Overview

Dataset statistics

Number of variables48
Number of observations703
Missing cells7363
Missing cells (%)21.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory283.7 KiB
Average record size in memory413.2 B

Variable types

Numeric10
Categorical21
Text6
Unsupported9
DateTime1
Boolean1

Dataset

Description2021-08-01
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 (93.4%)Imbalance
위생업태명 is highly imbalanced (93.4%)Imbalance
남성종사자수 is highly imbalanced (67.0%)Imbalance
영업장주변구분명 is highly imbalanced (58.4%)Imbalance
급수시설구분명 is highly imbalanced (62.0%)Imbalance
공장판매직종업원수 is highly imbalanced (59.8%)Imbalance
보증액 is highly imbalanced (77.8%)Imbalance
월세액 is highly imbalanced (78.5%)Imbalance
인허가취소일자 has 703 (100.0%) missing valuesMissing
폐업일자 has 361 (51.4%) missing valuesMissing
휴업시작일자 has 703 (100.0%) missing valuesMissing
휴업종료일자 has 703 (100.0%) missing valuesMissing
재개업일자 has 703 (100.0%) missing valuesMissing
소재지전화 has 75 (10.7%) missing valuesMissing
소재지면적 has 112 (15.9%) missing valuesMissing
소재지우편번호 has 11 (1.6%) missing valuesMissing
도로명전체주소 has 205 (29.2%) missing valuesMissing
도로명우편번호 has 218 (31.0%) missing valuesMissing
좌표정보(x) has 27 (3.8%) missing valuesMissing
좌표정보(y) has 27 (3.8%) missing valuesMissing
총종업원수 has 703 (100.0%) missing valuesMissing
전통업소지정번호 has 703 (100.0%) missing valuesMissing
전통업소주된음식 has 703 (100.0%) missing valuesMissing
홈페이지 has 703 (100.0%) missing valuesMissing
Unnamed: 47 has 703 (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 583 (82.9%) zerosZeros

Reproduction

Analysis started2024-04-21 07:35:37.177506
Analysis finished2024-04-21 07:35:38.634693
Duration1.46 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct703
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean352
Minimum1
Maximum703
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.3 KiB
2024-04-21T16:35:38.827052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile36.1
Q1176.5
median352
Q3527.5
95-th percentile667.9
Maximum703
Range702
Interquartile range (IQR)351

Descriptive statistics

Standard deviation203.08291
Coefficient of variation (CV)0.57694007
Kurtosis-1.2
Mean352
Median Absolute Deviation (MAD)176
Skewness0
Sum247456
Variance41242.667
MonotonicityStrictly increasing
2024-04-21T16:35:39.290901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
2 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%
471 1
 
0.1%
472 1
 
0.1%
Other values (693) 693
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 (%)
703 1
0.1%
702 1
0.1%
701 1
0.1%
700 1
0.1%
699 1
0.1%
698 1
0.1%
697 1
0.1%
696 1
0.1%
695 1
0.1%
694 1
0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
식품판매업(기타)
703 

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) 703
100.0%

Length

2024-04-21T16:35:39.727326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:35:40.055521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품판매업(기타 703
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
07_22_13_P
703 

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 703
100.0%

Length

2024-04-21T16:35:40.408110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:35:40.743208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_13_p 703
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3333015.6
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.3 KiB
2024-04-21T16:35:41.049263image/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 deviation38375.243
Coefficient of variation (CV)0.01151367
Kurtosis-0.71085938
Mean3333015.6
Median Absolute Deviation (MAD)30000
Skewness0.01991749
Sum2.34311 × 109
Variance1.4726593 × 109
MonotonicityNot monotonic
2024-04-21T16:35:41.466628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3320000 97
13.8%
3340000 74
10.5%
3330000 66
9.4%
3290000 63
9.0%
3350000 54
7.7%
3390000 52
 
7.4%
3300000 45
 
6.4%
3400000 44
 
6.3%
3310000 41
 
5.8%
3380000 36
 
5.1%
Other values (6) 131
18.6%
ValueCountFrequency (%)
3250000 16
 
2.3%
3260000 12
 
1.7%
3270000 11
 
1.6%
3280000 29
 
4.1%
3290000 63
9.0%
3300000 45
6.4%
3310000 41
5.8%
3320000 97
13.8%
3330000 66
9.4%
3340000 74
10.5%
ValueCountFrequency (%)
3400000 44
6.3%
3390000 52
7.4%
3380000 36
 
5.1%
3370000 30
 
4.3%
3360000 33
 
4.7%
3350000 54
7.7%
3340000 74
10.5%
3330000 66
9.4%
3320000 97
13.8%
3310000 41
5.8%

관리번호
Text

UNIQUE 

Distinct703
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
2024-04-21T16:35:42.217249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters15466
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

Unique703 ?
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%
3350000-114-2016-00005 1
 
0.1%
3350000-114-2016-00001 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 (693) 693
98.6%
2024-04-21T16:35:43.192412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6048
39.1%
1 2286
 
14.8%
- 2109
 
13.6%
3 1536
 
9.9%
2 1014
 
6.6%
4 985
 
6.4%
9 604
 
3.9%
6 287
 
1.9%
5 229
 
1.5%
7 189
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13357
86.4%
Dash Punctuation 2109
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6048
45.3%
1 2286
 
17.1%
3 1536
 
11.5%
2 1014
 
7.6%
4 985
 
7.4%
9 604
 
4.5%
6 287
 
2.1%
5 229
 
1.7%
7 189
 
1.4%
8 179
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 2109
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15466
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6048
39.1%
1 2286
 
14.8%
- 2109
 
13.6%
3 1536
 
9.9%
2 1014
 
6.6%
4 985
 
6.4%
9 604
 
3.9%
6 287
 
1.9%
5 229
 
1.5%
7 189
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15466
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6048
39.1%
1 2286
 
14.8%
- 2109
 
13.6%
3 1536
 
9.9%
2 1014
 
6.6%
4 985
 
6.4%
9 604
 
3.9%
6 287
 
1.9%
5 229
 
1.5%
7 189
 
1.2%

인허가일자
Real number (ℝ)

Distinct627
Distinct (%)89.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20068536
Minimum19850909
Maximum20210609
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.3 KiB
2024-04-21T16:35:43.482697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19850909
5-th percentile19960617
Q119990268
median20070918
Q320140719
95-th percentile20200525
Maximum20210609
Range359700
Interquartile range (IQR)150450.5

Descriptive statistics

Standard deviation83233.137
Coefficient of variation (CV)0.0041474445
Kurtosis-1.2679754
Mean20068536
Median Absolute Deviation (MAD)79197
Skewness0.030711512
Sum1.410818 × 1010
Variance6.9277551 × 109
MonotonicityNot monotonic
2024-04-21T16:35:43.796293image/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%
19960722 3
 
0.4%
19960625 3
 
0.4%
19990622 3
 
0.4%
20000124 3
 
0.4%
19960617 3
 
0.4%
20020321 2
 
0.3%
Other values (617) 669
95.2%
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 (%)
20210609 1
0.1%
20210531 2
0.3%
20210507 1
0.1%
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%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing703
Missing (%)100.0%
Memory size6.3 KiB

영업상태구분코드
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
1
361 
3
342 

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
51.4%
3 342
48.6%

Length

2024-04-21T16:35:44.082433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:35:44.289575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 361
51.4%
3 342
48.6%

영업상태명
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
영업/정상
361 
폐업
342 

Length

Max length5
Median length5
Mean length3.5405405
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 361
51.4%
폐업 342
48.6%

Length

2024-04-21T16:35:44.479841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:35:44.679402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 361
51.4%
폐업 342
48.6%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
1
361 
2
342 

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
51.4%
2 342
48.6%

Length

2024-04-21T16:35:44.859187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:35:45.045794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 361
51.4%
2 342
48.6%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
영업
361 
폐업
342 

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
51.4%
폐업 342
48.6%

Length

2024-04-21T16:35:45.283367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:35:45.608592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 361
51.4%
폐업 342
48.6%

폐업일자
Real number (ℝ)

MISSING 

Distinct288
Distinct (%)84.2%
Missing361
Missing (%)51.4%
Infinite0
Infinite (%)0.0%
Mean20100312
Minimum19941010
Maximum20210601
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.3 KiB
2024-04-21T16:35:45.974770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19941010
5-th percentile19991565
Q120050912
median20095660
Q320167888
95-th percentile20201112
Maximum20210601
Range269591
Interquartile range (IQR)116976

Descriptive statistics

Standard deviation71300.457
Coefficient of variation (CV)0.0035472313
Kurtosis-1.2379543
Mean20100312
Median Absolute Deviation (MAD)64492
Skewness0.0091987485
Sum6.8743068 × 109
Variance5.0837552 × 109
MonotonicityNot monotonic
2024-04-21T16:35:46.429809image/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%
20151202 2
 
0.3%
20190201 2
 
0.3%
20000609 2
 
0.3%
20100310 2
 
0.3%
20140102 2
 
0.3%
20120221 2
 
0.3%
20140120 2
 
0.3%
Other values (278) 282
40.1%
(Missing) 361
51.4%
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 (%)
20210601 1
0.1%
20210527 1
0.1%
20210507 1
0.1%
20210504 1
0.1%
20210310 1
0.1%
20210303 2
0.3%
20210222 1
0.1%
20210203 1
0.1%
20210128 1
0.1%
20210127 1
0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing703
Missing (%)100.0%
Memory size6.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing703
Missing (%)100.0%
Memory size6.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing703
Missing (%)100.0%
Memory size6.3 KiB

소재지전화
Text

MISSING 

Distinct561
Distinct (%)89.3%
Missing75
Missing (%)10.7%
Memory size5.6 KiB
2024-04-21T16:35:47.760873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.667197
Min length1

Characters and Unicode

Total characters6699
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

Unique544 ?
Unique (%)86.6%

Sample

1st row051 529 5700
2nd row0517279910
3rd row051 7242949
4th row051 7227585
5th row051 722 4475
ValueCountFrequency (%)
051 569
39.4%
727 8
 
0.6%
724 6
 
0.4%
343 5
 
0.3%
728 5
 
0.3%
755 4
 
0.3%
782 4
 
0.3%
703 4
 
0.3%
759 4
 
0.3%
897 4
 
0.3%
Other values (706) 830
57.5%
2024-04-21T16:35:49.035744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1213
18.1%
5 1050
15.7%
1 1004
15.0%
827
12.3%
2 510
7.6%
3 418
 
6.2%
8 375
 
5.6%
7 363
 
5.4%
4 340
 
5.1%
6 332
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5872
87.7%
Space Separator 827
 
12.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1213
20.7%
5 1050
17.9%
1 1004
17.1%
2 510
8.7%
3 418
 
7.1%
8 375
 
6.4%
7 363
 
6.2%
4 340
 
5.8%
6 332
 
5.7%
9 267
 
4.5%
Space Separator
ValueCountFrequency (%)
827
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6699
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1213
18.1%
5 1050
15.7%
1 1004
15.0%
827
12.3%
2 510
7.6%
3 418
 
6.2%
8 375
 
5.6%
7 363
 
5.4%
4 340
 
5.1%
6 332
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6699
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1213
18.1%
5 1050
15.7%
1 1004
15.0%
827
12.3%
2 510
7.6%
3 418
 
6.2%
8 375
 
5.6%
7 363
 
5.4%
4 340
 
5.1%
6 332
 
5.0%

소재지면적
Text

MISSING 

Distinct544
Distinct (%)92.0%
Missing112
Missing (%)15.9%
Memory size5.6 KiB
2024-04-21T16:35:50.193098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length6
Mean length6.2318105
Min length3

Characters and Unicode

Total characters3683
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

Unique513 ?
Unique (%)86.8%

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%
660.00 2
 
0.3%
570.00 2
 
0.3%
476.84 2
 
0.3%
390.00 2
 
0.3%
580.80 2
 
0.3%
495.00 2
 
0.3%
304.50 2
 
0.3%
579.00 2
 
0.3%
Other values (534) 555
93.9%
2024-04-21T16:35:51.631072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 621
16.9%
. 591
16.0%
3 310
8.4%
5 296
8.0%
6 275
7.5%
4 274
7.4%
7 254
6.9%
2 250
6.8%
9 246
 
6.7%
1 240
 
6.5%
Other values (2) 326
8.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2990
81.2%
Other Punctuation 693
 
18.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 621
20.8%
3 310
10.4%
5 296
9.9%
6 275
9.2%
4 274
9.2%
7 254
8.5%
2 250
8.4%
9 246
 
8.2%
1 240
 
8.0%
8 224
 
7.5%
Other Punctuation
ValueCountFrequency (%)
. 591
85.3%
, 102
 
14.7%

Most occurring scripts

ValueCountFrequency (%)
Common 3683
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 621
16.9%
. 591
16.0%
3 310
8.4%
5 296
8.0%
6 275
7.5%
4 274
7.4%
7 254
6.9%
2 250
6.8%
9 246
 
6.7%
1 240
 
6.5%
Other values (2) 326
8.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3683
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 621
16.9%
. 591
16.0%
3 310
8.4%
5 296
8.0%
6 275
7.5%
4 274
7.4%
7 254
6.9%
2 250
6.8%
9 246
 
6.7%
1 240
 
6.5%
Other values (2) 326
8.9%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct342
Distinct (%)49.4%
Missing11
Missing (%)1.6%
Infinite0
Infinite (%)0.0%
Mean611966.63
Minimum600016
Maximum619953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.3 KiB
2024-04-21T16:35:51.953933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600016
5-th percentile602808
Q1607831
median612824.5
Q3616815.25
95-th percentile618814.9
Maximum619953
Range19937
Interquartile range (IQR)8984.25

Descriptive statistics

Standard deviation5225.5658
Coefficient of variation (CV)0.0085389718
Kurtosis-0.89024942
Mean611966.63
Median Absolute Deviation (MAD)4005.5
Skewness-0.37367878
Sum4.2348091 × 108
Variance27306538
MonotonicityNot monotonic
2024-04-21T16:35:52.423861image/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 (332) 622
88.5%
(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%

소재지전체주소
Text

Distinct512
Distinct (%)72.8%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
2024-04-21T16:35:53.591004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length45
Mean length23.766714
Min length14

Characters and Unicode

Total characters16708
Distinct characters245
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique424 ?
Unique (%)60.3%

Sample

1st row부산광역시 기장군 기장읍 내리 ***-*번지
2nd row부산광역시 기장군 장안읍 길천리 ***-*번지
3rd row부산광역시 기장군 일광면 삼성리 **-*번지
4th row부산광역시 기장군 기장읍 대라리 **-*번지
5th row부산광역시 기장군 기장읍 동부리 ***
ValueCountFrequency (%)
부산광역시 703
21.7%
번지 578
17.9%
145
 
4.5%
북구 97
 
3.0%
사하구 74
 
2.3%
해운대구 66
 
2.0%
부산진구 63
 
1.9%
금정구 54
 
1.7%
사상구 52
 
1.6%
동래구 45
 
1.4%
Other values (295) 1359
42.0%
2024-04-21T16:35:55.287280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 3323
19.9%
2534
15.2%
부 824
 
4.9%
산 813
 
4.9%
동 777
 
4.7%
광 726
 
4.3%
시 720
 
4.3%
지 706
 
4.2%
역 704
 
4.2%
구 704
 
4.2%
Other values (235) 4877
29.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10151
60.8%
Other Punctuation 3365
 
20.1%
Space Separator 2534
 
15.2%
Dash Punctuation 568
 
3.4%
Uppercase Letter 39
 
0.2%
Open Punctuation 23
 
0.1%
Close Punctuation 23
 
0.1%
Math Symbol 4
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 824
 
8.1%
산 813
 
8.0%
동 777
 
7.7%
광 726
 
7.2%
시 720
 
7.1%
지 706
 
7.0%
역 704
 
6.9%
구 704
 
6.9%
번 579
 
5.7%
사 142
 
1.4%
Other values (217) 3456
34.0%
Uppercase Letter
ValueCountFrequency (%)
B 18
46.2%
T 7
 
17.9%
G 3
 
7.7%
A 3
 
7.7%
L 2
 
5.1%
K 2
 
5.1%
H 2
 
5.1%
C 1
 
2.6%
S 1
 
2.6%
Other Punctuation
ValueCountFrequency (%)
* 3323
98.8%
, 38
 
1.1%
@ 4
 
0.1%
Space Separator
ValueCountFrequency (%)
2534
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 568
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10151
60.8%
Common 6517
39.0%
Latin 40
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 824
 
8.1%
산 813
 
8.0%
동 777
 
7.7%
광 726
 
7.2%
시 720
 
7.1%
지 706
 
7.0%
역 704
 
6.9%
구 704
 
6.9%
번 579
 
5.7%
사 142
 
1.4%
Other values (217) 3456
34.0%
Latin
ValueCountFrequency (%)
B 18
45.0%
T 7
 
17.5%
G 3
 
7.5%
A 3
 
7.5%
L 2
 
5.0%
K 2
 
5.0%
H 2
 
5.0%
e 1
 
2.5%
C 1
 
2.5%
S 1
 
2.5%
Common
ValueCountFrequency (%)
* 3323
51.0%
2534
38.9%
- 568
 
8.7%
, 38
 
0.6%
( 23
 
0.4%
) 23
 
0.4%
~ 4
 
0.1%
@ 4
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10151
60.8%
ASCII 6557
39.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 3323
50.7%
2534
38.6%
- 568
 
8.7%
, 38
 
0.6%
( 23
 
0.4%
) 23
 
0.4%
B 18
 
0.3%
T 7
 
0.1%
~ 4
 
0.1%
@ 4
 
0.1%
Other values (8) 15
 
0.2%
Hangul
ValueCountFrequency (%)
부 824
 
8.1%
산 813
 
8.0%
동 777
 
7.7%
광 726
 
7.2%
시 720
 
7.1%
지 706
 
7.0%
역 704
 
6.9%
구 704
 
6.9%
번 579
 
5.7%
사 142
 
1.4%
Other values (217) 3456
34.0%

도로명전체주소
Text

MISSING 

Distinct462
Distinct (%)92.8%
Missing205
Missing (%)29.2%
Memory size5.6 KiB
2024-04-21T16:35:56.478179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length52
Mean length30.359438
Min length20

Characters and Unicode

Total characters15119
Distinct characters293
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique430 ?
Unique (%)86.3%

Sample

1st row부산광역시 기장군 기장읍 기장대로 **, *층
2nd row부산광역시 기장군 장안읍 해맞이로 ***
3rd row부산광역시 기장군 기장읍 차성로 ***
4th row부산광역시 기장군 기장읍 차성동로 **
5th row부산광역시 기장군 기장읍 차성로 ***
ValueCountFrequency (%)
505
 
17.1%
부산광역시 498
 
16.8%
층 118
 
4.0%
해운대구 55
 
1.9%
사하구 55
 
1.9%
호 48
 
1.6%
부산진구 47
 
1.6%
금정구 41
 
1.4%
지하*층 40
 
1.4%
사상구 38
 
1.3%
Other values (551) 1514
51.2%
2024-04-21T16:35:58.136533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2466
16.3%
* 2242
 
14.8%
동 631
 
4.2%
부 606
 
4.0%
산 601
 
4.0%
시 535
 
3.5%
광 530
 
3.5%
역 498
 
3.3%
구 496
 
3.3%
로 492
 
3.3%
Other values (283) 6022
39.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8983
59.4%
Other Punctuation 2610
 
17.3%
Space Separator 2466
 
16.3%
Open Punctuation 479
 
3.2%
Close Punctuation 479
 
3.2%
Uppercase Letter 41
 
0.3%
Dash Punctuation 39
 
0.3%
Math Symbol 20
 
0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 631
 
7.0%
부 606
 
6.7%
산 601
 
6.7%
시 535
 
6.0%
광 530
 
5.9%
역 498
 
5.5%
구 496
 
5.5%
로 492
 
5.5%
대 232
 
2.6%
층 205
 
2.3%
Other values (262) 4157
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%
T 1
 
2.4%
P 1
 
2.4%
Other Punctuation
ValueCountFrequency (%)
* 2242
85.9%
, 366
 
14.0%
@ 2
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
e 1
50.0%
b 1
50.0%
Space Separator
ValueCountFrequency (%)
2466
100.0%
Open Punctuation
ValueCountFrequency (%)
( 479
100.0%
Close Punctuation
ValueCountFrequency (%)
) 479
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 39
100.0%
Math Symbol
ValueCountFrequency (%)
~ 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8983
59.4%
Common 6093
40.3%
Latin 43
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 631
 
7.0%
부 606
 
6.7%
산 601
 
6.7%
시 535
 
6.0%
광 530
 
5.9%
역 498
 
5.5%
구 496
 
5.5%
로 492
 
5.5%
대 232
 
2.6%
층 205
 
2.3%
Other values (262) 4157
46.3%
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%
T 1
 
2.3%
Other values (3) 3
 
7.0%
Common
ValueCountFrequency (%)
2466
40.5%
* 2242
36.8%
( 479
 
7.9%
) 479
 
7.9%
, 366
 
6.0%
- 39
 
0.6%
~ 20
 
0.3%
@ 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8983
59.4%
ASCII 6136
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2466
40.2%
* 2242
36.5%
( 479
 
7.8%
) 479
 
7.8%
, 366
 
6.0%
- 39
 
0.6%
~ 20
 
0.3%
B 20
 
0.3%
A 6
 
0.1%
C 4
 
0.1%
Other values (11) 15
 
0.2%
Hangul
ValueCountFrequency (%)
동 631
 
7.0%
부 606
 
6.7%
산 601
 
6.7%
시 535
 
6.0%
광 530
 
5.9%
역 498
 
5.5%
구 496
 
5.5%
로 492
 
5.5%
대 232
 
2.6%
층 205
 
2.3%
Other values (262) 4157
46.3%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct365
Distinct (%)75.3%
Missing218
Missing (%)31.0%
Infinite0
Infinite (%)0.0%
Mean47688.351
Minimum46008
Maximum49520
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.3 KiB
2024-04-21T16:35:58.550031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46008
5-th percentile46069.2
Q146759
median47712
Q348497
95-th percentile49388
Maximum49520
Range3512
Interquartile range (IQR)1738

Descriptive statistics

Standard deviation1062.0974
Coefficient of variation (CV)0.022271631
Kurtosis-1.1528971
Mean47688.351
Median Absolute Deviation (MAD)832
Skewness0.12762364
Sum23128850
Variance1128050.8
MonotonicityNot monotonic
2024-04-21T16:35:58.919580image/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%
49108 4
 
0.6%
49494 4
 
0.6%
46762 4
 
0.6%
47369 4
 
0.6%
47038 3
 
0.4%
48053 3
 
0.4%
49010 3
 
0.4%
Other values (355) 443
63.0%
(Missing) 218
31.0%
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 2
0.3%
49497 1
 
0.1%
49496 1
 
0.1%
49494 4
0.6%
49490 1
 
0.1%
49482 1
 
0.1%
49477 2
0.3%

사업장명
Text

Distinct606
Distinct (%)86.2%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
2024-04-21T16:35:59.683583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length20
Mean length8.230441
Min length2

Characters and Unicode

Total characters5786
Distinct characters325
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

Unique561 ?
Unique (%)79.8%

Sample

1st row농축산마트
2nd row동양마트
3rd row(주)홈마트
4th row빅세일기장점
5th row엄마야마트가자
ValueCountFrequency (%)
탑마트 18
 
2.0%
주)서원유통 18
 
2.0%
탑플러스마트 13
 
1.4%
롯데쇼핑(주)롯데슈퍼 12
 
1.3%
빅세일마트 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 (647) 784
87.3%
2024-04-21T16:36:00.687061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
마 466
 
8.1%
트 456
 
7.9%
) 274
 
4.7%
점 270
 
4.7%
( 270
 
4.7%
주 250
 
4.3%
195
 
3.4%
스 159
 
2.7%
산 91
 
1.6%
탑 89
 
1.5%
Other values (315) 3266
56.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4952
85.6%
Close Punctuation 274
 
4.7%
Open Punctuation 270
 
4.7%
Space Separator 195
 
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 (%)
마 466
 
9.4%
트 456
 
9.2%
점 270
 
5.5%
주 250
 
5.0%
스 159
 
3.2%
산 91
 
1.8%
탑 89
 
1.8%
데 74
 
1.5%
리 70
 
1.4%
지 69
 
1.4%
Other values (280) 2958
59.7%
Uppercase Letter
ValueCountFrequency (%)
S 15
22.4%
G 10
14.9%
C 8
11.9%
K 5
 
7.5%
M 5
 
7.5%
J 4
 
6.0%
H 3
 
4.5%
L 3
 
4.5%
F 2
 
3.0%
R 2
 
3.0%
Other values (7) 10
14.9%
Decimal Number
ValueCountFrequency (%)
2 9
50.0%
1 3
 
16.7%
3 2
 
11.1%
5 1
 
5.6%
6 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 (%)
195
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4952
85.6%
Common 764
 
13.2%
Latin 70
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 466
 
9.4%
트 456
 
9.2%
점 270
 
5.5%
주 250
 
5.0%
스 159
 
3.2%
산 91
 
1.8%
탑 89
 
1.8%
데 74
 
1.5%
리 70
 
1.4%
지 69
 
1.4%
Other values (280) 2958
59.7%
Latin
ValueCountFrequency (%)
S 15
21.4%
G 10
14.3%
C 8
11.4%
K 5
 
7.1%
M 5
 
7.1%
J 4
 
5.7%
H 3
 
4.3%
L 3
 
4.3%
F 2
 
2.9%
R 2
 
2.9%
Other values (10) 13
18.6%
Common
ValueCountFrequency (%)
) 274
35.9%
( 270
35.3%
195
25.5%
2 9
 
1.2%
1 3
 
0.4%
. 2
 
0.3%
- 2
 
0.3%
3 2
 
0.3%
5 1
 
0.1%
6 1
 
0.1%
Other values (5) 5
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4952
85.6%
ASCII 834
 
14.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
마 466
 
9.4%
트 456
 
9.2%
점 270
 
5.5%
주 250
 
5.0%
스 159
 
3.2%
산 91
 
1.8%
탑 89
 
1.8%
데 74
 
1.5%
리 70
 
1.4%
지 69
 
1.4%
Other values (280) 2958
59.7%
ASCII
ValueCountFrequency (%)
) 274
32.9%
( 270
32.4%
195
23.4%
S 15
 
1.8%
G 10
 
1.2%
2 9
 
1.1%
C 8
 
1.0%
K 5
 
0.6%
M 5
 
0.6%
J 4
 
0.5%
Other values (25) 39
 
4.7%

최종수정시점
Real number (ℝ)

Distinct620
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0136423 × 1013
Minimum1.9990607 × 1013
Maximum2.0210628 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.3 KiB
2024-04-21T16:36:00.961001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990607 × 1013
5-th percentile2.0010728 × 1013
Q12.0080514 × 1013
median2.0160426 × 1013
Q32.0191219 × 1013
95-th percentile2.0210428 × 1013
Maximum2.0210628 × 1013
Range2.200211 × 1011
Interquartile range (IQR)1.1070456 × 1011

Descriptive statistics

Standard deviation6.952198 × 1010
Coefficient of variation (CV)0.0034525486
Kurtosis-0.97002383
Mean2.0136423 × 1013
Median Absolute Deviation (MAD)4.0203004 × 1010
Skewness-0.73360152
Sum1.4155906 × 1016
Variance4.8333057 × 1021
MonotonicityNot monotonic
2024-04-21T16:36:01.256414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20020305000000 19
 
2.7%
20010728000000 13
 
1.8%
20010511000000 12
 
1.7%
20010510000000 10
 
1.4%
20010731000000 7
 
1.0%
20020225000000 6
 
0.9%
20020731000000 6
 
0.9%
20040618000000 5
 
0.7%
20020227000000 4
 
0.6%
20020608000000 3
 
0.4%
Other values (610) 618
87.9%
ValueCountFrequency (%)
19990607000000 1
 
0.1%
20010411000000 1
 
0.1%
20010510000000 10
1.4%
20010511000000 12
1.7%
20010716000000 1
 
0.1%
20010728000000 13
1.8%
20010731000000 7
1.0%
20010822000000 1
 
0.1%
20010823000000 1
 
0.1%
20010920000000 1
 
0.1%
ValueCountFrequency (%)
20210628104900 1
0.1%
20210624205353 1
0.1%
20210621144128 1
0.1%
20210619134305 1
0.1%
20210609132514 1
0.1%
20210609120058 1
0.1%
20210607154434 1
0.1%
20210604153729 1
0.1%
20210604144557 1
0.1%
20210604141322 1
0.1%

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
I
474 
U
229 

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 474
67.4%
U 229
32.6%

Length

2024-04-21T16:36:01.667095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:36:01.989269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 474
67.4%
u 229
32.6%

데이터갱신일자
Date

Distinct200
Distinct (%)28.4%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
Minimum2018-08-31 23:59:59
Maximum2021-06-30 02:40:00
2024-04-21T16:36:02.336385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T16:36:02.748380image/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
694 
식품조사처리업
 
8
<NA>
 
1

Length

Max length7
Median length7
Mean length6.9957326
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
기타식품판매업 694
98.7%
식품조사처리업 8
 
1.1%
<NA> 1
 
0.1%

Length

2024-04-21T16:36:03.175767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:36:03.517012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타식품판매업 694
98.7%
식품조사처리업 8
 
1.1%
na 1
 
0.1%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct545
Distinct (%)80.6%
Missing27
Missing (%)3.8%
Infinite0
Infinite (%)0.0%
Mean387536.83
Minimum366779.27
Maximum409357.26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.3 KiB
2024-04-21T16:36:03.861873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum366779.27
5-th percentile378632.84
Q1382713.5
median387859.41
Q3391612.29
95-th percentile399419.15
Maximum409357.26
Range42577.984
Interquartile range (IQR)8898.7911

Descriptive statistics

Standard deviation6844.745
Coefficient of variation (CV)0.01766218
Kurtosis0.42914925
Mean387536.83
Median Absolute Deviation (MAD)4518.1674
Skewness0.13775049
Sum2.619749 × 108
Variance46850535
MonotonicityNot monotonic
2024-04-21T16:36:04.308441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
387887.847333871 3
 
0.4%
390241.469793416 3
 
0.4%
396492.414590809 3
 
0.4%
393767.387550068 3
 
0.4%
392819.056323176 3
 
0.4%
392378.665367078 3
 
0.4%
385248.617963518 3
 
0.4%
383653.280812518 3
 
0.4%
381186.646505489 3
 
0.4%
385770.215097102 3
 
0.4%
Other values (535) 646
91.9%
(Missing) 27
 
3.8%
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 

Distinct545
Distinct (%)80.6%
Missing27
Missing (%)3.8%
Infinite0
Infinite (%)0.0%
Mean187542.06
Minimum174289.98
Maximum206150.93
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.3 KiB
2024-04-21T16:36:04.710774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum174289.98
5-th percentile177653.44
Q1182853.52
median187674.28
Q3191805.86
95-th percentile197820.18
Maximum206150.93
Range31860.948
Interquartile range (IQR)8952.3414

Descriptive statistics

Standard deviation6505.7794
Coefficient of variation (CV)0.034689709
Kurtosis-0.052476698
Mean187542.06
Median Absolute Deviation (MAD)4224.3491
Skewness0.27568745
Sum1.2677843 × 108
Variance42325166
MonotonicityNot monotonic
2024-04-21T16:36:05.353310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
187966.542955171 3
 
0.4%
197865.684207345 3
 
0.4%
187577.195994037 3
 
0.4%
190085.274360331 3
 
0.4%
187998.552610803 3
 
0.4%
184491.727482399 3
 
0.4%
192002.846191644 3
 
0.4%
197805.007825397 3
 
0.4%
190340.141159379 3
 
0.4%
192276.385535768 3
 
0.4%
Other values (535) 646
91.9%
(Missing) 27
 
3.8%
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
694 
식품조사처리업
 
8
<NA>
 
1

Length

Max length7
Median length7
Mean length6.9957326
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
기타식품판매업 694
98.7%
식품조사처리업 8
 
1.1%
<NA> 1
 
0.1%

Length

2024-04-21T16:36:05.796229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:36:06.139905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타식품판매업 694
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>
623 
0
79 
1
 
1

Length

Max length4
Median length4
Mean length3.658606
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> 623
88.6%
0 79
 
11.2%
1 1
 
0.1%

Length

2024-04-21T16:36:06.517300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:36:06.854294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 623
88.6%
0 79
 
11.2%
1 1
 
0.1%

여성종사자수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
<NA>
624 
0
79 

Length

Max length4
Median length4
Mean length3.6628734
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> 624
88.8%
0 79
 
11.2%

Length

2024-04-21T16:36:07.220168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:36:07.554879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 624
88.8%
0 79
 
11.2%

영업장주변구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
<NA>
504 
기타
188 
주택가주변
 
7
아파트지역
 
3
학교정화(절대)
 
1

Length

Max length8
Median length4
Mean length3.485064
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> 504
71.7%
기타 188
 
26.7%
주택가주변 7
 
1.0%
아파트지역 3
 
0.4%
학교정화(절대) 1
 
0.1%

Length

2024-04-21T16:36:07.929815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:36:08.284215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 504
71.7%
기타 188
 
26.7%
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>
504 
기타
189 
자율
 
10

Length

Max length4
Median length4
Mean length3.4338549
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> 504
71.7%
기타 189
 
26.9%
자율 10
 
1.4%

Length

2024-04-21T16:36:08.702252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:36:09.060742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 504
71.7%
기타 189
 
26.9%
자율 10
 
1.4%

급수시설구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
<NA>
603 
상수도전용
99 
상수도(음용)지하수(주방용)겸용
 
1

Length

Max length17
Median length4
Mean length4.1593172
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> 603
85.8%
상수도전용 99
 
14.1%
상수도(음용)지하수(주방용)겸용 1
 
0.1%

Length

2024-04-21T16:36:09.441861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:36:09.790578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 603
85.8%
상수도전용 99
 
14.1%
상수도(음용)지하수(주방용)겸용 1
 
0.1%

총종업원수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing703
Missing (%)100.0%
Memory size6.3 KiB

본사종업원수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
0
423 
<NA>
280 

Length

Max length4
Median length1
Mean length2.1948791
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 423
60.2%
<NA> 280
39.8%

Length

2024-04-21T16:36:10.178157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:36:10.503944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 423
60.2%
na 280
39.8%

공장사무직종업원수
Categorical

Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
0
420 
<NA>
280 
1
 
2
2
 
1

Length

Max length4
Median length1
Mean length2.1948791
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 420
59.7%
<NA> 280
39.8%
1 2
 
0.3%
2 1
 
0.1%

Length

2024-04-21T16:36:10.877406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:36:11.221003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 420
59.7%
na 280
39.8%
1 2
 
0.3%
2 1
 
0.1%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
0
418 
<NA>
280 
6
 
2
15
 
1
5
 
1

Length

Max length4
Median length1
Mean length2.197724
Min length1

Unique

Unique3 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
0 418
59.5%
<NA> 280
39.8%
6 2
 
0.3%
15 1
 
0.1%
5 1
 
0.1%
75 1
 
0.1%

Length

2024-04-21T16:36:11.601781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:36:11.948851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 418
59.5%
na 280
39.8%
6 2
 
0.3%
15 1
 
0.1%
5 1
 
0.1%
75 1
 
0.1%

공장생산직종업원수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
0
423 
<NA>
280 

Length

Max length4
Median length1
Mean length2.1948791
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 423
60.2%
<NA> 280
39.8%

Length

2024-04-21T16:36:12.348613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:36:12.685580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 423
60.2%
na 280
39.8%

건물소유구분명
Categorical

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
<NA>
526 
자가
121 
임대
56 

Length

Max length4
Median length4
Mean length3.4964438
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> 526
74.8%
자가 121
 
17.2%
임대 56
 
8.0%

Length

2024-04-21T16:36:13.080312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:36:13.399364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 526
74.8%
자가 121
 
17.2%
임대 56
 
8.0%

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
<NA>
678 
0
 
25

Length

Max length4
Median length4
Mean length3.8933144
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> 678
96.4%
0 25
 
3.6%

Length

2024-04-21T16:36:13.739368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:36:14.071817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 678
96.4%
0 25
 
3.6%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
<NA>
679 
0
 
24

Length

Max length4
Median length4
Mean length3.8975818
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> 679
96.6%
0 24
 
3.4%

Length

2024-04-21T16:36:14.434469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:36:14.781373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 679
96.6%
0 24
 
3.4%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size831.0 B
False
703 
ValueCountFrequency (%)
False 703
100.0%
2024-04-21T16:36:15.054715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

ZEROS 

Distinct116
Distinct (%)16.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean80.757425
Minimum0
Maximum9790.33
Zeros583
Zeros (%)82.9%
Negative0
Negative (%)0.0%
Memory size6.3 KiB
2024-04-21T16:36:15.396969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile554.661
Maximum9790.33
Range9790.33
Interquartile range (IQR)0

Descriptive statistics

Standard deviation462.34458
Coefficient of variation (CV)5.725103
Kurtosis286.09855
Mean80.757425
Median Absolute Deviation (MAD)0
Skewness14.82158
Sum56772.47
Variance213762.51
MonotonicityNot monotonic
2024-04-21T16:36:15.843577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 583
82.9%
6.46 3
 
0.4%
16.8 2
 
0.3%
495.0 2
 
0.3%
682.72 2
 
0.3%
5.8 1
 
0.1%
16.81 1
 
0.1%
38.02 1
 
0.1%
21.6 1
 
0.1%
35.2 1
 
0.1%
Other values (106) 106
 
15.1%
ValueCountFrequency (%)
0.0 583
82.9%
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 

Missing703
Missing (%)100.0%
Memory size6.3 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing703
Missing (%)100.0%
Memory size6.3 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing703
Missing (%)100.0%
Memory size6.3 KiB

Unnamed: 47
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing703
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 ***-*번지부산광역시 기장군 기장읍 기장대로 **, *층46076농축산마트20180905201521U2018-09-05 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 ***-*번지부산광역시 기장군 장안읍 해맞이로 ***<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 **-*번지<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 **-*번지<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 ***부산광역시 기장군 기장읍 차성로 ***46061엄마야마트가자20200629160333U2020-07-01 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 **-*번지<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 **번지부산광역시 기장군 기장읍 차성동로 **46066홈플러스 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 ***-*번지부산광역시 기장군 기장읍 차성로 ***46055우와마트20160205091400I2018-08-31 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 ***-**번지<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 ***번지<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
693694식품판매업(기타)07_22_13_P32600003260000-114-2019-0000120190327<NA>1영업/정상1영업<NA><NA><NA><NA>051 257 85891,131.95602838부산광역시 서구 토성동*가 **-*번지 경동 리인부산광역시 서구 보수대로 **, *층 (토성동*가, 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>
694695식품판매업(기타)07_22_13_P32500003250000-114-2021-0000120210114<NA>1영업/정상1영업<NA><NA><NA><NA>051 241 4980680.00600074부산광역시 중구 부평동*가 **-*부산광역시 중구 보수대로 **, *층 (부평동*가)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>
695696식품판매업(기타)07_22_13_P32500003250000-114-2009-0000220091218<NA>1영업/정상1영업<NA><NA><NA><NA>051 67830041,147.00600017부산광역시 중구 중앙동*가 **-*번지 외***필지 (롯데백화점 지하*층)부산광역시 중구 중앙대로 *, 지하*층 (중앙동*가, 외***필지 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>
696697식품판매업(기타)07_22_13_P32500003250000-114-2016-0000220161118<NA>1영업/정상1영업<NA><NA><NA><NA>051 469 5770595.77600815부산광역시 중구 중앙동*가 **-**번지부산광역시 중구 중앙대로**번길 *, *층 (중앙동*가)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>
697698식품판매업(기타)07_22_13_P32500003250000-114-2016-0000120160727<NA>1영업/정상1영업<NA><NA><NA><NA>051 254 0035576.13600044부산광역시 중구 남포동*가 **-*부산광역시 중구 자갈치해안로 **, *~*층 (남포동*가)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>
698699식품판매업(기타)07_22_13_P32500003250000-114-2014-0000120140825<NA>1영업/정상1영업<NA><NA><NA><NA><NA>963.00600017부산광역시 중구 중앙동*가 **-*번지 롯데몰 마트시네마동 롯데마트광복점 지하*층부산광역시 중구 중앙대로 *, 지하*층 (중앙동*가, 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>
699700식품판매업(기타)07_22_13_P32500003250000-114-2011-0000120110110<NA>1영업/정상1영업<NA><NA><NA><NA>051 2421577530.19600061부산광역시 중구 신창동*가 *-*번지 외 *필지부산광역시 중구 광복중앙로 ** (신창동*가, 외 *필지)48948가람리테일20120209093220I2018-08-31 23:59:59.0기타식품판매업385074.807762180030.905431기타식품판매업<NA><NA><NA><NA><NA><NA>0000자가<NA><NA>N0.0<NA><NA><NA><NA>
700701식품판매업(기타)07_22_13_P32500003250000-114-1996-0041619961114<NA>1영업/정상1영업<NA><NA><NA><NA>051 2454900473.37600806부산광역시 중구 부평동*가 **번지부산광역시 중구 부평*길 ** (부평동*가)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>
701702식품판매업(기타)07_22_13_P32500003250000-114-1996-0041419960906<NA>1영업/정상1영업<NA><NA><NA><NA>051 25077002,405.07600046부산광역시 중구 남포동*가 *-*부산광역시 중구 구덕로 ** (남포동*가)48982(주)농협부산경남유통 하나로클럽자갈치점20210127144302U2021-01-29 02:40:00.0기타식품판매업384820.119269179460.841059기타식품판매업00기타기타<NA><NA>0000<NA><NA><NA>N2405.07<NA><NA><NA><NA>
702703식품판매업(기타)07_22_13_P32500003250000-114-2000-0000220010809<NA>1영업/정상1영업<NA><NA><NA><NA>051 2488106565.36600046부산광역시 중구 남포동*가 *번지 신천지백화점 *층부산광역시 중구 자갈치로 **, *층 (남포동*가, 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>