723
63.4%
Common 3846
36.2%
Latin 41
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
401
 
6.0%
396
 
5.9%
394
 
5.9%
384
 
5.7%
372
 
5.5%
364
 
5.4%
361
 
5.4%
359
 
5.3%
359
 
5.3%
359
 
5.3%
Other values (200) 2974
44.2%
Latin
ValueCountFrequency (%)
K 5
 
12.2%
e 4
 
9.8%
S 4
 
9.8%
n 3
 
7.3%
t 2
 
4.9%
C 2
 
4.9%
c 2
 
4.9%
r 2
 
4.9%
V 2
 
4.9%
A 2
 
4.9%
Other values (10) 13
31.7%
Common
ValueCountFrequency (%)
* 1791
46.6%
1741
45.3%
- 266
 
6.9%
) 9
 
0.2%
( 9
 
0.2%
2 8
 
0.2%
, 4
 
0.1%
3 3
 
0.1%
6 3
 
0.1%
~ 2
 
0.1%
Other values (7) 10
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6723
63.4%
ASCII 3887
36.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 1791
46.1%
1741
44.8%
- 266
 
6.8%
) 9
 
0.2%
( 9
 
0.2%
2 8
 
0.2%
K 5
 
0.1%
, 4
 
0.1%
e 4
 
0.1%
S 4
 
0.1%
Other values (27) 46
 
1.2%
Hangul
ValueCountFrequency (%)
401
 
6.0%
396
 
5.9%
394
 
5.9%
384
 
5.7%
372
 
5.5%
364
 
5.4%
361
 
5.4%
359
 
5.3%
359
 
5.3%
359
 
5.3%
Other values (200) 2974
44.2%

도로명주소
Text

MISSING 

Distinct283
Distinct (%)88.4%
Missing40
Missing (%)11.1%
Memory size2.9 KiB
2024-05-11T15:20:49.210111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length51
Mean length39.903125
Min length24

Characters and Unicode

Total characters12769
Distinct characters242
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique255 ?
Unique (%)79.7%

Sample

1st row서울특별시 영등포구 도신로 ** (도림동,유미빌딩 *층)
2nd row서울특별시 영등포구 양평로**길 ** (양평동*가)
3rd row서울특별시 영등포구 국회대로**길 * (여의도동,아크로폴리스 ***호)
4th row서울특별시 영등포구 당산로*길 ** (문래동*가,에이스테크노타운*층***호)
5th row서울특별시 영등포구 가마산로46길 3 (대림동)
ValueCountFrequency (%)
서울특별시 320
13.8%
영등포구 319
13.8%
317
13.7%
197
 
8.5%
173
 
7.5%
여의도동 84
 
3.6%
당산동*가 50
 
2.2%
양평동*가 48
 
2.1%
국회대로**길 37
 
1.6%
문래동*가 34
 
1.5%
Other values (304) 732
31.7%
2024-05-11T15:20:49.937075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 2213
 
17.3%
1992
 
15.6%
, 390
 
3.1%
385
 
3.0%
373
 
2.9%
372
 
2.9%
370
 
2.9%
336
 
2.6%
329
 
2.6%
325
 
2.5%
Other values (232) 5684
44.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7394
57.9%
Other Punctuation 2604
 
20.4%
Space Separator 1992
 
15.6%
Close Punctuation 324
 
2.5%
Open Punctuation 324
 
2.5%
Uppercase Letter 41
 
0.3%
Dash Punctuation 37
 
0.3%
Decimal Number 37
 
0.3%
Lowercase Letter 14
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
385
 
5.2%
373
 
5.0%
372
 
5.0%
370
 
5.0%
336
 
4.5%
329
 
4.4%
325
 
4.4%
322
 
4.4%
320
 
4.3%
320
 
4.3%
Other values (196) 3942
53.3%
Uppercase Letter
ValueCountFrequency (%)
B 13
31.7%
A 9
22.0%
C 4
 
9.8%
S 4
 
9.8%
K 3
 
7.3%
V 2
 
4.9%
D 1
 
2.4%
G 1
 
2.4%
E 1
 
2.4%
W 1
 
2.4%
Other values (2) 2
 
4.9%
Decimal Number
ValueCountFrequency (%)
2 10
27.0%
3 5
13.5%
0 5
13.5%
1 4
 
10.8%
7 4
 
10.8%
6 3
 
8.1%
8 3
 
8.1%
4 2
 
5.4%
5 1
 
2.7%
Lowercase Letter
ValueCountFrequency (%)
e 4
28.6%
r 2
14.3%
n 2
14.3%
t 2
14.3%
c 2
14.3%
k 1
 
7.1%
s 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
* 2213
85.0%
, 390
 
15.0%
. 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
1992
100.0%
Close Punctuation
ValueCountFrequency (%)
) 324
100.0%
Open Punctuation
ValueCountFrequency (%)
( 324
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 37
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7394
57.9%
Common 5320
41.7%
Latin 55
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
385
 
5.2%
373
 
5.0%
372
 
5.0%
370
 
5.0%
336
 
4.5%
329
 
4.4%
325
 
4.4%
322
 
4.4%
320
 
4.3%
320
 
4.3%
Other values (196) 3942
53.3%
Latin
ValueCountFrequency (%)
B 13
23.6%
A 9
16.4%
C 4
 
7.3%
e 4
 
7.3%
S 4
 
7.3%
K 3
 
5.5%
r 2
 
3.6%
n 2
 
3.6%
t 2
 
3.6%
c 2
 
3.6%
Other values (9) 10
18.2%
Common
ValueCountFrequency (%)
* 2213
41.6%
1992
37.4%
, 390
 
7.3%
) 324
 
6.1%
( 324
 
6.1%
- 37
 
0.7%
2 10
 
0.2%
3 5
 
0.1%
0 5
 
0.1%
1 4
 
0.1%
Other values (7) 16
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7394
57.9%
ASCII 5375
42.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 2213
41.2%
1992
37.1%
, 390
 
7.3%
) 324
 
6.0%
( 324
 
6.0%
- 37
 
0.7%
B 13
 
0.2%
2 10
 
0.2%
A 9
 
0.2%
3 5
 
0.1%
Other values (26) 58
 
1.1%
Hangul
ValueCountFrequency (%)
385
 
5.2%
373
 
5.0%
372
 
5.0%
370
 
5.0%
336
 
4.5%
329
 
4.4%
325
 
4.4%
322
 
4.4%
320
 
4.3%
320
 
4.3%
Other values (196) 3942
53.3%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct103
Distinct (%)32.2%
Missing40
Missing (%)11.1%
Infinite0
Infinite (%)0.0%
Mean7289.9563
Minimum7203
Maximum8391
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2024-05-11T15:20:50.240843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7203
5-th percentile7207
Q17237
median7282
Q37331
95-th percentile7413.05
Maximum8391
Range1188
Interquartile range (IQR)94

Descriptive statistics

Standard deviation87.652767
Coefficient of variation (CV)0.012023771
Kurtosis77.128791
Mean7289.9563
Median Absolute Deviation (MAD)46
Skewness6.4150712
Sum2332786
Variance7683.0075
MonotonicityNot monotonic
2024-05-11T15:20:50.521621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7238 23
 
6.4%
7333 15
 
4.2%
7223 12
 
3.3%
7208 12
 
3.3%
7345 9
 
2.5%
7299 8
 
2.2%
7287 8
 
2.2%
7318 8
 
2.2%
7256 7
 
1.9%
7325 6
 
1.7%
Other values (93) 212
58.9%
(Missing) 40
 
11.1%
ValueCountFrequency (%)
7203 2
 
0.6%
7205 4
 
1.1%
7206 6
1.7%
7207 6
1.7%
7208 12
3.3%
7209 2
 
0.6%
7213 2
 
0.6%
7214 2
 
0.6%
7217 4
 
1.1%
7218 2
 
0.6%
ValueCountFrequency (%)
8391 1
 
0.3%
7445 1
 
0.3%
7444 1
 
0.3%
7442 1
 
0.3%
7433 2
0.6%
7429 3
0.8%
7424 1
 
0.3%
7422 2
0.6%
7420 1
 
0.3%
7415 1
 
0.3%
Distinct357
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
2024-05-11T15:20:50.950086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length15
Mean length8.2222222
Min length2

Characters and Unicode

Total characters2960
Distinct characters369
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique354 ?
Unique (%)98.3%

Sample

1st row(주)다고다고
2nd row롯데웰푸드(주)
3rd row초록원
4th row(주)굿메디신
5th row봄빅스코리아(주)
ValueCountFrequency (%)
주식회사 69
 
15.5%
성우활성수소(주 2
 
0.5%
korea 2
 
0.5%
롯데웰푸드(주 2
 
0.5%
주)아이피씨코리아(ipc 2
 
0.5%
주)엘지생활건강 2
 
0.5%
주)엘씨엠싸이언스 1
 
0.2%
주식회사닥터파이브 1
 
0.2%
뉴트라랩 1
 
0.2%
이비엠케이에스 1
 
0.2%
Other values (361) 361
81.3%
2024-05-11T15:20:51.585461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
264
 
8.9%
) 189
 
6.4%
( 188
 
6.4%
141
 
4.8%
95
 
3.2%
94
 
3.2%
88
 
3.0%
85
 
2.9%
84
 
2.8%
48
 
1.6%
Other values (359) 1684
56.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2420
81.8%
Close Punctuation 189
 
6.4%
Open Punctuation 188
 
6.4%
Space Separator 84
 
2.8%
Uppercase Letter 43
 
1.5%
Lowercase Letter 29
 
1.0%
Decimal Number 6
 
0.2%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
264
 
10.9%
141
 
5.8%
95
 
3.9%
94
 
3.9%
88
 
3.6%
85
 
3.5%
48
 
2.0%
45
 
1.9%
44
 
1.8%
40
 
1.7%
Other values (320) 1476
61.0%
Uppercase Letter
ValueCountFrequency (%)
I 5
11.6%
M 4
 
9.3%
L 4
 
9.3%
K 3
 
7.0%
N 3
 
7.0%
C 3
 
7.0%
S 3
 
7.0%
U 2
 
4.7%
R 2
 
4.7%
E 2
 
4.7%
Other values (9) 12
27.9%
Lowercase Letter
ValueCountFrequency (%)
e 6
20.7%
a 5
17.2%
o 3
10.3%
t 2
 
6.9%
s 2
 
6.9%
b 2
 
6.9%
l 2
 
6.9%
r 2
 
6.9%
n 1
 
3.4%
g 1
 
3.4%
Other values (3) 3
10.3%
Decimal Number
ValueCountFrequency (%)
3 2
33.3%
6 2
33.3%
5 2
33.3%
Close Punctuation
ValueCountFrequency (%)
) 189
100.0%
Open Punctuation
ValueCountFrequency (%)
( 188
100.0%
Space Separator
ValueCountFrequency (%)
84
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2420
81.8%
Common 468
 
15.8%
Latin 72
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
264
 
10.9%
141
 
5.8%
95
 
3.9%
94
 
3.9%
88
 
3.6%
85
 
3.5%
48
 
2.0%
45
 
1.9%
44
 
1.8%
40
 
1.7%
Other values (320) 1476
61.0%
Latin
ValueCountFrequency (%)
e 6
 
8.3%
I 5
 
6.9%
a 5
 
6.9%
M 4
 
5.6%
L 4
 
5.6%
K 3
 
4.2%
N 3
 
4.2%
C 3
 
4.2%
S 3
 
4.2%
o 3
 
4.2%
Other values (22) 33
45.8%
Common
ValueCountFrequency (%)
) 189
40.4%
( 188
40.2%
84
17.9%
3 2
 
0.4%
6 2
 
0.4%
5 2
 
0.4%
& 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2420
81.8%
ASCII 540
 
18.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
264
 
10.9%
141
 
5.8%
95
 
3.9%
94
 
3.9%
88
 
3.6%
85
 
3.5%
48
 
2.0%
45
 
1.9%
44
 
1.8%
40
 
1.7%
Other values (320) 1476
61.0%
ASCII
ValueCountFrequency (%)
) 189
35.0%
( 188
34.8%
84
15.6%
e 6
 
1.1%
I 5
 
0.9%
a 5
 
0.9%
M 4
 
0.7%
L 4
 
0.7%
K 3
 
0.6%
N 3
 
0.6%
Other values (29) 49
 
9.1%

최종수정일자
Date

UNIQUE 

Distinct360
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
Minimum2004-05-27 00:00:00
Maximum2024-05-02 11:18:38
2024-05-11T15:20:51.815984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:20:52.097522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
I
183 
U
177 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 183
50.8%
U 177
49.2%

Length

2024-05-11T15:20:52.357270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:52.551147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 183
50.8%
u 177
49.2%
Distinct205
Distinct (%)56.9%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:04:00
2024-05-11T15:20:52.765731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:20:53.027074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
건강기능식품유통전문판매업
360 

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 360
100.0%

Length

2024-05-11T15:20:53.334194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:53.540612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건강기능식품유통전문판매업 360
100.0%

좌표정보(X)
Real number (ℝ)

Distinct219
Distinct (%)61.3%
Missing3
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean191716.72
Minimum189664.26
Maximum194592.28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2024-05-11T15:20:53.726262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189664.26
5-th percentile190079.22
Q1190649.27
median191365.51
Q3192880.95
95-th percentile193818.18
Maximum194592.28
Range4928.0139
Interquartile range (IQR)2231.6722

Descriptive statistics

Standard deviation1276.59
Coefficient of variation (CV)0.0066587305
Kurtosis-0.91951235
Mean191716.72
Median Absolute Deviation (MAD)849.99978
Skewness0.51530488
Sum68442870
Variance1629682
MonotonicityNot monotonic
2024-05-11T15:20:53.943299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
190649.039032094 9
 
2.5%
190079.219797466 8
 
2.2%
194530.535390096 8
 
2.2%
191425.722339989 7
 
1.9%
192959.271161366 6
 
1.7%
193165.490137352 6
 
1.7%
193592.000380036 5
 
1.4%
192739.314354154 5
 
1.4%
190996.357288859 5
 
1.4%
190586.062540107 4
 
1.1%
Other values (209) 294
81.7%
ValueCountFrequency (%)
189664.262881986 1
 
0.3%
189667.63984485 1
 
0.3%
189785.752470051 1
 
0.3%
189849.410292461 3
0.8%
189921.671894763 1
 
0.3%
189955.804848895 1
 
0.3%
189958.938841997 3
0.8%
189959.044020878 1
 
0.3%
190023.48828661 1
 
0.3%
190075.470408684 1
 
0.3%
ValueCountFrequency (%)
194592.276750438 1
 
0.3%
194561.746032498 3
 
0.8%
194530.535390096 8
2.2%
193861.272368256 1
 
0.3%
193844.169062846 2
 
0.6%
193839.302798329 1
 
0.3%
193818.18014 3
 
0.8%
193808.969259588 1
 
0.3%
193798.948251805 2
 
0.6%
193787.762269762 1
 
0.3%

좌표정보(Y)
Real number (ℝ)

Distinct219
Distinct (%)61.3%
Missing3
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean446576.41
Minimum442456.4
Maximum448883.82
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2024-05-11T15:20:54.189628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum442456.4
5-th percentile443743.89
Q1446044.58
median446719.35
Q3447465.58
95-th percentile448225.55
Maximum448883.82
Range6427.4177
Interquartile range (IQR)1420.9984

Descriptive statistics

Standard deviation1274.6618
Coefficient of variation (CV)0.0028542973
Kurtosis0.79328463
Mean446576.41
Median Absolute Deviation (MAD)728.99013
Skewness-0.95597053
Sum1.5942778 × 108
Variance1624762.8
MonotonicityNot monotonic
2024-05-11T15:20:54.823855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
448224.111919951 9
 
2.5%
445778.895201988 8
 
2.2%
446306.787198089 8
 
2.2%
447891.794625907 7
 
1.9%
447637.656082358 6
 
1.7%
446797.341447363 6
 
1.7%
447092.629432527 5
 
1.4%
446552.469845648 5
 
1.4%
445841.377603245 5
 
1.4%
447216.925498911 4
 
1.1%
Other values (209) 294
81.7%
ValueCountFrequency (%)
442456.401362068 1
0.3%
442812.211045947 2
0.6%
442854.752471143 1
0.3%
443069.375417429 1
0.3%
443157.388663332 1
0.3%
443236.05842825 1
0.3%
443424.618220267 1
0.3%
443459.977285487 2
0.6%
443480.577591489 1
0.3%
443591.339482046 1
0.3%
ValueCountFrequency (%)
448883.819038659 2
0.6%
448642.112414847 4
1.1%
448554.360195644 1
 
0.3%
448471.434635038 2
0.6%
448401.741284772 1
 
0.3%
448352.840608043 1
 
0.3%
448350.61743141 1
 
0.3%
448341.565014161 1
 
0.3%
448289.617887109 1
 
0.3%
448279.993287223 1
 
0.3%

위생업태명
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
건강기능식품유통전문판매업
241 
<NA>
119 

Length

Max length13
Median length13
Mean length10.025
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건강기능식품유통전문판매업 241
66.9%
<NA> 119
33.1%

Length

2024-05-11T15:20:55.030842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:55.174245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건강기능식품유통전문판매업 241
66.9%
na 119
33.1%
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
0
241 
<NA>
119 

Length

Max length4
Median length1
Mean length1.9916667
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 241
66.9%
<NA> 119
33.1%

Length

2024-05-11T15:20:55.376008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:55.595087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 241
66.9%
na 119
33.1%
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
0
241 
<NA>
119 

Length

Max length4
Median length1
Mean length1.9916667
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 241
66.9%
<NA> 119
33.1%

Length

2024-05-11T15:20:55.814207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:56.022497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 241
66.9%
na 119
33.1%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing360
Missing (%)100.0%
Memory size3.3 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing360
Missing (%)100.0%
Memory size3.3 KiB

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
<NA>
353 
상수도전용
 
7

Length

Max length5
Median length4
Mean length4.0194444
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> 353
98.1%
상수도전용 7
 
1.9%

Length

2024-05-11T15:20:56.216753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:56.404654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 353
98.1%
상수도전용 7
 
1.9%

총인원
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
0
241 
<NA>
119 

Length

Max length4
Median length1
Mean length1.9916667
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 241
66.9%
<NA> 119
33.1%

Length

2024-05-11T15:20:56.647645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:56.869427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 241
66.9%
na 119
33.1%

본사종업원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
0
239 
<NA>
119 
5
 
1
10
 
1

Length

Max length4
Median length1
Mean length1.9944444
Min length1

Unique

Unique2 ?
Unique (%)0.6%

Sample

1st row0
2nd row<NA>
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 239
66.4%
<NA> 119
33.1%
5 1
 
0.3%
10 1
 
0.3%

Length

2024-05-11T15:20:57.063161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:57.281987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 239
66.4%
na 119
33.1%
5 1
 
0.3%
10 1
 
0.3%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
0
238 
<NA>
119 
2
 
2
7
 
1

Length

Max length4
Median length1
Mean length1.9916667
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row0
2nd row<NA>
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 238
66.1%
<NA> 119
33.1%
2 2
 
0.6%
7 1
 
0.3%

Length

2024-05-11T15:20:57.510356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:57.714797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 238
66.1%
na 119
33.1%
2 2
 
0.6%
7 1
 
0.3%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
0
239 
<NA>
119 
3
 
1
23
 
1

Length

Max length4
Median length1
Mean length1.9944444
Min length1

Unique

Unique2 ?
Unique (%)0.6%

Sample

1st row0
2nd row<NA>
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 239
66.4%
<NA> 119
33.1%
3 1
 
0.3%
23 1
 
0.3%

Length

2024-05-11T15:20:57.935769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:58.140298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 239
66.4%
na 119
33.1%
3 1
 
0.3%
23 1
 
0.3%
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
0
241 
<NA>
119 

Length

Max length4
Median length1
Mean length1.9916667
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 241
66.9%
<NA> 119
33.1%

Length

2024-05-11T15:20:58.374381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:58.597006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 241
66.9%
na 119
33.1%
Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
<NA>
284 
자가
39 
임대
37 

Length

Max length4
Median length4
Mean length3.5777778
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> 284
78.9%
자가 39
 
10.8%
임대 37
 
10.3%

Length

2024-05-11T15:20:58.834536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:59.149318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 284
78.9%
자가 39
 
10.8%
임대 37
 
10.3%

보증액
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
0
238 
<NA>
119 
18000000
 
1
20000000
 
1
10000000
 
1

Length

Max length8
Median length1
Mean length2.05
Min length1

Unique

Unique3 ?
Unique (%)0.8%

Sample

1st row0
2nd row<NA>
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 238
66.1%
<NA> 119
33.1%
18000000 1
 
0.3%
20000000 1
 
0.3%
10000000 1
 
0.3%

Length

2024-05-11T15:20:59.360202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:20:59.582336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 238
66.1%
na 119
33.1%
18000000 1
 
0.3%
20000000 1
 
0.3%
10000000 1
 
0.3%

월세액
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
0
238 
<NA>
119 
1800000
 
1
200000
 
1
750000
 
1

Length

Max length7
Median length1
Mean length2.0361111
Min length1

Unique

Unique3 ?
Unique (%)0.8%

Sample

1st row0
2nd row<NA>
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 238
66.1%
<NA> 119
33.1%
1800000 1
 
0.3%
200000 1
 
0.3%
750000 1
 
0.3%

Length

2024-05-11T15:20:59.808559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:21:00.028195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 238
66.1%
na 119
33.1%
1800000 1
 
0.3%
200000 1
 
0.3%
750000 1
 
0.3%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.4%
Missing119
Missing (%)33.1%
Memory size852.0 B
False
241 
(Missing)
119 
ValueCountFrequency (%)
False 241
66.9%
(Missing) 119
33.1%
2024-05-11T15:21:00.259813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)2.9%
Missing119
Missing (%)33.1%
Infinite0
Infinite (%)0.0%
Mean1.9995851
Minimum0
Maximum251.13
Zeros235
Zeros (%)65.3%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2024-05-11T15:21:00.418765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum251.13
Range251.13
Interquartile range (IQR)0

Descriptive statistics

Standard deviation19.019352
Coefficient of variation (CV)9.5116496
Kurtosis137.07303
Mean1.9995851
Median Absolute Deviation (MAD)0
Skewness11.354296
Sum481.9
Variance361.73577
MonotonicityNot monotonic
2024-05-11T15:21:00.639801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0.0 235
65.3%
251.13 1
 
0.3%
146.31 1
 
0.3%
29.0 1
 
0.3%
2.0 1
 
0.3%
49.46 1
 
0.3%
4.0 1
 
0.3%
(Missing) 119
33.1%
ValueCountFrequency (%)
0.0 235
65.3%
2.0 1
 
0.3%
4.0 1
 
0.3%
29.0 1
 
0.3%
49.46 1
 
0.3%
146.31 1
 
0.3%
251.13 1
 
0.3%
ValueCountFrequency (%)
251.13 1
 
0.3%
146.31 1
 
0.3%
49.46 1
 
0.3%
29.0 1
 
0.3%
4.0 1
 
0.3%
2.0 1
 
0.3%
0.0 235
65.3%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing360
Missing (%)100.0%
Memory size3.3 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing360
Missing (%)100.0%
Memory size3.3 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing360
Missing (%)100.0%
Memory size3.3 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031800003180000-135-2004-0000220040403<NA>3폐업2폐업20200128<NA><NA><NA>02 8359007<NA>150830서울특별시 영등포구 도림동 ***-**번지 유미빌딩 *층서울특별시 영등포구 도신로 ** (도림동,유미빌딩 *층)7369(주)다고다고2020-02-13 10:37:46U2020-02-15 02:40:00.0건강기능식품유통전문판매업191365.507989445057.650334건강기능식품유통전문판매업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
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231800003180000-135-2004-0000420040506<NA>3폐업2폐업20080305<NA><NA><NA>0226380161<NA>150042서울특별시 영등포구 당산동*가 **-*번지<NA><NA>초록원2004-11-30 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업190555.768992446698.814323건강기능식품유통전문판매업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
331800003180000-135-2004-0000520040527<NA>3폐업2폐업20061011<NA><NA><NA>0226327002<NA>150040서울특별시 영등포구 당산동 ***-***번지<NA><NA>(주)굿메디신2004-05-27 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업191928.342369447179.193432건강기능식품유통전문판매업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
431800003180000-135-2004-0000620040602<NA>3폐업2폐업20181228<NA><NA><NA>02 7822165<NA>150871서울특별시 영등포구 여의도동 **-*번지 아크로폴리스 ***호서울특별시 영등포구 국회대로**길 * (여의도동,아크로폴리스 ***호)7238봄빅스코리아(주)2018-12-28 16:50:01U2018-12-30 02:40:00.0건강기능식품유통전문판매업192870.536136447546.574775건강기능식품유통전문판매업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
531800003180000-135-2004-0000720040607<NA>3폐업2폐업20060901<NA><NA><NA>02 7867503<NA>150727서울특별시 영등포구 여의도동 **-*번지 금산빌딩 ***호<NA><NA>(주)천지산2005-09-06 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업192549.933121447340.688671건강기능식품유통전문판매업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
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831800003180000-135-2004-0001020040618<NA>3폐업2폐업20050126<NA><NA><NA>0226760765<NA>150800서울특별시 영등포구 당산동*가 **-*번지 *층<NA><NA>헬스파크2004-06-18 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업190794.717473446580.680063건강기능식품유통전문판매업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
931800003180000-135-2004-0001120040618<NA>3폐업2폐업20071012<NA><NA><NA>0226781998<NA>150035서울특별시 영등포구 영등포동*가 **-*번지 영림빌딩 *층<NA><NA>휴먼라이프2008-01-07 13:20:40I2018-08-31 23:59:59.0건강기능식품유통전문판매업191564.707809446517.110244건강기능식품유통전문판매업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
35031800003180000-135-2023-000192023-11-15<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>150-809서울특별시 영등포구 당산동*가 ***-* 수정빌딩서울특별시 영등포구 양평로 **, 수정빌딩 *층 ***호 (당산동*가)7223주식회사 백년건강2023-11-15 14:33:06I2022-10-31 23:07:00.0건강기능식품유통전문판매업191425.72234447891.794626<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
35131800003180000-135-2023-000202023-11-23<NA>1영업/정상1영업<NA><NA><NA><NA>02 7695166<NA>150-890서울특별시 영등포구 여의도동 **-** 인영빌딩서울특별시 영등포구 의사당대로*길 **, 인영빌딩 *층 ***호 (여의도동)7333정풍 주식회사2023-11-23 15:49:46I2022-10-31 22:05:00.0건강기능식품유통전문판매업193808.96926446429.983929<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
35231800003180000-135-2023-000212023-11-28<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>150-105서울특별시 영등포구 양평동*가 ** 선유도 투웨니퍼스트밸리서울특별시 영등포구 양평로 ***, 선유도 투웨니퍼스트밸리 D***호 (양평동*가)7207주식회사 리뉴플로우2023-11-28 13:34:47I2022-10-31 21:00:00.0건강기능식품유통전문판매업190237.437423448554.360196<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
35331800003180000-135-2024-000012024-01-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>150-862서울특별시 영등포구 양평동*가 **-**서울특별시 영등포구 선유로**길 *, ***-*호 (양평동*가)7262(주)에스제이파워2024-01-02 11:14:39I2023-12-01 00:04:00.0건강기능식품유통전문판매업190321.762458446889.707932<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
35431800003180000-135-2024-000022024-01-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>150-890서울특별시 영등포구 여의도동 **-** 제일빌딩서울특별시 영등포구 여의대방로 ***, 제일빌딩 *층 ***호 (여의도동)7333퀸즈본가2024-01-03 14:10:20I2023-12-01 00:05:00.0건강기능식품유통전문판매업193818.18014446332.089777<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
35531800003180000-135-2024-000042024-03-14<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>150-732서울특별시 영등포구 여의도동 **-* 콤비빌딩서울특별시 영등포구 **로 **, 콤비빌딩 ****호 (여의도동)7345주식회사 비엔에스마케팅2024-03-14 11:36:05I2023-12-02 23:06:00.0건강기능식품유통전문판매업194530.53539446306.787198<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
35631800003180000-135-2024-000052024-03-27<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>150-890서울특별시 영등포구 여의도동 **-**서울특별시 영등포구 여의대방로**길 **, *층 디**호 (여의도동)7333주식회사 퍼스트위스퍼2024-03-27 09:40:36I2023-12-02 22:09:00.0건강기능식품유통전문판매업193767.231404446397.113007<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
35731800003180000-135-2024-000062024-03-27<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>150-835서울특별시 영등포구 문래동*가 **-* 문래동메가트리움서울특별시 영등포구 문래로**길 *, ***동 ***호 (문래동*가, 문래동메가트리움)7297주식회사 테라퓨젠바이오2024-03-27 17:26:27I2023-12-02 22:09:00.0건강기능식품유통전문판매업190866.605827446211.615914<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
35831800003180000-135-2024-000072024-04-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>150-037서울특별시 영등포구 영등포동*가 **-**서울특별시 영등포구 국회대로**길 **, *층 ***호 (영등포동*가)7247(주)엘앤에스코퍼레이션2024-04-01 10:45:31I2023-12-04 00:03:00.0건강기능식품유통전문판매업191833.590372446855.148019<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
35931800003180000-135-2024-000082024-05-02<NA>1영업/정상1영업<NA><NA><NA><NA>07086570226<NA>150-095서울특별시 영등포구 문래동*가 ** 하우스디 비즈서울특별시 영등포구 선유로*길 **, 하우스디 비즈 *층 ***호 (문래동*가)7285엠에스무역2024-05-02 11:18:38I2023-12-05 00:04:00.0건강기능식품유통전문판매업189921.671895445990.538307<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>