Overview

Dataset statistics

Number of variables44
Number of observations140
Missing cells1646
Missing cells (%)26.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory51.7 KiB
Average record size in memory377.9 B

Variable types

Numeric5
Text7
DateTime4
Unsupported9
Categorical18
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
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-16079/S/1/datasetView.do

Alerts

업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
급수시설구분명 is highly imbalanced (57.8%)Imbalance
건물소유구분명 is highly imbalanced (58.4%)Imbalance
인허가취소일자 has 140 (100.0%) missing valuesMissing
폐업일자 has 23 (16.4%) missing valuesMissing
휴업시작일자 has 140 (100.0%) missing valuesMissing
휴업종료일자 has 140 (100.0%) missing valuesMissing
재개업일자 has 140 (100.0%) missing valuesMissing
전화번호 has 35 (25.0%) missing valuesMissing
소재지면적 has 29 (20.7%) missing valuesMissing
소재지우편번호 has 21 (15.0%) missing valuesMissing
도로명주소 has 57 (40.7%) missing valuesMissing
도로명우편번호 has 57 (40.7%) missing valuesMissing
좌표정보(X) has 48 (34.3%) missing valuesMissing
좌표정보(Y) has 48 (34.3%) missing valuesMissing
영업장주변구분명 has 140 (100.0%) missing valuesMissing
등급구분명 has 140 (100.0%) missing valuesMissing
다중이용업소여부 has 34 (24.3%) missing valuesMissing
시설총규모 has 34 (24.3%) missing valuesMissing
전통업소지정번호 has 140 (100.0%) missing valuesMissing
전통업소주된음식 has 140 (100.0%) missing valuesMissing
홈페이지 has 140 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
영업장주변구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
등급구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
시설총규모 has 89 (63.6%) zerosZeros

Reproduction

Analysis started2024-05-11 08:37:18.878332
Analysis finished2024-05-11 08:37:20.621841
Duration1.74 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Real number (ℝ)

Distinct22
Distinct (%)15.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3147714.3
Minimum3010000
Maximum3240000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-05-11T08:37:20.923016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3010000
5-th percentile3030000
Q13130000
median3165000
Q33180000
95-th percentile3230000
Maximum3240000
Range230000
Interquartile range (IQR)50000

Descriptive statistics

Standard deviation53849.549
Coefficient of variation (CV)0.017107508
Kurtosis0.098051827
Mean3147714.3
Median Absolute Deviation (MAD)15000
Skewness-0.88125448
Sum4.4068 × 108
Variance2.8997739 × 109
MonotonicityNot monotonic
2024-05-11T08:37:21.449248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
3170000 32
22.9%
3180000 18
12.9%
3150000 17
12.1%
3160000 15
10.7%
3030000 9
 
6.4%
3230000 6
 
4.3%
3060000 5
 
3.6%
3090000 5
 
3.6%
3070000 3
 
2.1%
3190000 3
 
2.1%
Other values (12) 27
19.3%
ValueCountFrequency (%)
3010000 1
 
0.7%
3030000 9
6.4%
3040000 1
 
0.7%
3050000 2
 
1.4%
3060000 5
3.6%
3070000 3
 
2.1%
3080000 3
 
2.1%
3090000 5
3.6%
3110000 2
 
1.4%
3120000 3
 
2.1%
ValueCountFrequency (%)
3240000 2
 
1.4%
3230000 6
 
4.3%
3220000 3
 
2.1%
3210000 3
 
2.1%
3200000 3
 
2.1%
3190000 3
 
2.1%
3180000 18
12.9%
3170000 32
22.9%
3160000 15
10.7%
3150000 17
12.1%

관리번호
Text

UNIQUE 

Distinct140
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-05-11T08:37:22.211658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters3080
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

Unique140 ?
Unique (%)100.0%

Sample

1st row3170000-108-2011-00011
2nd row3150000-108-2023-00001
3rd row3180000-108-2011-00001
4th row3230000-108-2023-00001
5th row3150000-108-2018-00002
ValueCountFrequency (%)
3170000-108-2011-00011 1
 
0.7%
3170000-108-2016-00001 1
 
0.7%
3170000-108-2011-00001 1
 
0.7%
3170000-108-2011-00007 1
 
0.7%
3170000-108-2014-00002 1
 
0.7%
3170000-108-2014-00001 1
 
0.7%
3170000-108-2012-00001 1
 
0.7%
3170000-108-2011-00013 1
 
0.7%
3170000-108-2011-00012 1
 
0.7%
3180000-108-2011-00007 1
 
0.7%
Other values (130) 130
92.9%
2024-05-11T08:37:23.773888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1439
46.7%
1 506
 
16.4%
- 420
 
13.6%
2 231
 
7.5%
3 176
 
5.7%
8 171
 
5.6%
7 45
 
1.5%
5 37
 
1.2%
6 28
 
0.9%
4 17
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2660
86.4%
Dash Punctuation 420
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1439
54.1%
1 506
 
19.0%
2 231
 
8.7%
3 176
 
6.6%
8 171
 
6.4%
7 45
 
1.7%
5 37
 
1.4%
6 28
 
1.1%
4 17
 
0.6%
9 10
 
0.4%
Dash Punctuation
ValueCountFrequency (%)
- 420
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3080
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1439
46.7%
1 506
 
16.4%
- 420
 
13.6%
2 231
 
7.5%
3 176
 
5.7%
8 171
 
5.6%
7 45
 
1.5%
5 37
 
1.2%
6 28
 
0.9%
4 17
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3080
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1439
46.7%
1 506
 
16.4%
- 420
 
13.6%
2 231
 
7.5%
3 176
 
5.7%
8 171
 
5.6%
7 45
 
1.5%
5 37
 
1.2%
6 28
 
0.9%
4 17
 
0.6%
Distinct122
Distinct (%)87.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum1963-04-17 00:00:00
Maximum2024-04-03 00:00:00
2024-05-11T08:37:24.530469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:37:25.391900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing140
Missing (%)100.0%
Memory size1.4 KiB
Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
3
117 
1
23 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 117
83.6%
1 23
 
16.4%

Length

2024-05-11T08:37:26.045717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:37:26.399337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 117
83.6%
1 23
 
16.4%

영업상태명
Categorical

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
폐업
117 
영업/정상
23 

Length

Max length5
Median length2
Mean length2.4928571
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 117
83.6%
영업/정상 23
 
16.4%

Length

2024-05-11T08:37:26.852617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:37:27.253974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 117
83.6%
영업/정상 23
 
16.4%
Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2
117 
1
23 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 117
83.6%
1 23
 
16.4%

Length

2024-05-11T08:37:27.716316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:37:28.090082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 117
83.6%
1 23
 
16.4%
Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
폐업
117 
영업
23 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 117
83.6%
영업 23
 
16.4%

Length

2024-05-11T08:37:28.476959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:37:29.012879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 117
83.6%
영업 23
 
16.4%

폐업일자
Date

MISSING 

Distinct98
Distinct (%)83.8%
Missing23
Missing (%)16.4%
Memory size1.2 KiB
Minimum1998-04-03 00:00:00
Maximum2024-04-18 00:00:00
2024-05-11T08:37:29.502481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:37:29.959660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing140
Missing (%)100.0%
Memory size1.4 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing140
Missing (%)100.0%
Memory size1.4 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing140
Missing (%)100.0%
Memory size1.4 KiB

전화번호
Text

MISSING 

Distinct94
Distinct (%)89.5%
Missing35
Missing (%)25.0%
Memory size1.2 KiB
2024-05-11T08:37:30.561683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.07619
Min length8

Characters and Unicode

Total characters1058
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

Unique87 ?
Unique (%)82.9%

Sample

1st row02 703 2411
2nd row0226706678
3rd row0269569858
4th row02 948 1980
5th row027518144
ValueCountFrequency (%)
02 19
 
13.5%
070 10
 
7.1%
028049028 4
 
2.8%
023688251 3
 
2.1%
026336694 3
 
2.1%
028540401 2
 
1.4%
022209575 2
 
1.4%
024356111 2
 
1.4%
026344221 2
 
1.4%
62943303 1
 
0.7%
Other values (93) 93
66.0%
2024-05-11T08:37:31.862530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 206
19.5%
2 170
16.1%
8 98
9.3%
6 85
8.0%
1 85
8.0%
3 84
7.9%
7 79
 
7.5%
5 69
 
6.5%
4 68
 
6.4%
9 61
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1005
95.0%
Space Separator 53
 
5.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 206
20.5%
2 170
16.9%
8 98
9.8%
6 85
8.5%
1 85
8.5%
3 84
8.4%
7 79
 
7.9%
5 69
 
6.9%
4 68
 
6.8%
9 61
 
6.1%
Space Separator
ValueCountFrequency (%)
53
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1058
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 206
19.5%
2 170
16.1%
8 98
9.3%
6 85
8.0%
1 85
8.0%
3 84
7.9%
7 79
 
7.5%
5 69
 
6.5%
4 68
 
6.4%
9 61
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1058
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 206
19.5%
2 170
16.1%
8 98
9.3%
6 85
8.0%
1 85
8.0%
3 84
7.9%
7 79
 
7.5%
5 69
 
6.5%
4 68
 
6.4%
9 61
 
5.8%

소재지면적
Text

MISSING 

Distinct108
Distinct (%)97.3%
Missing29
Missing (%)20.7%
Memory size1.2 KiB
2024-05-11T08:37:32.672724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length5.5225225
Min length3

Characters and Unicode

Total characters613
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

Unique106 ?
Unique (%)95.5%

Sample

1st row268.59
2nd row146.16
3rd row2264.00
4th row37.35
5th row95.86
ValueCountFrequency (%)
00 3
 
2.7%
30.00 2
 
1.8%
120.00 1
 
0.9%
268.59 1
 
0.9%
67.26 1
 
0.9%
79.42 1
 
0.9%
114.61 1
 
0.9%
93.52 1
 
0.9%
29.52 1
 
0.9%
1795.22 1
 
0.9%
Other values (98) 98
88.3%
2024-05-11T08:37:34.085442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 111
18.1%
0 90
14.7%
1 76
12.4%
2 61
10.0%
4 47
7.7%
3 46
7.5%
5 44
 
7.2%
8 38
 
6.2%
6 37
 
6.0%
7 30
 
4.9%
Other values (2) 33
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 496
80.9%
Other Punctuation 117
 
19.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 90
18.1%
1 76
15.3%
2 61
12.3%
4 47
9.5%
3 46
9.3%
5 44
8.9%
8 38
7.7%
6 37
7.5%
7 30
 
6.0%
9 27
 
5.4%
Other Punctuation
ValueCountFrequency (%)
. 111
94.9%
, 6
 
5.1%

Most occurring scripts

ValueCountFrequency (%)
Common 613
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 111
18.1%
0 90
14.7%
1 76
12.4%
2 61
10.0%
4 47
7.7%
3 46
7.5%
5 44
 
7.2%
8 38
 
6.2%
6 37
 
6.0%
7 30
 
4.9%
Other values (2) 33
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 613
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 111
18.1%
0 90
14.7%
1 76
12.4%
2 61
10.0%
4 47
7.7%
3 46
7.5%
5 44
 
7.2%
8 38
 
6.2%
6 37
 
6.0%
7 30
 
4.9%
Other values (2) 33
 
5.4%

소재지우편번호
Text

MISSING 

Distinct91
Distinct (%)76.5%
Missing21
Missing (%)15.0%
Memory size1.2 KiB
2024-05-11T08:37:34.849407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1848739
Min length6

Characters and Unicode

Total characters736
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

Unique82 ?
Unique (%)68.9%

Sample

1st row153-776
2nd row157-838
3rd row150-866
4th row138-850
5th row157-851
ValueCountFrequency (%)
153803 10
 
8.4%
153802 6
 
5.0%
152848 6
 
5.0%
157200 4
 
3.4%
153-803 3
 
2.5%
153023 2
 
1.7%
150095 2
 
1.7%
133832 2
 
1.7%
157801 2
 
1.7%
138828 1
 
0.8%
Other values (81) 81
68.1%
2024-05-11T08:37:36.252173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 151
20.5%
8 124
16.8%
5 99
13.5%
3 98
13.3%
0 82
11.1%
2 56
 
7.6%
7 36
 
4.9%
4 31
 
4.2%
6 24
 
3.3%
- 22
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 714
97.0%
Dash Punctuation 22
 
3.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 151
21.1%
8 124
17.4%
5 99
13.9%
3 98
13.7%
0 82
11.5%
2 56
 
7.8%
7 36
 
5.0%
4 31
 
4.3%
6 24
 
3.4%
9 13
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 736
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 151
20.5%
8 124
16.8%
5 99
13.5%
3 98
13.3%
0 82
11.1%
2 56
 
7.6%
7 36
 
4.9%
4 31
 
4.2%
6 24
 
3.3%
- 22
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 736
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 151
20.5%
8 124
16.8%
5 99
13.5%
3 98
13.3%
0 82
11.1%
2 56
 
7.6%
7 36
 
4.9%
4 31
 
4.2%
6 24
 
3.3%
- 22
 
3.0%
Distinct124
Distinct (%)88.6%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-05-11T08:37:37.442974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length37
Mean length24.7
Min length11

Characters and Unicode

Total characters3458
Distinct characters194
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

Unique117 ?
Unique (%)83.6%

Sample

1st row서울특별시 금천구 가산동 680 우림라이온스밸리2차 1006호
2nd row서울특별시 강서구 등촌동 629-1
3rd row서울특별시 영등포구 양평동4가 19
4th row서울특별시 송파구 송파동 84-2 평화빌딩 3층
5th row서울특별시 강서구 방화동 597-31 삼광빌딩
ValueCountFrequency (%)
서울특별시 140
 
21.5%
금천구 32
 
4.9%
가산동 25
 
3.8%
영등포구 18
 
2.8%
강서구 17
 
2.6%
번지 16
 
2.5%
구로구 15
 
2.3%
성동구 9
 
1.4%
구로동 8
 
1.2%
가양동 7
 
1.1%
Other values (284) 363
55.8%
2024-05-11T08:37:39.441974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
650
18.8%
163
 
4.7%
163
 
4.7%
143
 
4.1%
143
 
4.1%
140
 
4.0%
140
 
4.0%
140
 
4.0%
1 139
 
4.0%
2 103
 
3.0%
Other values (184) 1534
44.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2086
60.3%
Space Separator 650
 
18.8%
Decimal Number 611
 
17.7%
Dash Punctuation 93
 
2.7%
Uppercase Letter 12
 
0.3%
Other Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
163
 
7.8%
163
 
7.8%
143
 
6.9%
143
 
6.9%
140
 
6.7%
140
 
6.7%
140
 
6.7%
82
 
3.9%
69
 
3.3%
59
 
2.8%
Other values (162) 844
40.5%
Decimal Number
ValueCountFrequency (%)
1 139
22.7%
2 103
16.9%
0 58
9.5%
4 51
 
8.3%
6 51
 
8.3%
5 47
 
7.7%
3 45
 
7.4%
7 44
 
7.2%
9 39
 
6.4%
8 34
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
K 3
25.0%
B 2
16.7%
S 2
16.7%
A 2
16.7%
T 1
 
8.3%
I 1
 
8.3%
M 1
 
8.3%
Space Separator
ValueCountFrequency (%)
650
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 93
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2086
60.3%
Common 1360
39.3%
Latin 12
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
163
 
7.8%
163
 
7.8%
143
 
6.9%
143
 
6.9%
140
 
6.7%
140
 
6.7%
140
 
6.7%
82
 
3.9%
69
 
3.3%
59
 
2.8%
Other values (162) 844
40.5%
Common
ValueCountFrequency (%)
650
47.8%
1 139
 
10.2%
2 103
 
7.6%
- 93
 
6.8%
0 58
 
4.3%
4 51
 
3.8%
6 51
 
3.8%
5 47
 
3.5%
3 45
 
3.3%
7 44
 
3.2%
Other values (5) 79
 
5.8%
Latin
ValueCountFrequency (%)
K 3
25.0%
B 2
16.7%
S 2
16.7%
A 2
16.7%
T 1
 
8.3%
I 1
 
8.3%
M 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2086
60.3%
ASCII 1372
39.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
650
47.4%
1 139
 
10.1%
2 103
 
7.5%
- 93
 
6.8%
0 58
 
4.2%
4 51
 
3.7%
6 51
 
3.7%
5 47
 
3.4%
3 45
 
3.3%
7 44
 
3.2%
Other values (12) 91
 
6.6%
Hangul
ValueCountFrequency (%)
163
 
7.8%
163
 
7.8%
143
 
6.9%
143
 
6.9%
140
 
6.7%
140
 
6.7%
140
 
6.7%
82
 
3.9%
69
 
3.3%
59
 
2.8%
Other values (162) 844
40.5%

도로명주소
Text

MISSING 

Distinct83
Distinct (%)100.0%
Missing57
Missing (%)40.7%
Memory size1.2 KiB
2024-05-11T08:37:40.529835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length44
Mean length37.807229
Min length22

Characters and Unicode

Total characters3138
Distinct characters215
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique83 ?
Unique (%)100.0%

Sample

1st row서울특별시 금천구 가산디지털1로 2-0, 1006호 (가산동, 우림라이온스밸리 2차)
2nd row서울특별시 강서구 양천로 532, 1508호~1510호 (등촌동)
3rd row서울특별시 영등포구 양평로21길 25 (양평동4가)
4th row서울특별시 송파구 백제고분로 384, 평화빌딩 3층 (송파동)
5th row서울특별시 강서구 금낭화로 31, 삼광빌딩 3층 (방화동)
ValueCountFrequency (%)
서울특별시 83
 
14.4%
금천구 22
 
3.8%
가산동 18
 
3.1%
강서구 10
 
1.7%
구로구 9
 
1.6%
2층 9
 
1.6%
영등포구 9
 
1.6%
1층 8
 
1.4%
가산디지털1로 8
 
1.4%
구로동 5
 
0.9%
Other values (324) 394
68.5%
2024-05-11T08:37:42.326979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
492
 
15.7%
1 164
 
5.2%
105
 
3.3%
, 102
 
3.3%
99
 
3.2%
98
 
3.1%
96
 
3.1%
89
 
2.8%
2 88
 
2.8%
) 85
 
2.7%
Other values (205) 1720
54.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1784
56.9%
Decimal Number 547
 
17.4%
Space Separator 492
 
15.7%
Other Punctuation 103
 
3.3%
Close Punctuation 85
 
2.7%
Open Punctuation 85
 
2.7%
Uppercase Letter 22
 
0.7%
Dash Punctuation 19
 
0.6%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
105
 
5.9%
99
 
5.5%
98
 
5.5%
96
 
5.4%
89
 
5.0%
84
 
4.7%
83
 
4.7%
83
 
4.7%
56
 
3.1%
52
 
2.9%
Other values (181) 939
52.6%
Decimal Number
ValueCountFrequency (%)
1 164
30.0%
2 88
16.1%
0 60
 
11.0%
5 42
 
7.7%
4 39
 
7.1%
3 38
 
6.9%
6 35
 
6.4%
8 35
 
6.4%
7 25
 
4.6%
9 21
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
B 8
36.4%
A 4
18.2%
K 3
 
13.6%
I 2
 
9.1%
T 2
 
9.1%
S 2
 
9.1%
M 1
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 102
99.0%
. 1
 
1.0%
Space Separator
ValueCountFrequency (%)
492
100.0%
Close Punctuation
ValueCountFrequency (%)
) 85
100.0%
Open Punctuation
ValueCountFrequency (%)
( 85
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1784
56.9%
Common 1332
42.4%
Latin 22
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
105
 
5.9%
99
 
5.5%
98
 
5.5%
96
 
5.4%
89
 
5.0%
84
 
4.7%
83
 
4.7%
83
 
4.7%
56
 
3.1%
52
 
2.9%
Other values (181) 939
52.6%
Common
ValueCountFrequency (%)
492
36.9%
1 164
 
12.3%
, 102
 
7.7%
2 88
 
6.6%
) 85
 
6.4%
( 85
 
6.4%
0 60
 
4.5%
5 42
 
3.2%
4 39
 
2.9%
3 38
 
2.9%
Other values (7) 137
 
10.3%
Latin
ValueCountFrequency (%)
B 8
36.4%
A 4
18.2%
K 3
 
13.6%
I 2
 
9.1%
T 2
 
9.1%
S 2
 
9.1%
M 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1784
56.9%
ASCII 1354
43.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
492
36.3%
1 164
 
12.1%
, 102
 
7.5%
2 88
 
6.5%
) 85
 
6.3%
( 85
 
6.3%
0 60
 
4.4%
5 42
 
3.1%
4 39
 
2.9%
3 38
 
2.8%
Other values (14) 159
 
11.7%
Hangul
ValueCountFrequency (%)
105
 
5.9%
99
 
5.5%
98
 
5.5%
96
 
5.4%
89
 
5.0%
84
 
4.7%
83
 
4.7%
83
 
4.7%
56
 
3.1%
52
 
2.9%
Other values (181) 939
52.6%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct71
Distinct (%)85.5%
Missing57
Missing (%)40.7%
Infinite0
Infinite (%)0.0%
Mean6806.0482
Minimum1070
Maximum8863
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-05-11T08:37:42.737423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1070
5-th percentile2011.5
Q15654.5
median7605
Q38502.5
95-th percentile8631
Maximum8863
Range7793
Interquartile range (IQR)2848

Descriptive statistics

Standard deviation2206.7953
Coefficient of variation (CV)0.32424032
Kurtosis0.74018922
Mean6806.0482
Median Absolute Deviation (MAD)902
Skewness-1.3379986
Sum564902
Variance4869945.3
MonotonicityNot monotonic
2024-05-11T08:37:43.275966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8592 4
 
2.9%
8506 4
 
2.9%
8501 4
 
2.9%
1070 2
 
1.4%
8381 2
 
1.4%
8635 2
 
1.4%
8375 1
 
0.7%
8390 1
 
0.7%
8301 1
 
0.7%
7205 1
 
0.7%
Other values (61) 61
43.6%
(Missing) 57
40.7%
ValueCountFrequency (%)
1070 2
1.4%
1100 1
0.7%
1414 1
0.7%
2008 1
0.7%
2043 1
0.7%
2094 1
0.7%
2568 1
0.7%
2718 1
0.7%
2785 1
0.7%
3963 1
0.7%
ValueCountFrequency (%)
8863 1
 
0.7%
8860 1
 
0.7%
8858 1
 
0.7%
8635 2
1.4%
8595 1
 
0.7%
8592 4
2.9%
8591 1
 
0.7%
8589 1
 
0.7%
8584 1
 
0.7%
8517 1
 
0.7%
Distinct125
Distinct (%)89.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-05-11T08:37:44.132859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length13
Mean length7.5285714
Min length2

Characters and Unicode

Total characters1054
Distinct characters229
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique115 ?
Unique (%)82.1%

Sample

1st row케이피씨
2nd row주식회사 퓨어
3rd row롯데웰푸드(주)
4th row주식회사 르빵
5th row주식회사 디오빈스
ValueCountFrequency (%)
주식회사 18
 
10.9%
대상(주 4
 
2.4%
주)대상 3
 
1.8%
주)원지산업 3
 
1.8%
롯데제과(주 3
 
1.8%
푸드아로마 2
 
1.2%
제니코식품(주 2
 
1.2%
주)롯데삼강 2
 
1.2%
케이에프티씨 2
 
1.2%
서울우유협동조합 2
 
1.2%
Other values (123) 124
75.2%
2024-05-11T08:37:46.028138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
84
 
8.0%
( 67
 
6.4%
) 67
 
6.4%
44
 
4.2%
32
 
3.0%
29
 
2.8%
26
 
2.5%
25
 
2.4%
22
 
2.1%
20
 
1.9%
Other values (219) 638
60.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 860
81.6%
Open Punctuation 67
 
6.4%
Close Punctuation 67
 
6.4%
Space Separator 25
 
2.4%
Uppercase Letter 17
 
1.6%
Lowercase Letter 12
 
1.1%
Connector Punctuation 2
 
0.2%
Other Punctuation 2
 
0.2%
Decimal Number 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
84
 
9.8%
44
 
5.1%
32
 
3.7%
29
 
3.4%
26
 
3.0%
22
 
2.6%
20
 
2.3%
19
 
2.2%
17
 
2.0%
15
 
1.7%
Other values (192) 552
64.2%
Uppercase Letter
ValueCountFrequency (%)
T 4
23.5%
C 4
23.5%
A 1
 
5.9%
H 1
 
5.9%
O 1
 
5.9%
L 1
 
5.9%
J 1
 
5.9%
S 1
 
5.9%
E 1
 
5.9%
K 1
 
5.9%
Lowercase Letter
ValueCountFrequency (%)
r 3
25.0%
a 2
16.7%
p 1
 
8.3%
o 1
 
8.3%
g 1
 
8.3%
i 1
 
8.3%
n 1
 
8.3%
e 1
 
8.3%
k 1
 
8.3%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 67
100.0%
Close Punctuation
ValueCountFrequency (%)
) 67
100.0%
Space Separator
ValueCountFrequency (%)
25
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 860
81.6%
Common 165
 
15.7%
Latin 29
 
2.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
84
 
9.8%
44
 
5.1%
32
 
3.7%
29
 
3.4%
26
 
3.0%
22
 
2.6%
20
 
2.3%
19
 
2.2%
17
 
2.0%
15
 
1.7%
Other values (192) 552
64.2%
Latin
ValueCountFrequency (%)
T 4
 
13.8%
C 4
 
13.8%
r 3
 
10.3%
a 2
 
6.9%
p 1
 
3.4%
o 1
 
3.4%
g 1
 
3.4%
i 1
 
3.4%
A 1
 
3.4%
H 1
 
3.4%
Other values (10) 10
34.5%
Common
ValueCountFrequency (%)
( 67
40.6%
) 67
40.6%
25
 
15.2%
_ 2
 
1.2%
. 2
 
1.2%
2 1
 
0.6%
1 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 860
81.6%
ASCII 194
 
18.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
84
 
9.8%
44
 
5.1%
32
 
3.7%
29
 
3.4%
26
 
3.0%
22
 
2.6%
20
 
2.3%
19
 
2.2%
17
 
2.0%
15
 
1.7%
Other values (192) 552
64.2%
ASCII
ValueCountFrequency (%)
( 67
34.5%
) 67
34.5%
25
 
12.9%
T 4
 
2.1%
C 4
 
2.1%
r 3
 
1.5%
_ 2
 
1.0%
. 2
 
1.0%
a 2
 
1.0%
p 1
 
0.5%
Other values (17) 17
 
8.8%
Distinct110
Distinct (%)78.6%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum2006-08-18 22:29:41
Maximum2024-04-18 13:39:07
2024-05-11T08:37:46.638986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:37:47.263387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
I
93 
U
47 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 93
66.4%
U 47
33.6%

Length

2024-05-11T08:37:47.861928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:37:48.266973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 93
66.4%
u 47
33.6%
Distinct55
Distinct (%)39.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:05:00
2024-05-11T08:37:48.642918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:37:49.202777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
식품첨가물제조업
140 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품첨가물제조업 140
100.0%

Length

2024-05-11T08:37:49.798562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:37:50.176068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품첨가물제조업 140
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct85
Distinct (%)92.4%
Missing48
Missing (%)34.3%
Infinite0
Infinite (%)0.0%
Mean194485.7
Minimum183278.12
Maximum213070.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-05-11T08:37:50.565722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum183278.12
5-th percentile184188.37
Q1189369.54
median190477.92
Q3202261.63
95-th percentile209520.71
Maximum213070.5
Range29792.374
Interquartile range (IQR)12892.089

Descriptive statistics

Standard deviation8177.4585
Coefficient of variation (CV)0.04204658
Kurtosis-0.8399468
Mean194485.7
Median Absolute Deviation (MAD)2807.125
Skewness0.76030187
Sum17892684
Variance66870828
MonotonicityNot monotonic
2024-05-11T08:37:51.074296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
189369.53962474 3
 
2.1%
189812.421197411 3
 
2.1%
189232.30642848 2
 
1.4%
201974.958688991 2
 
1.4%
189089.927764903 2
 
1.4%
189978.050925581 1
 
0.7%
189575.815287955 1
 
0.7%
188968.189711073 1
 
0.7%
191217.502722028 1
 
0.7%
189127.981104583 1
 
0.7%
Other values (75) 75
53.6%
(Missing) 48
34.3%
ValueCountFrequency (%)
183278.121362815 1
0.7%
183621.112641016 1
0.7%
183664.577761335 1
0.7%
183676.676699478 1
0.7%
183717.389594075 1
0.7%
184573.723475124 1
0.7%
186108.118527493 1
0.7%
186380.509205927 1
0.7%
186700.342736365 1
0.7%
186723.502831215 1
0.7%
ValueCountFrequency (%)
213070.495037105 1
0.7%
210753.037585195 1
0.7%
210627.0 1
0.7%
210078.558889886 1
0.7%
209549.864184816 1
0.7%
209496.859211168 1
0.7%
209038.198426983 1
0.7%
208231.356512091 1
0.7%
208072.625904312 1
0.7%
207157.192115985 1
0.7%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct85
Distinct (%)92.4%
Missing48
Missing (%)34.3%
Infinite0
Infinite (%)0.0%
Mean446511.45
Minimum438683.88
Maximum462924.42
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-05-11T08:37:51.713291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum438683.88
5-th percentile440432.68
Q1441985.53
median445218.81
Q3450354.96
95-th percentile457318.2
Maximum462924.42
Range24240.545
Interquartile range (IQR)8369.4281

Descriptive statistics

Standard deviation5662.6045
Coefficient of variation (CV)0.01268188
Kurtosis0.18766745
Mean446511.45
Median Absolute Deviation (MAD)3589.4534
Skewness0.92886769
Sum41079053
Variance32065090
MonotonicityNot monotonic
2024-05-11T08:37:52.269601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
441629.361414684 3
 
2.1%
440866.434242768 3
 
2.1%
442478.356256941 2
 
1.4%
459917.064973621 2
 
1.4%
442569.300676147 2
 
1.4%
440363.954453659 1
 
0.7%
441503.181731081 1
 
0.7%
442119.780901928 1
 
0.7%
438683.876519238 1
 
0.7%
442460.505542105 1
 
0.7%
Other values (75) 75
53.6%
(Missing) 48
34.3%
ValueCountFrequency (%)
438683.876519238 1
 
0.7%
438765.406099377 1
 
0.7%
439810.25559883 1
 
0.7%
440263.768319604 1
 
0.7%
440363.954453659 1
 
0.7%
440488.915356426 1
 
0.7%
440523.497478209 1
 
0.7%
440764.426277932 1
 
0.7%
440866.434242768 3
2.1%
440870.092608694 1
 
0.7%
ValueCountFrequency (%)
462924.421741165 1
0.7%
461119.957690091 1
0.7%
459917.064973621 2
1.4%
458704.862300894 1
0.7%
456183.667189931 1
0.7%
456138.417214882 1
0.7%
456108.815873556 1
0.7%
455821.617180441 1
0.7%
455262.351193571 1
0.7%
454281.625467611 1
0.7%

위생업태명
Categorical

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
식품첨가물제조업
106 
<NA>
34 

Length

Max length8
Median length8
Mean length7.0285714
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 (%)
식품첨가물제조업 106
75.7%
<NA> 34
 
24.3%

Length

2024-05-11T08:37:52.760758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:37:53.364921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품첨가물제조업 106
75.7%
na 34
 
24.3%
Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
123 
0
17 

Length

Max length4
Median length4
Mean length3.6357143
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 123
87.9%
0 17
 
12.1%

Length

2024-05-11T08:37:53.821702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:37:54.164909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 123
87.9%
0 17
 
12.1%
Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
123 
0
17 

Length

Max length4
Median length4
Mean length3.6357143
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 123
87.9%
0 17
 
12.1%

Length

2024-05-11T08:37:54.545107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:37:54.915431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 123
87.9%
0 17
 
12.1%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing140
Missing (%)100.0%
Memory size1.4 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing140
Missing (%)100.0%
Memory size1.4 KiB

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
128 
상수도전용
 
12

Length

Max length5
Median length4
Mean length4.0857143
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> 128
91.4%
상수도전용 12
 
8.6%

Length

2024-05-11T08:37:55.283362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:37:55.595003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 128
91.4%
상수도전용 12
 
8.6%

총인원
Categorical

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
123 
0
17 

Length

Max length4
Median length4
Mean length3.6357143
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 123
87.9%
0 17
 
12.1%

Length

2024-05-11T08:37:55.955078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:37:56.440683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 123
87.9%
0 17
 
12.1%
Distinct5
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
74 
0
62 
1
 
2
3
 
1
4
 
1

Length

Max length4
Median length4
Mean length2.5857143
Min length1

Unique

Unique2 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 74
52.9%
0 62
44.3%
1 2
 
1.4%
3 1
 
0.7%
4 1
 
0.7%

Length

2024-05-11T08:37:56.834000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:37:57.203813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 74
52.9%
0 62
44.3%
1 2
 
1.4%
3 1
 
0.7%
4 1
 
0.7%
Distinct3
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
74 
0
65 
2
 
1

Length

Max length4
Median length4
Mean length2.5857143
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 74
52.9%
0 65
46.4%
2 1
 
0.7%

Length

2024-05-11T08:37:57.634633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:37:57.963074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 74
52.9%
0 65
46.4%
2 1
 
0.7%
Distinct3
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
74 
0
65 
1
 
1

Length

Max length4
Median length4
Mean length2.5857143
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 74
52.9%
0 65
46.4%
1 1
 
0.7%

Length

2024-05-11T08:37:58.351223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:37:58.748702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 74
52.9%
0 65
46.4%
1 1
 
0.7%
Distinct3
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
73 
0
65 
1
 
2

Length

Max length4
Median length4
Mean length2.5642857
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 73
52.1%
0 65
46.4%
1 2
 
1.4%

Length

2024-05-11T08:37:59.123856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:37:59.684437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 73
52.1%
0 65
46.4%
1 2
 
1.4%

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
120 
임대
18 
자가
 
2

Length

Max length4
Median length4
Mean length3.7142857
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> 120
85.7%
임대 18
 
12.9%
자가 2
 
1.4%

Length

2024-05-11T08:38:00.129874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:38:00.527707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 120
85.7%
임대 18
 
12.9%
자가 2
 
1.4%

보증액
Categorical

Distinct4
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
90 
0
48 
1100
 
1
100000000
 
1

Length

Max length9
Median length4
Mean length3.0071429
Min length1

Unique

Unique2 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 90
64.3%
0 48
34.3%
1100 1
 
0.7%
100000000 1
 
0.7%

Length

2024-05-11T08:38:00.916897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:38:01.286958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 90
64.3%
0 48
34.3%
1100 1
 
0.7%
100000000 1
 
0.7%

월세액
Categorical

Distinct4
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
90 
0
48 
110
 
1
10780000
 
1

Length

Max length8
Median length4
Mean length2.9928571
Min length1

Unique

Unique2 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 90
64.3%
0 48
34.3%
110 1
 
0.7%
10780000 1
 
0.7%

Length

2024-05-11T08:38:01.634210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:38:01.885225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 90
64.3%
0 48
34.3%
110 1
 
0.7%
10780000 1
 
0.7%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.9%
Missing34
Missing (%)24.3%
Memory size412.0 B
False
106 
(Missing)
34 
ValueCountFrequency (%)
False 106
75.7%
(Missing) 34
 
24.3%
2024-05-11T08:38:02.090023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct18
Distinct (%)17.0%
Missing34
Missing (%)24.3%
Infinite0
Infinite (%)0.0%
Mean6.2422642
Minimum0
Maximum98.82
Zeros89
Zeros (%)63.6%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-05-11T08:38:02.391078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile50.4825
Maximum98.82
Range98.82
Interquartile range (IQR)0

Descriptive statistics

Standard deviation18.734069
Coefficient of variation (CV)3.0011657
Kurtosis11.296497
Mean6.2422642
Median Absolute Deviation (MAD)0
Skewness3.4034957
Sum661.68
Variance350.96535
MonotonicityNot monotonic
2024-05-11T08:38:02.777857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0.0 89
63.6%
72.21 1
 
0.7%
14.25 1
 
0.7%
62.76 1
 
0.7%
29.7 1
 
0.7%
33.21 1
 
0.7%
12.4 1
 
0.7%
29.52 1
 
0.7%
81.85 1
 
0.7%
24.37 1
 
0.7%
Other values (8) 8
 
5.7%
(Missing) 34
 
24.3%
ValueCountFrequency (%)
0.0 89
63.6%
1.86 1
 
0.7%
3.0 1
 
0.7%
8.0 1
 
0.7%
12.0 1
 
0.7%
12.4 1
 
0.7%
14.25 1
 
0.7%
24.37 1
 
0.7%
29.52 1
 
0.7%
29.7 1
 
0.7%
ValueCountFrequency (%)
98.82 1
0.7%
81.85 1
0.7%
81.72 1
0.7%
72.21 1
0.7%
62.76 1
0.7%
52.96 1
0.7%
43.05 1
0.7%
33.21 1
0.7%
29.7 1
0.7%
29.52 1
0.7%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing140
Missing (%)100.0%
Memory size1.4 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing140
Missing (%)100.0%
Memory size1.4 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing140
Missing (%)100.0%
Memory size1.4 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031700003170000-108-2011-000112006-12-05<NA>3폐업2폐업2023-07-17<NA><NA><NA>02 703 2411268.59153-776서울특별시 금천구 가산동 680 우림라이온스밸리2차 1006호서울특별시 금천구 가산디지털1로 2-0, 1006호 (가산동, 우림라이온스밸리 2차)8591케이피씨2023-07-17 13:47:48U2022-12-06 23:09:00.0식품첨가물제조업190050.903573440523.497478<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
131500003150000-108-2023-000012023-08-14<NA>1영업/정상1영업<NA><NA><NA><NA><NA>146.16157-838서울특별시 강서구 등촌동 629-1서울특별시 강서구 양천로 532, 1508호~1510호 (등촌동)7549주식회사 퓨어2023-08-14 09:33:37I2022-12-07 23:07:00.0식품첨가물제조업187381.316534450751.226504<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
231800003180000-108-2011-000011971-02-24<NA>1영업/정상1영업<NA><NA><NA><NA>02267066782264.00150-866서울특별시 영등포구 양평동4가 19서울특별시 영등포구 양평로21길 25 (양평동4가)7209롯데웰푸드(주)2023-04-20 11:38:51U2022-12-03 22:03:00.0식품첨가물제조업190508.589813448196.897432<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
332300003230000-108-2023-000012023-05-10<NA>1영업/정상1영업<NA><NA><NA><NA><NA>37.35138-850서울특별시 송파구 송파동 84-2 평화빌딩 3층서울특별시 송파구 백제고분로 384, 평화빌딩 3층 (송파동)5667주식회사 르빵2023-05-10 10:45:52I2022-12-04 23:02:00.0식품첨가물제조업209549.864185444844.574391<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
431500003150000-108-2018-000022018-02-27<NA>3폐업2폐업2023-05-31<NA><NA><NA><NA>95.86157-851서울특별시 강서구 방화동 597-31 삼광빌딩서울특별시 강서구 금낭화로 31, 삼광빌딩 3층 (방화동)7608주식회사 디오빈스2023-05-31 10:38:27U2022-12-06 00:02:00.0식품첨가물제조업183278.121363451786.08276<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
531700003170000-108-2023-000012023-07-06<NA>1영업/정상1영업<NA><NA><NA><NA><NA>40.80153-803서울특별시 금천구 가산동 371-57 가산 더스카이밸리 1차서울특별시 금천구 가산디지털1로 142, 가산 더스카이밸리 1차 514호 (가산동)8507씨엘오투(CLO2)2023-07-06 13:14:21I2022-12-07 00:08:00.0식품첨가물제조업189603.222917441801.135064<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
631300003130000-108-2023-000012023-12-08<NA>1영업/정상1영업<NA><NA><NA><NA>026956985824.60121-827서울특별시 마포구 망원동 478-11서울특별시 마포구 월드컵로 125, 4층 (망원동)3963(주)코리아허니2023-12-09 11:43:31I2022-11-01 23:01:00.0식품첨가물제조업191685.79278450778.221421<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
730800003080000-108-2017-000012017-05-30<NA>1영업/정상1영업<NA><NA><NA><NA>02 948 198019.50142-847서울특별시 강북구 수유동 220-70서울특별시 강북구 한천로143길 34-21, 2층 (수유동)1070주식회사 대성씨엔에프2023-08-25 17:34:44U2022-12-07 22:07:00.0식품첨가물제조업201974.958689459917.064974<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
830100003010000-108-2011-0000119680305<NA>3폐업2폐업20041231<NA><NA><NA>027518144<NA>100865서울특별시 중구 태평로2가 150번지<NA><NA>씨제이(CJ)주식회사2008-04-23 18:00:02I2018-08-31 23:59:59.0식품첨가물제조업197728.372837451030.853937식품첨가물제조업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
930300003030000-108-2011-0000319681007<NA>3폐업2폐업20030414<NA><NA><NA>024634104773.30133831서울특별시 성동구 성수동2가 275-36 번지<NA><NA>(주)삼풍식연2006-08-18 22:29:41I2018-08-31 23:59:59.0식품첨가물제조업<NA><NA>식품첨가물제조업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
13032300003230000-108-2011-0000119971101<NA>3폐업2폐업20060602<NA><NA><NA>024164391<NA><NA>서울특별시 송파구<NA><NA>극동와인(주)2006-08-18 22:29:41I2018-08-31 23:59:59.0식품첨가물제조업<NA><NA>식품첨가물제조업<NA><NA><NA><NA><NA><NA>0000<NA>00N0.0<NA><NA><NA>
13132300003230000-108-2018-0000120180816<NA>1영업/정상1영업<NA><NA><NA><NA><NA>74.00138888서울특별시 송파구 문정동 642번지 송파 테라타워2서울특별시 송파구 송파대로 201, 송파 테라타워2 A동 610호 (문정동)5854인센트랩2018-08-16 09:39:17I2018-08-31 23:59:59.0식품첨가물제조업210627.0442875.0식품첨가물제조업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
13232400003240000-108-2015-0000220150804<NA>3폐업2폐업20190527<NA><NA><NA>070 8875796630.00134851서울특별시 강동구 성내동 556번지 다모아빌딩, 2층 201호서울특별시 강동구 성내로6길 14-5, 2층 201호 (성내동, 다모아빌딩)5398웰튼헬스케어2019-05-27 17:22:45U2019-05-29 02:40:00.0식품첨가물제조업210753.037585447466.691105식품첨가물제조업<NA><NA><NA><NA><NA><NA>1000임대<NA><NA>N0.0<NA><NA><NA>
13332400003240000-108-2015-0000120150701<NA>3폐업2폐업20160119<NA><NA><NA><NA>16.35134809서울특별시 강동구 길동 160번지서울특별시 강동구 천중로 254, 1층 11호 (길동)5346브레쓰아트2015-07-03 13:33:14I2018-08-31 23:59:59.0식품첨가물제조업213070.495037448552.74791식품첨가물제조업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>임대<NA><NA>N0.0<NA><NA><NA>
13431800003180000-108-2018-0000120180404<NA>3폐업2폐업20221230<NA><NA><NA>0264033388136.90150095서울특별시 영등포구 문래동5가 23-5 문래동 빅토리 테크노 타워서울특별시 영등포구 선유서로 17, 문래동 빅토리 테크노 타워 1층 (문래동5가)7284(주)바이오믹스테크2022-12-30 13:40:29U2022-12-01 00:01:00.0식품첨가물제조업189667.639845446140.637416<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
13532300003230000-108-2018-0000220181116<NA>3폐업2폐업20230120<NA><NA><NA><NA>54.50138828서울특별시 송파구 방이동 66-2 세기빌딩서울특별시 송파구 오금로 111, 세기빌딩 B202-1호 (방이동)5548(주)삼성컴퍼니2023-01-20 13:17:48U2022-11-30 22:02:00.0식품첨가물제조업209496.859211445600.046916<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
13631700003170000-108-2020-0000120200429<NA>3폐업2폐업20221216<NA><NA><NA>02 18336633142.14153768서울특별시 금천구 가산동 550-1 IT캐슬 2동 1011호서울특별시 금천구 가산디지털2로 98, IT캐슬 2동 1011호 (가산동)8506오케이주식회사2022-12-15 18:58:06U2021-11-01 23:07:00.0식품첨가물제조업189369.539625441629.361415<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
13731700003170000-108-2022-0000120220524<NA>1영업/정상1영업<NA><NA><NA><NA><NA>30.80153864서울특별시 금천구 시흥동 991 아람아이씨티타워서울특별시 금천구 시흥대로 193, 아람아이씨티타워 5층 502호 (시흥동)8635주나에프에스2022-07-12 16:40:08U2021-12-06 23:04:00.0식품첨가물제조업191203.85206438765.406099<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
13832000003200000-108-2017-000012017-11-17<NA>3폐업2폐업2023-11-29<NA><NA><NA>02 69587580131.20151-015서울특별시 관악구 신림동 1738 파로스프라자A동서울특별시 관악구 난곡로 100, 지하1층 비07, 16, 17호 (신림동, 파로스프라자A동)8860주식회사 더가넷2023-11-29 10:31:50U2022-11-02 00:01:00.0식품첨가물제조업192817.818457440263.76832<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
13931800003180000-108-2020-000012020-03-05<NA>1영업/정상1영업<NA><NA><NA><NA><NA>89.71150-096서울특별시 영등포구 문래동6가 33 910호서울특별시 영등포구 문래북로 8, 910호 (문래동6가)7280노비스헬스케어 유한회사2023-07-21 09:06:31U2022-12-06 22:03:00.0식품첨가물제조업189825.743146446574.176568<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>