Overview

Dataset statistics

Number of variables48
Number of observations1684
Missing cells21241
Missing cells (%)26.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory681.0 KiB
Average record size in memory414.1 B

Variable types

Numeric11
Categorical19
Text6
Unsupported10
DateTime1
Boolean1

Dataset

Description2021-01-04
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
업태구분명 has constant value ""Constant
위생업태명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (66.6%)Imbalance
영업장주변구분명 is highly imbalanced (86.0%)Imbalance
등급구분명 is highly imbalanced (86.9%)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 1684 (100.0%) missing valuesMissing
폐업일자 has 701 (41.6%) missing valuesMissing
휴업시작일자 has 1684 (100.0%) missing valuesMissing
휴업종료일자 has 1684 (100.0%) missing valuesMissing
재개업일자 has 1684 (100.0%) missing valuesMissing
소재지전화 has 399 (23.7%) missing valuesMissing
소재지면적 has 519 (30.8%) missing valuesMissing
소재지우편번호 has 65 (3.9%) missing valuesMissing
도로명전체주소 has 570 (33.8%) missing valuesMissing
도로명우편번호 has 587 (34.9%) missing valuesMissing
좌표정보(x) has 140 (8.3%) missing valuesMissing
좌표정보(y) has 140 (8.3%) missing valuesMissing
여성종사자수 has 1276 (75.8%) missing valuesMissing
총종업원수 has 1684 (100.0%) missing valuesMissing
건물소유구분명 has 1684 (100.0%) missing valuesMissing
전통업소지정번호 has 1684 (100.0%) missing valuesMissing
전통업소주된음식 has 1684 (100.0%) missing valuesMissing
홈페이지 has 1684 (100.0%) missing valuesMissing
Unnamed: 47 has 1684 (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 (19.6%) zerosZeros
시설총규모 has 566 (33.6%) zerosZeros

Reproduction

Analysis started2024-04-17 05:36:47.395899
Analysis finished2024-04-17 05:36:48.499063
Duration1.1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct1684
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean842.5
Minimum1
Maximum1684
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.9 KiB
2024-04-17T14:36:48.559486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile85.15
Q1421.75
median842.5
Q31263.25
95-th percentile1599.85
Maximum1684
Range1683
Interquartile range (IQR)841.5

Descriptive statistics

Standard deviation486.27324
Coefficient of variation (CV)0.57717892
Kurtosis-1.2
Mean842.5
Median Absolute Deviation (MAD)421
Skewness0
Sum1418770
Variance236461.67
MonotonicityStrictly increasing
2024-04-17T14:36:48.693579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
1108 1
 
0.1%
1132 1
 
0.1%
1131 1
 
0.1%
1130 1
 
0.1%
1129 1
 
0.1%
1128 1
 
0.1%
1127 1
 
0.1%
1126 1
 
0.1%
1125 1
 
0.1%
Other values (1674) 1674
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 (%)
1684 1
0.1%
1683 1
0.1%
1682 1
0.1%
1681 1
0.1%
1680 1
0.1%
1679 1
0.1%
1678 1
0.1%
1677 1
0.1%
1676 1
0.1%
1675 1
0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
위탁급식영업
1684 

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 1684
100.0%

Length

2024-04-17T14:36:48.805082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T14:36:48.925233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
위탁급식영업 1684
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
07_21_01_P
1684 

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 1684
100.0%

Length

2024-04-17T14:36:49.018057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T14:36:49.107897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_21_01_p 1684
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3342096.2
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.9 KiB
2024-04-17T14:36:49.187456image/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 deviation37452.29
Coefficient of variation (CV)0.011206227
Kurtosis-0.39032617
Mean3342096.2
Median Absolute Deviation (MAD)20000
Skewness-0.54844025
Sum5.62809 × 109
Variance1.402674 × 109
MonotonicityNot monotonic
2024-04-17T14:36:49.295060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3360000 505
30.0%
3340000 181
 
10.7%
3400000 127
 
7.5%
3390000 110
 
6.5%
3330000 109
 
6.5%
3310000 105
 
6.2%
3350000 86
 
5.1%
3290000 84
 
5.0%
3300000 69
 
4.1%
3370000 61
 
3.6%
Other values (6) 247
14.7%
ValueCountFrequency (%)
3250000 16
 
1.0%
3260000 55
 
3.3%
3270000 38
 
2.3%
3280000 55
 
3.3%
3290000 84
5.0%
3300000 69
 
4.1%
3310000 105
6.2%
3320000 45
 
2.7%
3330000 109
6.5%
3340000 181
10.7%
ValueCountFrequency (%)
3400000 127
 
7.5%
3390000 110
 
6.5%
3380000 38
 
2.3%
3370000 61
 
3.6%
3360000 505
30.0%
3350000 86
 
5.1%
3340000 181
 
10.7%
3330000 109
 
6.5%
3320000 45
 
2.7%
3310000 105
 
6.2%

관리번호
Text

UNIQUE 

Distinct1684
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
2024-04-17T14:36:49.489534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters37048
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

Unique1684 ?
Unique (%)100.0%

Sample

1st row3330000-120-2020-00007
2nd row3330000-120-2020-00006
3rd row3330000-120-2020-00005
4th row3330000-120-2020-00004
5th row3330000-120-2018-00005
ValueCountFrequency (%)
3330000-120-2020-00007 1
 
0.1%
3360000-120-2012-00009 1
 
0.1%
3360000-120-2007-00039 1
 
0.1%
3360000-120-2007-00040 1
 
0.1%
3360000-120-2007-00043 1
 
0.1%
3360000-120-2007-00045 1
 
0.1%
3360000-120-2010-00005 1
 
0.1%
3360000-120-2010-00006 1
 
0.1%
3360000-120-2010-00012 1
 
0.1%
3360000-120-2010-00014 1
 
0.1%
Other values (1674) 1674
99.4%
2024-04-17T14:36:49.815385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 17594
47.5%
- 5052
 
13.6%
2 4232
 
11.4%
3 3853
 
10.4%
1 3197
 
8.6%
6 886
 
2.4%
4 685
 
1.8%
9 411
 
1.1%
5 406
 
1.1%
7 398
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31996
86.4%
Dash Punctuation 5052
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 17594
55.0%
2 4232
 
13.2%
3 3853
 
12.0%
1 3197
 
10.0%
6 886
 
2.8%
4 685
 
2.1%
9 411
 
1.3%
5 406
 
1.3%
7 398
 
1.2%
8 334
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 5052
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 37048
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 17594
47.5%
- 5052
 
13.6%
2 4232
 
11.4%
3 3853
 
10.4%
1 3197
 
8.6%
6 886
 
2.4%
4 685
 
1.8%
9 411
 
1.1%
5 406
 
1.1%
7 398
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 37048
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 17594
47.5%
- 5052
 
13.6%
2 4232
 
11.4%
3 3853
 
10.4%
1 3197
 
8.6%
6 886
 
2.4%
4 685
 
1.8%
9 411
 
1.1%
5 406
 
1.1%
7 398
 
1.1%

인허가일자
Real number (ℝ)

Distinct1150
Distinct (%)68.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20095218
Minimum20030521
Maximum20201229
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.9 KiB
2024-04-17T14:36:49.961901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20030521
5-th percentile20030530
Q120040410
median20081004
Q320141006
95-th percentile20190821
Maximum20201229
Range170708
Interquartile range (IQR)100596.25

Descriptive statistics

Standard deviation55738.187
Coefficient of variation (CV)0.002773704
Kurtosis-1.1970938
Mean20095218
Median Absolute Deviation (MAD)49983.5
Skewness0.38081559
Sum3.3840348 × 1010
Variance3.1067455 × 109
MonotonicityNot monotonic
2024-04-17T14:36:50.120564image/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
 
1.0%
20030529 13
 
0.8%
20031015 12
 
0.7%
20030616 12
 
0.7%
20031013 11
 
0.7%
20030623 11
 
0.7%
20161101 9
 
0.5%
Other values (1140) 1527
90.7%
ValueCountFrequency (%)
20030521 1
 
0.1%
20030522 6
 
0.4%
20030523 7
 
0.4%
20030526 4
 
0.2%
20030527 16
1.0%
20030528 24
1.4%
20030529 13
0.8%
20030530 17
1.0%
20030531 2
 
0.1%
20030602 32
1.9%
ValueCountFrequency (%)
20201229 1
0.1%
20201215 2
0.1%
20201211 1
0.1%
20201209 1
0.1%
20201207 1
0.1%
20201201 1
0.1%
20201119 1
0.1%
20201118 1
0.1%
20201111 1
0.1%
20201109 2
0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1684
Missing (%)100.0%
Memory size14.9 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
3
983 
1
701 

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 (%)
3 983
58.4%
1 701
41.6%

Length

2024-04-17T14:36:50.247783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T14:36:50.340951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 983
58.4%
1 701
41.6%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
폐업
983 
영업/정상
701 

Length

Max length5
Median length2
Mean length3.2488124
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 983
58.4%
영업/정상 701
41.6%

Length

2024-04-17T14:36:50.435888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T14:36:50.532476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 983
58.4%
영업/정상 701
41.6%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
2
983 
1
701 

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 (%)
2 983
58.4%
1 701
41.6%

Length

2024-04-17T14:36:50.634403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T14:36:50.726007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 983
58.4%
1 701
41.6%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
폐업
983 
영업
701 

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 983
58.4%
영업 701
41.6%

Length

2024-04-17T14:36:50.812390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T14:36:50.903388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 983
58.4%
영업 701
41.6%

폐업일자
Real number (ℝ)

MISSING 

Distinct797
Distinct (%)81.1%
Missing701
Missing (%)41.6%
Infinite0
Infinite (%)0.0%
Mean20122463
Minimum20030923
Maximum20201231
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.9 KiB
2024-04-17T14:36:51.017273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20030923
5-th percentile20050526
Q120080928
median20120426
Q320161101
95-th percentile20200194
Maximum20201231
Range170308
Interquartile range (IQR)80173.5

Descriptive statistics

Standard deviation47068.651
Coefficient of variation (CV)0.0023391098
Kurtosis-1.1851089
Mean20122463
Median Absolute Deviation (MAD)40108
Skewness0.035821041
Sum1.9780381 × 1010
Variance2.2154579 × 109
MonotonicityNot monotonic
2024-04-17T14:36:51.167906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20161101 9
 
0.5%
20181231 5
 
0.3%
20171229 5
 
0.3%
20071001 4
 
0.2%
20100303 4
 
0.2%
20120102 4
 
0.2%
20180531 4
 
0.2%
20131231 3
 
0.2%
20151231 3
 
0.2%
20190430 3
 
0.2%
Other values (787) 939
55.8%
(Missing) 701
41.6%
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 (%)
20201231 2
0.1%
20201202 1
0.1%
20201123 1
0.1%
20201120 2
0.1%
20201111 1
0.1%
20201106 1
0.1%
20201105 2
0.1%
20201103 1
0.1%
20201030 1
0.1%
20201029 1
0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1684
Missing (%)100.0%
Memory size14.9 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1684
Missing (%)100.0%
Memory size14.9 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1684
Missing (%)100.0%
Memory size14.9 KiB

소재지전화
Text

MISSING 

Distinct1109
Distinct (%)86.3%
Missing399
Missing (%)23.7%
Memory size13.3 KiB
2024-04-17T14:36:51.516990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.297276
Min length3

Characters and Unicode

Total characters14517
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

Unique1017 ?
Unique (%)79.1%

Sample

1st row051 745 2046
2nd row051 702 3344
3rd row051 974 0700
4th row051 915 7474
5th row051 714 1322
ValueCountFrequency (%)
051 1044
33.9%
831 89
 
2.9%
055 53
 
1.7%
070 37
 
1.2%
02 16
 
0.5%
0102 15
 
0.5%
973 15
 
0.5%
2820 14
 
0.5%
3880 14
 
0.5%
633 14
 
0.5%
Other values (1307) 1770
57.4%
2024-04-17T14:36:52.214079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2419
16.7%
1 2179
15.0%
5 2016
13.9%
1813
12.5%
2 1092
7.5%
3 1066
7.3%
8 936
 
6.4%
7 838
 
5.8%
6 790
 
5.4%
4 704
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12704
87.5%
Space Separator 1813
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2419
19.0%
1 2179
17.2%
5 2016
15.9%
2 1092
8.6%
3 1066
8.4%
8 936
 
7.4%
7 838
 
6.6%
6 790
 
6.2%
4 704
 
5.5%
9 664
 
5.2%
Space Separator
ValueCountFrequency (%)
1813
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14517
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2419
16.7%
1 2179
15.0%
5 2016
13.9%
1813
12.5%
2 1092
7.5%
3 1066
7.3%
8 936
 
6.4%
7 838
 
5.8%
6 790
 
5.4%
4 704
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14517
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2419
16.7%
1 2179
15.0%
5 2016
13.9%
1813
12.5%
2 1092
7.5%
3 1066
7.3%
8 936
 
6.4%
7 838
 
5.8%
6 790
 
5.4%
4 704
 
4.8%

소재지면적
Text

MISSING 

Distinct982
Distinct (%)84.3%
Missing519
Missing (%)30.8%
Memory size13.3 KiB
2024-04-17T14:36:52.483280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length5.7545064
Min length3

Characters and Unicode

Total characters6704
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

Unique873 ?
Unique (%)74.9%

Sample

1st row5.66
2nd row2.39
3rd row3.88
4th row17.00
5th row6.70
ValueCountFrequency (%)
00 34
 
2.9%
132.00 7
 
0.6%
66.00 5
 
0.4%
165.00 4
 
0.3%
12.00 4
 
0.3%
70.00 4
 
0.3%
168.22 4
 
0.3%
131.04 4
 
0.3%
90.00 4
 
0.3%
300.00 4
 
0.3%
Other values (972) 1091
93.6%
2024-04-17T14:36:52.883507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1168
17.4%
. 1165
17.4%
1 761
11.4%
2 638
9.5%
4 479
7.1%
6 468
7.0%
3 467
 
7.0%
5 439
 
6.5%
8 371
 
5.5%
9 360
 
5.4%
Other values (2) 388
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5510
82.2%
Other Punctuation 1194
 
17.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1168
21.2%
1 761
13.8%
2 638
11.6%
4 479
8.7%
6 468
8.5%
3 467
 
8.5%
5 439
 
8.0%
8 371
 
6.7%
9 360
 
6.5%
7 359
 
6.5%
Other Punctuation
ValueCountFrequency (%)
. 1165
97.6%
, 29
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Common 6704
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1168
17.4%
. 1165
17.4%
1 761
11.4%
2 638
9.5%
4 479
7.1%
6 468
7.0%
3 467
 
7.0%
5 439
 
6.5%
8 371
 
5.5%
9 360
 
5.4%
Other values (2) 388
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6704
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1168
17.4%
. 1165
17.4%
1 761
11.4%
2 638
9.5%
4 479
7.1%
6 468
7.0%
3 467
 
7.0%
5 439
 
6.5%
8 371
 
5.5%
9 360
 
5.4%
Other values (2) 388
 
5.8%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct425
Distinct (%)26.3%
Missing65
Missing (%)3.9%
Infinite0
Infinite (%)0.0%
Mean612920.34
Minimum600013
Maximum619953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.9 KiB
2024-04-17T14:36:53.036647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600013
5-th percentile602702
Q1607838.5
median613828
Q3618280
95-th percentile618820
Maximum619953
Range19940
Interquartile range (IQR)10441.5

Descriptive statistics

Standard deviation5833.7192
Coefficient of variation (CV)0.0095179077
Kurtosis-1.1892093
Mean612920.34
Median Absolute Deviation (MAD)4989
Skewness-0.46958508
Sum9.9231803 × 108
Variance34032280
MonotonicityNot monotonic
2024-04-17T14:36:53.197515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
618819 71
 
4.2%
618817 70
 
4.2%
618230 60
 
3.6%
618818 57
 
3.4%
618820 55
 
3.3%
604836 47
 
2.8%
618280 33
 
2.0%
618220 28
 
1.7%
618250 19
 
1.1%
604826 18
 
1.1%
Other values (415) 1161
68.9%
(Missing) 65
 
3.9%
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
1.0%
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%
Distinct1449
Distinct (%)86.2%
Missing4
Missing (%)0.2%
Memory size13.3 KiB
2024-04-17T14:36:53.533545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length46
Mean length23.83631
Min length16

Characters and Unicode

Total characters40045
Distinct characters355
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

Unique1277 ?
Unique (%)76.0%

Sample

1st row부산광역시 해운대구 우동 1493 센텀시티 몰
2nd row부산광역시 해운대구 송정동 306-4
3rd row부산광역시 해운대구 중동 1405-16 그랜드 조선 부산
4th row부산광역시 해운대구 중동 1227-2 해운대빌딩
5th row부산광역시 해운대구 석대동 609번지
ValueCountFrequency (%)
부산광역시 1680
 
21.8%
강서구 503
 
6.5%
송정동 260
 
3.4%
사하구 181
 
2.3%
기장군 126
 
1.6%
사상구 110
 
1.4%
해운대구 109
 
1.4%
남구 105
 
1.4%
95
 
1.2%
금정구 85
 
1.1%
Other values (1855) 4464
57.8%
2024-04-17T14:36:54.001585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6042
 
15.1%
2063
 
5.2%
1 1957
 
4.9%
1941
 
4.8%
1838
 
4.6%
1759
 
4.4%
1708
 
4.3%
1697
 
4.2%
1683
 
4.2%
1636
 
4.1%
Other values (345) 17721
44.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25072
62.6%
Decimal Number 7349
 
18.4%
Space Separator 6042
 
15.1%
Dash Punctuation 1230
 
3.1%
Uppercase Letter 108
 
0.3%
Open Punctuation 105
 
0.3%
Close Punctuation 104
 
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 (%)
2063
 
8.2%
1941
 
7.7%
1838
 
7.3%
1759
 
7.0%
1708
 
6.8%
1697
 
6.8%
1683
 
6.7%
1636
 
6.5%
1567
 
6.2%
591
 
2.4%
Other values (303) 8589
34.3%
Uppercase Letter
ValueCountFrequency (%)
B 25
23.1%
A 18
16.7%
I 12
11.1%
C 9
 
8.3%
T 8
 
7.4%
K 8
 
7.4%
S 7
 
6.5%
L 6
 
5.6%
H 2
 
1.9%
R 2
 
1.9%
Other values (8) 11
10.2%
Decimal Number
ValueCountFrequency (%)
1 1957
26.6%
2 739
 
10.1%
5 735
 
10.0%
4 665
 
9.0%
3 657
 
8.9%
6 600
 
8.2%
0 542
 
7.4%
7 516
 
7.0%
8 509
 
6.9%
9 429
 
5.8%
Other Punctuation
ValueCountFrequency (%)
, 19
63.3%
& 5
 
16.7%
. 3
 
10.0%
: 2
 
6.7%
/ 1
 
3.3%
Open Punctuation
ValueCountFrequency (%)
( 104
99.0%
[ 1
 
1.0%
Close Punctuation
ValueCountFrequency (%)
) 103
99.0%
] 1
 
1.0%
Lowercase Letter
ValueCountFrequency (%)
i 3
75.0%
o 1
 
25.0%
Space Separator
ValueCountFrequency (%)
6042
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1230
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25072
62.6%
Common 14861
37.1%
Latin 112
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2063
 
8.2%
1941
 
7.7%
1838
 
7.3%
1759
 
7.0%
1708
 
6.8%
1697
 
6.8%
1683
 
6.7%
1636
 
6.5%
1567
 
6.2%
591
 
2.4%
Other values (303) 8589
34.3%
Common
ValueCountFrequency (%)
6042
40.7%
1 1957
 
13.2%
- 1230
 
8.3%
2 739
 
5.0%
5 735
 
4.9%
4 665
 
4.5%
3 657
 
4.4%
6 600
 
4.0%
0 542
 
3.6%
7 516
 
3.5%
Other values (12) 1178
 
7.9%
Latin
ValueCountFrequency (%)
B 25
22.3%
A 18
16.1%
I 12
10.7%
C 9
 
8.0%
T 8
 
7.1%
K 8
 
7.1%
S 7
 
6.2%
L 6
 
5.4%
i 3
 
2.7%
H 2
 
1.8%
Other values (10) 14
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25072
62.6%
ASCII 14973
37.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6042
40.4%
1 1957
 
13.1%
- 1230
 
8.2%
2 739
 
4.9%
5 735
 
4.9%
4 665
 
4.4%
3 657
 
4.4%
6 600
 
4.0%
0 542
 
3.6%
7 516
 
3.4%
Other values (32) 1290
 
8.6%
Hangul
ValueCountFrequency (%)
2063
 
8.2%
1941
 
7.7%
1838
 
7.3%
1759
 
7.0%
1708
 
6.8%
1697
 
6.8%
1683
 
6.7%
1636
 
6.5%
1567
 
6.2%
591
 
2.4%
Other values (303) 8589
34.3%

도로명전체주소
Text

MISSING 

Distinct1031
Distinct (%)92.5%
Missing570
Missing (%)33.8%
Memory size13.3 KiB
2024-04-17T14:36:54.351249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length47
Mean length29.64632
Min length20

Characters and Unicode

Total characters33026
Distinct characters370
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

Unique959 ?
Unique (%)86.1%

Sample

1st row부산광역시 해운대구 센텀4로 15, 센텀시티 몰 지하2층 (우동)
2nd row부산광역시 해운대구 송정1로7번길 30-5, 1층 일부 (송정동)
3rd row부산광역시 해운대구 해운대해변로 292, 그랜드 조선 부산 지하2층 일부 (중동)
4th row부산광역시 해운대구 중동2로10번길 29, 해운대빌딩 3층 301호 (중동)
5th row부산광역시 해운대구 반송로513번길 66-48, 3층 (석대동)
ValueCountFrequency (%)
부산광역시 1114
 
17.5%
강서구 382
 
6.0%
송정동 186
 
2.9%
사하구 124
 
1.9%
1층 109
 
1.7%
해운대구 81
 
1.3%
기장군 79
 
1.2%
사상구 72
 
1.1%
남구 56
 
0.9%
금정구 54
 
0.8%
Other values (1316) 4125
64.6%
2024-04-17T14:36:54.785124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5268
 
16.0%
1847
 
5.6%
1319
 
4.0%
1303
 
3.9%
1145
 
3.5%
1139
 
3.4%
1116
 
3.4%
( 1114
 
3.4%
) 1112
 
3.4%
1100
 
3.3%
Other values (360) 16563
50.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20148
61.0%
Space Separator 5268
 
16.0%
Decimal Number 4645
 
14.1%
Open Punctuation 1114
 
3.4%
Close Punctuation 1112
 
3.4%
Other Punctuation 552
 
1.7%
Uppercase Letter 97
 
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 (%)
1847
 
9.2%
1319
 
6.5%
1303
 
6.5%
1145
 
5.7%
1139
 
5.7%
1116
 
5.5%
1100
 
5.5%
1097
 
5.4%
492
 
2.4%
446
 
2.2%
Other values (320) 9144
45.4%
Uppercase Letter
ValueCountFrequency (%)
B 20
20.6%
A 17
17.5%
C 13
13.4%
K 8
 
8.2%
S 7
 
7.2%
T 6
 
6.2%
N 4
 
4.1%
I 4
 
4.1%
G 3
 
3.1%
E 3
 
3.1%
Other values (8) 12
12.4%
Decimal Number
ValueCountFrequency (%)
1 1013
21.8%
2 705
15.2%
3 580
12.5%
4 413
8.9%
6 403
 
8.7%
5 383
 
8.2%
0 325
 
7.0%
7 316
 
6.8%
9 280
 
6.0%
8 227
 
4.9%
Lowercase Letter
ValueCountFrequency (%)
e 2
40.0%
l 1
20.0%
t 1
20.0%
o 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 547
99.1%
& 4
 
0.7%
: 1
 
0.2%
Space Separator
ValueCountFrequency (%)
5268
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1114
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1112
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 80
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20148
61.0%
Common 12776
38.7%
Latin 102
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1847
 
9.2%
1319
 
6.5%
1303
 
6.5%
1145
 
5.7%
1139
 
5.7%
1116
 
5.5%
1100
 
5.5%
1097
 
5.4%
492
 
2.4%
446
 
2.2%
Other values (320) 9144
45.4%
Latin
ValueCountFrequency (%)
B 20
19.6%
A 17
16.7%
C 13
12.7%
K 8
 
7.8%
S 7
 
6.9%
T 6
 
5.9%
N 4
 
3.9%
I 4
 
3.9%
G 3
 
2.9%
E 3
 
2.9%
Other values (12) 17
16.7%
Common
ValueCountFrequency (%)
5268
41.2%
( 1114
 
8.7%
) 1112
 
8.7%
1 1013
 
7.9%
2 705
 
5.5%
3 580
 
4.5%
, 547
 
4.3%
4 413
 
3.2%
6 403
 
3.2%
5 383
 
3.0%
Other values (8) 1238
 
9.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20148
61.0%
ASCII 12878
39.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5268
40.9%
( 1114
 
8.7%
) 1112
 
8.6%
1 1013
 
7.9%
2 705
 
5.5%
3 580
 
4.5%
, 547
 
4.2%
4 413
 
3.2%
6 403
 
3.1%
5 383
 
3.0%
Other values (30) 1340
 
10.4%
Hangul
ValueCountFrequency (%)
1847
 
9.2%
1319
 
6.5%
1303
 
6.5%
1145
 
5.7%
1139
 
5.7%
1116
 
5.5%
1100
 
5.5%
1097
 
5.4%
492
 
2.4%
446
 
2.2%
Other values (320) 9144
45.4%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct382
Distinct (%)34.8%
Missing587
Missing (%)34.9%
Infinite0
Infinite (%)0.0%
Mean47485.331
Minimum46002
Maximum49526
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.9 KiB
2024-04-17T14:36:54.931085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46002
5-th percentile46034
Q146742
median46942
Q348400
95-th percentile49460
Maximum49526
Range3524
Interquartile range (IQR)1658

Descriptive statistics

Standard deviation1089.6625
Coefficient of variation (CV)0.022947349
Kurtosis-0.98316483
Mean47485.331
Median Absolute Deviation (MAD)610
Skewness0.62140458
Sum52091408
Variance1187364.3
MonotonicityNot monotonic
2024-04-17T14:36:55.066870image/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 30
 
1.8%
46754 29
 
1.7%
46751 27
 
1.6%
46755 23
 
1.4%
46744 18
 
1.1%
46027 15
 
0.9%
46727 14
 
0.8%
Other values (372) 821
48.8%
(Missing) 587
34.9%
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 1
 
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%
Distinct1570
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
2024-04-17T14:36:55.306273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length24
Mean length11.348575
Min length2

Characters and Unicode

Total characters19111
Distinct characters515
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

Unique1484 ?
Unique (%)88.1%

Sample

1st row신세계푸드(센텀시티몰)
2nd row푸디스트(주)해운대실버홈점
3rd row신세계푸드 그랜드조선부산
4th row주식회사 푸드샘-어르신학교데이케어센터점
5th row우리식당
ValueCountFrequency (%)
구내식당 65
 
2.6%
주)아워홈 40
 
1.6%
주)풀무원푸드앤컬처 36
 
1.4%
주)새손 34
 
1.3%
주)호성식품 31
 
1.2%
주식회사 30
 
1.2%
주)동원홈푸드 28
 
1.1%
주)삼보유통 27
 
1.1%
주)신세계푸드 17
 
0.7%
주)현대그린푸드 15
 
0.6%
Other values (1761) 2206
87.2%
2024-04-17T14:36:55.689606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 963
 
5.0%
942
 
4.9%
( 940
 
4.9%
846
 
4.4%
713
 
3.7%
521
 
2.7%
491
 
2.6%
421
 
2.2%
412
 
2.2%
389
 
2.0%
Other values (505) 12473
65.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16092
84.2%
Close Punctuation 964
 
5.0%
Open Punctuation 941
 
4.9%
Space Separator 846
 
4.4%
Uppercase Letter 197
 
1.0%
Decimal Number 34
 
0.2%
Other Punctuation 24
 
0.1%
Dash Punctuation 9
 
< 0.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
942
 
5.9%
713
 
4.4%
521
 
3.2%
491
 
3.1%
421
 
2.6%
412
 
2.6%
389
 
2.4%
386
 
2.4%
384
 
2.4%
339
 
2.1%
Other values (459) 11094
68.9%
Uppercase Letter
ValueCountFrequency (%)
S 37
18.8%
C 23
11.7%
T 20
10.2%
K 17
8.6%
F 17
8.6%
G 12
 
6.1%
N 9
 
4.6%
J 9
 
4.6%
E 6
 
3.0%
B 6
 
3.0%
Other values (14) 41
20.8%
Decimal Number
ValueCountFrequency (%)
2 13
38.2%
1 8
23.5%
3 6
17.6%
7 2
 
5.9%
5 2
 
5.9%
0 2
 
5.9%
4 1
 
2.9%
Other Punctuation
ValueCountFrequency (%)
. 12
50.0%
& 7
29.2%
/ 3
 
12.5%
· 1
 
4.2%
, 1
 
4.2%
Lowercase Letter
ValueCountFrequency (%)
w 1
25.0%
p 1
25.0%
s 1
25.0%
k 1
25.0%
Close Punctuation
ValueCountFrequency (%)
) 963
99.9%
] 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 940
99.9%
[ 1
 
0.1%
Space Separator
ValueCountFrequency (%)
846
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16092
84.2%
Common 2818
 
14.7%
Latin 201
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
942
 
5.9%
713
 
4.4%
521
 
3.2%
491
 
3.1%
421
 
2.6%
412
 
2.6%
389
 
2.4%
386
 
2.4%
384
 
2.4%
339
 
2.1%
Other values (459) 11094
68.9%
Latin
ValueCountFrequency (%)
S 37
18.4%
C 23
11.4%
T 20
10.0%
K 17
 
8.5%
F 17
 
8.5%
G 12
 
6.0%
N 9
 
4.5%
J 9
 
4.5%
E 6
 
3.0%
B 6
 
3.0%
Other values (18) 45
22.4%
Common
ValueCountFrequency (%)
) 963
34.2%
( 940
33.4%
846
30.0%
2 13
 
0.5%
. 12
 
0.4%
- 9
 
0.3%
1 8
 
0.3%
& 7
 
0.2%
3 6
 
0.2%
/ 3
 
0.1%
Other values (8) 11
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16092
84.2%
ASCII 3018
 
15.8%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 963
31.9%
( 940
31.1%
846
28.0%
S 37
 
1.2%
C 23
 
0.8%
T 20
 
0.7%
K 17
 
0.6%
F 17
 
0.6%
2 13
 
0.4%
G 12
 
0.4%
Other values (35) 130
 
4.3%
Hangul
ValueCountFrequency (%)
942
 
5.9%
713
 
4.4%
521
 
3.2%
491
 
3.1%
421
 
2.6%
412
 
2.6%
389
 
2.4%
386
 
2.4%
384
 
2.4%
339
 
2.1%
Other values (459) 11094
68.9%
None
ValueCountFrequency (%)
· 1
100.0%

최종수정시점
Real number (ℝ)

Distinct1550
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0135888 × 1013
Minimum2.0030522 × 1013
Maximum2.0201231 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.9 KiB
2024-04-17T14:36:55.819105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0030522 × 1013
5-th percentile2.003101 × 1013
Q12.0081019 × 1013
median2.0150928 × 1013
Q32.0190211 × 1013
95-th percentile2.0200822 × 1013
Maximum2.0201231 × 1013
Range1.7070917 × 1011
Interquartile range (IQR)1.0919246 × 1011

Descriptive statistics

Standard deviation5.7021577 × 1010
Coefficient of variation (CV)0.0028318381
Kurtosis-1.1718446
Mean2.0135888 × 1013
Median Absolute Deviation (MAD)4.0222429 × 1010
Skewness-0.4942045
Sum3.3908836 × 1016
Variance3.2514602 × 1021
MonotonicityNot monotonic
2024-04-17T14:36:55.952389image/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%
20050203000000 5
 
0.3%
20030623000000 5
 
0.3%
20030530000000 5
 
0.3%
20030528000000 5
 
0.3%
Other values (1540) 1602
95.1%
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 (%)
20201231172751 1
0.1%
20201231142007 1
0.1%
20201231135322 1
0.1%
20201231093112 1
0.1%
20201229163817 1
0.1%
20201229132026 1
0.1%
20201228144426 1
0.1%
20201228144332 1
0.1%
20201224140215 1
0.1%
20201218194645 1
0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
I
1213 
U
471 

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 1213
72.0%
U 471
 
28.0%

Length

2024-04-17T14:36:56.078665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T14:36:56.178164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1213
72.0%
u 471
 
28.0%
Distinct305
Distinct (%)18.1%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
Minimum2018-08-31 23:59:59
Maximum2021-01-02 02:40:00
2024-04-17T14:36:56.274997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T14:36:56.411161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
위탁급식영업
1684 

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 1684
100.0%

Length

2024-04-17T14:36:56.527567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T14:36:56.616430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
위탁급식영업 1684
100.0%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct1108
Distinct (%)71.8%
Missing140
Missing (%)8.3%
Infinite0
Infinite (%)0.0%
Mean382310.54
Minimum365010.39
Maximum407785.94
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.9 KiB
2024-04-17T14:36:56.719161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum365010.39
5-th percentile366621.37
Q1371065.51
median383088.97
Q3389910.43
95-th percentile399055.46
Maximum407785.94
Range42775.552
Interquartile range (IQR)18844.922

Descriptive statistics

Standard deviation10543.673
Coefficient of variation (CV)0.027578817
Kurtosis-0.95589865
Mean382310.54
Median Absolute Deviation (MAD)8074.6037
Skewness0.0020808913
Sum5.9028748 × 108
Variance1.1116903 × 108
MonotonicityNot monotonic
2024-04-17T14:36:56.840471image/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%
389087.131613449 6
 
0.4%
383317.542366441 6
 
0.4%
384030.498741004 6
 
0.4%
381979.829708763 5
 
0.3%
380039.42787448 5
 
0.3%
Other values (1098) 1466
87.1%
(Missing) 140
 
8.3%
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 

Distinct1108
Distinct (%)71.8%
Missing140
Missing (%)8.3%
Infinite0
Infinite (%)0.0%
Mean185055.07
Minimum174279.76
Maximum210424.66
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.9 KiB
2024-04-17T14:36:56.981789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum174279.76
5-th percentile177113.56
Q1178899.67
median183989.42
Q3189021.45
95-th percentile203778.51
Maximum210424.66
Range36144.896
Interquartile range (IQR)10121.787

Descriptive statistics

Standard deviation7404.8598
Coefficient of variation (CV)0.040014359
Kurtosis0.77869311
Mean185055.07
Median Absolute Deviation (MAD)5090.1475
Skewness1.0769998
Sum2.8572502 × 108
Variance54831949
MonotonicityNot monotonic
2024-04-17T14:36:57.119743image/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%
198411.005541894 6
 
0.4%
185013.86379536 6
 
0.4%
179806.024724594 6
 
0.4%
180171.574433073 5
 
0.3%
185929.061224432 5
 
0.3%
Other values (1098) 1466
87.1%
(Missing) 140
 
8.3%
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

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
위탁급식영업
1684 

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 1684
100.0%

Length

2024-04-17T14:36:57.243273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T14:36:57.331257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
위탁급식영업 1684
100.0%

남성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
<NA>
1297 
0
365 
1
 
17
2
 
3
3
 
1

Length

Max length4
Median length4
Mean length3.3105701
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row1

Common Values

ValueCountFrequency (%)
<NA> 1297
77.0%
0 365
 
21.7%
1 17
 
1.0%
2 3
 
0.2%
3 1
 
0.1%
5 1
 
0.1%

Length

2024-04-17T14:36:57.425836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T14:36:57.563742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1297
77.0%
0 365
 
21.7%
1 17
 
1.0%
2 3
 
0.2%
3 1
 
0.1%
5 1
 
0.1%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct15
Distinct (%)3.7%
Missing1276
Missing (%)75.8%
Infinite0
Infinite (%)0.0%
Mean0.78676471
Minimum0
Maximum20
Zeros330
Zeros (%)19.6%
Negative0
Negative (%)0.0%
Memory size14.9 KiB
2024-04-17T14:36:57.663461image/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
2024-04-17T14:36:57.773032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 330
 
19.6%
2 20
 
1.2%
4 15
 
0.9%
3 13
 
0.8%
1 11
 
0.7%
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) 1276
75.8%
ValueCountFrequency (%)
0 330
19.6%
1 11
 
0.7%
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 size13.3 KiB
<NA>
1575 
기타
 
88
주택가주변
 
7
아파트지역
 
5
학교정화(절대)
 
4
Other values (3)
 
5

Length

Max length8
Median length4
Mean length3.9233967
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> 1575
93.5%
기타 88
 
5.2%
주택가주변 7
 
0.4%
아파트지역 5
 
0.3%
학교정화(절대) 4
 
0.2%
유흥업소밀집지역 3
 
0.2%
학교정화(상대) 1
 
0.1%
결혼예식장주변 1
 
0.1%

Length

2024-04-17T14:36:57.903906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T14:36:58.033373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1575
93.5%
기타 88
 
5.2%
주택가주변 7
 
0.4%
아파트지역 5
 
0.3%
학교정화(절대 4
 
0.2%
유흥업소밀집지역 3
 
0.2%
학교정화(상대 1
 
0.1%
결혼예식장주변 1
 
0.1%

등급구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
<NA>
1637 
자율
 
33
기타
 
14

Length

Max length4
Median length4
Mean length3.9441805
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1637
97.2%
자율 33
 
2.0%
기타 14
 
0.8%

Length

2024-04-17T14:36:58.161658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T14:36:58.260754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1637
97.2%
자율 33
 
2.0%
기타 14
 
0.8%
Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
<NA>
1073 
상수도전용
585 
지하수전용
 
23
상수도(음용)지하수(주방용)겸용
 
3

Length

Max length17
Median length4
Mean length4.3842043
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1073
63.7%
상수도전용 585
34.7%
지하수전용 23
 
1.4%
상수도(음용)지하수(주방용)겸용 3
 
0.2%

Length

2024-04-17T14:36:58.367912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T14:36:58.461331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1073
63.7%
상수도전용 585
34.7%
지하수전용 23
 
1.4%
상수도(음용)지하수(주방용)겸용 3
 
0.2%

총종업원수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1684
Missing (%)100.0%
Memory size14.9 KiB

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
<NA>
1678 
0
 
6

Length

Max length4
Median length4
Mean length3.9893112
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> 1678
99.6%
0 6
 
0.4%

Length

2024-04-17T14:36:58.852207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T14:36:58.937690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1678
99.6%
0 6
 
0.4%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
<NA>
1679 
0
 
5

Length

Max length4
Median length4
Mean length3.9910926
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> 1679
99.7%
0 5
 
0.3%

Length

2024-04-17T14:36:59.042387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T14:36:59.136988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1679
99.7%
0 5
 
0.3%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
<NA>
1679 
0
 
5

Length

Max length4
Median length4
Mean length3.9910926
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> 1679
99.7%
0 5
 
0.3%

Length

2024-04-17T14:36:59.234581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T14:36:59.324551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1679
99.7%
0 5
 
0.3%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
<NA>
1679 
0
 
5

Length

Max length4
Median length4
Mean length3.9910926
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> 1679
99.7%
0 5
 
0.3%

Length

2024-04-17T14:36:59.420467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T14:36:59.518560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1679
99.7%
0 5
 
0.3%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1684
Missing (%)100.0%
Memory size14.9 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
<NA>
1678 
0
 
6

Length

Max length4
Median length4
Mean length3.9893112
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> 1678
99.6%
0 6
 
0.4%

Length

2024-04-17T14:36:59.619004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T14:36:59.714925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1678
99.6%
0 6
 
0.4%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
<NA>
1678 
0
 
6

Length

Max length4
Median length4
Mean length3.9893112
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> 1678
99.6%
0 6
 
0.4%

Length

2024-04-17T14:36:59.806743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T14:36:59.899095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1678
99.6%
0 6
 
0.4%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
False
1684 
ValueCountFrequency (%)
False 1684
100.0%
2024-04-17T14:36:59.973895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

ZEROS 

Distinct971
Distinct (%)57.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean183.8308
Minimum0
Maximum4950
Zeros566
Zeros (%)33.6%
Negative0
Negative (%)0.0%
Memory size14.9 KiB
2024-04-17T14:37:00.076802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median116.05
Q3252.985
95-th percentile602.55
Maximum4950
Range4950
Interquartile range (IQR)252.985

Descriptive statistics

Standard deviation291.80574
Coefficient of variation (CV)1.5873605
Kurtosis63.480633
Mean183.8308
Median Absolute Deviation (MAD)116.05
Skewness5.8274006
Sum309571.06
Variance85150.587
MonotonicityNot monotonic
2024-04-17T14:37:00.205218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 566
33.6%
132.0 7
 
0.4%
168.22 4
 
0.2%
70.0 4
 
0.2%
131.04 4
 
0.2%
90.0 4
 
0.2%
66.0 4
 
0.2%
165.0 4
 
0.2%
264.0 4
 
0.2%
300.0 4
 
0.2%
Other values (961) 1079
64.1%
ValueCountFrequency (%)
0.0 566
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%
1914.0 1
0.1%
1592.96 1
0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1684
Missing (%)100.0%
Memory size14.9 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1684
Missing (%)100.0%
Memory size14.9 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1684
Missing (%)100.0%
Memory size14.9 KiB

Unnamed: 47
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1684
Missing (%)100.0%
Memory size14.9 KiB

Sample

번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지Unnamed: 47
01위탁급식영업07_21_01_P33300003330000-120-2020-0000720201207<NA>1영업/정상1영업<NA><NA><NA><NA>051 745 20465.66612020부산광역시 해운대구 우동 1493 센텀시티 몰부산광역시 해운대구 센텀4로 15, 센텀시티 몰 지하2층 (우동)48058신세계푸드(센텀시티몰)20201224140215U2020-12-26 02:40:00.0위탁급식영업393825.077518187704.240303위탁급식영업<NA><NA><NA>자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N5.66<NA><NA><NA><NA>
12위탁급식영업07_21_01_P33300003330000-120-2020-0000620200928<NA>1영업/정상1영업<NA><NA><NA><NA>051 702 33442.39612040부산광역시 해운대구 송정동 306-4부산광역시 해운대구 송정1로7번길 30-5, 1층 일부 (송정동)48068푸디스트(주)해운대실버홈점20201008143801U2020-10-10 02:40:00.0위탁급식영업400139.91814189094.280885위탁급식영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N2.39<NA><NA><NA><NA>
23위탁급식영업07_21_01_P33300003330000-120-2020-0000520200922<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.88612846부산광역시 해운대구 중동 1405-16 그랜드 조선 부산부산광역시 해운대구 해운대해변로 292, 그랜드 조선 부산 지하2층 일부 (중동)48099신세계푸드 그랜드조선부산20200928131840U2020-09-30 02:40:00.0위탁급식영업397022.97155186692.064622위탁급식영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N3.88<NA><NA><NA><NA>
34위탁급식영업07_21_01_P33300003330000-120-2020-0000420200902<NA>1영업/정상1영업<NA><NA><NA><NA>051 974 070017.00612847부산광역시 해운대구 중동 1227-2 해운대빌딩부산광역시 해운대구 중동2로10번길 29, 해운대빌딩 3층 301호 (중동)48096주식회사 푸드샘-어르신학교데이케어센터점20200902132449I2020-09-04 00:23:13.0위탁급식영업397263.861949187085.533914위탁급식영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N17.0<NA><NA><NA><NA>
45위탁급식영업07_21_01_P33300003330000-120-2018-0000520180914<NA>1영업/정상1영업<NA><NA><NA><NA><NA>6.70612070부산광역시 해운대구 석대동 609번지부산광역시 해운대구 반송로513번길 66-48, 3층 (석대동)48002우리식당20180921112616U2018-09-21 23:59:59.0위탁급식영업392951.789079193732.190684위탁급식영업12<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N6.7<NA><NA><NA><NA>
56위탁급식영업07_21_01_P33300003330000-120-2020-0000320200828<NA>1영업/정상1영업<NA><NA><NA><NA>051 915 747427.59612836부산광역시 해운대구 좌동 1461-1 울트라타워 4층부산광역시 해운대구 좌동로 88, 울트라타워 4층 (좌동)48106다조에프앤에스20200902131319U2020-09-04 02:40:00.0위탁급식영업398074.12757188030.04337위탁급식영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N27.59<NA><NA><NA><NA>
67위탁급식영업07_21_01_P33300003330000-120-2020-0000120200313<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.05612010부산광역시 해운대구 중동 1829번지 엘시티부산광역시 해운대구 달맞이길 30, 지하1층 (중동, 엘시티)48099롯데푸드 (주) 호텔시그니엘부산점20200326164916U2020-03-28 02:40:00.0위탁급식영업<NA><NA>위탁급식영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
78위탁급식영업07_21_01_P33300003330000-120-2019-0000820191004<NA>1영업/정상1영업<NA><NA><NA><NA>051 714 132210.96612020부산광역시 해운대구 우동 1466-2번지 영상산업센터부산광역시 해운대구 센텀서로 39, 영상산업센터 4층 (우동)48058(주)가내찬 영상산업센터점20191008141642U2019-10-10 02:40:00.0위탁급식영업393674.032956187973.297243위탁급식영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N10.96<NA><NA><NA><NA>
89위탁급식영업07_21_01_P33300003330000-120-2018-0000420180615<NA>1영업/정상1영업<NA><NA><NA><NA>051 797 669518.10612070부산광역시 해운대구 석대동 621번지부산광역시 해운대구 반송로513번길 66-25, 삼원FA 식당 4층 (석대동)48002엠푸드20180620115719I2018-08-31 23:59:59.0위탁급식영업392845.379088193497.363587위탁급식영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N18.1<NA><NA><NA><NA>
910위탁급식영업07_21_01_P33300003330000-120-2019-0000720190926<NA>1영업/정상1영업<NA><NA><NA><NA>051 746 106525.64612820부산광역시 해운대구 우동 524-5번지 에이치스위트 해운대부산광역시 해운대구 해운대로 601, 에이치스위트 해운대 B동 3층 (우동)48087에이치스위트 해운대점20191008141259U2019-10-10 02:40:00.0위탁급식영업396451.865582186987.11881위탁급식영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N25.64<NA><NA><NA><NA>
번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지Unnamed: 47
16741675위탁급식영업07_21_01_P33000003300000-120-2003-0001020030902<NA>3폐업2폐업20070104<NA><NA><NA>051 5281749<NA>607810부산광역시 동래구 명장동 산 14-2번지<NA><NA>주)진아 혜화여고 급식소20030902000000I2018-08-31 23:59:59.0위탁급식영업<NA><NA>위탁급식영업00<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
16751676위탁급식영업07_21_01_P32500003250000-120-2005-0000120050705<NA>3폐업2폐업20081001<NA><NA><NA><NA>9.62600015부산광역시 중구 중앙동5가 15-1번지<NA><NA>(주)이씨엠디증권선물거래소20050705000000I2018-08-31 23:59:59.0위탁급식영업385768.102867179934.163457위탁급식영업14<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N9.62<NA><NA><NA><NA>
16761677위탁급식영업07_21_01_P32500003250000-120-2003-0000520031224<NA>3폐업2폐업20160224<NA><NA><NA>051468 7985<NA>600013부산광역시 중구 중앙동3가 1번지부산광역시 중구 중앙대로 63 (중앙동3가)48931다와푸드20130725144023I2018-08-31 23:59:59.0위탁급식영업385561.650139180152.738082위탁급식영업00기타<NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
16771678위탁급식영업07_21_01_P32500003250000-120-2003-0000420031106<NA>3폐업2폐업20120601<NA><NA><NA>051 6033455169.84600816부산광역시 중구 중앙동4가 79-9번지부산광역시 중구 충장대로9번길 46 (중앙동4가)48936(주)신세계푸드한진해운부산20120127154403I2018-08-31 23:59:59.0위탁급식영업385801.526605180799.204372위탁급식영업00<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N169.84<NA><NA><NA><NA>
16781679위탁급식영업07_21_01_P32500003250000-120-2003-0000220030528<NA>3폐업2폐업20130724<NA><NA><NA>051 2403782<NA>600091부산광역시 중구 대청동1가 44번지부산광역시 중구 대청로 112 (대청동1가)48949한국은행부산지점20120127154021I2018-08-31 23:59:59.0위탁급식영업385221.047714180047.419477위탁급식영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
16791680위탁급식영업07_21_01_P32500003250000-120-2014-0000120140826<NA>3폐업2폐업20201106<NA><NA><NA>051 250 2926201.11600017부산광역시 중구 중앙동7가 20-1부산광역시 중구 중앙대로 2, 3층 (중앙동7가, 롯데몰마트시네마동)48944롯데푸드(주)마트광복20201106095558U2020-11-08 02:40:00.0위탁급식영업385590.814677179553.867032위탁급식영업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N201.11<NA><NA><NA><NA>
16801681위탁급식영업07_21_01_P32500003250000-120-2012-0000120120601<NA>3폐업2폐업20170630<NA><NA><NA>051 603 3456589.21600816부산광역시 중구 중앙동4가 79-9번지 한진해운 지하1층부산광역시 중구 충장대로9번길 46, 지하1층 (중앙동4가, 한진해운 내)48936(주)신세계푸드 한진해운부산20170630140050I2018-08-31 23:59:59.0위탁급식영업385801.526605180799.204372위탁급식영업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N589.21<NA><NA><NA><NA>
16811682위탁급식영업07_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>
16821683위탁급식영업07_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>
16831684위탁급식영업07_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>