Overview

Dataset statistics

Number of variables44
Number of observations28
Missing cells331
Missing cells (%)26.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.4 KiB
Average record size in memory379.7 B

Variable types

Categorical20
Text10
DateTime3
Unsupported7
Numeric3
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
Author금천구
URLhttps://data.seoul.go.kr/dataList/OA-18219/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
영업장주변구분명 has constant value ""Constant
등급구분명 has constant value ""Constant
급수시설구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
인허가취소일자 has 28 (100.0%) missing valuesMissing
폐업일자 has 14 (50.0%) missing valuesMissing
휴업시작일자 has 28 (100.0%) missing valuesMissing
휴업종료일자 has 28 (100.0%) missing valuesMissing
재개업일자 has 28 (100.0%) missing valuesMissing
전화번호 has 7 (25.0%) missing valuesMissing
소재지면적 has 11 (39.3%) missing valuesMissing
도로명주소 has 7 (25.0%) missing valuesMissing
도로명우편번호 has 8 (28.6%) missing valuesMissing
좌표정보(X) has 1 (3.6%) missing valuesMissing
좌표정보(Y) has 1 (3.6%) missing valuesMissing
영업장주변구분명 has 27 (96.4%) missing valuesMissing
등급구분명 has 27 (96.4%) missing valuesMissing
급수시설구분명 has 27 (96.4%) missing valuesMissing
다중이용업소여부 has 5 (17.9%) missing valuesMissing
전통업소지정번호 has 28 (100.0%) missing valuesMissing
전통업소주된음식 has 28 (100.0%) missing valuesMissing
홈페이지 has 28 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가일자 has unique valuesUnique
지번주소 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
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

Reproduction

Analysis started2024-05-11 06:58:26.805296
Analysis finished2024-05-11 06:58:27.464519
Duration0.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size356.0 B
3170000
28 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3170000
2nd row3170000
3rd row3170000
4th row3170000
5th row3170000

Common Values

ValueCountFrequency (%)
3170000 28
100.0%

Length

2024-05-11T15:58:27.536279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:27.659613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3170000 28
100.0%

관리번호
Text

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
2024-05-11T15:58:27.876485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters616
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

Unique28 ?
Unique (%)100.0%

Sample

1st row3170000-117-2001-00443
2nd row3170000-117-2002-00001
3rd row3170000-117-2002-00002
4th row3170000-117-2003-00001
5th row3170000-117-2003-00002
ValueCountFrequency (%)
3170000-117-2001-00443 1
 
3.6%
3170000-117-2002-00001 1
 
3.6%
3170000-117-2020-00002 1
 
3.6%
3170000-117-2020-00001 1
 
3.6%
3170000-117-2019-00002 1
 
3.6%
3170000-117-2019-00001 1
 
3.6%
3170000-117-2018-00001 1
 
3.6%
3170000-117-2017-00001 1
 
3.6%
3170000-117-2016-00001 1
 
3.6%
3170000-117-2015-00001 1
 
3.6%
Other values (18) 18
64.3%
2024-05-11T15:58:28.250238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 269
43.7%
1 112
18.2%
- 84
 
13.6%
7 58
 
9.4%
2 41
 
6.7%
3 33
 
5.4%
4 5
 
0.8%
6 5
 
0.8%
8 5
 
0.8%
9 3
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 532
86.4%
Dash Punctuation 84
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 269
50.6%
1 112
21.1%
7 58
 
10.9%
2 41
 
7.7%
3 33
 
6.2%
4 5
 
0.9%
6 5
 
0.9%
8 5
 
0.9%
9 3
 
0.6%
5 1
 
0.2%
Dash Punctuation
ValueCountFrequency (%)
- 84
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 616
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 269
43.7%
1 112
18.2%
- 84
 
13.6%
7 58
 
9.4%
2 41
 
6.7%
3 33
 
5.4%
4 5
 
0.8%
6 5
 
0.8%
8 5
 
0.8%
9 3
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 616
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 269
43.7%
1 112
18.2%
- 84
 
13.6%
7 58
 
9.4%
2 41
 
6.7%
3 33
 
5.4%
4 5
 
0.8%
6 5
 
0.8%
8 5
 
0.8%
9 3
 
0.5%

인허가일자
Date

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
Minimum2001-08-06 00:00:00
Maximum2022-04-19 00:00:00
2024-05-11T15:58:28.425687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:58:28.585988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing28
Missing (%)100.0%
Memory size384.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size356.0 B
1
14 
3
14 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 14
50.0%
3 14
50.0%

Length

2024-05-11T15:58:28.731145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:28.860850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 14
50.0%
3 14
50.0%

영업상태명
Categorical

Distinct2
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size356.0 B
영업/정상
14 
폐업
14 

Length

Max length5
Median length3.5
Mean length3.5
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 14
50.0%
폐업 14
50.0%

Length

2024-05-11T15:58:29.053007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:29.205211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 14
50.0%
폐업 14
50.0%

상세영업상태코드
Categorical

Distinct2
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size356.0 B
1
14 
2
14 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 14
50.0%
2 14
50.0%

Length

2024-05-11T15:58:29.347795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:29.461465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 14
50.0%
2 14
50.0%

상세영업상태명
Categorical

Distinct2
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size356.0 B
영업
14 
폐업
14 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 14
50.0%
폐업 14
50.0%

Length

2024-05-11T15:58:29.570570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:29.688707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 14
50.0%
폐업 14
50.0%

폐업일자
Date

MISSING 

Distinct14
Distinct (%)100.0%
Missing14
Missing (%)50.0%
Memory size356.0 B
Minimum2003-10-24 00:00:00
Maximum2023-07-06 00:00:00
2024-05-11T15:58:29.790009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:58:29.912096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing28
Missing (%)100.0%
Memory size384.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing28
Missing (%)100.0%
Memory size384.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing28
Missing (%)100.0%
Memory size384.0 B

전화번호
Text

MISSING 

Distinct21
Distinct (%)100.0%
Missing7
Missing (%)25.0%
Memory size356.0 B
2024-05-11T15:58:30.099087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length10.952381
Min length7

Characters and Unicode

Total characters230
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

Unique21 ?
Unique (%)100.0%

Sample

1st row02 8663355
2nd row02 728 5956
3rd row0232828162
4th row8057859
5th row0220263131
ValueCountFrequency (%)
02 14
31.1%
031 2
 
4.4%
812 1
 
2.2%
02866 1
 
2.2%
8576004 1
 
2.2%
8058805 1
 
2.2%
8802 1
 
2.2%
804 1
 
2.2%
5100 1
 
2.2%
449 1
 
2.2%
Other values (21) 21
46.7%
2024-05-11T15:58:30.458858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 41
17.8%
36
15.7%
2 33
14.3%
8 24
10.4%
5 19
8.3%
6 17
7.4%
1 16
 
7.0%
3 13
 
5.7%
9 13
 
5.7%
4 10
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 194
84.3%
Space Separator 36
 
15.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 41
21.1%
2 33
17.0%
8 24
12.4%
5 19
9.8%
6 17
8.8%
1 16
 
8.2%
3 13
 
6.7%
9 13
 
6.7%
4 10
 
5.2%
7 8
 
4.1%
Space Separator
ValueCountFrequency (%)
36
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 230
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 41
17.8%
36
15.7%
2 33
14.3%
8 24
10.4%
5 19
8.3%
6 17
7.4%
1 16
 
7.0%
3 13
 
5.7%
9 13
 
5.7%
4 10
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 230
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 41
17.8%
36
15.7%
2 33
14.3%
8 24
10.4%
5 19
8.3%
6 17
7.4%
1 16
 
7.0%
3 13
 
5.7%
9 13
 
5.7%
4 10
 
4.3%

소재지면적
Text

MISSING 

Distinct17
Distinct (%)100.0%
Missing11
Missing (%)39.3%
Memory size356.0 B
2024-05-11T15:58:30.699274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length5.5294118
Min length5

Characters and Unicode

Total characters94
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

Unique17 ?
Unique (%)100.0%

Sample

1st row13,732.35
2nd row43.00
3rd row75.33
4th row36.80
5th row198.00
ValueCountFrequency (%)
13,732.35 1
 
5.9%
78.85 1
 
5.9%
87.48 1
 
5.9%
129.67 1
 
5.9%
113.40 1
 
5.9%
31.90 1
 
5.9%
99.00 1
 
5.9%
174.93 1
 
5.9%
52.50 1
 
5.9%
43.00 1
 
5.9%
Other values (7) 7
41.2%
2024-05-11T15:58:31.107301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 17
18.1%
0 16
17.0%
3 11
11.7%
1 10
10.6%
4 7
7.4%
8 7
7.4%
7 6
 
6.4%
9 6
 
6.4%
2 5
 
5.3%
5 5
 
5.3%
Other values (2) 4
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 76
80.9%
Other Punctuation 18
 
19.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 16
21.1%
3 11
14.5%
1 10
13.2%
4 7
9.2%
8 7
9.2%
7 6
 
7.9%
9 6
 
7.9%
2 5
 
6.6%
5 5
 
6.6%
6 3
 
3.9%
Other Punctuation
ValueCountFrequency (%)
. 17
94.4%
, 1
 
5.6%

Most occurring scripts

ValueCountFrequency (%)
Common 94
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 17
18.1%
0 16
17.0%
3 11
11.7%
1 10
10.6%
4 7
7.4%
8 7
7.4%
7 6
 
6.4%
9 6
 
6.4%
2 5
 
5.3%
5 5
 
5.3%
Other values (2) 4
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 94
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 17
18.1%
0 16
17.0%
3 11
11.7%
1 10
10.6%
4 7
7.4%
8 7
7.4%
7 6
 
6.4%
9 6
 
6.4%
2 5
 
5.3%
5 5
 
5.3%
Other values (2) 4
 
4.3%

소재지우편번호
Text

Distinct18
Distinct (%)64.3%
Missing0
Missing (%)0.0%
Memory size356.0 B
2024-05-11T15:58:31.344567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1428571
Min length6

Characters and Unicode

Total characters172
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

Unique12 ?
Unique (%)42.9%

Sample

1st row153802
2nd row153-814
3rd row153803
4th row153821
5th row153813
ValueCountFrequency (%)
153803 4
14.3%
153813 3
 
10.7%
153864 3
 
10.7%
153802 2
 
7.1%
153801 2
 
7.1%
153821 2
 
7.1%
153828 1
 
3.6%
153837 1
 
3.6%
153030 1
 
3.6%
153779 1
 
3.6%
Other values (8) 8
28.6%
2024-05-11T15:58:31.665851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 41
23.8%
1 39
22.7%
5 28
16.3%
8 24
14.0%
0 15
 
8.7%
2 6
 
3.5%
6 5
 
2.9%
7 5
 
2.9%
4 4
 
2.3%
- 4
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 168
97.7%
Dash Punctuation 4
 
2.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 41
24.4%
1 39
23.2%
5 28
16.7%
8 24
14.3%
0 15
 
8.9%
2 6
 
3.6%
6 5
 
3.0%
7 5
 
3.0%
4 4
 
2.4%
9 1
 
0.6%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 172
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 41
23.8%
1 39
22.7%
5 28
16.3%
8 24
14.0%
0 15
 
8.7%
2 6
 
3.5%
6 5
 
2.9%
7 5
 
2.9%
4 4
 
2.3%
- 4
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 172
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 41
23.8%
1 39
22.7%
5 28
16.3%
8 24
14.0%
0 15
 
8.7%
2 6
 
3.5%
6 5
 
2.9%
7 5
 
2.9%
4 4
 
2.3%
- 4
 
2.3%

지번주소
Text

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
2024-05-11T15:58:31.884923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length35.5
Mean length32.535714
Min length18

Characters and Unicode

Total characters911
Distinct characters100
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)100.0%

Sample

1st row서울특별시 금천구 가산동 ***-* [디지털단지로 ***]
2nd row서울특별시 금천구 독산동 ***-* [두산로 **]
3rd row서울특별시 금천구 가산동 ***-** [디지털단지로 ***]
4th row서울특별시 금천구 독산동 ****-*번지
5th row서울특별시 금천구 독산동 ***-*번지 협진식품빌딩 B-*-**호
ValueCountFrequency (%)
서울특별시 28
16.8%
금천구 28
16.8%
20
12.0%
번지 16
9.6%
가산동 12
 
7.2%
독산동 10
 
6.0%
호 10
 
6.0%
시흥동 7
 
4.2%
디지털단지로 2
 
1.2%
에이스테크노타워**차 1
 
0.6%
Other values (33) 33
19.8%
2024-05-11T15:58:32.238502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 193
21.2%
158
17.3%
시 36
 
4.0%
동 32
 
3.5%
구 29
 
3.2%
서 28
 
3.1%
특 28
 
3.1%
별 28
 
3.1%
금 28
 
3.1%
천 28
 
3.1%
Other values (90) 323
35.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 511
56.1%
Other Punctuation 193
 
21.2%
Space Separator 158
 
17.3%
Dash Punctuation 26
 
2.9%
Close Punctuation 10
 
1.1%
Open Punctuation 10
 
1.1%
Uppercase Letter 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 36
 
7.0%
동 32
 
6.3%
구 29
 
5.7%
서 28
 
5.5%
특 28
 
5.5%
별 28
 
5.5%
금 28
 
5.5%
천 28
 
5.5%
울 28
 
5.5%
산 27
 
5.3%
Other values (81) 219
42.9%
Close Punctuation
ValueCountFrequency (%)
] 8
80.0%
) 2
 
20.0%
Open Punctuation
ValueCountFrequency (%)
[ 8
80.0%
( 2
 
20.0%
Uppercase Letter
ValueCountFrequency (%)
B 2
66.7%
A 1
33.3%
Other Punctuation
ValueCountFrequency (%)
* 193
100.0%
Space Separator
ValueCountFrequency (%)
158
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 511
56.1%
Common 397
43.6%
Latin 3
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 36
 
7.0%
동 32
 
6.3%
구 29
 
5.7%
서 28
 
5.5%
특 28
 
5.5%
별 28
 
5.5%
금 28
 
5.5%
천 28
 
5.5%
울 28
 
5.5%
산 27
 
5.3%
Other values (81) 219
42.9%
Common
ValueCountFrequency (%)
* 193
48.6%
158
39.8%
- 26
 
6.5%
] 8
 
2.0%
[ 8
 
2.0%
) 2
 
0.5%
( 2
 
0.5%
Latin
ValueCountFrequency (%)
B 2
66.7%
A 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 511
56.1%
ASCII 400
43.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 193
48.2%
158
39.5%
- 26
 
6.5%
] 8
 
2.0%
[ 8
 
2.0%
) 2
 
0.5%
( 2
 
0.5%
B 2
 
0.5%
A 1
 
0.2%
Hangul
ValueCountFrequency (%)
시 36
 
7.0%
동 32
 
6.3%
구 29
 
5.7%
서 28
 
5.5%
특 28
 
5.5%
별 28
 
5.5%
금 28
 
5.5%
천 28
 
5.5%
울 28
 
5.5%
산 27
 
5.3%
Other values (81) 219
42.9%

도로명주소
Text

MISSING 

Distinct20
Distinct (%)95.2%
Missing7
Missing (%)25.0%
Memory size356.0 B
2024-05-11T15:58:32.498115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length42
Mean length39.666667
Min length29

Characters and Unicode

Total characters833
Distinct characters88
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)90.5%

Sample

1st row서울특별시 금천구 디지털로 *** (가산동,[디지털단지로 ***])
2nd row서울특별시 금천구 두산로 ** (독산동,[두산로 **])
3rd row서울특별시 금천구 가산디지털*로 ** (가산동,[디지털단지로 ***])
4th row서울특별시 금천구 가산디지털*로 ***, B동 ****호 (가산동, 우림라이온스밸리)
5th row서울특별시 금천구 시흥대로**길 **, *층 (시흥동)
ValueCountFrequency (%)
26
17.6%
서울특별시 21
14.2%
금천구 21
14.2%
호 12
 
8.1%
가산동 8
 
5.4%
가산디지털*로 7
 
4.7%
시흥동 6
 
4.1%
시흥대로**길 5
 
3.4%
층 3
 
2.0%
가산동,[디지털단지로 2
 
1.4%
Other values (35) 37
25.0%
2024-05-11T15:58:32.908354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 144
17.3%
127
 
15.2%
시 34
 
4.1%
산 31
 
3.7%
, 27
 
3.2%
로 25
 
3.0%
동 25
 
3.0%
( 22
 
2.6%
) 22
 
2.6%
서 21
 
2.5%
Other values (78) 355
42.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 478
57.4%
Other Punctuation 171
 
20.5%
Space Separator 127
 
15.2%
Open Punctuation 27
 
3.2%
Close Punctuation 27
 
3.2%
Uppercase Letter 2
 
0.2%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 34
 
7.1%
산 31
 
6.5%
로 25
 
5.2%
동 25
 
5.2%
서 21
 
4.4%
특 21
 
4.4%
별 21
 
4.4%
금 21
 
4.4%
천 21
 
4.4%
구 21
 
4.4%
Other values (68) 237
49.6%
Other Punctuation
ValueCountFrequency (%)
* 144
84.2%
, 27
 
15.8%
Open Punctuation
ValueCountFrequency (%)
( 22
81.5%
[ 5
 
18.5%
Close Punctuation
ValueCountFrequency (%)
) 22
81.5%
] 5
 
18.5%
Uppercase Letter
ValueCountFrequency (%)
A 1
50.0%
B 1
50.0%
Space Separator
ValueCountFrequency (%)
127
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 478
57.4%
Common 353
42.4%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 34
 
7.1%
산 31
 
6.5%
로 25
 
5.2%
동 25
 
5.2%
서 21
 
4.4%
특 21
 
4.4%
별 21
 
4.4%
금 21
 
4.4%
천 21
 
4.4%
구 21
 
4.4%
Other values (68) 237
49.6%
Common
ValueCountFrequency (%)
* 144
40.8%
127
36.0%
, 27
 
7.6%
( 22
 
6.2%
) 22
 
6.2%
] 5
 
1.4%
[ 5
 
1.4%
- 1
 
0.3%
Latin
ValueCountFrequency (%)
A 1
50.0%
B 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 478
57.4%
ASCII 355
42.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 144
40.6%
127
35.8%
, 27
 
7.6%
( 22
 
6.2%
) 22
 
6.2%
] 5
 
1.4%
[ 5
 
1.4%
A 1
 
0.3%
B 1
 
0.3%
- 1
 
0.3%
Hangul
ValueCountFrequency (%)
시 34
 
7.1%
산 31
 
6.5%
로 25
 
5.2%
동 25
 
5.2%
서 21
 
4.4%
특 21
 
4.4%
별 21
 
4.4%
금 21
 
4.4%
천 21
 
4.4%
구 21
 
4.4%
Other values (68) 237
49.6%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct17
Distinct (%)85.0%
Missing8
Missing (%)28.6%
Infinite0
Infinite (%)0.0%
Mean8569.7
Minimum8502
Maximum8638
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2024-05-11T15:58:33.087166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8502
5-th percentile8502.95
Q18511.5
median8583
Q38599.5
95-th percentile8632.3
Maximum8638
Range136
Interquartile range (IQR)88

Descriptive statistics

Standard deviation46.62177
Coefficient of variation (CV)0.0054403037
Kurtosis-1.222722
Mean8569.7
Median Absolute Deviation (MAD)30
Skewness-0.42470651
Sum171394
Variance2173.5895
MonotonicityNot monotonic
2024-05-11T15:58:33.233384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
8503 2
 
7.1%
8613 2
 
7.1%
8590 2
 
7.1%
8581 1
 
3.6%
8582 1
 
3.6%
8576 1
 
3.6%
8632 1
 
3.6%
8502 1
 
3.6%
8588 1
 
3.6%
8638 1
 
3.6%
Other values (7) 7
25.0%
(Missing) 8
28.6%
ValueCountFrequency (%)
8502 1
3.6%
8503 2
7.1%
8506 1
3.6%
8507 1
3.6%
8513 1
3.6%
8564 1
3.6%
8576 1
3.6%
8581 1
3.6%
8582 1
3.6%
8584 1
3.6%
ValueCountFrequency (%)
8638 1
3.6%
8632 1
3.6%
8614 1
3.6%
8613 2
7.1%
8595 1
3.6%
8590 2
7.1%
8588 1
3.6%
8584 1
3.6%
8582 1
3.6%
8581 1
3.6%

사업장명
Text

Distinct27
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Memory size356.0 B
2024-05-11T15:58:33.509812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length7.1071429
Min length4

Characters and Unicode

Total characters199
Distinct characters88
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)92.9%

Sample

1st row롯데글로벌로지스(주)
2nd row(주)한진
3rd row(주)한진
4th row영석상사
5th row시온케터링
ValueCountFrequency (%)
주식회사 3
 
9.4%
주)한진 2
 
6.2%
주 1
 
3.1%
조은상유통 1
 
3.1%
주)신화종합물류 1
 
3.1%
웃는아이 1
 
3.1%
주)에스앤피로지스 1
 
3.1%
지평로지스 1
 
3.1%
주)대림종합운수 1
 
3.1%
한솔운수(주 1
 
3.1%
Other values (19) 19
59.4%
2024-05-11T15:58:34.207502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 18
 
9.0%
( 14
 
7.0%
) 14
 
7.0%
스 6
 
3.0%
로 5
 
2.5%
지 5
 
2.5%
이 5
 
2.5%
대 5
 
2.5%
한 5
 
2.5%
사 5
 
2.5%
Other values (78) 117
58.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 164
82.4%
Open Punctuation 14
 
7.0%
Close Punctuation 14
 
7.0%
Space Separator 4
 
2.0%
Uppercase Letter 2
 
1.0%
Other Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 18
 
11.0%
스 6
 
3.7%
로 5
 
3.0%
지 5
 
3.0%
이 5
 
3.0%
대 5
 
3.0%
한 5
 
3.0%
사 5
 
3.0%
종 4
 
2.4%
합 3
 
1.8%
Other values (72) 103
62.8%
Uppercase Letter
ValueCountFrequency (%)
C 1
50.0%
L 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 164
82.4%
Common 33
 
16.6%
Latin 2
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 18
 
11.0%
스 6
 
3.7%
로 5
 
3.0%
지 5
 
3.0%
이 5
 
3.0%
대 5
 
3.0%
한 5
 
3.0%
사 5
 
3.0%
종 4
 
2.4%
합 3
 
1.8%
Other values (72) 103
62.8%
Common
ValueCountFrequency (%)
( 14
42.4%
) 14
42.4%
4
 
12.1%
& 1
 
3.0%
Latin
ValueCountFrequency (%)
C 1
50.0%
L 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 164
82.4%
ASCII 35
 
17.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 18
 
11.0%
스 6
 
3.7%
로 5
 
3.0%
지 5
 
3.0%
이 5
 
3.0%
대 5
 
3.0%
한 5
 
3.0%
사 5
 
3.0%
종 4
 
2.4%
합 3
 
1.8%
Other values (72) 103
62.8%
ASCII
ValueCountFrequency (%)
( 14
40.0%
) 14
40.0%
4
 
11.4%
C 1
 
2.9%
& 1
 
2.9%
L 1
 
2.9%

최종수정일자
Date

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
Minimum2003-09-29 00:00:00
Maximum2024-01-10 09:41:03
2024-05-11T15:58:34.372949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:58:34.525765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)

데이터갱신구분
Categorical

Distinct2
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size356.0 B
I
18 
U
10 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 18
64.3%
U 10
35.7%

Length

2024-05-11T15:58:34.693555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:34.810559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 18
64.3%
u 10
35.7%

데이터갱신일자
Categorical

Distinct12
Distinct (%)42.9%
Missing0
Missing (%)0.0%
Memory size356.0 B
2018-08-31 23:59:59.0
14 
2022-02-11 02:40:00.0
4 
2022-12-07 00:08:00.0
 
1
2022-03-18 02:40:00.0
 
1
2022-12-05 22:03:00.0
 
1
Other values (7)
7 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique10 ?
Unique (%)35.7%

Sample

1st row2022-02-11 02:40:00.0
2nd row2022-12-07 00:08:00.0
3rd row2022-03-18 02:40:00.0
4th row2018-08-31 23:59:59.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 14
50.0%
2022-02-11 02:40:00.0 4
 
14.3%
2022-12-07 00:08:00.0 1
 
3.6%
2022-03-18 02:40:00.0 1
 
3.6%
2022-12-05 22:03:00.0 1
 
3.6%
2019-03-08 02:40:00.0 1
 
3.6%
2023-11-30 23:02:00.0 1
 
3.6%
2020-11-06 02:40:00.0 1
 
3.6%
2019-07-03 02:21:41.0 1
 
3.6%
2022-12-03 23:06:00.0 1
 
3.6%
Other values (2) 2
 
7.1%

Length

2024-05-11T15:58:34.940927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 14
25.0%
23:59:59.0 14
25.0%
02:40:00.0 7
12.5%
2022-02-11 4
 
7.1%
2020-11-06 1
 
1.8%
2021-12-03 1
 
1.8%
00:23:14.0 1
 
1.8%
2020-08-06 1
 
1.8%
23:06:00.0 1
 
1.8%
2022-12-03 1
 
1.8%
Other values (11) 11
19.6%

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size356.0 B
식품운반업
28 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품운반업 28
100.0%

Length

2024-05-11T15:58:35.061944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:35.160978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품운반업 28
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct27
Distinct (%)100.0%
Missing1
Missing (%)3.6%
Infinite0
Infinite (%)0.0%
Mean190403.75
Minimum189208.08
Maximum192147.81
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2024-05-11T15:58:35.272949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189208.08
5-th percentile189354.64
Q1189743.94
median190489.65
Q3191045.91
95-th percentile191326.31
Maximum192147.81
Range2939.7304
Interquartile range (IQR)1301.9715

Descriptive statistics

Standard deviation784.50441
Coefficient of variation (CV)0.004120215
Kurtosis-0.86695185
Mean190403.75
Median Absolute Deviation (MAD)622.73209
Skewness0.11245795
Sum5140901.3
Variance615447.16
MonotonicityNot monotonic
2024-05-11T15:58:35.420377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
189690.633210559 1
 
3.6%
190251.903279301 1
 
3.6%
190099.41176063 1
 
3.6%
189350.592434703 1
 
3.6%
189797.251808445 1
 
3.6%
190718.377249788 1
 
3.6%
192147.806763979 1
 
3.6%
189364.095969911 1
 
3.6%
189829.504142672 1
 
3.6%
190694.880295092 1
 
3.6%
Other values (17) 17
60.7%
ValueCountFrequency (%)
189208.076361179 1
3.6%
189350.592434703 1
3.6%
189364.095969911 1
3.6%
189372.681522711 1
3.6%
189417.708595762 1
3.6%
189538.020935968 1
3.6%
189690.633210559 1
3.6%
189797.251808445 1
3.6%
189829.504142672 1
3.6%
189956.130370439 1
3.6%
ValueCountFrequency (%)
192147.806763979 1
3.6%
191334.587401502 1
3.6%
191307.004413889 1
3.6%
191113.674823972 1
3.6%
191112.386672558 1
3.6%
191106.044793348 1
3.6%
191050.584448517 1
3.6%
191041.243653765 1
3.6%
190996.579111216 1
3.6%
190953.350904794 1
3.6%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct27
Distinct (%)100.0%
Missing1
Missing (%)3.6%
Infinite0
Infinite (%)0.0%
Mean440791.89
Minimum438307.42
Maximum442309.17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2024-05-11T15:58:35.557729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum438307.42
5-th percentile438823.12
Q1440458.58
median440875.38
Q3441656.71
95-th percentile442178.73
Maximum442309.17
Range4001.7516
Interquartile range (IQR)1198.1293

Descriptive statistics

Standard deviation1097.2304
Coefficient of variation (CV)0.0024892254
Kurtosis-0.23134629
Mean440791.89
Median Absolute Deviation (MAD)742.68697
Skewness-0.71726917
Sum11901381
Variance1203914.5
MonotonicityNot monotonic
2024-05-11T15:58:35.744973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
441583.577484134 1
 
3.6%
440875.384680866 1
 
3.6%
440416.170972838 1
 
3.6%
442143.206055455 1
 
3.6%
441250.271238238 1
 
3.6%
439322.42742435 1
 
3.6%
439872.136912651 1
 
3.6%
441746.981529543 1
 
3.6%
441618.071646624 1
 
3.6%
440764.426277932 1
 
3.6%
Other values (17) 17
60.7%
ValueCountFrequency (%)
438307.423372216 1
3.6%
438711.564180845 1
3.6%
439083.411970871 1
3.6%
439251.334214938 1
3.6%
439322.42742435 1
3.6%
439872.136912651 1
3.6%
440416.170972838 1
3.6%
440500.995945057 1
3.6%
440515.66903538 1
3.6%
440569.045195958 1
3.6%
ValueCountFrequency (%)
442309.174987731 1
3.6%
442193.951625785 1
3.6%
442143.206055455 1
3.6%
441982.427934953 1
3.6%
441746.981529543 1
3.6%
441699.385300487 1
3.6%
441695.353875235 1
3.6%
441618.071646624 1
3.6%
441583.577484134 1
3.6%
441433.526777708 1
3.6%

위생업태명
Categorical

Distinct2
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size356.0 B
식품운반업
23 
<NA>
5 

Length

Max length5
Median length5
Mean length4.8214286
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품운반업 23
82.1%
<NA> 5
 
17.9%

Length

2024-05-11T15:58:35.960664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:36.073267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품운반업 23
82.1%
na 5
 
17.9%

남성종사자수
Categorical

Distinct2
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size356.0 B
<NA>
24 
0
4 

Length

Max length4
Median length4
Mean length3.5714286
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 24
85.7%
0 4
 
14.3%

Length

2024-05-11T15:58:36.201350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:36.313137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 24
85.7%
0 4
 
14.3%

여성종사자수
Categorical

Distinct2
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size356.0 B
<NA>
24 
0
4 

Length

Max length4
Median length4
Mean length3.5714286
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 24
85.7%
0 4
 
14.3%

Length

2024-05-11T15:58:36.434366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:36.541450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 24
85.7%
0 4
 
14.3%

영업장주변구분명
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing27
Missing (%)96.4%
Memory size356.0 B
2024-05-11T15:58:36.622576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row기타
ValueCountFrequency (%)
기타 1
100.0%
2024-05-11T15:58:36.830820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 1
50.0%
타 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 1
50.0%
타 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 1
50.0%
타 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 1
50.0%
타 1
50.0%

등급구분명
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing27
Missing (%)96.4%
Memory size356.0 B
2024-05-11T15:58:36.929790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row기타
ValueCountFrequency (%)
기타 1
100.0%
2024-05-11T15:58:37.173649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 1
50.0%
타 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 1
50.0%
타 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 1
50.0%
타 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 1
50.0%
타 1
50.0%

급수시설구분명
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing27
Missing (%)96.4%
Memory size356.0 B
2024-05-11T15:58:37.320012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row상수도전용
ValueCountFrequency (%)
상수도전용 1
100.0%
2024-05-11T15:58:37.622918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
상 1
20.0%
수 1
20.0%
도 1
20.0%
전 1
20.0%
용 1
20.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 1
20.0%
수 1
20.0%
도 1
20.0%
전 1
20.0%
용 1
20.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 1
20.0%
수 1
20.0%
도 1
20.0%
전 1
20.0%
용 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
상 1
20.0%
수 1
20.0%
도 1
20.0%
전 1
20.0%
용 1
20.0%

총인원
Categorical

Distinct2
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size356.0 B
<NA>
24 
0
4 

Length

Max length4
Median length4
Mean length3.5714286
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 24
85.7%
0 4
 
14.3%

Length

2024-05-11T15:58:37.821606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:38.004034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 24
85.7%
0 4
 
14.3%

본사종업원수
Categorical

Distinct2
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size356.0 B
0
15 
<NA>
13 

Length

Max length4
Median length1
Mean length2.3928571
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 15
53.6%
<NA> 13
46.4%

Length

2024-05-11T15:58:38.217795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:38.356885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 15
53.6%
na 13
46.4%

공장사무직종업원수
Categorical

Distinct2
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size356.0 B
0
15 
<NA>
13 

Length

Max length4
Median length1
Mean length2.3928571
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 15
53.6%
<NA> 13
46.4%

Length

2024-05-11T15:58:38.517200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:38.670302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 15
53.6%
na 13
46.4%

공장판매직종업원수
Categorical

Distinct2
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size356.0 B
0
15 
<NA>
13 

Length

Max length4
Median length1
Mean length2.3928571
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 15
53.6%
<NA> 13
46.4%

Length

2024-05-11T15:58:38.835949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:38.985004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 15
53.6%
na 13
46.4%

공장생산직종업원수
Categorical

Distinct2
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size356.0 B
0
15 
<NA>
13 

Length

Max length4
Median length1
Mean length2.3928571
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 15
53.6%
<NA> 13
46.4%

Length

2024-05-11T15:58:39.151710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:39.315533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 15
53.6%
na 13
46.4%

건물소유구분명
Categorical

Distinct3
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size356.0 B
<NA>
16 
자가
7 
임대
5 

Length

Max length4
Median length4
Mean length3.1428571
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 16
57.1%
자가 7
25.0%
임대 5
 
17.9%

Length

2024-05-11T15:58:39.480239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:39.638047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 16
57.1%
자가 7
25.0%
임대 5
 
17.9%

보증액
Categorical

Distinct3
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size356.0 B
<NA>
20 
0
7 
20000000
 
1

Length

Max length8
Median length4
Mean length3.3928571
Min length1

Unique

Unique1 ?
Unique (%)3.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 20
71.4%
0 7
 
25.0%
20000000 1
 
3.6%

Length

2024-05-11T15:58:39.799306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:39.925017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 20
71.4%
0 7
 
25.0%
20000000 1
 
3.6%

월세액
Categorical

Distinct3
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size356.0 B
<NA>
20 
0
7 
1900000
 
1

Length

Max length7
Median length4
Mean length3.3571429
Min length1

Unique

Unique1 ?
Unique (%)3.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 20
71.4%
0 7
 
25.0%
1900000 1
 
3.6%

Length

2024-05-11T15:58:40.069829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:40.209869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 20
71.4%
0 7
 
25.0%
1900000 1
 
3.6%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)4.3%
Missing5
Missing (%)17.9%
Memory size188.0 B
False
23 
(Missing)
5 
ValueCountFrequency (%)
False 23
82.1%
(Missing) 5
 
17.9%
2024-05-11T15:58:40.330138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Categorical

Distinct4
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size356.0 B
0.0
21 
<NA>
5 
4017.09
 
1
4.2
 
1

Length

Max length7
Median length3
Mean length3.3214286
Min length3

Unique

Unique2 ?
Unique (%)7.1%

Sample

1st row4017.09
2nd row<NA>
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 21
75.0%
<NA> 5
 
17.9%
4017.09 1
 
3.6%
4.2 1
 
3.6%

Length

2024-05-11T15:58:40.530810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:40.691005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 21
75.0%
na 5
 
17.9%
4017.09 1
 
3.6%
4.2 1
 
3.6%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing28
Missing (%)100.0%
Memory size384.0 B

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing28
Missing (%)100.0%
Memory size384.0 B

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing28
Missing (%)100.0%
Memory size384.0 B

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031700003170000-117-2001-0044320010903<NA>1영업/정상1영업<NA><NA><NA><NA>02 866335513,732.35153802서울특별시 금천구 가산동 ***-* [디지털단지로 ***]서울특별시 금천구 디지털로 *** (가산동,[디지털단지로 ***])8590롯데글로벌로지스(주)2022-02-09 14:51:03U2022-02-11 02:40:00.0식품운반업189690.633211441583.577484식품운반업00기타기타<NA>00000<NA>00N4017.09<NA><NA><NA>
131700003170000-117-2002-000012001-08-06<NA>3폐업2폐업2023-07-06<NA><NA><NA>02 728 5956<NA>153-814서울특별시 금천구 독산동 ***-* [두산로 **]서울특별시 금천구 두산로 ** (독산동,[두산로 **])<NA>(주)한진2023-07-06 16:30:09U2022-12-07 00:08:00.0식품운반업190251.903279440875.384681<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
231700003170000-117-2002-0000220010829<NA>1영업/정상1영업<NA><NA><NA><NA>0232828162<NA>153803서울특별시 금천구 가산동 ***-** [디지털단지로 ***]서울특별시 금천구 가산디지털*로 ** (가산동,[디지털단지로 ***])8588(주)한진2022-03-16 16:38:16U2022-03-18 02:40:00.0식품운반업189372.681523441433.526778식품운반업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
331700003170000-117-2003-0000120030929<NA>3폐업2폐업20050826<NA><NA><NA><NA><NA>153821서울특별시 금천구 독산동 ****-*번지<NA><NA>영석상사2003-09-29 00:00:00I2018-08-31 23:59:59.0식품운반업191334.587402440722.939632식품운반업<NA><NA><NA><NA><NA><NA>0000임대00N0.0<NA><NA><NA>
431700003170000-117-2003-0000220031022<NA>3폐업2폐업20031024<NA><NA><NA><NA><NA>153813서울특별시 금천구 독산동 ***-*번지 협진식품빌딩 B-*-**호<NA><NA>시온케터링2003-10-22 00:00:00I2018-08-31 23:59:59.0식품운반업190771.59559440515.669035식품운반업<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA>
531700003170000-117-2006-0000120060109<NA>3폐업2폐업20110708<NA><NA><NA>8057859<NA>153813서울특별시 금천구 독산동 ***-**번지 (지상*층)[작은말미길 *]<NA><NA>번영유통2007-10-17 14:09:10I2018-08-31 23:59:59.0식품운반업190489.654581440569.045196식품운반업<NA><NA><NA><NA><NA><NA>0000자가<NA><NA>N0.0<NA><NA><NA>
631700003170000-117-2006-0000220060707<NA>3폐업2폐업20070820<NA><NA><NA><NA><NA>153010서울특별시 금천구 독산동 ***번지 신도브래뉴아파트 상가 ***호<NA><NA>두산종가남부대리점2006-07-07 00:00:00I2018-08-31 23:59:59.0식품운반업191106.044793441695.353875식품운반업<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA>
731700003170000-117-2006-000032006-08-17<NA>1영업/정상1영업<NA><NA><NA><NA>0220263131<NA>153-776서울특별시 금천구 가산동 ***-** 우림라이온스밸리 B동 ****호서울특별시 금천구 가산디지털*로 ***, B동 ****호 (가산동, 우림라이온스밸리)8507대원냉동(주)2023-06-21 14:17:00U2022-12-05 22:03:00.0식품운반업189538.020936441982.427935<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
831700003170000-117-2006-0000420061012<NA>1영업/정상1영업<NA><NA><NA><NA>02 817 856643.00153864서울특별시 금천구 시흥동 ***-**번지 *층서울특별시 금천구 시흥대로**길 **, *층 (시흥동)8632주식회사 삼원푸드2019-03-06 11:22:39U2019-03-08 02:40:00.0식품운반업190996.579111439083.411971식품운반업<NA><NA><NA><NA><NA><NA>0000임대<NA><NA>N0.0<NA><NA><NA>
931700003170000-117-2007-0000120070917<NA>3폐업2폐업20160719<NA><NA><NA>02 8649300<NA>153821서울특별시 금천구 독산동 ****-**번지 지상*층서울특별시 금천구 범안로 **** (독산동,지상*층)8581신성메디슨(주)2016-07-19 14:18:50I2018-08-31 23:59:59.0식품운반업191112.386673440500.995945식품운반업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
1831700003170000-117-2014-0000120140627<NA>3폐업2폐업20170720<NA><NA><NA><NA>52.50153863서울특별시 금천구 시흥동 ***-**번지 ***호서울특별시 금천구 시흥대로**길 **-*, ***호 (시흥동)8638힐프라자2017-07-20 16:01:48I2018-08-31 23:59:59.0식품운반업191307.004414438307.423372식품운반업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N4.2<NA><NA><NA>
1931700003170000-117-2015-0000120150604<NA>3폐업2폐업20170116<NA><NA><NA>022104669178.85153813서울특별시 금천구 독산동 ***-*번지 A동 ****호서울특별시 금천구 두산로 **, A동 ****호 (독산동, 현대지식산업센터)8584(주)하이스쿨푸드2015-06-04 16:27:25I2018-08-31 23:59:59.0식품운반업190694.880295440764.426278식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA>
2031700003170000-117-2016-0000120161209<NA>1영업/정상1영업<NA><NA><NA><NA>031 424 0781174.93153801서울특별시 금천구 가산동 **-** 벽산디지털밸리*차 ****호서울특별시 금천구 벚꽃로 ***, ****호 (가산동, 벽산디지털밸리*차)8513(주)케이알2022-02-09 14:15:51U2022-02-11 02:40:00.0식품운반업189829.504143441618.071647식품운반업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
2131700003170000-117-2017-0000120170320<NA>3폐업2폐업20170719<NA><NA><NA>02 2601990999.00153779서울특별시 금천구 가산동 ***-*번지 뉴티캐슬 ***호서울특별시 금천구 가산디지털*로 ***, ***호 (가산동, 뉴티캐슬)8506한솔운수(주)2017-07-19 16:10:44I2018-08-31 23:59:59.0식품운반업189364.09597441746.98153식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
2231700003170000-117-2018-0000120180309<NA>1영업/정상1영업<NA><NA><NA><NA>031 449 510031.90153030서울특별시 금천구 시흥동 **** 엠메디컬타워 지상**층 ****호서울특별시 금천구 시흥대로**길 **, 엠메디컬타워 지상**층 ****호 (시흥동)8613(주)대림종합운수2020-11-04 16:15:00U2020-11-06 02:40:00.0식품운반업<NA><NA>식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA>
2331700003170000-117-2019-0000120190701<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>153837서울특별시 금천구 시흥동 *-***번지 흥양주택서울특별시 금천구 독산로**마길 **, ***호 (시흥동, 흥양주택)8564지평로지스2019-07-01 13:28:32I2019-07-03 02:21:41.0식품운반업192147.806764439872.136913식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
2431700003170000-117-2019-000022019-08-28<NA>1영업/정상1영업<NA><NA><NA><NA>02 804 8802113.40153-030서울특별시 금천구 시흥동 ****서울특별시 금천구 시흥대로**길 **, ****호 (시흥동)8613(주)에스앤피로지스2023-04-14 09:43:25U2022-12-03 23:06:00.0식품운반업190718.37725439322.427424<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2531700003170000-117-2020-0000120200804<NA>1영업/정상1영업<NA><NA><NA><NA><NA>129.67153802서울특별시 금천구 가산동 ***-* 에이스하이엔드타워*차서울특별시 금천구 가산디지털*로 **, 에이스하이엔드타워*차 지하*층 ***호 (가산동)8590웃는아이2020-08-04 11:51:00I2020-08-06 00:23:14.0식품운반업189797.251808441250.271238식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA>
2631700003170000-117-2020-0000220200522<NA>1영업/정상1영업<NA><NA><NA><NA>02 805880587.48153803서울특별시 금천구 가산동 ***-*** 가산 더블유센터서울특별시 금천구 가산디지털*로 ***, 가산 더블유센터 ***호 (가산동)8503(주)신화종합물류2022-02-09 14:03:39U2022-02-11 02:40:00.0식품운반업189350.592435442143.206055식품운반업00<NA><NA><NA>00000임대00N0.0<NA><NA><NA>
2731700003170000-117-2022-0000120220419<NA>1영업/정상1영업<NA><NA><NA><NA>02866 203010.00153803서울특별시 금천구 가산동 *** 하우스디 더 스카이밸리 가산*차 ***(일부)호서울특별시 금천구 범안로 ****, 하우스디 더 스카이밸리 가산*차 ***(일부)호 (가산동)8595대동로지스 주식회사2022-04-19 10:20:16I2021-12-03 22:01:00.0식품운반업190099.411761440416.170973<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>