Overview

Dataset statistics

Number of variables48
Number of observations1700
Missing cells21434
Missing cells (%)26.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory687.4 KiB
Average record size in memory414.1 B

Variable types

Numeric11
Categorical19
Text6
Unsupported10
DateTime1
Boolean1

Dataset

Description2021-05-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123092

Alerts

개방서비스명 has constant value ""Constant
개방서비스id has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (99.3%)Imbalance
위생업태명 is highly imbalanced (99.3%)Imbalance
남성종사자수 is highly imbalanced (66.7%)Imbalance
영업장주변구분명 is highly imbalanced (86.1%)Imbalance
등급구분명 is highly imbalanced (87.0%)Imbalance
본사종업원수 is highly imbalanced (96.6%)Imbalance
공장사무직종업원수 is highly imbalanced (97.1%)Imbalance
공장판매직종업원수 is highly imbalanced (97.1%)Imbalance
공장생산직종업원수 is highly imbalanced (97.1%)Imbalance
보증액 is highly imbalanced (96.6%)Imbalance
월세액 is highly imbalanced (96.6%)Imbalance
인허가취소일자 has 1700 (100.0%) missing valuesMissing
폐업일자 has 706 (41.5%) missing valuesMissing
휴업시작일자 has 1700 (100.0%) missing valuesMissing
휴업종료일자 has 1700 (100.0%) missing valuesMissing
재개업일자 has 1700 (100.0%) missing valuesMissing
소재지전화 has 410 (24.1%) missing valuesMissing
소재지면적 has 521 (30.6%) missing valuesMissing
소재지우편번호 has 65 (3.8%) missing valuesMissing
도로명전체주소 has 570 (33.5%) missing valuesMissing
도로명우편번호 has 586 (34.5%) missing valuesMissing
좌표정보(x) has 140 (8.2%) missing valuesMissing
좌표정보(y) has 140 (8.2%) missing valuesMissing
여성종사자수 has 1292 (76.0%) missing valuesMissing
총종업원수 has 1700 (100.0%) missing valuesMissing
건물소유구분명 has 1700 (100.0%) missing valuesMissing
전통업소지정번호 has 1700 (100.0%) missing valuesMissing
전통업소주된음식 has 1700 (100.0%) missing valuesMissing
홈페이지 has 1700 (100.0%) missing valuesMissing
Unnamed: 47 has 1700 (100.0%) missing valuesMissing
번호 has unique valuesUnique
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
총종업원수 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물소유구분명 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
Unnamed: 47 is an unsupported type, check if it needs cleaning or further analysisUnsupported
여성종사자수 has 330 (19.4%) zerosZeros
시설총규모 has 571 (33.6%) zerosZeros

Reproduction

Analysis started2024-04-17 05:35:48.928355
Analysis finished2024-04-17 05:35:50.030773
Duration1.1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct1700
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean850.5
Minimum1
Maximum1700
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.1 KiB
2024-04-17T14:35:50.092674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile85.95
Q1425.75
median850.5
Q31275.25
95-th percentile1615.05
Maximum1700
Range1699
Interquartile range (IQR)849.5

Descriptive statistics

Standard deviation490.89205
Coefficient of variation (CV)0.57718054
Kurtosis-1.2
Mean850.5
Median Absolute Deviation (MAD)425
Skewness0
Sum1445850
Variance240975
MonotonicityStrictly increasing
2024-04-17T14:35:50.222233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
1144 1
 
0.1%
1142 1
 
0.1%
1141 1
 
0.1%
1140 1
 
0.1%
1139 1
 
0.1%
1138 1
 
0.1%
1137 1
 
0.1%
1136 1
 
0.1%
1135 1
 
0.1%
Other values (1690) 1690
99.4%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1700 1
0.1%
1699 1
0.1%
1698 1
0.1%
1697 1
0.1%
1696 1
0.1%
1695 1
0.1%
1694 1
0.1%
1693 1
0.1%
1692 1
0.1%
1691 1
0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.4 KiB
위탁급식영업
1700 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
위탁급식영업 1700
100.0%

Length

2024-04-17T14:35:50.341431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T14:35:50.426637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
위탁급식영업 1700
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.4 KiB
07_21_01_P
1700 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row07_21_01_P
2nd row07_21_01_P
3rd row07_21_01_P
4th row07_21_01_P
5th row07_21_01_P

Common Values

ValueCountFrequency (%)
07_21_01_P 1700
100.0%

Length

2024-04-17T14:35:50.510773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T14:35:50.598935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_21_01_p 1700
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3342100
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.1 KiB
2024-04-17T14:35:50.684895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3270000
Q13310000
median3350000
Q33360000
95-th percentile3400000
Maximum3400000
Range150000
Interquartile range (IQR)50000

Descriptive statistics

Standard deviation37463.759
Coefficient of variation (CV)0.011209646
Kurtosis-0.40058284
Mean3342100
Median Absolute Deviation (MAD)20000
Skewness-0.54525549
Sum5.68157 × 109
Variance1.4035333 × 109
MonotonicityNot monotonic
2024-04-17T14:35:50.796812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3360000 508
29.9%
3340000 183
 
10.8%
3400000 127
 
7.5%
3390000 114
 
6.7%
3330000 110
 
6.5%
3310000 105
 
6.2%
3290000 86
 
5.1%
3350000 86
 
5.1%
3300000 71
 
4.2%
3370000 62
 
3.6%
Other values (6) 248
14.6%
ValueCountFrequency (%)
3250000 16
 
0.9%
3260000 55
 
3.2%
3270000 38
 
2.2%
3280000 56
 
3.3%
3290000 86
5.1%
3300000 71
 
4.2%
3310000 105
6.2%
3320000 45
 
2.6%
3330000 110
6.5%
3340000 183
10.8%
ValueCountFrequency (%)
3400000 127
 
7.5%
3390000 114
 
6.7%
3380000 38
 
2.2%
3370000 62
 
3.6%
3360000 508
29.9%
3350000 86
 
5.1%
3340000 183
 
10.8%
3330000 110
 
6.5%
3320000 45
 
2.6%
3310000 105
 
6.2%

관리번호
Text

UNIQUE 

Distinct1700
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size13.4 KiB
2024-04-17T14:35:51.208066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters37400
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

Unique1700 ?
Unique (%)100.0%

Sample

1st row3250000-120-2008-00001
2nd row3250000-120-2009-00001
3rd row3250000-120-2003-00001
4th row3250000-120-2003-00003
5th row3250000-120-2006-00001
ValueCountFrequency (%)
3250000-120-2008-00001 1
 
0.1%
3360000-120-2004-00022 1
 
0.1%
3360000-120-2005-00015 1
 
0.1%
3360000-120-2004-00016 1
 
0.1%
3360000-120-2004-00013 1
 
0.1%
3360000-120-2004-00012 1
 
0.1%
3360000-120-2004-00011 1
 
0.1%
3360000-120-2016-00011 1
 
0.1%
3360000-120-2004-00001 1
 
0.1%
3360000-120-2003-00066 1
 
0.1%
Other values (1690) 1690
99.4%
2024-04-17T14:35:51.484366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 17756
47.5%
- 5100
 
13.6%
2 4288
 
11.5%
3 3885
 
10.4%
1 3237
 
8.7%
6 889
 
2.4%
4 688
 
1.8%
9 417
 
1.1%
5 406
 
1.1%
7 399
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 32300
86.4%
Dash Punctuation 5100
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 17756
55.0%
2 4288
 
13.3%
3 3885
 
12.0%
1 3237
 
10.0%
6 889
 
2.8%
4 688
 
2.1%
9 417
 
1.3%
5 406
 
1.3%
7 399
 
1.2%
8 335
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 5100
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 37400
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 17756
47.5%
- 5100
 
13.6%
2 4288
 
11.5%
3 3885
 
10.4%
1 3237
 
8.7%
6 889
 
2.4%
4 688
 
1.8%
9 417
 
1.1%
5 406
 
1.1%
7 399
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 37400
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 17756
47.5%
- 5100
 
13.6%
2 4288
 
11.5%
3 3885
 
10.4%
1 3237
 
8.7%
6 889
 
2.4%
4 688
 
1.8%
9 417
 
1.1%
5 406
 
1.1%
7 399
 
1.1%

인허가일자
Real number (ℝ)

Distinct1163
Distinct (%)68.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20096300
Minimum20030521
Maximum20210331
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.1 KiB
2024-04-17T14:35:51.629783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20030521
5-th percentile20030530
Q120040414
median20081117
Q320141218
95-th percentile20191119
Maximum20210331
Range179810
Interquartile range (IQR)100804

Descriptive statistics

Standard deviation56575.321
Coefficient of variation (CV)0.0028152108
Kurtosis-1.1882411
Mean20096300
Median Absolute Deviation (MAD)50095
Skewness0.38237677
Sum3.416371 × 1010
Variance3.2007669 × 109
MonotonicityNot monotonic
2024-04-17T14:35:51.760234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030602 32
 
1.9%
20030528 24
 
1.4%
20030530 17
 
1.0%
20030527 16
 
0.9%
20030529 13
 
0.8%
20031015 12
 
0.7%
20030616 12
 
0.7%
20031013 11
 
0.6%
20030623 11
 
0.6%
20161101 9
 
0.5%
Other values (1153) 1543
90.8%
ValueCountFrequency (%)
20030521 1
 
0.1%
20030522 6
 
0.4%
20030523 7
 
0.4%
20030526 4
 
0.2%
20030527 16
0.9%
20030528 24
1.4%
20030529 13
0.8%
20030530 17
1.0%
20030531 2
 
0.1%
20030602 32
1.9%
ValueCountFrequency (%)
20210331 1
 
0.1%
20210309 1
 
0.1%
20210225 1
 
0.1%
20210215 1
 
0.1%
20210209 1
 
0.1%
20210208 1
 
0.1%
20210203 1
 
0.1%
20210129 3
0.2%
20210125 2
0.1%
20210122 1
 
0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1700
Missing (%)100.0%
Memory size15.1 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.4 KiB
3
994 
1
706 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 994
58.5%
1 706
41.5%

Length

2024-04-17T14:35:51.878126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T14:35:51.965625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 994
58.5%
1 706
41.5%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.4 KiB
폐업
994 
영업/정상
706 

Length

Max length5
Median length2
Mean length3.2458824
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 994
58.5%
영업/정상 706
41.5%

Length

2024-04-17T14:35:52.057087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T14:35:52.148251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 994
58.5%
영업/정상 706
41.5%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.4 KiB
2
994 
1
706 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 994
58.5%
1 706
41.5%

Length

2024-04-17T14:35:52.238567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T14:35:52.329755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 994
58.5%
1 706
41.5%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.4 KiB
폐업
994 
영업
706 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 994
58.5%
영업 706
41.5%

Length

2024-04-17T14:35:52.418761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T14:35:52.507332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 994
58.5%
영업 706
41.5%

폐업일자
Real number (ℝ)

MISSING 

Distinct808
Distinct (%)81.3%
Missing706
Missing (%)41.5%
Infinite0
Infinite (%)0.0%
Mean20123434
Minimum20030923
Maximum20210323
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.1 KiB
2024-04-17T14:35:52.605780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20030923
5-th percentile20050529
Q120081001
median20120602
Q320161226
95-th percentile20200422
Maximum20210323
Range179400
Interquartile range (IQR)80224.75

Descriptive statistics

Standard deviation47699.51
Coefficient of variation (CV)0.0023703464
Kurtosis-1.177246
Mean20123434
Median Absolute Deviation (MAD)40117.5
Skewness0.041913583
Sum2.0002693 × 1010
Variance2.2752433 × 109
MonotonicityNot monotonic
2024-04-17T14:35:52.742265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20161101 9
 
0.5%
20171229 5
 
0.3%
20181231 5
 
0.3%
20071001 4
 
0.2%
20180531 4
 
0.2%
20120102 4
 
0.2%
20100303 4
 
0.2%
20191231 3
 
0.2%
20111014 3
 
0.2%
20180919 3
 
0.2%
Other values (798) 950
55.9%
(Missing) 706
41.5%
ValueCountFrequency (%)
20030923 1
0.1%
20030925 2
0.1%
20031124 1
0.1%
20031231 2
0.1%
20040114 1
0.1%
20040129 1
0.1%
20040203 1
0.1%
20040223 1
0.1%
20040226 1
0.1%
20040227 2
0.1%
ValueCountFrequency (%)
20210323 1
0.1%
20210316 1
0.1%
20210305 1
0.1%
20210223 1
0.1%
20210222 1
0.1%
20210210 1
0.1%
20210129 1
0.1%
20210128 1
0.1%
20210125 1
0.1%
20210106 1
0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1700
Missing (%)100.0%
Memory size15.1 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1700
Missing (%)100.0%
Memory size15.1 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1700
Missing (%)100.0%
Memory size15.1 KiB

소재지전화
Text

MISSING 

Distinct1112
Distinct (%)86.2%
Missing410
Missing (%)24.1%
Memory size13.4 KiB
2024-04-17T14:35:53.064844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.297674
Min length3

Characters and Unicode

Total characters14574
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

Unique1021 ?
Unique (%)79.1%

Sample

1st row051 660 2401
2nd row051 7187229
3rd row051 4630400
4th row051 4628468
5th row051 464 7307
ValueCountFrequency (%)
051 1050
33.9%
831 92
 
3.0%
055 52
 
1.7%
070 36
 
1.2%
02 17
 
0.5%
973 17
 
0.5%
2820 16
 
0.5%
0102 15
 
0.5%
633 14
 
0.5%
3880 14
 
0.5%
Other values (1313) 1772
57.3%
2024-04-17T14:35:53.478785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2415
16.6%
1 2195
15.1%
5 2022
13.9%
1823
12.5%
2 1098
7.5%
3 1076
7.4%
8 942
 
6.5%
7 843
 
5.8%
6 792
 
5.4%
4 702
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12751
87.5%
Space Separator 1823
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2415
18.9%
1 2195
17.2%
5 2022
15.9%
2 1098
8.6%
3 1076
8.4%
8 942
 
7.4%
7 843
 
6.6%
6 792
 
6.2%
4 702
 
5.5%
9 666
 
5.2%
Space Separator
ValueCountFrequency (%)
1823
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14574
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2415
16.6%
1 2195
15.1%
5 2022
13.9%
1823
12.5%
2 1098
7.5%
3 1076
7.4%
8 942
 
6.5%
7 843
 
5.8%
6 792
 
5.4%
4 702
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14574
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2415
16.6%
1 2195
15.1%
5 2022
13.9%
1823
12.5%
2 1098
7.5%
3 1076
7.4%
8 942
 
6.5%
7 843
 
5.8%
6 792
 
5.4%
4 702
 
4.8%

소재지면적
Text

MISSING 

Distinct991
Distinct (%)84.1%
Missing521
Missing (%)30.6%
Memory size13.4 KiB
2024-04-17T14:35:53.817614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length5.7506361
Min length3

Characters and Unicode

Total characters6780
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

Unique880 ?
Unique (%)74.6%

Sample

1st row411.30
2nd row443.75
3rd row308.00
4th row10.14
5th row153.11
ValueCountFrequency (%)
00 36
 
3.1%
132.00 7
 
0.6%
66.00 5
 
0.4%
165.00 4
 
0.3%
12.00 4
 
0.3%
168.22 4
 
0.3%
264.00 4
 
0.3%
131.04 4
 
0.3%
90.00 4
 
0.3%
70.00 4
 
0.3%
Other values (981) 1103
93.6%
2024-04-17T14:35:54.237190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1180
17.4%
. 1179
17.4%
1 771
11.4%
2 643
9.5%
4 486
7.2%
6 474
7.0%
3 471
 
6.9%
5 444
 
6.5%
8 376
 
5.5%
9 364
 
5.4%
Other values (2) 392
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5571
82.2%
Other Punctuation 1209
 
17.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1180
21.2%
1 771
13.8%
2 643
11.5%
4 486
8.7%
6 474
8.5%
3 471
 
8.5%
5 444
 
8.0%
8 376
 
6.7%
9 364
 
6.5%
7 362
 
6.5%
Other Punctuation
ValueCountFrequency (%)
. 1179
97.5%
, 30
 
2.5%

Most occurring scripts

ValueCountFrequency (%)
Common 6780
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1180
17.4%
. 1179
17.4%
1 771
11.4%
2 643
9.5%
4 486
7.2%
6 474
7.0%
3 471
 
6.9%
5 444
 
6.5%
8 376
 
5.5%
9 364
 
5.4%
Other values (2) 392
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6780
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1180
17.4%
. 1179
17.4%
1 771
11.4%
2 643
9.5%
4 486
7.2%
6 474
7.0%
3 471
 
6.9%
5 444
 
6.5%
8 376
 
5.5%
9 364
 
5.4%
Other values (2) 392
 
5.8%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct427
Distinct (%)26.1%
Missing65
Missing (%)3.8%
Infinite0
Infinite (%)0.0%
Mean612924.4
Minimum600013
Maximum619953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.1 KiB
2024-04-17T14:35:54.378843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600013
5-th percentile602711.1
Q1607838
median613833
Q3618280
95-th percentile618820
Maximum619953
Range19940
Interquartile range (IQR)10442

Descriptive statistics

Standard deviation5827.3025
Coefficient of variation (CV)0.0095073756
Kurtosis-1.1887639
Mean612924.4
Median Absolute Deviation (MAD)4984
Skewness-0.47023987
Sum1.0021314 × 109
Variance33957454
MonotonicityNot monotonic
2024-04-17T14:35:54.517841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
618819 72
 
4.2%
618817 70
 
4.1%
618230 61
 
3.6%
618818 57
 
3.4%
618820 56
 
3.3%
604836 48
 
2.8%
618280 33
 
1.9%
618220 28
 
1.6%
618250 19
 
1.1%
604826 18
 
1.1%
Other values (417) 1173
69.0%
(Missing) 65
 
3.8%
ValueCountFrequency (%)
600013 2
 
0.1%
600015 2
 
0.1%
600017 3
0.2%
600023 1
 
0.1%
600046 1
 
0.1%
600091 1
 
0.1%
600814 1
 
0.1%
600816 5
0.3%
601010 1
 
0.1%
601050 5
0.3%
ValueCountFrequency (%)
619953 10
0.6%
619952 16
0.9%
619951 10
0.6%
619913 3
 
0.2%
619912 1
 
0.1%
619906 3
 
0.2%
619904 1
 
0.1%
619903 1
 
0.1%
619902 6
 
0.4%
619901 5
 
0.3%
Distinct1470
Distinct (%)86.7%
Missing4
Missing (%)0.2%
Memory size13.4 KiB
2024-04-17T14:35:54.866955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length46
Mean length23.73467
Min length16

Characters and Unicode

Total characters40254
Distinct characters359
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1299 ?
Unique (%)76.6%

Sample

1st row부산광역시 중구 중앙동4가 74-1번지
2nd row부산광역시 중구 중앙동5가 50번지
3rd row부산광역시 중구 중앙동4가 75-1
4th row부산광역시 중구 중앙동3가 18-1번지
5th row부산광역시 중구 중앙동4가 22-1번지
ValueCountFrequency (%)
부산광역시 1696
 
21.8%
강서구 506
 
6.5%
송정동 262
 
3.4%
사하구 183
 
2.3%
기장군 126
 
1.6%
사상구 114
 
1.5%
해운대구 110
 
1.4%
남구 105
 
1.3%
95
 
1.2%
부산진구 86
 
1.1%
Other values (1892) 4508
57.9%
2024-04-17T14:35:55.326987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6099
 
15.2%
2083
 
5.2%
1 1969
 
4.9%
1961
 
4.9%
1859
 
4.6%
1724
 
4.3%
1714
 
4.3%
1699
 
4.2%
1683
 
4.2%
1654
 
4.1%
Other values (349) 17809
44.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25133
62.4%
Decimal Number 7414
 
18.4%
Space Separator 6099
 
15.2%
Dash Punctuation 1241
 
3.1%
Uppercase Letter 121
 
0.3%
Open Punctuation 106
 
0.3%
Close Punctuation 105
 
0.3%
Other Punctuation 30
 
0.1%
Lowercase Letter 4
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2083
 
8.3%
1961
 
7.8%
1859
 
7.4%
1724
 
6.9%
1714
 
6.8%
1699
 
6.8%
1683
 
6.7%
1654
 
6.6%
1489
 
5.9%
595
 
2.4%
Other values (305) 8672
34.5%
Uppercase Letter
ValueCountFrequency (%)
B 25
20.7%
A 18
14.9%
I 14
11.6%
C 10
 
8.3%
T 9
 
7.4%
K 9
 
7.4%
S 8
 
6.6%
L 6
 
5.0%
R 4
 
3.3%
E 3
 
2.5%
Other values (10) 15
12.4%
Decimal Number
ValueCountFrequency (%)
1 1969
26.6%
2 746
 
10.1%
5 741
 
10.0%
4 673
 
9.1%
3 663
 
8.9%
6 606
 
8.2%
0 548
 
7.4%
7 523
 
7.1%
8 513
 
6.9%
9 432
 
5.8%
Other Punctuation
ValueCountFrequency (%)
, 19
63.3%
& 5
 
16.7%
. 3
 
10.0%
: 2
 
6.7%
/ 1
 
3.3%
Open Punctuation
ValueCountFrequency (%)
( 105
99.1%
[ 1
 
0.9%
Close Punctuation
ValueCountFrequency (%)
) 104
99.0%
] 1
 
1.0%
Lowercase Letter
ValueCountFrequency (%)
i 3
75.0%
o 1
 
25.0%
Space Separator
ValueCountFrequency (%)
6099
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1241
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25133
62.4%
Common 14996
37.3%
Latin 125
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2083
 
8.3%
1961
 
7.8%
1859
 
7.4%
1724
 
6.9%
1714
 
6.8%
1699
 
6.8%
1683
 
6.7%
1654
 
6.6%
1489
 
5.9%
595
 
2.4%
Other values (305) 8672
34.5%
Common
ValueCountFrequency (%)
6099
40.7%
1 1969
 
13.1%
- 1241
 
8.3%
2 746
 
5.0%
5 741
 
4.9%
4 673
 
4.5%
3 663
 
4.4%
6 606
 
4.0%
0 548
 
3.7%
7 523
 
3.5%
Other values (12) 1187
 
7.9%
Latin
ValueCountFrequency (%)
B 25
20.0%
A 18
14.4%
I 14
11.2%
C 10
 
8.0%
T 9
 
7.2%
K 9
 
7.2%
S 8
 
6.4%
L 6
 
4.8%
R 4
 
3.2%
E 3
 
2.4%
Other values (12) 19
15.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25133
62.4%
ASCII 15121
37.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6099
40.3%
1 1969
 
13.0%
- 1241
 
8.2%
2 746
 
4.9%
5 741
 
4.9%
4 673
 
4.5%
3 663
 
4.4%
6 606
 
4.0%
0 548
 
3.6%
7 523
 
3.5%
Other values (34) 1312
 
8.7%
Hangul
ValueCountFrequency (%)
2083
 
8.3%
1961
 
7.8%
1859
 
7.4%
1724
 
6.9%
1714
 
6.8%
1699
 
6.8%
1683
 
6.7%
1654
 
6.6%
1489
 
5.9%
595
 
2.4%
Other values (305) 8672
34.5%

도로명전체주소
Text

MISSING 

Distinct1045
Distinct (%)92.5%
Missing570
Missing (%)33.5%
Memory size13.4 KiB
2024-04-17T14:35:55.630847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length47
Mean length29.712389
Min length20

Characters and Unicode

Total characters33575
Distinct characters371
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique971 ?
Unique (%)85.9%

Sample

1st row부산광역시 중구 충장대로13번길 67 (중앙동4가)
2nd row부산광역시 중구 중앙대로 52 (중앙동5가)
3rd row부산광역시 중구 충장대로5번길 72 (중앙동4가)
4th row부산광역시 중구 대청로 135 (중앙동3가)
5th row부산광역시 중구 충장대로 6 (중앙동4가)
ValueCountFrequency (%)
부산광역시 1130
 
17.4%
강서구 385
 
5.9%
송정동 188
 
2.9%
사하구 126
 
1.9%
1층 114
 
1.8%
해운대구 82
 
1.3%
기장군 79
 
1.2%
사상구 76
 
1.2%
남구 56
 
0.9%
금정구 54
 
0.8%
Other values (1330) 4200
64.7%
2024-04-17T14:35:56.089381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5360
 
16.0%
1871
 
5.6%
1340
 
4.0%
1329
 
4.0%
1162
 
3.5%
1155
 
3.4%
1132
 
3.4%
( 1131
 
3.4%
) 1129
 
3.4%
1116
 
3.3%
Other values (361) 16850
50.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20470
61.0%
Space Separator 5360
 
16.0%
Decimal Number 4725
 
14.1%
Open Punctuation 1131
 
3.4%
Close Punctuation 1129
 
3.4%
Other Punctuation 569
 
1.7%
Uppercase Letter 101
 
0.3%
Dash Punctuation 80
 
0.2%
Math Symbol 5
 
< 0.1%
Lowercase Letter 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1871
 
9.1%
1340
 
6.5%
1329
 
6.5%
1162
 
5.7%
1155
 
5.6%
1132
 
5.5%
1116
 
5.5%
1115
 
5.4%
499
 
2.4%
451
 
2.2%
Other values (321) 9300
45.4%
Uppercase Letter
ValueCountFrequency (%)
B 21
20.8%
A 18
17.8%
C 14
13.9%
K 8
 
7.9%
S 7
 
6.9%
T 6
 
5.9%
N 5
 
5.0%
I 4
 
4.0%
E 3
 
3.0%
G 3
 
3.0%
Other values (8) 12
11.9%
Decimal Number
ValueCountFrequency (%)
1 1030
21.8%
2 716
15.2%
3 587
12.4%
4 425
9.0%
6 411
 
8.7%
5 390
 
8.3%
0 331
 
7.0%
7 319
 
6.8%
9 284
 
6.0%
8 232
 
4.9%
Lowercase Letter
ValueCountFrequency (%)
e 2
40.0%
o 1
20.0%
l 1
20.0%
t 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 564
99.1%
& 4
 
0.7%
: 1
 
0.2%
Space Separator
ValueCountFrequency (%)
5360
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1131
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1129
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 80
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20470
61.0%
Common 12999
38.7%
Latin 106
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1871
 
9.1%
1340
 
6.5%
1329
 
6.5%
1162
 
5.7%
1155
 
5.6%
1132
 
5.5%
1116
 
5.5%
1115
 
5.4%
499
 
2.4%
451
 
2.2%
Other values (321) 9300
45.4%
Latin
ValueCountFrequency (%)
B 21
19.8%
A 18
17.0%
C 14
13.2%
K 8
 
7.5%
S 7
 
6.6%
T 6
 
5.7%
N 5
 
4.7%
I 4
 
3.8%
E 3
 
2.8%
G 3
 
2.8%
Other values (12) 17
16.0%
Common
ValueCountFrequency (%)
5360
41.2%
( 1131
 
8.7%
) 1129
 
8.7%
1 1030
 
7.9%
2 716
 
5.5%
3 587
 
4.5%
, 564
 
4.3%
4 425
 
3.3%
6 411
 
3.2%
5 390
 
3.0%
Other values (8) 1256
 
9.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20470
61.0%
ASCII 13105
39.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5360
40.9%
( 1131
 
8.6%
) 1129
 
8.6%
1 1030
 
7.9%
2 716
 
5.5%
3 587
 
4.5%
, 564
 
4.3%
4 425
 
3.2%
6 411
 
3.1%
5 390
 
3.0%
Other values (30) 1362
 
10.4%
Hangul
ValueCountFrequency (%)
1871
 
9.1%
1340
 
6.5%
1329
 
6.5%
1162
 
5.7%
1155
 
5.6%
1132
 
5.5%
1116
 
5.5%
1115
 
5.4%
499
 
2.4%
451
 
2.2%
Other values (321) 9300
45.4%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct390
Distinct (%)35.0%
Missing586
Missing (%)34.5%
Infinite0
Infinite (%)0.0%
Mean47486.699
Minimum46002
Maximum49526
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.1 KiB
2024-04-17T14:35:56.226213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46002
5-th percentile46034
Q146743.25
median46958
Q348379
95-th percentile49460
Maximum49526
Range3524
Interquartile range (IQR)1635.75

Descriptive statistics

Standard deviation1087.2708
Coefficient of variation (CV)0.022896323
Kurtosis-0.97407171
Mean47486.699
Median Absolute Deviation (MAD)610
Skewness0.62484519
Sum52900183
Variance1182157.8
MonotonicityNot monotonic
2024-04-17T14:35:56.362820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
46753 44
 
2.6%
46742 44
 
2.6%
46752 32
 
1.9%
46757 31
 
1.8%
46754 30
 
1.8%
46751 27
 
1.6%
46755 23
 
1.4%
46744 18
 
1.1%
46027 15
 
0.9%
46727 14
 
0.8%
Other values (380) 836
49.2%
(Missing) 586
34.5%
ValueCountFrequency (%)
46002 2
 
0.1%
46006 1
 
0.1%
46014 1
 
0.1%
46015 3
 
0.2%
46018 1
 
0.1%
46019 1
 
0.1%
46020 10
0.6%
46023 1
 
0.1%
46026 4
 
0.2%
46027 15
0.9%
ValueCountFrequency (%)
49526 6
0.4%
49524 2
 
0.1%
49523 1
 
0.1%
49520 1
 
0.1%
49511 1
 
0.1%
49500 2
 
0.1%
49499 4
0.2%
49498 1
 
0.1%
49491 1
 
0.1%
49489 3
0.2%
Distinct1585
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Memory size13.4 KiB
2024-04-17T14:35:56.611317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length24
Mean length11.304118
Min length2

Characters and Unicode

Total characters19217
Distinct characters516
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1498 ?
Unique (%)88.1%

Sample

1st row웰리브디섹점
2nd row(주)아워홈엘지유플러스 중앙동사옥점
3rd row재단법인 케이티그룹희망나눔재단 서부산
4th row씨제이프레시웨이 주식회사 SC은행부산점
5th row(주)아워홈한진중공업중앙점
ValueCountFrequency (%)
구내식당 66
 
2.6%
주)아워홈 41
 
1.6%
주)새손 35
 
1.4%
주)풀무원푸드앤컬처 34
 
1.3%
주식회사 31
 
1.2%
주)호성식품 31
 
1.2%
주)동원홈푸드 28
 
1.1%
주)삼보유통 27
 
1.1%
주)신세계푸드 17
 
0.7%
주)현대그린푸드 15
 
0.6%
Other values (1768) 2229
87.3%
2024-04-17T14:35:56.982791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 968
 
5.0%
947
 
4.9%
( 945
 
4.9%
855
 
4.4%
718
 
3.7%
527
 
2.7%
494
 
2.6%
423
 
2.2%
416
 
2.2%
392
 
2.0%
Other values (506) 12532
65.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16187
84.2%
Close Punctuation 969
 
5.0%
Open Punctuation 946
 
4.9%
Space Separator 855
 
4.4%
Uppercase Letter 190
 
1.0%
Decimal Number 34
 
0.2%
Other Punctuation 23
 
0.1%
Dash Punctuation 9
 
< 0.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
947
 
5.9%
718
 
4.4%
527
 
3.3%
494
 
3.1%
423
 
2.6%
416
 
2.6%
392
 
2.4%
389
 
2.4%
383
 
2.4%
342
 
2.1%
Other values (460) 11156
68.9%
Uppercase Letter
ValueCountFrequency (%)
S 35
18.4%
C 23
12.1%
T 18
9.5%
F 17
8.9%
K 16
8.4%
G 12
 
6.3%
J 9
 
4.7%
N 9
 
4.7%
P 6
 
3.2%
B 6
 
3.2%
Other values (14) 39
20.5%
Decimal Number
ValueCountFrequency (%)
2 13
38.2%
1 8
23.5%
3 6
17.6%
0 2
 
5.9%
5 2
 
5.9%
7 2
 
5.9%
4 1
 
2.9%
Other Punctuation
ValueCountFrequency (%)
. 12
52.2%
& 6
26.1%
/ 3
 
13.0%
· 1
 
4.3%
, 1
 
4.3%
Lowercase Letter
ValueCountFrequency (%)
w 1
25.0%
p 1
25.0%
s 1
25.0%
k 1
25.0%
Close Punctuation
ValueCountFrequency (%)
) 968
99.9%
] 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 945
99.9%
[ 1
 
0.1%
Space Separator
ValueCountFrequency (%)
855
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16187
84.2%
Common 2836
 
14.8%
Latin 194
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
947
 
5.9%
718
 
4.4%
527
 
3.3%
494
 
3.1%
423
 
2.6%
416
 
2.6%
392
 
2.4%
389
 
2.4%
383
 
2.4%
342
 
2.1%
Other values (460) 11156
68.9%
Latin
ValueCountFrequency (%)
S 35
18.0%
C 23
11.9%
T 18
9.3%
F 17
 
8.8%
K 16
 
8.2%
G 12
 
6.2%
J 9
 
4.6%
N 9
 
4.6%
P 6
 
3.1%
B 6
 
3.1%
Other values (18) 43
22.2%
Common
ValueCountFrequency (%)
) 968
34.1%
( 945
33.3%
855
30.1%
2 13
 
0.5%
. 12
 
0.4%
- 9
 
0.3%
1 8
 
0.3%
& 6
 
0.2%
3 6
 
0.2%
/ 3
 
0.1%
Other values (8) 11
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16187
84.2%
ASCII 3029
 
15.8%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 968
32.0%
( 945
31.2%
855
28.2%
S 35
 
1.2%
C 23
 
0.8%
T 18
 
0.6%
F 17
 
0.6%
K 16
 
0.5%
2 13
 
0.4%
. 12
 
0.4%
Other values (35) 127
 
4.2%
Hangul
ValueCountFrequency (%)
947
 
5.9%
718
 
4.4%
527
 
3.3%
494
 
3.1%
423
 
2.6%
416
 
2.6%
392
 
2.4%
389
 
2.4%
383
 
2.4%
342
 
2.1%
Other values (460) 11156
68.9%
None
ValueCountFrequency (%)
· 1
100.0%

최종수정시점
Real number (ℝ)

Distinct1566
Distinct (%)92.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0138229 × 1013
Minimum2.0030522 × 1013
Maximum2.0210331 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.1 KiB
2024-04-17T14:35:57.102656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0030522 × 1013
5-th percentile2.0031013 × 1013
Q12.0081125 × 1013
median2.0160117 × 1013
Q32.0190613 × 1013
95-th percentile2.0210114 × 1013
Maximum2.0210331 × 1013
Range1.7980915 × 1011
Interquartile range (IQR)1.0948849 × 1011

Descriptive statistics

Standard deviation5.8552199 × 1010
Coefficient of variation (CV)0.0029075147
Kurtosis-1.1817177
Mean2.0138229 × 1013
Median Absolute Deviation (MAD)4.0303983 × 1010
Skewness-0.48301302
Sum3.423499 × 1016
Variance3.42836 × 1021
MonotonicityNot monotonic
2024-04-17T14:35:57.230402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20041004000000 20
 
1.2%
20030602000000 14
 
0.8%
20040416000000 8
 
0.5%
20070601000000 7
 
0.4%
20030616000000 7
 
0.4%
20040805000000 6
 
0.4%
20030530000000 5
 
0.3%
20030623000000 5
 
0.3%
20050203000000 5
 
0.3%
20030528000000 5
 
0.3%
Other values (1556) 1618
95.2%
ValueCountFrequency (%)
20030522000000 1
 
0.1%
20030523000000 2
 
0.1%
20030526000000 3
 
0.2%
20030527000000 3
 
0.2%
20030528000000 5
 
0.3%
20030529000000 2
 
0.1%
20030530000000 5
 
0.3%
20030602000000 14
0.8%
20030605000000 2
 
0.1%
20030609000000 1
 
0.1%
ValueCountFrequency (%)
20210331151833 1
0.1%
20210330162124 1
0.1%
20210330161942 1
0.1%
20210329135609 1
0.1%
20210326161222 1
0.1%
20210325145038 1
0.1%
20210324174112 1
0.1%
20210323180455 1
0.1%
20210323180044 1
0.1%
20210323125719 1
0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.4 KiB
I
1171 
U
529 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 1171
68.9%
U 529
31.1%

Length

2024-04-17T14:35:57.346492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T14:35:57.442993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1171
68.9%
u 529
31.1%
Distinct331
Distinct (%)19.5%
Missing0
Missing (%)0.0%
Memory size13.4 KiB
Minimum2018-08-31 23:59:59
Maximum2021-04-02 00:22:59
2024-04-17T14:35:57.545412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T14:35:57.669426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.4 KiB
위탁급식영업
1699 
<NA>
 
1

Length

Max length6
Median length6
Mean length5.9988235
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
위탁급식영업 1699
99.9%
<NA> 1
 
0.1%

Length

2024-04-17T14:35:57.801440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T14:35:57.898749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
위탁급식영업 1699
99.9%
na 1
 
0.1%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct1117
Distinct (%)71.6%
Missing140
Missing (%)8.2%
Infinite0
Infinite (%)0.0%
Mean382312.93
Minimum365010.39
Maximum407785.94
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.1 KiB
2024-04-17T14:35:57.994990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum365010.39
5-th percentile366621.37
Q1371070.27
median383068.7
Q3389910.43
95-th percentile399045.49
Maximum407785.94
Range42775.552
Interquartile range (IQR)18840.16

Descriptive statistics

Standard deviation10525.034
Coefficient of variation (CV)0.027529893
Kurtosis-0.95199758
Mean382312.93
Median Absolute Deviation (MAD)8017.2932
Skewness0.00040783392
Sum5.9640818 × 108
Variance1.1077635 × 108
MonotonicityNot monotonic
2024-04-17T14:35:58.119677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
382570.401135476 14
 
0.8%
391796.495138673 12
 
0.7%
366543.906759876 9
 
0.5%
389811.392307835 8
 
0.5%
388199.207334794 7
 
0.4%
384030.498741004 6
 
0.4%
383317.542366441 6
 
0.4%
389087.131613449 6
 
0.4%
389314.662085919 5
 
0.3%
371094.285732956 5
 
0.3%
Other values (1107) 1482
87.2%
(Missing) 140
 
8.2%
ValueCountFrequency (%)
365010.390597385 1
 
0.1%
365093.532168897 1
 
0.1%
365094.004922601 1
 
0.1%
365115.866440903 4
0.2%
365292.225416155 2
0.1%
365307.209621952 1
 
0.1%
365331.554111646 1
 
0.1%
365359.221940167 2
0.1%
365395.142740959 1
 
0.1%
365399.645488953 1
 
0.1%
ValueCountFrequency (%)
407785.942175253 1
 
0.1%
407533.057972118 2
0.1%
406868.288952732 1
 
0.1%
406242.577428169 4
0.2%
405967.49653678 1
 
0.1%
405914.665215376 1
 
0.1%
405900.785278243 1
 
0.1%
405732.292736473 2
0.1%
405651.592697969 1
 
0.1%
405621.168961124 1
 
0.1%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct1117
Distinct (%)71.6%
Missing140
Missing (%)8.2%
Infinite0
Infinite (%)0.0%
Mean185044.87
Minimum174279.76
Maximum210424.66
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.1 KiB
2024-04-17T14:35:58.513610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum174279.76
5-th percentile177102.13
Q1178897.32
median183989.42
Q3189021.45
95-th percentile203778.51
Maximum210424.66
Range36144.896
Interquartile range (IQR)10124.137

Descriptive statistics

Standard deviation7386.0535
Coefficient of variation (CV)0.039914932
Kurtosis0.78941065
Mean185044.87
Median Absolute Deviation (MAD)5093.2541
Skewness1.0750942
Sum2.8867 × 108
Variance54553786
MonotonicityNot monotonic
2024-04-17T14:35:58.627321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
187570.045156033 14
 
0.8%
183632.373950837 12
 
0.7%
177215.872329016 9
 
0.5%
180523.822532435 8
 
0.5%
194848.323369342 7
 
0.4%
179806.024724594 6
 
0.4%
185013.86379536 6
 
0.4%
198411.005541894 6
 
0.4%
194669.898821687 5
 
0.3%
185672.987884383 5
 
0.3%
Other values (1107) 1482
87.2%
(Missing) 140
 
8.2%
ValueCountFrequency (%)
174279.764300288 2
0.1%
174282.637515014 1
 
0.1%
174294.918563971 1
 
0.1%
174315.265600106 3
0.2%
174355.708212487 2
0.1%
174406.140455233 1
 
0.1%
174554.282651552 1
 
0.1%
174579.426185065 1
 
0.1%
174683.069423816 1
 
0.1%
174689.221061664 1
 
0.1%
ValueCountFrequency (%)
210424.660206307 1
0.1%
210246.141637797 1
0.1%
210015.613769918 1
0.1%
209053.527592549 1
0.1%
207205.169188125 1
0.1%
206785.626185688 1
0.1%
206475.252052201 2
0.1%
205878.362596249 1
0.1%
205815.507582338 1
0.1%
205725.080113219 2
0.1%

위생업태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.4 KiB
위탁급식영업
1699 
<NA>
 
1

Length

Max length6
Median length6
Mean length5.9988235
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
위탁급식영업 1699
99.9%
<NA> 1
 
0.1%

Length

2024-04-17T14:35:58.748969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T14:35:58.845993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
위탁급식영업 1699
99.9%
na 1
 
0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size13.4 KiB
<NA>
1313 
0
365 
1
 
17
2
 
3
5
 
1

Length

Max length4
Median length4
Mean length3.3170588
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1313
77.2%
0 365
 
21.5%
1 17
 
1.0%
2 3
 
0.2%
5 1
 
0.1%
3 1
 
0.1%

Length

2024-04-17T14:35:58.947268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T14:35:59.054704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1313
77.2%
0 365
 
21.5%
1 17
 
1.0%
2 3
 
0.2%
5 1
 
0.1%
3 1
 
0.1%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct15
Distinct (%)3.7%
Missing1292
Missing (%)76.0%
Infinite0
Infinite (%)0.0%
Mean0.78676471
Minimum0
Maximum20
Zeros330
Zeros (%)19.4%
Negative0
Negative (%)0.0%
Memory size15.1 KiB
2024-04-17T14:35:59.146175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4
Maximum20
Range20
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.2058937
Coefficient of variation (CV)2.8037527
Kurtosis22.76693
Mean0.78676471
Median Absolute Deviation (MAD)0
Skewness4.2196529
Sum321
Variance4.8659669
MonotonicityNot monotonic
2024-04-17T14:35:59.253393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 330
 
19.4%
2 20
 
1.2%
4 15
 
0.9%
3 13
 
0.8%
1 11
 
0.6%
7 4
 
0.2%
6 3
 
0.2%
12 3
 
0.2%
5 2
 
0.1%
8 2
 
0.1%
Other values (5) 5
 
0.3%
(Missing) 1292
76.0%
ValueCountFrequency (%)
0 330
19.4%
1 11
 
0.6%
2 20
 
1.2%
3 13
 
0.8%
4 15
 
0.9%
5 2
 
0.1%
6 3
 
0.2%
7 4
 
0.2%
8 2
 
0.1%
9 1
 
0.1%
ValueCountFrequency (%)
20 1
 
0.1%
13 1
 
0.1%
12 3
0.2%
11 1
 
0.1%
10 1
 
0.1%
9 1
 
0.1%
8 2
0.1%
7 4
0.2%
6 3
0.2%
5 2
0.1%

영업장주변구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size13.4 KiB
<NA>
1591 
기타
 
88
주택가주변
 
7
아파트지역
 
5
학교정화(절대)
 
4
Other values (3)
 
5

Length

Max length8
Median length4
Mean length3.9241176
Min length2

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1591
93.6%
기타 88
 
5.2%
주택가주변 7
 
0.4%
아파트지역 5
 
0.3%
학교정화(절대) 4
 
0.2%
유흥업소밀집지역 3
 
0.2%
결혼예식장주변 1
 
0.1%
학교정화(상대) 1
 
0.1%

Length

2024-04-17T14:35:59.369093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T14:35:59.497407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1591
93.6%
기타 88
 
5.2%
주택가주변 7
 
0.4%
아파트지역 5
 
0.3%
학교정화(절대 4
 
0.2%
유흥업소밀집지역 3
 
0.2%
결혼예식장주변 1
 
0.1%
학교정화(상대 1
 
0.1%

등급구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size13.4 KiB
<NA>
1653 
자율
 
33
기타
 
14

Length

Max length4
Median length4
Mean length3.9447059
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> 1653
97.2%
자율 33
 
1.9%
기타 14
 
0.8%

Length

2024-04-17T14:35:59.629180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T14:35:59.742139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1653
97.2%
자율 33
 
1.9%
기타 14
 
0.8%
Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size13.4 KiB
<NA>
1088 
상수도전용
586 
지하수전용
 
23
상수도(음용)지하수(주방용)겸용
 
3

Length

Max length17
Median length4
Mean length4.3811765
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1088
64.0%
상수도전용 586
34.5%
지하수전용 23
 
1.4%
상수도(음용)지하수(주방용)겸용 3
 
0.2%

Length

2024-04-17T14:35:59.853458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T14:35:59.952585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1088
64.0%
상수도전용 586
34.5%
지하수전용 23
 
1.4%
상수도(음용)지하수(주방용)겸용 3
 
0.2%

총종업원수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1700
Missing (%)100.0%
Memory size15.1 KiB

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.4 KiB
<NA>
1694 
0
 
6

Length

Max length4
Median length4
Mean length3.9894118
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> 1694
99.6%
0 6
 
0.4%

Length

2024-04-17T14:36:00.062074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T14:36:00.153125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1694
99.6%
0 6
 
0.4%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.4 KiB
<NA>
1695 
0
 
5

Length

Max length4
Median length4
Mean length3.9911765
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> 1695
99.7%
0 5
 
0.3%

Length

2024-04-17T14:36:00.252283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T14:36:00.341155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1695
99.7%
0 5
 
0.3%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.4 KiB
<NA>
1695 
0
 
5

Length

Max length4
Median length4
Mean length3.9911765
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> 1695
99.7%
0 5
 
0.3%

Length

2024-04-17T14:36:00.436675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T14:36:00.526623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1695
99.7%
0 5
 
0.3%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.4 KiB
<NA>
1695 
0
 
5

Length

Max length4
Median length4
Mean length3.9911765
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> 1695
99.7%
0 5
 
0.3%

Length

2024-04-17T14:36:00.627804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T14:36:00.723311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1695
99.7%
0 5
 
0.3%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1700
Missing (%)100.0%
Memory size15.1 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.4 KiB
<NA>
1694 
0
 
6

Length

Max length4
Median length4
Mean length3.9894118
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> 1694
99.6%
0 6
 
0.4%

Length

2024-04-17T14:36:00.826268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T14:36:00.917798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1694
99.6%
0 6
 
0.4%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.4 KiB
<NA>
1694 
0
 
6

Length

Max length4
Median length4
Mean length3.9894118
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> 1694
99.6%
0 6
 
0.4%

Length

2024-04-17T14:36:01.022260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T14:36:01.124844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1694
99.6%
0 6
 
0.4%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
False
1700 
ValueCountFrequency (%)
False 1700
100.0%
2024-04-17T14:36:01.201510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

ZEROS 

Distinct978
Distinct (%)57.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean184.91569
Minimum0
Maximum4950
Zeros571
Zeros (%)33.6%
Negative0
Negative (%)0.0%
Memory size15.1 KiB
2024-04-17T14:36:01.297780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median116.515
Q3253.425
95-th percentile608.28
Maximum4950
Range4950
Interquartile range (IQR)253.425

Descriptive statistics

Standard deviation294.30984
Coefficient of variation (CV)1.5915893
Kurtosis61.273644
Mean184.91569
Median Absolute Deviation (MAD)116.515
Skewness5.7413877
Sum314356.68
Variance86618.283
MonotonicityNot monotonic
2024-04-17T14:36:01.415563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 571
33.6%
132.0 7
 
0.4%
168.22 4
 
0.2%
66.0 4
 
0.2%
12.0 4
 
0.2%
165.0 4
 
0.2%
131.04 4
 
0.2%
90.0 4
 
0.2%
300.0 4
 
0.2%
264.0 4
 
0.2%
Other values (968) 1090
64.1%
ValueCountFrequency (%)
0.0 571
33.6%
2.39 1
 
0.1%
3.88 1
 
0.1%
5.5 1
 
0.1%
5.66 1
 
0.1%
5.78 1
 
0.1%
5.94 1
 
0.1%
6.0 3
 
0.2%
6.3 1
 
0.1%
6.6 1
 
0.1%
ValueCountFrequency (%)
4950.0 1
0.1%
3412.2 1
0.1%
2923.72 1
0.1%
2593.8 1
0.1%
2115.0 1
0.1%
2088.92 1
0.1%
2036.23 1
0.1%
1932.68 1
0.1%
1914.01 1
0.1%
1914.0 1
0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1700
Missing (%)100.0%
Memory size15.1 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1700
Missing (%)100.0%
Memory size15.1 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1700
Missing (%)100.0%
Memory size15.1 KiB

Unnamed: 47
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1700
Missing (%)100.0%
Memory size15.1 KiB

Sample

번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지Unnamed: 47
01위탁급식영업07_21_01_P32500003250000-120-2008-0000120081222<NA>1영업/정상1영업<NA><NA><NA><NA>051 660 2401411.30600816부산광역시 중구 중앙동4가 74-1번지부산광역시 중구 충장대로13번길 67 (중앙동4가)48934웰리브디섹점20200427150246U2020-04-29 02:40:00.0위탁급식영업385873.204924181044.594333위탁급식영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N411.3<NA><NA><NA><NA>
12위탁급식영업07_21_01_P32500003250000-120-2009-0000120090303<NA>1영업/정상1영업<NA><NA><NA><NA>051 7187229443.75600015부산광역시 중구 중앙동5가 50번지부산광역시 중구 중앙대로 52 (중앙동5가)48942(주)아워홈엘지유플러스 중앙동사옥점20200326202336U2020-03-28 02:40:00.0위탁급식영업385650.848776180019.638851위탁급식영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N443.75<NA><NA><NA><NA>
23위탁급식영업07_21_01_P32500003250000-120-2003-0000120030523<NA>1영업/정상1영업<NA><NA><NA><NA>051 4630400308.00600816부산광역시 중구 중앙동4가 75-1부산광역시 중구 충장대로5번길 72 (중앙동4가)48934재단법인 케이티그룹희망나눔재단 서부산20210226142610U2021-02-28 02:40:00.0위탁급식영업385811.634937180996.883871위탁급식영업00<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N308.0<NA><NA><NA><NA>
34위탁급식영업07_21_01_P32500003250000-120-2003-0000320031009<NA>1영업/정상1영업<NA><NA><NA><NA>051 462846810.14600013부산광역시 중구 중앙동3가 18-1번지부산광역시 중구 대청로 135 (중앙동3가)48931씨제이프레시웨이 주식회사 SC은행부산점20161031151520I2018-08-31 23:59:59.0위탁급식영업385463.118214180123.108148위탁급식영업00<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N10.14<NA><NA><NA><NA>
45위탁급식영업07_21_01_P32500003250000-120-2006-0000120060403<NA>1영업/정상1영업<NA><NA><NA><NA>051 464 7307<NA>600814부산광역시 중구 중앙동4가 22-1번지부산광역시 중구 충장대로 6 (중앙동4가)48941(주)아워홈한진중공업중앙점20200313140101U2020-03-15 02:40:00.0위탁급식영업385668.490694180298.97818위탁급식영업00<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
56위탁급식영업07_21_01_P32500003250000-120-2006-0000220061012<NA>1영업/정상1영업<NA><NA><NA><NA>051 660 6323153.11600816부산광역시 중구 중앙동4가 74-11번지부산광역시 중구 중앙대로148번길 13 (중앙동4가)48934명문푸드서비스(주)(부산지방보훈청)20130814172229I2018-08-31 23:59:59.0위탁급식영업385849.59648180938.063707위탁급식영업00<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N153.11<NA><NA><NA><NA>
67위탁급식영업07_21_01_P32500003250000-120-2020-0000120200701<NA>1영업/정상1영업<NA><NA><NA><NA><NA>500.00600017부산광역시 중구 중앙동7가 20-1 롯데백화점광복점부산광역시 중구 중앙대로 2, 롯데백화점광복점 지하 2층 (중앙동7가)48944롯데푸드(주)롯데백화점 광복점20200701134359I2020-07-03 00:23:16.0위탁급식영업385590.814677179553.867032위탁급식영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N500.0<NA><NA><NA><NA>
78위탁급식영업07_21_01_P32500003250000-120-2007-0000120070424<NA>3폐업2폐업20100614<NA><NA><NA>051 244605946.02600023부산광역시 중구 동광동3가 1-2번지<NA><NA>선미식품20070424000000I2018-08-31 23:59:59.0위탁급식영업385426.971852180059.930553위탁급식영업00기타<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N46.02<NA><NA><NA><NA>
89위탁급식영업07_21_01_P32500003250000-120-2009-0000220091211<NA>3폐업2폐업20200630<NA><NA><NA>051 6782089499.71600017부산광역시 중구 중앙동7가 20-1 외 110필지 롯데백화점부산광역시 중구 중앙대로 2 (중앙동7가, 외 110필지 롯데백화점)48944(주) 엠푸드 롯데백화점 광복지점20200630152536U2020-07-02 02:40:00.0위탁급식영업385590.814677179553.867032위탁급식영업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N499.71<NA><NA><NA><NA>
910위탁급식영업07_21_01_P32500003250000-120-2011-0000120111209<NA>3폐업2폐업20150911<NA><NA><NA>070 77065826194.94600046부산광역시 중구 남포동6가 63번지부산광역시 중구 구덕로 90 (남포동6가)48981바른정형외과점20150716144057I2018-08-31 23:59:59.0위탁급식영업384670.317658179489.43507위탁급식영업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N194.94<NA><NA><NA><NA>
번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지Unnamed: 47
16901691위탁급식영업07_21_01_P33300003330000-120-2003-0001020030619<NA>3폐업2폐업20100105<NA><NA><NA>051 7426533<NA>612846부산광역시 해운대구 중동 1411-1번지<NA><NA>(주)에이텍서비스 파라다이스호텔20070102000000I2018-08-31 23:59:59.0위탁급식영업397114.551437186672.768207위탁급식영업00<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
16911692위탁급식영업07_21_01_P33300003330000-120-2003-0001220030621<NA>3폐업2폐업20120521<NA><NA><NA><NA><NA>612846부산광역시 해운대구 중동 1408-5번지부산광역시 해운대구 해운대해변로 296 (중동)48099삼성에버랜드(주)파라다이스호텔20120430163905I2018-08-31 23:59:59.0위탁급식영업397216.86091186702.956398위탁급식영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
16921693위탁급식영업07_21_01_P33300003330000-120-2003-0001120030621<NA>3폐업2폐업20071204<NA><NA><NA>051 5203000<NA>612809부산광역시 해운대구 반여동 791-1번지<NA><NA>(주)서원통상 동희정공점20051220000000I2018-08-31 23:59:59.0위탁급식영업<NA><NA>위탁급식영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
16931694위탁급식영업07_21_01_P33300003330000-120-2003-0001320030624<NA>3폐업2폐업20160706<NA><NA><NA>7315216<NA>612818부산광역시 해운대구 우동 278번지 해운대중,고등학교<NA><NA>(주)다조에프앤에스20070605000000I2018-08-31 23:59:59.0위탁급식영업<NA><NA>위탁급식영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
16941695위탁급식영업07_21_01_P33300003330000-120-2003-0001420030625<NA>3폐업2폐업20071119<NA><NA><NA>051 7833078<NA>612050부산광역시 해운대구 재송동 1329번지<NA><NA>(주)서원통상 기린반여점20040913000000I2018-08-31 23:59:59.0위탁급식영업392834.943298190123.491885위탁급식영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
16951696위탁급식영업07_21_01_P33300003330000-120-2003-0001520030627<NA>3폐업2폐업20091202<NA><NA><NA>051 7434448<NA>612823부산광역시 해운대구 우동 934-2번지<NA><NA>주식회사 남양도시락20030627000000I2018-08-31 23:59:59.0위탁급식영업395320.758711187448.045063위탁급식영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
16961697위탁급식영업07_21_01_P33300003330000-120-2003-0001620030627<NA>3폐업2폐업20101208<NA><NA><NA>051 5428881<NA>612802부산광역시 해운대구 반송동 248-1번지<NA><NA>농협외식사업단성심정보고점20090317154036I2018-08-31 23:59:59.0위탁급식영업396206.249746193917.505881위탁급식영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
16971698위탁급식영업07_21_01_P33300003330000-120-2018-0000320180409<NA>3폐업2폐업20190927<NA><NA><NA>051 973 4378<NA>612020부산광역시 해운대구 우동 1466-2번지 영상산업센터부산광역시 해운대구 센텀서로 39, 영상산업센터 4층 (우동)48058파머스푸드 영상산업센터점20190927165415U2019-09-29 02:40:00.0위탁급식영업393674.032956187973.297243위탁급식영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
16981699위탁급식영업07_21_01_P33300003330000-120-2015-0000420151229<NA>3폐업2폐업20171229<NA><NA><NA>051 850 7831429.00612832부산광역시 해운대구 재송동 1133번지부산광역시 해운대구 재반로112번길 19 (재송동)48053(주)에스에프에스 동부지청점20171229164146I2018-08-31 23:59:59.0위탁급식영업393868.994321189852.559798위탁급식영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N429.0<NA><NA><NA><NA>
16991700위탁급식영업07_21_01_P33300003330000-120-2020-0000220200604<NA>3폐업2폐업20200901<NA><NA><NA>051 702 137625.98612846부산광역시 해운대구 중동 1439-8부산광역시 해운대구 해운대로781번길 33, 4층 일부 (중동)48102맛있는 쿡20200901174711U2020-09-03 02:40:00.0위탁급식영업398074.12757188030.04337위탁급식영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N25.98<NA><NA><NA><NA>