Overview

Dataset statistics

Number of variables48
Number of observations699
Missing cells7325
Missing cells (%)21.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory282.0 KiB
Average record size in memory413.2 B

Variable types

Numeric10
Categorical21
Text6
Unsupported9
DateTime1
Boolean1

Dataset

Description2021-06-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123106

Alerts

개방서비스명 has constant value ""Constant
개방서비스id has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (93.3%)Imbalance
위생업태명 is highly imbalanced (93.3%)Imbalance
남성종사자수 is highly imbalanced (66.9%)Imbalance
영업장주변구분명 is highly imbalanced (58.3%)Imbalance
급수시설구분명 is highly imbalanced (62.1%)Imbalance
공장판매직종업원수 is highly imbalanced (59.8%)Imbalance
보증액 is highly imbalanced (77.7%)Imbalance
월세액 is highly imbalanced (78.4%)Imbalance
인허가취소일자 has 699 (100.0%) missing valuesMissing
폐업일자 has 361 (51.6%) missing valuesMissing
휴업시작일자 has 699 (100.0%) missing valuesMissing
휴업종료일자 has 699 (100.0%) missing valuesMissing
재개업일자 has 699 (100.0%) missing valuesMissing
소재지전화 has 73 (10.4%) missing valuesMissing
소재지면적 has 112 (16.0%) missing valuesMissing
소재지우편번호 has 11 (1.6%) missing valuesMissing
도로명전체주소 has 205 (29.3%) missing valuesMissing
도로명우편번호 has 218 (31.2%) missing valuesMissing
좌표정보(x) has 27 (3.9%) missing valuesMissing
좌표정보(y) has 27 (3.9%) missing valuesMissing
총종업원수 has 699 (100.0%) missing valuesMissing
전통업소지정번호 has 699 (100.0%) missing valuesMissing
전통업소주된음식 has 699 (100.0%) missing valuesMissing
홈페이지 has 699 (100.0%) missing valuesMissing
Unnamed: 47 has 699 (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
시설총규모 has 580 (83.0%) zerosZeros

Reproduction

Analysis started2024-04-21 07:41:47.053602
Analysis finished2024-04-21 07:41:48.503312
Duration1.45 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct699
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean350
Minimum1
Maximum699
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.3 KiB
2024-04-21T16:41:48.687086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile35.9
Q1175.5
median350
Q3524.5
95-th percentile664.1
Maximum699
Range698
Interquartile range (IQR)349

Descriptive statistics

Standard deviation201.92821
Coefficient of variation (CV)0.57693773
Kurtosis-1.2
Mean350
Median Absolute Deviation (MAD)175
Skewness0
Sum244650
Variance40775
MonotonicityStrictly increasing
2024-04-21T16:41:49.133233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
471 1
 
0.1%
463 1
 
0.1%
464 1
 
0.1%
465 1
 
0.1%
466 1
 
0.1%
467 1
 
0.1%
468 1
 
0.1%
469 1
 
0.1%
470 1
 
0.1%
Other values (689) 689
98.6%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
699 1
0.1%
698 1
0.1%
697 1
0.1%
696 1
0.1%
695 1
0.1%
694 1
0.1%
693 1
0.1%
692 1
0.1%
691 1
0.1%
690 1
0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
식품판매업(기타)
699 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row식품판매업(기타)
2nd row식품판매업(기타)
3rd row식품판매업(기타)
4th row식품판매업(기타)
5th row식품판매업(기타)

Common Values

ValueCountFrequency (%)
식품판매업(기타) 699
100.0%

Length

2024-04-21T16:41:49.559106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:41:49.861670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품판매업(기타 699
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
07_22_13_P
699 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row07_22_13_P
2nd row07_22_13_P
3rd row07_22_13_P
4th row07_22_13_P
5th row07_22_13_P

Common Values

ValueCountFrequency (%)
07_22_13_P 699
100.0%

Length

2024-04-21T16:41:50.186164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:41:50.490112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_13_p 699
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3333032.9
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.3 KiB
2024-04-21T16:41:50.775954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3270000
Q13305000
median3330000
Q33360000
95-th percentile3400000
Maximum3400000
Range150000
Interquartile range (IQR)55000

Descriptive statistics

Standard deviation38406.106
Coefficient of variation (CV)0.01152287
Kurtosis-0.71159173
Mean3333032.9
Median Absolute Deviation (MAD)30000
Skewness0.021120065
Sum2.32979 × 109
Variance1.475029 × 109
MonotonicityNot monotonic
2024-04-21T16:41:51.159028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3320000 97
13.9%
3340000 73
10.4%
3330000 65
9.3%
3290000 63
9.0%
3350000 54
7.7%
3390000 52
7.4%
3300000 45
 
6.4%
3400000 44
 
6.3%
3310000 41
 
5.9%
3380000 36
 
5.2%
Other values (6) 129
18.5%
ValueCountFrequency (%)
3250000 16
 
2.3%
3260000 12
 
1.7%
3270000 11
 
1.6%
3280000 28
 
4.0%
3290000 63
9.0%
3300000 45
6.4%
3310000 41
5.9%
3320000 97
13.9%
3330000 65
9.3%
3340000 73
10.4%
ValueCountFrequency (%)
3400000 44
6.3%
3390000 52
7.4%
3380000 36
 
5.2%
3370000 29
 
4.1%
3360000 33
 
4.7%
3350000 54
7.7%
3340000 73
10.4%
3330000 65
9.3%
3320000 97
13.9%
3310000 41
5.9%

관리번호
Text

UNIQUE 

Distinct699
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
2024-04-21T16:41:51.887506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters15378
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

Unique699 ?
Unique (%)100.0%

Sample

1st row3400000-114-2011-00002
2nd row3400000-114-2008-00001
3rd row3400000-114-1999-00233
4th row3400000-114-1998-00177
5th row3400000-114-2007-00002
ValueCountFrequency (%)
3400000-114-2011-00002 1
 
0.1%
3350000-114-1996-00432 1
 
0.1%
3350000-114-2020-00002 1
 
0.1%
3350000-114-2015-00002 1
 
0.1%
3350000-114-2015-00001 1
 
0.1%
3350000-114-2012-00006 1
 
0.1%
3350000-114-2018-00001 1
 
0.1%
3350000-114-2017-00002 1
 
0.1%
3350000-114-2012-00002 1
 
0.1%
3350000-114-1996-00433 1
 
0.1%
Other values (689) 689
98.6%
2024-04-21T16:41:52.987490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6012
39.1%
1 2272
 
14.8%
- 2097
 
13.6%
3 1527
 
9.9%
2 1004
 
6.5%
4 980
 
6.4%
9 604
 
3.9%
6 287
 
1.9%
5 229
 
1.5%
7 188
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13281
86.4%
Dash Punctuation 2097
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6012
45.3%
1 2272
 
17.1%
3 1527
 
11.5%
2 1004
 
7.6%
4 980
 
7.4%
9 604
 
4.5%
6 287
 
2.2%
5 229
 
1.7%
7 188
 
1.4%
8 178
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 2097
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15378
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6012
39.1%
1 2272
 
14.8%
- 2097
 
13.6%
3 1527
 
9.9%
2 1004
 
6.5%
4 980
 
6.4%
9 604
 
3.9%
6 287
 
1.9%
5 229
 
1.5%
7 188
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15378
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6012
39.1%
1 2272
 
14.8%
- 2097
 
13.6%
3 1527
 
9.9%
2 1004
 
6.5%
4 980
 
6.4%
9 604
 
3.9%
6 287
 
1.9%
5 229
 
1.5%
7 188
 
1.2%

인허가일자
Real number (ℝ)

Distinct624
Distinct (%)89.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20067723
Minimum19850909
Maximum20210405
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.3 KiB
2024-04-21T16:41:53.401466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19850909
5-th percentile19960617
Q119990210
median20070906
Q320140630
95-th percentile20200313
Maximum20210405
Range359496
Interquartile range (IQR)150419.5

Descriptive statistics

Standard deviation82772.138
Coefficient of variation (CV)0.0041246403
Kurtosis-1.2679414
Mean20067723
Median Absolute Deviation (MAD)70786
Skewness0.031922769
Sum1.4027338 × 1010
Variance6.8512268 × 109
MonotonicityNot monotonic
2024-04-21T16:41:54.049585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19960620 5
 
0.7%
19960619 5
 
0.7%
19960710 4
 
0.6%
19960923 3
 
0.4%
19960617 3
 
0.4%
19960722 3
 
0.4%
19960625 3
 
0.4%
20000124 3
 
0.4%
19990622 3
 
0.4%
20191011 2
 
0.3%
Other values (614) 665
95.1%
ValueCountFrequency (%)
19850909 1
0.1%
19890702 1
0.1%
19900314 1
0.1%
19920123 1
0.1%
19921230 1
0.1%
19930324 1
0.1%
19930524 1
0.1%
19931229 2
0.3%
19940215 1
0.1%
19940325 1
0.1%
ValueCountFrequency (%)
20210405 1
0.1%
20210329 1
0.1%
20210311 1
0.1%
20210305 1
0.1%
20210226 1
0.1%
20210219 1
0.1%
20210218 1
0.1%
20210202 1
0.1%
20210129 1
0.1%
20210121 1
0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing699
Missing (%)100.0%
Memory size6.3 KiB
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
1
361 
3
338 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 361
51.6%
3 338
48.4%

Length

2024-04-21T16:41:54.475762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:41:54.788125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 361
51.6%
3 338
48.4%

영업상태명
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
영업/정상
361 
폐업
338 

Length

Max length5
Median length5
Mean length3.5493562
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 361
51.6%
폐업 338
48.4%

Length

2024-04-21T16:41:55.146952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:41:55.476344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 361
51.6%
폐업 338
48.4%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
1
361 
2
338 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 361
51.6%
2 338
48.4%

Length

2024-04-21T16:41:55.813074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:41:56.124709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 361
51.6%
2 338
48.4%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
영업
361 
폐업
338 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 361
51.6%
폐업 338
48.4%

Length

2024-04-21T16:41:56.459347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:41:56.770882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 361
51.6%
폐업 338
48.4%

폐업일자
Real number (ℝ)

MISSING 

Distinct284
Distinct (%)84.0%
Missing361
Missing (%)51.6%
Infinite0
Infinite (%)0.0%
Mean20099008
Minimum19941010
Maximum20210310
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.3 KiB
2024-04-21T16:41:57.122582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19941010
5-th percentile19991102
Q120050848
median20091118
Q320161128
95-th percentile20201009
Maximum20210310
Range269300
Interquartile range (IQR)110280.25

Descriptive statistics

Standard deviation70697.867
Coefficient of variation (CV)0.0035174804
Kurtosis-1.226126
Mean20099008
Median Absolute Deviation (MAD)60084.5
Skewness0.019987895
Sum6.7934647 × 109
Variance4.9981884 × 109
MonotonicityNot monotonic
2024-04-21T16:41:57.579021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20051128 37
 
5.3%
20100607 5
 
0.7%
20050614 4
 
0.6%
20140725 2
 
0.3%
20151202 2
 
0.3%
20210303 2
 
0.3%
20100111 2
 
0.3%
20000609 2
 
0.3%
20190201 2
 
0.3%
20100701 2
 
0.3%
Other values (274) 278
39.8%
(Missing) 361
51.6%
ValueCountFrequency (%)
19941010 1
0.1%
19951107 1
0.1%
19960830 1
0.1%
19961101 1
0.1%
19970402 1
0.1%
19970424 1
0.1%
19970620 1
0.1%
19980220 1
0.1%
19980521 1
0.1%
19981102 1
0.1%
ValueCountFrequency (%)
20210310 1
0.1%
20210303 2
0.3%
20210222 1
0.1%
20210203 1
0.1%
20210128 1
0.1%
20210127 1
0.1%
20210120 1
0.1%
20201231 1
0.1%
20201228 1
0.1%
20201218 1
0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing699
Missing (%)100.0%
Memory size6.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing699
Missing (%)100.0%
Memory size6.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing699
Missing (%)100.0%
Memory size6.3 KiB

소재지전화
Text

MISSING 

Distinct559
Distinct (%)89.3%
Missing73
Missing (%)10.4%
Memory size5.6 KiB
2024-04-21T16:41:58.693960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.662939
Min length1

Characters and Unicode

Total characters6675
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

Unique542 ?
Unique (%)86.6%

Sample

1st row051 529 5700
2nd row0517279910
3rd row051 7242949
4th row051 7227585
5th row051 722 4475
ValueCountFrequency (%)
051 567
39.5%
727 8
 
0.6%
724 6
 
0.4%
728 5
 
0.3%
343 5
 
0.3%
755 4
 
0.3%
759 4
 
0.3%
897 4
 
0.3%
202 4
 
0.3%
782 4
 
0.3%
Other values (704) 826
57.5%
2024-04-21T16:42:00.194209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1209
18.1%
5 1047
15.7%
1 1001
15.0%
823
12.3%
2 508
7.6%
3 417
 
6.2%
8 374
 
5.6%
7 361
 
5.4%
4 337
 
5.0%
6 331
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5852
87.7%
Space Separator 823
 
12.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1209
20.7%
5 1047
17.9%
1 1001
17.1%
2 508
8.7%
3 417
 
7.1%
8 374
 
6.4%
7 361
 
6.2%
4 337
 
5.8%
6 331
 
5.7%
9 267
 
4.6%
Space Separator
ValueCountFrequency (%)
823
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6675
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1209
18.1%
5 1047
15.7%
1 1001
15.0%
823
12.3%
2 508
7.6%
3 417
 
6.2%
8 374
 
5.6%
7 361
 
5.4%
4 337
 
5.0%
6 331
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6675
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1209
18.1%
5 1047
15.7%
1 1001
15.0%
823
12.3%
2 508
7.6%
3 417
 
6.2%
8 374
 
5.6%
7 361
 
5.4%
4 337
 
5.0%
6 331
 
5.0%

소재지면적
Text

MISSING 

Distinct540
Distinct (%)92.0%
Missing112
Missing (%)16.0%
Memory size5.6 KiB
2024-04-21T16:42:01.463550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length6
Mean length6.2333901
Min length3

Characters and Unicode

Total characters3659
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique509 ?
Unique (%)86.7%

Sample

1st row546.94
2nd row348.25
3rd row1,336.00
4th row316.25
5th row1,821.83
ValueCountFrequency (%)
00 17
 
2.9%
396.00 3
 
0.5%
963.00 2
 
0.3%
476.84 2
 
0.3%
522.72 2
 
0.3%
407.87 2
 
0.3%
445.50 2
 
0.3%
536.14 2
 
0.3%
1,500.00 2
 
0.3%
599.76 2
 
0.3%
Other values (530) 551
93.9%
2024-04-21T16:42:03.142138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 616
16.8%
. 587
16.0%
3 308
8.4%
5 294
8.0%
6 274
7.5%
4 272
7.4%
7 253
6.9%
2 250
6.8%
9 244
 
6.7%
1 239
 
6.5%
Other values (2) 322
8.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2970
81.2%
Other Punctuation 689
 
18.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 616
20.7%
3 308
10.4%
5 294
9.9%
6 274
9.2%
4 272
9.2%
7 253
8.5%
2 250
8.4%
9 244
 
8.2%
1 239
 
8.0%
8 220
 
7.4%
Other Punctuation
ValueCountFrequency (%)
. 587
85.2%
, 102
 
14.8%

Most occurring scripts

ValueCountFrequency (%)
Common 3659
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 616
16.8%
. 587
16.0%
3 308
8.4%
5 294
8.0%
6 274
7.5%
4 272
7.4%
7 253
6.9%
2 250
6.8%
9 244
 
6.7%
1 239
 
6.5%
Other values (2) 322
8.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3659
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 616
16.8%
. 587
16.0%
3 308
8.4%
5 294
8.0%
6 274
7.5%
4 272
7.4%
7 253
6.9%
2 250
6.8%
9 244
 
6.7%
1 239
 
6.5%
Other values (2) 322
8.8%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct341
Distinct (%)49.6%
Missing11
Missing (%)1.6%
Infinite0
Infinite (%)0.0%
Mean611983.49
Minimum600016
Maximum619953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.3 KiB
2024-04-21T16:42:03.563278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600016
5-th percentile602808
Q1607831.75
median612830
Q3616816
95-th percentile618815.3
Maximum619953
Range19937
Interquartile range (IQR)8984.25

Descriptive statistics

Standard deviation5229.8547
Coefficient of variation (CV)0.0085457447
Kurtosis-0.88645584
Mean611983.49
Median Absolute Deviation (MAD)4002.5
Skewness-0.37954115
Sum4.2104464 × 108
Variance27351380
MonotonicityNot monotonic
2024-04-21T16:42:04.020656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
618814 10
 
1.4%
616826 8
 
1.1%
618200 7
 
1.0%
616829 7
 
1.0%
617808 7
 
1.0%
616807 7
 
1.0%
604813 6
 
0.9%
616827 6
 
0.9%
612824 6
 
0.9%
604851 6
 
0.9%
Other values (331) 618
88.4%
(Missing) 11
 
1.6%
ValueCountFrequency (%)
600016 2
0.3%
600017 2
0.3%
600044 1
 
0.1%
600046 4
0.6%
600061 2
0.3%
600074 2
0.3%
600805 1
 
0.1%
600806 1
 
0.1%
600815 1
 
0.1%
601060 2
0.3%
ValueCountFrequency (%)
619953 1
 
0.1%
619952 3
0.4%
619951 3
0.4%
619912 3
0.4%
619911 1
 
0.1%
619906 3
0.4%
619905 3
0.4%
619903 6
0.9%
619902 4
0.6%
619901 4
0.6%
Distinct645
Distinct (%)92.3%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
2024-04-21T16:42:05.091048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length45
Mean length23.796853
Min length14

Characters and Unicode

Total characters16634
Distinct characters254
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique596 ?
Unique (%)85.3%

Sample

1st row부산광역시 기장군 기장읍 내리 775-5번지
2nd row부산광역시 기장군 장안읍 길천리 207-3번지
3rd row부산광역시 기장군 일광면 삼성리 36-4번지
4th row부산광역시 기장군 기장읍 대라리 68-9번지
5th row부산광역시 기장군 기장읍 동부리 124
ValueCountFrequency (%)
부산광역시 699
 
21.7%
북구 97
 
3.0%
사하구 73
 
2.3%
해운대구 65
 
2.0%
부산진구 63
 
2.0%
금정구 54
 
1.7%
사상구 52
 
1.6%
동래구 45
 
1.4%
기장군 44
 
1.4%
남구 41
 
1.3%
Other values (954) 1986
61.7%
2024-04-21T16:42:06.631954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2521
 
15.2%
820
 
4.9%
809
 
4.9%
1 791
 
4.8%
773
 
4.6%
722
 
4.3%
716
 
4.3%
712
 
4.3%
700
 
4.2%
700
 
4.2%
Other values (244) 7370
44.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10116
60.8%
Decimal Number 3302
 
19.9%
Space Separator 2521
 
15.2%
Dash Punctuation 564
 
3.4%
Other Punctuation 41
 
0.2%
Uppercase Letter 39
 
0.2%
Close Punctuation 23
 
0.1%
Open Punctuation 23
 
0.1%
Math Symbol 4
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
820
 
8.1%
809
 
8.0%
773
 
7.6%
722
 
7.1%
716
 
7.1%
712
 
7.0%
700
 
6.9%
700
 
6.9%
587
 
5.8%
141
 
1.4%
Other values (217) 3436
34.0%
Decimal Number
ValueCountFrequency (%)
1 791
24.0%
2 407
12.3%
3 361
10.9%
5 303
 
9.2%
0 283
 
8.6%
4 279
 
8.4%
8 236
 
7.1%
7 225
 
6.8%
6 222
 
6.7%
9 195
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
B 18
46.2%
T 7
 
17.9%
G 3
 
7.7%
A 3
 
7.7%
L 2
 
5.1%
H 2
 
5.1%
K 2
 
5.1%
S 1
 
2.6%
C 1
 
2.6%
Other Punctuation
ValueCountFrequency (%)
, 37
90.2%
@ 4
 
9.8%
Space Separator
ValueCountFrequency (%)
2521
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 564
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10116
60.8%
Common 6478
38.9%
Latin 40
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
820
 
8.1%
809
 
8.0%
773
 
7.6%
722
 
7.1%
716
 
7.1%
712
 
7.0%
700
 
6.9%
700
 
6.9%
587
 
5.8%
141
 
1.4%
Other values (217) 3436
34.0%
Common
ValueCountFrequency (%)
2521
38.9%
1 791
 
12.2%
- 564
 
8.7%
2 407
 
6.3%
3 361
 
5.6%
5 303
 
4.7%
0 283
 
4.4%
4 279
 
4.3%
8 236
 
3.6%
7 225
 
3.5%
Other values (7) 508
 
7.8%
Latin
ValueCountFrequency (%)
B 18
45.0%
T 7
 
17.5%
G 3
 
7.5%
A 3
 
7.5%
L 2
 
5.0%
H 2
 
5.0%
K 2
 
5.0%
S 1
 
2.5%
e 1
 
2.5%
C 1
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10116
60.8%
ASCII 6518
39.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2521
38.7%
1 791
 
12.1%
- 564
 
8.7%
2 407
 
6.2%
3 361
 
5.5%
5 303
 
4.6%
0 283
 
4.3%
4 279
 
4.3%
8 236
 
3.6%
7 225
 
3.5%
Other values (17) 548
 
8.4%
Hangul
ValueCountFrequency (%)
820
 
8.1%
809
 
8.0%
773
 
7.6%
722
 
7.1%
716
 
7.1%
712
 
7.0%
700
 
6.9%
700
 
6.9%
587
 
5.8%
141
 
1.4%
Other values (217) 3436
34.0%

도로명전체주소
Text

MISSING 

Distinct481
Distinct (%)97.4%
Missing205
Missing (%)29.3%
Memory size5.6 KiB
2024-04-21T16:42:08.040607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length52
Mean length30.346154
Min length20

Characters and Unicode

Total characters14991
Distinct characters301
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique468 ?
Unique (%)94.7%

Sample

1st row부산광역시 기장군 기장읍 기장대로 85, 1층
2nd row부산광역시 기장군 장안읍 해맞이로 424
3rd row부산광역시 기장군 기장읍 차성로 314
4th row부산광역시 기장군 기장읍 차성동로 63
5th row부산광역시 기장군 기장읍 차성로 434
ValueCountFrequency (%)
부산광역시 494
 
16.8%
1층 95
 
3.2%
사하구 54
 
1.8%
해운대구 54
 
1.8%
부산진구 47
 
1.6%
금정구 41
 
1.4%
사상구 38
 
1.3%
지하1층 35
 
1.2%
기장군 34
 
1.2%
강서구 33
 
1.1%
Other values (903) 2011
68.5%
2024-04-21T16:42:09.883629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2447
 
16.3%
1 706
 
4.7%
626
 
4.2%
602
 
4.0%
597
 
4.0%
531
 
3.5%
526
 
3.5%
494
 
3.3%
492
 
3.3%
488
 
3.3%
Other values (291) 7482
49.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8910
59.4%
Space Separator 2447
 
16.3%
Decimal Number 2219
 
14.8%
Close Punctuation 475
 
3.2%
Open Punctuation 475
 
3.2%
Other Punctuation 364
 
2.4%
Uppercase Letter 41
 
0.3%
Dash Punctuation 38
 
0.3%
Math Symbol 20
 
0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
626
 
7.0%
602
 
6.8%
597
 
6.7%
531
 
6.0%
526
 
5.9%
494
 
5.5%
492
 
5.5%
488
 
5.5%
229
 
2.6%
201
 
2.3%
Other values (261) 4124
46.3%
Uppercase Letter
ValueCountFrequency (%)
B 20
48.8%
A 6
 
14.6%
C 4
 
9.8%
G 2
 
4.9%
K 2
 
4.9%
H 2
 
4.9%
L 1
 
2.4%
S 1
 
2.4%
N 1
 
2.4%
T 1
 
2.4%
Decimal Number
ValueCountFrequency (%)
1 706
31.8%
2 287
12.9%
3 220
 
9.9%
0 200
 
9.0%
4 196
 
8.8%
5 155
 
7.0%
7 129
 
5.8%
6 117
 
5.3%
9 106
 
4.8%
8 103
 
4.6%
Other Punctuation
ValueCountFrequency (%)
, 362
99.5%
@ 2
 
0.5%
Lowercase Letter
ValueCountFrequency (%)
e 1
50.0%
b 1
50.0%
Space Separator
ValueCountFrequency (%)
2447
100.0%
Close Punctuation
ValueCountFrequency (%)
) 475
100.0%
Open Punctuation
ValueCountFrequency (%)
( 475
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%
Math Symbol
ValueCountFrequency (%)
~ 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8910
59.4%
Common 6038
40.3%
Latin 43
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
626
 
7.0%
602
 
6.8%
597
 
6.7%
531
 
6.0%
526
 
5.9%
494
 
5.5%
492
 
5.5%
488
 
5.5%
229
 
2.6%
201
 
2.3%
Other values (261) 4124
46.3%
Common
ValueCountFrequency (%)
2447
40.5%
1 706
 
11.7%
) 475
 
7.9%
( 475
 
7.9%
, 362
 
6.0%
2 287
 
4.8%
3 220
 
3.6%
0 200
 
3.3%
4 196
 
3.2%
5 155
 
2.6%
Other values (7) 515
 
8.5%
Latin
ValueCountFrequency (%)
B 20
46.5%
A 6
 
14.0%
C 4
 
9.3%
G 2
 
4.7%
K 2
 
4.7%
H 2
 
4.7%
L 1
 
2.3%
S 1
 
2.3%
e 1
 
2.3%
b 1
 
2.3%
Other values (3) 3
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8910
59.4%
ASCII 6081
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2447
40.2%
1 706
 
11.6%
) 475
 
7.8%
( 475
 
7.8%
, 362
 
6.0%
2 287
 
4.7%
3 220
 
3.6%
0 200
 
3.3%
4 196
 
3.2%
5 155
 
2.5%
Other values (20) 558
 
9.2%
Hangul
ValueCountFrequency (%)
626
 
7.0%
602
 
6.8%
597
 
6.7%
531
 
6.0%
526
 
5.9%
494
 
5.5%
492
 
5.5%
488
 
5.5%
229
 
2.6%
201
 
2.3%
Other values (261) 4124
46.3%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct364
Distinct (%)75.7%
Missing218
Missing (%)31.2%
Infinite0
Infinite (%)0.0%
Mean47681.237
Minimum46008
Maximum49520
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.3 KiB
2024-04-21T16:42:10.289987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46008
5-th percentile46069
Q146759
median47712
Q348495
95-th percentile49384
Maximum49520
Range3512
Interquartile range (IQR)1736

Descriptive statistics

Standard deviation1061.2327
Coefficient of variation (CV)0.02225682
Kurtosis-1.151986
Mean47681.237
Median Absolute Deviation (MAD)832
Skewness0.13405055
Sum22934675
Variance1126214.8
MonotonicityNot monotonic
2024-04-21T16:42:10.727023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
46726 7
 
1.0%
46230 5
 
0.7%
46759 5
 
0.7%
47369 4
 
0.6%
49108 4
 
0.6%
46762 4
 
0.6%
49494 4
 
0.6%
47038 3
 
0.4%
47813 3
 
0.4%
49010 3
 
0.4%
Other values (354) 439
62.8%
(Missing) 218
31.2%
ValueCountFrequency (%)
46008 2
0.3%
46012 2
0.3%
46015 1
0.1%
46016 1
0.1%
46017 1
0.1%
46021 1
0.1%
46022 1
0.1%
46024 1
0.1%
46029 1
0.1%
46036 1
0.1%
ValueCountFrequency (%)
49520 1
 
0.1%
49519 1
 
0.1%
49515 1
 
0.1%
49511 1
 
0.1%
49497 1
 
0.1%
49496 1
 
0.1%
49494 4
0.6%
49490 1
 
0.1%
49482 1
 
0.1%
49477 2
0.3%
Distinct604
Distinct (%)86.4%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
2024-04-21T16:42:11.815038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length20
Mean length8.2432046
Min length2

Characters and Unicode

Total characters5762
Distinct characters324
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique559 ?
Unique (%)80.0%

Sample

1st row농축산마트
2nd row동양마트
3rd row(주)홈마트
4th row빅세일기장점
5th row엄마야마트가자
ValueCountFrequency (%)
탑마트 18
 
2.0%
주)서원유통 18
 
2.0%
롯데쇼핑(주)롯데슈퍼 12
 
1.3%
빅세일마트 11
 
1.2%
탑플러스마트 11
 
1.2%
탑세일마트 10
 
1.1%
더마트 9
 
1.0%
농축산마트 8
 
0.9%
주)지에스리테일 8
 
0.9%
홈플러스(주 7
 
0.8%
Other values (646) 781
87.5%
2024-04-21T16:42:13.077021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
462
 
8.0%
453
 
7.9%
) 274
 
4.8%
( 270
 
4.7%
268
 
4.7%
250
 
4.3%
194
 
3.4%
159
 
2.8%
92
 
1.6%
88
 
1.5%
Other values (314) 3252
56.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4929
85.5%
Close Punctuation 274
 
4.8%
Open Punctuation 270
 
4.7%
Space Separator 194
 
3.4%
Uppercase Letter 67
 
1.2%
Decimal Number 18
 
0.3%
Other Punctuation 4
 
0.1%
Lowercase Letter 3
 
0.1%
Dash Punctuation 2
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
462
 
9.4%
453
 
9.2%
268
 
5.4%
250
 
5.1%
159
 
3.2%
92
 
1.9%
88
 
1.8%
74
 
1.5%
69
 
1.4%
69
 
1.4%
Other values (279) 2945
59.7%
Uppercase Letter
ValueCountFrequency (%)
S 15
22.4%
G 10
14.9%
C 8
11.9%
M 5
 
7.5%
K 5
 
7.5%
J 4
 
6.0%
H 3
 
4.5%
L 3
 
4.5%
F 2
 
3.0%
T 2
 
3.0%
Other values (7) 10
14.9%
Decimal Number
ValueCountFrequency (%)
2 9
50.0%
1 3
 
16.7%
3 2
 
11.1%
6 1
 
5.6%
5 1
 
5.6%
4 1
 
5.6%
7 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 2
50.0%
& 1
25.0%
, 1
25.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
33.3%
n 1
33.3%
o 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 274
100.0%
Open Punctuation
ValueCountFrequency (%)
( 270
100.0%
Space Separator
ValueCountFrequency (%)
194
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4929
85.5%
Common 763
 
13.2%
Latin 70
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
462
 
9.4%
453
 
9.2%
268
 
5.4%
250
 
5.1%
159
 
3.2%
92
 
1.9%
88
 
1.8%
74
 
1.5%
69
 
1.4%
69
 
1.4%
Other values (279) 2945
59.7%
Latin
ValueCountFrequency (%)
S 15
21.4%
G 10
14.3%
C 8
11.4%
M 5
 
7.1%
K 5
 
7.1%
J 4
 
5.7%
H 3
 
4.3%
L 3
 
4.3%
F 2
 
2.9%
T 2
 
2.9%
Other values (10) 13
18.6%
Common
ValueCountFrequency (%)
) 274
35.9%
( 270
35.4%
194
25.4%
2 9
 
1.2%
1 3
 
0.4%
- 2
 
0.3%
3 2
 
0.3%
. 2
 
0.3%
6 1
 
0.1%
5 1
 
0.1%
Other values (5) 5
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4929
85.5%
ASCII 833
 
14.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
462
 
9.4%
453
 
9.2%
268
 
5.4%
250
 
5.1%
159
 
3.2%
92
 
1.9%
88
 
1.8%
74
 
1.5%
69
 
1.4%
69
 
1.4%
Other values (279) 2945
59.7%
ASCII
ValueCountFrequency (%)
) 274
32.9%
( 270
32.4%
194
23.3%
S 15
 
1.8%
G 10
 
1.2%
2 9
 
1.1%
C 8
 
1.0%
M 5
 
0.6%
K 5
 
0.6%
J 4
 
0.5%
Other values (25) 39
 
4.7%

최종수정시점
Real number (ℝ)

Distinct616
Distinct (%)88.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0135502 × 1013
Minimum1.9990607 × 1013
Maximum2.0210429 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.3 KiB
2024-04-21T16:42:13.337735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990607 × 1013
5-th percentile2.0010728 × 1013
Q12.0080368 × 1013
median2.0160304 × 1013
Q32.0191008 × 1013
95-th percentile2.0210208 × 1013
Maximum2.0210429 × 1013
Range2.1982215 × 1011
Interquartile range (IQR)1.1064002 × 1011

Descriptive statistics

Standard deviation6.9210746 × 1010
Coefficient of variation (CV)0.0034372497
Kurtosis-0.98160362
Mean2.0135502 × 1013
Median Absolute Deviation (MAD)4.0185943 × 1010
Skewness-0.7269294
Sum1.4074716 × 1016
Variance4.7901274 × 1021
MonotonicityNot monotonic
2024-04-21T16:42:13.767045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20020305000000 19
 
2.7%
20010728000000 13
 
1.9%
20010511000000 12
 
1.7%
20010510000000 10
 
1.4%
20010731000000 7
 
1.0%
20020731000000 6
 
0.9%
20020225000000 6
 
0.9%
20040618000000 5
 
0.7%
20020227000000 4
 
0.6%
20020608000000 3
 
0.4%
Other values (606) 614
87.8%
ValueCountFrequency (%)
19990607000000 1
 
0.1%
20010411000000 1
 
0.1%
20010510000000 10
1.4%
20010511000000 12
1.7%
20010716000000 1
 
0.1%
20010728000000 13
1.9%
20010731000000 7
1.0%
20010822000000 1
 
0.1%
20010823000000 1
 
0.1%
20010920000000 1
 
0.1%
ValueCountFrequency (%)
20210429145557 1
0.1%
20210428163625 1
0.1%
20210428135917 1
0.1%
20210423144219 1
0.1%
20210416162515 1
0.1%
20210415160252 1
0.1%
20210413165049 1
0.1%
20210408162115 1
0.1%
20210407111338 1
0.1%
20210406132814 1
0.1%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
I
477 
U
222 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 477
68.2%
U 222
31.8%

Length

2024-04-21T16:42:14.174855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:42:14.485489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 477
68.2%
u 222
31.8%
Distinct191
Distinct (%)27.3%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
Minimum2018-08-31 23:59:59
Maximum2021-05-01 02:40:00
2024-04-21T16:42:15.029523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T16:42:15.435838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
기타식품판매업
690 
식품조사처리업
 
8
<NA>
 
1

Length

Max length7
Median length7
Mean length6.9957082
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
기타식품판매업 690
98.7%
식품조사처리업 8
 
1.1%
<NA> 1
 
0.1%

Length

2024-04-21T16:42:15.853036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:42:16.185191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타식품판매업 690
98.7%
식품조사처리업 8
 
1.1%
na 1
 
0.1%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct543
Distinct (%)80.8%
Missing27
Missing (%)3.9%
Infinite0
Infinite (%)0.0%
Mean387534.99
Minimum366779.27
Maximum409357.26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.3 KiB
2024-04-21T16:42:16.533814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum366779.27
5-th percentile378628.47
Q1382713.5
median387859.41
Q3391612.29
95-th percentile399687.28
Maximum409357.26
Range42577.984
Interquartile range (IQR)8898.7911

Descriptive statistics

Standard deviation6850.8043
Coefficient of variation (CV)0.017677899
Kurtosis0.43258277
Mean387534.99
Median Absolute Deviation (MAD)4518.1674
Skewness0.13809262
Sum2.6042351 × 108
Variance46933519
MonotonicityNot monotonic
2024-04-21T16:42:16.960666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
392378.665367078 3
 
0.4%
385770.215097102 3
 
0.4%
381186.646505489 3
 
0.4%
380214.174893599 3
 
0.4%
383653.280812518 3
 
0.4%
393767.387550068 3
 
0.4%
385248.617963518 3
 
0.4%
387887.847333871 3
 
0.4%
387274.123524645 3
 
0.4%
390241.469793416 3
 
0.4%
Other values (533) 642
91.8%
(Missing) 27
 
3.9%
ValueCountFrequency (%)
366779.273666901 1
0.1%
366799.216536177 1
0.1%
366829.531355754 1
0.1%
368045.907990854 1
0.1%
369120.976733162 1
0.1%
371059.782971609 1
0.1%
371178.823833358 2
0.3%
371213.53898747 1
0.1%
371340.785805731 2
0.3%
371572.909768186 1
0.1%
ValueCountFrequency (%)
409357.257713329 1
0.1%
407434.691805327 1
0.1%
407418.648415535 1
0.1%
407291.08814632 1
0.1%
407245.567193252 2
0.3%
405376.494345932 1
0.1%
404088.637899457 1
0.1%
403214.461974909 1
0.1%
403206.588717483 1
0.1%
402168.434114938 1
0.1%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct543
Distinct (%)80.8%
Missing27
Missing (%)3.9%
Infinite0
Infinite (%)0.0%
Mean187567.51
Minimum174289.98
Maximum206150.93
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.3 KiB
2024-04-21T16:42:17.351839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum174289.98
5-th percentile177659.33
Q1182992.2
median187679.17
Q3191823.55
95-th percentile197832.31
Maximum206150.93
Range31860.948
Interquartile range (IQR)8831.3487

Descriptive statistics

Standard deviation6502.9799
Coefficient of variation (CV)0.034670076
Kurtosis-0.049320627
Mean187567.51
Median Absolute Deviation (MAD)4219.466
Skewness0.27587044
Sum1.2604537 × 108
Variance42288748
MonotonicityNot monotonic
2024-04-21T16:42:17.772000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
184491.727482399 3
 
0.4%
192276.385535768 3
 
0.4%
190340.141159379 3
 
0.4%
182729.264942974 3
 
0.4%
197805.007825397 3
 
0.4%
190085.274360331 3
 
0.4%
192002.846191644 3
 
0.4%
187966.542955171 3
 
0.4%
184575.633639399 3
 
0.4%
197865.684207345 3
 
0.4%
Other values (533) 642
91.8%
(Missing) 27
 
3.9%
ValueCountFrequency (%)
174289.976688419 1
0.1%
174307.148168245 1
0.1%
174638.869997904 1
0.1%
174774.894177567 2
0.3%
174811.513941031 1
0.1%
174835.290190736 1
0.1%
174871.825606384 1
0.1%
175314.286676535 2
0.3%
175515.467301635 1
0.1%
175649.486849662 1
0.1%
ValueCountFrequency (%)
206150.925111083 1
0.1%
206113.876185521 1
0.1%
205902.169686546 1
0.1%
205698.982734607 1
0.1%
205690.94819215 1
0.1%
205620.650144116 1
0.1%
205540.482346069 2
0.3%
205187.183814795 2
0.3%
204903.216935529 1
0.1%
204878.045544401 1
0.1%

위생업태명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
기타식품판매업
690 
식품조사처리업
 
8
<NA>
 
1

Length

Max length7
Median length7
Mean length6.9957082
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
기타식품판매업 690
98.7%
식품조사처리업 8
 
1.1%
<NA> 1
 
0.1%

Length

2024-04-21T16:42:18.208630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:42:18.542690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타식품판매업 690
98.7%
식품조사처리업 8
 
1.1%
na 1
 
0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
<NA>
619 
0
79 
1
 
1

Length

Max length4
Median length4
Mean length3.6566524
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 619
88.6%
0 79
 
11.3%
1 1
 
0.1%

Length

2024-04-21T16:42:18.904722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:42:19.233129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 619
88.6%
0 79
 
11.3%
1 1
 
0.1%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
<NA>
620 
0
79 

Length

Max length4
Median length4
Mean length3.6609442
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> 620
88.7%
0 79
 
11.3%

Length

2024-04-21T16:42:19.596666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:42:19.921509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 620
88.7%
0 79
 
11.3%

영업장주변구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
<NA>
500 
기타
188 
주택가주변
 
7
아파트지역
 
3
학교정화(절대)
 
1

Length

Max length8
Median length4
Mean length3.4821173
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 500
71.5%
기타 188
 
26.9%
주택가주변 7
 
1.0%
아파트지역 3
 
0.4%
학교정화(절대) 1
 
0.1%

Length

2024-04-21T16:42:20.274513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:42:20.609928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 500
71.5%
기타 188
 
26.9%
주택가주변 7
 
1.0%
아파트지역 3
 
0.4%
학교정화(절대 1
 
0.1%

등급구분명
Categorical

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
<NA>
500 
기타
189 
자율
 
10

Length

Max length4
Median length4
Mean length3.4306152
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> 500
71.5%
기타 189
 
27.0%
자율 10
 
1.4%

Length

2024-04-21T16:42:21.011405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:42:21.305693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 500
71.5%
기타 189
 
27.0%
자율 10
 
1.4%

급수시설구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
<NA>
600 
상수도전용
98 
상수도(음용)지하수(주방용)겸용
 
1

Length

Max length17
Median length4
Mean length4.1587983
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 600
85.8%
상수도전용 98
 
14.0%
상수도(음용)지하수(주방용)겸용 1
 
0.1%

Length

2024-04-21T16:42:21.506201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:42:21.691501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 600
85.8%
상수도전용 98
 
14.0%
상수도(음용)지하수(주방용)겸용 1
 
0.1%

총종업원수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing699
Missing (%)100.0%
Memory size6.3 KiB
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
0
420 
<NA>
279 

Length

Max length4
Median length1
Mean length2.1974249
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 420
60.1%
<NA> 279
39.9%

Length

2024-04-21T16:42:21.885512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:42:22.058370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 420
60.1%
na 279
39.9%
Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
0
417 
<NA>
279 
1
 
2
2
 
1

Length

Max length4
Median length1
Mean length2.1974249
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 417
59.7%
<NA> 279
39.9%
1 2
 
0.3%
2 1
 
0.1%

Length

2024-04-21T16:42:22.243819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:42:22.426551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 417
59.7%
na 279
39.9%
1 2
 
0.3%
2 1
 
0.1%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
0
415 
<NA>
279 
6
 
2
15
 
1
5
 
1

Length

Max length4
Median length1
Mean length2.2002861
Min length1

Unique

Unique3 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
0 415
59.4%
<NA> 279
39.9%
6 2
 
0.3%
15 1
 
0.1%
5 1
 
0.1%
75 1
 
0.1%

Length

2024-04-21T16:42:22.619924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:42:22.838618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 415
59.4%
na 279
39.9%
6 2
 
0.3%
15 1
 
0.1%
5 1
 
0.1%
75 1
 
0.1%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
0
420 
<NA>
279 

Length

Max length4
Median length1
Mean length2.1974249
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 420
60.1%
<NA> 279
39.9%

Length

2024-04-21T16:42:23.239777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:42:23.574926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 420
60.1%
na 279
39.9%
Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
<NA>
522 
자가
121 
임대
56 

Length

Max length4
Median length4
Mean length3.4935622
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 522
74.7%
자가 121
 
17.3%
임대 56
 
8.0%

Length

2024-04-21T16:42:23.946486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:42:24.299047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 522
74.7%
자가 121
 
17.3%
임대 56
 
8.0%

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
<NA>
674 
0
 
25

Length

Max length4
Median length4
Mean length3.8927039
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> 674
96.4%
0 25
 
3.6%

Length

2024-04-21T16:42:24.681882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:42:25.020825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 674
96.4%
0 25
 
3.6%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
<NA>
675 
0
 
24

Length

Max length4
Median length4
Mean length3.8969957
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> 675
96.6%
0 24
 
3.4%

Length

2024-04-21T16:42:25.370539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:42:25.700858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 675
96.6%
0 24
 
3.4%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size827.0 B
False
699 
ValueCountFrequency (%)
False 699
100.0%
2024-04-21T16:42:25.957780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

ZEROS 

Distinct115
Distinct (%)16.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean81.184149
Minimum0
Maximum9790.33
Zeros580
Zeros (%)83.0%
Negative0
Negative (%)0.0%
Memory size6.3 KiB
2024-04-21T16:42:26.294147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile558.925
Maximum9790.33
Range9790.33
Interquartile range (IQR)0

Descriptive statistics

Standard deviation463.63219
Coefficient of variation (CV)5.7108708
Kurtosis284.49795
Mean81.184149
Median Absolute Deviation (MAD)0
Skewness14.780164
Sum56747.72
Variance214954.8
MonotonicityNot monotonic
2024-04-21T16:42:26.732934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 580
83.0%
6.46 3
 
0.4%
16.8 2
 
0.3%
495.0 2
 
0.3%
682.72 2
 
0.3%
31.5 1
 
0.1%
21.6 1
 
0.1%
35.2 1
 
0.1%
11.5 1
 
0.1%
30.0 1
 
0.1%
Other values (105) 105
 
15.0%
ValueCountFrequency (%)
0.0 580
83.0%
2.81 1
 
0.1%
3.36 1
 
0.1%
4.0 1
 
0.1%
4.4 1
 
0.1%
4.94 1
 
0.1%
5.5 1
 
0.1%
5.6 1
 
0.1%
5.8 1
 
0.1%
6.0 1
 
0.1%
ValueCountFrequency (%)
9790.33 1
0.1%
3799.2 1
0.1%
2552.0 1
0.1%
2405.07 1
0.1%
2396.76 1
0.1%
1720.62 1
0.1%
1425.2 1
0.1%
1422.83 1
0.1%
1096.0 1
0.1%
981.54 1
0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing699
Missing (%)100.0%
Memory size6.3 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing699
Missing (%)100.0%
Memory size6.3 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing699
Missing (%)100.0%
Memory size6.3 KiB

Unnamed: 47
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing699
Missing (%)100.0%
Memory size6.3 KiB

Sample

번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지Unnamed: 47
01식품판매업(기타)07_22_13_P34000003400000-114-2011-0000220110808<NA>3폐업2폐업20180905<NA><NA><NA>051 529 5700546.94619902부산광역시 기장군 기장읍 내리 775-5번지부산광역시 기장군 기장읍 기장대로 85, 1층46076농축산마트20180905201521U2018-09-05 23:59:59.0기타식품판매업400809.773502191737.640257기타식품판매업<NA><NA><NA><NA><NA><NA>0000자가<NA><NA>N0.0<NA><NA><NA><NA>
12식품판매업(기타)07_22_13_P34000003400000-114-2008-0000120080110<NA>3폐업2폐업20130401<NA><NA><NA>0517279910348.25619952부산광역시 기장군 장안읍 길천리 207-3번지부산광역시 기장군 장안읍 해맞이로 424<NA>동양마트20080115100332I2018-08-31 23:59:59.0기타식품판매업407434.691805205690.948192기타식품판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
23식품판매업(기타)07_22_13_P34000003400000-114-1999-0023319990518<NA>3폐업2폐업20060306<NA><NA><NA>051 7242949<NA>619912부산광역시 기장군 일광면 삼성리 36-4번지<NA><NA>(주)홈마트20020608000000I2018-08-31 23:59:59.0기타식품판매업403206.588717198493.463979기타식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
34식품판매업(기타)07_22_13_P34000003400000-114-1998-0017719981020<NA>3폐업2폐업20060922<NA><NA><NA>051 7227585<NA>619903부산광역시 기장군 기장읍 대라리 68-9번지<NA><NA>빅세일기장점20020608000000I2018-08-31 23:59:59.0기타식품판매업401617.635228196097.170744기타식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
45식품판매업(기타)07_22_13_P34000003400000-114-2007-0000220070807<NA>3폐업2폐업20200629<NA><NA><NA>051 722 44751,336.00619905부산광역시 기장군 기장읍 동부리 124부산광역시 기장군 기장읍 차성로 31446061엄마야마트가자20200629160333U2020-07-01 02:40:00.0기타식품판매업401451.766564196278.102759기타식품판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
56식품판매업(기타)07_22_13_P34000003400000-114-2007-0000120070207<NA>3폐업2폐업20100111<NA><NA><NA>051 7274983316.25619951부산광역시 기장군 장안읍 월내리 11-1번지<NA><NA>세호마트20070207000000I2018-08-31 23:59:59.0기타식품판매업407245.567193205540.482346기타식품판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
67식품판매업(기타)07_22_13_P34000003400000-114-2003-0000120030801<NA>3폐업2폐업20180315<NA><NA><NA>051 724 45001,821.83619903부산광역시 기장군 기장읍 대라리 57번지부산광역시 기장군 기장읍 차성동로 6346066홈플러스 익스프레스 기장점20180315161123I2018-08-31 23:59:59.0기타식품판매업401671.55937196027.51628기타식품판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
78식품판매업(기타)07_22_13_P34000003400000-114-2002-0000120020928<NA>3폐업2폐업20160205<NA><NA><NA>0<NA>619901부산광역시 기장군 기장읍 교리 356-2번지부산광역시 기장군 기장읍 차성로 43446055우와마트20160205091400I2018-08-31 23:59:59.0기타식품판매업401756.2462197244.945141기타식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
89식품판매업(기타)07_22_13_P34000003400000-114-1998-0017619980117<NA>3폐업2폐업19990203<NA><NA><NA>051 7224176.00619903부산광역시 기장군 기장읍 대라리 162-13번지<NA><NA>무지개식품20020225000000I2018-08-31 23:59:59.0기타식품판매업401222.307932195403.978931기타식품판매업1<NA>아파트지역기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
910식품판매업(기타)07_22_13_P34000003400000-114-1996-0017419960819<NA>3폐업2폐업20030113<NA><NA><NA>051 7226771<NA>619905부산광역시 기장군 기장읍 동부리 124번지<NA><NA>성암빅마트기장점20020608000000I2018-08-31 23:59:59.0기타식품판매업401451.766564196278.102759기타식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지Unnamed: 47
689690식품판매업(기타)07_22_13_P32600003260000-114-2019-0000120190327<NA>1영업/정상1영업<NA><NA><NA><NA>051 257 85891,131.95602838부산광역시 서구 토성동1가 25-1번지 경동 리인부산광역시 서구 보수대로 27, 1층 (토성동1가, 경동 리인)49247경동빅마트20200423112743U2020-04-25 02:40:00.0기타식품판매업384479.162542179674.832922기타식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA><NA>
690691식품판매업(기타)07_22_13_P32500003250000-114-2021-0000120210114<NA>1영업/정상1영업<NA><NA><NA><NA>051 241 4980680.00600074부산광역시 중구 부평동4가 52-3부산광역시 중구 보수대로 82, 1층 (부평동4가)48973에스씨(SC)마트20210114145443I2021-01-16 00:23:15.0기타식품판매업384249.201711180080.172972기타식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N680.0<NA><NA><NA><NA>
691692식품판매업(기타)07_22_13_P32500003250000-114-2009-0000220091218<NA>1영업/정상1영업<NA><NA><NA><NA>051 67830041,147.00600017부산광역시 중구 중앙동7가 20-1번지 외110필지 (롯데백화점 지하1층)부산광역시 중구 중앙대로 2, 지하1층 (중앙동7가, 외110필지 롯데백화점)48944롯데쇼핑주식회사20200213155607U2020-02-15 02:40:00.0기타식품판매업385590.814677179553.867032기타식품판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
692693식품판매업(기타)07_22_13_P32500003250000-114-2016-0000220161118<NA>1영업/정상1영업<NA><NA><NA><NA>051 469 5770595.77600815부산광역시 중구 중앙동4가 37-16번지부산광역시 중구 중앙대로81번길 9, 1층 (중앙동4가)48930(주)두배로마트20170811133214I2018-08-31 23:59:59.0기타식품판매업385473.57641180297.978229기타식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N595.77<NA><NA><NA><NA>
693694식품판매업(기타)07_22_13_P32500003250000-114-2016-0000120160727<NA>1영업/정상1영업<NA><NA><NA><NA>051 254 0035576.13600044부산광역시 중구 남포동4가 44-3부산광역시 중구 자갈치해안로 60, 1~3층 (남포동4가)48984제1,2구 잠수기수협 바다마트20201224104416U2020-12-26 02:40:00.0기타식품판매업385191.013393179401.283402기타식품판매업<NA><NA><NA><NA><NA><NA>0000자가<NA><NA>N576.13<NA><NA><NA><NA>
694695식품판매업(기타)07_22_13_P32500003250000-114-2014-0000120140825<NA>1영업/정상1영업<NA><NA><NA><NA><NA>963.00600017부산광역시 중구 중앙동7가 20-1번지 롯데몰 마트시네마동 롯데마트광복점 지하2층부산광역시 중구 중앙대로 2, 지하1층 (중앙동7가, 롯데몰 마트시네마동 롯데마트광복점)48944롯데쇼핑(주)롯데마트광복점20170417172731I2018-08-31 23:59:59.0기타식품판매업385590.814677179553.867032기타식품판매업<NA><NA><NA><NA>상수도전용<NA>00750자가<NA><NA>N0.0<NA><NA><NA><NA>
695696식품판매업(기타)07_22_13_P32500003250000-114-2011-0000120110110<NA>1영업/정상1영업<NA><NA><NA><NA>051 2421577530.19600061부산광역시 중구 신창동1가 1-3번지 외 1필지부산광역시 중구 광복중앙로 33 (신창동1가, 외 1필지)48948가람리테일20120209093220I2018-08-31 23:59:59.0기타식품판매업385074.807762180030.905431기타식품판매업<NA><NA><NA><NA><NA><NA>0000자가<NA><NA>N0.0<NA><NA><NA><NA>
696697식품판매업(기타)07_22_13_P32500003250000-114-1996-0041619961114<NA>1영업/정상1영업<NA><NA><NA><NA>051 2454900473.37600806부산광역시 중구 부평동2가 16번지부산광역시 중구 부평1길 48 (부평동2가)48977(주)프로유통(빅세일마트)20160615114558I2018-08-31 23:59:59.0기타식품판매업384663.000969179927.870276기타식품판매업<NA><NA>기타기타<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
697698식품판매업(기타)07_22_13_P32500003250000-114-1996-0041419960906<NA>1영업/정상1영업<NA><NA><NA><NA>051 25077002,405.07600046부산광역시 중구 남포동6가 1-0부산광역시 중구 구덕로 73 (남포동6가)48982(주)농협부산경남유통 하나로클럽자갈치점20210127144302U2021-01-29 02:40:00.0기타식품판매업384820.119269179460.841059기타식품판매업00기타기타<NA><NA>0000<NA><NA><NA>N2405.07<NA><NA><NA><NA>
698699식품판매업(기타)07_22_13_P32500003250000-114-2000-0000220010809<NA>1영업/정상1영업<NA><NA><NA><NA>051 2488106565.36600046부산광역시 중구 남포동6가 3번지 신천지백화점 1층부산광역시 중구 자갈치로 33, 1층 (남포동6가, 신천지백화점)48982자갈치 탑마트20130402154802I2018-08-31 23:59:59.0기타식품판매업384836.914456179432.73458기타식품판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N565.36<NA><NA><NA><NA>