Overview

Dataset statistics

Number of variables48
Number of observations266
Missing cells3339
Missing cells (%)26.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory107.9 KiB
Average record size in memory415.5 B

Variable types

Numeric10
Categorical19
Text6
Unsupported11
DateTime1
Boolean1

Dataset

Description2021-04-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123102

Alerts

개방서비스명 has constant value ""Constant
개방서비스id has constant value ""Constant
업태구분명 has constant value ""Constant
위생업태명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (96.4%)Imbalance
여성종사자수 is highly imbalanced (96.4%)Imbalance
급수시설구분명 is highly imbalanced (50.3%)Imbalance
공장사무직종업원수 is highly imbalanced (54.1%)Imbalance
공장생산직종업원수 is highly imbalanced (58.5%)Imbalance
인허가취소일자 has 266 (100.0%) missing valuesMissing
폐업일자 has 118 (44.4%) missing valuesMissing
휴업시작일자 has 266 (100.0%) missing valuesMissing
휴업종료일자 has 266 (100.0%) missing valuesMissing
재개업일자 has 266 (100.0%) missing valuesMissing
소재지전화 has 63 (23.7%) missing valuesMissing
소재지면적 has 67 (25.2%) missing valuesMissing
소재지우편번호 has 7 (2.6%) missing valuesMissing
소재지전체주소 has 3 (1.1%) missing valuesMissing
도로명전체주소 has 67 (25.2%) missing valuesMissing
도로명우편번호 has 68 (25.6%) missing valuesMissing
좌표정보(x) has 10 (3.8%) missing valuesMissing
좌표정보(y) has 10 (3.8%) missing valuesMissing
영업장주변구분명 has 266 (100.0%) missing valuesMissing
등급구분명 has 266 (100.0%) missing valuesMissing
총종업원수 has 266 (100.0%) missing valuesMissing
전통업소지정번호 has 266 (100.0%) missing valuesMissing
전통업소주된음식 has 266 (100.0%) missing valuesMissing
홈페이지 has 266 (100.0%) missing valuesMissing
Unnamed: 47 has 266 (100.0%) missing valuesMissing
번호 has unique valuesUnique
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
영업장주변구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
등급구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
총종업원수 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 47 is an unsupported type, check if it needs cleaning or further analysisUnsupported
시설총규모 has 250 (94.0%) zerosZeros

Reproduction

Analysis started2024-04-16 15:58:05.336633
Analysis finished2024-04-16 15:58:05.917404
Duration0.58 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct266
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean133.5
Minimum1
Maximum266
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-04-17T00:58:05.976570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile14.25
Q167.25
median133.5
Q3199.75
95-th percentile252.75
Maximum266
Range265
Interquartile range (IQR)132.5

Descriptive statistics

Standard deviation76.931788
Coefficient of variation (CV)0.57626807
Kurtosis-1.2
Mean133.5
Median Absolute Deviation (MAD)66.5
Skewness0
Sum35511
Variance5918.5
MonotonicityStrictly increasing
2024-04-17T00:58:06.143823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
184 1
 
0.4%
170 1
 
0.4%
171 1
 
0.4%
172 1
 
0.4%
173 1
 
0.4%
174 1
 
0.4%
175 1
 
0.4%
176 1
 
0.4%
177 1
 
0.4%
Other values (256) 256
96.2%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
266 1
0.4%
265 1
0.4%
264 1
0.4%
263 1
0.4%
262 1
0.4%
261 1
0.4%
260 1
0.4%
259 1
0.4%
258 1
0.4%
257 1
0.4%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
식품운반업
266 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품운반업 266
100.0%

Length

2024-04-17T00:58:06.274188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T00:58:06.361453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품운반업 266
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
07_22_09_P
266 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row07_22_09_P
2nd row07_22_09_P
3rd row07_22_09_P
4th row07_22_09_P
5th row07_22_09_P

Common Values

ValueCountFrequency (%)
07_22_09_P 266
100.0%

Length

2024-04-17T00:58:06.443930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T00:58:06.525781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_09_p 266
100.0%

개방자치단체코드
Real number (ℝ)

Distinct15
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3334398.5
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-04-17T00:58:06.601169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3260000
Q13300000
median3340000
Q33360000
95-th percentile3390000
Maximum3400000
Range150000
Interquartile range (IQR)60000

Descriptive statistics

Standard deviation41715.739
Coefficient of variation (CV)0.012510724
Kurtosis-0.79188767
Mean3334398.5
Median Absolute Deviation (MAD)30000
Skewness-0.33419975
Sum8.8695 × 108
Variance1.7402029 × 109
MonotonicityNot monotonic
2024-04-17T00:58:06.701937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
3340000 46
17.3%
3390000 35
13.2%
3360000 34
12.8%
3290000 23
8.6%
3330000 21
7.9%
3350000 19
7.1%
3260000 18
 
6.8%
3300000 13
 
4.9%
3270000 12
 
4.5%
3320000 11
 
4.1%
Other values (5) 34
12.8%
ValueCountFrequency (%)
3250000 6
 
2.3%
3260000 18
 
6.8%
3270000 12
 
4.5%
3290000 23
8.6%
3300000 13
 
4.9%
3310000 7
 
2.6%
3320000 11
 
4.1%
3330000 21
7.9%
3340000 46
17.3%
3350000 19
7.1%
ValueCountFrequency (%)
3400000 11
 
4.1%
3390000 35
13.2%
3380000 6
 
2.3%
3370000 4
 
1.5%
3360000 34
12.8%
3350000 19
7.1%
3340000 46
17.3%
3330000 21
7.9%
3320000 11
 
4.1%
3310000 7
 
2.6%

관리번호
Text

UNIQUE 

Distinct266
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2024-04-17T00:58:06.866311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters5852
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

Unique266 ?
Unique (%)100.0%

Sample

1st row3250000-117-2006-00001
2nd row3250000-117-2014-00001
3rd row3250000-117-2020-00001
4th row3260000-117-2004-00001
5th row3260000-117-2005-00001
ValueCountFrequency (%)
3250000-117-2006-00001 1
 
0.4%
3340000-117-2005-00001 1
 
0.4%
3330000-117-2005-00004 1
 
0.4%
3340000-117-2009-00003 1
 
0.4%
3330000-117-2005-00003 1
 
0.4%
3330000-117-2006-00001 1
 
0.4%
3330000-117-2007-00001 1
 
0.4%
3330000-117-2009-00001 1
 
0.4%
3340000-117-2009-00008 1
 
0.4%
3340000-117-2013-00001 1
 
0.4%
Other values (256) 256
96.2%
2024-04-17T00:58:07.133214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2580
44.1%
1 815
 
13.9%
- 798
 
13.6%
3 535
 
9.1%
2 434
 
7.4%
7 327
 
5.6%
4 92
 
1.6%
9 83
 
1.4%
6 74
 
1.3%
5 69
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5054
86.4%
Dash Punctuation 798
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2580
51.0%
1 815
 
16.1%
3 535
 
10.6%
2 434
 
8.6%
7 327
 
6.5%
4 92
 
1.8%
9 83
 
1.6%
6 74
 
1.5%
5 69
 
1.4%
8 45
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 798
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5852
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2580
44.1%
1 815
 
13.9%
- 798
 
13.6%
3 535
 
9.1%
2 434
 
7.4%
7 327
 
5.6%
4 92
 
1.6%
9 83
 
1.4%
6 74
 
1.3%
5 69
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5852
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2580
44.1%
1 815
 
13.9%
- 798
 
13.6%
3 535
 
9.1%
2 434
 
7.4%
7 327
 
5.6%
4 92
 
1.6%
9 83
 
1.4%
6 74
 
1.3%
5 69
 
1.2%

인허가일자
Real number (ℝ)

Distinct218
Distinct (%)82.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20106540
Minimum19970528
Maximum20210224
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-04-17T00:58:07.267921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19970528
5-th percentile20033395
Q120063370
median20090660
Q320150758
95-th percentile20200825
Maximum20210224
Range239696
Interquartile range (IQR)87389

Descriptive statistics

Standard deviation52960.954
Coefficient of variation (CV)0.0026340163
Kurtosis-0.87852675
Mean20106540
Median Absolute Deviation (MAD)39553.5
Skewness0.3632374
Sum5.3483395 × 109
Variance2.8048626 × 109
MonotonicityNot monotonic
2024-04-17T00:58:07.408265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20200818 4
 
1.5%
20081223 3
 
1.1%
20071127 3
 
1.1%
20171116 3
 
1.1%
20110831 3
 
1.1%
20050718 3
 
1.1%
20070427 3
 
1.1%
20111111 3
 
1.1%
20050824 2
 
0.8%
20051215 2
 
0.8%
Other values (208) 237
89.1%
ValueCountFrequency (%)
19970528 1
0.4%
20000806 1
0.4%
20011108 1
0.4%
20030227 1
0.4%
20030324 1
0.4%
20030512 1
0.4%
20030823 1
0.4%
20030826 1
0.4%
20031015 1
0.4%
20031020 1
0.4%
ValueCountFrequency (%)
20210224 2
0.8%
20210111 1
0.4%
20210106 2
0.8%
20201023 1
0.4%
20201013 1
0.4%
20200909 1
0.4%
20200908 1
0.4%
20200904 1
0.4%
20200902 1
0.4%
20200901 1
0.4%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing266
Missing (%)100.0%
Memory size2.5 KiB

영업상태구분코드
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
3
148 
1
118 

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 (%)
3 148
55.6%
1 118
44.4%

Length

2024-04-17T00:58:07.569793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T00:58:07.666137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 148
55.6%
1 118
44.4%

영업상태명
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
폐업
148 
영업/정상
118 

Length

Max length5
Median length2
Mean length3.3308271
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 148
55.6%
영업/정상 118
44.4%

Length

2024-04-17T00:58:07.762037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T00:58:07.851456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 148
55.6%
영업/정상 118
44.4%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2
148 
1
118 

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 (%)
2 148
55.6%
1 118
44.4%

Length

2024-04-17T00:58:07.934863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T00:58:08.012652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 148
55.6%
1 118
44.4%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
폐업
148 
영업
118 

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 148
55.6%
영업 118
44.4%

Length

2024-04-17T00:58:08.098544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T00:58:08.190243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 148
55.6%
영업 118
44.4%

폐업일자
Real number (ℝ)

MISSING 

Distinct137
Distinct (%)92.6%
Missing118
Missing (%)44.4%
Infinite0
Infinite (%)0.0%
Mean20137428
Minimum20030114
Maximum20210129
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-04-17T00:58:08.300647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20030114
5-th percentile20060492
Q120100617
median20140405
Q320180124
95-th percentile20201012
Maximum20210129
Range180015
Interquartile range (IQR)79507.5

Descriptive statistics

Standard deviation46299.901
Coefficient of variation (CV)0.0022991963
Kurtosis-0.9346367
Mean20137428
Median Absolute Deviation (MAD)39754.5
Skewness-0.23911899
Sum2.9803394 × 109
Variance2.1436809 × 109
MonotonicityNot monotonic
2024-04-17T00:58:08.439872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20201006 7
 
2.6%
20200608 2
 
0.8%
20160426 2
 
0.8%
20140328 2
 
0.8%
20180921 2
 
0.8%
20091216 2
 
0.8%
20140403 1
 
0.4%
20100319 1
 
0.4%
20071204 1
 
0.4%
20131213 1
 
0.4%
Other values (127) 127
47.7%
(Missing) 118
44.4%
ValueCountFrequency (%)
20030114 1
0.4%
20031210 1
0.4%
20050215 1
0.4%
20050629 1
0.4%
20050805 1
0.4%
20051110 1
0.4%
20060308 1
0.4%
20060421 1
0.4%
20060623 1
0.4%
20070119 1
0.4%
ValueCountFrequency (%)
20210129 1
 
0.4%
20210120 1
 
0.4%
20201231 1
 
0.4%
20201218 1
 
0.4%
20201216 1
 
0.4%
20201125 1
 
0.4%
20201030 1
 
0.4%
20201016 1
 
0.4%
20201006 7
2.6%
20200608 2
 
0.8%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing266
Missing (%)100.0%
Memory size2.5 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing266
Missing (%)100.0%
Memory size2.5 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing266
Missing (%)100.0%
Memory size2.5 KiB

소재지전화
Text

MISSING 

Distinct174
Distinct (%)85.7%
Missing63
Missing (%)23.7%
Memory size2.2 KiB
2024-04-17T00:58:08.917413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.364532
Min length7

Characters and Unicode

Total characters2307
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

Unique152 ?
Unique (%)74.9%

Sample

1st row051 2572471
2nd row051 442 2038
3rd row051 463 3211
4th row051 2573331
5th row051 242 2993
ValueCountFrequency (%)
051 177
35.5%
070 7
 
1.4%
242 5
 
1.0%
583 4
 
0.8%
257 4
 
0.8%
3006 4
 
0.8%
3911 3
 
0.6%
5833911 3
 
0.6%
7591280 3
 
0.6%
5280454 3
 
0.6%
Other values (247) 285
57.2%
2024-04-17T00:58:09.249325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 354
15.3%
0 353
15.3%
5 333
14.4%
297
12.9%
2 182
7.9%
3 172
7.5%
4 160
6.9%
6 155
6.7%
8 111
 
4.8%
9 97
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2010
87.1%
Space Separator 297
 
12.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 354
17.6%
0 353
17.6%
5 333
16.6%
2 182
9.1%
3 172
8.6%
4 160
8.0%
6 155
7.7%
8 111
 
5.5%
9 97
 
4.8%
7 93
 
4.6%
Space Separator
ValueCountFrequency (%)
297
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2307
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 354
15.3%
0 353
15.3%
5 333
14.4%
297
12.9%
2 182
7.9%
3 172
7.5%
4 160
6.9%
6 155
6.7%
8 111
 
4.8%
9 97
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2307
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 354
15.3%
0 353
15.3%
5 333
14.4%
297
12.9%
2 182
7.9%
3 172
7.5%
4 160
6.9%
6 155
6.7%
8 111
 
4.8%
9 97
 
4.2%

소재지면적
Text

MISSING 

Distinct153
Distinct (%)76.9%
Missing67
Missing (%)25.2%
Memory size2.2 KiB
2024-04-17T00:58:09.560550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.0301508
Min length3

Characters and Unicode

Total characters1001
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

Unique128 ?
Unique (%)64.3%

Sample

1st row100.11
2nd row85.93
3rd row30.00
4th row30.00
5th row16.52
ValueCountFrequency (%)
00 11
 
5.5%
60.00 6
 
3.0%
33.00 5
 
2.5%
30.00 4
 
2.0%
39.60 3
 
1.5%
15.00 3
 
1.5%
50.00 3
 
1.5%
88.20 2
 
1.0%
11.93 2
 
1.0%
145.80 2
 
1.0%
Other values (143) 158
79.4%
2024-04-17T00:58:09.998110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 230
23.0%
. 199
19.9%
1 100
10.0%
6 76
 
7.6%
5 72
 
7.2%
3 71
 
7.1%
2 59
 
5.9%
8 50
 
5.0%
4 50
 
5.0%
9 49
 
4.9%
Other values (2) 45
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 801
80.0%
Other Punctuation 200
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 230
28.7%
1 100
12.5%
6 76
 
9.5%
5 72
 
9.0%
3 71
 
8.9%
2 59
 
7.4%
8 50
 
6.2%
4 50
 
6.2%
9 49
 
6.1%
7 44
 
5.5%
Other Punctuation
ValueCountFrequency (%)
. 199
99.5%
, 1
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Common 1001
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 230
23.0%
. 199
19.9%
1 100
10.0%
6 76
 
7.6%
5 72
 
7.2%
3 71
 
7.1%
2 59
 
5.9%
8 50
 
5.0%
4 50
 
5.0%
9 49
 
4.9%
Other values (2) 45
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1001
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 230
23.0%
. 199
19.9%
1 100
10.0%
6 76
 
7.6%
5 72
 
7.2%
3 71
 
7.1%
2 59
 
5.9%
8 50
 
5.0%
4 50
 
5.0%
9 49
 
4.9%
Other values (2) 45
 
4.5%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct139
Distinct (%)53.7%
Missing7
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean611329.29
Minimum600021
Maximum619953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-04-17T00:58:10.131089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600021
5-th percentile601837.9
Q1604837
median612809
Q3617806.5
95-th percentile618819
Maximum619953
Range19932
Interquartile range (IQR)12969.5

Descriptive statistics

Standard deviation6179.9772
Coefficient of variation (CV)0.010109081
Kurtosis-1.4413113
Mean611329.29
Median Absolute Deviation (MAD)5022
Skewness-0.20445852
Sum1.5833429 × 108
Variance38192118
MonotonicityNot monotonic
2024-04-17T00:58:10.299528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
604804 14
 
5.3%
617831 11
 
4.1%
617804 9
 
3.4%
602030 8
 
3.0%
609845 6
 
2.3%
618803 6
 
2.3%
602833 6
 
2.3%
618817 5
 
1.9%
612828 4
 
1.5%
614826 4
 
1.5%
Other values (129) 186
69.9%
(Missing) 7
 
2.6%
ValueCountFrequency (%)
600021 1
0.4%
600804 1
0.4%
600816 2
0.8%
600817 2
0.8%
601010 1
0.4%
601803 1
0.4%
601808 1
0.4%
601812 1
0.4%
601813 1
0.4%
601837 2
0.8%
ValueCountFrequency (%)
619953 1
 
0.4%
619913 3
1.1%
619906 3
1.1%
618899 4
1.5%
618820 1
 
0.4%
618819 4
1.5%
618817 5
1.9%
618816 1
 
0.4%
618815 1
 
0.4%
618812 1
 
0.4%

소재지전체주소
Text

MISSING 

Distinct231
Distinct (%)87.8%
Missing3
Missing (%)1.1%
Memory size2.2 KiB
2024-04-17T00:58:10.569064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length38
Mean length24.585551
Min length15

Characters and Unicode

Total characters6466
Distinct characters203
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique211 ?
Unique (%)80.2%

Sample

1st row부산광역시 중구 동광동1가 7번지 우리은행 304호
2nd row부산광역시 중구 중앙동4가 80-16번지 3층 306호
3rd row부산광역시 중구 중앙동4가 81-7
4th row부산광역시 서구 암남동 712번지
5th row부산광역시 서구 암남동 620-29번지 원양프라자 902호
ValueCountFrequency (%)
부산광역시 263
 
21.1%
사하구 46
 
3.7%
사상구 35
 
2.8%
강서구 34
 
2.7%
부산진구 22
 
1.8%
해운대구 20
 
1.6%
금정구 19
 
1.5%
서구 18
 
1.4%
감천동 16
 
1.3%
2층 15
 
1.2%
Other values (410) 758
60.8%
2024-04-17T00:58:10.946701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
983
 
15.2%
부 313
 
4.8%
동 306
 
4.7%
산 303
 
4.7%
1 298
 
4.6%
광 270
 
4.2%
시 267
 
4.1%
구 264
 
4.1%
역 263
 
4.1%
2 230
 
3.6%
Other values (193) 2969
45.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3860
59.7%
Decimal Number 1363
 
21.1%
Space Separator 983
 
15.2%
Dash Punctuation 213
 
3.3%
Close Punctuation 14
 
0.2%
Open Punctuation 14
 
0.2%
Uppercase Letter 14
 
0.2%
Other Punctuation 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 313
 
8.1%
동 306
 
7.9%
산 303
 
7.8%
광 270
 
7.0%
시 267
 
6.9%
구 264
 
6.8%
역 263
 
6.8%
지 230
 
6.0%
번 219
 
5.7%
사 88
 
2.3%
Other values (171) 1337
34.6%
Decimal Number
ValueCountFrequency (%)
1 298
21.9%
2 230
16.9%
3 139
10.2%
4 128
9.4%
0 110
 
8.1%
5 106
 
7.8%
6 102
 
7.5%
9 89
 
6.5%
8 81
 
5.9%
7 80
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
A 6
42.9%
B 2
 
14.3%
K 2
 
14.3%
T 1
 
7.1%
P 1
 
7.1%
I 1
 
7.1%
W 1
 
7.1%
Space Separator
ValueCountFrequency (%)
983
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 213
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3860
59.7%
Common 2592
40.1%
Latin 14
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 313
 
8.1%
동 306
 
7.9%
산 303
 
7.8%
광 270
 
7.0%
시 267
 
6.9%
구 264
 
6.8%
역 263
 
6.8%
지 230
 
6.0%
번 219
 
5.7%
사 88
 
2.3%
Other values (171) 1337
34.6%
Common
ValueCountFrequency (%)
983
37.9%
1 298
 
11.5%
2 230
 
8.9%
- 213
 
8.2%
3 139
 
5.4%
4 128
 
4.9%
0 110
 
4.2%
5 106
 
4.1%
6 102
 
3.9%
9 89
 
3.4%
Other values (5) 194
 
7.5%
Latin
ValueCountFrequency (%)
A 6
42.9%
B 2
 
14.3%
K 2
 
14.3%
T 1
 
7.1%
P 1
 
7.1%
I 1
 
7.1%
W 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3860
59.7%
ASCII 2606
40.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
983
37.7%
1 298
 
11.4%
2 230
 
8.8%
- 213
 
8.2%
3 139
 
5.3%
4 128
 
4.9%
0 110
 
4.2%
5 106
 
4.1%
6 102
 
3.9%
9 89
 
3.4%
Other values (12) 208
 
8.0%
Hangul
ValueCountFrequency (%)
부 313
 
8.1%
동 306
 
7.9%
산 303
 
7.8%
광 270
 
7.0%
시 267
 
6.9%
구 264
 
6.8%
역 263
 
6.8%
지 230
 
6.0%
번 219
 
5.7%
사 88
 
2.3%
Other values (171) 1337
34.6%

도로명전체주소
Text

MISSING 

Distinct181
Distinct (%)91.0%
Missing67
Missing (%)25.2%
Memory size2.2 KiB
2024-04-17T00:58:11.226824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length70
Median length42
Mean length31.638191
Min length21

Characters and Unicode

Total characters6296
Distinct characters229
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique168 ?
Unique (%)84.4%

Sample

1st row부산광역시 중구 광복로97번길 11, 304호 (동광동1가, 우리은행)
2nd row부산광역시 중구 충장대로9번길 28, 3층 306호 (중앙동4가)
3rd row부산광역시 중구 충장대로9번길 35-1, 3층 (중앙동4가)
4th row부산광역시 서구 원양로 310, 304호 (암남동)
5th row부산광역시 서구 원양로 105, 9층 902호 (암남동, 원양프라자)
ValueCountFrequency (%)
부산광역시 199
 
16.4%
1층 29
 
2.4%
2층 29
 
2.4%
사하구 26
 
2.1%
사상구 25
 
2.1%
강서구 24
 
2.0%
원양로 19
 
1.6%
해운대구 18
 
1.5%
부산진구 17
 
1.4%
금정구 16
 
1.3%
Other values (450) 814
66.9%
2024-04-17T00:58:11.656291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1018
 
16.2%
1 282
 
4.5%
동 264
 
4.2%
부 250
 
4.0%
산 247
 
3.9%
광 208
 
3.3%
시 207
 
3.3%
역 199
 
3.2%
로 199
 
3.2%
( 198
 
3.1%
Other values (219) 3224
51.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3600
57.2%
Decimal Number 1053
 
16.7%
Space Separator 1018
 
16.2%
Open Punctuation 198
 
3.1%
Close Punctuation 198
 
3.1%
Other Punctuation 172
 
2.7%
Dash Punctuation 39
 
0.6%
Uppercase Letter 16
 
0.3%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 264
 
7.3%
부 250
 
6.9%
산 247
 
6.9%
광 208
 
5.8%
시 207
 
5.8%
역 199
 
5.5%
로 199
 
5.5%
구 198
 
5.5%
층 103
 
2.9%
대 93
 
2.6%
Other values (195) 1632
45.3%
Decimal Number
ValueCountFrequency (%)
1 282
26.8%
2 156
14.8%
3 106
 
10.1%
0 91
 
8.6%
4 89
 
8.5%
6 77
 
7.3%
7 72
 
6.8%
5 68
 
6.5%
9 65
 
6.2%
8 47
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
A 7
43.8%
B 3
18.8%
K 2
 
12.5%
T 1
 
6.2%
I 1
 
6.2%
P 1
 
6.2%
W 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
, 171
99.4%
: 1
 
0.6%
Space Separator
ValueCountFrequency (%)
1018
100.0%
Open Punctuation
ValueCountFrequency (%)
( 198
100.0%
Close Punctuation
ValueCountFrequency (%)
) 198
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 39
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3600
57.2%
Common 2680
42.6%
Latin 16
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 264
 
7.3%
부 250
 
6.9%
산 247
 
6.9%
광 208
 
5.8%
시 207
 
5.8%
역 199
 
5.5%
로 199
 
5.5%
구 198
 
5.5%
층 103
 
2.9%
대 93
 
2.6%
Other values (195) 1632
45.3%
Common
ValueCountFrequency (%)
1018
38.0%
1 282
 
10.5%
( 198
 
7.4%
) 198
 
7.4%
, 171
 
6.4%
2 156
 
5.8%
3 106
 
4.0%
0 91
 
3.4%
4 89
 
3.3%
6 77
 
2.9%
Other values (7) 294
 
11.0%
Latin
ValueCountFrequency (%)
A 7
43.8%
B 3
18.8%
K 2
 
12.5%
T 1
 
6.2%
I 1
 
6.2%
P 1
 
6.2%
W 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3600
57.2%
ASCII 2696
42.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1018
37.8%
1 282
 
10.5%
( 198
 
7.3%
) 198
 
7.3%
, 171
 
6.3%
2 156
 
5.8%
3 106
 
3.9%
0 91
 
3.4%
4 89
 
3.3%
6 77
 
2.9%
Other values (14) 310
 
11.5%
Hangul
ValueCountFrequency (%)
동 264
 
7.3%
부 250
 
6.9%
산 247
 
6.9%
광 208
 
5.8%
시 207
 
5.8%
역 199
 
5.5%
로 199
 
5.5%
구 198
 
5.5%
층 103
 
2.9%
대 93
 
2.6%
Other values (195) 1632
45.3%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct127
Distinct (%)64.1%
Missing68
Missing (%)25.6%
Infinite0
Infinite (%)0.0%
Mean47716.778
Minimum46004
Maximum49478
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-04-17T00:58:11.785159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46004
5-th percentile46199.85
Q146725.5
median47456
Q348788.75
95-th percentile49452
Maximum49478
Range3474
Interquartile range (IQR)2063.25

Descriptive statistics

Standard deviation1125.6799
Coefficient of variation (CV)0.023590862
Kurtosis-1.3064232
Mean47716.778
Median Absolute Deviation (MAD)756
Skewness0.2572599
Sum9447922
Variance1267155.2
MonotonicityNot monotonic
2024-04-17T00:58:11.907468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
49273 12
 
4.5%
47027 9
 
3.4%
46259 6
 
2.3%
48056 4
 
1.5%
46721 4
 
1.5%
46043 3
 
1.1%
48031 3
 
1.1%
49449 3
 
1.1%
46703 3
 
1.1%
46700 3
 
1.1%
Other values (117) 148
55.6%
(Missing) 68
25.6%
ValueCountFrequency (%)
46004 2
 
0.8%
46022 1
 
0.4%
46033 1
 
0.4%
46043 3
1.1%
46064 1
 
0.4%
46078 1
 
0.4%
46080 1
 
0.4%
46221 1
 
0.4%
46222 1
 
0.4%
46259 6
2.3%
ValueCountFrequency (%)
49478 1
 
0.4%
49463 1
 
0.4%
49462 1
 
0.4%
49460 3
1.1%
49455 2
0.8%
49453 1
 
0.4%
49452 2
0.8%
49451 2
0.8%
49449 3
1.1%
49423 1
 
0.4%

사업장명
Text

Distinct223
Distinct (%)83.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2024-04-17T00:58:12.196662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length17
Mean length6.8308271
Min length2

Characters and Unicode

Total characters1817
Distinct characters222
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique192 ?
Unique (%)72.2%

Sample

1st row(주)에어앤씨카고
2nd row합자회사 동신기업사
3rd row동아통운(주)
4th row(주)삼일물류
5th row(주)한맥로지스틱스
ValueCountFrequency (%)
주식회사 8
 
2.8%
개별화물 6
 
2.1%
개인용달 4
 
1.4%
주)한맥물류 4
 
1.4%
주)세종물류 3
 
1.1%
용진운수(주 3
 
1.1%
주)영진지엘에스 3
 
1.1%
주)중앙로지스 3
 
1.1%
대경유통 2
 
0.7%
보성지티에스(주 2
 
0.7%
Other values (220) 243
86.5%
2024-04-17T00:58:12.613535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 149
 
8.2%
( 138
 
7.6%
) 138
 
7.6%
물 64
 
3.5%
스 50
 
2.8%
류 48
 
2.6%
동 38
 
2.1%
수 38
 
2.1%
운 37
 
2.0%
지 35
 
1.9%
Other values (212) 1082
59.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1494
82.2%
Open Punctuation 138
 
7.6%
Close Punctuation 138
 
7.6%
Uppercase Letter 19
 
1.0%
Space Separator 15
 
0.8%
Decimal Number 8
 
0.4%
Other Punctuation 5
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 149
 
10.0%
물 64
 
4.3%
스 50
 
3.3%
류 48
 
3.2%
동 38
 
2.5%
수 38
 
2.5%
운 37
 
2.5%
지 35
 
2.3%
통 33
 
2.2%
에 31
 
2.1%
Other values (192) 971
65.0%
Uppercase Letter
ValueCountFrequency (%)
S 3
15.8%
T 3
15.8%
C 3
15.8%
Y 2
10.5%
F 2
10.5%
B 1
 
5.3%
G 1
 
5.3%
A 1
 
5.3%
W 1
 
5.3%
K 1
 
5.3%
Decimal Number
ValueCountFrequency (%)
9 4
50.0%
2 2
25.0%
5 2
25.0%
Other Punctuation
ValueCountFrequency (%)
, 2
40.0%
. 2
40.0%
& 1
20.0%
Open Punctuation
ValueCountFrequency (%)
( 138
100.0%
Close Punctuation
ValueCountFrequency (%)
) 138
100.0%
Space Separator
ValueCountFrequency (%)
15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1494
82.2%
Common 304
 
16.7%
Latin 19
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 149
 
10.0%
물 64
 
4.3%
스 50
 
3.3%
류 48
 
3.2%
동 38
 
2.5%
수 38
 
2.5%
운 37
 
2.5%
지 35
 
2.3%
통 33
 
2.2%
에 31
 
2.1%
Other values (192) 971
65.0%
Latin
ValueCountFrequency (%)
S 3
15.8%
T 3
15.8%
C 3
15.8%
Y 2
10.5%
F 2
10.5%
B 1
 
5.3%
G 1
 
5.3%
A 1
 
5.3%
W 1
 
5.3%
K 1
 
5.3%
Common
ValueCountFrequency (%)
( 138
45.4%
) 138
45.4%
15
 
4.9%
9 4
 
1.3%
2 2
 
0.7%
, 2
 
0.7%
. 2
 
0.7%
5 2
 
0.7%
& 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1494
82.2%
ASCII 323
 
17.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 149
 
10.0%
물 64
 
4.3%
스 50
 
3.3%
류 48
 
3.2%
동 38
 
2.5%
수 38
 
2.5%
운 37
 
2.5%
지 35
 
2.3%
통 33
 
2.2%
에 31
 
2.1%
Other values (192) 971
65.0%
ASCII
ValueCountFrequency (%)
( 138
42.7%
) 138
42.7%
15
 
4.6%
9 4
 
1.2%
S 3
 
0.9%
T 3
 
0.9%
C 3
 
0.9%
2 2
 
0.6%
, 2
 
0.6%
. 2
 
0.6%
Other values (10) 13
 
4.0%

최종수정시점
Real number (ℝ)

Distinct265
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0143698 × 1013
Minimum2.0020226 × 1013
Maximum2.0210224 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-04-17T00:58:12.741008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0020226 × 1013
5-th percentile2.0050651 × 1013
Q12.0100347 × 1013
median2.0160406 × 1013
Q32.0191066 × 1013
95-th percentile2.0207883 × 1013
Maximum2.0210224 × 1013
Range1.8999816 × 1011
Interquartile range (IQR)9.0719294 × 1010

Descriptive statistics

Standard deviation5.4252515 × 1010
Coefficient of variation (CV)0.0026932748
Kurtosis-1.0246803
Mean2.0143698 × 1013
Median Absolute Deviation (MAD)4.0212524 × 1010
Skewness-0.52464301
Sum5.3582238 × 1015
Variance2.9433354 × 1021
MonotonicityNot monotonic
2024-04-17T00:58:12.867380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20050824000000 2
 
0.8%
20120207161656 1
 
0.4%
20201010234229 1
 
0.4%
20201010234320 1
 
0.4%
20080527134138 1
 
0.4%
20201010234252 1
 
0.4%
20050429000000 1
 
0.4%
20040709000000 1
 
0.4%
20040217000000 1
 
0.4%
20210105144925 1
 
0.4%
Other values (255) 255
95.9%
ValueCountFrequency (%)
20020226000000 1
0.4%
20030324000000 1
0.4%
20030512000000 1
0.4%
20031020000000 1
0.4%
20031021000000 1
0.4%
20031027000000 1
0.4%
20031121000000 1
0.4%
20040217000000 1
0.4%
20040315000000 1
0.4%
20040709000000 1
0.4%
ValueCountFrequency (%)
20210224163610 1
0.4%
20210224163251 1
0.4%
20210129162247 1
0.4%
20210129161818 1
0.4%
20210122184201 1
0.4%
20210122093839 1
0.4%
20210120113054 1
0.4%
20210118143407 1
0.4%
20210114125620 1
0.4%
20210113115643 1
0.4%

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
I
190 
U
76 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 190
71.4%
U 76
 
28.6%

Length

2024-04-17T00:58:12.975672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T00:58:13.048893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 190
71.4%
u 76
 
28.6%

데이터갱신일자
Date

Distinct74
Distinct (%)27.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Minimum2018-08-31 23:59:59
Maximum2021-02-26 00:23:01
2024-04-17T00:58:13.133242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T00:58:13.264940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
식품운반업
266 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품운반업 266
100.0%

Length

2024-04-17T00:58:13.389930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T00:58:13.470644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품운반업 266
100.0%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct196
Distinct (%)76.6%
Missing10
Missing (%)3.8%
Infinite0
Infinite (%)0.0%
Mean385029.61
Minimum367454.56
Maximum403920.39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-04-17T00:58:13.561383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum367454.56
5-th percentile374493.77
Q1380263.44
median383531.62
Q3389904.34
95-th percentile395910.86
Maximum403920.39
Range36465.83
Interquartile range (IQR)9640.8938

Descriptive statistics

Standard deviation6956.6638
Coefficient of variation (CV)0.018067867
Kurtosis0.55364058
Mean385029.61
Median Absolute Deviation (MAD)4130.3584
Skewness0.13996937
Sum98567580
Variance48395171
MonotonicityNot monotonic
2024-04-17T00:58:13.681370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
379764.389679699 9
 
3.4%
383518.040204105 6
 
2.3%
393054.070020468 5
 
1.9%
367454.564232222 5
 
1.9%
381454.594898065 4
 
1.5%
393233.931123062 3
 
1.1%
382852.793754942 3
 
1.1%
382859.036470648 3
 
1.1%
378913.002700159 3
 
1.1%
393564.154856479 3
 
1.1%
Other values (186) 212
79.7%
(Missing) 10
 
3.8%
ValueCountFrequency (%)
367454.564232222 5
1.9%
368098.86127099 1
 
0.4%
368677.63451413 1
 
0.4%
369324.667538937 1
 
0.4%
369510.064865473 2
 
0.8%
372337.596274806 1
 
0.4%
372994.73172451 1
 
0.4%
373017.818475368 1
 
0.4%
374985.749975672 1
 
0.4%
376683.252769612 1
 
0.4%
ValueCountFrequency (%)
403920.394694604 1
 
0.4%
403400.70176596 3
1.1%
403232.866658086 1
 
0.4%
401995.797588582 1
 
0.4%
401928.416182264 1
 
0.4%
400921.195390687 1
 
0.4%
398687.383627252 1
 
0.4%
398663.970066616 1
 
0.4%
398128.076450259 1
 
0.4%
397438.831338517 1
 
0.4%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct196
Distinct (%)76.6%
Missing10
Missing (%)3.8%
Infinite0
Infinite (%)0.0%
Mean185842.36
Minimum174611.96
Maximum206599.78
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-04-17T00:58:13.831284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum174611.96
5-th percentile175767.56
Q1179554.38
median185333.75
Q3190975.31
95-th percentile198173.95
Maximum206599.78
Range31987.822
Interquartile range (IQR)11420.93

Descriptive statistics

Standard deviation6992.7719
Coefficient of variation (CV)0.037627439
Kurtosis-0.41155542
Mean185842.36
Median Absolute Deviation (MAD)5664.4271
Skewness0.40854833
Sum47575643
Variance48898859
MonotonicityNot monotonic
2024-04-17T00:58:13.957996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
185333.750017244 9
 
3.4%
175580.741380931 6
 
2.3%
194090.700712147 5
 
1.9%
179343.014764116 5
 
1.9%
177164.789486544 4
 
1.5%
192684.487637586 3
 
1.1%
177505.422460379 3
 
1.1%
177962.876339211 3
 
1.1%
182671.353228429 3
 
1.1%
189232.298979587 3
 
1.1%
Other values (186) 212
79.7%
(Missing) 10
 
3.8%
ValueCountFrequency (%)
174611.961458235 1
 
0.4%
174626.658689664 2
 
0.8%
175140.099221406 1
 
0.4%
175274.144961403 1
 
0.4%
175469.439982525 1
 
0.4%
175580.741380931 6
2.3%
175767.563913389 2
 
0.8%
175944.196657226 2
 
0.8%
176183.105551719 1
 
0.4%
176522.453427325 3
1.1%
ValueCountFrequency (%)
206599.783800745 1
 
0.4%
206240.13184752 1
 
0.4%
204872.34472323 1
 
0.4%
203653.574237789 1
 
0.4%
203648.795712099 1
 
0.4%
198866.796058539 3
1.1%
198690.393083898 1
 
0.4%
198690.232287766 1
 
0.4%
198457.294596131 1
 
0.4%
198403.97184169 1
 
0.4%

위생업태명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
식품운반업
266 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품운반업 266
100.0%

Length

2024-04-17T00:58:14.067461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T00:58:14.146667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품운반업 266
100.0%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
265 
0
 
1

Length

Max length4
Median length4
Mean length3.9887218
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 265
99.6%
0 1
 
0.4%

Length

2024-04-17T00:58:14.230174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T00:58:14.312846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 265
99.6%
0 1
 
0.4%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
265 
0
 
1

Length

Max length4
Median length4
Mean length3.9887218
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 265
99.6%
0 1
 
0.4%

Length

2024-04-17T00:58:14.481362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T00:58:14.581172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 265
99.6%
0 1
 
0.4%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing266
Missing (%)100.0%
Memory size2.5 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing266
Missing (%)100.0%
Memory size2.5 KiB

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
237 
상수도전용
29 

Length

Max length5
Median length4
Mean length4.1090226
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 237
89.1%
상수도전용 29
 
10.9%

Length

2024-04-17T00:58:14.668713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T00:58:14.747259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 237
89.1%
상수도전용 29
 
10.9%

총종업원수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing266
Missing (%)100.0%
Memory size2.5 KiB

본사종업원수
Categorical

Distinct4
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
0
169 
<NA>
95 
1
 
1
96
 
1

Length

Max length4
Median length1
Mean length2.075188
Min length1

Unique

Unique2 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
0 169
63.5%
<NA> 95
35.7%
1 1
 
0.4%
96 1
 
0.4%

Length

2024-04-17T00:58:14.835073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T00:58:14.921612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 169
63.5%
na 95
35.7%
1 1
 
0.4%
96 1
 
0.4%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct6
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
0
164 
<NA>
93 
1
 
4
3
 
2
2
 
2

Length

Max length4
Median length1
Mean length2.0488722
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
0 164
61.7%
<NA> 93
35.0%
1 4
 
1.5%
3 2
 
0.8%
2 2
 
0.8%
6 1
 
0.4%

Length

2024-04-17T00:58:15.013793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T00:58:15.127162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 164
61.7%
na 93
35.0%
1 4
 
1.5%
3 2
 
0.8%
2 2
 
0.8%
6 1
 
0.4%

공장판매직종업원수
Categorical

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
0
169 
<NA>
96 
2
 
1

Length

Max length4
Median length1
Mean length2.0827068
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
0 169
63.5%
<NA> 96
36.1%
2 1
 
0.4%

Length

2024-04-17T00:58:15.243652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T00:58:15.334398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 169
63.5%
na 96
36.1%
2 1
 
0.4%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct6
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
0
167 
<NA>
95 
1
 
1
4
 
1
11
 
1

Length

Max length4
Median length1
Mean length2.075188
Min length1

Unique

Unique4 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
0 167
62.8%
<NA> 95
35.7%
1 1
 
0.4%
4 1
 
0.4%
11 1
 
0.4%
3 1
 
0.4%

Length

2024-04-17T00:58:15.441710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T00:58:15.573106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 167
62.8%
na 95
35.7%
1 1
 
0.4%
4 1
 
0.4%
11 1
 
0.4%
3 1
 
0.4%

건물소유구분명
Categorical

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
151 
자가
72 
임대
43 

Length

Max length4
Median length4
Mean length3.1353383
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 151
56.8%
자가 72
27.1%
임대 43
 
16.2%

Length

2024-04-17T00:58:15.689157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T00:58:15.794768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 151
56.8%
자가 72
27.1%
임대 43
 
16.2%

보증액
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
226 
0
40 

Length

Max length4
Median length4
Mean length3.5488722
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 226
85.0%
0 40
 
15.0%

Length

2024-04-17T00:58:15.892120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T00:58:15.976369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 226
85.0%
0 40
 
15.0%

월세액
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
226 
0
40 

Length

Max length4
Median length4
Mean length3.5488722
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 226
85.0%
0 40
 
15.0%

Length

2024-04-17T00:58:16.367852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T00:58:16.449242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 226
85.0%
0 40
 
15.0%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size398.0 B
False
266 
ValueCountFrequency (%)
False 266
100.0%
2024-04-17T00:58:16.518272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

ZEROS 

Distinct15
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.4119925
Minimum0
Maximum1204
Zeros250
Zeros (%)94.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-04-17T00:58:16.611086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile19
Maximum1204
Range1204
Interquartile range (IQR)0

Descriptive statistics

Standard deviation75.531134
Coefficient of variation (CV)10.190395
Kurtosis240.30947
Mean7.4119925
Median Absolute Deviation (MAD)0
Skewness15.204764
Sum1971.59
Variance5704.9522
MonotonicityNot monotonic
2024-04-17T00:58:16.709115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0.0 250
94.0%
49.5 2
 
0.8%
19.0 2
 
0.8%
26.4 1
 
0.4%
196.0 1
 
0.4%
39.6 1
 
0.4%
33.0 1
 
0.4%
1204.0 1
 
0.4%
24.0 1
 
0.4%
43.3 1
 
0.4%
Other values (5) 5
 
1.9%
ValueCountFrequency (%)
0.0 250
94.0%
3.7 1
 
0.4%
19.0 2
 
0.8%
24.0 1
 
0.4%
26.4 1
 
0.4%
33.0 1
 
0.4%
33.04 1
 
0.4%
36.55 1
 
0.4%
39.6 1
 
0.4%
43.3 1
 
0.4%
ValueCountFrequency (%)
1204.0 1
0.4%
196.0 1
0.4%
150.0 1
0.4%
49.5 2
0.8%
45.0 1
0.4%
43.3 1
0.4%
39.6 1
0.4%
36.55 1
0.4%
33.04 1
0.4%
33.0 1
0.4%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing266
Missing (%)100.0%
Memory size2.5 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing266
Missing (%)100.0%
Memory size2.5 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing266
Missing (%)100.0%
Memory size2.5 KiB

Unnamed: 47
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing266
Missing (%)100.0%
Memory size2.5 KiB

Sample

번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지Unnamed: 47
01식품운반업07_22_09_P32500003250000-117-2006-0000120060411<NA>1영업/정상1영업<NA><NA><NA><NA>051 2572471100.11600021부산광역시 중구 동광동1가 7번지 우리은행 304호부산광역시 중구 광복로97번길 11, 304호 (동광동1가, 우리은행)48952(주)에어앤씨카고20120207161656I2018-08-31 23:59:59.0식품운반업385498.102705179739.963317식품운반업<NA><NA><NA><NA><NA><NA>0000자가<NA><NA>N0.0<NA><NA><NA><NA>
12식품운반업07_22_09_P32500003250000-117-2014-0000120140210<NA>1영업/정상1영업<NA><NA><NA><NA>051 442 203885.93600817부산광역시 중구 중앙동4가 80-16번지 3층 306호부산광역시 중구 충장대로9번길 28, 3층 306호 (중앙동4가)48937합자회사 동신기업사20180806154758I2018-08-31 23:59:59.0식품운반업385730.223219180633.142129식품운반업<NA><NA><NA><NA>상수도전용<NA>0000자가<NA><NA>N0.0<NA><NA><NA><NA>
23식품운반업07_22_09_P32500003250000-117-2020-0000120200708<NA>1영업/정상1영업<NA><NA><NA><NA>051 463 321130.00600817부산광역시 중구 중앙동4가 81-7부산광역시 중구 충장대로9번길 35-1, 3층 (중앙동4가)48937동아통운(주)20200708095342I2020-07-10 00:23:16.0식품운반업385731.290616180730.387826식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
34식품운반업07_22_09_P32600003260000-117-2004-0000120040312<NA>1영업/정상1영업<NA><NA><NA><NA>051 257333130.00602030부산광역시 서구 암남동 712번지부산광역시 서구 원양로 310, 304호 (암남동)49273(주)삼일물류20171206134428I2018-08-31 23:59:59.0식품운반업382890.650587177336.22369식품운반업<NA><NA><NA><NA><NA><NA>0000자가<NA><NA>N0.0<NA><NA><NA><NA>
45식품운반업07_22_09_P32600003260000-117-2005-0000120050907<NA>1영업/정상1영업<NA><NA><NA><NA>051 242 299316.52602833부산광역시 서구 암남동 620-29번지 원양프라자 902호부산광역시 서구 원양로 105, 9층 902호 (암남동, 원양프라자)49273(주)한맥로지스틱스20200115154114U2020-01-17 02:40:00.0식품운반업383518.040204175580.741381식품운반업<NA><NA><NA><NA><NA><NA>0000임대<NA><NA>N0.0<NA><NA><NA><NA>
56식품운반업07_22_09_P32600003260000-117-2007-0000420071120<NA>1영업/정상1영업<NA><NA><NA><NA>051 203 347423.80602030부산광역시 서구 암남동 753번지 동양글로벌냉장 5층부산광역시 서구 원양로 243, 5층 (암남동, 동양글로벌냉장)49273백두냉동운수(주)20190219113531U2019-02-21 02:40:00.0식품운반업382929.6612176610.19321식품운반업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
67식품운반업07_22_09_P32600003260000-117-2007-0000220071127<NA>1영업/정상1영업<NA><NA><NA><NA>051 242 283336.30602030부산광역시 서구 암남동 712번지 동영빌딩 304호부산광역시 서구 원양로 310, 304호 (암남동, 동영빌딩)49273(주)해인지엘에스20150817153006I2018-08-31 23:59:59.0식품운반업382890.650587177336.22369식품운반업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
78식품운반업07_22_09_P32600003260000-117-2009-0000120090527<NA>1영업/정상1영업<NA><NA><NA><NA>051 242 688633.00602833부산광역시 서구 암남동 620-29번지 원양프라자 902호부산광역시 서구 원양로 105, 9층 902호 (암남동, 원양프라자)49273(주)한맥물류20170830102943I2018-08-31 23:59:59.0식품운반업383518.040204175580.741381식품운반업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
89식품운반업07_22_09_P32600003260000-117-2011-0000120110831<NA>1영업/정상1영업<NA><NA><NA><NA>051 256 596019.60602030부산광역시 서구 암남동 716번지 냉장인터불고2공장 7층부산광역시 서구 원양로 125, 7층 (암남동, 냉장인터불고2공장)49273(주)푸드엔씨20161108142159I2018-08-31 23:59:59.0식품운반업383539.60243175767.563913식품운반업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
910식품운반업07_22_09_P32600003260000-117-2011-0000220111205<NA>1영업/정상1영업<NA><NA><NA><NA>051 231 900039.20602030부산광역시 서구 암남동 735 (2층)부산광역시 서구 원양로 189 (암남동)49273(주)이스턴웰스20200729153515U2020-07-31 02:40:00.0식품운반업383161.450357176183.105552식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA><NA>
번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지Unnamed: 47
256257식품운반업07_22_09_P33900003390000-117-2011-0000220110822<NA>3폐업2폐업20150820<NA><NA><NA>070 8169400088.20617831부산광역시 사상구 엄궁동 651-39번지부산광역시 사상구 강변대로456번길 16-8 (엄궁동)47033(주)아이온에프앤지20130115093032I2018-08-31 23:59:59.0식품운반업378870.066218182430.977571식품운반업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
257258식품운반업07_22_09_P33900003390000-117-2012-0000120121123<NA>3폐업2폐업20151210<NA><NA><NA>051 645 636022.30617831부산광역시 사상구 엄궁동 651-14번지 2층부산광역시 사상구 강변대로 458 (엄궁동)47033대상베스트코 주식회사20121220111411I2018-08-31 23:59:59.0식품운반업378882.565675182515.834086식품운반업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA><NA>
258259식품운반업07_22_09_P33900003390000-117-2014-0000120140326<NA>3폐업2폐업20150427<NA><NA><NA>051 325 566937.50617804부산광역시 사상구 감전동 168-22번지 1층부산광역시 사상구 낙동대로1016번길 17, 1층 (감전동)47027천하특수20140514204808I2018-08-31 23:59:59.0식품운반업379764.38968185333.750017식품운반업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
259260식품운반업07_22_09_P33900003390000-117-2015-0000120150604<NA>3폐업2폐업20150619<NA><NA><NA><NA><NA>617721부산광역시 사상구 감전동 152-2번지 부산산업용재유통상가 4동 110호부산광역시 사상구 새벽로 131, 4동 110호 (감전동, 부산산업용재유통상가)46988용달20150604100012I2018-08-31 23:59:59.0식품운반업380482.767624185582.274948식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
260261식품운반업07_22_09_P33900003390000-117-2015-0000220151019<NA>3폐업2폐업20170424<NA><NA><NA><NA>60.00617804부산광역시 사상구 감전동 168-22번지 A동 2층부산광역시 사상구 낙동대로1016번길 17, A동 2층 (감전동)47027연승물류20170424144227I2018-08-31 23:59:59.0식품운반업379764.38968185333.750017식품운반업<NA><NA><NA><NA><NA><NA>0000임대<NA><NA>N0.0<NA><NA><NA><NA>
261262식품운반업07_22_09_P33900003390000-117-2018-0000120180330<NA>3폐업2폐업20190315<NA><NA><NA>051 322 296935.70617828부산광역시 사상구 엄궁동 512-2번지부산광역시 사상구 낙동대로776번길 19, 2층 (엄궁동)47039(주)현대로지스20190315150748U2019-03-17 02:40:00.0식품운반업379707.209193182943.722265식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
262263식품운반업07_22_09_P34000003400000-117-2008-0000220081201<NA>3폐업2폐업20180921<NA><NA><NA><NA><NA>619906부산광역시 기장군 기장읍 청강리 27-1번지부산광역시 기장군 기장읍 기장대로 543-846064세흥물류20180927113118U2018-09-27 23:59:59.0식품운반업401995.797589196084.044896식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
263264식품운반업07_22_09_P34000003400000-117-2011-0000120110831<NA>3폐업2폐업20180921<NA><NA><NA>051 582 458133.04<NA>부산광역시 기장군 정관읍 용수리 449-1번지 A동부산광역시 기장군 정관읍 산막길 60, A동46004동현푸드시스템20180927112056U2018-09-27 23:59:59.0식품운반업397438.831339206240.131848식품운반업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N33.04<NA><NA><NA><NA>
264265식품운반업07_22_09_P34000003400000-117-2017-0000120170822<NA>3폐업2폐업20201125<NA><NA><NA>051 714 3322150.00<NA>부산광역시 기장군 정관읍 달산리 425<NA><NA>(주)성원푸드스토리20201125154729U2020-11-27 02:40:00.0식품운반업398663.970067203653.574238식품운반업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N150.0<NA><NA><NA><NA>
265266식품운반업07_22_09_P34000003400000-117-2018-0000120181218<NA>3폐업2폐업20210120<NA><NA><NA><NA>29.10619906부산광역시 기장군 기장읍 청강리 258 씨앤스타빌부산광역시 기장군 기장읍 기장대로 470, 213호 (씨앤스타빌)46080개별화물20210120113054U2021-01-22 02:40:00.0식품운반업401928.416182195359.203787식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N3.7<NA><NA><NA><NA>