Overview

Dataset statistics

Number of variables48
Number of observations479
Missing cells5028
Missing cells (%)21.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory193.8 KiB
Average record size in memory414.3 B

Variable types

Numeric10
Categorical24
Text5
Unsupported8
Boolean1

Dataset

Description2022-09-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123114

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
업태구분명 has constant value ""Constant
위생업태명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
데이터갱신구분 is highly imbalanced (76.9%)Imbalance
데이터갱신일자 is highly imbalanced (90.5%)Imbalance
남성종사자수 is highly imbalanced (55.4%)Imbalance
여성종사자수 is highly imbalanced (55.4%)Imbalance
총직원수 is highly imbalanced (93.0%)Imbalance
건물소유구분명 is highly imbalanced (84.7%)Imbalance
보증액 is highly imbalanced (83.1%)Imbalance
월세액 is highly imbalanced (83.1%)Imbalance
시설총규모 is highly imbalanced (96.3%)Imbalance
인허가취소일자 has 479 (100.0%) missing valuesMissing
폐업일자 has 85 (17.7%) missing valuesMissing
휴업시작일자 has 479 (100.0%) missing valuesMissing
휴업종료일자 has 479 (100.0%) missing valuesMissing
재개업일자 has 479 (100.0%) missing valuesMissing
소재지전화 has 32 (6.7%) missing valuesMissing
소재지면적 has 188 (39.2%) missing valuesMissing
도로명전체주소 has 369 (77.0%) missing valuesMissing
도로명우편번호 has 372 (77.7%) missing valuesMissing
좌표정보(x) has 75 (15.7%) missing valuesMissing
좌표정보(y) has 75 (15.7%) missing valuesMissing
전통업소지정번호 has 479 (100.0%) missing valuesMissing
전통업소주된음식 has 479 (100.0%) missing valuesMissing
홈페이지 has 479 (100.0%) missing valuesMissing
Unnamed: 47 has 479 (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
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 54 (11.3%) zerosZeros

Reproduction

Analysis started2024-04-16 14:35:33.308712
Analysis finished2024-04-16 14:35:33.826569
Duration0.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct479
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean240
Minimum1
Maximum479
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-04-16T23:35:33.884021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile24.9
Q1120.5
median240
Q3359.5
95-th percentile455.1
Maximum479
Range478
Interquartile range (IQR)239

Descriptive statistics

Standard deviation138.41965
Coefficient of variation (CV)0.57674855
Kurtosis-1.2
Mean240
Median Absolute Deviation (MAD)120
Skewness0
Sum114960
Variance19160
MonotonicityStrictly increasing
2024-04-16T23:35:33.992787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
2 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%
323 1
 
0.2%
322 1
 
0.2%
Other values (469) 469
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 (%)
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%
472 1
0.2%
471 1
0.2%
470 1
0.2%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
식용얼음판매업
479 

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 479
100.0%

Length

2024-04-16T23:35:34.104865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:35:34.188315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식용얼음판매업 479
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
07_22_21_P
479 

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 479
100.0%

Length

2024-04-16T23:35:34.279974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:35:34.353835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_21_p 479
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3322714
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-04-16T23:35:34.429373image/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 deviation42791.501
Coefficient of variation (CV)0.012878479
Kurtosis-1.1109376
Mean3322714
Median Absolute Deviation (MAD)30000
Skewness0.26661067
Sum1.59158 × 109
Variance1.8311126 × 109
MonotonicityNot monotonic
2024-04-16T23:35:34.564700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3290000 76
15.9%
3390000 70
14.6%
3300000 43
9.0%
3270000 41
8.6%
3340000 39
8.1%
3320000 38
7.9%
3330000 30
 
6.3%
3350000 27
 
5.6%
3310000 24
 
5.0%
3260000 22
 
4.6%
Other values (6) 69
14.4%
ValueCountFrequency (%)
3250000 11
 
2.3%
3260000 22
 
4.6%
3270000 41
8.6%
3280000 13
 
2.7%
3290000 76
15.9%
3300000 43
9.0%
3310000 24
 
5.0%
3320000 38
7.9%
3330000 30
 
6.3%
3340000 39
8.1%
ValueCountFrequency (%)
3400000 4
 
0.8%
3390000 70
14.6%
3380000 21
 
4.4%
3370000 17
 
3.5%
3360000 3
 
0.6%
3350000 27
 
5.6%
3340000 39
8.1%
3330000 30
6.3%
3320000 38
7.9%
3310000 24
 
5.0%

관리번호
Text

UNIQUE 

Distinct479
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2024-04-16T23:35:34.731888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters10538
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

Unique479 ?
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%
3340000-111-1973-00278 1
 
0.2%
3330000-111-2006-00001 1
 
0.2%
3330000-111-1974-00385 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%
Other values (469) 469
97.9%
2024-04-16T23:35:35.004344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3488
33.1%
1 2098
19.9%
- 1437
13.6%
3 977
 
9.3%
9 836
 
7.9%
2 492
 
4.7%
8 307
 
2.9%
7 303
 
2.9%
5 243
 
2.3%
4 202
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9101
86.4%
Dash Punctuation 1437
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3488
38.3%
1 2098
23.1%
3 977
 
10.7%
9 836
 
9.2%
2 492
 
5.4%
8 307
 
3.4%
7 303
 
3.3%
5 243
 
2.7%
4 202
 
2.2%
6 155
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 1437
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10538
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3488
33.1%
1 2098
19.9%
- 1437
13.6%
3 977
 
9.3%
9 836
 
7.9%
2 492
 
4.7%
8 307
 
2.9%
7 303
 
2.9%
5 243
 
2.3%
4 202
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10538
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3488
33.1%
1 2098
19.9%
- 1437
13.6%
3 977
 
9.3%
9 836
 
7.9%
2 492
 
4.7%
8 307
 
2.9%
7 303
 
2.9%
5 243
 
2.3%
4 202
 
1.9%

인허가일자
Real number (ℝ)

Distinct433
Distinct (%)90.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19899723
Minimum19680403
Maximum20190625
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-04-16T23:35:35.123574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19680403
5-th percentile19710726
Q119820719
median19910517
Q319980466
95-th percentile20060804
Maximum20190625
Range510222
Interquartile range (IQR)159746.5

Descriptive statistics

Standard deviation108955.35
Coefficient of variation (CV)0.0054752192
Kurtosis-0.63046244
Mean19899723
Median Absolute Deviation (MAD)70198
Skewness-0.058260854
Sum9.5319674 × 109
Variance1.1871267 × 1010
MonotonicityNot monotonic
2024-04-16T23:35:35.241003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19700714 5
 
1.0%
19740504 3
 
0.6%
19910822 2
 
0.4%
19990528 2
 
0.4%
19850528 2
 
0.4%
19980523 2
 
0.4%
19850621 2
 
0.4%
19740515 2
 
0.4%
19830603 2
 
0.4%
19710709 2
 
0.4%
Other values (423) 455
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 

Missing479
Missing (%)100.0%
Memory size4.3 KiB

영업상태구분코드
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
3
394 
1
85 

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
82.3%
1 85
 
17.7%

Length

2024-04-16T23:35:35.342116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:35:35.411902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 394
82.3%
1 85
 
17.7%

영업상태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
폐업
394 
영업/정상
85 

Length

Max length5
Median length2
Mean length2.5323591
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
82.3%
영업/정상 85
 
17.7%

Length

2024-04-16T23:35:35.492018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:35:35.565991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 394
82.3%
영업/정상 85
 
17.7%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2
394 
1
85 

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
82.3%
1 85
 
17.7%

Length

2024-04-16T23:35:35.642961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:35:35.721760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 394
82.3%
1 85
 
17.7%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
폐업
394 
영업
85 

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
82.3%
영업 85
 
17.7%

Length

2024-04-16T23:35:35.814909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:35:35.905122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 394
82.3%
영업 85
 
17.7%

폐업일자
Real number (ℝ)

MISSING 

Distinct281
Distinct (%)71.3%
Missing85
Missing (%)17.7%
Infinite0
Infinite (%)0.0%
Mean20031031
Minimum19830804
Maximum20211122
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-04-16T23:35:36.017790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19830804
5-th percentile19887192
Q119991020
median20030965
Q320071165
95-th percentile20170948
Maximum20211122
Range380318
Interquartile range (IQR)80144.75

Descriptive statistics

Standard deviation74016.853
Coefficient of variation (CV)0.0036951094
Kurtosis0.67555822
Mean20031031
Median Absolute Deviation (MAD)39947.5
Skewness-0.21242029
Sum7.8922264 × 109
Variance5.4784945 × 109
MonotonicityNot monotonic
2024-04-16T23:35:36.137055image/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
 
1.3%
19991016 5
 
1.0%
20100111 5
 
1.0%
20070809 5
 
1.0%
20060503 5
 
1.0%
Other values (271) 315
65.8%
(Missing) 85
 
17.7%
ValueCountFrequency (%)
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
1.3%
19891128 1
 
0.2%
19910718 1
 
0.2%
ValueCountFrequency (%)
20211122 1
0.2%
20211109 1
0.2%
20210923 1
0.2%
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%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing479
Missing (%)100.0%
Memory size4.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing479
Missing (%)100.0%
Memory size4.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing479
Missing (%)100.0%
Memory size4.3 KiB

소재지전화
Text

MISSING 

Distinct162
Distinct (%)36.2%
Missing32
Missing (%)6.7%
Memory size3.9 KiB
2024-04-16T23:35:36.401606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length3
Mean length6.0290828
Min length3

Characters and Unicode

Total characters2695
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 (%)34.5%

Sample

1st row051 2552029
2nd row051
3rd row051 2445538
4th row051 244 1005
5th row051 244 7716
ValueCountFrequency (%)
051 430
68.4%
6223618 3
 
0.5%
6428800 3
 
0.5%
5182627 2
 
0.3%
3288254 2
 
0.3%
3415119 2
 
0.3%
245 2
 
0.3%
5135 2
 
0.3%
5253435 2
 
0.3%
244 2
 
0.3%
Other values (178) 179
28.5%
2024-04-16T23:35:36.735072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 597
22.2%
1 570
21.2%
0 559
20.7%
182
 
6.8%
2 139
 
5.2%
3 134
 
5.0%
6 120
 
4.5%
8 120
 
4.5%
4 116
 
4.3%
7 88
 
3.3%
Other values (2) 70
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2512
93.2%
Space Separator 182
 
6.8%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 597
23.8%
1 570
22.7%
0 559
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 2695
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 597
22.2%
1 570
21.2%
0 559
20.7%
182
 
6.8%
2 139
 
5.2%
3 134
 
5.0%
6 120
 
4.5%
8 120
 
4.5%
4 116
 
4.3%
7 88
 
3.3%
Other values (2) 70
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2695
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 597
22.2%
1 570
21.2%
0 559
20.7%
182
 
6.8%
2 139
 
5.2%
3 134
 
5.0%
6 120
 
4.5%
8 120
 
4.5%
4 116
 
4.3%
7 88
 
3.3%
Other values (2) 70
 
2.6%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct183
Distinct (%)62.9%
Missing188
Missing (%)39.2%
Infinite0
Infinite (%)0.0%
Mean11.512302
Minimum0
Maximum98.66
Zeros54
Zeros (%)11.3%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-04-16T23:35:36.859333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15.48
median9.9
Q316
95-th percentile28.045
Maximum98.66
Range98.66
Interquartile range (IQR)10.52

Descriptive statistics

Standard deviation11.406889
Coefficient of variation (CV)0.99084342
Kurtosis16.007507
Mean11.512302
Median Absolute Deviation (MAD)5.14
Skewness3.0039336
Sum3350.08
Variance130.11712
MonotonicityNot monotonic
2024-04-16T23:35:36.966735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 54
 
11.3%
6.0 7
 
1.5%
12.0 6
 
1.3%
20.0 6
 
1.3%
18.0 5
 
1.0%
7.5 4
 
0.8%
10.5 3
 
0.6%
15.0 3
 
0.6%
5.7 3
 
0.6%
10.0 3
 
0.6%
Other values (173) 197
41.1%
(Missing) 188
39.2%
ValueCountFrequency (%)
0.0 54
11.3%
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 (%)59.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean610924.36
Minimum600013
Maximum619913
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-04-16T23:35:37.074178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600013
5-th percentile601811.9
Q1606062
median612050
Q3614868.5
95-th percentile617828
Maximum619913
Range19900
Interquartile range (IQR)8806.5

Descriptive statistics

Standard deviation5621.4862
Coefficient of variation (CV)0.0092016075
Kurtosis-1.2006268
Mean610924.36
Median Absolute Deviation (MAD)4751
Skewness-0.33997242
Sum2.9263277 × 108
Variance31601107
MonotonicityNot monotonic
2024-04-16T23:35:37.203089image/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
 
1.3%
601812 6
 
1.3%
617816 6
 
1.3%
601829 5
 
1.0%
617808 5
 
1.0%
617819 5
 
1.0%
617807 5
 
1.0%
607831 5
 
1.0%
Other values (275) 417
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 1
0.2%
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

Distinct456
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2024-04-16T23:35:37.398333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length38
Mean length20.356994
Min length15

Characters and Unicode

Total characters9751
Distinct characters142
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique434 ?
Unique (%)90.6%

Sample

1st row부산광역시 중구 부평동2가 77 (나69호, 70호)
2nd row부산광역시 중구 남포동4가 371
3rd row부산광역시 서구 아미동2가 42-16
4th row부산광역시 서구 암남동 3-12
5th row부산광역시 서구 충무동2가 4-2
ValueCountFrequency (%)
부산광역시 479
23.9%
부산진구 76
 
3.8%
사상구 70
 
3.5%
동래구 43
 
2.1%
동구 41
 
2.0%
사하구 39
 
1.9%
북구 38
 
1.9%
해운대구 30
 
1.5%
부전동 27
 
1.3%
금정구 27
 
1.3%
Other values (623) 1137
56.7%
2024-04-16T23:35:37.926920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1529
15.7%
부 601
 
6.2%
산 586
 
6.0%
동 579
 
5.9%
구 498
 
5.1%
광 487
 
5.0%
시 487
 
5.0%
역 479
 
4.9%
- 462
 
4.7%
1 462
 
4.7%
Other values (132) 3581
36.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5451
55.9%
Decimal Number 2264
23.2%
Space Separator 1529
 
15.7%
Dash Punctuation 462
 
4.7%
Uppercase Letter 20
 
0.2%
Other Punctuation 12
 
0.1%
Close Punctuation 7
 
0.1%
Open Punctuation 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 601
11.0%
산 586
 
10.8%
동 579
 
10.6%
구 498
 
9.1%
광 487
 
8.9%
시 487
 
8.9%
역 479
 
8.8%
사 118
 
2.2%
진 76
 
1.4%
상 75
 
1.4%
Other values (112) 1465
26.9%
Decimal Number
ValueCountFrequency (%)
1 462
20.4%
2 321
14.2%
3 253
11.2%
5 229
10.1%
4 225
9.9%
7 175
 
7.7%
6 167
 
7.4%
0 158
 
7.0%
8 149
 
6.6%
9 125
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
B 11
55.0%
T 8
40.0%
A 1
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 11
91.7%
/ 1
 
8.3%
Close Punctuation
ValueCountFrequency (%)
) 6
85.7%
] 1
 
14.3%
Space Separator
ValueCountFrequency (%)
1529
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 462
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5451
55.9%
Common 4280
43.9%
Latin 20
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 601
11.0%
산 586
 
10.8%
동 579
 
10.6%
구 498
 
9.1%
광 487
 
8.9%
시 487
 
8.9%
역 479
 
8.8%
사 118
 
2.2%
진 76
 
1.4%
상 75
 
1.4%
Other values (112) 1465
26.9%
Common
ValueCountFrequency (%)
1529
35.7%
- 462
 
10.8%
1 462
 
10.8%
2 321
 
7.5%
3 253
 
5.9%
5 229
 
5.4%
4 225
 
5.3%
7 175
 
4.1%
6 167
 
3.9%
0 158
 
3.7%
Other values (7) 299
 
7.0%
Latin
ValueCountFrequency (%)
B 11
55.0%
T 8
40.0%
A 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5451
55.9%
ASCII 4300
44.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1529
35.6%
- 462
 
10.7%
1 462
 
10.7%
2 321
 
7.5%
3 253
 
5.9%
5 229
 
5.3%
4 225
 
5.2%
7 175
 
4.1%
6 167
 
3.9%
0 158
 
3.7%
Other values (10) 319
 
7.4%
Hangul
ValueCountFrequency (%)
부 601
11.0%
산 586
 
10.8%
동 579
 
10.6%
구 498
 
9.1%
광 487
 
8.9%
시 487
 
8.9%
역 479
 
8.8%
사 118
 
2.2%
진 76
 
1.4%
상 75
 
1.4%
Other values (112) 1465
26.9%

도로명전체주소
Text

MISSING 

Distinct109
Distinct (%)99.1%
Missing369
Missing (%)77.0%
Memory size3.9 KiB
2024-04-16T23:35:38.173729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length35
Mean length28.036364
Min length21

Characters and Unicode

Total characters3084
Distinct characters161
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique108 ?
Unique (%)98.2%

Sample

1st row부산광역시 중구 흑교로 34, 나69.70호 (부평동2가)
2nd row부산광역시 서구 까치고개로197번길 21 (아미동2가)
3rd row부산광역시 서구 천해로45번길 7 (암남동)
4th row부산광역시 서구 구덕로119번길 40-4 (충무동2가)
5th row부산광역시 서구 암남공원로 16 (암남동)
ValueCountFrequency (%)
부산광역시 110
 
19.0%
사상구 14
 
2.4%
부산진구 13
 
2.2%
동래구 10
 
1.7%
해운대구 10
 
1.7%
북구 10
 
1.7%
사하구 10
 
1.7%
수영구 9
 
1.6%
1층 8
 
1.4%
서구 7
 
1.2%
Other values (263) 377
65.2%
2024-04-16T23:35:38.583796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
469
 
15.2%
동 143
 
4.6%
부 137
 
4.4%
산 135
 
4.4%
구 122
 
4.0%
시 117
 
3.8%
1 116
 
3.8%
광 115
 
3.7%
역 110
 
3.6%
( 110
 
3.6%
Other values (151) 1510
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1847
59.9%
Decimal Number 499
 
16.2%
Space Separator 469
 
15.2%
Open Punctuation 110
 
3.6%
Close Punctuation 110
 
3.6%
Other Punctuation 26
 
0.8%
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%
Decimal Number
ValueCountFrequency (%)
1 116
23.2%
2 71
14.2%
3 53
10.6%
6 50
10.0%
4 42
 
8.4%
5 41
 
8.2%
7 38
 
7.6%
0 32
 
6.4%
9 31
 
6.2%
8 25
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 25
96.2%
. 1
 
3.8%
Space Separator
ValueCountFrequency (%)
469
100.0%
Open Punctuation
ValueCountFrequency (%)
( 110
100.0%
Close 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 (%)
469
37.9%
1 116
 
9.4%
( 110
 
8.9%
) 110
 
8.9%
2 71
 
5.7%
3 53
 
4.3%
6 50
 
4.0%
4 42
 
3.4%
5 41
 
3.3%
7 38
 
3.1%
Other values (6) 136
 
11.0%
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 (%)
469
37.9%
1 116
 
9.4%
( 110
 
8.9%
) 110
 
8.9%
2 71
 
5.7%
3 53
 
4.3%
6 50
 
4.0%
4 42
 
3.4%
5 41
 
3.3%
7 38
 
3.1%
Other values (7) 137
 
11.1%
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%
Missing372
Missing (%)77.7%
Infinite0
Infinite (%)0.0%
Mean47876.692
Minimum46066
Maximum49476
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-04-16T23:35:38.716492image/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
2024-04-16T23:35:38.847684image/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%
47594 2
 
0.4%
46582 2
 
0.4%
47032 1
 
0.2%
47290 1
 
0.2%
48592 1
 
0.2%
47788 1
 
0.2%
Other values (91) 91
 
19.0%
(Missing) 372
77.7%
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

Distinct386
Distinct (%)80.6%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2024-04-16T23:35:39.119735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length4
Mean length4.2275574
Min length2

Characters and Unicode

Total characters2025
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

Unique330 ?
Unique (%)68.9%

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%
합천얼음 5
 
1.0%
부산얼음 5
 
1.0%
범일얼음 4
 
0.8%
영남얼음 4
 
0.8%
금성얼음 3
 
0.6%
Other values (383) 442
88.9%
2024-04-16T23:35:39.512008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
얼 345
 
17.0%
음 345
 
17.0%
상 89
 
4.4%
회 73
 
3.6%
집 53
 
2.6%
동 48
 
2.4%
일 46
 
2.3%
부 37
 
1.8%
성 33
 
1.6%
대 30
 
1.5%
Other values (217) 926
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2005
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 345
 
17.2%
음 345
 
17.2%
상 89
 
4.4%
회 73
 
3.6%
집 53
 
2.6%
동 48
 
2.4%
일 46
 
2.3%
부 37
 
1.8%
성 33
 
1.6%
대 30
 
1.5%
Other values (214) 906
45.2%
Space Separator
ValueCountFrequency (%)
18
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2005
99.0%
Common 20
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
얼 345
 
17.2%
음 345
 
17.2%
상 89
 
4.4%
회 73
 
3.6%
집 53
 
2.6%
동 48
 
2.4%
일 46
 
2.3%
부 37
 
1.8%
성 33
 
1.6%
대 30
 
1.5%
Other values (214) 906
45.2%
Common
ValueCountFrequency (%)
18
90.0%
2 1
 
5.0%
) 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2005
99.0%
ASCII 20
 
1.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
얼 345
 
17.2%
음 345
 
17.2%
상 89
 
4.4%
회 73
 
3.6%
집 53
 
2.6%
동 48
 
2.4%
일 46
 
2.3%
부 37
 
1.8%
성 33
 
1.6%
대 30
 
1.5%
Other values (214) 906
45.2%
ASCII
ValueCountFrequency (%)
18
90.0%
2 1
 
5.0%
) 1
 
5.0%

최종수정시점
Real number (ℝ)

Distinct210
Distinct (%)43.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0051512 × 1013
Minimum1.9990316 × 1013
Maximum2.0220616 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-04-16T23:35:39.640228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990316 × 1013
5-th percentile2.0000402 × 1013
Q12.0020358 × 1013
median2.0020828 × 1013
Q32.0070909 × 1013
95-th percentile2.0180141 × 1013
Maximum2.0220616 × 1013
Range2.3030011 × 1011
Interquartile range (IQR)5.0550551 × 1010

Descriptive statistics

Standard deviation5.3714317 × 1010
Coefficient of variation (CV)0.0026788163
Kurtosis0.97004405
Mean2.0051512 × 1013
Median Absolute Deviation (MAD)1.0314 × 1010
Skewness1.3962488
Sum9.6046742 × 1015
Variance2.8852279 × 1021
MonotonicityNot monotonic
2024-04-16T23:35:39.757355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20020816000000 46
 
9.6%
20020828000000 41
 
8.6%
20040217000000 27
 
5.6%
20010731000000 27
 
5.6%
20020305000000 15
 
3.1%
20020612000000 13
 
2.7%
20020814000000 13
 
2.7%
20010514000000 11
 
2.3%
19990330000000 11
 
2.3%
20020222000000 10
 
2.1%
Other values (200) 265
55.3%
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 (%)
20220616113028 1
0.2%
20211122105431 1
0.2%
20211112143247 1
0.2%
20211109111114 1
0.2%
20210923171256 1
0.2%
20210303135432 1
0.2%
20200615131735 1
0.2%
20200521104602 1
0.2%
20200429103935 1
0.2%
20200422135444 1
0.2%

데이터갱신구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
I
461 
U
 
18

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 461
96.2%
U 18
 
3.8%

Length

2024-04-16T23:35:39.866087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:35:39.936450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 461
96.2%
u 18
 
3.8%

데이터갱신일자
Categorical

IMBALANCE 

Distinct20
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2018-08-31 23:59:59.0
460 
2019-06-27 02:21:22.0
 
1
2018-10-21 02:37:06.0
 
1
2020-04-24 02:40:00.0
 
1
2022-06-18 02:40:00.0
 
1
Other values (15)
 
15

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique19 ?
Unique (%)4.0%

Sample

1st row2018-08-31 23:59:59.0
2nd row2018-08-31 23:59:59.0
3rd row2018-08-31 23:59:59.0
4th row2018-08-31 23:59:59.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 460
96.0%
2019-06-27 02:21:22.0 1
 
0.2%
2018-10-21 02:37:06.0 1
 
0.2%
2020-04-24 02:40:00.0 1
 
0.2%
2022-06-18 02:40:00.0 1
 
0.2%
2021-11-11 02:40:00.0 1
 
0.2%
2020-05-23 02:40:00.0 1
 
0.2%
2019-09-26 02:40:00.0 1
 
0.2%
2021-11-14 02:40:00.0 1
 
0.2%
2018-11-08 02:36:58.0 1
 
0.2%
Other values (10) 10
 
2.1%

Length

2024-04-16T23:35:40.012323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 460
48.0%
23:59:59.0 460
48.0%
02:40:00.0 15
 
1.6%
02:36:58.0 1
 
0.1%
02:37:01.0 1
 
0.1%
2018-11-21 1
 
0.1%
2021-11-24 1
 
0.1%
2020-05-01 1
 
0.1%
2020-06-17 1
 
0.1%
2020-04-11 1
 
0.1%
Other values (16) 16
 
1.7%

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
식용얼음판매업
479 

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 479
100.0%

Length

2024-04-16T23:35:40.097866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:35:40.172454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식용얼음판매업 479
100.0%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct379
Distinct (%)93.8%
Missing75
Missing (%)15.7%
Infinite0
Infinite (%)0.0%
Mean386453.47
Minimum376040.04
Maximum403430.89
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-04-16T23:35:40.253237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum376040.04
5-th percentile379869.74
Q1382254.66
median386765.57
Q3389953.41
95-th percentile393487.42
Maximum403430.89
Range27390.855
Interquartile range (IQR)7698.7434

Descriptive statistics

Standard deviation4816.184
Coefficient of variation (CV)0.01246252
Kurtosis-0.1272594
Mean386453.47
Median Absolute Deviation (MAD)3593.9698
Skewness0.37458709
Sum1.561272 × 108
Variance23195629
MonotonicityNot monotonic
2024-04-16T23:35:40.360661image/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%
383825.69780499 2
 
0.4%
393366.528779577 2
 
0.4%
378904.299819951 2
 
0.4%
390170.225935291 2
 
0.4%
393213.841162929 2
 
0.4%
379321.651090423 2
 
0.4%
380993.03498227 2
 
0.4%
379679.925556587 2
 
0.4%
Other values (369) 382
79.7%
(Missing) 75
 
15.7%
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%
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%
396119.553448278 1
0.2%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct379
Distinct (%)93.8%
Missing75
Missing (%)15.7%
Infinite0
Infinite (%)0.0%
Mean186746.02
Minimum174894.55
Maximum199237.92
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-04-16T23:35:40.487058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum174894.55
5-th percentile178662.75
Q1183845.46
median186449.67
Q3190743.13
95-th percentile194710.24
Maximum199237.92
Range24343.369
Interquartile range (IQR)6897.6708

Descriptive statistics

Standard deviation4959.3097
Coefficient of variation (CV)0.026556441
Kurtosis-0.39452172
Mean186746.02
Median Absolute Deviation (MAD)3505.5822
Skewness-0.022007156
Sum75445393
Variance24594753
MonotonicityNot monotonic
2024-04-16T23:35:40.636180image/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%
177181.350422336 2
 
0.4%
189566.495038421 2
 
0.4%
180909.234614291 2
 
0.4%
193598.889623478 2
 
0.4%
186185.376953244 2
 
0.4%
183030.975769364 2
 
0.4%
186914.505471542 2
 
0.4%
182935.928623368 2
 
0.4%
Other values (369) 382
79.7%
(Missing) 75
 
15.7%
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%
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%
196227.625071792 1
0.2%

위생업태명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
식용얼음판매업
479 

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 479
100.0%

Length

2024-04-16T23:35:40.745655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:35:40.822700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식용얼음판매업 479
100.0%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
393 
0
84 
1
 
2

Length

Max length4
Median length4
Mean length3.4613779
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> 393
82.0%
0 84
 
17.5%
1 2
 
0.4%

Length

2024-04-16T23:35:40.906536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:35:40.982685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 393
82.0%
0 84
 
17.5%
1 2
 
0.4%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
393 
0
84 
1
 
2

Length

Max length4
Median length4
Mean length3.4613779
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> 393
82.0%
0 84
 
17.5%
1 2
 
0.4%

Length

2024-04-16T23:35:41.086424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:35:41.170219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 393
82.0%
0 84
 
17.5%
1 2
 
0.4%

영업장주변구분명
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
기타
383 
<NA>
80 
주택가주변
 
16

Length

Max length5
Median length2
Mean length2.434238
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타 383
80.0%
<NA> 80
 
16.7%
주택가주변 16
 
3.3%

Length

2024-04-16T23:35:41.251387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:35:41.338634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타 383
80.0%
na 80
 
16.7%
주택가주변 16
 
3.3%

등급구분명
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
기타
359 
<NA>
80 
자율
40 

Length

Max length4
Median length2
Mean length2.3340292
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타 359
74.9%
<NA> 80
 
16.7%
자율 40
 
8.4%

Length

2024-04-16T23:35:41.422613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:35:41.504295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타 359
74.9%
na 80
 
16.7%
자율 40
 
8.4%

급수시설구분명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
421 
상수도전용
58 

Length

Max length5
Median length4
Mean length4.1210856
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> 421
87.9%
상수도전용 58
 
12.1%

Length

2024-04-16T23:35:41.584700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:35:41.655407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 421
87.9%
상수도전용 58
 
12.1%

총직원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
475 
0
 
4

Length

Max length4
Median length4
Mean length3.9749478
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> 475
99.2%
0 4
 
0.8%

Length

2024-04-16T23:35:41.742510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:35:41.821023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 475
99.2%
0 4
 
0.8%

본사직원수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
327 
0
152 

Length

Max length4
Median length4
Mean length3.0480167
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 327
68.3%
0 152
31.7%

Length

2024-04-16T23:35:41.904572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:35:41.982257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 327
68.3%
0 152
31.7%

공장사무직직원수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
327 
0
152 

Length

Max length4
Median length4
Mean length3.0480167
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 327
68.3%
0 152
31.7%

Length

2024-04-16T23:35:42.063842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:35:42.142160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 327
68.3%
0 152
31.7%

공장판매직직원수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
327 
0
152 

Length

Max length4
Median length4
Mean length3.0480167
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 327
68.3%
0 152
31.7%

Length

2024-04-16T23:35:42.223485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:35:42.310907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 327
68.3%
0 152
31.7%

공장생산직직원수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
327 
0
152 

Length

Max length4
Median length4
Mean length3.0480167
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 327
68.3%
0 152
31.7%

Length

2024-04-16T23:35:42.414728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:35:42.507042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 327
68.3%
0 152
31.7%

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
463 
임대
 
10
자가
 
6

Length

Max length4
Median length4
Mean length3.9331942
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> 463
96.7%
임대 10
 
2.1%
자가 6
 
1.3%

Length

2024-04-16T23:35:42.614989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:35:42.698043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 463
96.7%
임대 10
 
2.1%
자가 6
 
1.3%

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
467 
0
 
12

Length

Max length4
Median length4
Mean length3.9248434
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> 467
97.5%
0 12
 
2.5%

Length

2024-04-16T23:35:42.781522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:35:42.880763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 467
97.5%
0 12
 
2.5%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
467 
0
 
12

Length

Max length4
Median length4
Mean length3.9248434
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> 467
97.5%
0 12
 
2.5%

Length

2024-04-16T23:35:42.981707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:35:43.059548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 467
97.5%
0 12
 
2.5%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size611.0 B
False
479 
ValueCountFrequency (%)
False 479
100.0%
2024-04-16T23:35:43.119134image/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
475 
2.8
 
1
4.9
 
1
6.0
 
1
8.41
 
1

Length

Max length4
Median length3
Mean length3.0020877
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 (%)
0.0 475
99.2%
2.8 1
 
0.2%
4.9 1
 
0.2%
6.0 1
 
0.2%
8.41 1
 
0.2%

Length

2024-04-16T23:35:43.193297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T23:35:43.273584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 475
99.2%
2.8 1
 
0.2%
4.9 1
 
0.2%
6.0 1
 
0.2%
8.41 1
 
0.2%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing479
Missing (%)100.0%
Memory size4.3 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing479
Missing (%)100.0%
Memory size4.3 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing479
Missing (%)100.0%
Memory size4.3 KiB

Unnamed: 47
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing479
Missing (%)100.0%
Memory size4.3 KiB

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총직원수본사직원수공장사무직직원수공장판매직직원수공장생산직직원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지Unnamed: 47
01식용얼음판매업07_22_21_P32500003250000-111-1973-0000119730612<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.58600806부산광역시 중구 부평동2가 77 (나69호, 70호)부산광역시 중구 흑교로 34, 나69.70호 (부평동2가)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 남포동4가 371<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 아미동2가 42-16부산광역시 서구 까치고개로197번길 21 (아미동2가)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 3-12부산광역시 서구 천해로45번길 7 (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 충무동2가 4-2부산광역시 서구 구덕로119번길 40-4 (충무동2가)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 546-10부산광역시 서구 암남공원로 16 (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 서대신동1가 98 1층 일부부산광역시 서구 부용로 20 (서대신동1가)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 동대신동3가 127-29<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 토성동2가 9-7 1층부산광역시 서구 구덕로186번길 26, 1층 (토성동2가)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 부민동1가 2-1부산광역시 서구 보수대로 105 (부민동1가)49223대원상회20120517105508I2018-08-31 23:59:59.0식용얼음판매업384207.495228180321.995012식용얼음판매업<NA><NA>기타기타<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총직원수본사직원수공장사무직직원수공장판매직직원수공장생산직직원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지Unnamed: 47
469470식용얼음판매업07_22_21_P33900003390000-111-2015-0000120150316<NA>3폐업2폐업20150721<NA><NA><NA><NA>20.47617827부산광역시 사상구 삼락동 413-6 수림연립아파트 B동 101호부산광역시 사상구 낙동대로1264번길 24, B동 101호 (삼락동, 수림연립아파트)46912건성얼음20150326113914I2018-08-31 23:59:59.0식용얼음판매업380145.182748187718.364173식용얼음판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
470471식용얼음판매업07_22_21_P33900003390000-111-1996-0015019960514<NA>3폐업2폐업20050422<NA><NA><NA>051<NA>617807부산광역시 사상구 괘법동 532-21<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>
471472식용얼음판매업07_22_21_P33900003390000-111-1997-0015319970506<NA>3폐업2폐업19991016<NA><NA><NA>051<NA>617808부산광역시 사상구 괘법동 516-1<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>
472473식용얼음판매업07_22_21_P33900003390000-111-1997-0015519970529<NA>3폐업2폐업19991016<NA><NA><NA>051<NA>617808부산광역시 사상구 괘법동 524-15<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>
473474식용얼음판매업07_22_21_P33900003390000-111-1998-0015919980422<NA>3폐업2폐업20010215<NA><NA><NA>0510.0617822부산광역시 사상구 모라동 927-1<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>
474475식용얼음판매업07_22_21_P33900003390000-111-1998-0016219980525<NA>3폐업2폐업20050216<NA><NA><NA>051 3139911<NA>617838부산광역시 사상구 주례동 1162-173<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>
475476식용얼음판매업07_22_21_P34000003400000-111-1974-0018619740727<NA>3폐업2폐업20080128<NA><NA><NA><NA><NA>619903부산광역시 기장군 기장읍 대라리 73<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>
476477식용얼음판매업07_22_21_P34000003400000-111-1976-0018619760731<NA>3폐업2폐업20080129<NA><NA><NA><NA><NA>619912부산광역시 기장군 일광면 삼성리 115-5<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>
477478식용얼음판매업07_22_21_P34000003400000-111-1978-0018719780714<NA>3폐업2폐업20080326<NA><NA><NA><NA><NA>619913부산광역시 기장군 일광면 이천리 820-7<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>
478479식용얼음판매업07_22_21_P34000003400000-111-2001-0000120010530<NA>3폐업2폐업20120614<NA><NA><NA><NA><NA>619903부산광역시 기장군 기장읍 대라리 68-9부산광역시 기장군 기장읍 차성동로67번길 846066부산식품20020608000000I2018-08-31 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>