Overview

Dataset statistics

Number of variables48
Number of observations4929
Missing cells68665
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

Description2021-06-01
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 (62.0%)Imbalance
위생업태명 is highly imbalanced (62.1%)Imbalance
남성종사자수 is highly imbalanced (70.6%)Imbalance
여성종사자수 is highly imbalanced (67.4%)Imbalance
영업장주변구분명 is highly imbalanced (65.9%)Imbalance
급수시설구분명 is highly imbalanced (60.1%)Imbalance
인허가취소일자 has 4929 (100.0%) missing valuesMissing
폐업일자 has 1375 (27.9%) missing valuesMissing
휴업시작일자 has 4929 (100.0%) missing valuesMissing
휴업종료일자 has 4929 (100.0%) missing valuesMissing
재개업일자 has 4929 (100.0%) missing valuesMissing
소재지전화 has 977 (19.8%) missing valuesMissing
소재지면적 has 641 (13.0%) missing valuesMissing
소재지우편번호 has 98 (2.0%) missing valuesMissing
도로명전체주소 has 2179 (44.2%) missing valuesMissing
도로명우편번호 has 2227 (45.2%) missing valuesMissing
좌표정보(x) has 249 (5.1%) missing valuesMissing
좌표정보(y) has 249 (5.1%) missing valuesMissing
총종업원수 has 4929 (100.0%) missing valuesMissing
본사종업원수 has 1805 (36.6%) missing valuesMissing
공장사무직종업원수 has 1788 (36.3%) missing valuesMissing
공장판매직종업원수 has 1805 (36.6%) missing valuesMissing
공장생산직종업원수 has 1754 (35.6%) missing valuesMissing
보증액 has 4615 (93.6%) missing valuesMissing
월세액 has 4615 (93.6%) missing valuesMissing
전통업소지정번호 has 4929 (100.0%) missing valuesMissing
전통업소주된음식 has 4929 (100.0%) missing valuesMissing
홈페이지 has 4851 (98.4%) missing valuesMissing
Unnamed: 47 has 4929 (100.0%) missing valuesMissing
폐업일자 is highly skewed (γ1 = -37.13387702)Skewed
본사종업원수 is highly skewed (γ1 = 55.89265447)Skewed
공장판매직종업원수 is highly skewed (γ1 = 24.81602729)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 3084 (62.6%) zerosZeros
공장사무직종업원수 has 2809 (57.0%) zerosZeros
공장판매직종업원수 has 3089 (62.7%) zerosZeros
공장생산직종업원수 has 2555 (51.8%) zerosZeros
보증액 has 306 (6.2%) zerosZeros
월세액 has 306 (6.2%) zerosZeros
시설총규모 has 3738 (75.8%) zerosZeros

Reproduction

Analysis started2024-04-20 13:21:26.304424
Analysis finished2024-04-20 13:21:28.837759
Duration2.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct4929
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2465
Minimum1
Maximum4929
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-20T22:21:29.039370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile247.4
Q11233
median2465
Q33697
95-th percentile4682.6
Maximum4929
Range4928
Interquartile range (IQR)2464

Descriptive statistics

Standard deviation1423.0241
Coefficient of variation (CV)0.57729171
Kurtosis-1.2
Mean2465
Median Absolute Deviation (MAD)1232
Skewness0
Sum12149985
Variance2024997.5
MonotonicityStrictly increasing
2024-04-20T22:21:29.473779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
3285 1
 
< 0.1%
3292 1
 
< 0.1%
3291 1
 
< 0.1%
3290 1
 
< 0.1%
3289 1
 
< 0.1%
3288 1
 
< 0.1%
3287 1
 
< 0.1%
3286 1
 
< 0.1%
3284 1
 
< 0.1%
Other values (4919) 4919
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 (%)
4929 1
< 0.1%
4928 1
< 0.1%
4927 1
< 0.1%
4926 1
< 0.1%
4925 1
< 0.1%
4924 1
< 0.1%
4923 1
< 0.1%
4922 1
< 0.1%
4921 1
< 0.1%
4920 1
< 0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
식품제조가공업
4929 

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 4929
100.0%

Length

2024-04-20T22:21:29.878437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T22:21:30.156683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 4929
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
07_22_11_P
4929 

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 4929
100.0%

Length

2024-04-20T22:21:30.322326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T22:21:30.504870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_11_p 4929
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3336007.3
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-20T22:21:30.784141image/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 deviation41770.437
Coefficient of variation (CV)0.012521087
Kurtosis-0.88608395
Mean3336007.3
Median Absolute Deviation (MAD)30000
Skewness-0.18829772
Sum1.644318 × 1010
Variance1.7447694 × 109
MonotonicityNot monotonic
2024-04-20T22:21:31.167827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3340000 781
15.8%
3390000 487
9.9%
3290000 468
9.5%
3400000 425
8.6%
3330000 401
8.1%
3350000 382
7.8%
3360000 320
 
6.5%
3300000 311
 
6.3%
3260000 282
 
5.7%
3310000 220
 
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 468
9.5%
3300000 311
 
6.3%
3310000 220
 
4.5%
3320000 192
 
3.9%
3330000 401
8.1%
3340000 781
15.8%
ValueCountFrequency (%)
3400000 425
8.6%
3390000 487
9.9%
3380000 201
 
4.1%
3370000 177
 
3.6%
3360000 320
6.5%
3350000 382
7.8%
3340000 781
15.8%
3330000 401
8.1%
3320000 192
 
3.9%
3310000 220
 
4.5%

관리번호
Text

UNIQUE 

Distinct4929
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
2024-04-20T22:21:31.901309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters108438
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

Unique4929 ?
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%
3400000-106-2016-00018 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%
3400000-106-1992-00146 1
 
< 0.1%
3400000-106-2002-00015 1
 
< 0.1%
Other values (4919) 4919
99.8%
2024-04-20T22:21:33.074693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 47371
43.7%
- 14787
 
13.6%
1 10897
 
10.0%
3 10212
 
9.4%
6 6833
 
6.3%
2 6763
 
6.2%
9 4082
 
3.8%
4 2491
 
2.3%
8 1754
 
1.6%
5 1635
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 93651
86.4%
Dash Punctuation 14787
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 47371
50.6%
1 10897
 
11.6%
3 10212
 
10.9%
6 6833
 
7.3%
2 6763
 
7.2%
9 4082
 
4.4%
4 2491
 
2.7%
8 1754
 
1.9%
5 1635
 
1.7%
7 1613
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 14787
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 108438
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 47371
43.7%
- 14787
 
13.6%
1 10897
 
10.0%
3 10212
 
9.4%
6 6833
 
6.3%
2 6763
 
6.2%
9 4082
 
3.8%
4 2491
 
2.3%
8 1754
 
1.6%
5 1635
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 108438
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 47371
43.7%
- 14787
 
13.6%
1 10897
 
10.0%
3 10212
 
9.4%
6 6833
 
6.3%
2 6763
 
6.2%
9 4082
 
3.8%
4 2491
 
2.3%
8 1754
 
1.6%
5 1635
 
1.5%

인허가일자
Real number (ℝ)

Distinct3499
Distinct (%)71.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20050489
Minimum19631010
Maximum20210427
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-20T22:21:33.318303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19631010
5-th percentile19850119
Q120000226
median20060621
Q320140121
95-th percentile20190521
Maximum20210427
Range579417
Interquartile range (IQR)139895

Descriptive statistics

Standard deviation109377.37
Coefficient of variation (CV)0.0054550973
Kurtosis1.5978503
Mean20050489
Median Absolute Deviation (MAD)69907
Skewness-1.111451
Sum9.8828863 × 1010
Variance1.1963409 × 1010
MonotonicityNot monotonic
2024-04-20T22:21:33.658692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20020326 20
 
0.4%
20120525 8
 
0.2%
20010517 8
 
0.2%
19720113 8
 
0.2%
20010511 7
 
0.1%
20061128 7
 
0.1%
20140613 6
 
0.1%
20181203 6
 
0.1%
20150918 6
 
0.1%
20190107 6
 
0.1%
Other values (3489) 4847
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 (%)
20210427 3
0.1%
20210422 1
 
< 0.1%
20210421 1
 
< 0.1%
20210419 1
 
< 0.1%
20210414 1
 
< 0.1%
20210412 1
 
< 0.1%
20210405 1
 
< 0.1%
20210324 1
 
< 0.1%
20210323 2
< 0.1%
20210319 1
 
< 0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4929
Missing (%)100.0%
Memory size43.4 KiB

영업상태구분코드
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
3
3554 
1
1375 

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 3554
72.1%
1 1375
 
27.9%

Length

2024-04-20T22:21:34.060920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T22:21:34.360093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 3554
72.1%
1 1375
 
27.9%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
폐업
3554 
영업/정상
1375 

Length

Max length5
Median length2
Mean length2.8368837
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 3554
72.1%
영업/정상 1375
 
27.9%

Length

2024-04-20T22:21:34.701025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T22:21:35.015920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3554
72.1%
영업/정상 1375
 
27.9%

상세영업상태코드
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
2
3554 
1
1375 

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 3554
72.1%
1 1375
 
27.9%

Length

2024-04-20T22:21:35.417735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T22:21:35.709728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 3554
72.1%
1 1375
 
27.9%

상세영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
폐업
3554 
영업
1375 

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 3554
72.1%
영업 1375
 
27.9%

Length

2024-04-20T22:21:36.018079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T22:21:36.312276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3554
72.1%
영업 1375
 
27.9%

폐업일자
Real number (ℝ)

MISSING  SKEWED 

Distinct2472
Distinct (%)69.6%
Missing1375
Missing (%)27.9%
Infinite0
Infinite (%)0.0%
Mean20087015
Minimum10000101
Maximum20210430
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-20T22:21:36.661920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10000101
5-th percentile19990719
Q120030927
median20090614
Q320151020
95-th percentile20200225
Maximum20210430
Range10210329
Interquartile range (IQR)120092.75

Descriptive statistics

Standard deviation236724.81
Coefficient of variation (CV)0.011784967
Kurtosis1509.1389
Mean20087015
Median Absolute Deviation (MAD)60002
Skewness-37.133877
Sum7.1389251 × 1010
Variance5.6038636 × 1010
MonotonicityNot monotonic
2024-04-20T22:21:37.117117image/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%
20130404 8
 
0.2%
20041224 8
 
0.2%
20040126 7
 
0.1%
20050330 7
 
0.1%
20021230 7
 
0.1%
Other values (2462) 3448
70.0%
(Missing) 1375
 
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 (%)
20210430 1
< 0.1%
20210427 1
< 0.1%
20210426 2
< 0.1%
20210415 1
< 0.1%
20210413 1
< 0.1%
20210407 2
< 0.1%
20210405 1
< 0.1%
20210402 1
< 0.1%
20210330 1
< 0.1%
20210326 1
< 0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4929
Missing (%)100.0%
Memory size43.4 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4929
Missing (%)100.0%
Memory size43.4 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4929
Missing (%)100.0%
Memory size43.4 KiB

소재지전화
Text

MISSING 

Distinct3316
Distinct (%)83.9%
Missing977
Missing (%)19.8%
Memory size38.6 KiB
2024-04-20T22:21:38.153328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.531123
Min length2

Characters and Unicode

Total characters41619
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

Unique3057 ?
Unique (%)77.4%

Sample

1st row051 3176677
2nd row051 3282358
3rd row051 3013269
4th row051311 5930
5th row051 301 6297
ValueCountFrequency (%)
051 3470
40.8%
070 115
 
1.4%
727 21
 
0.2%
261 19
 
0.2%
231 19
 
0.2%
722 18
 
0.2%
266 18
 
0.2%
831 17
 
0.2%
728 17
 
0.2%
253 17
 
0.2%
Other values (3525) 4767
56.1%
2024-04-20T22:21:39.386587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6626
15.9%
5 6480
15.6%
1 6283
15.1%
4596
11.0%
2 3612
8.7%
7 2660
6.4%
6 2604
 
6.3%
3 2596
 
6.2%
8 2308
 
5.5%
4 2155
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 37023
89.0%
Space Separator 4596
 
11.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6626
17.9%
5 6480
17.5%
1 6283
17.0%
2 3612
9.8%
7 2660
7.2%
6 2604
 
7.0%
3 2596
 
7.0%
8 2308
 
6.2%
4 2155
 
5.8%
9 1699
 
4.6%
Space Separator
ValueCountFrequency (%)
4596
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 41619
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6626
15.9%
5 6480
15.6%
1 6283
15.1%
4596
11.0%
2 3612
8.7%
7 2660
6.4%
6 2604
 
6.3%
3 2596
 
6.2%
8 2308
 
5.5%
4 2155
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41619
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6626
15.9%
5 6480
15.6%
1 6283
15.1%
4596
11.0%
2 3612
8.7%
7 2660
6.4%
6 2604
 
6.3%
3 2596
 
6.2%
8 2308
 
5.5%
4 2155
 
5.2%

소재지면적
Text

MISSING 

Distinct3036
Distinct (%)70.8%
Missing641
Missing (%)13.0%
Memory size38.6 KiB
2024-04-20T22:21:40.670522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length5.3360541
Min length3

Characters and Unicode

Total characters22881
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

Unique2564 ?
Unique (%)59.8%

Sample

1st row1,480.80
2nd row421.25
3rd row27.50
4th row1,251.05
5th row293.00
ValueCountFrequency (%)
00 374
 
8.7%
27.00 23
 
0.5%
33.00 11
 
0.3%
20.00 10
 
0.2%
48.00 10
 
0.2%
12.00 10
 
0.2%
36.00 10
 
0.2%
60.00 10
 
0.2%
24.00 10
 
0.2%
100.00 9
 
0.2%
Other values (3026) 3811
88.9%
2024-04-20T22:21:42.300999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 4288
18.7%
0 4285
18.7%
1 2143
9.4%
2 1976
8.6%
4 1612
 
7.0%
3 1571
 
6.9%
5 1494
 
6.5%
6 1470
 
6.4%
8 1337
 
5.8%
9 1293
 
5.7%
Other values (2) 1412
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18411
80.5%
Other Punctuation 4470
 
19.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4285
23.3%
1 2143
11.6%
2 1976
10.7%
4 1612
 
8.8%
3 1571
 
8.5%
5 1494
 
8.1%
6 1470
 
8.0%
8 1337
 
7.3%
9 1293
 
7.0%
7 1230
 
6.7%
Other Punctuation
ValueCountFrequency (%)
. 4288
95.9%
, 182
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
Common 22881
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 4288
18.7%
0 4285
18.7%
1 2143
9.4%
2 1976
8.6%
4 1612
 
7.0%
3 1571
 
6.9%
5 1494
 
6.5%
6 1470
 
6.4%
8 1337
 
5.8%
9 1293
 
5.7%
Other values (2) 1412
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22881
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 4288
18.7%
0 4285
18.7%
1 2143
9.4%
2 1976
8.6%
4 1612
 
7.0%
3 1571
 
6.9%
5 1494
 
6.5%
6 1470
 
6.4%
8 1337
 
5.8%
9 1293
 
5.7%
Other values (2) 1412
 
6.2%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct725
Distinct (%)15.0%
Missing98
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean611332.61
Minimum600011
Maximum619953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-20T22:21:42.601714image/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 deviation5722.6357
Coefficient of variation (CV)0.0093609201
Kurtosis-1.2370339
Mean611332.61
Median Absolute Deviation (MAD)5224
Skewness-0.12458263
Sum2.9533478 × 109
Variance32748559
MonotonicityNot monotonic
2024-04-20T22:21:43.299131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
604842 146
 
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%
604824 45
 
0.9%
Other values (715) 4076
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 39
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

Distinct4315
Distinct (%)87.6%
Missing5
Missing (%)0.1%
Memory size38.6 KiB
2024-04-20T22:21:44.524436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length82
Median length67
Mean length24.22563
Min length16

Characters and Unicode

Total characters119287
Distinct characters402
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

Unique3913 ?
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 4927
 
21.7%
사하구 778
 
3.4%
사상구 486
 
2.1%
부산진구 469
 
2.1%
기장군 425
 
1.9%
장림동 402
 
1.8%
해운대구 400
 
1.8%
금정구 382
 
1.7%
강서구 320
 
1.4%
동래구 311
 
1.4%
Other values (4883) 13767
60.7%
2024-04-20T22:21:46.030518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17747
 
14.9%
산 5911
 
5.0%
부 5874
 
4.9%
동 5456
 
4.6%
1 5365
 
4.5%
광 5065
 
4.2%
시 5042
 
4.2%
역 4932
 
4.1%
지 4911
 
4.1%
구 4709
 
3.9%
Other values (392) 54275
45.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 71646
60.1%
Decimal Number 24420
 
20.5%
Space Separator 17747
 
14.9%
Dash Punctuation 4413
 
3.7%
Uppercase Letter 431
 
0.4%
Other Punctuation 227
 
0.2%
Open Punctuation 194
 
0.2%
Close Punctuation 192
 
0.2%
Math Symbol 12
 
< 0.1%
Lowercase Letter 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 5911
 
8.3%
부 5874
 
8.2%
동 5456
 
7.6%
광 5065
 
7.1%
시 5042
 
7.0%
역 4932
 
6.9%
지 4911
 
6.9%
구 4709
 
6.6%
번 4476
 
6.2%
사 1384
 
1.9%
Other values (350) 23886
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%
S 5
 
1.2%
D 5
 
1.2%
E 4
 
0.9%
L 4
 
0.9%
Other values (7) 7
 
1.6%
Decimal Number
ValueCountFrequency (%)
1 5365
22.0%
2 3183
13.0%
3 2719
11.1%
4 2388
9.8%
5 2103
 
8.6%
0 1980
 
8.1%
6 1837
 
7.5%
7 1791
 
7.3%
8 1622
 
6.6%
9 1432
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 198
87.2%
. 22
 
9.7%
/ 4
 
1.8%
@ 2
 
0.9%
: 1
 
0.4%
Lowercase Letter
ValueCountFrequency (%)
t 1
20.0%
p 1
20.0%
a 1
20.0%
e 1
20.0%
b 1
20.0%
Space Separator
ValueCountFrequency (%)
17747
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4413
100.0%
Open Punctuation
ValueCountFrequency (%)
( 194
100.0%
Close Punctuation
ValueCountFrequency (%)
) 192
100.0%
Math Symbol
ValueCountFrequency (%)
~ 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 71646
60.1%
Common 47205
39.6%
Latin 436
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 5911
 
8.3%
부 5874
 
8.2%
동 5456
 
7.6%
광 5065
 
7.1%
시 5042
 
7.0%
역 4932
 
6.9%
지 4911
 
6.9%
구 4709
 
6.6%
번 4476
 
6.2%
사 1384
 
1.9%
Other values (350) 23886
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%
S 5
 
1.1%
D 5
 
1.1%
E 4
 
0.9%
L 4
 
0.9%
Other values (12) 12
 
2.8%
Common
ValueCountFrequency (%)
17747
37.6%
1 5365
 
11.4%
- 4413
 
9.3%
2 3183
 
6.7%
3 2719
 
5.8%
4 2388
 
5.1%
5 2103
 
4.5%
0 1980
 
4.2%
6 1837
 
3.9%
7 1791
 
3.8%
Other values (10) 3679
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 71644
60.1%
ASCII 47641
39.9%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17747
37.3%
1 5365
 
11.3%
- 4413
 
9.3%
2 3183
 
6.7%
3 2719
 
5.7%
4 2388
 
5.0%
5 2103
 
4.4%
0 1980
 
4.2%
6 1837
 
3.9%
7 1791
 
3.8%
Other values (32) 4115
 
8.6%
Hangul
ValueCountFrequency (%)
산 5911
 
8.3%
부 5874
 
8.2%
동 5456
 
7.6%
광 5065
 
7.1%
시 5042
 
7.0%
역 4932
 
6.9%
지 4911
 
6.9%
구 4709
 
6.6%
번 4476
 
6.2%
사 1384
 
1.9%
Other values (349) 23884
33.3%
Compat Jamo
ValueCountFrequency (%)
ㅎ 2
100.0%

도로명전체주소
Text

MISSING 

Distinct2611
Distinct (%)94.9%
Missing2179
Missing (%)44.2%
Memory size38.6 KiB
2024-04-20T22:21:47.323056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length87
Median length59
Mean length30.645091
Min length19

Characters and Unicode

Total characters84274
Distinct characters407
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

Unique2500 ?
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 2753
 
17.0%
1층 477
 
2.9%
사하구 444
 
2.7%
기장군 288
 
1.8%
사상구 269
 
1.7%
부산진구 254
 
1.6%
해운대구 228
 
1.4%
금정구 225
 
1.4%
강서구 212
 
1.3%
장림동 209
 
1.3%
Other values (3020) 10830
66.9%
2024-04-20T22:21:48.820906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13444
 
16.0%
산 3490
 
4.1%
1 3485
 
4.1%
부 3350
 
4.0%
동 3315
 
3.9%
시 2915
 
3.5%
광 2898
 
3.4%
역 2756
 
3.3%
구 2612
 
3.1%
로 2600
 
3.1%
Other values (397) 43409
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 49467
58.7%
Decimal Number 13608
 
16.1%
Space Separator 13444
 
16.0%
Open Punctuation 2552
 
3.0%
Close Punctuation 2552
 
3.0%
Other Punctuation 1933
 
2.3%
Dash Punctuation 494
 
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 3490
 
7.1%
부 3350
 
6.8%
동 3315
 
6.7%
시 2915
 
5.9%
광 2898
 
5.9%
역 2756
 
5.6%
구 2612
 
5.3%
로 2600
 
5.3%
길 1632
 
3.3%
번 1485
 
3.0%
Other values (359) 22414
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 3485
25.6%
2 1987
14.6%
3 1531
11.3%
4 1179
 
8.7%
0 1127
 
8.3%
5 1053
 
7.7%
6 1017
 
7.5%
7 788
 
5.8%
9 737
 
5.4%
8 704
 
5.2%
Other Punctuation
ValueCountFrequency (%)
, 1928
99.7%
. 2
 
0.1%
* 1
 
0.1%
/ 1
 
0.1%
@ 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 2551
> 99.9%
[ 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 2551
> 99.9%
] 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
13444
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 494
100.0%
Math Symbol
ValueCountFrequency (%)
~ 34
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 49467
58.7%
Common 34617
41.1%
Latin 190
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 3490
 
7.1%
부 3350
 
6.8%
동 3315
 
6.7%
시 2915
 
5.9%
광 2898
 
5.9%
역 2756
 
5.6%
구 2612
 
5.3%
로 2600
 
5.3%
길 1632
 
3.3%
번 1485
 
3.0%
Other values (359) 22414
45.3%
Common
ValueCountFrequency (%)
13444
38.8%
1 3485
 
10.1%
( 2551
 
7.4%
) 2551
 
7.4%
2 1987
 
5.7%
, 1928
 
5.6%
3 1531
 
4.4%
4 1179
 
3.4%
0 1127
 
3.3%
5 1053
 
3.0%
Other values (12) 3781
 
10.9%
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 49467
58.7%
ASCII 34807
41.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13444
38.6%
1 3485
 
10.0%
( 2551
 
7.3%
) 2551
 
7.3%
2 1987
 
5.7%
, 1928
 
5.5%
3 1531
 
4.4%
4 1179
 
3.4%
0 1127
 
3.2%
5 1053
 
3.0%
Other values (28) 3971
 
11.4%
Hangul
ValueCountFrequency (%)
산 3490
 
7.1%
부 3350
 
6.8%
동 3315
 
6.7%
시 2915
 
5.9%
광 2898
 
5.9%
역 2756
 
5.6%
구 2612
 
5.3%
로 2600
 
5.3%
길 1632
 
3.3%
번 1485
 
3.0%
Other values (359) 22414
45.3%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct994
Distinct (%)36.8%
Missing2227
Missing (%)45.2%
Infinite0
Infinite (%)0.0%
Mean47721.219
Minimum46000
Maximum49526
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-20T22:21:49.081766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46000
5-th percentile46047
Q146712.25
median47576
Q348961.5
95-th percentile49478
Maximum49526
Range3526
Interquartile range (IQR)2249.25

Descriptive statistics

Standard deviation1184.4694
Coefficient of variation (CV)0.024820602
Kurtosis-1.3326086
Mean47721.219
Median Absolute Deviation (MAD)934.5
Skewness0.17003394
Sum1.2894273 × 108
Variance1402967.7
MonotonicityNot monotonic
2024-04-20T22:21:49.366395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
49478 66
 
1.3%
49277 60
 
1.2%
46079 39
 
0.8%
47032 38
 
0.8%
49469 37
 
0.8%
49526 28
 
0.6%
49273 26
 
0.5%
46706 24
 
0.5%
47253 22
 
0.4%
46704 18
 
0.4%
Other values (984) 2344
47.6%
(Missing) 2227
45.2%
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 28
0.6%
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

Distinct4092
Distinct (%)83.0%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
2024-04-20T22:21:50.303714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length31
Mean length6.0229255
Min length1

Characters and Unicode

Total characters29687
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

Unique3509 ?
Unique (%)71.2%

Sample

1st row한양식품
2nd row(주)로띠번코리아
3rd row주왕산식품
4th row제일식품
5th row서울제분
ValueCountFrequency (%)
주식회사 170
 
3.1%
식품 21
 
0.4%
coffee 17
 
0.3%
도시락 12
 
0.2%
주 10
 
0.2%
농업회사법인 9
 
0.2%
푸드 9
 
0.2%
food 9
 
0.2%
하나식품 9
 
0.2%
동해식품 8
 
0.1%
Other values (4303) 5267
95.1%
2024-04-20T22:21:51.718268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 1690
 
5.7%
품 1445
 
4.9%
주 1236
 
4.2%
) 1145
 
3.9%
( 1140
 
3.8%
산 640
 
2.2%
613
 
2.1%
드 562
 
1.9%
이 556
 
1.9%
푸 500
 
1.7%
Other values (790) 20160
67.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25344
85.4%
Close Punctuation 1145
 
3.9%
Open Punctuation 1140
 
3.8%
Uppercase Letter 827
 
2.8%
Space Separator 613
 
2.1%
Lowercase Letter 381
 
1.3%
Decimal Number 135
 
0.5%
Other Punctuation 91
 
0.3%
Dash Punctuation 6
 
< 0.1%
Other Symbol 3
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 1690
 
6.7%
품 1445
 
5.7%
주 1236
 
4.9%
산 640
 
2.5%
드 562
 
2.2%
이 556
 
2.2%
푸 500
 
2.0%
스 490
 
1.9%
사 480
 
1.9%
리 349
 
1.4%
Other values (719) 17396
68.6%
Uppercase Letter
ValueCountFrequency (%)
F 100
12.1%
O 86
 
10.4%
S 69
 
8.3%
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) 233
28.2%
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%
r 18
 
4.7%
t 18
 
4.7%
i 15
 
3.9%
m 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%
7 7
 
5.2%
8 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 (%)
) 1145
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1140
100.0%
Space Separator
ValueCountFrequency (%)
613
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
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 25336
85.3%
Common 3131
 
10.5%
Latin 1209
 
4.1%
Han 11
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 1690
 
6.7%
품 1445
 
5.7%
주 1236
 
4.9%
산 640
 
2.5%
드 562
 
2.2%
이 556
 
2.2%
푸 500
 
2.0%
스 490
 
1.9%
사 480
 
1.9%
리 349
 
1.4%
Other values (709) 17388
68.6%
Latin
ValueCountFrequency (%)
F 100
 
8.3%
O 86
 
7.1%
S 69
 
5.7%
C 67
 
5.5%
E 65
 
5.4%
e 61
 
5.0%
o 57
 
4.7%
A 52
 
4.3%
T 44
 
3.6%
R 38
 
3.1%
Other values (37) 570
47.1%
Common
ValueCountFrequency (%)
) 1145
36.6%
( 1140
36.4%
613
19.6%
& 49
 
1.6%
2 39
 
1.2%
. 32
 
1.0%
1 28
 
0.9%
0 14
 
0.4%
3 12
 
0.4%
4 10
 
0.3%
Other values (13) 49
 
1.6%
Han
ValueCountFrequency (%)
茶 1
9.1%
中 1
9.1%
院 1
9.1%
見 1
9.1%
手 1
9.1%
若 1
9.1%
水 1
9.1%
情 1
9.1%
功 1
9.1%
父 1
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25333
85.3%
ASCII 4337
 
14.6%
CJK 11
 
< 0.1%
None 5
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 1690
 
6.7%
품 1445
 
5.7%
주 1236
 
4.9%
산 640
 
2.5%
드 562
 
2.2%
이 556
 
2.2%
푸 500
 
2.0%
스 490
 
1.9%
사 480
 
1.9%
리 349
 
1.4%
Other values (708) 17385
68.6%
ASCII
ValueCountFrequency (%)
) 1145
26.4%
( 1140
26.3%
613
14.1%
F 100
 
2.3%
O 86
 
2.0%
S 69
 
1.6%
C 67
 
1.5%
E 65
 
1.5%
e 61
 
1.4%
o 57
 
1.3%
Other values (58) 934
21.5%
None
ValueCountFrequency (%)
㈜ 3
60.0%
· 2
40.0%
CJK
ValueCountFrequency (%)
茶 1
9.1%
中 1
9.1%
院 1
9.1%
見 1
9.1%
手 1
9.1%
若 1
9.1%
水 1
9.1%
情 1
9.1%
功 1
9.1%
父 1
9.1%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

최종수정시점
Real number (ℝ)

Distinct3916
Distinct (%)79.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.011496 × 1013
Minimum1.9990203 × 1013
Maximum2.021043 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-20T22:21:51.969196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990203 × 1013
5-th percentile2.0011018 × 1013
Q12.0040609 × 1013
median2.0130328 × 1013
Q32.0180612 × 1013
95-th percentile2.0201215 × 1013
Maximum2.021043 × 1013
Range2.2022715 × 1011
Interquartile range (IQR)1.4000311 × 1011

Descriptive statistics

Standard deviation7.0749289 × 1010
Coefficient of variation (CV)0.0035172473
Kurtosis-1.4999983
Mean2.011496 × 1013
Median Absolute Deviation (MAD)6.0485012 × 1010
Skewness-0.22580862
Sum9.9146638 × 1016
Variance5.0054619 × 1021
MonotonicityNot monotonic
2024-04-20T22:21:52.224191image/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 (3906) 4544
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 (%)
20210430145613 1
< 0.1%
20210430105913 1
< 0.1%
20210430105019 1
< 0.1%
20210429154532 1
< 0.1%
20210429154359 1
< 0.1%
20210428170438 1
< 0.1%
20210428114030 1
< 0.1%
20210428091844 1
< 0.1%
20210427171240 1
< 0.1%
20210427103529 1
< 0.1%

데이터갱신구분
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
I
3982 
U
947 

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 3982
80.8%
U 947
 
19.2%

Length

2024-04-20T22:21:52.562640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T22:21:52.889369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 3982
80.8%
u 947
 
19.2%

데이터갱신일자
Date

Distinct653
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
Minimum2018-08-31 23:59:59
Maximum2021-05-02 02:40:00
2024-04-20T22:21:53.252981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T22:21:53.527696image/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 size38.6 KiB
식품제조가공업
3720 
기타 식품제조가공업
1013 
<NA>
 
175
도시락제조업
 
19
분식
 
1

Length

Max length10
Median length7
Mean length7.5047677
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 3720
75.5%
기타 식품제조가공업 1013
 
20.6%
<NA> 175
 
3.6%
도시락제조업 19
 
0.4%
분식 1
 
< 0.1%
주류제조업 1
 
< 0.1%

Length

2024-04-20T22:21:53.779575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T22:21:53.983488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 4733
79.7%
기타 1013
 
17.0%
na 175
 
2.9%
도시락제조업 19
 
0.3%
분식 1
 
< 0.1%
주류제조업 1
 
< 0.1%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct3484
Distinct (%)74.4%
Missing249
Missing (%)5.1%
Infinite0
Infinite (%)0.0%
Mean386967.29
Minimum362913.86
Maximum409357.26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-20T22:21:54.213872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum362913.86
5-th percentile377378.4
Q1380874.17
median386934.94
Q3391694.89
95-th percentile401557.83
Maximum409357.26
Range46443.402
Interquartile range (IQR)10820.718

Descriptive statistics

Standard deviation7418.8413
Coefficient of variation (CV)0.019171753
Kurtosis0.0038604534
Mean386967.29
Median Absolute Deviation (MAD)5515.9936
Skewness0.32967689
Sum1.8110069 × 109
Variance55039207
MonotonicityNot monotonic
2024-04-20T22:21:54.622743image/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%
378428.966209849 12
 
0.2%
402792.323019555 12
 
0.2%
379815.215807943 12
 
0.2%
382728.324657277 11
 
0.2%
Other values (3474) 4471
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 

Distinct3484
Distinct (%)74.4%
Missing249
Missing (%)5.1%
Infinite0
Infinite (%)0.0%
Mean186683.85
Minimum170926.8
Maximum211328.08
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-20T22:21:55.017708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum170926.8
5-th percentile176355.03
Q1180290.15
median186998.39
Q3191448.87
95-th percentile198370.93
Maximum211328.08
Range40401.285
Interquartile range (IQR)11158.722

Descriptive statistics

Standard deviation7173.7882
Coefficient of variation (CV)0.038427471
Kurtosis-0.17153221
Mean186683.85
Median Absolute Deviation (MAD)5223.0676
Skewness0.33340748
Sum8.7368042 × 108
Variance51463237
MonotonicityNot monotonic
2024-04-20T22:21:55.521808image/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%
177298.418573324 12
 
0.2%
199422.531912758 12
 
0.2%
177453.67734986 12
 
0.2%
175767.563913389 11
 
0.2%
Other values (3474) 4472
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 11
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%
210316.862590787 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%

위생업태명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
식품제조가공업
3730 
기타 식품제조가공업
1003 
<NA>
 
175
도시락제조업
 
19
분식
 
1

Length

Max length10
Median length7
Mean length7.4986813
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 3730
75.7%
기타 식품제조가공업 1003
 
20.3%
<NA> 175
 
3.6%
도시락제조업 19
 
0.4%
분식 1
 
< 0.1%
주류제조업 1
 
< 0.1%

Length

2024-04-20T22:21:56.269046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T22:21:56.683213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 4733
79.8%
기타 1003
 
16.9%
na 175
 
3.0%
도시락제조업 19
 
0.3%
분식 1
 
< 0.1%
주류제조업 1
 
< 0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
4049 
0
816 
1
 
38
2
 
22
3
 
3

Length

Max length4
Median length4
Mean length3.4643944
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> 4049
82.1%
0 816
 
16.6%
1 38
 
0.8%
2 22
 
0.4%
3 3
 
0.1%
4 1
 
< 0.1%

Length

2024-04-20T22:21:57.172608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T22:21:57.852927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4049
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 size38.6 KiB
<NA>
4050 
0
816 
1
 
42
2
 
18
3
 
3

Length

Max length4
Median length4
Mean length3.465003
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> 4050
82.2%
0 816
 
16.6%
1 42
 
0.9%
2 18
 
0.4%
3 3
 
0.1%

Length

2024-04-20T22:21:58.278155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T22:21:58.682363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4050
82.2%
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 size38.6 KiB
<NA>
3414 
기타
1416 
주택가주변
 
75
아파트지역
 
11
학교정화(상대)
 
6
Other values (3)
 
7

Length

Max length8
Median length4
Mean length3.4530331
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> 3414
69.3%
기타 1416
28.7%
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

2024-04-20T22:21:59.156098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T22:21:59.566515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3414
69.3%
기타 1416
28.7%
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 size38.6 KiB
<NA>
3414 
기타
1402 
자율
 
112
지도
 
1

Length

Max length4
Median length4
Mean length3.3852708
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> 3414
69.3%
기타 1402
28.4%
자율 112
 
2.3%
지도 1
 
< 0.1%

Length

2024-04-20T22:21:59.920850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T22:22:00.120126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3414
69.3%
기타 1402
28.4%
자율 112
 
2.3%
지도 1
 
< 0.1%

급수시설구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
3038 
상수도전용
1848 
지하수전용
 
28
상수도(음용)지하수(주방용)겸용
 
10
간이상수도
 
4

Length

Max length19
Median length4
Mean length4.4108338
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3038
61.6%
상수도전용 1848
37.5%
지하수전용 28
 
0.6%
상수도(음용)지하수(주방용)겸용 10
 
0.2%
간이상수도 4
 
0.1%
전용상수도(특정시설의 자가용 수도) 1
 
< 0.1%

Length

2024-04-20T22:22:00.338241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T22:22:00.539256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3038
61.6%
상수도전용 1848
37.5%
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 

Missing4929
Missing (%)100.0%
Memory size43.4 KiB

본사종업원수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct14
Distinct (%)0.4%
Missing1805
Missing (%)36.6%
Infinite0
Infinite (%)0.0%
Mean28.701344
Minimum0
Maximum89417
Zeros3084
Zeros (%)62.6%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-20T22:22:00.761349image/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 deviation1599.7955
Coefficient of variation (CV)55.739391
Kurtosis3123.9925
Mean28.701344
Median Absolute Deviation (MAD)0
Skewness55.892654
Sum89663
Variance2559345.5
MonotonicityNot monotonic
2024-04-20T22:22:00.946777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 3084
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) 1805
36.6%
ValueCountFrequency (%)
0 3084
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%
Missing1788
Missing (%)36.3%
Infinite0
Infinite (%)0.0%
Mean0.33333333
Minimum0
Maximum47
Zeros2809
Zeros (%)57.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-20T22:22:01.156198image/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 deviation1.6986319
Coefficient of variation (CV)5.0958957
Kurtosis341.53946
Mean0.33333333
Median Absolute Deviation (MAD)0
Skewness15.527678
Sum1047
Variance2.8853503
MonotonicityNot monotonic
2024-04-20T22:22:01.348592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 2809
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) 1788
36.3%
ValueCountFrequency (%)
0 2809
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%
Missing1805
Missing (%)36.6%
Infinite0
Infinite (%)0.0%
Mean0.027528809
Minimum0
Maximum15
Zeros3089
Zeros (%)62.7%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-20T22:22:01.529241image/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 deviation0.39352448
Coefficient of variation (CV)14.295006
Kurtosis783.5956
Mean0.027528809
Median Absolute Deviation (MAD)0
Skewness24.816027
Sum86
Variance0.15486152
MonotonicityNot monotonic
2024-04-20T22:22:01.842706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 3089
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) 1805
36.6%
ValueCountFrequency (%)
0 3089
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 3089
62.7%

공장생산직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct41
Distinct (%)1.3%
Missing1754
Missing (%)35.6%
Infinite0
Infinite (%)0.0%
Mean1.2809449
Minimum0
Maximum158
Zeros2555
Zeros (%)51.8%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-20T22:22:02.230833image/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 deviation6.1841973
Coefficient of variation (CV)4.8278403
Kurtosis294.18171
Mean1.2809449
Median Absolute Deviation (MAD)0
Skewness14.692818
Sum4067
Variance38.244297
MonotonicityNot monotonic
2024-04-20T22:22:02.671152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
0 2555
51.8%
1 181
 
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) 1754
35.6%
ValueCountFrequency (%)
0 2555
51.8%
1 181
 
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 size38.6 KiB
<NA>
3130 
임대
1049 
자가
750 

Length

Max length4
Median length4
Mean length3.2700345
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> 3130
63.5%
임대 1049
 
21.3%
자가 750
 
15.2%

Length

2024-04-20T22:22:03.071130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T22:22:03.302026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3130
63.5%
임대 1049
 
21.3%
자가 750
 
15.2%

보증액
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)2.9%
Missing4615
Missing (%)93.6%
Infinite0
Infinite (%)0.0%
Mean496207.01
Minimum0
Maximum96800000
Zeros306
Zeros (%)6.2%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-20T22:22:03.464709image/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
2024-04-20T22:22:03.704619image/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) 4615
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%
Missing4615
Missing (%)93.6%
Infinite0
Infinite (%)0.0%
Mean35030.955
Minimum0
Maximum8349000
Zeros306
Zeros (%)6.2%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-20T22:22:04.047075image/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
2024-04-20T22:22:04.242859image/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) 4615
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
4929 
ValueCountFrequency (%)
False 4929
100.0%
2024-04-20T22:22:04.535204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

ZEROS 

Distinct873
Distinct (%)17.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.63931
Minimum0
Maximum4977.66
Zeros3738
Zeros (%)75.8%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-20T22:22:04.861873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile98.248
Maximum4977.66
Range4977.66
Interquartile range (IQR)0

Descriptive statistics

Standard deviation202.74334
Coefficient of variation (CV)7.0791979
Kurtosis299.45287
Mean28.63931
Median Absolute Deviation (MAD)0
Skewness15.78508
Sum141163.16
Variance41104.863
MonotonicityNot monotonic
2024-04-20T22:22:05.293509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3738
75.8%
6.0 13
 
0.3%
3.0 13
 
0.3%
288.36 11
 
0.2%
205.74 11
 
0.2%
5.0 9
 
0.2%
4.0 8
 
0.2%
10.8 8
 
0.2%
8.0 7
 
0.1%
246.24 7
 
0.1%
Other values (863) 1104
 
22.4%
ValueCountFrequency (%)
0.0 3738
75.8%
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 

Missing4929
Missing (%)100.0%
Memory size43.4 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4929
Missing (%)100.0%
Memory size43.4 KiB

홈페이지
Text

MISSING 

Distinct73
Distinct (%)93.6%
Missing4851
Missing (%)98.4%
Memory size38.6 KiB
2024-04-20T22:22:06.254418image/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%
2024-04-20T22:22:07.430604image/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 

Missing4929
Missing (%)100.0%
Memory size43.4 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
49194920식품제조가공업07_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>
49204921식품제조가공업07_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>
49214922식품제조가공업07_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>
49224923식품제조가공업07_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>
49234924식품제조가공업07_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>
49244925식품제조가공업07_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>
49254926식품제조가공업07_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>
49264927식품제조가공업07_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>
49274928식품제조가공업07_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>
49284929식품제조가공업07_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>