Overview

Dataset statistics

Number of variables48
Number of observations4915
Missing cells68479
Missing cells (%)29.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 MiB
Average record size in memory412.0 B

Variable types

Numeric16
Categorical15
Text7
Unsupported8
DateTime1
Boolean1

Dataset

Description2021-05-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123104

Alerts

개방서비스명 has constant value ""Constant
개방서비스id has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (62.2%)Imbalance
위생업태명 is highly imbalanced (62.3%)Imbalance
남성종사자수 is highly imbalanced (70.5%)Imbalance
여성종사자수 is highly imbalanced (67.3%)Imbalance
영업장주변구분명 is highly imbalanced (65.9%)Imbalance
급수시설구분명 is highly imbalanced (60.1%)Imbalance
인허가취소일자 has 4915 (100.0%) missing valuesMissing
폐업일자 has 1371 (27.9%) missing valuesMissing
휴업시작일자 has 4915 (100.0%) missing valuesMissing
휴업종료일자 has 4915 (100.0%) missing valuesMissing
재개업일자 has 4915 (100.0%) missing valuesMissing
소재지전화 has 969 (19.7%) missing valuesMissing
소재지면적 has 641 (13.0%) missing valuesMissing
소재지우편번호 has 98 (2.0%) missing valuesMissing
도로명전체주소 has 2179 (44.3%) missing valuesMissing
도로명우편번호 has 2227 (45.3%) missing valuesMissing
좌표정보(x) has 249 (5.1%) missing valuesMissing
좌표정보(y) has 249 (5.1%) missing valuesMissing
총종업원수 has 4915 (100.0%) missing valuesMissing
본사종업원수 has 1800 (36.6%) missing valuesMissing
공장사무직종업원수 has 1783 (36.3%) missing valuesMissing
공장판매직종업원수 has 1800 (36.6%) missing valuesMissing
공장생산직종업원수 has 1749 (35.6%) missing valuesMissing
보증액 has 4601 (93.6%) missing valuesMissing
월세액 has 4601 (93.6%) missing valuesMissing
전통업소지정번호 has 4915 (100.0%) missing valuesMissing
전통업소주된음식 has 4915 (100.0%) missing valuesMissing
홈페이지 has 4837 (98.4%) missing valuesMissing
Unnamed: 47 has 4915 (100.0%) missing valuesMissing
폐업일자 is highly skewed (γ1 = -37.12033185)Skewed
본사종업원수 is highly skewed (γ1 = 55.81208521)Skewed
공장판매직종업원수 is highly skewed (γ1 = 24.78021024)Skewed
번호 has unique valuesUnique
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
총종업원수 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 47 is an unsupported type, check if it needs cleaning or further analysisUnsupported
본사종업원수 has 3075 (62.6%) zerosZeros
공장사무직종업원수 has 2800 (57.0%) zerosZeros
공장판매직종업원수 has 3080 (62.7%) zerosZeros
공장생산직종업원수 has 2547 (51.8%) zerosZeros
보증액 has 306 (6.2%) zerosZeros
월세액 has 306 (6.2%) zerosZeros
시설총규모 has 3736 (76.0%) zerosZeros

Reproduction

Analysis started2024-04-20 13:18:59.171691
Analysis finished2024-04-20 13:19:01.691453
Duration2.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct4915
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2458
Minimum1
Maximum4915
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-04-20T22:19:01.887347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile246.7
Q11229.5
median2458
Q33686.5
95-th percentile4669.3
Maximum4915
Range4914
Interquartile range (IQR)2457

Descriptive statistics

Standard deviation1418.9826
Coefficient of variation (CV)0.57729154
Kurtosis-1.2
Mean2458
Median Absolute Deviation (MAD)1229
Skewness0
Sum12081070
Variance2013511.7
MonotonicityStrictly increasing
2024-04-20T22:19:02.335684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
3276 1
 
< 0.1%
3283 1
 
< 0.1%
3282 1
 
< 0.1%
3281 1
 
< 0.1%
3280 1
 
< 0.1%
3279 1
 
< 0.1%
3278 1
 
< 0.1%
3277 1
 
< 0.1%
3275 1
 
< 0.1%
Other values (4905) 4905
99.8%
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 (%)
4915 1
< 0.1%
4914 1
< 0.1%
4913 1
< 0.1%
4912 1
< 0.1%
4911 1
< 0.1%
4910 1
< 0.1%
4909 1
< 0.1%
4908 1
< 0.1%
4907 1
< 0.1%
4906 1
< 0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
식품제조가공업
4915 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 4915
100.0%

Length

2024-04-20T22:19:02.803241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T22:19:03.116898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 4915
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
07_22_11_P
4915 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row07_22_11_P
2nd row07_22_11_P
3rd row07_22_11_P
4th row07_22_11_P
5th row07_22_11_P

Common Values

ValueCountFrequency (%)
07_22_11_P 4915
100.0%

Length

2024-04-20T22:19:03.352579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T22:19:03.507987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_11_p 4915
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3335975.6
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-04-20T22:19:03.677424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3260000
Q13300000
median3340000
Q33370000
95-th percentile3400000
Maximum3400000
Range150000
Interquartile range (IQR)70000

Descriptive statistics

Standard deviation41784.077
Coefficient of variation (CV)0.012525294
Kurtosis-0.88687959
Mean3335975.6
Median Absolute Deviation (MAD)30000
Skewness-0.18788071
Sum1.639632 × 1010
Variance1.745909 × 109
MonotonicityNot monotonic
2024-04-20T22:19:03.883725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3340000 779
15.8%
3390000 484
9.8%
3290000 466
9.5%
3400000 424
8.6%
3330000 399
8.1%
3350000 380
7.7%
3360000 319
 
6.5%
3300000 311
 
6.3%
3260000 282
 
5.7%
3310000 219
 
4.5%
Other values (6) 852
17.3%
ValueCountFrequency (%)
3250000 78
 
1.6%
3260000 282
 
5.7%
3270000 99
 
2.0%
3280000 105
 
2.1%
3290000 466
9.5%
3300000 311
 
6.3%
3310000 219
 
4.5%
3320000 192
 
3.9%
3330000 399
8.1%
3340000 779
15.8%
ValueCountFrequency (%)
3400000 424
8.6%
3390000 484
9.8%
3380000 201
 
4.1%
3370000 177
 
3.6%
3360000 319
6.5%
3350000 380
7.7%
3340000 779
15.8%
3330000 399
8.1%
3320000 192
 
3.9%
3310000 219
 
4.5%

관리번호
Text

UNIQUE 

Distinct4915
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
2024-04-20T22:19:04.523406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters108130
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

Unique4915 ?
Unique (%)100.0%

Sample

1st row3390000-106-2002-00003
2nd row3390000-106-2013-00009
3rd row3390000-106-2000-00885
4th row3390000-106-1997-00280
5th row3390000-106-1997-00581
ValueCountFrequency (%)
3390000-106-2002-00003 1
 
< 0.1%
3400000-106-1995-00147 1
 
< 0.1%
3400000-106-1995-00045 1
 
< 0.1%
3400000-106-1995-00227 1
 
< 0.1%
3400000-106-1994-00137 1
 
< 0.1%
3400000-106-1994-00174 1
 
< 0.1%
3400000-106-1994-00044 1
 
< 0.1%
3400000-106-1992-00129 1
 
< 0.1%
3400000-106-2016-00019 1
 
< 0.1%
3400000-106-2016-00018 1
 
< 0.1%
Other values (4905) 4905
99.8%
2024-04-20T22:19:05.405459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 47232
43.7%
- 14745
 
13.6%
1 10865
 
10.0%
3 10182
 
9.4%
6 6817
 
6.3%
2 6734
 
6.2%
9 4076
 
3.8%
4 2486
 
2.3%
8 1751
 
1.6%
5 1631
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 93385
86.4%
Dash Punctuation 14745
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 47232
50.6%
1 10865
 
11.6%
3 10182
 
10.9%
6 6817
 
7.3%
2 6734
 
7.2%
9 4076
 
4.4%
4 2486
 
2.7%
8 1751
 
1.9%
5 1631
 
1.7%
7 1611
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 14745
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 108130
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 47232
43.7%
- 14745
 
13.6%
1 10865
 
10.0%
3 10182
 
9.4%
6 6817
 
6.3%
2 6734
 
6.2%
9 4076
 
3.8%
4 2486
 
2.3%
8 1751
 
1.6%
5 1631
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 108130
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 47232
43.7%
- 14745
 
13.6%
1 10865
 
10.0%
3 10182
 
9.4%
6 6817
 
6.3%
2 6734
 
6.2%
9 4076
 
3.8%
4 2486
 
2.3%
8 1751
 
1.6%
5 1631
 
1.5%

인허가일자
Real number (ℝ)

Distinct3491
Distinct (%)71.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20050064
Minimum19631010
Maximum20210324
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-04-20T22:19:05.658387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19631010
5-th percentile19847445
Q120000224
median20060523
Q320140106
95-th percentile20190425
Maximum20210324
Range579314
Interquartile range (IQR)139883

Descriptive statistics

Standard deviation109236.44
Coefficient of variation (CV)0.0054481838
Kurtosis1.6064753
Mean20050064
Median Absolute Deviation (MAD)69896
Skewness-1.1149117
Sum9.8546067 × 1010
Variance1.1932599 × 1010
MonotonicityNot monotonic
2024-04-20T22:19:06.235229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20020326 20
 
0.4%
20120525 8
 
0.2%
19720113 8
 
0.2%
20010517 8
 
0.2%
20010511 7
 
0.1%
20061128 7
 
0.1%
20150918 6
 
0.1%
20181203 6
 
0.1%
20140530 6
 
0.1%
20140613 6
 
0.1%
Other values (3481) 4833
98.3%
ValueCountFrequency (%)
19631010 3
0.1%
19640110 2
< 0.1%
19640212 1
 
< 0.1%
19660401 1
 
< 0.1%
19660419 1
 
< 0.1%
19660430 1
 
< 0.1%
19660708 1
 
< 0.1%
19660902 1
 
< 0.1%
19661019 1
 
< 0.1%
19661107 1
 
< 0.1%
ValueCountFrequency (%)
20210324 1
 
< 0.1%
20210323 2
< 0.1%
20210319 1
 
< 0.1%
20210317 3
0.1%
20210312 1
 
< 0.1%
20210310 1
 
< 0.1%
20210305 2
< 0.1%
20210303 3
0.1%
20210219 1
 
< 0.1%
20210218 1
 
< 0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4915
Missing (%)100.0%
Memory size43.3 KiB

영업상태구분코드
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
3
3544 
1
1371 

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 3544
72.1%
1 1371
 
27.9%

Length

2024-04-20T22:19:06.694376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T22:19:07.008650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 3544
72.1%
1 1371
 
27.9%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
폐업
3544 
영업/정상
1371 

Length

Max length5
Median length2
Mean length2.836826
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 3544
72.1%
영업/정상 1371
 
27.9%

Length

2024-04-20T22:19:07.369467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T22:19:07.821427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3544
72.1%
영업/정상 1371
 
27.9%

상세영업상태코드
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
2
3544 
1
1371 

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 3544
72.1%
1 1371
 
27.9%

Length

2024-04-20T22:19:08.290726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T22:19:08.669007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 3544
72.1%
1 1371
 
27.9%

상세영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
폐업
3544 
영업
1371 

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 3544
72.1%
영업 1371
 
27.9%

Length

2024-04-20T22:19:09.136110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T22:19:09.522704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3544
72.1%
영업 1371
 
27.9%

폐업일자
Real number (ℝ)

MISSING  SKEWED 

Distinct2464
Distinct (%)69.5%
Missing1371
Missing (%)27.9%
Infinite0
Infinite (%)0.0%
Mean20086667
Minimum10000101
Maximum20210330
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-04-20T22:19:10.222341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10000101
5-th percentile19990719
Q120030926
median20090601
Q320151012
95-th percentile20200207
Maximum20210330
Range10210229
Interquartile range (IQR)120086.25

Descriptive statistics

Standard deviation236967.72
Coefficient of variation (CV)0.011797265
Kurtosis1506.9872
Mean20086667
Median Absolute Deviation (MAD)60004
Skewness-37.120332
Sum7.1187147 × 1010
Variance5.6153702 × 1010
MonotonicityNot monotonic
2024-04-20T22:19:10.812602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20061215 18
 
0.4%
20080225 16
 
0.3%
20031203 14
 
0.3%
20050614 12
 
0.2%
20000331 9
 
0.2%
20041224 8
 
0.2%
20130404 8
 
0.2%
20050330 7
 
0.1%
20030916 7
 
0.1%
20040126 7
 
0.1%
Other values (2454) 3438
69.9%
(Missing) 1371
 
27.9%
ValueCountFrequency (%)
10000101 1
< 0.1%
11111111 1
< 0.1%
19851214 1
< 0.1%
19900103 1
< 0.1%
19900131 1
< 0.1%
19900607 1
< 0.1%
19900703 1
< 0.1%
19900713 1
< 0.1%
19910314 1
< 0.1%
19921021 1
< 0.1%
ValueCountFrequency (%)
20210330 1
 
< 0.1%
20210326 1
 
< 0.1%
20210325 1
 
< 0.1%
20210324 1
 
< 0.1%
20210322 2
< 0.1%
20210317 2
< 0.1%
20210309 1
 
< 0.1%
20210305 1
 
< 0.1%
20210303 1
 
< 0.1%
20210302 4
0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4915
Missing (%)100.0%
Memory size43.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4915
Missing (%)100.0%
Memory size43.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4915
Missing (%)100.0%
Memory size43.3 KiB

소재지전화
Text

MISSING 

Distinct3310
Distinct (%)83.9%
Missing969
Missing (%)19.7%
Memory size38.5 KiB
2024-04-20T22:19:12.134774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.529143
Min length2

Characters and Unicode

Total characters41548
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

Unique3051 ?
Unique (%)77.3%

Sample

1st row051 3176677
2nd row051 3282358
3rd row051 3013269
4th row051311 5930
5th row051 301 6297
ValueCountFrequency (%)
051 3465
40.9%
070 115
 
1.4%
727 21
 
0.2%
261 19
 
0.2%
231 19
 
0.2%
722 18
 
0.2%
266 18
 
0.2%
728 17
 
0.2%
831 17
 
0.2%
253 17
 
0.2%
Other values (3518) 4756
56.1%
2024-04-20T22:19:13.479749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6614
15.9%
5 6473
15.6%
1 6272
15.1%
4586
11.0%
2 3608
8.7%
7 2650
6.4%
6 2601
 
6.3%
3 2594
 
6.2%
8 2308
 
5.6%
4 2148
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 36962
89.0%
Space Separator 4586
 
11.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6614
17.9%
5 6473
17.5%
1 6272
17.0%
2 3608
9.8%
7 2650
7.2%
6 2601
 
7.0%
3 2594
 
7.0%
8 2308
 
6.2%
4 2148
 
5.8%
9 1694
 
4.6%
Space Separator
ValueCountFrequency (%)
4586
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 41548
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6614
15.9%
5 6473
15.6%
1 6272
15.1%
4586
11.0%
2 3608
8.7%
7 2650
6.4%
6 2601
 
6.3%
3 2594
 
6.2%
8 2308
 
5.6%
4 2148
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41548
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6614
15.9%
5 6473
15.6%
1 6272
15.1%
4586
11.0%
2 3608
8.7%
7 2650
6.4%
6 2601
 
6.3%
3 2594
 
6.2%
8 2308
 
5.6%
4 2148
 
5.2%

소재지면적
Text

MISSING 

Distinct3024
Distinct (%)70.8%
Missing641
Missing (%)13.0%
Memory size38.5 KiB
2024-04-20T22:19:14.744052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length5.3352831
Min length3

Characters and Unicode

Total characters22803
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

Unique2551 ?
Unique (%)59.7%

Sample

1st row1,480.80
2nd row421.25
3rd row27.50
4th row1,251.05
5th row293.00
ValueCountFrequency (%)
00 374
 
8.8%
27.00 23
 
0.5%
33.00 11
 
0.3%
36.00 10
 
0.2%
20.00 10
 
0.2%
12.00 10
 
0.2%
24.00 10
 
0.2%
60.00 10
 
0.2%
48.00 10
 
0.2%
330.00 9
 
0.2%
Other values (3014) 3797
88.8%
2024-04-20T22:19:16.187726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4279
18.8%
. 4274
18.7%
1 2143
9.4%
2 1969
8.6%
4 1604
 
7.0%
3 1563
 
6.9%
5 1487
 
6.5%
6 1460
 
6.4%
8 1329
 
5.8%
9 1289
 
5.7%
Other values (2) 1406
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18348
80.5%
Other Punctuation 4455
 
19.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4279
23.3%
1 2143
11.7%
2 1969
10.7%
4 1604
 
8.7%
3 1563
 
8.5%
5 1487
 
8.1%
6 1460
 
8.0%
8 1329
 
7.2%
9 1289
 
7.0%
7 1225
 
6.7%
Other Punctuation
ValueCountFrequency (%)
. 4274
95.9%
, 181
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
Common 22803
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4279
18.8%
. 4274
18.7%
1 2143
9.4%
2 1969
8.6%
4 1604
 
7.0%
3 1563
 
6.9%
5 1487
 
6.5%
6 1460
 
6.4%
8 1329
 
5.8%
9 1289
 
5.7%
Other values (2) 1406
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22803
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4279
18.8%
. 4274
18.7%
1 2143
9.4%
2 1969
8.6%
4 1604
 
7.0%
3 1563
 
6.9%
5 1487
 
6.5%
6 1460
 
6.4%
8 1329
 
5.8%
9 1289
 
5.7%
Other values (2) 1406
 
6.2%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct725
Distinct (%)15.1%
Missing98
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean611327
Minimum600011
Maximum619953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-04-20T22:19:16.444981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600011
5-th percentile602030
Q1604851
median611836
Q3616819
95-th percentile619903
Maximum619953
Range19942
Interquartile range (IQR)11968

Descriptive statistics

Standard deviation5724.0416
Coefficient of variation (CV)0.0093633058
Kurtosis-1.237591
Mean611327
Median Absolute Deviation (MAD)5224
Skewness-0.12346026
Sum2.9447622 × 109
Variance32764653
MonotonicityNot monotonic
2024-04-20T22:19:16.886974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
604842 145
 
3.0%
604846 106
 
2.2%
602030 105
 
2.1%
604845 70
 
1.4%
619904 67
 
1.4%
617831 65
 
1.3%
614843 56
 
1.1%
609845 50
 
1.0%
609809 45
 
0.9%
604817 45
 
0.9%
Other values (715) 4063
82.7%
(Missing) 98
 
2.0%
ValueCountFrequency (%)
600011 1
 
< 0.1%
600017 2
 
< 0.1%
600024 1
 
< 0.1%
600025 2
 
< 0.1%
600032 1
 
< 0.1%
600041 4
0.1%
600044 9
0.2%
600045 5
0.1%
600046 4
0.1%
600074 4
0.1%
ValueCountFrequency (%)
619953 6
 
0.1%
619952 19
 
0.4%
619951 38
0.8%
619913 19
 
0.4%
619912 26
 
0.5%
619911 13
 
0.3%
619906 29
0.6%
619905 22
 
0.4%
619904 67
1.4%
619903 34
0.7%

소재지전체주소
Text

Distinct4301
Distinct (%)87.6%
Missing5
Missing (%)0.1%
Memory size38.5 KiB
2024-04-20T22:19:18.219522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length82
Median length67
Mean length24.24277
Min length16

Characters and Unicode

Total characters119032
Distinct characters401
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3901 ?
Unique (%)79.5%

Sample

1st row부산광역시 사상구 학장동 748-7번지
2nd row부산광역시 사상구 감전동 133-7번지
3rd row부산광역시 사상구 감전동 143-16번지
4th row부산광역시 사상구 삼락동 390-5번지
5th row부산광역시 사상구 학장동 226-9번지
ValueCountFrequency (%)
부산광역시 4913
 
21.7%
사하구 776
 
3.4%
사상구 483
 
2.1%
부산진구 467
 
2.1%
기장군 424
 
1.9%
장림동 401
 
1.8%
해운대구 398
 
1.8%
금정구 380
 
1.7%
강서구 319
 
1.4%
동래구 311
 
1.4%
Other values (4866) 13736
60.8%
2024-04-20T22:19:20.015786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17702
 
14.9%
산 5894
 
5.0%
부 5860
 
4.9%
동 5442
 
4.6%
1 5341
 
4.5%
광 5051
 
4.2%
시 5028
 
4.2%
지 4934
 
4.1%
역 4919
 
4.1%
구 4694
 
3.9%
Other values (391) 54167
45.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 71525
60.1%
Decimal Number 24346
 
20.5%
Space Separator 17702
 
14.9%
Dash Punctuation 4400
 
3.7%
Uppercase Letter 431
 
0.4%
Other Punctuation 227
 
0.2%
Open Punctuation 193
 
0.2%
Close Punctuation 191
 
0.2%
Math Symbol 12
 
< 0.1%
Lowercase Letter 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 5894
 
8.2%
부 5860
 
8.2%
동 5442
 
7.6%
광 5051
 
7.1%
시 5028
 
7.0%
지 4934
 
6.9%
역 4919
 
6.9%
구 4694
 
6.6%
번 4499
 
6.3%
사 1379
 
1.9%
Other values (349) 23825
33.3%
Uppercase Letter
ValueCountFrequency (%)
B 213
49.4%
T 129
29.9%
A 39
 
9.0%
C 11
 
2.6%
F 9
 
2.1%
P 5
 
1.2%
D 5
 
1.2%
S 5
 
1.2%
E 4
 
0.9%
L 4
 
0.9%
Other values (7) 7
 
1.6%
Decimal Number
ValueCountFrequency (%)
1 5341
21.9%
2 3173
13.0%
3 2714
11.1%
4 2384
9.8%
5 2097
 
8.6%
0 1971
 
8.1%
6 1831
 
7.5%
7 1789
 
7.3%
8 1615
 
6.6%
9 1431
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 198
87.2%
. 22
 
9.7%
/ 4
 
1.8%
@ 2
 
0.9%
: 1
 
0.4%
Lowercase Letter
ValueCountFrequency (%)
e 1
20.0%
a 1
20.0%
p 1
20.0%
t 1
20.0%
b 1
20.0%
Space Separator
ValueCountFrequency (%)
17702
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4400
100.0%
Open Punctuation
ValueCountFrequency (%)
( 193
100.0%
Close Punctuation
ValueCountFrequency (%)
) 191
100.0%
Math Symbol
ValueCountFrequency (%)
~ 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 71525
60.1%
Common 47071
39.5%
Latin 436
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 5894
 
8.2%
부 5860
 
8.2%
동 5442
 
7.6%
광 5051
 
7.1%
시 5028
 
7.0%
지 4934
 
6.9%
역 4919
 
6.9%
구 4694
 
6.6%
번 4499
 
6.3%
사 1379
 
1.9%
Other values (349) 23825
33.3%
Latin
ValueCountFrequency (%)
B 213
48.9%
T 129
29.6%
A 39
 
8.9%
C 11
 
2.5%
F 9
 
2.1%
P 5
 
1.1%
D 5
 
1.1%
S 5
 
1.1%
E 4
 
0.9%
L 4
 
0.9%
Other values (12) 12
 
2.8%
Common
ValueCountFrequency (%)
17702
37.6%
1 5341
 
11.3%
- 4400
 
9.3%
2 3173
 
6.7%
3 2714
 
5.8%
4 2384
 
5.1%
5 2097
 
4.5%
0 1971
 
4.2%
6 1831
 
3.9%
7 1789
 
3.8%
Other values (10) 3669
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 71523
60.1%
ASCII 47507
39.9%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17702
37.3%
1 5341
 
11.2%
- 4400
 
9.3%
2 3173
 
6.7%
3 2714
 
5.7%
4 2384
 
5.0%
5 2097
 
4.4%
0 1971
 
4.1%
6 1831
 
3.9%
7 1789
 
3.8%
Other values (32) 4105
 
8.6%
Hangul
ValueCountFrequency (%)
산 5894
 
8.2%
부 5860
 
8.2%
동 5442
 
7.6%
광 5051
 
7.1%
시 5028
 
7.0%
지 4934
 
6.9%
역 4919
 
6.9%
구 4694
 
6.6%
번 4499
 
6.3%
사 1379
 
1.9%
Other values (348) 23823
33.3%
Compat Jamo
ValueCountFrequency (%)
ㅎ 2
100.0%

도로명전체주소
Text

MISSING 

Distinct2597
Distinct (%)94.9%
Missing2179
Missing (%)44.3%
Memory size38.5 KiB
2024-04-20T22:19:21.406050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length87
Median length59
Mean length30.630117
Min length19

Characters and Unicode

Total characters83804
Distinct characters406
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

Unique2486 ?
Unique (%)90.9%

Sample

1st row부산광역시 사상구 학장로83번길 34 (학장동)
2nd row부산광역시 사상구 새벽시장로133번길 11, 1~2층 (감전동)
3rd row부산광역시 사상구 새벽로 141 (감전동)
4th row부산광역시 사상구 낙동대로1348번길 54 (삼락동)
5th row부산광역시 사상구 가야대로104번길 36 (학장동)
ValueCountFrequency (%)
부산광역시 2739
 
17.0%
1층 470
 
2.9%
사하구 442
 
2.7%
기장군 287
 
1.8%
사상구 266
 
1.7%
부산진구 252
 
1.6%
해운대구 226
 
1.4%
금정구 223
 
1.4%
강서구 211
 
1.3%
장림동 208
 
1.3%
Other values (3007) 10771
66.9%
2024-04-20T22:19:23.327659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13364
 
15.9%
산 3471
 
4.1%
1 3459
 
4.1%
부 3334
 
4.0%
동 3296
 
3.9%
시 2901
 
3.5%
광 2883
 
3.4%
역 2743
 
3.3%
구 2595
 
3.1%
로 2586
 
3.1%
Other values (396) 43172
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 49213
58.7%
Decimal Number 13519
 
16.1%
Space Separator 13364
 
15.9%
Open Punctuation 2539
 
3.0%
Close Punctuation 2539
 
3.0%
Other Punctuation 1916
 
2.3%
Dash Punctuation 490
 
0.6%
Uppercase Letter 189
 
0.2%
Math Symbol 34
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 3471
 
7.1%
부 3334
 
6.8%
동 3296
 
6.7%
시 2901
 
5.9%
광 2883
 
5.9%
역 2743
 
5.6%
구 2595
 
5.3%
로 2586
 
5.3%
길 1620
 
3.3%
번 1474
 
3.0%
Other values (358) 22310
45.3%
Uppercase Letter
ValueCountFrequency (%)
B 90
47.6%
A 52
27.5%
C 15
 
7.9%
F 5
 
2.6%
I 5
 
2.6%
E 5
 
2.6%
S 4
 
2.1%
G 3
 
1.6%
D 2
 
1.1%
P 2
 
1.1%
Other values (5) 6
 
3.2%
Decimal Number
ValueCountFrequency (%)
1 3459
25.6%
2 1969
14.6%
3 1524
11.3%
4 1170
 
8.7%
0 1119
 
8.3%
5 1041
 
7.7%
6 1011
 
7.5%
7 789
 
5.8%
9 734
 
5.4%
8 703
 
5.2%
Other Punctuation
ValueCountFrequency (%)
, 1911
99.7%
. 2
 
0.1%
* 1
 
0.1%
/ 1
 
0.1%
@ 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 2538
> 99.9%
[ 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 2538
> 99.9%
] 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
13364
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 490
100.0%
Math Symbol
ValueCountFrequency (%)
~ 34
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 49213
58.7%
Common 34401
41.0%
Latin 190
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 3471
 
7.1%
부 3334
 
6.8%
동 3296
 
6.7%
시 2901
 
5.9%
광 2883
 
5.9%
역 2743
 
5.6%
구 2595
 
5.3%
로 2586
 
5.3%
길 1620
 
3.3%
번 1474
 
3.0%
Other values (358) 22310
45.3%
Common
ValueCountFrequency (%)
13364
38.8%
1 3459
 
10.1%
( 2538
 
7.4%
) 2538
 
7.4%
2 1969
 
5.7%
, 1911
 
5.6%
3 1524
 
4.4%
4 1170
 
3.4%
0 1119
 
3.3%
5 1041
 
3.0%
Other values (12) 3768
 
11.0%
Latin
ValueCountFrequency (%)
B 90
47.4%
A 52
27.4%
C 15
 
7.9%
F 5
 
2.6%
I 5
 
2.6%
E 5
 
2.6%
S 4
 
2.1%
G 3
 
1.6%
D 2
 
1.1%
P 2
 
1.1%
Other values (6) 7
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 49213
58.7%
ASCII 34591
41.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13364
38.6%
1 3459
 
10.0%
( 2538
 
7.3%
) 2538
 
7.3%
2 1969
 
5.7%
, 1911
 
5.5%
3 1524
 
4.4%
4 1170
 
3.4%
0 1119
 
3.2%
5 1041
 
3.0%
Other values (28) 3958
 
11.4%
Hangul
ValueCountFrequency (%)
산 3471
 
7.1%
부 3334
 
6.8%
동 3296
 
6.7%
시 2901
 
5.9%
광 2883
 
5.9%
역 2743
 
5.6%
구 2595
 
5.3%
로 2586
 
5.3%
길 1620
 
3.3%
번 1474
 
3.0%
Other values (358) 22310
45.3%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct991
Distinct (%)36.9%
Missing2227
Missing (%)45.3%
Infinite0
Infinite (%)0.0%
Mean47722.647
Minimum46000
Maximum49526
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-04-20T22:19:23.583713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46000
5-th percentile46047
Q146712.75
median47579
Q348964
95-th percentile49478
Maximum49526
Range3526
Interquartile range (IQR)2251.25

Descriptive statistics

Standard deviation1184.7725
Coefficient of variation (CV)0.024826212
Kurtosis-1.3342183
Mean47722.647
Median Absolute Deviation (MAD)933
Skewness0.16772863
Sum1.2827847 × 108
Variance1403686
MonotonicityNot monotonic
2024-04-20T22:19:23.977528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
49478 64
 
1.3%
49277 60
 
1.2%
46079 39
 
0.8%
47032 38
 
0.8%
49469 37
 
0.8%
49526 27
 
0.5%
49273 26
 
0.5%
46706 23
 
0.5%
47253 22
 
0.4%
46704 18
 
0.4%
Other values (981) 2334
47.5%
(Missing) 2227
45.3%
ValueCountFrequency (%)
46000 1
 
< 0.1%
46003 1
 
< 0.1%
46004 3
 
0.1%
46006 5
0.1%
46007 1
 
< 0.1%
46008 4
 
0.1%
46013 1
 
< 0.1%
46015 1
 
< 0.1%
46017 2
 
< 0.1%
46018 12
0.2%
ValueCountFrequency (%)
49526 27
0.5%
49525 1
 
< 0.1%
49522 5
 
0.1%
49521 4
 
0.1%
49516 1
 
< 0.1%
49511 2
 
< 0.1%
49510 1
 
< 0.1%
49505 1
 
< 0.1%
49504 1
 
< 0.1%
49501 1
 
< 0.1%

사업장명
Text

Distinct4081
Distinct (%)83.0%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
2024-04-20T22:19:25.171196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length31
Mean length6.014649
Min length1

Characters and Unicode

Total characters29562
Distinct characters800
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3500 ?
Unique (%)71.2%

Sample

1st row한양식품
2nd row(주)로띠번코리아
3rd row주왕산식품
4th row제일식품
5th row서울제분
ValueCountFrequency (%)
주식회사 165
 
3.0%
식품 21
 
0.4%
coffee 17
 
0.3%
도시락 12
 
0.2%
주 10
 
0.2%
하나식품 9
 
0.2%
푸드 9
 
0.2%
food 9
 
0.2%
농업회사법인 9
 
0.2%
제일식품 8
 
0.1%
Other values (4291) 5251
95.1%
2024-04-20T22:19:26.814541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 1684
 
5.7%
품 1444
 
4.9%
주 1226
 
4.1%
) 1139
 
3.9%
( 1134
 
3.8%
산 640
 
2.2%
606
 
2.0%
드 559
 
1.9%
이 552
 
1.9%
푸 498
 
1.7%
Other values (790) 20080
67.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25239
85.4%
Close Punctuation 1139
 
3.9%
Open Punctuation 1134
 
3.8%
Uppercase Letter 825
 
2.8%
Space Separator 606
 
2.0%
Lowercase Letter 381
 
1.3%
Decimal Number 135
 
0.5%
Other Punctuation 91
 
0.3%
Dash Punctuation 7
 
< 0.1%
Other Symbol 3
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 1684
 
6.7%
품 1444
 
5.7%
주 1226
 
4.9%
산 640
 
2.5%
드 559
 
2.2%
이 552
 
2.2%
푸 498
 
2.0%
스 483
 
1.9%
사 473
 
1.9%
리 348
 
1.4%
Other values (719) 17332
68.7%
Uppercase Letter
ValueCountFrequency (%)
F 100
12.1%
O 86
 
10.4%
S 69
 
8.4%
C 67
 
8.1%
E 65
 
7.9%
A 52
 
6.3%
T 44
 
5.3%
R 38
 
4.6%
B 37
 
4.5%
D 36
 
4.4%
Other values (13) 231
28.0%
Lowercase Letter
ValueCountFrequency (%)
e 61
16.0%
o 57
15.0%
a 37
9.7%
n 33
 
8.7%
s 21
 
5.5%
f 20
 
5.2%
t 18
 
4.7%
r 18
 
4.7%
i 15
 
3.9%
d 13
 
3.4%
Other values (13) 88
23.1%
Decimal Number
ValueCountFrequency (%)
2 39
28.9%
1 28
20.7%
0 14
 
10.4%
3 12
 
8.9%
4 10
 
7.4%
9 9
 
6.7%
8 7
 
5.2%
7 7
 
5.2%
5 6
 
4.4%
6 3
 
2.2%
Other Punctuation
ValueCountFrequency (%)
& 49
53.8%
. 32
35.2%
' 3
 
3.3%
· 2
 
2.2%
" 2
 
2.2%
, 1
 
1.1%
! 1
 
1.1%
/ 1
 
1.1%
Close Punctuation
ValueCountFrequency (%)
) 1139
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1134
100.0%
Space Separator
ValueCountFrequency (%)
606
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25231
85.3%
Common 3113
 
10.5%
Latin 1207
 
4.1%
Han 11
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 1684
 
6.7%
품 1444
 
5.7%
주 1226
 
4.9%
산 640
 
2.5%
드 559
 
2.2%
이 552
 
2.2%
푸 498
 
2.0%
스 483
 
1.9%
사 473
 
1.9%
리 348
 
1.4%
Other values (709) 17324
68.7%
Latin
ValueCountFrequency (%)
F 100
 
8.3%
O 86
 
7.1%
S 69
 
5.7%
C 67
 
5.6%
E 65
 
5.4%
e 61
 
5.1%
o 57
 
4.7%
A 52
 
4.3%
T 44
 
3.6%
R 38
 
3.1%
Other values (37) 568
47.1%
Common
ValueCountFrequency (%)
) 1139
36.6%
( 1134
36.4%
606
19.5%
& 49
 
1.6%
2 39
 
1.3%
. 32
 
1.0%
1 28
 
0.9%
0 14
 
0.4%
3 12
 
0.4%
4 10
 
0.3%
Other values (13) 50
 
1.6%
Han
ValueCountFrequency (%)
中 1
9.1%
茶 1
9.1%
見 1
9.1%
院 1
9.1%
手 1
9.1%
功 1
9.1%
若 1
9.1%
情 1
9.1%
水 1
9.1%
父 1
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25228
85.3%
ASCII 4317
 
14.6%
CJK 11
 
< 0.1%
None 5
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 1684
 
6.7%
품 1444
 
5.7%
주 1226
 
4.9%
산 640
 
2.5%
드 559
 
2.2%
이 552
 
2.2%
푸 498
 
2.0%
스 483
 
1.9%
사 473
 
1.9%
리 348
 
1.4%
Other values (708) 17321
68.7%
ASCII
ValueCountFrequency (%)
) 1139
26.4%
( 1134
26.3%
606
14.0%
F 100
 
2.3%
O 86
 
2.0%
S 69
 
1.6%
C 67
 
1.6%
E 65
 
1.5%
e 61
 
1.4%
o 57
 
1.3%
Other values (58) 933
21.6%
None
ValueCountFrequency (%)
㈜ 3
60.0%
· 2
40.0%
CJK
ValueCountFrequency (%)
中 1
9.1%
茶 1
9.1%
見 1
9.1%
院 1
9.1%
手 1
9.1%
功 1
9.1%
若 1
9.1%
情 1
9.1%
水 1
9.1%
父 1
9.1%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

최종수정시점
Real number (ℝ)

Distinct3902
Distinct (%)79.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0114512 × 1013
Minimum1.9990203 × 1013
Maximum2.0210331 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-04-20T22:19:27.241440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990203 × 1013
5-th percentile2.001101 × 1013
Q12.0040602 × 1013
median2.0130328 × 1013
Q32.0180504 × 1013
95-th percentile2.0201112 × 1013
Maximum2.0210331 × 1013
Range2.2012818 × 1011
Interquartile range (IQR)1.3990213 × 1011

Descriptive statistics

Standard deviation7.0472869 × 1010
Coefficient of variation (CV)0.0035035833
Kurtosis-1.5017825
Mean2.0114512 × 1013
Median Absolute Deviation (MAD)6.0392015 × 1010
Skewness-0.22639504
Sum9.8862829 × 1016
Variance4.9664253 × 1021
MonotonicityNot monotonic
2024-04-20T22:19:27.689847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20020612000000 58
 
1.2%
20060428000000 50
 
1.0%
20020225000000 45
 
0.9%
20010731000000 42
 
0.9%
20020715000000 36
 
0.7%
20020305000000 35
 
0.7%
20010728000000 34
 
0.7%
20020527000000 33
 
0.7%
20031204000000 27
 
0.5%
20020829000000 25
 
0.5%
Other values (3892) 4530
92.2%
ValueCountFrequency (%)
19990203000000 7
0.1%
19990205000000 1
 
< 0.1%
19990218000000 5
0.1%
19990219000000 2
 
< 0.1%
19990310000000 1
 
< 0.1%
19990312000000 1
 
< 0.1%
19990316000000 10
0.2%
19990318000000 12
0.2%
19990324000000 1
 
< 0.1%
19990329000000 4
 
0.1%
ValueCountFrequency (%)
20210331180924 1
< 0.1%
20210330161956 1
< 0.1%
20210330155639 1
< 0.1%
20210330110422 1
< 0.1%
20210329160308 1
< 0.1%
20210329133837 1
< 0.1%
20210329101733 1
< 0.1%
20210326150801 1
< 0.1%
20210326104038 1
< 0.1%
20210325165925 1
< 0.1%

데이터갱신구분
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
I
3995 
U
920 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 3995
81.3%
U 920
 
18.7%

Length

2024-04-20T22:19:28.100292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T22:19:28.360152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 3995
81.3%
u 920
 
18.7%

데이터갱신일자
Date

Distinct631
Distinct (%)12.8%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
Minimum2018-08-31 23:59:59
Maximum2021-04-02 02:40:00
2024-04-20T22:19:28.634179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T22:19:29.096269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
식품제조가공업
3719 
기타 식품제조가공업
1001 
<NA>
 
175
도시락제조업
 
18
분식
 
1

Length

Max length10
Median length7
Mean length7.4990844
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 3719
75.7%
기타 식품제조가공업 1001
 
20.4%
<NA> 175
 
3.6%
도시락제조업 18
 
0.4%
분식 1
 
< 0.1%
주류제조업 1
 
< 0.1%

Length

2024-04-20T22:19:29.570222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T22:19:29.936270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 4720
79.8%
기타 1001
 
16.9%
na 175
 
3.0%
도시락제조업 18
 
0.3%
분식 1
 
< 0.1%
주류제조업 1
 
< 0.1%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct3474
Distinct (%)74.5%
Missing249
Missing (%)5.1%
Infinite0
Infinite (%)0.0%
Mean386968.71
Minimum362913.86
Maximum409357.26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-04-20T22:19:30.301083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum362913.86
5-th percentile377379.22
Q1380874.97
median386942.69
Q3391698.03
95-th percentile401557.32
Maximum409357.26
Range46443.402
Interquartile range (IQR)10823.057

Descriptive statistics

Standard deviation7415.4946
Coefficient of variation (CV)0.019163034
Kurtosis0.0056760637
Mean386968.71
Median Absolute Deviation (MAD)5510.1981
Skewness0.32784412
Sum1.805596 × 109
Variance54989561
MonotonicityNot monotonic
2024-04-20T22:19:30.619887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
383449.669961635 53
 
1.1%
378968.772298381 35
 
0.7%
393233.931123062 26
 
0.5%
382570.401135476 20
 
0.4%
387528.393422261 15
 
0.3%
402750.992777099 13
 
0.3%
402792.323019555 12
 
0.2%
378428.966209849 12
 
0.2%
379815.215807943 12
 
0.2%
383539.602429996 11
 
0.2%
Other values (3464) 4457
90.7%
(Missing) 249
 
5.1%
ValueCountFrequency (%)
362913.855865642 1
< 0.1%
364635.160006689 1
< 0.1%
365083.695260416 1
< 0.1%
366344.108366431 1
< 0.1%
367098.648578583 1
< 0.1%
367302.077334803 1
< 0.1%
367390.559894293 1
< 0.1%
367423.884531247 1
< 0.1%
367815.737104513 1
< 0.1%
367820.128988913 1
< 0.1%
ValueCountFrequency (%)
409357.257713329 2
< 0.1%
409147.720337583 1
< 0.1%
407919.897384557 1
< 0.1%
407871.508884898 2
< 0.1%
407820.16806719 1
< 0.1%
407703.086321502 1
< 0.1%
407541.852777801 1
< 0.1%
407432.77113005 1
< 0.1%
407418.648415535 1
< 0.1%
407233.962652867 1
< 0.1%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct3474
Distinct (%)74.5%
Missing249
Missing (%)5.1%
Infinite0
Infinite (%)0.0%
Mean186678
Minimum170926.8
Maximum211328.08
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-04-20T22:19:31.097915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum170926.8
5-th percentile176356.96
Q1180265.69
median186998.39
Q3191444.9
95-th percentile198366.67
Maximum211328.08
Range40401.285
Interquartile range (IQR)11179.21

Descriptive statistics

Standard deviation7167.4745
Coefficient of variation (CV)0.038394853
Kurtosis-0.18265561
Mean186678
Median Absolute Deviation (MAD)5223.0676
Skewness0.32997185
Sum8.7103956 × 108
Variance51372691
MonotonicityNot monotonic
2024-04-20T22:19:31.571404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
174683.069423816 53
 
1.1%
182801.31604478 35
 
0.7%
192684.487637586 26
 
0.5%
187570.045156033 19
 
0.4%
186694.666831446 15
 
0.3%
194137.607655897 13
 
0.3%
199422.531912758 12
 
0.2%
177298.418573324 12
 
0.2%
177453.67734986 12
 
0.2%
181864.088029051 11
 
0.2%
Other values (3464) 4458
90.7%
(Missing) 249
 
5.1%
ValueCountFrequency (%)
170926.797137097 1
 
< 0.1%
174096.498143437 1
 
< 0.1%
174156.617297535 1
 
< 0.1%
174213.492106852 1
 
< 0.1%
174289.976688419 2
 
< 0.1%
174380.190006345 1
 
< 0.1%
174415.425547526 10
0.2%
174419.270504403 4
 
0.1%
174422.347875421 1
 
< 0.1%
174428.418993288 4
 
0.1%
ValueCountFrequency (%)
211328.08235601 1
< 0.1%
210855.07033937 1
< 0.1%
210458.376643536 2
< 0.1%
210346.680159948 1
< 0.1%
210004.830136767 1
< 0.1%
209900.932326718 1
< 0.1%
209890.530128105 1
< 0.1%
209640.461628918 1
< 0.1%
209337.11910772 1
< 0.1%
209321.781147486 1
< 0.1%

위생업태명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
식품제조가공업
3729 
기타 식품제조가공업
991 
<NA>
 
175
도시락제조업
 
18
분식
 
1

Length

Max length10
Median length7
Mean length7.4929807
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 3729
75.9%
기타 식품제조가공업 991
 
20.2%
<NA> 175
 
3.6%
도시락제조업 18
 
0.4%
분식 1
 
< 0.1%
주류제조업 1
 
< 0.1%

Length

2024-04-20T22:19:32.049103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T22:19:32.380131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 4720
79.9%
기타 991
 
16.8%
na 175
 
3.0%
도시락제조업 18
 
0.3%
분식 1
 
< 0.1%
주류제조업 1
 
< 0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
<NA>
4035 
0
816 
1
 
38
2
 
22
3
 
3

Length

Max length4
Median length4
Mean length3.4628688
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4035
82.1%
0 816
 
16.6%
1 38
 
0.8%
2 22
 
0.4%
3 3
 
0.1%
4 1
 
< 0.1%

Length

2024-04-20T22:19:32.605182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T22:19:32.820608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4035
82.1%
0 816
 
16.6%
1 38
 
0.8%
2 22
 
0.4%
3 3
 
0.1%
4 1
 
< 0.1%

여성종사자수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
<NA>
4036 
0
816 
1
 
42
2
 
18
3
 
3

Length

Max length4
Median length4
Mean length3.4634791
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4036
82.1%
0 816
 
16.6%
1 42
 
0.9%
2 18
 
0.4%
3 3
 
0.1%

Length

2024-04-20T22:19:33.249936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T22:19:33.588340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4036
82.1%
0 816
 
16.6%
1 42
 
0.9%
2 18
 
0.4%
3 3
 
0.1%

영업장주변구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
<NA>
3400 
기타
1416 
주택가주변
 
75
아파트지역
 
11
학교정화(상대)
 
6
Other values (3)
 
7

Length

Max length8
Median length4
Mean length3.4514751
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3400
69.2%
기타 1416
28.8%
주택가주변 75
 
1.5%
아파트지역 11
 
0.2%
학교정화(상대) 6
 
0.1%
유흥업소밀집지역 4
 
0.1%
결혼예식장주변 2
 
< 0.1%
학교정화(절대) 1
 
< 0.1%

Length

2024-04-20T22:19:33.980015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T22:19:34.329295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3400
69.2%
기타 1416
28.8%
주택가주변 75
 
1.5%
아파트지역 11
 
0.2%
학교정화(상대 6
 
0.1%
유흥업소밀집지역 4
 
0.1%
결혼예식장주변 2
 
< 0.1%
학교정화(절대 1
 
< 0.1%

등급구분명
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
<NA>
3400 
기타
1402 
자율
 
112
지도
 
1

Length

Max length4
Median length4
Mean length3.3835198
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3400
69.2%
기타 1402
28.5%
자율 112
 
2.3%
지도 1
 
< 0.1%

Length

2024-04-20T22:19:34.656106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T22:19:34.941045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3400
69.2%
기타 1402
28.5%
자율 112
 
2.3%
지도 1
 
< 0.1%

급수시설구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
<NA>
3032 
상수도전용
1840 
지하수전용
 
28
상수도(음용)지하수(주방용)겸용
 
10
간이상수도
 
4

Length

Max length19
Median length4
Mean length4.4103764
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3032
61.7%
상수도전용 1840
37.4%
지하수전용 28
 
0.6%
상수도(음용)지하수(주방용)겸용 10
 
0.2%
간이상수도 4
 
0.1%
전용상수도(특정시설의 자가용 수도) 1
 
< 0.1%

Length

2024-04-20T22:19:35.325207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T22:19:35.666077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3032
61.7%
상수도전용 1840
37.4%
지하수전용 28
 
0.6%
상수도(음용)지하수(주방용)겸용 10
 
0.2%
간이상수도 4
 
0.1%
전용상수도(특정시설의 1
 
< 0.1%
자가용 1
 
< 0.1%
수도 1
 
< 0.1%

총종업원수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4915
Missing (%)100.0%
Memory size43.3 KiB

본사종업원수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct14
Distinct (%)0.4%
Missing1800
Missing (%)36.6%
Infinite0
Infinite (%)0.0%
Mean28.78427
Minimum0
Maximum89417
Zeros3075
Zeros (%)62.6%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-04-20T22:19:35.937630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum89417
Range89417
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1602.1049
Coefficient of variation (CV)55.659042
Kurtosis3114.9926
Mean28.78427
Median Absolute Deviation (MAD)0
Skewness55.812085
Sum89663
Variance2566740.1
MonotonicityNot monotonic
2024-04-20T22:19:36.121974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 3075
62.6%
1 22
 
0.4%
2 6
 
0.1%
3 2
 
< 0.1%
19 1
 
< 0.1%
15 1
 
< 0.1%
31 1
 
< 0.1%
89417 1
 
< 0.1%
83 1
 
< 0.1%
9 1
 
< 0.1%
Other values (4) 4
 
0.1%
(Missing) 1800
36.6%
ValueCountFrequency (%)
0 3075
62.6%
1 22
 
0.4%
2 6
 
0.1%
3 2
 
< 0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%
9 1
 
< 0.1%
12 1
 
< 0.1%
15 1
 
< 0.1%
19 1
 
< 0.1%
ValueCountFrequency (%)
89417 1
< 0.1%
83 1
< 0.1%
31 1
< 0.1%
28 1
< 0.1%
19 1
< 0.1%
15 1
< 0.1%
12 1
< 0.1%
9 1
< 0.1%
5 1
< 0.1%
4 1
< 0.1%

공장사무직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct16
Distinct (%)0.5%
Missing1783
Missing (%)36.3%
Infinite0
Infinite (%)0.0%
Mean0.33429119
Minimum0
Maximum47
Zeros2800
Zeros (%)57.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-04-20T22:19:36.314342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum47
Range47
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.7009773
Coefficient of variation (CV)5.0883104
Kurtosis340.59489
Mean0.33429119
Median Absolute Deviation (MAD)0
Skewness15.506343
Sum1047
Variance2.8933239
MonotonicityNot monotonic
2024-04-20T22:19:36.579565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 2800
57.0%
3 167
 
3.4%
1 104
 
2.1%
2 19
 
0.4%
4 12
 
0.2%
8 7
 
0.1%
7 6
 
0.1%
5 4
 
0.1%
9 3
 
0.1%
6 3
 
0.1%
Other values (6) 7
 
0.1%
(Missing) 1783
36.3%
ValueCountFrequency (%)
0 2800
57.0%
1 104
 
2.1%
2 19
 
0.4%
3 167
 
3.4%
4 12
 
0.2%
5 4
 
0.1%
6 3
 
0.1%
7 6
 
0.1%
8 7
 
0.1%
9 3
 
0.1%
ValueCountFrequency (%)
47 1
 
< 0.1%
38 1
 
< 0.1%
36 1
 
< 0.1%
22 2
 
< 0.1%
18 1
 
< 0.1%
10 1
 
< 0.1%
9 3
0.1%
8 7
0.1%
7 6
0.1%
6 3
0.1%

공장판매직종업원수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct9
Distinct (%)0.3%
Missing1800
Missing (%)36.6%
Infinite0
Infinite (%)0.0%
Mean0.027608347
Minimum0
Maximum15
Zeros3080
Zeros (%)62.7%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-04-20T22:19:36.839788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum15
Range15
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.39408996
Coefficient of variation (CV)14.274305
Kurtosis781.33525
Mean0.027608347
Median Absolute Deviation (MAD)0
Skewness24.78021
Sum86
Variance0.1553069
MonotonicityNot monotonic
2024-04-20T22:19:37.035666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 3080
62.7%
1 21
 
0.4%
2 5
 
0.1%
4 3
 
0.1%
5 2
 
< 0.1%
7 1
 
< 0.1%
15 1
 
< 0.1%
8 1
 
< 0.1%
3 1
 
< 0.1%
(Missing) 1800
36.6%
ValueCountFrequency (%)
0 3080
62.7%
1 21
 
0.4%
2 5
 
0.1%
3 1
 
< 0.1%
4 3
 
0.1%
5 2
 
< 0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%
15 1
 
< 0.1%
ValueCountFrequency (%)
15 1
 
< 0.1%
8 1
 
< 0.1%
7 1
 
< 0.1%
5 2
 
< 0.1%
4 3
 
0.1%
3 1
 
< 0.1%
2 5
 
0.1%
1 21
 
0.4%
0 3080
62.7%

공장생산직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct41
Distinct (%)1.3%
Missing1749
Missing (%)35.6%
Infinite0
Infinite (%)0.0%
Mean1.2842704
Minimum0
Maximum158
Zeros2547
Zeros (%)51.8%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-04-20T22:19:37.261437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile8
Maximum158
Range158
Interquartile range (IQR)0

Descriptive statistics

Standard deviation6.192646
Coefficient of variation (CV)4.8219177
Kurtosis293.37372
Mean1.2842704
Median Absolute Deviation (MAD)0
Skewness14.67281
Sum4066
Variance38.348865
MonotonicityNot monotonic
2024-04-20T22:19:37.526975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
0 2547
51.8%
1 180
 
3.7%
8 162
 
3.3%
2 82
 
1.7%
3 49
 
1.0%
4 34
 
0.7%
5 26
 
0.5%
6 15
 
0.3%
10 9
 
0.2%
7 8
 
0.2%
Other values (31) 54
 
1.1%
(Missing) 1749
35.6%
ValueCountFrequency (%)
0 2547
51.8%
1 180
 
3.7%
2 82
 
1.7%
3 49
 
1.0%
4 34
 
0.7%
5 26
 
0.5%
6 15
 
0.3%
7 8
 
0.2%
8 162
 
3.3%
9 4
 
0.1%
ValueCountFrequency (%)
158 1
< 0.1%
139 1
< 0.1%
127 1
< 0.1%
96 1
< 0.1%
70 2
< 0.1%
52 1
< 0.1%
51 1
< 0.1%
46 1
< 0.1%
43 2
< 0.1%
40 2
< 0.1%

건물소유구분명
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.5 KiB
<NA>
3118 
임대
1048 
자가
749 

Length

Max length4
Median length4
Mean length3.2687691
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3118
63.4%
임대 1048
 
21.3%
자가 749
 
15.2%

Length

2024-04-20T22:19:37.790779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T22:19:37.995208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3118
63.4%
임대 1048
 
21.3%
자가 749
 
15.2%

보증액
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)2.9%
Missing4601
Missing (%)93.6%
Infinite0
Infinite (%)0.0%
Mean496207.01
Minimum0
Maximum96800000
Zeros306
Zeros (%)6.2%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-04-20T22:19:38.163712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum96800000
Range96800000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5730342.6
Coefficient of variation (CV)11.54829
Kurtosis258.01544
Mean496207.01
Median Absolute Deviation (MAD)0
Skewness15.581678
Sum1.55809 × 108
Variance3.2836826 × 1013
MonotonicityNot monotonic
2024-04-20T22:19:38.478602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 306
 
6.2%
96800000 1
 
< 0.1%
25000000 1
 
< 0.1%
9000 1
 
< 0.1%
5000000 1
 
< 0.1%
1000000 1
 
< 0.1%
10000000 1
 
< 0.1%
3000000 1
 
< 0.1%
15000000 1
 
< 0.1%
(Missing) 4601
93.6%
ValueCountFrequency (%)
0 306
6.2%
9000 1
 
< 0.1%
1000000 1
 
< 0.1%
3000000 1
 
< 0.1%
5000000 1
 
< 0.1%
10000000 1
 
< 0.1%
15000000 1
 
< 0.1%
25000000 1
 
< 0.1%
96800000 1
 
< 0.1%
ValueCountFrequency (%)
96800000 1
 
< 0.1%
25000000 1
 
< 0.1%
15000000 1
 
< 0.1%
10000000 1
 
< 0.1%
5000000 1
 
< 0.1%
3000000 1
 
< 0.1%
1000000 1
 
< 0.1%
9000 1
 
< 0.1%
0 306
6.2%

월세액
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)2.9%
Missing4601
Missing (%)93.6%
Infinite0
Infinite (%)0.0%
Mean35030.955
Minimum0
Maximum8349000
Zeros306
Zeros (%)6.2%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-04-20T22:19:38.789073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum8349000
Range8349000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation475780.75
Coefficient of variation (CV)13.581723
Kurtosis300.66364
Mean35030.955
Median Absolute Deviation (MAD)0
Skewness17.1805
Sum10999720
Variance2.2636732 × 1011
MonotonicityNot monotonic
2024-04-20T22:19:38.983778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 306
 
6.2%
8349000 1
 
< 0.1%
500000 1
 
< 0.1%
690 1
 
< 0.1%
400000 1
 
< 0.1%
800000 1
 
< 0.1%
600000 1
 
< 0.1%
350000 1
 
< 0.1%
30 1
 
< 0.1%
(Missing) 4601
93.6%
ValueCountFrequency (%)
0 306
6.2%
30 1
 
< 0.1%
690 1
 
< 0.1%
350000 1
 
< 0.1%
400000 1
 
< 0.1%
500000 1
 
< 0.1%
600000 1
 
< 0.1%
800000 1
 
< 0.1%
8349000 1
 
< 0.1%
ValueCountFrequency (%)
8349000 1
 
< 0.1%
800000 1
 
< 0.1%
600000 1
 
< 0.1%
500000 1
 
< 0.1%
400000 1
 
< 0.1%
350000 1
 
< 0.1%
690 1
 
< 0.1%
30 1
 
< 0.1%
0 306
6.2%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
False
4915 
ValueCountFrequency (%)
False 4915
100.0%
2024-04-20T22:19:39.141691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

ZEROS 

Distinct869
Distinct (%)17.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.669896
Minimum0
Maximum4977.66
Zeros3736
Zeros (%)76.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-04-20T22:19:39.326268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile97.984
Maximum4977.66
Range4977.66
Interquartile range (IQR)0

Descriptive statistics

Standard deviation203.1124
Coefficient of variation (CV)7.0845182
Kurtosis298.12303
Mean28.669896
Median Absolute Deviation (MAD)0
Skewness15.747605
Sum140912.54
Variance41254.648
MonotonicityNot monotonic
2024-04-20T22:19:39.683167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3736
76.0%
6.0 13
 
0.3%
3.0 11
 
0.2%
288.36 11
 
0.2%
205.74 11
 
0.2%
5.0 9
 
0.2%
10.8 8
 
0.2%
4.0 8
 
0.2%
8.0 7
 
0.1%
4.2 7
 
0.1%
Other values (859) 1094
 
22.3%
ValueCountFrequency (%)
0.0 3736
76.0%
0.7 1
 
< 0.1%
0.8 1
 
< 0.1%
1.0 2
 
< 0.1%
1.01 1
 
< 0.1%
1.07 1
 
< 0.1%
1.2 1
 
< 0.1%
1.21 1
 
< 0.1%
1.3 1
 
< 0.1%
1.35 1
 
< 0.1%
ValueCountFrequency (%)
4977.66 1
< 0.1%
4936.96 1
< 0.1%
4356.67 1
< 0.1%
4016.48 1
< 0.1%
3505.99 1
< 0.1%
3428.82 1
< 0.1%
3093.38 1
< 0.1%
3015.05 1
< 0.1%
2914.4 1
< 0.1%
2880.26 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4915
Missing (%)100.0%
Memory size43.3 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4915
Missing (%)100.0%
Memory size43.3 KiB

홈페이지
Text

MISSING 

Distinct73
Distinct (%)93.6%
Missing4837
Missing (%)98.4%
Memory size38.5 KiB
2024-04-20T22:19:40.730330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length22
Mean length18.25641
Min length1

Characters and Unicode

Total characters1424
Distinct characters41
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique68 ?
Unique (%)87.2%

Sample

1st rowpeopales2015@naver,com
2nd rowtofeelsm@gmail.com
3rd rowsj7040577@naver.com
4th rowmonarizamk@naver.com
5th rowjaijain@nate.com
ValueCountFrequency (%)
happyrak82@hamail.net 2
 
2.5%
rbhcom@naver.com 2
 
2.5%
dlatl3552@nate.com 2
 
2.5%
jaijain@nate.com 2
 
2.5%
inmyport@naver.com 2
 
2.5%
sj201073@naver.com 1
 
1.2%
dia37@naver.com 1
 
1.2%
www.gaemizib.com 1
 
1.2%
jyino88@naver.com 1
 
1.2%
gontrangaeundae@gontrancherrier.kr 1
 
1.2%
Other values (65) 65
81.2%
2024-04-20T22:19:42.318709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 120
 
8.4%
m 108
 
7.6%
o 108
 
7.6%
n 106
 
7.4%
e 100
 
7.0%
c 79
 
5.5%
. 75
 
5.3%
@ 74
 
5.2%
r 72
 
5.1%
i 51
 
3.6%
Other values (31) 531
37.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1089
76.5%
Decimal Number 178
 
12.5%
Other Punctuation 153
 
10.7%
Space Separator 2
 
0.1%
Dash Punctuation 1
 
0.1%
Other Letter 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 120
11.0%
m 108
9.9%
o 108
9.9%
n 106
9.7%
e 100
 
9.2%
c 79
 
7.3%
r 72
 
6.6%
i 51
 
4.7%
v 47
 
4.3%
t 43
 
3.9%
Other values (15) 255
23.4%
Decimal Number
ValueCountFrequency (%)
0 30
16.9%
2 25
14.0%
1 25
14.0%
5 22
12.4%
3 20
11.2%
7 15
8.4%
4 13
7.3%
9 12
 
6.7%
8 9
 
5.1%
6 7
 
3.9%
Other Punctuation
ValueCountFrequency (%)
. 75
49.0%
@ 74
48.4%
, 4
 
2.6%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Letter
ValueCountFrequency (%)
ㅍ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1089
76.5%
Common 334
 
23.5%
Hangul 1
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 120
11.0%
m 108
9.9%
o 108
9.9%
n 106
9.7%
e 100
 
9.2%
c 79
 
7.3%
r 72
 
6.6%
i 51
 
4.7%
v 47
 
4.3%
t 43
 
3.9%
Other values (15) 255
23.4%
Common
ValueCountFrequency (%)
. 75
22.5%
@ 74
22.2%
0 30
 
9.0%
2 25
 
7.5%
1 25
 
7.5%
5 22
 
6.6%
3 20
 
6.0%
7 15
 
4.5%
4 13
 
3.9%
9 12
 
3.6%
Other values (5) 23
 
6.9%
Hangul
ValueCountFrequency (%)
ㅍ 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1423
99.9%
Compat Jamo 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 120
 
8.4%
m 108
 
7.6%
o 108
 
7.6%
n 106
 
7.4%
e 100
 
7.0%
c 79
 
5.6%
. 75
 
5.3%
@ 74
 
5.2%
r 72
 
5.1%
i 51
 
3.6%
Other values (30) 530
37.2%
Compat Jamo
ValueCountFrequency (%)
ㅍ 1
100.0%

Unnamed: 47
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4915
Missing (%)100.0%
Memory size43.3 KiB

Sample

번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지Unnamed: 47
01식품제조가공업07_22_11_P33900003390000-106-2002-0000319941107<NA>1영업/정상1영업<NA><NA><NA><NA>051 31766771,480.80617843부산광역시 사상구 학장동 748-7번지부산광역시 사상구 학장로83번길 34 (학장동)47026한양식품20190628112834U2019-06-30 02:40:00.0식품제조가공업379973.954136184128.731833식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
12식품제조가공업07_22_11_P33900003390000-106-2013-0000920131024<NA>1영업/정상1영업<NA><NA><NA><NA><NA>421.25617800부산광역시 사상구 감전동 133-7번지부산광역시 사상구 새벽시장로133번길 11, 1~2층 (감전동)46984(주)로띠번코리아20190115105516U2019-01-17 02:40:00.0식품제조가공업381095.335708185733.686814식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0000자가<NA><NA>N47.0<NA><NA><NA><NA>
23식품제조가공업07_22_11_P33900003390000-106-2000-0088519961118<NA>1영업/정상1영업<NA><NA><NA><NA>051 328235827.50617803부산광역시 사상구 감전동 143-16번지부산광역시 사상구 새벽로 141 (감전동)46988주왕산식품20171205114341I2018-08-31 23:59:59.0식품제조가공업380496.343014185656.394047식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
34식품제조가공업07_22_11_P33900003390000-106-1997-0028019970212<NA>1영업/정상1영업<NA><NA><NA><NA>051 30132691,251.05617826부산광역시 사상구 삼락동 390-5번지부산광역시 사상구 낙동대로1348번길 54 (삼락동)46909제일식품20200103170619U2020-01-05 02:40:00.0식품제조가공업380216.408114188521.903319식품제조가공업00기타기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
45식품제조가공업07_22_11_P33900003390000-106-1997-0058119970425<NA>1영업/정상1영업<NA><NA><NA><NA>051311 5930293.00617841부산광역시 사상구 학장동 226-9번지부산광역시 사상구 가야대로104번길 36 (학장동)47019서울제분20160318135257I2018-08-31 23:59:59.0식품제조가공업380661.678929185070.84027식품제조가공업00기타기타<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
56식품제조가공업07_22_11_P33900003390000-106-1997-0077219971125<NA>1영업/정상1영업<NA><NA><NA><NA>051 301 6297643.41617826부산광역시 사상구 삼락동 392-8번지부산광역시 사상구 낙동대로1330번길 37 (삼락동)46911금강물산20160318130945I2018-08-31 23:59:59.0식품제조가공업380138.396713188404.560034식품제조가공업00기타기타상수도전용<NA>0000<NA><NA><NA>N5.72<NA><NA><NA><NA>
67식품제조가공업07_22_11_P33900003390000-106-2000-0072519980406<NA>1영업/정상1영업<NA><NA><NA><NA>051 3028682299.60617825부산광역시 사상구 삼락동 51-8번지부산광역시 사상구 삼락천로 325 (삼락동)46901산해식품20160318134829I2018-08-31 23:59:59.0식품제조가공업380939.951092190257.976351식품제조가공업<NA><NA>기타기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
78식품제조가공업07_22_11_P33300003330000-106-2016-0000220160224<NA>1영업/정상1영업<NA><NA><NA><NA>051 782 201582.38612050부산광역시 해운대구 재송동 1221번지부산광역시 해운대구 센텀동로 90, 2층 215호 (재송동, 센텀필2관)48059피플스컴퍼니(PEOPLESCOMPANY)20171219094300I2018-08-31 23:59:59.0기타 식품제조가공업393720.031658188352.780012기타 식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N10.11<NA><NA>peopales2015@naver,com<NA>
89식품제조가공업07_22_11_P33200003320000-106-2009-0000920090320<NA>1영업/정상1영업<NA><NA><NA><NA>051 633 6634498.10616827부산광역시 북구 만덕동 381-1번지 (1,2,3층)부산광역시 북구 중리로 31, 1,2,3층 (만덕동)46607맘스쌀과자20170105101342I2018-08-31 23:59:59.0식품제조가공업385724.99879192265.387957식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N498.1<NA><NA><NA><NA>
910식품제조가공업07_22_11_P33300003330000-106-2016-0000520160624<NA>1영업/정상1영업<NA><NA><NA><NA><NA>59.77612857부산광역시 해운대구 반여동 660-0부산광역시 해운대구 삼어로133번가길 19-28, 1층 (반여동)48044우림푸드20210330110422U2021-04-01 02:40:00.0기타 식품제조가공업392747.410672192177.85365기타 식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0102임대<NA><NA>N2.03<NA><NA><NA><NA>
번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지Unnamed: 47
49054906식품제조가공업07_22_11_P34000003400000-106-2019-0000120190102<NA>3폐업2폐업20200207<NA><NA><NA>051 727 471729.40619911부산광역시 기장군 일광면 동백리 449번지부산광역시 기장군 일광면 문오성길 22, 1층46041주식회사 헤이든20200207143351U2020-02-09 02:40:00.0기타 식품제조가공업405241.716598200470.1192기타 식품제조가공업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA><NA>
49064907식품제조가공업07_22_11_P33500003350000-106-2018-0001320181107<NA>3폐업2폐업20190220<NA><NA><NA>051803589580.50609809부산광역시 금정구 금사동 115-6번지부산광역시 금정구 반송로490번길 26-9 (금사동)46334상도유통20190220170749U2019-02-22 02:40:00.0기타 식품제조가공업392700.863498192703.206679기타 식품제조가공업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
49074908식품제조가공업07_22_11_P33300003330000-106-2018-0002320181120<NA>3폐업2폐업20201007<NA><NA><NA>051 523 5501291.16612070부산광역시 해운대구 석대동 638부산광역시 해운대구 반송로525번길 15, 해운대타워 106호 (석대동)48002(주)한상푸드20201007090942U2020-10-09 02:40:00.0기타 식품제조가공업392978.97572193113.409233기타 식품제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
49084909식품제조가공업07_22_11_P33000003300000-106-2018-0000820181127<NA>3폐업2폐업20200701<NA><NA><NA><NA>135.70607803부산광역시 동래구 명륜동 721-19부산광역시 동래구 온천천로 71, 2층 (명륜동)47741라페니체 커피로스팅20200701094136U2020-07-03 02:40:00.0기타 식품제조가공업389379.256261192391.175877기타 식품제조가공업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N78.0<NA><NA><NA><NA>
49094910식품제조가공업07_22_11_P33100003310000-106-2018-0001320181210<NA>3폐업2폐업20200814<NA><NA><NA>0707777828684.96608804부산광역시 남구 대연동 54-5 103호부산광역시 남구 수영로 324, 1층 103호 (대연동)48508교토마블 부산점20200814172108U2020-08-16 02:40:00.0기타 식품제조가공업391472.555827184076.524057기타 식품제조가공업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N21.92<NA><NA><NA><NA>
49104911식품제조가공업07_22_11_P32900003290000-106-2018-0001720181217<NA>3폐업2폐업20190627<NA><NA><NA><NA>199.68614873부산광역시 부산진구 초읍동 230-12번지 초읍동 복합상가부산광역시 부산진구 초읍천로 113-3, 초읍동 복합상가 7층 (초읍동)47100황세란유인균발효연구원20190627153551U2019-06-29 02:40:00.0기타 식품제조가공업386325.470803188899.571054기타 식품제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N10.2<NA><NA><NA><NA>
49114912식품제조가공업07_22_11_P33300003330000-106-2018-0002620181220<NA>3폐업2폐업20190502<NA><NA><NA><NA>29.66612824부산광역시 해운대구 우동 1432번지 현대베네시티아파트부산광역시 해운대구 해운대해변로 163, 상가동 103,104호 (우동, 현대베네시티아파트)48091거대곰탕20190502103306U2019-05-04 02:40:00.0기타 식품제조가공업395881.345449186497.871164기타 식품제조가공업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
49124913식품제조가공업07_22_11_P33000003300000-106-2018-0001020181207<NA>3폐업2폐업20200914<NA><NA><NA>051 6238222139.68607816부산광역시 동래구 사직동 136-5부산광역시 동래구 여고로63번길 86 (사직동)47841조아컴퍼니20200914113108U2020-09-16 02:40:00.0기타 식품제조가공업388408.660844190939.823684기타 식품제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N74.87<NA><NA><NA><NA>
49134914식품제조가공업07_22_11_P33300003330000-106-2018-0002420181211<NA>3폐업2폐업20191212<NA><NA><NA>051731 522545.43612846부산광역시 해운대구 중동 149-1번지 해운대메트로하이츠부산광역시 해운대구 좌동순환로8번길 78, B1층 14호 (중동, 해운대메트로하이츠)48082더데이지20191212114334U2019-12-14 02:40:00.0기타 식품제조가공업397663.103737187763.906198기타 식품제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
49144915식품제조가공업07_22_11_P33800003380000-106-2021-0000120210126<NA>3폐업2폐업20210322<NA><NA><NA><NA>69.80613832부산광역시 수영구 수영동 491-33부산광역시 수영구 구락로43번길 28, 1층 (수영동)48225배가푸드20210322151116U2021-03-24 02:40:00.0기타 식품제조가공업392890.650967187809.674629기타 식품제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N19.5<NA><NA><NA><NA>