Overview

Dataset statistics

Number of variables48
Number of observations708
Missing cells6708
Missing cells (%)19.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory285.7 KiB
Average record size in memory413.2 B

Variable types

Numeric10
Categorical22
Text6
Unsupported8
DateTime1
Boolean1

Dataset

Description2022-01-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123106

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (96.5%)Imbalance
위생업태명 is highly imbalanced (96.5%)Imbalance
남성종사자수 is highly imbalanced (62.9%)Imbalance
영업장주변구분명 is highly imbalanced (58.5%)Imbalance
총종업원수 is highly imbalanced (82.2%)Imbalance
공장판매직종업원수 is highly imbalanced (59.9%)Imbalance
보증액 is highly imbalanced (66.4%)Imbalance
월세액 is highly imbalanced (67.0%)Imbalance
인허가취소일자 has 708 (100.0%) missing valuesMissing
폐업일자 has 362 (51.1%) missing valuesMissing
휴업시작일자 has 708 (100.0%) missing valuesMissing
휴업종료일자 has 708 (100.0%) missing valuesMissing
재개업일자 has 708 (100.0%) missing valuesMissing
소재지전화 has 80 (11.3%) missing valuesMissing
소재지면적 has 112 (15.8%) missing valuesMissing
소재지우편번호 has 13 (1.8%) missing valuesMissing
도로명전체주소 has 205 (29.0%) missing valuesMissing
도로명우편번호 has 218 (30.8%) missing valuesMissing
좌표정보(x) has 27 (3.8%) missing valuesMissing
좌표정보(y) has 27 (3.8%) missing valuesMissing
전통업소지정번호 has 708 (100.0%) missing valuesMissing
전통업소주된음식 has 708 (100.0%) missing valuesMissing
홈페이지 has 708 (100.0%) missing valuesMissing
Unnamed: 47 has 708 (100.0%) missing valuesMissing
번호 has unique valuesUnique
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 47 is an unsupported type, check if it needs cleaning or further analysisUnsupported
시설총규모 has 572 (80.8%) zerosZeros

Reproduction

Analysis started2024-04-21 07:41:13.931072
Analysis finished2024-04-21 07:41:15.294907
Duration1.36 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct708
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean354.5
Minimum1
Maximum708
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.3 KiB
2024-04-21T16:41:15.478946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile36.35
Q1177.75
median354.5
Q3531.25
95-th percentile672.65
Maximum708
Range707
Interquartile range (IQR)353.5

Descriptive statistics

Standard deviation204.52628
Coefficient of variation (CV)0.57694297
Kurtosis-1.2
Mean354.5
Median Absolute Deviation (MAD)177
Skewness0
Sum250986
Variance41831
MonotonicityStrictly increasing
2024-04-21T16:41:15.927385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
445 1
 
0.1%
469 1
 
0.1%
470 1
 
0.1%
471 1
 
0.1%
472 1
 
0.1%
473 1
 
0.1%
474 1
 
0.1%
475 1
 
0.1%
476 1
 
0.1%
Other values (698) 698
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 (%)
708 1
0.1%
707 1
0.1%
706 1
0.1%
705 1
0.1%
704 1
0.1%
703 1
0.1%
702 1
0.1%
701 1
0.1%
700 1
0.1%
699 1
0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
식품판매업(기타)
708 

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) 708
100.0%

Length

2024-04-21T16:41:16.292390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:41:16.462314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품판매업(기타 708
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
07_22_13_P
708 

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 708
100.0%

Length

2024-04-21T16:41:16.634210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:41:16.805094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_13_p 708
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3333432.2
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.3 KiB
2024-04-21T16:41:16.959339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3270000
Q13310000
median3330000
Q33360000
95-th percentile3400000
Maximum3400000
Range150000
Interquartile range (IQR)50000

Descriptive statistics

Standard deviation38562.57
Coefficient of variation (CV)0.011568428
Kurtosis-0.72985049
Mean3333432.2
Median Absolute Deviation (MAD)30000
Skewness0.013577839
Sum2.36007 × 109
Variance1.4870718 × 109
MonotonicityNot monotonic
2024-04-21T16:41:17.167431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3320000 97
13.7%
3340000 74
10.5%
3330000 66
9.3%
3290000 63
8.9%
3390000 54
7.6%
3350000 54
7.6%
3400000 46
 
6.5%
3300000 45
 
6.4%
3310000 41
 
5.8%
3380000 37
 
5.2%
Other values (6) 131
18.5%
ValueCountFrequency (%)
3250000 16
 
2.3%
3260000 12
 
1.7%
3270000 11
 
1.6%
3280000 29
 
4.1%
3290000 63
8.9%
3300000 45
6.4%
3310000 41
5.8%
3320000 97
13.7%
3330000 66
9.3%
3340000 74
10.5%
ValueCountFrequency (%)
3400000 46
6.5%
3390000 54
7.6%
3380000 37
 
5.2%
3370000 30
 
4.2%
3360000 33
 
4.7%
3350000 54
7.6%
3340000 74
10.5%
3330000 66
9.3%
3320000 97
13.7%
3310000 41
5.8%

관리번호
Text

UNIQUE 

Distinct708
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
2024-04-21T16:41:17.786297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters15576
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

Unique708 ?
Unique (%)100.0%

Sample

1st row3250000-114-2000-00002
2nd row3250000-114-1996-00414
3rd row3250000-114-1996-00416
4th row3250000-114-2011-00001
5th row3250000-114-2014-00001
ValueCountFrequency (%)
3250000-114-2000-00002 1
 
0.1%
3300000-114-2016-00001 1
 
0.1%
3320000-114-1996-00357 1
 
0.1%
3320000-114-1994-00125 1
 
0.1%
3320000-114-1994-00351 1
 
0.1%
3320000-114-1994-00129 1
 
0.1%
3320000-114-1994-00131 1
 
0.1%
3320000-114-1995-00353 1
 
0.1%
3320000-114-1996-00352 1
 
0.1%
3320000-114-1996-00155 1
 
0.1%
Other values (698) 698
98.6%
2024-04-21T16:41:18.628617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6095
39.1%
1 2301
 
14.8%
- 2124
 
13.6%
3 1546
 
9.9%
2 1026
 
6.6%
4 993
 
6.4%
9 606
 
3.9%
6 287
 
1.8%
5 229
 
1.5%
7 189
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13452
86.4%
Dash Punctuation 2124
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6095
45.3%
1 2301
 
17.1%
3 1546
 
11.5%
2 1026
 
7.6%
4 993
 
7.4%
9 606
 
4.5%
6 287
 
2.1%
5 229
 
1.7%
7 189
 
1.4%
8 180
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 2124
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15576
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6095
39.1%
1 2301
 
14.8%
- 2124
 
13.6%
3 1546
 
9.9%
2 1026
 
6.6%
4 993
 
6.4%
9 606
 
3.9%
6 287
 
1.8%
5 229
 
1.5%
7 189
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15576
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6095
39.1%
1 2301
 
14.8%
- 2124
 
13.6%
3 1546
 
9.9%
2 1026
 
6.6%
4 993
 
6.4%
9 606
 
3.9%
6 287
 
1.8%
5 229
 
1.5%
7 189
 
1.2%

인허가일자
Real number (ℝ)

Distinct632
Distinct (%)89.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20069540
Minimum19850909
Maximum20211025
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.3 KiB
2024-04-21T16:41:18.888270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19850909
5-th percentile19960617
Q119990401
median20071015
Q320140825
95-th percentile20200624
Maximum20211025
Range360116
Interquartile range (IQR)150423.75

Descriptive statistics

Standard deviation83791.138
Coefficient of variation (CV)0.0041750402
Kurtosis-1.2689377
Mean20069540
Median Absolute Deviation (MAD)79244.5
Skewness0.028542044
Sum1.4209235 × 1010
Variance7.0209549 × 109
MonotonicityNot monotonic
2024-04-21T16:41:19.151077image/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%
20000124 3
 
0.4%
19960625 3
 
0.4%
19960617 3
 
0.4%
19960923 3
 
0.4%
19990622 3
 
0.4%
19960722 3
 
0.4%
20160802 2
 
0.3%
Other values (622) 674
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 (%)
20211025 1
0.1%
20210824 1
0.1%
20210812 1
0.1%
20210802 1
0.1%
20210713 1
0.1%
20210609 1
0.1%
20210531 2
0.3%
20210507 1
0.1%
20210405 1
0.1%
20210329 1
0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing708
Missing (%)100.0%
Memory size6.3 KiB
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
1
362 
3
346 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 362
51.1%
3 346
48.9%

Length

2024-04-21T16:41:19.391214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:41:19.567524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 362
51.1%
3 346
48.9%

영업상태명
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
영업/정상
362 
폐업
346 

Length

Max length5
Median length5
Mean length3.5338983
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업/정상
2nd row영업/정상
3rd row영업/정상
4th row영업/정상
5th row영업/정상

Common Values

ValueCountFrequency (%)
영업/정상 362
51.1%
폐업 346
48.9%

Length

2024-04-21T16:41:19.757463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:41:19.941540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 362
51.1%
폐업 346
48.9%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
1
362 
2
346 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 362
51.1%
2 346
48.9%

Length

2024-04-21T16:41:20.123005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:41:20.298958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 362
51.1%
2 346
48.9%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
영업
362 
폐업
346 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 362
51.1%
폐업 346
48.9%

Length

2024-04-21T16:41:20.480198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:41:20.656569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 362
51.1%
폐업 346
48.9%

폐업일자
Real number (ℝ)

MISSING 

Distinct292
Distinct (%)84.4%
Missing362
Missing (%)51.1%
Infinite0
Infinite (%)0.0%
Mean20101593
Minimum19941010
Maximum20211129
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.3 KiB
2024-04-21T16:41:20.861796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19941010
5-th percentile19993363
Q120050936
median20100113
Q320170538
95-th percentile20201226
Maximum20211129
Range270119
Interquartile range (IQR)119602.25

Descriptive statistics

Standard deviation71870.553
Coefficient of variation (CV)0.0035753661
Kurtosis-1.2494183
Mean20101593
Median Absolute Deviation (MAD)60097.5
Skewness-0.0022125485
Sum6.9551511 × 109
Variance5.1653764 × 109
MonotonicityNot monotonic
2024-04-21T16:41:21.152915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20051128 37
 
5.2%
20100607 5
 
0.7%
20050614 4
 
0.6%
20140120 2
 
0.3%
20140102 2
 
0.3%
20210303 2
 
0.3%
20140725 2
 
0.3%
20120221 2
 
0.3%
20000609 2
 
0.3%
20100701 2
 
0.3%
Other values (282) 286
40.4%
(Missing) 362
51.1%
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 (%)
20211129 1
0.1%
20211108 1
0.1%
20211102 1
0.1%
20210907 1
0.1%
20210601 1
0.1%
20210527 1
0.1%
20210507 1
0.1%
20210504 1
0.1%
20210310 1
0.1%
20210303 2
0.3%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing708
Missing (%)100.0%
Memory size6.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing708
Missing (%)100.0%
Memory size6.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing708
Missing (%)100.0%
Memory size6.3 KiB

소재지전화
Text

MISSING 

Distinct561
Distinct (%)89.3%
Missing80
Missing (%)11.3%
Memory size5.7 KiB
2024-04-21T16:41:22.145583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.670382
Min length1

Characters and Unicode

Total characters6701
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 2488106
2nd row051 2507700
3rd row051 2454900
4th row051 2421577
5th row051 254 0035
ValueCountFrequency (%)
051 570
39.4%
727 8
 
0.6%
724 6
 
0.4%
343 5
 
0.3%
728 5
 
0.3%
703 4
 
0.3%
782 4
 
0.3%
8589 4
 
0.3%
202 4
 
0.3%
515 4
 
0.3%
Other values (707) 831
57.5%
2024-04-21T16:41:23.292886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1212
18.1%
5 1050
15.7%
1 1004
15.0%
829
12.4%
2 510
7.6%
3 417
 
6.2%
8 374
 
5.6%
7 365
 
5.4%
4 340
 
5.1%
6 332
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5872
87.6%
Space Separator 829
 
12.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1212
20.6%
5 1050
17.9%
1 1004
17.1%
2 510
8.7%
3 417
 
7.1%
8 374
 
6.4%
7 365
 
6.2%
4 340
 
5.8%
6 332
 
5.7%
9 268
 
4.6%
Space Separator
ValueCountFrequency (%)
829
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6701
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1212
18.1%
5 1050
15.7%
1 1004
15.0%
829
12.4%
2 510
7.6%
3 417
 
6.2%
8 374
 
5.6%
7 365
 
5.4%
4 340
 
5.1%
6 332
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6701
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1212
18.1%
5 1050
15.7%
1 1004
15.0%
829
12.4%
2 510
7.6%
3 417
 
6.2%
8 374
 
5.6%
7 365
 
5.4%
4 340
 
5.1%
6 332
 
5.0%

소재지면적
Text

MISSING 

Distinct549
Distinct (%)92.1%
Missing112
Missing (%)15.8%
Memory size5.7 KiB
2024-04-21T16:41:24.388039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length6
Mean length6.2332215
Min length3

Characters and Unicode

Total characters3715
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

Unique518 ?
Unique (%)86.9%

Sample

1st row565.36
2nd row2,405.07
3rd row473.37
4th row530.19
5th row963.00
ValueCountFrequency (%)
00 17
 
2.9%
396.00 3
 
0.5%
476.84 2
 
0.3%
400.00 2
 
0.3%
579.00 2
 
0.3%
663.50 2
 
0.3%
304.50 2
 
0.3%
755.00 2
 
0.3%
445.50 2
 
0.3%
941.49 2
 
0.3%
Other values (539) 560
94.0%
2024-04-21T16:41:25.699638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 625
16.8%
. 596
16.0%
3 313
8.4%
5 297
8.0%
4 277
7.5%
6 276
7.4%
7 257
6.9%
2 250
 
6.7%
9 249
 
6.7%
1 242
 
6.5%
Other values (2) 333
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3016
81.2%
Other Punctuation 699
 
18.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 625
20.7%
3 313
10.4%
5 297
9.8%
4 277
9.2%
6 276
9.2%
7 257
8.5%
2 250
 
8.3%
9 249
 
8.3%
1 242
 
8.0%
8 230
 
7.6%
Other Punctuation
ValueCountFrequency (%)
. 596
85.3%
, 103
 
14.7%

Most occurring scripts

ValueCountFrequency (%)
Common 3715
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 625
16.8%
. 596
16.0%
3 313
8.4%
5 297
8.0%
4 277
7.5%
6 276
7.4%
7 257
6.9%
2 250
 
6.7%
9 249
 
6.7%
1 242
 
6.5%
Other values (2) 333
9.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3715
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 625
16.8%
. 596
16.0%
3 313
8.4%
5 297
8.0%
4 277
7.5%
6 276
7.4%
7 257
6.9%
2 250
 
6.7%
9 249
 
6.7%
1 242
 
6.5%
Other values (2) 333
9.0%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct345
Distinct (%)49.6%
Missing13
Missing (%)1.8%
Infinite0
Infinite (%)0.0%
Mean611986.04
Minimum600016
Maximum619953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.3 KiB
2024-04-21T16:41:26.143080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600016
5-th percentile602808
Q1607831.5
median612829
Q3616816
95-th percentile618814.6
Maximum619953
Range19937
Interquartile range (IQR)8984.5

Descriptive statistics

Standard deviation5224.0503
Coefficient of variation (CV)0.0085362245
Kurtosis-0.88690006
Mean611986.04
Median Absolute Deviation (MAD)4002
Skewness-0.3794982
Sum4.253303 × 108
Variance27290701
MonotonicityNot monotonic
2024-04-21T16:41:26.408160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
618814 10
 
1.4%
616826 8
 
1.1%
616829 7
 
1.0%
616807 7
 
1.0%
618200 7
 
1.0%
617808 7
 
1.0%
604852 6
 
0.8%
604851 6
 
0.8%
606080 6
 
0.8%
616846 6
 
0.8%
Other values (335) 625
88.3%
(Missing) 13
 
1.8%
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
0.8%
619902 4
0.6%
619901 4
0.6%
Distinct518
Distinct (%)73.2%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
2024-04-21T16:41:27.408666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length45
Mean length23.694915
Min length14

Characters and Unicode

Total characters16776
Distinct characters248
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

Unique429 ?
Unique (%)60.6%

Sample

1st row부산광역시 중구 남포동*가 *번지 신천지백화점 *층
2nd row부산광역시 중구 남포동*가 *-*
3rd row부산광역시 중구 부평동*가 **번지
4th row부산광역시 중구 신창동*가 *-*번지 외 *필지
5th row부산광역시 중구 중앙동*가 **-*번지 롯데몰 마트시네마동 롯데마트광복점 지하*층
ValueCountFrequency (%)
부산광역시 708
21.7%
번지 559
17.2%
169
 
5.2%
북구 97
 
3.0%
사하구 74
 
2.3%
해운대구 66
 
2.0%
부산진구 63
 
1.9%
사상구 54
 
1.7%
금정구 54
 
1.7%
기장군 46
 
1.4%
Other values (297) 1369
42.0%
2024-04-21T16:41:28.680186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 3340
19.9%
2552
15.2%
829
 
4.9%
818
 
4.9%
780
 
4.6%
731
 
4.4%
725
 
4.3%
709
 
4.2%
707
 
4.2%
687
 
4.1%
Other values (238) 4898
29.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10181
60.7%
Other Punctuation 3382
 
20.2%
Space Separator 2552
 
15.2%
Dash Punctuation 571
 
3.4%
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 (%)
829
 
8.1%
818
 
8.0%
780
 
7.7%
731
 
7.2%
725
 
7.1%
709
 
7.0%
707
 
6.9%
687
 
6.7%
560
 
5.5%
144
 
1.4%
Other values (220) 3491
34.3%
Uppercase Letter
ValueCountFrequency (%)
B 18
46.2%
T 7
 
17.9%
A 3
 
7.7%
G 3
 
7.7%
L 2
 
5.1%
K 2
 
5.1%
H 2
 
5.1%
S 1
 
2.6%
C 1
 
2.6%
Other Punctuation
ValueCountFrequency (%)
* 3340
98.8%
, 38
 
1.1%
@ 4
 
0.1%
Space Separator
ValueCountFrequency (%)
2552
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 571
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 10181
60.7%
Common 6555
39.1%
Latin 40
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
829
 
8.1%
818
 
8.0%
780
 
7.7%
731
 
7.2%
725
 
7.1%
709
 
7.0%
707
 
6.9%
687
 
6.7%
560
 
5.5%
144
 
1.4%
Other values (220) 3491
34.3%
Latin
ValueCountFrequency (%)
B 18
45.0%
T 7
 
17.5%
A 3
 
7.5%
G 3
 
7.5%
L 2
 
5.0%
K 2
 
5.0%
H 2
 
5.0%
S 1
 
2.5%
C 1
 
2.5%
e 1
 
2.5%
Common
ValueCountFrequency (%)
* 3340
51.0%
2552
38.9%
- 571
 
8.7%
, 38
 
0.6%
) 23
 
0.4%
( 23
 
0.4%
@ 4
 
0.1%
~ 4
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10181
60.7%
ASCII 6595
39.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 3340
50.6%
2552
38.7%
- 571
 
8.7%
, 38
 
0.6%
) 23
 
0.3%
( 23
 
0.3%
B 18
 
0.3%
T 7
 
0.1%
@ 4
 
0.1%
~ 4
 
0.1%
Other values (8) 15
 
0.2%
Hangul
ValueCountFrequency (%)
829
 
8.1%
818
 
8.0%
780
 
7.7%
731
 
7.2%
725
 
7.1%
709
 
7.0%
707
 
6.9%
687
 
6.7%
560
 
5.5%
144
 
1.4%
Other values (220) 3491
34.3%

도로명전체주소
Text

MISSING 

Distinct467
Distinct (%)92.8%
Missing205
Missing (%)29.0%
Memory size5.7 KiB
2024-04-21T16:41:29.644098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length52
Mean length30.32008
Min length20

Characters and Unicode

Total characters15251
Distinct characters296
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

Unique435 ?
Unique (%)86.5%

Sample

1st row부산광역시 중구 자갈치로 **, *층 (남포동*가, 신천지백화점)
2nd row부산광역시 중구 구덕로 ** (남포동*가)
3rd row부산광역시 중구 부평*길 ** (부평동*가)
4th row부산광역시 중구 광복중앙로 ** (신창동*가, 외 *필지)
5th row부산광역시 중구 중앙대로 *, 지하*층 (중앙동*가, 롯데몰 마트시네마동 롯데마트광복점)
ValueCountFrequency (%)
510
 
17.1%
부산광역시 503
 
16.8%
122
 
4.1%
사하구 55
 
1.8%
해운대구 55
 
1.8%
48
 
1.6%
부산진구 47
 
1.6%
금정구 41
 
1.4%
지하*층 40
 
1.3%
사상구 40
 
1.3%
Other values (553) 1528
51.1%
2024-04-21T16:41:30.858728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2491
16.3%
* 2258
 
14.8%
634
 
4.2%
611
 
4.0%
608
 
4.0%
541
 
3.5%
535
 
3.5%
503
 
3.3%
499
 
3.3%
497
 
3.3%
Other values (286) 6074
39.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9063
59.4%
Other Punctuation 2630
 
17.2%
Space Separator 2491
 
16.3%
Close Punctuation 482
 
3.2%
Open Punctuation 482
 
3.2%
Uppercase Letter 41
 
0.3%
Dash Punctuation 39
 
0.3%
Math Symbol 21
 
0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
634
 
7.0%
611
 
6.7%
608
 
6.7%
541
 
6.0%
535
 
5.9%
503
 
5.6%
499
 
5.5%
497
 
5.5%
232
 
2.6%
209
 
2.3%
Other values (265) 4194
46.3%
Uppercase Letter
ValueCountFrequency (%)
B 20
48.8%
A 6
 
14.6%
C 4
 
9.8%
K 2
 
4.9%
G 2
 
4.9%
H 2
 
4.9%
L 1
 
2.4%
S 1
 
2.4%
N 1
 
2.4%
T 1
 
2.4%
Other Punctuation
ValueCountFrequency (%)
* 2258
85.9%
, 370
 
14.1%
@ 2
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
e 1
50.0%
b 1
50.0%
Space Separator
ValueCountFrequency (%)
2491
100.0%
Close Punctuation
ValueCountFrequency (%)
) 482
100.0%
Open Punctuation
ValueCountFrequency (%)
( 482
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 39
100.0%
Math Symbol
ValueCountFrequency (%)
~ 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9063
59.4%
Common 6145
40.3%
Latin 43
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
634
 
7.0%
611
 
6.7%
608
 
6.7%
541
 
6.0%
535
 
5.9%
503
 
5.6%
499
 
5.5%
497
 
5.5%
232
 
2.6%
209
 
2.3%
Other values (265) 4194
46.3%
Latin
ValueCountFrequency (%)
B 20
46.5%
A 6
 
14.0%
C 4
 
9.3%
K 2
 
4.7%
G 2
 
4.7%
H 2
 
4.7%
e 1
 
2.3%
b 1
 
2.3%
L 1
 
2.3%
S 1
 
2.3%
Other values (3) 3
 
7.0%
Common
ValueCountFrequency (%)
2491
40.5%
* 2258
36.7%
) 482
 
7.8%
( 482
 
7.8%
, 370
 
6.0%
- 39
 
0.6%
~ 21
 
0.3%
@ 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9063
59.4%
ASCII 6188
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2491
40.3%
* 2258
36.5%
) 482
 
7.8%
( 482
 
7.8%
, 370
 
6.0%
- 39
 
0.6%
~ 21
 
0.3%
B 20
 
0.3%
A 6
 
0.1%
C 4
 
0.1%
Other values (11) 15
 
0.2%
Hangul
ValueCountFrequency (%)
634
 
7.0%
611
 
6.7%
608
 
6.7%
541
 
6.0%
535
 
5.9%
503
 
5.6%
499
 
5.5%
497
 
5.5%
232
 
2.6%
209
 
2.3%
Other values (265) 4194
46.3%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct369
Distinct (%)75.3%
Missing218
Missing (%)30.8%
Infinite0
Infinite (%)0.0%
Mean47679.906
Minimum46004
Maximum49520
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.3 KiB
2024-04-21T16:41:31.099250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46004
5-th percentile46063.25
Q146759
median47711
Q348492.5
95-th percentile49386.75
Maximum49520
Range3516
Interquartile range (IQR)1733.5

Descriptive statistics

Standard deviation1063.3963
Coefficient of variation (CV)0.02230282
Kurtosis-1.1500886
Mean47679.906
Median Absolute Deviation (MAD)832
Skewness0.13270465
Sum23363154
Variance1130811.8
MonotonicityNot monotonic
2024-04-21T16:41:31.348640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
46726 7
 
1.0%
46759 5
 
0.7%
46230 5
 
0.7%
49494 4
 
0.6%
47369 4
 
0.6%
49108 4
 
0.6%
46762 4
 
0.6%
46084 3
 
0.4%
49053 3
 
0.4%
48515 3
 
0.4%
Other values (359) 448
63.3%
(Missing) 218
30.8%
ValueCountFrequency (%)
46004 2
0.3%
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%
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%
Distinct612
Distinct (%)86.4%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
2024-04-21T16:41:32.077875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length20
Mean length8.2810734
Min length2

Characters and Unicode

Total characters5863
Distinct characters323
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

Unique567 ?
Unique (%)80.1%

Sample

1st row자갈치 탑마트
2nd row(주)농협유통 하나로마트 자갈치점
3rd row(주)프로유통(빅세일마트)
4th row가람리테일
5th row롯데쇼핑(주)롯데마트광복점
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 (654) 801
87.5%
2024-04-21T16:41:33.023446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
471
 
8.0%
462
 
7.9%
) 281
 
4.8%
( 277
 
4.7%
274
 
4.7%
256
 
4.4%
207
 
3.5%
159
 
2.7%
89
 
1.5%
89
 
1.5%
Other values (313) 3298
56.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5003
85.3%
Close Punctuation 281
 
4.8%
Open Punctuation 277
 
4.7%
Space Separator 207
 
3.5%
Uppercase Letter 67
 
1.1%
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 (%)
471
 
9.4%
462
 
9.2%
274
 
5.5%
256
 
5.1%
159
 
3.2%
89
 
1.8%
89
 
1.8%
74
 
1.5%
73
 
1.5%
71
 
1.4%
Other values (278) 2985
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%
A 2
 
3.0%
E 2
 
3.0%
Other values (7) 10
14.9%
Decimal Number
ValueCountFrequency (%)
2 9
50.0%
1 3
 
16.7%
3 2
 
11.1%
4 1
 
5.6%
7 1
 
5.6%
5 1
 
5.6%
6 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 2
50.0%
& 1
25.0%
, 1
25.0%
Lowercase Letter
ValueCountFrequency (%)
o 1
33.3%
n 1
33.3%
e 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 281
100.0%
Open Punctuation
ValueCountFrequency (%)
( 277
100.0%
Space Separator
ValueCountFrequency (%)
207
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5003
85.3%
Common 790
 
13.5%
Latin 70
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
471
 
9.4%
462
 
9.2%
274
 
5.5%
256
 
5.1%
159
 
3.2%
89
 
1.8%
89
 
1.8%
74
 
1.5%
73
 
1.5%
71
 
1.4%
Other values (278) 2985
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%
A 2
 
2.9%
E 2
 
2.9%
Other values (10) 13
18.6%
Common
ValueCountFrequency (%)
) 281
35.6%
( 277
35.1%
207
26.2%
2 9
 
1.1%
1 3
 
0.4%
- 2
 
0.3%
3 2
 
0.3%
. 2
 
0.3%
4 1
 
0.1%
& 1
 
0.1%
Other values (5) 5
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5003
85.3%
ASCII 860
 
14.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
471
 
9.4%
462
 
9.2%
274
 
5.5%
256
 
5.1%
159
 
3.2%
89
 
1.8%
89
 
1.8%
74
 
1.5%
73
 
1.5%
71
 
1.4%
Other values (278) 2985
59.7%
ASCII
ValueCountFrequency (%)
) 281
32.7%
( 277
32.2%
207
24.1%
S 15
 
1.7%
G 10
 
1.2%
2 9
 
1.0%
C 8
 
0.9%
M 5
 
0.6%
K 5
 
0.6%
J 4
 
0.5%
Other values (25) 39
 
4.5%

최종수정시점
Real number (ℝ)

Distinct627
Distinct (%)88.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.013903 × 1013
Minimum1.9990607 × 1013
Maximum2.0211129 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.3 KiB
2024-04-21T16:41:33.263891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990607 × 1013
5-th percentile2.0010728 × 1013
Q12.0090201 × 1013
median2.0161016 × 1013
Q32.0200405 × 1013
95-th percentile2.0210616 × 1013
Maximum2.0211129 × 1013
Range2.2052215 × 1011
Interquartile range (IQR)1.1020378 × 1011

Descriptive statistics

Standard deviation7.010324 × 1010
Coefficient of variation (CV)0.0034809641
Kurtosis-0.92372433
Mean2.013903 × 1013
Median Absolute Deviation (MAD)3.9995525 × 1010
Skewness-0.76808383
Sum1.4258433 × 1016
Variance4.9144642 × 1021
MonotonicityNot monotonic
2024-04-21T16:41:33.516115image/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
 
0.8%
20020731000000 6
 
0.8%
20040618000000 5
 
0.7%
20020608000000 3
 
0.4%
20020802000000 3
 
0.4%
Other values (617) 624
88.1%
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 (%)
20211129145037 1
0.1%
20211129143646 1
0.1%
20211126135105 1
0.1%
20211126135036 1
0.1%
20211126134913 1
0.1%
20211124162501 1
0.1%
20211124162419 1
0.1%
20211116133256 1
0.1%
20211112112845 1
0.1%
20211111180056 1
0.1%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
I
460 
U
248 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 460
65.0%
U 248
35.0%

Length

2024-04-21T16:41:33.742750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:41:33.918339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 460
65.0%
u 248
35.0%
Distinct212
Distinct (%)29.9%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
Minimum2018-08-31 23:59:59
Maximum2021-12-01 02:40:00
2024-04-21T16:41:34.114587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T16:41:34.366390image/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 size5.7 KiB
기타식품판매업
704 
식품조사처리업
 
3
<NA>
 
1

Length

Max length7
Median length7
Mean length6.9957627
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
기타식품판매업 704
99.4%
식품조사처리업 3
 
0.4%
<NA> 1
 
0.1%

Length

2024-04-21T16:41:34.601967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:41:34.788975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타식품판매업 704
99.4%
식품조사처리업 3
 
0.4%
na 1
 
0.1%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct550
Distinct (%)80.8%
Missing27
Missing (%)3.8%
Infinite0
Infinite (%)0.0%
Mean387550.89
Minimum366779.27
Maximum409357.26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.3 KiB
2024-04-21T16:41:34.996675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum366779.27
5-th percentile378638.3
Q1382703.07
median387866.61
Q3391649.27
95-th percentile399083.98
Maximum409357.26
Range42577.984
Interquartile range (IQR)8946.199

Descriptive statistics

Standard deviation6856.8323
Coefficient of variation (CV)0.017692727
Kurtosis0.39815611
Mean387550.89
Median Absolute Deviation (MAD)4512.0549
Skewness0.13576563
Sum2.6392216 × 108
Variance47016149
MonotonicityNot monotonic
2024-04-21T16:41:35.243325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
390057.531834683 3
 
0.4%
380214.174893599 3
 
0.4%
387274.123524645 3
 
0.4%
389016.879191556 3
 
0.4%
390241.469793416 3
 
0.4%
387887.847333871 3
 
0.4%
385770.215097102 3
 
0.4%
390038.68419681 3
 
0.4%
392378.665367078 3
 
0.4%
381186.646505489 3
 
0.4%
Other values (540) 651
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 

Distinct550
Distinct (%)80.8%
Missing27
Missing (%)3.8%
Infinite0
Infinite (%)0.0%
Mean187582.42
Minimum174289.98
Maximum206150.93
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.3 KiB
2024-04-21T16:41:35.479183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum174289.98
5-th percentile177653.44
Q1182894.94
median187669.4
Q3191812.6
95-th percentile197865.68
Maximum206150.93
Range31860.948
Interquartile range (IQR)8917.6616

Descriptive statistics

Standard deviation6557.2684
Coefficient of variation (CV)0.034956733
Kurtosis-0.010216512
Mean187582.42
Median Absolute Deviation (MAD)4235.2399
Skewness0.30739298
Sum1.2774363 × 108
Variance42997769
MonotonicityNot monotonic
2024-04-21T16:41:35.718423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
196950.450593302 3
 
0.4%
182729.264942974 3
 
0.4%
184575.633639399 3
 
0.4%
176951.726317049 3
 
0.4%
197865.684207345 3
 
0.4%
187966.542955171 3
 
0.4%
192276.385535768 3
 
0.4%
191142.980733675 3
 
0.4%
184491.727482399 3
 
0.4%
190340.141159379 3
 
0.4%
Other values (540) 651
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%
205423.702303922 1
0.1%
205344.463400676 1
0.1%
205187.183814795 2
0.3%

위생업태명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
기타식품판매업
704 
식품조사처리업
 
3
<NA>
 
1

Length

Max length7
Median length7
Mean length6.9957627
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
기타식품판매업 704
99.4%
식품조사처리업 3
 
0.4%
<NA> 1
 
0.1%

Length

2024-04-21T16:41:35.961500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:41:36.154485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타식품판매업 704
99.4%
식품조사처리업 3
 
0.4%
na 1
 
0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
<NA>
611 
0
96 
1
 
1

Length

Max length4
Median length4
Mean length3.5889831
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 611
86.3%
0 96
 
13.6%
1 1
 
0.1%

Length

2024-04-21T16:41:36.349528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:41:36.536627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 611
86.3%
0 96
 
13.6%
1 1
 
0.1%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
<NA>
612 
0
96 

Length

Max length4
Median length4
Mean length3.5932203
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 612
86.4%
0 96
 
13.6%

Length

2024-04-21T16:41:36.731728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:41:36.916865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 612
86.4%
0 96
 
13.6%

영업장주변구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
<NA>
509 
기타
188 
주택가주변
 
7
아파트지역
 
3
학교정화(절대)
 
1

Length

Max length8
Median length4
Mean length3.4887006
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 509
71.9%
기타 188
 
26.6%
주택가주변 7
 
1.0%
아파트지역 3
 
0.4%
학교정화(절대) 1
 
0.1%

Length

2024-04-21T16:41:37.106343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:41:37.302311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 509
71.9%
기타 188
 
26.6%
주택가주변 7
 
1.0%
아파트지역 3
 
0.4%
학교정화(절대 1
 
0.1%

등급구분명
Categorical

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
<NA>
509 
기타
189 
자율
 
10

Length

Max length4
Median length4
Mean length3.4378531
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 509
71.9%
기타 189
 
26.7%
자율 10
 
1.4%

Length

2024-04-21T16:41:37.522086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:41:37.720596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 509
71.9%
기타 189
 
26.7%
자율 10
 
1.4%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
<NA>
608 
상수도전용
100 

Length

Max length5
Median length4
Mean length4.1412429
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 608
85.9%
상수도전용 100
 
14.1%

Length

2024-04-21T16:41:38.134240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:41:38.311741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 608
85.9%
상수도전용 100
 
14.1%

총종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
<NA>
689 
0
 
19

Length

Max length4
Median length4
Mean length3.9194915
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> 689
97.3%
0 19
 
2.7%

Length

2024-04-21T16:41:38.504788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:41:38.690604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 689
97.3%
0 19
 
2.7%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
0
430 
<NA>
278 

Length

Max length4
Median length1
Mean length2.1779661
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 430
60.7%
<NA> 278
39.3%

Length

2024-04-21T16:41:38.898065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:41:39.219788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 430
60.7%
na 278
39.3%
Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
0
427 
<NA>
278 
1
 
2
2
 
1

Length

Max length4
Median length1
Mean length2.1779661
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 427
60.3%
<NA> 278
39.3%
1 2
 
0.3%
2 1
 
0.1%

Length

2024-04-21T16:41:39.566493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:41:39.897698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 427
60.3%
na 278
39.3%
1 2
 
0.3%
2 1
 
0.1%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
0
425 
<NA>
278 
6
 
2
75
 
1
5
 
1

Length

Max length4
Median length1
Mean length2.180791
Min length1

Unique

Unique3 ?
Unique (%)0.4%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row75

Common Values

ValueCountFrequency (%)
0 425
60.0%
<NA> 278
39.3%
6 2
 
0.3%
75 1
 
0.1%
5 1
 
0.1%
15 1
 
0.1%

Length

2024-04-21T16:41:40.264819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:41:40.605942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 425
60.0%
na 278
39.3%
6 2
 
0.3%
75 1
 
0.1%
5 1
 
0.1%
15 1
 
0.1%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
0
430 
<NA>
278 

Length

Max length4
Median length1
Mean length2.1779661
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 430
60.7%
<NA> 278
39.3%

Length

2024-04-21T16:41:40.992064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:41:41.320330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 430
60.7%
na 278
39.3%
Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
<NA>
528 
자가
124 
임대
56 

Length

Max length4
Median length4
Mean length3.4915254
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 528
74.6%
자가 124
 
17.5%
임대 56
 
7.9%

Length

2024-04-21T16:41:41.688343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:41:42.036027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 528
74.6%
자가 124
 
17.5%
임대 56
 
7.9%

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
<NA>
664 
0
 
44

Length

Max length4
Median length4
Mean length3.8135593
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> 664
93.8%
0 44
 
6.2%

Length

2024-04-21T16:41:42.403710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:41:42.733020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 664
93.8%
0 44
 
6.2%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
<NA>
665 
0
 
43

Length

Max length4
Median length4
Mean length3.8177966
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> 665
93.9%
0 43
 
6.1%

Length

2024-04-21T16:41:43.082548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:41:43.411132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 665
93.9%
0 43
 
6.1%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size836.0 B
False
708 
ValueCountFrequency (%)
False 708
100.0%
2024-04-21T16:41:43.679942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

ZEROS 

Distinct131
Distinct (%)18.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean84.532486
Minimum0
Maximum9790.33
Zeros572
Zeros (%)80.8%
Negative0
Negative (%)0.0%
Memory size6.3 KiB
2024-04-21T16:41:44.020180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile562.8575
Maximum9790.33
Range9790.33
Interquartile range (IQR)0

Descriptive statistics

Standard deviation465.86693
Coefficient of variation (CV)5.5110993
Kurtosis275.34499
Mean84.532486
Median Absolute Deviation (MAD)0
Skewness14.447255
Sum59849
Variance217031.99
MonotonicityNot monotonic
2024-04-21T16:41:44.459241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 572
80.8%
6.46 3
 
0.4%
16.8 2
 
0.3%
15.0 2
 
0.3%
682.72 2
 
0.3%
495.0 2
 
0.3%
7.8 1
 
0.1%
3799.2 1
 
0.1%
6.9 1
 
0.1%
311.72 1
 
0.1%
Other values (121) 121
 
17.1%
ValueCountFrequency (%)
0.0 572
80.8%
2.81 1
 
0.1%
3.3 1
 
0.1%
3.36 1
 
0.1%
4.0 1
 
0.1%
4.35 1
 
0.1%
4.4 1
 
0.1%
4.94 1
 
0.1%
5.5 1
 
0.1%
5.6 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%
2015.23 1
0.1%
1720.62 1
0.1%
1425.2 1
0.1%
1096.0 1
0.1%
996.8 1
0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing708
Missing (%)100.0%
Memory size6.3 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing708
Missing (%)100.0%
Memory size6.3 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing708
Missing (%)100.0%
Memory size6.3 KiB

Unnamed: 47
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing708
Missing (%)100.0%
Memory size6.3 KiB

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지Unnamed: 47
01식품판매업(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>
12식품판매업(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)농협유통 하나로마트 자갈치점20211110152957U2021-11-12 02:40:00.0기타식품판매업384820.119269179460.841059기타식품판매업00기타기타<NA><NA>0000<NA><NA><NA>N2405.07<NA><NA><NA><NA>
23식품판매업(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>
34식품판매업(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>
45식품판매업(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>
56식품판매업(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>
67식품판매업(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>
78식품판매업(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>
89식품판매업(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>N10.0<NA><NA><NA><NA>
910식품판매업(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>
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지Unnamed: 47
698699식품판매업(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>
699700식품판매업(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>
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