Overview

Dataset statistics

Number of variables48
Number of observations734
Missing cells6997
Missing cells (%)19.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory294.0 KiB
Average record size in memory410.2 B

Variable types

Numeric7
Categorical22
Text6
DateTime4
Unsupported8
Boolean1

Dataset

Description2023-08-01
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 (96.6%)Imbalance
위생업태명 is highly imbalanced (96.6%)Imbalance
영업장주변구분명 is highly imbalanced (59.3%)Imbalance
공장사무직직원수 is highly imbalanced (50.9%)Imbalance
공장판매직직원수 is highly imbalanced (60.9%)Imbalance
인허가취소일자 has 734 (100.0%) missing valuesMissing
폐업일자 has 361 (49.2%) missing valuesMissing
휴업시작일자 has 734 (100.0%) missing valuesMissing
휴업종료일자 has 734 (100.0%) missing valuesMissing
재개업일자 has 734 (100.0%) missing valuesMissing
소재지전화 has 144 (19.6%) missing valuesMissing
소재지면적 has 112 (15.3%) missing valuesMissing
소재지우편번호 has 15 (2.0%) missing valuesMissing
도로명전체주소 has 205 (27.9%) missing valuesMissing
도로명우편번호 has 218 (29.7%) missing valuesMissing
좌표정보(x) has 35 (4.8%) missing valuesMissing
좌표정보(y) has 35 (4.8%) missing valuesMissing
전통업소지정번호 has 734 (100.0%) missing valuesMissing
전통업소주된음식 has 734 (100.0%) missing valuesMissing
홈페이지 has 734 (100.0%) missing valuesMissing
Unnamed: 47 has 734 (100.0%) missing valuesMissing
번호 has unique valuesUnique
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 47 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 16 (2.2%) zerosZeros
시설총규모 has 585 (79.7%) zerosZeros

Reproduction

Analysis started2024-04-21 07:23:43.436867
Analysis finished2024-04-21 07:23:45.040363
Duration1.6 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct734
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean367.5
Minimum1
Maximum734
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.6 KiB
2024-04-21T16:23:45.223838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile37.65
Q1184.25
median367.5
Q3550.75
95-th percentile697.35
Maximum734
Range733
Interquartile range (IQR)366.5

Descriptive statistics

Standard deviation212.03184
Coefficient of variation (CV)0.57695738
Kurtosis-1.2
Mean367.5
Median Absolute Deviation (MAD)183.5
Skewness0
Sum269745
Variance44957.5
MonotonicityStrictly increasing
2024-04-21T16:23:45.684227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
484 1
 
0.1%
486 1
 
0.1%
487 1
 
0.1%
488 1
 
0.1%
489 1
 
0.1%
490 1
 
0.1%
491 1
 
0.1%
492 1
 
0.1%
493 1
 
0.1%
Other values (724) 724
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 (%)
734 1
0.1%
733 1
0.1%
732 1
0.1%
731 1
0.1%
730 1
0.1%
729 1
0.1%
728 1
0.1%
727 1
0.1%
726 1
0.1%
725 1
0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
식품판매업(기타)
734 

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) 734
100.0%

Length

2024-04-21T16:23:46.110052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:23:46.436952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품판매업(기타 734
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
07_22_13_P
734 

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 734
100.0%

Length

2024-04-21T16:23:46.776665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:23:47.092980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_13_p 734
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3333733
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.6 KiB
2024-04-21T16:23:47.395241image/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 deviation38334.559
Coefficient of variation (CV)0.011498989
Kurtosis-0.7225968
Mean3333733
Median Absolute Deviation (MAD)30000
Skewness0.0036101977
Sum2.44696 × 109
Variance1.4695384 × 109
MonotonicityNot monotonic
2024-04-21T16:23:47.789264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3320000 99
13.5%
3340000 78
10.6%
3330000 68
9.3%
3290000 66
9.0%
3350000 56
7.6%
3390000 55
7.5%
3400000 47
 
6.4%
3300000 45
 
6.1%
3310000 44
 
6.0%
3380000 39
 
5.3%
Other values (6) 137
18.7%
ValueCountFrequency (%)
3250000 16
 
2.2%
3260000 12
 
1.6%
3270000 11
 
1.5%
3280000 29
 
4.0%
3290000 66
9.0%
3300000 45
6.1%
3310000 44
6.0%
3320000 99
13.5%
3330000 68
9.3%
3340000 78
10.6%
ValueCountFrequency (%)
3400000 47
6.4%
3390000 55
7.5%
3380000 39
 
5.3%
3370000 32
 
4.4%
3360000 37
 
5.0%
3350000 56
7.6%
3340000 78
10.6%
3330000 68
9.3%
3320000 99
13.5%
3310000 44
6.0%

관리번호
Text

UNIQUE 

Distinct734
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
2024-04-21T16:23:48.541928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters16148
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

Unique734 ?
Unique (%)100.0%

Sample

1st row3250000-114-2000-00002
2nd row3250000-114-1996-00414
3rd row3250000-114-1996-00416
4th row3250000-114-2014-00001
5th row3250000-114-2016-00001
ValueCountFrequency (%)
3250000-114-2000-00002 1
 
0.1%
3320000-114-1995-00353 1
 
0.1%
3320000-114-1996-00155 1
 
0.1%
3320000-114-1996-00354 1
 
0.1%
3320000-114-1996-00357 1
 
0.1%
3320000-114-1996-00356 1
 
0.1%
3320000-114-1996-00358 1
 
0.1%
3320000-114-1996-00359 1
 
0.1%
3320000-114-1996-00156 1
 
0.1%
3320000-114-1996-00158 1
 
0.1%
Other values (724) 724
98.6%
2024-04-21T16:23:49.667860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6330
39.2%
1 2372
 
14.7%
- 2202
 
13.6%
3 1609
 
10.0%
2 1103
 
6.8%
4 1025
 
6.3%
9 611
 
3.8%
6 292
 
1.8%
5 231
 
1.4%
7 191
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13946
86.4%
Dash Punctuation 2202
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6330
45.4%
1 2372
 
17.0%
3 1609
 
11.5%
2 1103
 
7.9%
4 1025
 
7.3%
9 611
 
4.4%
6 292
 
2.1%
5 231
 
1.7%
7 191
 
1.4%
8 182
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 2202
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 16148
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6330
39.2%
1 2372
 
14.7%
- 2202
 
13.6%
3 1609
 
10.0%
2 1103
 
6.8%
4 1025
 
6.3%
9 611
 
3.8%
6 292
 
1.8%
5 231
 
1.4%
7 191
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16148
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6330
39.2%
1 2372
 
14.7%
- 2202
 
13.6%
3 1609
 
10.0%
2 1103
 
6.8%
4 1025
 
6.3%
9 611
 
3.8%
6 292
 
1.8%
5 231
 
1.4%
7 191
 
1.2%
Distinct657
Distinct (%)89.5%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
Minimum1985-09-09 00:00:00
Maximum2023-07-10 00:00:00
2024-04-21T16:23:50.080797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T16:23:50.511460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing734
Missing (%)100.0%
Memory size6.6 KiB
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
3
373 
1
361 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 373
50.8%
1 361
49.2%

Length

2024-04-21T16:23:50.931154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:23:51.260965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 373
50.8%
1 361
49.2%

영업상태명
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
폐업
373 
영업/정상
361 

Length

Max length5
Median length2
Mean length3.4754768
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 373
50.8%
영업/정상 361
49.2%

Length

2024-04-21T16:23:51.625463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:23:51.970540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 373
50.8%
영업/정상 361
49.2%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
2
373 
1
361 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 373
50.8%
1 361
49.2%

Length

2024-04-21T16:23:52.317617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:23:52.640332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 373
50.8%
1 361
49.2%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
폐업
373 
영업
361 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 373
50.8%
영업 361
49.2%

Length

2024-04-21T16:23:52.986910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:23:53.306544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 373
50.8%
영업 361
49.2%

폐업일자
Date

MISSING 

Distinct319
Distinct (%)85.5%
Missing361
Missing (%)49.2%
Memory size5.9 KiB
Minimum1994-10-10 00:00:00
Maximum2023-07-12 00:00:00
2024-04-21T16:23:53.661626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T16:23:54.077829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing734
Missing (%)100.0%
Memory size6.6 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing734
Missing (%)100.0%
Memory size6.6 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing734
Missing (%)100.0%
Memory size6.6 KiB

소재지전화
Text

MISSING 

Distinct573
Distinct (%)97.1%
Missing144
Missing (%)19.6%
Memory size5.9 KiB
2024-04-21T16:23:55.053972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.398305
Min length7

Characters and Unicode

Total characters6725
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

Unique556 ?
Unique (%)94.2%

Sample

1st row051 2488106
2nd row051 2507700
3rd row051 2454900
4th row051 254 0035
5th row051 469 5770
ValueCountFrequency (%)
051 533
37.2%
727 8
 
0.6%
343 6
 
0.4%
724 6
 
0.4%
728 5
 
0.3%
703 4
 
0.3%
782 4
 
0.3%
759 4
 
0.3%
897 4
 
0.3%
755 4
 
0.3%
Other values (724) 856
59.7%
2024-04-21T16:23:56.386240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1190
17.7%
5 1028
15.3%
1 976
14.5%
853
12.7%
2 531
7.9%
3 429
 
6.4%
8 374
 
5.6%
7 372
 
5.5%
4 350
 
5.2%
6 345
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5872
87.3%
Space Separator 853
 
12.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1190
20.3%
5 1028
17.5%
1 976
16.6%
2 531
9.0%
3 429
 
7.3%
8 374
 
6.4%
7 372
 
6.3%
4 350
 
6.0%
6 345
 
5.9%
9 277
 
4.7%
Space Separator
ValueCountFrequency (%)
853
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6725
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1190
17.7%
5 1028
15.3%
1 976
14.5%
853
12.7%
2 531
7.9%
3 429
 
6.4%
8 374
 
5.6%
7 372
 
5.5%
4 350
 
5.2%
6 345
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6725
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1190
17.7%
5 1028
15.3%
1 976
14.5%
853
12.7%
2 531
7.9%
3 429
 
6.4%
8 374
 
5.6%
7 372
 
5.5%
4 350
 
5.2%
6 345
 
5.1%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct575
Distinct (%)92.4%
Missing112
Missing (%)15.3%
Infinite0
Infinite (%)0.0%
Mean1045.1528
Minimum0
Maximum20008
Zeros16
Zeros (%)2.2%
Negative0
Negative (%)0.0%
Memory size6.6 KiB
2024-04-21T16:23:56.638895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile38.318
Q1396.1875
median572.19
Q3873.49
95-th percentile3101.05
Maximum20008
Range20008
Interquartile range (IQR)477.3025

Descriptive statistics

Standard deviation1999.6667
Coefficient of variation (CV)1.9132768
Kurtosis38.517815
Mean1045.1528
Median Absolute Deviation (MAD)206.18
Skewness5.7816312
Sum650085.05
Variance3998666.8
MonotonicityNot monotonic
2024-04-21T16:23:57.019504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 16
 
2.2%
600.0 3
 
0.4%
396.0 3
 
0.4%
660.0 2
 
0.3%
446.0 2
 
0.3%
495.57 2
 
0.3%
599.76 2
 
0.3%
407.87 2
 
0.3%
495.0 2
 
0.3%
663.5 2
 
0.3%
Other values (565) 586
79.8%
(Missing) 112
 
15.3%
ValueCountFrequency (%)
0.0 16
2.2%
2.0 1
 
0.1%
9.0 1
 
0.1%
12.6 1
 
0.1%
16.64 1
 
0.1%
18.06 1
 
0.1%
21.76 1
 
0.1%
22.08 1
 
0.1%
22.32 1
 
0.1%
22.62 1
 
0.1%
ValueCountFrequency (%)
20008.0 1
0.1%
17325.0 1
0.1%
16529.0 1
0.1%
14644.91 1
0.1%
13785.0 1
0.1%
13626.9 1
0.1%
12317.5 1
0.1%
11262.0 1
0.1%
11001.0 1
0.1%
10778.98 1
0.1%

소재지우편번호
Text

MISSING 

Distinct350
Distinct (%)48.7%
Missing15
Missing (%)2.0%
Memory size5.9 KiB
2024-04-21T16:23:58.393065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters5033
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

Unique168 ?
Unique (%)23.4%

Sample

1st row600-046
2nd row600-046
3rd row600-806
4th row600-017
5th row600-044
ValueCountFrequency (%)
618-814 10
 
1.4%
616-826 8
 
1.1%
618-200 8
 
1.1%
616-807 7
 
1.0%
608-832 7
 
1.0%
616-829 7
 
1.0%
617-808 7
 
1.0%
612-824 7
 
1.0%
606-080 6
 
0.8%
619-903 6
 
0.8%
Other values (340) 646
89.8%
2024-04-21T16:23:59.922227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 939
18.7%
8 740
14.7%
- 719
14.3%
1 716
14.2%
0 639
12.7%
2 305
 
6.1%
4 282
 
5.6%
3 234
 
4.6%
7 181
 
3.6%
9 177
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4314
85.7%
Dash Punctuation 719
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 939
21.8%
8 740
17.2%
1 716
16.6%
0 639
14.8%
2 305
 
7.1%
4 282
 
6.5%
3 234
 
5.4%
7 181
 
4.2%
9 177
 
4.1%
5 101
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 719
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5033
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 939
18.7%
8 740
14.7%
- 719
14.3%
1 716
14.2%
0 639
12.7%
2 305
 
6.1%
4 282
 
5.6%
3 234
 
4.6%
7 181
 
3.6%
9 177
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5033
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 939
18.7%
8 740
14.7%
- 719
14.3%
1 716
14.2%
0 639
12.7%
2 305
 
6.1%
4 282
 
5.6%
3 234
 
4.6%
7 181
 
3.6%
9 177
 
3.5%
Distinct660
Distinct (%)89.9%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
2024-04-21T16:24:01.017382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length43.5
Mean length22.132153
Min length14

Characters and Unicode

Total characters16245
Distinct characters260
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

Unique592 ?
Unique (%)80.7%

Sample

1st row부산광역시 중구 남포동6가 3 신천지백화점 1층
2nd row부산광역시 중구 남포동6가 1-0
3rd row부산광역시 중구 부평동2가 16
4th row부산광역시 중구 중앙동7가 20-1 롯데몰 마트시네마동 롯데마트광복점 지하2층
5th row부산광역시 중구 남포동4가 44-3
ValueCountFrequency (%)
부산광역시 734
 
21.7%
북구 99
 
2.9%
사하구 78
 
2.3%
해운대구 68
 
2.0%
부산진구 66
 
2.0%
금정구 56
 
1.7%
사상구 55
 
1.6%
기장군 47
 
1.4%
동래구 45
 
1.3%
남구 44
 
1.3%
Other values (961) 2086
61.8%
2024-04-21T16:24:02.840582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2645
 
16.3%
859
 
5.3%
850
 
5.2%
1 827
 
5.1%
808
 
5.0%
758
 
4.7%
753
 
4.6%
736
 
4.5%
732
 
4.5%
- 593
 
3.7%
Other values (250) 6684
41.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9419
58.0%
Decimal Number 3453
 
21.3%
Space Separator 2645
 
16.3%
Dash Punctuation 593
 
3.7%
Other Punctuation 42
 
0.3%
Uppercase Letter 42
 
0.3%
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 (%)
859
 
9.1%
850
 
9.0%
808
 
8.6%
758
 
8.0%
753
 
8.0%
736
 
7.8%
732
 
7.8%
150
 
1.6%
138
 
1.5%
131
 
1.4%
Other values (222) 3504
37.2%
Decimal Number
ValueCountFrequency (%)
1 827
24.0%
2 420
12.2%
3 384
11.1%
5 316
 
9.2%
4 296
 
8.6%
0 289
 
8.4%
8 253
 
7.3%
7 234
 
6.8%
6 231
 
6.7%
9 203
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
B 18
42.9%
T 7
 
16.7%
G 4
 
9.5%
A 3
 
7.1%
L 2
 
4.8%
S 2
 
4.8%
K 2
 
4.8%
H 2
 
4.8%
W 1
 
2.4%
C 1
 
2.4%
Other Punctuation
ValueCountFrequency (%)
, 38
90.5%
@ 4
 
9.5%
Space Separator
ValueCountFrequency (%)
2645
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 593
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 9419
58.0%
Common 6783
41.8%
Latin 43
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
859
 
9.1%
850
 
9.0%
808
 
8.6%
758
 
8.0%
753
 
8.0%
736
 
7.8%
732
 
7.8%
150
 
1.6%
138
 
1.5%
131
 
1.4%
Other values (222) 3504
37.2%
Common
ValueCountFrequency (%)
2645
39.0%
1 827
 
12.2%
- 593
 
8.7%
2 420
 
6.2%
3 384
 
5.7%
5 316
 
4.7%
4 296
 
4.4%
0 289
 
4.3%
8 253
 
3.7%
7 234
 
3.4%
Other values (7) 526
 
7.8%
Latin
ValueCountFrequency (%)
B 18
41.9%
T 7
 
16.3%
G 4
 
9.3%
A 3
 
7.0%
L 2
 
4.7%
S 2
 
4.7%
K 2
 
4.7%
H 2
 
4.7%
e 1
 
2.3%
W 1
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9419
58.0%
ASCII 6826
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2645
38.7%
1 827
 
12.1%
- 593
 
8.7%
2 420
 
6.2%
3 384
 
5.6%
5 316
 
4.6%
4 296
 
4.3%
0 289
 
4.2%
8 253
 
3.7%
7 234
 
3.4%
Other values (18) 569
 
8.3%
Hangul
ValueCountFrequency (%)
859
 
9.1%
850
 
9.0%
808
 
8.6%
758
 
8.0%
753
 
8.0%
736
 
7.8%
732
 
7.8%
150
 
1.6%
138
 
1.5%
131
 
1.4%
Other values (222) 3504
37.2%

도로명전체주소
Text

MISSING 

Distinct509
Distinct (%)96.2%
Missing205
Missing (%)27.9%
Memory size5.9 KiB
2024-04-21T16:24:04.240916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length51
Mean length30.570888
Min length20

Characters and Unicode

Total characters16172
Distinct characters307
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

Unique489 ?
Unique (%)92.4%

Sample

1st row부산광역시 중구 자갈치로 33, 1층 (남포동6가, 신천지백화점)
2nd row부산광역시 중구 구덕로 73 (남포동6가)
3rd row부산광역시 중구 부평1길 48 (부평동2가)
4th row부산광역시 중구 중앙대로 2, 지하1층 (중앙동7가, 롯데몰 마트시네마동 롯데마트광복점)
5th row부산광역시 중구 자갈치해안로 60, 1~3층 (남포동4가)
ValueCountFrequency (%)
부산광역시 529
 
16.7%
1층 116
 
3.7%
사하구 59
 
1.9%
해운대구 57
 
1.8%
부산진구 50
 
1.6%
금정구 43
 
1.4%
사상구 41
 
1.3%
기장군 37
 
1.2%
강서구 37
 
1.2%
지하1층 36
 
1.1%
Other values (941) 2157
68.2%
2024-04-21T16:24:05.961677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2638
 
16.3%
1 773
 
4.8%
666
 
4.1%
644
 
4.0%
640
 
4.0%
570
 
3.5%
563
 
3.5%
530
 
3.3%
524
 
3.2%
521
 
3.2%
Other values (297) 8103
50.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9586
59.3%
Space Separator 2638
 
16.3%
Decimal Number 2416
 
14.9%
Open Punctuation 507
 
3.1%
Close Punctuation 507
 
3.1%
Other Punctuation 406
 
2.5%
Uppercase Letter 43
 
0.3%
Dash Punctuation 42
 
0.3%
Math Symbol 25
 
0.2%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
666
 
6.9%
644
 
6.7%
640
 
6.7%
570
 
5.9%
563
 
5.9%
530
 
5.5%
524
 
5.5%
521
 
5.4%
240
 
2.5%
229
 
2.4%
Other values (266) 4459
46.5%
Uppercase Letter
ValueCountFrequency (%)
B 19
44.2%
A 6
 
14.0%
C 4
 
9.3%
G 3
 
7.0%
S 2
 
4.7%
K 2
 
4.7%
H 2
 
4.7%
L 1
 
2.3%
N 1
 
2.3%
W 1
 
2.3%
Other values (2) 2
 
4.7%
Decimal Number
ValueCountFrequency (%)
1 773
32.0%
2 314
13.0%
3 242
 
10.0%
0 226
 
9.4%
4 212
 
8.8%
5 164
 
6.8%
7 137
 
5.7%
6 126
 
5.2%
9 115
 
4.8%
8 107
 
4.4%
Other Punctuation
ValueCountFrequency (%)
, 404
99.5%
@ 2
 
0.5%
Lowercase Letter
ValueCountFrequency (%)
e 1
50.0%
b 1
50.0%
Space Separator
ValueCountFrequency (%)
2638
100.0%
Open Punctuation
ValueCountFrequency (%)
( 507
100.0%
Close Punctuation
ValueCountFrequency (%)
) 507
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 42
100.0%
Math Symbol
ValueCountFrequency (%)
~ 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9586
59.3%
Common 6541
40.4%
Latin 45
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
666
 
6.9%
644
 
6.7%
640
 
6.7%
570
 
5.9%
563
 
5.9%
530
 
5.5%
524
 
5.5%
521
 
5.4%
240
 
2.5%
229
 
2.4%
Other values (266) 4459
46.5%
Common
ValueCountFrequency (%)
2638
40.3%
1 773
 
11.8%
( 507
 
7.8%
) 507
 
7.8%
, 404
 
6.2%
2 314
 
4.8%
3 242
 
3.7%
0 226
 
3.5%
4 212
 
3.2%
5 164
 
2.5%
Other values (7) 554
 
8.5%
Latin
ValueCountFrequency (%)
B 19
42.2%
A 6
 
13.3%
C 4
 
8.9%
G 3
 
6.7%
S 2
 
4.4%
K 2
 
4.4%
H 2
 
4.4%
e 1
 
2.2%
b 1
 
2.2%
L 1
 
2.2%
Other values (4) 4
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9586
59.3%
ASCII 6586
40.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2638
40.1%
1 773
 
11.7%
( 507
 
7.7%
) 507
 
7.7%
, 404
 
6.1%
2 314
 
4.8%
3 242
 
3.7%
0 226
 
3.4%
4 212
 
3.2%
5 164
 
2.5%
Other values (21) 599
 
9.1%
Hangul
ValueCountFrequency (%)
666
 
6.9%
644
 
6.7%
640
 
6.7%
570
 
5.9%
563
 
5.9%
530
 
5.5%
524
 
5.5%
521
 
5.4%
240
 
2.5%
229
 
2.4%
Other values (266) 4459
46.5%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct381
Distinct (%)73.8%
Missing218
Missing (%)29.7%
Infinite0
Infinite (%)0.0%
Mean47674.893
Minimum46004
Maximum49520
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.6 KiB
2024-04-21T16:24:06.371709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46004
5-th percentile46064.75
Q146759
median47599
Q348495.5
95-th percentile49403
Maximum49520
Range3516
Interquartile range (IQR)1736.5

Descriptive statistics

Standard deviation1063.1092
Coefficient of variation (CV)0.022299141
Kurtosis-1.1480033
Mean47674.893
Median Absolute Deviation (MAD)855.5
Skewness0.1484886
Sum24600245
Variance1130201.1
MonotonicityNot monotonic
2024-04-21T16:24:06.831432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
46230 5
 
0.7%
46759 5
 
0.7%
47369 4
 
0.5%
49494 4
 
0.5%
49108 4
 
0.5%
48515 4
 
0.5%
46762 4
 
0.5%
46726 4
 
0.5%
48053 3
 
0.4%
47038 3
 
0.4%
Other values (371) 476
64.9%
(Missing) 218
29.7%
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
0.5%
49490 1
 
0.1%
49482 1
 
0.1%
49477 2
0.3%
Distinct633
Distinct (%)86.2%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
2024-04-21T16:24:07.744200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length23
Mean length8.5081744
Min length2

Characters and Unicode

Total characters6245
Distinct characters328
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

Unique588 ?
Unique (%)80.1%

Sample

1st row자갈치 탑마트
2nd row(주)농협유통 하나로마트 자갈치점
3rd row(주)프로유통(빅세일마트)
4th row롯데쇼핑(주)롯데마트광복점
5th row제1,2구 잠수기수협 바다마트
ValueCountFrequency (%)
탑마트 19
 
1.9%
주)서원유통 19
 
1.9%
탑플러스마트 13
 
1.3%
빅세일마트 12
 
1.2%
롯데쇼핑(주)롯데슈퍼 12
 
1.2%
더마트 11
 
1.1%
탑세일마트 10
 
1.0%
주)지에스리테일 9
 
0.9%
농축산마트 8
 
0.8%
홈플러스(주 7
 
0.7%
Other values (680) 860
87.8%
2024-04-21T16:24:09.110705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
479
 
7.7%
469
 
7.5%
) 295
 
4.7%
( 292
 
4.7%
292
 
4.7%
268
 
4.3%
246
 
3.9%
175
 
2.8%
93
 
1.5%
89
 
1.4%
Other values (318) 3547
56.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5274
84.5%
Close Punctuation 295
 
4.7%
Open Punctuation 292
 
4.7%
Space Separator 246
 
3.9%
Uppercase Letter 110
 
1.8%
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 (%)
479
 
9.1%
469
 
8.9%
292
 
5.5%
268
 
5.1%
175
 
3.3%
93
 
1.8%
89
 
1.7%
81
 
1.5%
77
 
1.5%
73
 
1.4%
Other values (282) 3178
60.3%
Uppercase Letter
ValueCountFrequency (%)
S 25
22.7%
G 14
12.7%
E 10
 
9.1%
H 10
 
9.1%
C 9
 
8.2%
R 6
 
5.5%
F 6
 
5.5%
T 6
 
5.5%
K 5
 
4.5%
M 5
 
4.5%
Other values (8) 14
12.7%
Decimal Number
ValueCountFrequency (%)
2 9
50.0%
1 3
 
16.7%
3 2
 
11.1%
7 1
 
5.6%
4 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 (%)
) 295
100.0%
Open Punctuation
ValueCountFrequency (%)
( 292
100.0%
Space Separator
ValueCountFrequency (%)
246
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5274
84.5%
Common 858
 
13.7%
Latin 113
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
479
 
9.1%
469
 
8.9%
292
 
5.5%
268
 
5.1%
175
 
3.3%
93
 
1.8%
89
 
1.7%
81
 
1.5%
77
 
1.5%
73
 
1.4%
Other values (282) 3178
60.3%
Latin
ValueCountFrequency (%)
S 25
22.1%
G 14
12.4%
E 10
 
8.8%
H 10
 
8.8%
C 9
 
8.0%
R 6
 
5.3%
F 6
 
5.3%
T 6
 
5.3%
K 5
 
4.4%
M 5
 
4.4%
Other values (11) 17
15.0%
Common
ValueCountFrequency (%)
) 295
34.4%
( 292
34.0%
246
28.7%
2 9
 
1.0%
1 3
 
0.3%
3 2
 
0.2%
- 2
 
0.2%
. 2
 
0.2%
7 1
 
0.1%
& 1
 
0.1%
Other values (5) 5
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5274
84.5%
ASCII 971
 
15.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
479
 
9.1%
469
 
8.9%
292
 
5.5%
268
 
5.1%
175
 
3.3%
93
 
1.8%
89
 
1.7%
81
 
1.5%
77
 
1.5%
73
 
1.4%
Other values (282) 3178
60.3%
ASCII
ValueCountFrequency (%)
) 295
30.4%
( 292
30.1%
246
25.3%
S 25
 
2.6%
G 14
 
1.4%
E 10
 
1.0%
H 10
 
1.0%
2 9
 
0.9%
C 9
 
0.9%
R 6
 
0.6%
Other values (26) 55
 
5.7%
Distinct653
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
Minimum1999-06-07 00:00:00
Maximum2023-07-12 09:40:36
2024-04-21T16:24:09.419521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T16:24:09.729710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
I
384 
U
350 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 384
52.3%
U 350
47.7%

Length

2024-04-21T16:24:10.013950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:24:10.241654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 384
52.3%
u 350
47.7%
Distinct285
Distinct (%)38.8%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
Minimum2018-08-31 23:59:59
Maximum2023-07-14 02:40:00
2024-04-21T16:24:10.437123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T16:24:10.704461image/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 size5.9 KiB
기타식품판매업
730 
식품조사처리업
 
3
<NA>
 
1

Length

Max length7
Median length7
Mean length6.9959128
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
기타식품판매업 730
99.5%
식품조사처리업 3
 
0.4%
<NA> 1
 
0.1%

Length

2024-04-21T16:24:10.999654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:24:11.213034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타식품판매업 730
99.5%
식품조사처리업 3
 
0.4%
na 1
 
0.1%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct556
Distinct (%)79.5%
Missing35
Missing (%)4.8%
Infinite0
Infinite (%)0.0%
Mean387492.6
Minimum366779.27
Maximum409357.29
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.6 KiB
2024-04-21T16:24:11.425982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum366779.27
5-th percentile378387.11
Q1382563.51
median387835.93
Q3391732.31
95-th percentile399218.05
Maximum409357.29
Range42578.012
Interquartile range (IQR)9168.7981

Descriptive statistics

Standard deviation6906.8882
Coefficient of variation (CV)0.017824568
Kurtosis0.31270237
Mean387492.6
Median Absolute Deviation (MAD)4540.5678
Skewness0.13238776
Sum2.7085733 × 108
Variance47705105
MonotonicityNot monotonic
2024-04-21T16:24:11.686414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
390243.955026194 3
 
0.4%
392819.209113096 3
 
0.4%
388737.870459629 3
 
0.4%
380214.174893599 3
 
0.4%
387274.123524645 3
 
0.4%
390038.68419681 3
 
0.4%
389097.800933845 3
 
0.4%
387702.984126962 3
 
0.4%
387887.847334313 3
 
0.4%
389016.879192016 3
 
0.4%
Other values (546) 669
91.1%
(Missing) 35
 
4.8%
ValueCountFrequency (%)
366779.273667147 1
0.1%
366799.216536422 1
0.1%
366829.531355996 1
0.1%
368050.124865436 1
0.1%
369120.976733419 1
0.1%
371059.782971878 1
0.1%
371178.823833632 2
0.3%
371213.538987746 1
0.1%
371340.78580601 2
0.3%
371572.909768463 1
0.1%
ValueCountFrequency (%)
409357.285497075 1
0.1%
407434.699435546 1
0.1%
407418.650148508 1
0.1%
407290.984345075 1
0.1%
407245.51808397 2
0.3%
405376.498098434 1
0.1%
404088.624872995 1
0.1%
403214.458027912 1
0.1%
402187.626249677 1
0.1%
402168.69425719 1
0.1%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct556
Distinct (%)79.5%
Missing35
Missing (%)4.8%
Infinite0
Infinite (%)0.0%
Mean187540.69
Minimum174289.98
Maximum206150.93
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.6 KiB
2024-04-21T16:24:11.930771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum174289.98
5-th percentile177653.44
Q1182729.26
median187577.2
Q3191808.11
95-th percentile197899.88
Maximum206150.93
Range31860.948
Interquartile range (IQR)9078.8409

Descriptive statistics

Standard deviation6556.5288
Coefficient of variation (CV)0.034960566
Kurtosis-0.029594269
Mean187540.69
Median Absolute Deviation (MAD)4327.4433
Skewness0.32163408
Sum1.3109094 × 108
Variance42988069
MonotonicityNot monotonic
2024-04-21T16:24:12.192721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
197876.850318508 3
 
0.4%
187998.404942507 3
 
0.4%
189017.449131626 3
 
0.4%
182729.264942974 3
 
0.4%
184575.633639399 3
 
0.4%
191142.980733675 3
 
0.4%
192260.811648263 3
 
0.4%
184696.888361249 3
 
0.4%
187966.542955161 3
 
0.4%
176951.726317039 3
 
0.4%
Other values (546) 669
91.1%
(Missing) 35
 
4.8%
ValueCountFrequency (%)
174289.976688419 1
0.1%
174307.148168245 1
0.1%
174638.869997904 1
0.1%
174774.894177567 2
0.3%
174811.513941025 1
0.1%
174835.290190726 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%
206113.881439318 1
0.1%
205902.242523837 1
0.1%
205698.975086484 1
0.1%
205690.945808404 1
0.1%
205620.694333095 1
0.1%
205540.481848141 2
0.3%
205426.886676084 1
0.1%
205344.462661957 1
0.1%
205187.183814795 2
0.3%

위생업태명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
기타식품판매업
730 
식품조사처리업
 
3
<NA>
 
1

Length

Max length7
Median length7
Mean length6.9959128
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
기타식품판매업 730
99.5%
식품조사처리업 3
 
0.4%
<NA> 1
 
0.1%

Length

2024-04-21T16:24:12.460673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:24:12.681133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타식품판매업 730
99.5%
식품조사처리업 3
 
0.4%
na 1
 
0.1%
Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
<NA>
556 
0
177 
1
 
1

Length

Max length4
Median length4
Mean length3.2724796
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 556
75.7%
0 177
 
24.1%
1 1
 
0.1%

Length

2024-04-21T16:24:12.910076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:24:13.096943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 556
75.7%
0 177
 
24.1%
1 1
 
0.1%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
<NA>
557 
0
177 

Length

Max length4
Median length4
Mean length3.2765668
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 557
75.9%
0 177
 
24.1%

Length

2024-04-21T16:24:13.320787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:24:13.539505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 557
75.9%
0 177
 
24.1%

영업장주변구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
<NA>
535 
기타
188 
주택가주변
 
7
아파트지역
 
3
학교정화(절대)
 
1

Length

Max length8
Median length4
Mean length3.506812
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> 535
72.9%
기타 188
 
25.6%
주택가주변 7
 
1.0%
아파트지역 3
 
0.4%
학교정화(절대) 1
 
0.1%

Length

2024-04-21T16:24:13.755428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:24:13.954922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 535
72.9%
기타 188
 
25.6%
주택가주변 7
 
1.0%
아파트지역 3
 
0.4%
학교정화(절대 1
 
0.1%

등급구분명
Categorical

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
<NA>
535 
기타
189 
자율
 
10

Length

Max length4
Median length4
Mean length3.4577657
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> 535
72.9%
기타 189
 
25.7%
자율 10
 
1.4%

Length

2024-04-21T16:24:14.213598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:24:14.449738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 535
72.9%
기타 189
 
25.7%
자율 10
 
1.4%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
<NA>
631 
상수도전용
103 

Length

Max length5
Median length4
Mean length4.140327
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 631
86.0%
상수도전용 103
 
14.0%

Length

2024-04-21T16:24:14.646345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:24:14.850248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 631
86.0%
상수도전용 103
 
14.0%

총직원수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
<NA>
632 
0
102 

Length

Max length4
Median length4
Mean length3.5831063
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 632
86.1%
0 102
 
13.9%

Length

2024-04-21T16:24:15.078601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:24:15.281507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 632
86.1%
0 102
 
13.9%

본사직원수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
0
470 
<NA>
264 

Length

Max length4
Median length1
Mean length2.0790191
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 470
64.0%
<NA> 264
36.0%

Length

2024-04-21T16:24:15.673904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:24:15.875558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 470
64.0%
na 264
36.0%

공장사무직직원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
0
467 
<NA>
264 
1
 
2
2
 
1

Length

Max length4
Median length1
Mean length2.0790191
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 467
63.6%
<NA> 264
36.0%
1 2
 
0.3%
2 1
 
0.1%

Length

2024-04-21T16:24:16.092471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:24:16.318075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 467
63.6%
na 264
36.0%
1 2
 
0.3%
2 1
 
0.1%

공장판매직직원수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
0
465 
<NA>
264 
6
 
2
75
 
1
5
 
1

Length

Max length4
Median length1
Mean length2.0817439
Min length1

Unique

Unique3 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
0 465
63.4%
<NA> 264
36.0%
6 2
 
0.3%
75 1
 
0.1%
5 1
 
0.1%
15 1
 
0.1%

Length

2024-04-21T16:24:16.551244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:24:16.783671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 465
63.4%
na 264
36.0%
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 size5.9 KiB
0
470 
<NA>
264 

Length

Max length4
Median length1
Mean length2.0790191
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 470
64.0%
<NA> 264
36.0%

Length

2024-04-21T16:24:17.030449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:24:17.227615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 470
64.0%
na 264
36.0%
Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
<NA>
543 
자가
135 
임대
56 

Length

Max length4
Median length4
Mean length3.479564
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> 543
74.0%
자가 135
 
18.4%
임대 56
 
7.6%

Length

2024-04-21T16:24:17.429476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:24:17.638980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 543
74.0%
자가 135
 
18.4%
임대 56
 
7.6%

보증액
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
<NA>
609 
0
125 

Length

Max length4
Median length4
Mean length3.4891008
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 609
83.0%
0 125
 
17.0%

Length

2024-04-21T16:24:17.865536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:24:18.066082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 609
83.0%
0 125
 
17.0%

월세액
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
<NA>
609 
0
125 

Length

Max length4
Median length4
Mean length3.4891008
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 609
83.0%
0 125
 
17.0%

Length

2024-04-21T16:24:18.262028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:24:18.471327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 609
83.0%
0 125
 
17.0%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size862.0 B
False
734 
ValueCountFrequency (%)
False 734
100.0%
2024-04-21T16:24:18.645198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

ZEROS 

Distinct144
Distinct (%)19.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean85.976744
Minimum0
Maximum9790.33
Zeros585
Zeros (%)79.7%
Negative0
Negative (%)0.0%
Memory size6.6 KiB
2024-04-21T16:24:18.872735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile565.549
Maximum9790.33
Range9790.33
Interquartile range (IQR)0

Descriptive statistics

Standard deviation459.5496
Coefficient of variation (CV)5.3450454
Kurtosis280.28332
Mean85.976744
Median Absolute Deviation (MAD)0
Skewness14.515154
Sum63106.93
Variance211185.83
MonotonicityNot monotonic
2024-04-21T16:24:19.136726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 585
79.7%
6.46 3
 
0.4%
682.72 2
 
0.3%
15.0 2
 
0.3%
16.8 2
 
0.3%
495.0 2
 
0.3%
565.36 1
 
0.1%
732.17 1
 
0.1%
6.0 1
 
0.1%
996.8 1
 
0.1%
Other values (134) 134
 
18.3%
ValueCountFrequency (%)
0.0 585
79.7%
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%
5.2 1
 
0.1%
5.4 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 

Missing734
Missing (%)100.0%
Memory size6.6 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing734
Missing (%)100.0%
Memory size6.6 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing734
Missing (%)100.0%
Memory size6.6 KiB

Unnamed: 47
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing734
Missing (%)100.0%
Memory size6.6 KiB

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총직원수본사직원수공장사무직직원수공장판매직직원수공장생산직직원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지Unnamed: 47
01식품판매업(기타)07_22_13_P32500003250000-114-2000-000022001-08-09<NA>1영업/정상1영업<NA><NA><NA><NA>051 2488106565.36600-046부산광역시 중구 남포동6가 3 신천지백화점 1층부산광역시 중구 자갈치로 33, 1층 (남포동6가, 신천지백화점)48982자갈치 탑마트2013-04-02 15:48:02I2018-08-31 23:59:59기타식품판매업384836.914456179432.73458기타식품판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N565.36<NA><NA><NA><NA>
12식품판매업(기타)07_22_13_P32500003250000-114-1996-004141996-09-06<NA>1영업/정상1영업<NA><NA><NA><NA>051 25077002405.07600-046부산광역시 중구 남포동6가 1-0부산광역시 중구 구덕로 73 (남포동6가)48982(주)농협유통 하나로마트 자갈치점2022-04-11 14:28:01U2022-04-13 02:40:00기타식품판매업384820.119269179460.841059기타식품판매업00기타기타<NA><NA>0000<NA><NA><NA>N2405.07<NA><NA><NA><NA>
23식품판매업(기타)07_22_13_P32500003250000-114-1996-004161996-11-14<NA>1영업/정상1영업<NA><NA><NA><NA>051 2454900473.37600-806부산광역시 중구 부평동2가 16부산광역시 중구 부평1길 48 (부평동2가)48977(주)프로유통(빅세일마트)2016-06-15 11:45:58I2018-08-31 23:59:59기타식품판매업384663.000969179927.870276기타식품판매업<NA><NA>기타기타<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
34식품판매업(기타)07_22_13_P32500003250000-114-2014-000012014-08-25<NA>1영업/정상1영업<NA><NA><NA><NA><NA>963.0600-017부산광역시 중구 중앙동7가 20-1 롯데몰 마트시네마동 롯데마트광복점 지하2층부산광역시 중구 중앙대로 2, 지하1층 (중앙동7가, 롯데몰 마트시네마동 롯데마트광복점)48944롯데쇼핑(주)롯데마트광복점2022-04-19 15:52:04U2022-04-21 02:40:00기타식품판매업385590.814677179553.867032기타식품판매업<NA><NA><NA><NA>상수도전용<NA>00750자가<NA><NA>N0.0<NA><NA><NA><NA>
45식품판매업(기타)07_22_13_P32500003250000-114-2016-000012016-07-27<NA>1영업/정상1영업<NA><NA><NA><NA>051 254 0035576.13600-044부산광역시 중구 남포동4가 44-3부산광역시 중구 자갈치해안로 60, 1~3층 (남포동4가)48984제1,2구 잠수기수협 바다마트2023-04-07 17:55:25U2023-04-09 02:40:00기타식품판매업385191.013393179401.283402기타식품판매업00<NA><NA><NA>00000자가00N576.13<NA><NA><NA><NA>
56식품판매업(기타)07_22_13_P32500003250000-114-2016-000022016-11-18<NA>1영업/정상1영업<NA><NA><NA><NA>051 469 5770595.77600-815부산광역시 중구 중앙동4가 37-16부산광역시 중구 중앙대로81번길 9, 1층 (중앙동4가)48930(주)두배로마트2017-08-11 13:32:14I2018-08-31 23:59:59기타식품판매업385473.57641180297.978229기타식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N595.77<NA><NA><NA><NA>
67식품판매업(기타)07_22_13_P32500003250000-114-2009-000022009-12-18<NA>1영업/정상1영업<NA><NA><NA><NA>051 67830041147.0600-017부산광역시 중구 중앙동7가 20-1 외110필지 (롯데백화점 지하1층)부산광역시 중구 중앙대로 2, 지하1층 (중앙동7가, 외110필지 롯데백화점)48944롯데쇼핑주식회사2022-04-14 15:38:50U2022-04-16 02:40:00기타식품판매업385590.814677179553.867032기타식품판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
78식품판매업(기타)07_22_13_P32500003250000-114-2021-000012021-01-14<NA>1영업/정상1영업<NA><NA><NA><NA>051 241 4980680.0600-074부산광역시 중구 부평동4가 52-3부산광역시 중구 보수대로 82, 1층 (부평동4가)48973에스씨(SC)마트2021-01-14 14:54:43I2021-01-16 00:23:15기타식품판매업384249.201711180080.172972기타식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N10.0<NA><NA><NA><NA>
89식품판매업(기타)07_22_13_P32600003260000-114-2019-000012019-03-27<NA>1영업/정상1영업<NA><NA><NA><NA>051 25590051131.95602-838부산광역시 서구 토성동1가 25-1 경동 리인부산광역시 서구 보수대로 27, 1층 (토성동1가, 경동 리인)49247경동빅마트2022-06-29 17:15:58U2022-07-01 02:40:00기타식품판매업384479.160909179674.849131기타식품판매업00<NA><NA><NA>00000자가00N0.0<NA><NA><NA><NA>
910식품판매업(기타)07_22_13_P32600003260000-114-2021-000012021-02-26<NA>1영업/정상1영업<NA><NA><NA><NA>051 2427570545.93602-808부산광역시 서구 동대신동1가 392-1 (주)서구대성학원부산광역시 서구 구덕로 258 (주)서구대성학원 1층 (동대신동1가)49222동대마트2023-02-27 13:58:35U2023-03-01 02:40:00기타식품판매업384137.911315180621.372386기타식품판매업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA><NA>
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총직원수본사직원수공장사무직직원수공장판매직직원수공장생산직직원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지Unnamed: 47
724725식품판매업(기타)07_22_13_P34000003400000-114-1998-001761998-01-17<NA>3폐업2폐업1999-02-03<NA><NA><NA>051 72241760.0619-903부산광역시 기장군 기장읍 대라리 162-13<NA><NA>무지개식품2002-02-25 00:00:00I2018-08-31 23:59:59기타식품판매업401222.30775195403.979698기타식품판매업1<NA>아파트지역기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
725726식품판매업(기타)07_22_13_P34000003400000-114-2002-000012002-09-28<NA>3폐업2폐업2016-02-05<NA><NA><NA><NA><NA>619-901부산광역시 기장군 기장읍 교리 356-2부산광역시 기장군 기장읍 차성로 43446055우와마트2016-02-05 09:14:00I2018-08-31 23:59:59기타식품판매업401756.246296197244.945141기타식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
726727식품판매업(기타)07_22_13_P34000003400000-114-2003-000012003-08-01<NA>3폐업2폐업2018-03-15<NA><NA><NA>051 724 45001821.83619-903부산광역시 기장군 기장읍 대라리 57부산광역시 기장군 기장읍 차성동로 6346066홈플러스 익스프레스 기장점2018-03-15 16:11:23I2018-08-31 23:59:59기타식품판매업401671.555424196027.510818기타식품판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
727728식품판매업(기타)07_22_13_P34000003400000-114-2007-000012007-02-07<NA>3폐업2폐업2010-01-11<NA><NA><NA>051 7274983316.25619-951부산광역시 기장군 장안읍 월내리 11-1<NA><NA>세호마트2007-02-07 00:00:00I2018-08-31 23:59:59기타식품판매업407245.518084205540.481848기타식품판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
728729식품판매업(기타)07_22_13_P34000003400000-114-2007-000022007-08-07<NA>3폐업2폐업2020-06-29<NA><NA><NA>051 722 44751336.0619-905부산광역시 기장군 기장읍 동부리 124부산광역시 기장군 기장읍 차성로 31446061엄마야마트가자2020-06-29 16:03:33U2020-07-01 02:40:00기타식품판매업401451.765883196278.103365기타식품판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
729730식품판매업(기타)07_22_13_P34000003400000-114-1998-001771998-10-20<NA>3폐업2폐업2006-09-22<NA><NA><NA>051 7227585<NA>619-903부산광역시 기장군 기장읍 대라리 68-9<NA><NA>빅세일기장점2002-06-08 00:00:00I2018-08-31 23:59:59기타식품판매업401617.638635196097.167397기타식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
730731식품판매업(기타)07_22_13_P34000003400000-114-1999-002331999-05-18<NA>3폐업2폐업2006-03-06<NA><NA><NA>051 7242949<NA>619-912부산광역시 기장군 일광면 삼성리 36-4<NA><NA>(주)홈마트2002-06-08 00:00:00I2018-08-31 23:59:59기타식품판매업<NA><NA>기타식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
731732식품판매업(기타)07_22_13_P34000003400000-114-2008-000012008-01-10<NA>3폐업2폐업2013-04-01<NA><NA><NA>0517279910348.25619-952부산광역시 기장군 장안읍 길천리 207-3부산광역시 기장군 장안읍 해맞이로 424<NA>동양마트2008-01-15 10:03:32I2018-08-31 23:59:59기타식품판매업407434.699436205690.945808기타식품판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
732733식품판매업(기타)07_22_13_P34000003400000-114-2014-000052014-12-22<NA>3폐업2폐업2022-11-29<NA><NA><NA>051 727 1712435.0619-902부산광역시 기장군 기장읍 당사리 64 롯데몰 동부산점 A131호부산광역시 기장군 기장읍 기장해안로 147, A131호 (롯데몰 동부산점)46084동부산농협 향토특산물관2022-11-29 16:55:31U2023-05-26 08:48:36기타식품판매업401473.950699190354.255834기타식품판매업00<NA><NA>상수도전용00000자가00N435.0<NA><NA><NA><NA>
733734식품판매업(기타)07_22_13_P34000003400000-114-2011-000022011-08-08<NA>3폐업2폐업2018-09-05<NA><NA><NA>051 529 5700546.94619-902부산광역시 기장군 기장읍 내리 775-5부산광역시 기장군 기장읍 기장대로 85, 1층46076농축산마트2018-09-05 20:15:21U2018-09-05 23:59:59기타식품판매업400809.773502191737.640257기타식품판매업<NA><NA><NA><NA><NA><NA>0000자가<NA><NA>N0.0<NA><NA><NA><NA>