Overview

Dataset statistics

Number of variables48
Number of observations482
Missing cells5547
Missing cells (%)24.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory195.0 KiB
Average record size in memory414.3 B

Variable types

Numeric10
Categorical22
Text5
Unsupported9
DateTime1
Boolean1

Dataset

Description2021-08-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123114

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
데이터갱신구분 is highly imbalanced (81.0%)Imbalance
남성종사자수 is highly imbalanced (56.4%)Imbalance
여성종사자수 is highly imbalanced (56.4%)Imbalance
건물소유구분명 is highly imbalanced (84.7%)Imbalance
보증액 is highly imbalanced (87.8%)Imbalance
월세액 is highly imbalanced (87.8%)Imbalance
시설총규모 is highly imbalanced (96.3%)Imbalance
인허가취소일자 has 482 (100.0%) missing valuesMissing
폐업일자 has 88 (18.3%) missing valuesMissing
휴업시작일자 has 482 (100.0%) missing valuesMissing
휴업종료일자 has 482 (100.0%) missing valuesMissing
재개업일자 has 482 (100.0%) missing valuesMissing
소재지전화 has 33 (6.8%) missing valuesMissing
소재지면적 has 189 (39.2%) missing valuesMissing
도로명전체주소 has 372 (77.2%) missing valuesMissing
도로명우편번호 has 375 (77.8%) missing valuesMissing
좌표정보(x) has 76 (15.8%) missing valuesMissing
좌표정보(y) has 76 (15.8%) missing valuesMissing
총종업원수 has 482 (100.0%) missing valuesMissing
전통업소지정번호 has 482 (100.0%) missing valuesMissing
전통업소주된음식 has 482 (100.0%) missing valuesMissing
홈페이지 has 482 (100.0%) missing valuesMissing
Unnamed: 47 has 482 (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
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
소재지면적 has 56 (11.6%) zerosZeros

Reproduction

Analysis started2024-04-16 14:38:12.352293
Analysis finished2024-04-16 14:38:12.943628
Duration0.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct482
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean241.5
Minimum1
Maximum482
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-04-16T23:38:13.016900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile25.05
Q1121.25
median241.5
Q3361.75
95-th percentile457.95
Maximum482
Range481
Interquartile range (IQR)240.5

Descriptive statistics

Standard deviation139.28568
Coefficient of variation (CV)0.57675229
Kurtosis-1.2
Mean241.5
Median Absolute Deviation (MAD)120.5
Skewness0
Sum116403
Variance19400.5
MonotonicityStrictly increasing
2024-04-16T23:38:13.208870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
363 1
 
0.2%
331 1
 
0.2%
330 1
 
0.2%
329 1
 
0.2%
328 1
 
0.2%
327 1
 
0.2%
326 1
 
0.2%
325 1
 
0.2%
324 1
 
0.2%
Other values (472) 472
97.9%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
482 1
0.2%
481 1
0.2%
480 1
0.2%
479 1
0.2%
478 1
0.2%
477 1
0.2%
476 1
0.2%
475 1
0.2%
474 1
0.2%
473 1
0.2%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
식용얼음판매업
482 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식용얼음판매업 482
100.0%

Length

2024-04-16T23:38:13.320201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:38:13.393909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식용얼음판매업 482
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
07_22_21_P
482 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row07_22_21_P
2nd row07_22_21_P
3rd row07_22_21_P
4th row07_22_21_P
5th row07_22_21_P

Common Values

ValueCountFrequency (%)
07_22_21_P 482
100.0%

Length

2024-04-16T23:38:13.471990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:38:13.542515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_21_p 482
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3322655.6
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-04-16T23:38:13.610287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3260000
Q13290000
median3320000
Q33350000
95-th percentile3390000
Maximum3400000
Range150000
Interquartile range (IQR)60000

Descriptive statistics

Standard deviation42937.871
Coefficient of variation (CV)0.012922757
Kurtosis-1.1154536
Mean3322655.6
Median Absolute Deviation (MAD)30000
Skewness0.27078539
Sum1.60152 × 109
Variance1.8436608 × 109
MonotonicityNot monotonic
2024-04-16T23:38:13.701773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3290000 76
15.8%
3390000 70
14.5%
3270000 43
8.9%
3300000 43
8.9%
3340000 39
8.1%
3320000 38
7.9%
3330000 30
 
6.2%
3350000 27
 
5.6%
3310000 24
 
5.0%
3260000 22
 
4.6%
Other values (6) 70
14.5%
ValueCountFrequency (%)
3250000 11
 
2.3%
3260000 22
 
4.6%
3270000 43
8.9%
3280000 13
 
2.7%
3290000 76
15.8%
3300000 43
8.9%
3310000 24
 
5.0%
3320000 38
7.9%
3330000 30
 
6.2%
3340000 39
8.1%
ValueCountFrequency (%)
3400000 5
 
1.0%
3390000 70
14.5%
3380000 21
 
4.4%
3370000 17
 
3.5%
3360000 3
 
0.6%
3350000 27
 
5.6%
3340000 39
8.1%
3330000 30
6.2%
3320000 38
7.9%
3310000 24
 
5.0%

관리번호
Text

UNIQUE 

Distinct482
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2024-04-16T23:38:13.857389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters10604
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

Unique482 ?
Unique (%)100.0%

Sample

1st row3250000-111-1973-00001
2nd row3250000-111-1979-00002
3rd row3260000-111-1997-00510
4th row3260000-111-1991-00506
5th row3260000-111-2000-00922
ValueCountFrequency (%)
3250000-111-1973-00001 1
 
0.2%
3340000-111-2000-00972 1
 
0.2%
3330000-111-2001-00713 1
 
0.2%
3330000-111-2001-00741 1
 
0.2%
3330000-111-1998-00435 1
 
0.2%
3330000-111-2000-00571 1
 
0.2%
3330000-111-1999-00488 1
 
0.2%
3330000-111-1986-00429 1
 
0.2%
3330000-111-1994-00432 1
 
0.2%
3330000-111-1982-00428 1
 
0.2%
Other values (472) 472
97.9%
2024-04-16T23:38:14.117319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3512
33.1%
1 2112
19.9%
- 1446
13.6%
3 980
 
9.2%
9 840
 
7.9%
2 495
 
4.7%
8 308
 
2.9%
7 306
 
2.9%
5 245
 
2.3%
4 205
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9158
86.4%
Dash Punctuation 1446
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3512
38.3%
1 2112
23.1%
3 980
 
10.7%
9 840
 
9.2%
2 495
 
5.4%
8 308
 
3.4%
7 306
 
3.3%
5 245
 
2.7%
4 205
 
2.2%
6 155
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 1446
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10604
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3512
33.1%
1 2112
19.9%
- 1446
13.6%
3 980
 
9.2%
9 840
 
7.9%
2 495
 
4.7%
8 308
 
2.9%
7 306
 
2.9%
5 245
 
2.3%
4 205
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10604
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3512
33.1%
1 2112
19.9%
- 1446
13.6%
3 980
 
9.2%
9 840
 
7.9%
2 495
 
4.7%
8 308
 
2.9%
7 306
 
2.9%
5 245
 
2.3%
4 205
 
1.9%

인허가일자
Real number (ℝ)

Distinct436
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19900122
Minimum19680403
Maximum20190625
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-04-16T23:38:14.241368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19680403
5-th percentile19710730
Q119820742
median19910516
Q319980483
95-th percentile20060824
Maximum20190625
Range510222
Interquartile range (IQR)159741.5

Descriptive statistics

Standard deviation108999.49
Coefficient of variation (CV)0.0054773276
Kurtosis-0.62438726
Mean19900122
Median Absolute Deviation (MAD)70192.5
Skewness-0.055830338
Sum9.5918586 × 109
Variance1.1880888 × 1010
MonotonicityNot monotonic
2024-04-16T23:38:14.396677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19700714 5
 
1.0%
19740504 3
 
0.6%
19950803 2
 
0.4%
20010427 2
 
0.4%
19881122 2
 
0.4%
19960523 2
 
0.4%
19950525 2
 
0.4%
19870319 2
 
0.4%
19840412 2
 
0.4%
19910814 2
 
0.4%
Other values (426) 458
95.0%
ValueCountFrequency (%)
19680403 1
 
0.2%
19700313 1
 
0.2%
19700529 1
 
0.2%
19700619 1
 
0.2%
19700624 1
 
0.2%
19700625 1
 
0.2%
19700714 5
1.0%
19700725 1
 
0.2%
19710403 1
 
0.2%
19710409 1
 
0.2%
ValueCountFrequency (%)
20190625 1
0.2%
20160330 1
0.2%
20150819 1
0.2%
20150817 2
0.4%
20150703 1
0.2%
20150316 1
0.2%
20140526 1
0.2%
20140404 1
0.2%
20130821 1
0.2%
20120906 1
0.2%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing482
Missing (%)100.0%
Memory size4.4 KiB

영업상태구분코드
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
3
394 
1
88 

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 (%)
3 394
81.7%
1 88
 
18.3%

Length

2024-04-16T23:38:14.504151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:38:14.574378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 394
81.7%
1 88
 
18.3%

영업상태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
폐업
394 
영업/정상
88 

Length

Max length5
Median length2
Mean length2.5477178
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 394
81.7%
영업/정상 88
 
18.3%

Length

2024-04-16T23:38:14.658422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:38:14.732881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 394
81.7%
영업/정상 88
 
18.3%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2
394 
1
88 

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 (%)
2 394
81.7%
1 88
 
18.3%

Length

2024-04-16T23:38:14.821994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:38:14.897283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 394
81.7%
1 88
 
18.3%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
폐업
394 
영업
88 

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 394
81.7%
영업 88
 
18.3%

Length

2024-04-16T23:38:14.981202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:38:15.068706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 394
81.7%
영업 88
 
18.3%

폐업일자
Real number (ℝ)

MISSING 

Distinct280
Distinct (%)71.1%
Missing88
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean20028515
Minimum19820828
Maximum20210303
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-04-16T23:38:15.183208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19820828
5-th percentile19877184
Q119991016
median20030572
Q320070809
95-th percentile20160579
Maximum20210303
Range389475
Interquartile range (IQR)79793

Descriptive statistics

Standard deviation74009.519
Coefficient of variation (CV)0.0036952075
Kurtosis0.69397441
Mean20028515
Median Absolute Deviation (MAD)39804
Skewness-0.33882408
Sum7.891235 × 109
Variance5.4774089 × 109
MonotonicityNot monotonic
2024-04-16T23:38:15.337303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20050614 16
 
3.3%
19851206 14
 
2.9%
19970831 9
 
1.9%
20011008 7
 
1.5%
19991020 7
 
1.5%
19890627 6
 
1.2%
20100111 5
 
1.0%
19991016 5
 
1.0%
20060503 5
 
1.0%
20070809 5
 
1.0%
Other values (270) 315
65.4%
(Missing) 88
 
18.3%
ValueCountFrequency (%)
19820828 2
 
0.4%
19830804 1
 
0.2%
19840127 1
 
0.2%
19840510 1
 
0.2%
19851206 14
2.9%
19870629 1
 
0.2%
19880713 1
 
0.2%
19880812 1
 
0.2%
19890627 6
1.2%
19891128 1
 
0.2%
ValueCountFrequency (%)
20210303 1
0.2%
20200612 1
0.2%
20200521 1
0.2%
20200409 1
0.2%
20200401 1
0.2%
20190924 1
0.2%
20190318 1
0.2%
20181227 1
0.2%
20181119 1
0.2%
20181106 1
0.2%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing482
Missing (%)100.0%
Memory size4.4 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing482
Missing (%)100.0%
Memory size4.4 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing482
Missing (%)100.0%
Memory size4.4 KiB

소재지전화
Text

MISSING 

Distinct162
Distinct (%)36.1%
Missing33
Missing (%)6.8%
Memory size3.9 KiB
2024-04-16T23:38:15.580149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length3
Mean length6.0155902
Min length3

Characters and Unicode

Total characters2701
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique154 ?
Unique (%)34.3%

Sample

1st row051 2552029
2nd row051
3rd row051 2445538
4th row051 244 1005
5th row051 244 7716
ValueCountFrequency (%)
051 432
68.5%
6223618 3
 
0.5%
6428800 3
 
0.5%
3288254 2
 
0.3%
3415119 2
 
0.3%
5253435 2
 
0.3%
5182627 2
 
0.3%
245 2
 
0.3%
5135 2
 
0.3%
754 2
 
0.3%
Other values (178) 179
28.4%
2024-04-16T23:38:15.896146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 599
22.2%
1 572
21.2%
0 561
20.8%
182
 
6.7%
2 139
 
5.1%
3 134
 
5.0%
6 120
 
4.4%
8 120
 
4.4%
4 116
 
4.3%
7 88
 
3.3%
Other values (2) 70
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2518
93.2%
Space Separator 182
 
6.7%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 599
23.8%
1 572
22.7%
0 561
22.3%
2 139
 
5.5%
3 134
 
5.3%
6 120
 
4.8%
8 120
 
4.8%
4 116
 
4.6%
7 88
 
3.5%
9 69
 
2.7%
Space Separator
ValueCountFrequency (%)
182
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2701
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 599
22.2%
1 572
21.2%
0 561
20.8%
182
 
6.7%
2 139
 
5.1%
3 134
 
5.0%
6 120
 
4.4%
8 120
 
4.4%
4 116
 
4.3%
7 88
 
3.3%
Other values (2) 70
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2701
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 599
22.2%
1 572
21.2%
0 561
20.8%
182
 
6.7%
2 139
 
5.1%
3 134
 
5.0%
6 120
 
4.4%
8 120
 
4.4%
4 116
 
4.3%
7 88
 
3.3%
Other values (2) 70
 
2.6%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct183
Distinct (%)62.5%
Missing189
Missing (%)39.2%
Infinite0
Infinite (%)0.0%
Mean11.43372
Minimum0
Maximum98.66
Zeros56
Zeros (%)11.6%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-04-16T23:38:16.020433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15.44
median9.88
Q316
95-th percentile27.984
Maximum98.66
Range98.66
Interquartile range (IQR)10.56

Descriptive statistics

Standard deviation11.407343
Coefficient of variation (CV)0.99769302
Kurtosis15.962305
Mean11.43372
Median Absolute Deviation (MAD)5.28
Skewness2.9965819
Sum3350.08
Variance130.12747
MonotonicityNot monotonic
2024-04-16T23:38:16.133372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 56
 
11.6%
6.0 7
 
1.5%
20.0 6
 
1.2%
12.0 6
 
1.2%
18.0 5
 
1.0%
7.5 4
 
0.8%
15.0 3
 
0.6%
10.5 3
 
0.6%
5.7 3
 
0.6%
8.75 3
 
0.6%
Other values (173) 197
40.9%
(Missing) 189
39.2%
ValueCountFrequency (%)
0.0 56
11.6%
1.41 1
 
0.2%
2.0 1
 
0.2%
2.69 1
 
0.2%
2.93 1
 
0.2%
3.45 1
 
0.2%
3.6 2
 
0.4%
3.7 1
 
0.2%
4.0 2
 
0.4%
4.03 1
 
0.2%
ValueCountFrequency (%)
98.66 1
0.2%
73.0 1
0.2%
67.2 1
0.2%
50.8 1
0.2%
45.0 1
0.2%
44.57 1
0.2%
43.35 1
0.2%
41.4 1
0.2%
41.24 1
0.2%
33.0 1
0.2%

소재지우편번호
Real number (ℝ)

Distinct285
Distinct (%)59.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean610905.22
Minimum600013
Maximum619913
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-04-16T23:38:16.256701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600013
5-th percentile601812
Q1606061.25
median612045
Q3614869.25
95-th percentile617828
Maximum619913
Range19900
Interquartile range (IQR)8808

Descriptive statistics

Standard deviation5649.4556
Coefficient of variation (CV)0.0092476793
Kurtosis-1.2102082
Mean610905.22
Median Absolute Deviation (MAD)4756
Skewness-0.3317235
Sum2.9445632 × 108
Variance31916348
MonotonicityNot monotonic
2024-04-16T23:38:16.373760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
616801 11
 
2.3%
614849 8
 
1.7%
613828 6
 
1.2%
617816 6
 
1.2%
601812 6
 
1.2%
617819 5
 
1.0%
617808 5
 
1.0%
607831 5
 
1.0%
601829 5
 
1.0%
617807 5
 
1.0%
Other values (275) 420
87.1%
ValueCountFrequency (%)
600013 1
0.2%
600044 1
0.2%
600045 1
0.2%
600064 1
0.2%
600083 2
0.4%
600102 1
0.2%
600803 1
0.2%
600806 1
0.2%
600807 1
0.2%
600808 1
0.2%
ValueCountFrequency (%)
619913 1
0.2%
619912 2
0.4%
619903 2
0.4%
618813 1
0.2%
618806 1
0.2%
618803 1
0.2%
617846 1
0.2%
617845 1
0.2%
617844 1
0.2%
617841 2
0.4%

소재지전체주소
Text

Distinct260
Distinct (%)53.9%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2024-04-16T23:38:16.602413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length40
Mean length22.352697
Min length17

Characters and Unicode

Total characters10774
Distinct characters134
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique170 ?
Unique (%)35.3%

Sample

1st row부산광역시 중구 부평동*가 **번지 (나**호, **호)
2nd row부산광역시 중구 남포동*가 ***번지
3rd row부산광역시 서구 아미동*가 **-**번지
4th row부산광역시 서구 암남동 *-**번지
5th row부산광역시 서구 충무동*가 *-*번지
ValueCountFrequency (%)
부산광역시 482
23.9%
번지 481
23.8%
부산진구 76
 
3.8%
사상구 70
 
3.5%
동래구 43
 
2.1%
동구 43
 
2.1%
사하구 39
 
1.9%
북구 38
 
1.9%
해운대구 30
 
1.5%
부전동 27
 
1.3%
Other values (136) 691
34.2%
2024-04-16T23:38:17.209557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 2278
21.1%
1539
14.3%
부 604
 
5.6%
산 589
 
5.5%
동 583
 
5.4%
구 500
 
4.6%
광 491
 
4.6%
시 490
 
4.5%
지 488
 
4.5%
역 482
 
4.5%
Other values (124) 2730
25.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6447
59.8%
Other Punctuation 2290
 
21.3%
Space Separator 1539
 
14.3%
Dash Punctuation 465
 
4.3%
Uppercase Letter 20
 
0.2%
Close Punctuation 7
 
0.1%
Open Punctuation 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 604
 
9.4%
산 589
 
9.1%
동 583
 
9.0%
구 500
 
7.8%
광 491
 
7.6%
시 490
 
7.6%
지 488
 
7.6%
역 482
 
7.5%
번 481
 
7.5%
사 118
 
1.8%
Other values (113) 1621
25.1%
Other Punctuation
ValueCountFrequency (%)
* 2278
99.5%
, 11
 
0.5%
/ 1
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
B 11
55.0%
T 8
40.0%
A 1
 
5.0%
Close Punctuation
ValueCountFrequency (%)
) 6
85.7%
] 1
 
14.3%
Space Separator
ValueCountFrequency (%)
1539
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 465
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6447
59.8%
Common 4307
40.0%
Latin 20
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 604
 
9.4%
산 589
 
9.1%
동 583
 
9.0%
구 500
 
7.8%
광 491
 
7.6%
시 490
 
7.6%
지 488
 
7.6%
역 482
 
7.5%
번 481
 
7.5%
사 118
 
1.8%
Other values (113) 1621
25.1%
Common
ValueCountFrequency (%)
* 2278
52.9%
1539
35.7%
- 465
 
10.8%
, 11
 
0.3%
( 6
 
0.1%
) 6
 
0.1%
/ 1
 
< 0.1%
] 1
 
< 0.1%
Latin
ValueCountFrequency (%)
B 11
55.0%
T 8
40.0%
A 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6447
59.8%
ASCII 4327
40.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 2278
52.6%
1539
35.6%
- 465
 
10.7%
, 11
 
0.3%
B 11
 
0.3%
T 8
 
0.2%
( 6
 
0.1%
) 6
 
0.1%
A 1
 
< 0.1%
/ 1
 
< 0.1%
Hangul
ValueCountFrequency (%)
부 604
 
9.4%
산 589
 
9.1%
동 583
 
9.0%
구 500
 
7.8%
광 491
 
7.6%
시 490
 
7.6%
지 488
 
7.6%
역 482
 
7.5%
번 481
 
7.5%
사 118
 
1.8%
Other values (113) 1621
25.1%

도로명전체주소
Text

MISSING 

Distinct107
Distinct (%)97.3%
Missing372
Missing (%)77.2%
Memory size3.9 KiB
2024-04-16T23:38:17.459110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length35
Mean length28.036364
Min length21

Characters and Unicode

Total characters3084
Distinct characters152
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique105 ?
Unique (%)95.5%

Sample

1st row부산광역시 중구 흑교로 **, 나**.**호 (부평동*가)
2nd row부산광역시 서구 까치고개로***번길 ** (아미동*가)
3rd row부산광역시 서구 천해로**번길 * (암남동)
4th row부산광역시 서구 구덕로***번길 **-* (충무동*가)
5th row부산광역시 서구 암남공원로 ** (암남동)
ValueCountFrequency (%)
111
19.2%
부산광역시 110
19.0%
사상구 14
 
2.4%
부산진구 13
 
2.2%
해운대구 10
 
1.7%
북구 10
 
1.7%
사하구 10
 
1.7%
동래구 10
 
1.7%
수영구 9
 
1.6%
층 8
 
1.4%
Other values (170) 273
47.2%
2024-04-16T23:38:17.842943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 499
16.2%
469
15.2%
동 143
 
4.6%
부 137
 
4.4%
산 135
 
4.4%
구 122
 
4.0%
시 117
 
3.8%
광 115
 
3.7%
역 110
 
3.6%
) 110
 
3.6%
Other values (142) 1127
36.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1847
59.9%
Other Punctuation 525
 
17.0%
Space Separator 469
 
15.2%
Close Punctuation 110
 
3.6%
Open Punctuation 110
 
3.6%
Dash Punctuation 22
 
0.7%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 143
 
7.7%
부 137
 
7.4%
산 135
 
7.3%
구 122
 
6.6%
시 117
 
6.3%
광 115
 
6.2%
역 110
 
6.0%
로 107
 
5.8%
길 81
 
4.4%
번 79
 
4.3%
Other values (134) 701
38.0%
Other Punctuation
ValueCountFrequency (%)
* 499
95.0%
, 25
 
4.8%
. 1
 
0.2%
Space Separator
ValueCountFrequency (%)
469
100.0%
Close Punctuation
ValueCountFrequency (%)
) 110
100.0%
Open Punctuation
ValueCountFrequency (%)
( 110
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1847
59.9%
Common 1236
40.1%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 143
 
7.7%
부 137
 
7.4%
산 135
 
7.3%
구 122
 
6.6%
시 117
 
6.3%
광 115
 
6.2%
역 110
 
6.0%
로 107
 
5.8%
길 81
 
4.4%
번 79
 
4.3%
Other values (134) 701
38.0%
Common
ValueCountFrequency (%)
* 499
40.4%
469
37.9%
) 110
 
8.9%
( 110
 
8.9%
, 25
 
2.0%
- 22
 
1.8%
. 1
 
0.1%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1847
59.9%
ASCII 1237
40.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 499
40.3%
469
37.9%
) 110
 
8.9%
( 110
 
8.9%
, 25
 
2.0%
- 22
 
1.8%
. 1
 
0.1%
B 1
 
0.1%
Hangul
ValueCountFrequency (%)
동 143
 
7.7%
부 137
 
7.4%
산 135
 
7.3%
구 122
 
6.6%
시 117
 
6.3%
광 115
 
6.2%
역 110
 
6.0%
로 107
 
5.8%
길 81
 
4.4%
번 79
 
4.3%
Other values (134) 701
38.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct101
Distinct (%)94.4%
Missing375
Missing (%)77.8%
Infinite0
Infinite (%)0.0%
Mean47876.692
Minimum46066
Maximum49476
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-04-16T23:38:17.965822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46066
5-th percentile46513.5
Q147035.5
median47843
Q348547.5
95-th percentile49413.5
Maximum49476
Range3410
Interquartile range (IQR)1512

Descriptive statistics

Standard deviation953.48288
Coefficient of variation (CV)0.019915388
Kurtosis-1.0626417
Mean47876.692
Median Absolute Deviation (MAD)804
Skewness0.12614828
Sum5122806
Variance909129.61
MonotonicityNot monotonic
2024-04-16T23:38:18.085381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
46965 2
 
0.4%
47708 2
 
0.4%
47857 2
 
0.4%
48086 2
 
0.4%
46582 2
 
0.4%
47594 2
 
0.4%
47028 1
 
0.2%
48816 1
 
0.2%
47775 1
 
0.2%
48285 1
 
0.2%
Other values (91) 91
 
18.9%
(Missing) 375
77.8%
ValueCountFrequency (%)
46066 1
0.2%
46243 1
0.2%
46300 1
0.2%
46302 1
0.2%
46303 1
0.2%
46506 1
0.2%
46531 1
0.2%
46574 1
0.2%
46580 1
0.2%
46582 2
0.4%
ValueCountFrequency (%)
49476 1
0.2%
49458 1
0.2%
49449 1
0.2%
49441 1
0.2%
49431 1
0.2%
49415 1
0.2%
49410 1
0.2%
49356 1
0.2%
49323 1
0.2%
49307 1
0.2%

사업장명
Text

Distinct389
Distinct (%)80.7%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2024-04-16T23:38:18.386702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length4
Mean length4.2282158
Min length2

Characters and Unicode

Total characters2038
Distinct characters227
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique333 ?
Unique (%)69.1%

Sample

1st row시장얼음집
2nd row사)부산어패류처리조합
3rd row조은얼음상회
4th row제일위생얼음
5th row충무얼음
ValueCountFrequency (%)
제일얼음 9
 
1.8%
얼음집 7
 
1.4%
시장얼음 6
 
1.2%
얼음 6
 
1.2%
동아얼음 6
 
1.2%
부산얼음 5
 
1.0%
합천얼음 5
 
1.0%
범일얼음 4
 
0.8%
영남얼음 4
 
0.8%
시원얼음 3
 
0.6%
Other values (386) 445
89.0%
2024-04-16T23:38:18.778624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
얼 348
 
17.1%
음 348
 
17.1%
상 89
 
4.4%
회 73
 
3.6%
집 54
 
2.6%
동 48
 
2.4%
일 47
 
2.3%
부 37
 
1.8%
성 33
 
1.6%
대 30
 
1.5%
Other values (217) 931
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2018
99.0%
Space Separator 18
 
0.9%
Decimal Number 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
얼 348
 
17.2%
음 348
 
17.2%
상 89
 
4.4%
회 73
 
3.6%
집 54
 
2.7%
동 48
 
2.4%
일 47
 
2.3%
부 37
 
1.8%
성 33
 
1.6%
대 30
 
1.5%
Other values (214) 911
45.1%
Space Separator
ValueCountFrequency (%)
18
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2018
99.0%
Common 20
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
얼 348
 
17.2%
음 348
 
17.2%
상 89
 
4.4%
회 73
 
3.6%
집 54
 
2.7%
동 48
 
2.4%
일 47
 
2.3%
부 37
 
1.8%
성 33
 
1.6%
대 30
 
1.5%
Other values (214) 911
45.1%
Common
ValueCountFrequency (%)
18
90.0%
2 1
 
5.0%
) 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2018
99.0%
ASCII 20
 
1.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
얼 348
 
17.2%
음 348
 
17.2%
상 89
 
4.4%
회 73
 
3.6%
집 54
 
2.7%
동 48
 
2.4%
일 47
 
2.3%
부 37
 
1.8%
성 33
 
1.6%
대 30
 
1.5%
Other values (214) 911
45.1%
ASCII
ValueCountFrequency (%)
18
90.0%
2 1
 
5.0%
) 1
 
5.0%

최종수정시점
Real number (ℝ)

Distinct211
Distinct (%)43.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0050732 × 1013
Minimum1.9990316 × 1013
Maximum2.0210303 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-04-16T23:38:18.906483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990316 × 1013
5-th percentile2.000041 × 1013
Q12.0020415 × 1013
median2.0020828 × 1013
Q32.0070687 × 1013
95-th percentile2.0171011 × 1013
Maximum2.0210303 × 1013
Range2.1998714 × 1011
Interquartile range (IQR)5.027175 × 1010

Descriptive statistics

Standard deviation5.197148 × 1010
Coefficient of variation (CV)0.0025919991
Kurtosis0.77621045
Mean2.0050732 × 1013
Median Absolute Deviation (MAD)1.0314 × 1010
Skewness1.3425438
Sum9.664453 × 1015
Variance2.7010348 × 1021
MonotonicityNot monotonic
2024-04-16T23:38:19.038927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20020816000000 46
 
9.5%
20020828000000 41
 
8.5%
20040217000000 29
 
6.0%
20010731000000 27
 
5.6%
20020305000000 15
 
3.1%
20020814000000 13
 
2.7%
20020612000000 13
 
2.7%
19990330000000 11
 
2.3%
20010514000000 11
 
2.3%
20020222000000 10
 
2.1%
Other values (201) 266
55.2%
ValueCountFrequency (%)
19990316000000 2
 
0.4%
19990318000000 7
1.5%
19990330000000 11
2.3%
19990723000000 1
 
0.2%
19991129000000 1
 
0.2%
20000117000000 1
 
0.2%
20000329000000 1
 
0.2%
20000410000000 1
 
0.2%
20000418000000 1
 
0.2%
20000425000000 1
 
0.2%
ValueCountFrequency (%)
20210303135432 1
0.2%
20200615131735 1
0.2%
20200521104602 1
0.2%
20200429103935 1
0.2%
20200422135444 1
0.2%
20200409160613 1
0.2%
20200401172348 1
0.2%
20190924133006 1
0.2%
20190625152341 1
0.2%
20190412143744 1
0.2%

데이터갱신구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
I
468 
U
 
14

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 468
97.1%
U 14
 
2.9%

Length

2024-04-16T23:38:19.137700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:38:19.212525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 468
97.1%
u 14
 
2.9%

데이터갱신일자
Date

Distinct16
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
Minimum2018-08-31 23:59:59
Maximum2021-03-05 02:40:00
2024-04-16T23:38:19.278499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T23:38:19.385917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
식용얼음판매업
482 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식용얼음판매업 482
100.0%

Length

2024-04-16T23:38:19.494757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:38:19.589610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식용얼음판매업 482
100.0%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct381
Distinct (%)93.8%
Missing76
Missing (%)15.8%
Infinite0
Infinite (%)0.0%
Mean386494.47
Minimum376040.04
Maximum403430.89
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-04-16T23:38:19.699440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum376040.04
5-th percentile379881.45
Q1382262.11
median386765.57
Q3389985.14
95-th percentile393522.97
Maximum403430.89
Range27390.855
Interquartile range (IQR)7723.0314

Descriptive statistics

Standard deviation4875.1329
Coefficient of variation (CV)0.012613719
Kurtosis0.050323356
Mean386494.47
Median Absolute Deviation (MAD)3593.9698
Skewness0.43351578
Sum1.5691676 × 108
Variance23766920
MonotonicityNot monotonic
2024-04-16T23:38:19.827408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
393233.931123062 3
 
0.6%
380863.049882095 3
 
0.6%
391308.185584833 2
 
0.4%
385431.226070366 2
 
0.4%
393366.528779577 2
 
0.4%
382375.205698571 2
 
0.4%
382262.111868599 2
 
0.4%
385429.355755039 2
 
0.4%
384150.871127197 2
 
0.4%
386984.150798717 2
 
0.4%
Other values (371) 384
79.7%
(Missing) 76
 
15.8%
ValueCountFrequency (%)
376040.040165403 1
0.2%
377443.082160274 1
0.2%
378465.375496992 1
0.2%
378574.971264516 1
0.2%
378877.831049585 1
0.2%
378904.299819951 2
0.4%
379000.688309942 1
0.2%
379321.651090423 2
0.4%
379387.751992044 1
0.2%
379461.859303267 1
0.2%
ValueCountFrequency (%)
403430.89476242 1
0.2%
403184.566926778 1
0.2%
403140.157491273 1
0.2%
401617.635228305 1
0.2%
400701.324685691 1
0.2%
398052.162211836 1
0.2%
397553.907699438 1
0.2%
396948.807981283 1
0.2%
396397.293695168 1
0.2%
396318.377258543 1
0.2%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct381
Distinct (%)93.8%
Missing76
Missing (%)15.8%
Infinite0
Infinite (%)0.0%
Mean186765.81
Minimum174894.55
Maximum199237.92
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-04-16T23:38:19.945641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum174894.55
5-th percentile178663.17
Q1183819.26
median186449.67
Q3190784.68
95-th percentile194773.04
Maximum199237.92
Range24343.369
Interquartile range (IQR)6965.4262

Descriptive statistics

Standard deviation4981.8452
Coefficient of variation (CV)0.02667429
Kurtosis-0.38637332
Mean186765.81
Median Absolute Deviation (MAD)3505.5822
Skewness-0.0049040752
Sum75826917
Variance24818782
MonotonicityNot monotonic
2024-04-16T23:38:20.065096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
192684.487637586 3
 
0.6%
185818.363507736 3
 
0.6%
190929.905105163 2
 
0.4%
191814.618621583 2
 
0.4%
189566.495038421 2
 
0.4%
191639.58976948 2
 
0.4%
191738.852736136 2
 
0.4%
191906.174381765 2
 
0.4%
181093.150500684 2
 
0.4%
186392.942434009 2
 
0.4%
Other values (371) 384
79.7%
(Missing) 76
 
15.8%
ValueCountFrequency (%)
174894.547897189 1
0.2%
174919.996506752 1
0.2%
174939.394134738 1
0.2%
174969.214043093 1
0.2%
175937.283674331 1
0.2%
176920.905530731 1
0.2%
177181.350422336 2
0.4%
177352.593969904 1
0.2%
177422.100422251 1
0.2%
177500.683331479 1
0.2%
ValueCountFrequency (%)
199237.917206525 1
0.2%
198627.554228591 1
0.2%
198430.914843779 1
0.2%
198201.741870506 1
0.2%
198104.527294442 1
0.2%
197826.534766735 1
0.2%
197594.301171508 1
0.2%
197559.271584532 1
0.2%
197504.804067934 1
0.2%
197488.026495269 1
0.2%

위생업태명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
식용얼음판매업
482 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식용얼음판매업 482
100.0%

Length

2024-04-16T23:38:20.177398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:38:20.247235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식용얼음판매업 482
100.0%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
399 
0
81 
1
 
2

Length

Max length4
Median length4
Mean length3.4834025
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 399
82.8%
0 81
 
16.8%
1 2
 
0.4%

Length

2024-04-16T23:38:20.323411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:38:20.402176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 399
82.8%
0 81
 
16.8%
1 2
 
0.4%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
399 
0
81 
1
 
2

Length

Max length4
Median length4
Mean length3.4834025
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 399
82.8%
0 81
 
16.8%
1 2
 
0.4%

Length

2024-04-16T23:38:20.483052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:38:20.568222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 399
82.8%
0 81
 
16.8%
1 2
 
0.4%

영업장주변구분명
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
기타
385 
<NA>
81 
주택가주변
 
16

Length

Max length5
Median length2
Mean length2.4356846
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타 385
79.9%
<NA> 81
 
16.8%
주택가주변 16
 
3.3%

Length

2024-04-16T23:38:20.651020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:38:20.727774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타 385
79.9%
na 81
 
16.8%
주택가주변 16
 
3.3%

등급구분명
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
기타
361 
<NA>
81 
자율
40 

Length

Max length4
Median length2
Mean length2.3360996
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타 361
74.9%
<NA> 81
 
16.8%
자율 40
 
8.3%

Length

2024-04-16T23:38:20.821277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:38:20.902896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타 361
74.9%
na 81
 
16.8%
자율 40
 
8.3%

급수시설구분명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
422 
상수도전용
60 

Length

Max length5
Median length4
Mean length4.1244813
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 422
87.6%
상수도전용 60
 
12.4%

Length

2024-04-16T23:38:20.987473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:38:21.067502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 422
87.6%
상수도전용 60
 
12.4%

총종업원수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing482
Missing (%)100.0%
Memory size4.4 KiB

본사종업원수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
331 
0
151 

Length

Max length4
Median length4
Mean length3.060166
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 331
68.7%
0 151
31.3%

Length

2024-04-16T23:38:21.151164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:38:21.236687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 331
68.7%
0 151
31.3%

공장사무직종업원수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
331 
0
151 

Length

Max length4
Median length4
Mean length3.060166
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 331
68.7%
0 151
31.3%

Length

2024-04-16T23:38:21.326736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:38:21.421324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 331
68.7%
0 151
31.3%

공장판매직종업원수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
331 
0
151 

Length

Max length4
Median length4
Mean length3.060166
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 331
68.7%
0 151
31.3%

Length

2024-04-16T23:38:21.517732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:38:21.599245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 331
68.7%
0 151
31.3%

공장생산직종업원수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
331 
0
151 

Length

Max length4
Median length4
Mean length3.060166
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 331
68.7%
0 151
31.3%

Length

2024-04-16T23:38:21.690178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:38:21.774571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 331
68.7%
0 151
31.3%

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
466 
임대
 
10
자가
 
6

Length

Max length4
Median length4
Mean length3.93361
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> 466
96.7%
임대 10
 
2.1%
자가 6
 
1.2%

Length

2024-04-16T23:38:21.863051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:38:21.943616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 466
96.7%
임대 10
 
2.1%
자가 6
 
1.2%

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
474 
0
 
8

Length

Max length4
Median length4
Mean length3.9502075
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> 474
98.3%
0 8
 
1.7%

Length

2024-04-16T23:38:22.030264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:38:22.106514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 474
98.3%
0 8
 
1.7%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
474 
0
 
8

Length

Max length4
Median length4
Mean length3.9502075
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> 474
98.3%
0 8
 
1.7%

Length

2024-04-16T23:38:22.183590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:38:22.257988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 474
98.3%
0 8
 
1.7%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size614.0 B
False
482 
ValueCountFrequency (%)
False 482
100.0%
2024-04-16T23:38:22.317150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
0.0
478 
6.0
 
1
2.8
 
1
4.9
 
1
8.41
 
1

Length

Max length4
Median length3
Mean length3.0020747
Min length3

Unique

Unique4 ?
Unique (%)0.8%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 478
99.2%
6.0 1
 
0.2%
2.8 1
 
0.2%
4.9 1
 
0.2%
8.41 1
 
0.2%

Length

2024-04-16T23:38:22.399615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:38:22.490436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 478
99.2%
6.0 1
 
0.2%
2.8 1
 
0.2%
4.9 1
 
0.2%
8.41 1
 
0.2%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing482
Missing (%)100.0%
Memory size4.4 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing482
Missing (%)100.0%
Memory size4.4 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing482
Missing (%)100.0%
Memory size4.4 KiB

Unnamed: 47
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing482
Missing (%)100.0%
Memory size4.4 KiB

Sample

번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지Unnamed: 47
01식용얼음판매업07_22_21_P32500003250000-111-1973-0000119730612<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.58600806부산광역시 중구 부평동*가 **번지 (나**호, **호)부산광역시 중구 흑교로 **, 나**.**호 (부평동*가)48977시장얼음집20130925103829I2018-08-31 23:59:59.0식용얼음판매업384621.820885180029.395795식용얼음판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
12식용얼음판매업07_22_21_P32500003250000-111-1979-0000219790822<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>600044부산광역시 중구 남포동*가 ***번지<NA><NA>사)부산어패류처리조합20011206000000I2018-08-31 23:59:59.0식용얼음판매업<NA><NA>식용얼음판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
23식용얼음판매업07_22_21_P32600003260000-111-1997-0051019970407<NA>1영업/정상1영업<NA><NA><NA><NA>051 25520298.16602827부산광역시 서구 아미동*가 **-**번지부산광역시 서구 까치고개로***번길 ** (아미동*가)49241조은얼음상회20120517105640I2018-08-31 23:59:59.0식용얼음판매업383864.234537179838.611561식용얼음판매업<NA><NA>기타기타<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
34식용얼음판매업07_22_21_P32600003260000-111-1991-0050619911010<NA>1영업/정상1영업<NA><NA><NA><NA>0515.52602830부산광역시 서구 암남동 *-**번지부산광역시 서구 천해로**번길 * (암남동)49260제일위생얼음20120517105552I2018-08-31 23:59:59.0식용얼음판매업383657.65041177974.883652식용얼음판매업<NA><NA>기타기타<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
45식용얼음판매업07_22_21_P32600003260000-111-2000-0092220001106<NA>1영업/정상1영업<NA><NA><NA><NA>051 244553812.18602012부산광역시 서구 충무동*가 *-*번지부산광역시 서구 구덕로***번길 **-* (충무동*가)49253충무얼음20120517105817I2018-08-31 23:59:59.0식용얼음판매업384374.411628179180.143454식용얼음판매업00기타기타<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
56식용얼음판매업07_22_21_P32600003260000-111-2013-0000120130821<NA>1영업/정상1영업<NA><NA><NA><NA>051 244 10057.84602833부산광역시 서구 암남동 ***-**번지부산광역시 서구 암남공원로 ** (암남동)49270우리얼음20131107171426I2018-08-31 23:59:59.0식용얼음판매업383725.279827176920.905531식용얼음판매업<NA><NA><NA><NA><NA><NA>0000자가<NA><NA>N0.0<NA><NA><NA><NA>
67식용얼음판매업07_22_21_P32600003260000-111-2014-0000120140404<NA>1영업/정상1영업<NA><NA><NA><NA>051 244 77166.0602091부산광역시 서구 서대신동*가 **번지 *층 일부부산광역시 서구 부용로 ** (서대신동*가)49233선미슈퍼마켓20140429173300I2018-08-31 23:59:59.0식용얼음판매업383863.488115180642.344262식용얼음판매업<NA><NA><NA><NA>상수도전용<NA>0000자가<NA><NA>N0.0<NA><NA><NA><NA>
78식용얼음판매업07_22_21_P32600003260000-111-1975-0050119750529<NA>1영업/정상1영업<NA><NA><NA><NA>05113.12602812부산광역시 서구 동대신동*가 ***-**번지<NA><NA>진해얼음20140509144224I2018-08-31 23:59:59.0식용얼음판매업<NA><NA>식용얼음판매업<NA><NA>기타기타<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
89식용얼음판매업07_22_21_P32600003260000-111-1982-0000119820719<NA>1영업/정상1영업<NA><NA><NA><NA>051 245 513573.0602052부산광역시 서구 토성동*가 *-*번지 *층부산광역시 서구 구덕로***번길 **, *층 (토성동*가)49224부평얼음20140226160607I2018-08-31 23:59:59.0식용얼음판매업384232.914073179867.436092식용얼음판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
910식용얼음판매업07_22_21_P32600003260000-111-1985-0050319850401<NA>1영업/정상1영업<NA><NA><NA><NA>0516.87602815부산광역시 서구 부민동*가 *-*번지부산광역시 서구 보수대로 *** (부민동*가)49223대원상회20120517105508I2018-08-31 23:59:59.0식용얼음판매업384207.495228180321.995012식용얼음판매업<NA><NA>기타기타<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지Unnamed: 47
472473식용얼음판매업07_22_21_P33900003390000-111-1996-0015019960514<NA>3폐업2폐업20050422<NA><NA><NA>051<NA>617807부산광역시 사상구 괘법동 ***-**번지<NA><NA>상상얼음20020222000000I2018-08-31 23:59:59.0식용얼음판매업380366.471758186771.498958식용얼음판매업<NA><NA>기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
473474식용얼음판매업07_22_21_P33900003390000-111-1997-0015319970506<NA>3폐업2폐업19991016<NA><NA><NA>051<NA>617808부산광역시 사상구 괘법동 ***-*번지<NA><NA>손맛식품20020828000000I2018-08-31 23:59:59.0식용얼음판매업380368.471071187194.552154식용얼음판매업<NA><NA>기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
474475식용얼음판매업07_22_21_P33900003390000-111-1997-0015519970529<NA>3폐업2폐업19991016<NA><NA><NA>051<NA>617808부산광역시 사상구 괘법동 ***-**번지<NA><NA>하얀얼음20020828000000I2018-08-31 23:59:59.0식용얼음판매업380429.779874186995.371586식용얼음판매업<NA><NA>기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
475476식용얼음판매업07_22_21_P33900003390000-111-1998-0015919980422<NA>3폐업2폐업20010215<NA><NA><NA>0510.0617822부산광역시 사상구 모라동 ***-*번지<NA><NA>제일얼음20020828000000I2018-08-31 23:59:59.0식용얼음판매업381066.612768189242.138956식용얼음판매업00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
476477식용얼음판매업07_22_21_P33900003390000-111-1998-0016219980525<NA>3폐업2폐업20050216<NA><NA><NA>051 3139911<NA>617838부산광역시 사상구 주례동 ****-***번지<NA><NA>부산얼음판매20020222000000I2018-08-31 23:59:59.0식용얼음판매업382326.837704185158.676207식용얼음판매업<NA><NA>기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
477478식용얼음판매업07_22_21_P34000003400000-111-1974-0018619740727<NA>3폐업2폐업20080128<NA><NA><NA><NA><NA>619903부산광역시 기장군 기장읍 대라리 **번지<NA><NA>부산얼음집20020608000000I2018-08-31 23:59:59.0식용얼음판매업<NA><NA>식용얼음판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
478479식용얼음판매업07_22_21_P34000003400000-111-1976-0018619760731<NA>3폐업2폐업20080129<NA><NA><NA><NA><NA>619912부산광역시 기장군 일광면 삼성리 ***-*번지<NA><NA>동해얼음집20020608000000I2018-08-31 23:59:59.0식용얼음판매업403184.566927198201.741871식용얼음판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
479480식용얼음판매업07_22_21_P34000003400000-111-1978-0018719780714<NA>3폐업2폐업20080326<NA><NA><NA><NA><NA>619913부산광역시 기장군 일광면 이천리 ***-*번지<NA><NA>이천얼음집20020608000000I2018-08-31 23:59:59.0식용얼음판매업403430.894762198627.554229식용얼음판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
480481식용얼음판매업07_22_21_P34000003400000-111-2001-0000120010530<NA>3폐업2폐업20120614<NA><NA><NA><NA><NA>619903부산광역시 기장군 기장읍 대라리 **-*번지부산광역시 기장군 기장읍 차성동로**번길 *46066부산식품20020608000000I2018-08-31 23:59:59.0식용얼음판매업401617.635228196097.170744식용얼음판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
481482식용얼음판매업07_22_21_P34000003400000-111-2010-0000120100303<NA>3폐업2폐업20100115<NA><NA><NA><NA><NA>619912부산광역시 기장군 일광면 삼성리 ***-**번지<NA><NA>일광얼음집20150716135255I2018-08-31 23:59:59.0식용얼음판매업403140.157491198104.527294식용얼음판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>