Overview

Dataset statistics

Number of variables40
Number of observations53
Missing cells866
Missing cells (%)40.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.0 KiB
Average record size in memory348.5 B

Variable types

Numeric9
Categorical12
Text7
Unsupported11
DateTime1

Dataset

Description2021-11-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123141

Alerts

개방서비스명 has constant value ""Constant
개방서비스id has constant value ""Constant
저장설비위치 has constant value ""Constant
배관설치장소 has constant value ""Constant
재개업일자 is highly imbalanced (79.8%)Imbalance
도로명우편번호 is highly imbalanced (76.9%)Imbalance
인허가취소일자 has 53 (100.0%) missing valuesMissing
폐업일자 has 29 (54.7%) missing valuesMissing
휴업시작일자 has 47 (88.7%) missing valuesMissing
휴업종료일자 has 47 (88.7%) missing valuesMissing
소재지전화 has 50 (94.3%) missing valuesMissing
소재지면적 has 53 (100.0%) missing valuesMissing
소재지우편번호 has 53 (100.0%) missing valuesMissing
소재지전체주소 has 3 (5.7%) missing valuesMissing
도로명전체주소 has 1 (1.9%) missing valuesMissing
업태구분명 has 53 (100.0%) missing valuesMissing
좌표정보(x) has 1 (1.9%) missing valuesMissing
좌표정보(y) has 1 (1.9%) missing valuesMissing
저장설비위치 has 52 (98.1%) missing valuesMissing
배관설치장소 has 52 (98.1%) missing valuesMissing
길이변경내용 has 53 (100.0%) missing valuesMissing
취급가스용량 has 53 (100.0%) missing valuesMissing
가스용품종류명 has 53 (100.0%) missing valuesMissing
설비명 has 53 (100.0%) missing valuesMissing
물품규격 has 53 (100.0%) missing valuesMissing
면제범위 has 53 (100.0%) missing valuesMissing
Unnamed: 39 has 53 (100.0%) missing valuesMissing
번호 has unique valuesUnique
관리번호 has unique valuesUnique
최종수정시점 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지우편번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
길이변경내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported
취급가스용량 is an unsupported type, check if it needs cleaning or further analysisUnsupported
가스용품종류명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
설비명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
물품규격 is an unsupported type, check if it needs cleaning or further analysisUnsupported
면제범위 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 39 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-16 11:46:09.466453
Analysis finished2024-04-16 11:46:09.875067
Duration0.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct53
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27
Minimum1
Maximum53
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2024-04-16T20:46:10.154999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.6
Q114
median27
Q340
95-th percentile50.4
Maximum53
Range52
Interquartile range (IQR)26

Descriptive statistics

Standard deviation15.443445
Coefficient of variation (CV)0.57197945
Kurtosis-1.2
Mean27
Median Absolute Deviation (MAD)13
Skewness0
Sum1431
Variance238.5
MonotonicityStrictly increasing
2024-04-16T20:46:10.276256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.9%
41 1
 
1.9%
30 1
 
1.9%
31 1
 
1.9%
32 1
 
1.9%
33 1
 
1.9%
34 1
 
1.9%
35 1
 
1.9%
36 1
 
1.9%
37 1
 
1.9%
Other values (43) 43
81.1%
ValueCountFrequency (%)
1 1
1.9%
2 1
1.9%
3 1
1.9%
4 1
1.9%
5 1
1.9%
6 1
1.9%
7 1
1.9%
8 1
1.9%
9 1
1.9%
10 1
1.9%
ValueCountFrequency (%)
53 1
1.9%
52 1
1.9%
51 1
1.9%
50 1
1.9%
49 1
1.9%
48 1
1.9%
47 1
1.9%
46 1
1.9%
45 1
1.9%
44 1
1.9%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size556.0 B
액화석유가스용품제조업체
53 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
액화석유가스용품제조업체 53
100.0%

Length

2024-04-16T20:46:10.402493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:46:10.481070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
액화석유가스용품제조업체 53
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size556.0 B
09_28_09_P
53 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row09_28_09_P
2nd row09_28_09_P
3rd row09_28_09_P
4th row09_28_09_P
5th row09_28_09_P

Common Values

ValueCountFrequency (%)
09_28_09_P 53
100.0%

Length

2024-04-16T20:46:10.563713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:46:10.650524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_28_09_p 53
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)15.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3369622.6
Minimum3310000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2024-04-16T20:46:10.735966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3310000
5-th percentile3340000
Q13360000
median3360000
Q33390000
95-th percentile3394000
Maximum3400000
Range90000
Interquartile range (IQR)30000

Descriptive statistics

Standard deviation21746.995
Coefficient of variation (CV)0.0064538369
Kurtosis-0.59326563
Mean3369622.6
Median Absolute Deviation (MAD)20000
Skewness-0.43945452
Sum1.7859 × 108
Variance4.7293179 × 108
MonotonicityIncreasing
2024-04-16T20:46:10.819771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3390000 20
37.7%
3360000 19
35.8%
3340000 7
 
13.2%
3400000 3
 
5.7%
3310000 1
 
1.9%
3330000 1
 
1.9%
3350000 1
 
1.9%
3380000 1
 
1.9%
ValueCountFrequency (%)
3310000 1
 
1.9%
3330000 1
 
1.9%
3340000 7
 
13.2%
3350000 1
 
1.9%
3360000 19
35.8%
3380000 1
 
1.9%
3390000 20
37.7%
3400000 3
 
5.7%
ValueCountFrequency (%)
3400000 3
 
5.7%
3390000 20
37.7%
3380000 1
 
1.9%
3360000 19
35.8%
3350000 1
 
1.9%
3340000 7
 
13.2%
3330000 1
 
1.9%
3310000 1
 
1.9%

관리번호
Text

UNIQUE 

Distinct53
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size556.0 B
2024-04-16T20:46:10.987423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters1325
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

Unique53 ?
Unique (%)100.0%

Sample

1st row2000331001604100023-00001
2nd row1980333001504100001-00001
3rd row2013334000004100001-00001
4th row2011334008004100002-00001
5th row0000334000004100001-00001
ValueCountFrequency (%)
2000331001604100023-00001 1
 
1.9%
2017336014504100002-00001 1
 
1.9%
1987338006204100001-00001 1
 
1.9%
1997339000004100002-00001 1
 
1.9%
1982339000004100001-00001 1
 
1.9%
2005339000004100001-00001 1
 
1.9%
2016339009104100001-00001 1
 
1.9%
2012339008304100003-00001 1
 
1.9%
1999339000004100001-00001 1
 
1.9%
2001339000004100002-00001 1
 
1.9%
Other values (43) 43
81.1%
2024-04-16T20:46:11.279982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 691
52.2%
1 189
 
14.3%
3 119
 
9.0%
2 76
 
5.7%
4 71
 
5.4%
- 53
 
4.0%
9 43
 
3.2%
6 36
 
2.7%
8 23
 
1.7%
5 17
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1272
96.0%
Dash Punctuation 53
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 691
54.3%
1 189
 
14.9%
3 119
 
9.4%
2 76
 
6.0%
4 71
 
5.6%
9 43
 
3.4%
6 36
 
2.8%
8 23
 
1.8%
5 17
 
1.3%
7 7
 
0.6%
Dash Punctuation
ValueCountFrequency (%)
- 53
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1325
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 691
52.2%
1 189
 
14.3%
3 119
 
9.0%
2 76
 
5.7%
4 71
 
5.4%
- 53
 
4.0%
9 43
 
3.2%
6 36
 
2.7%
8 23
 
1.7%
5 17
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1325
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 691
52.2%
1 189
 
14.3%
3 119
 
9.0%
2 76
 
5.7%
4 71
 
5.4%
- 53
 
4.0%
9 43
 
3.2%
6 36
 
2.7%
8 23
 
1.7%
5 17
 
1.3%

인허가일자
Real number (ℝ)

Distinct52
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20068644
Minimum19800502
Maximum20210405
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2024-04-16T20:46:11.412694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19800502
5-th percentile19862369
Q120020602
median20090504
Q320130923
95-th percentile20171166
Maximum20210405
Range409903
Interquartile range (IQR)110321

Descriptive statistics

Standard deviation96714.688
Coefficient of variation (CV)0.0048191941
Kurtosis0.97099338
Mean20068644
Median Absolute Deviation (MAD)50211
Skewness-1.1820593
Sum1.0636381 × 109
Variance9.3537309 × 109
MonotonicityNot monotonic
2024-04-16T20:46:11.534716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20050408 2
 
3.8%
20001102 1
 
1.9%
20171129 1
 
1.9%
19871203 1
 
1.9%
19971105 1
 
1.9%
19820928 1
 
1.9%
20160613 1
 
1.9%
20120816 1
 
1.9%
19990225 1
 
1.9%
20010822 1
 
1.9%
Other values (42) 42
79.2%
ValueCountFrequency (%)
19800502 1
1.9%
19820928 1
1.9%
19850607 1
1.9%
19870210 1
1.9%
19871203 1
1.9%
19900903 1
1.9%
19971105 1
1.9%
19980508 1
1.9%
19990225 1
1.9%
20001102 1
1.9%
ValueCountFrequency (%)
20210405 1
1.9%
20200312 1
1.9%
20171222 1
1.9%
20171129 1
1.9%
20170906 1
1.9%
20160720 1
1.9%
20160613 1
1.9%
20160503 1
1.9%
20150902 1
1.9%
20150716 1
1.9%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing53
Missing (%)100.0%
Memory size609.0 B

영업상태구분코드
Categorical

Distinct3
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size556.0 B
1
28 
3
24 
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.9%

Sample

1st row3
2nd row3
3rd row1
4th row3
5th row3

Common Values

ValueCountFrequency (%)
1 28
52.8%
3 24
45.3%
2 1
 
1.9%

Length

2024-04-16T20:46:11.636952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:46:11.741724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 28
52.8%
3 24
45.3%
2 1
 
1.9%

영업상태명
Categorical

Distinct3
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size556.0 B
영업/정상
28 
폐업
24 
휴업
 
1

Length

Max length5
Median length5
Mean length3.5849057
Min length2

Unique

Unique1 ?
Unique (%)1.9%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 28
52.8%
폐업 24
45.3%
휴업 1
 
1.9%

Length

2024-04-16T20:46:11.846397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:46:11.930827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 28
52.8%
폐업 24
45.3%
휴업 1
 
1.9%

상세영업상태코드
Categorical

Distinct6
Distinct (%)11.3%
Missing0
Missing (%)0.0%
Memory size556.0 B
3
24 
BBBB
10 
1
8 
5
7 
4
3 

Length

Max length4
Median length1
Mean length1.5660377
Min length1

Unique

Unique1 ?
Unique (%)1.9%

Sample

1st row3
2nd row3
3rd row1
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 24
45.3%
BBBB 10
18.9%
1 8
 
15.1%
5 7
 
13.2%
4 3
 
5.7%
2 1
 
1.9%

Length

2024-04-16T20:46:12.044211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:46:12.157007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 24
45.3%
bbbb 10
18.9%
1 8
 
15.1%
5 7
 
13.2%
4 3
 
5.7%
2 1
 
1.9%

상세영업상태명
Categorical

Distinct6
Distinct (%)11.3%
Missing0
Missing (%)0.0%
Memory size556.0 B
폐지
24 
<NA>
10 
신규
8 
개시
7 
휴지사업재개
3 

Length

Max length6
Median length2
Mean length2.6037736
Min length2

Unique

Unique1 ?
Unique (%)1.9%

Sample

1st row폐지
2nd row폐지
3rd row신규
4th row폐지
5th row폐지

Common Values

ValueCountFrequency (%)
폐지 24
45.3%
<NA> 10
18.9%
신규 8
 
15.1%
개시 7
 
13.2%
휴지사업재개 3
 
5.7%
휴지 1
 
1.9%

Length

2024-04-16T20:46:12.261376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:46:12.355590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐지 24
45.3%
na 10
18.9%
신규 8
 
15.1%
개시 7
 
13.2%
휴지사업재개 3
 
5.7%
휴지 1
 
1.9%

폐업일자
Real number (ℝ)

MISSING 

Distinct21
Distinct (%)87.5%
Missing29
Missing (%)54.7%
Infinite0
Infinite (%)0.0%
Mean20138974
Minimum20090402
Maximum20200522
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2024-04-16T20:46:12.454369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20090402
5-th percentile20090438
Q120110876
median20130418
Q320170802
95-th percentile20188622
Maximum20200522
Range110120
Interquartile range (IQR)59925.5

Descriptive statistics

Standard deviation34668.406
Coefficient of variation (CV)0.0017214584
Kurtosis-1.3548822
Mean20138974
Median Absolute Deviation (MAD)35203.5
Skewness0.12732144
Sum4.8333538 × 108
Variance1.2018984 × 109
MonotonicityNot monotonic
2024-04-16T20:46:12.562950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
20170802 3
 
5.7%
20130220 2
 
3.8%
20160921 1
 
1.9%
20090514 1
 
1.9%
20130320 1
 
1.9%
20110425 1
 
1.9%
20170621 1
 
1.9%
20101223 1
 
1.9%
20130515 1
 
1.9%
20180105 1
 
1.9%
Other values (11) 11
 
20.8%
(Missing) 29
54.7%
ValueCountFrequency (%)
20090402 1
1.9%
20090424 1
1.9%
20090514 1
1.9%
20100721 1
1.9%
20101223 1
1.9%
20110425 1
1.9%
20111027 1
1.9%
20111227 1
1.9%
20121109 1
1.9%
20130220 2
3.8%
ValueCountFrequency (%)
20200522 1
 
1.9%
20190125 1
 
1.9%
20180105 1
 
1.9%
20170811 1
 
1.9%
20170802 3
5.7%
20170707 1
 
1.9%
20170621 1
 
1.9%
20160921 1
 
1.9%
20130820 1
 
1.9%
20130515 1
 
1.9%

휴업시작일자
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)100.0%
Missing47
Missing (%)88.7%
Infinite0
Infinite (%)0.0%
Mean20157321
Minimum20121005
Maximum20171220
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2024-04-16T20:46:12.662894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20121005
5-th percentile20130785
Q120160175
median20160725
Q320167874
95-th percentile20170946
Maximum20171220
Range50215
Interquartile range (IQR)7699.25

Descriptive statistics

Standard deviation18478.678
Coefficient of variation (CV)0.00091672293
Kurtosis4.5796827
Mean20157321
Median Absolute Deviation (MAD)4999.5
Skewness-2.0447306
Sum1.2094392 × 108
Variance3.4146154 × 108
MonotonicityNot monotonic
2024-04-16T20:46:12.753627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
20171220 1
 
1.9%
20160325 1
 
1.9%
20160125 1
 
1.9%
20170124 1
 
1.9%
20161125 1
 
1.9%
20121005 1
 
1.9%
(Missing) 47
88.7%
ValueCountFrequency (%)
20121005 1
1.9%
20160125 1
1.9%
20160325 1
1.9%
20161125 1
1.9%
20170124 1
1.9%
20171220 1
1.9%
ValueCountFrequency (%)
20171220 1
1.9%
20170124 1
1.9%
20161125 1
1.9%
20160325 1
1.9%
20160125 1
1.9%
20121005 1
1.9%

휴업종료일자
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)100.0%
Missing47
Missing (%)88.7%
Infinite0
Infinite (%)0.0%
Mean20165714
Minimum20130405
Maximum20181220
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2024-04-16T20:46:12.842738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20130405
5-th percentile20137980
Q120163206
median20170916
Q320177873
95-th percentile20180946
Maximum20181220
Range50815
Interquartile range (IQR)14667.75

Descriptive statistics

Standard deviation18836.502
Coefficient of variation (CV)0.00093408554
Kurtosis2.9653228
Mean20165714
Median Absolute Deviation (MAD)9709
Skewness-1.667269
Sum1.2099428 × 108
Variance3.5481381 × 108
MonotonicityNot monotonic
2024-04-16T20:46:12.941097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
20181220 1
 
1.9%
20170707 1
 
1.9%
20160705 1
 
1.9%
20180123 1
 
1.9%
20171124 1
 
1.9%
20130405 1
 
1.9%
(Missing) 47
88.7%
ValueCountFrequency (%)
20130405 1
1.9%
20160705 1
1.9%
20170707 1
1.9%
20171124 1
1.9%
20180123 1
1.9%
20181220 1
1.9%
ValueCountFrequency (%)
20181220 1
1.9%
20180123 1
1.9%
20171124 1
1.9%
20170707 1
1.9%
20160705 1
1.9%
20130405 1
1.9%

재개업일자
Categorical

IMBALANCE 

Distinct4
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size556.0 B
<NA>
50 
20160706
 
1
20200814
 
1
20140710
 
1

Length

Max length8
Median length4
Mean length4.2264151
Min length4

Unique

Unique3 ?
Unique (%)5.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 50
94.3%
20160706 1
 
1.9%
20200814 1
 
1.9%
20140710 1
 
1.9%

Length

2024-04-16T20:46:13.060394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:46:13.171989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 50
94.3%
20160706 1
 
1.9%
20200814 1
 
1.9%
20140710 1
 
1.9%

소재지전화
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing50
Missing (%)94.3%
Memory size556.0 B
2024-04-16T20:46:13.268738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters33
Distinct characters9
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

Unique3 ?
Unique (%)100.0%

Sample

1st row051 6113680
2nd row051 5231225
3rd row051 7580337
ValueCountFrequency (%)
051 3
50.0%
6113680 1
 
16.7%
5231225 1
 
16.7%
7580337 1
 
16.7%
2024-04-16T20:46:13.474706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 6
18.2%
1 6
18.2%
0 5
15.2%
3 4
12.1%
3
9.1%
2 3
9.1%
6 2
 
6.1%
8 2
 
6.1%
7 2
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30
90.9%
Space Separator 3
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 6
20.0%
1 6
20.0%
0 5
16.7%
3 4
13.3%
2 3
10.0%
6 2
 
6.7%
8 2
 
6.7%
7 2
 
6.7%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 33
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 6
18.2%
1 6
18.2%
0 5
15.2%
3 4
12.1%
3
9.1%
2 3
9.1%
6 2
 
6.1%
8 2
 
6.1%
7 2
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 33
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 6
18.2%
1 6
18.2%
0 5
15.2%
3 4
12.1%
3
9.1%
2 3
9.1%
6 2
 
6.1%
8 2
 
6.1%
7 2
 
6.1%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing53
Missing (%)100.0%
Memory size609.0 B

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing53
Missing (%)100.0%
Memory size609.0 B

소재지전체주소
Text

MISSING 

Distinct28
Distinct (%)56.0%
Missing3
Missing (%)5.7%
Memory size556.0 B
2024-04-16T20:46:13.633030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length26
Mean length22.82
Min length19

Characters and Unicode

Total characters1141
Distinct characters62
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)36.0%

Sample

1st row부산광역시 남구 용호동 ***번지 * 호
2nd row부산광역시 해운대구 반여동 ****번지 반여*동
3rd row부산광역시 사하구 다대*동 ****번지 *호
4th row부산광역시 사하구 다대동 ****번지 *호
5th row부산광역시 사하구 다대동 ****번지 *호
ValueCountFrequency (%)
부산광역시 50
19.8%
번지 48
19.0%
호 46
18.3%
사상구 19
 
7.5%
강서구 18
 
7.1%
송정동 7
 
2.8%
사하구 6
 
2.4%
다대동 5
 
2.0%
감전동 5
 
2.0%
화전동 4
 
1.6%
Other values (29) 44
17.5%
2024-04-16T20:46:13.923161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 228
20.0%
204
17.9%
동 53
 
4.6%
부 50
 
4.4%
광 50
 
4.4%
역 50
 
4.4%
시 50
 
4.4%
산 50
 
4.4%
지 50
 
4.4%
번 48
 
4.2%
Other values (52) 308
27.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 708
62.1%
Other Punctuation 228
 
20.0%
Space Separator 204
 
17.9%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 53
 
7.5%
부 50
 
7.1%
광 50
 
7.1%
역 50
 
7.1%
시 50
 
7.1%
산 50
 
7.1%
지 50
 
7.1%
번 48
 
6.8%
구 47
 
6.6%
호 47
 
6.6%
Other values (49) 213
30.1%
Other Punctuation
ValueCountFrequency (%)
* 228
100.0%
Space Separator
ValueCountFrequency (%)
204
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 708
62.1%
Common 433
37.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 53
 
7.5%
부 50
 
7.1%
광 50
 
7.1%
역 50
 
7.1%
시 50
 
7.1%
산 50
 
7.1%
지 50
 
7.1%
번 48
 
6.8%
구 47
 
6.6%
호 47
 
6.6%
Other values (49) 213
30.1%
Common
ValueCountFrequency (%)
* 228
52.7%
204
47.1%
- 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 708
62.1%
ASCII 433
37.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 228
52.7%
204
47.1%
- 1
 
0.2%
Hangul
ValueCountFrequency (%)
동 53
 
7.5%
부 50
 
7.1%
광 50
 
7.1%
역 50
 
7.1%
시 50
 
7.1%
산 50
 
7.1%
지 50
 
7.1%
번 48
 
6.8%
구 47
 
6.6%
호 47
 
6.6%
Other values (49) 213
30.1%

도로명전체주소
Text

MISSING 

Distinct48
Distinct (%)92.3%
Missing1
Missing (%)1.9%
Memory size556.0 B
2024-04-16T20:46:14.137271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length30
Mean length26.326923
Min length22

Characters and Unicode

Total characters1369
Distinct characters82
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)86.5%

Sample

1st row부산광역시 남구 용호로***번길 ** (용호동)
2nd row부산광역시 해운대구 반여로**번길 ** (반여동)
3rd row부산광역시 사하구 홍티로 *** (다대동)
4th row부산광역시 사하구 다대로 *** (다대동)
5th row부산광역시 사하구 다산로***번길 ** (다대동)
ValueCountFrequency (%)
부산광역시 52
19.8%
52
19.8%
사상구 20
 
7.6%
강서구 18
 
6.8%
다대동 7
 
2.7%
사하구 7
 
2.7%
송정동 7
 
2.7%
감전동 5
 
1.9%
학장동 4
 
1.5%
삼락동 4
 
1.5%
Other values (60) 87
33.1%
2024-04-16T20:46:14.480361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
223
16.3%
* 211
15.4%
산 79
 
5.8%
동 60
 
4.4%
부 53
 
3.9%
시 53
 
3.9%
광 52
 
3.8%
역 52
 
3.8%
) 50
 
3.7%
( 50
 
3.7%
Other values (72) 486
35.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 827
60.4%
Space Separator 223
 
16.3%
Other Punctuation 213
 
15.6%
Close Punctuation 50
 
3.7%
Open Punctuation 50
 
3.7%
Dash Punctuation 6
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 79
 
9.6%
동 60
 
7.3%
부 53
 
6.4%
시 53
 
6.4%
광 52
 
6.3%
역 52
 
6.3%
구 50
 
6.0%
로 49
 
5.9%
사 34
 
4.1%
상 26
 
3.1%
Other values (66) 319
38.6%
Other Punctuation
ValueCountFrequency (%)
* 211
99.1%
, 2
 
0.9%
Space Separator
ValueCountFrequency (%)
223
100.0%
Close Punctuation
ValueCountFrequency (%)
) 50
100.0%
Open Punctuation
ValueCountFrequency (%)
( 50
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 827
60.4%
Common 542
39.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 79
 
9.6%
동 60
 
7.3%
부 53
 
6.4%
시 53
 
6.4%
광 52
 
6.3%
역 52
 
6.3%
구 50
 
6.0%
로 49
 
5.9%
사 34
 
4.1%
상 26
 
3.1%
Other values (66) 319
38.6%
Common
ValueCountFrequency (%)
223
41.1%
* 211
38.9%
) 50
 
9.2%
( 50
 
9.2%
- 6
 
1.1%
, 2
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 827
60.4%
ASCII 542
39.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
223
41.1%
* 211
38.9%
) 50
 
9.2%
( 50
 
9.2%
- 6
 
1.1%
, 2
 
0.4%
Hangul
ValueCountFrequency (%)
산 79
 
9.6%
동 60
 
7.3%
부 53
 
6.4%
시 53
 
6.4%
광 52
 
6.3%
역 52
 
6.3%
구 50
 
6.0%
로 49
 
5.9%
사 34
 
4.1%
상 26
 
3.1%
Other values (66) 319
38.6%

도로명우편번호
Categorical

IMBALANCE 

Distinct5
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Memory size556.0 B
<NA>
49 
46739
 
1
46751
 
1
46925
 
1
46028
 
1

Length

Max length5
Median length4
Mean length4.0754717
Min length4

Unique

Unique4 ?
Unique (%)7.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 49
92.5%
46739 1
 
1.9%
46751 1
 
1.9%
46925 1
 
1.9%
46028 1
 
1.9%

Length

2024-04-16T20:46:14.618472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:46:14.722122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 49
92.5%
46739 1
 
1.9%
46751 1
 
1.9%
46925 1
 
1.9%
46028 1
 
1.9%

사업장명
Text

Distinct51
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Memory size556.0 B
2024-04-16T20:46:14.910916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length7.4528302
Min length2

Characters and Unicode

Total characters395
Distinct characters120
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)92.5%

Sample

1st row(주)삼정지텍
2nd row(주)성철사
3rd row부영CST(주)
4th row(주)진원에너지
5th row삼주이엔지(주)
ValueCountFrequency (%)
주)로커스 2
 
3.4%
주식회사 2
 
3.4%
주)엔에스브이 2
 
3.4%
주)ms이엔지 1
 
1.7%
주)디케이코리아 1
 
1.7%
성화퓨렌텍(주 1
 
1.7%
태연기계(주 1
 
1.7%
주)삼정지텍 1
 
1.7%
주)한신주방냉동 1
 
1.7%
주)티와이밸브 1
 
1.7%
Other values (45) 45
77.6%
2024-04-16T20:46:15.229321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 47
 
11.9%
( 41
 
10.4%
) 41
 
10.4%
이 16
 
4.1%
동 9
 
2.3%
엔 9
 
2.3%
지 8
 
2.0%
스 8
 
2.0%
에 7
 
1.8%
영 7
 
1.8%
Other values (110) 202
51.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 298
75.4%
Open Punctuation 41
 
10.4%
Close Punctuation 41
 
10.4%
Space Separator 5
 
1.3%
Uppercase Letter 5
 
1.3%
Other Punctuation 2
 
0.5%
Decimal Number 2
 
0.5%
Other Symbol 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 47
 
15.8%
이 16
 
5.4%
동 9
 
3.0%
엔 9
 
3.0%
지 8
 
2.7%
스 8
 
2.7%
에 7
 
2.3%
영 7
 
2.3%
사 6
 
2.0%
브 6
 
2.0%
Other values (100) 175
58.7%
Uppercase Letter
ValueCountFrequency (%)
S 2
40.0%
M 1
20.0%
C 1
20.0%
T 1
20.0%
Open Punctuation
ValueCountFrequency (%)
( 41
100.0%
Close Punctuation
ValueCountFrequency (%)
) 41
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Decimal Number
ValueCountFrequency (%)
2 2
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 299
75.7%
Common 91
 
23.0%
Latin 5
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 47
 
15.7%
이 16
 
5.4%
동 9
 
3.0%
엔 9
 
3.0%
지 8
 
2.7%
스 8
 
2.7%
에 7
 
2.3%
영 7
 
2.3%
사 6
 
2.0%
브 6
 
2.0%
Other values (101) 176
58.9%
Common
ValueCountFrequency (%)
( 41
45.1%
) 41
45.1%
5
 
5.5%
. 2
 
2.2%
2 2
 
2.2%
Latin
ValueCountFrequency (%)
S 2
40.0%
M 1
20.0%
C 1
20.0%
T 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 298
75.4%
ASCII 96
 
24.3%
None 1
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 47
 
15.8%
이 16
 
5.4%
동 9
 
3.0%
엔 9
 
3.0%
지 8
 
2.7%
스 8
 
2.7%
에 7
 
2.3%
영 7
 
2.3%
사 6
 
2.0%
브 6
 
2.0%
Other values (100) 175
58.7%
ASCII
ValueCountFrequency (%)
( 41
42.7%
) 41
42.7%
5
 
5.2%
S 2
 
2.1%
. 2
 
2.1%
2 2
 
2.1%
M 1
 
1.0%
C 1
 
1.0%
T 1
 
1.0%
None
ValueCountFrequency (%)
㈜ 1
100.0%

최종수정시점
Real number (ℝ)

UNIQUE 

Distinct53
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0153958 × 1013
Minimum2.0081208 × 1013
Maximum2.0210422 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2024-04-16T20:46:15.359790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0081208 × 1013
5-th percentile2.0090472 × 1013
Q12.013022 × 1013
median2.0170124 × 1013
Q32.0190125 × 1013
95-th percentile2.0204817 × 1013
Maximum2.0210422 × 1013
Range1.2921398 × 1011
Interquartile range (IQR)5.9905011 × 1010

Descriptive statistics

Standard deviation3.7281543 × 1010
Coefficient of variation (CV)0.0018498373
Kurtosis-1.1897356
Mean2.0153958 × 1013
Median Absolute Deviation (MAD)3.1097981 × 1010
Skewness-0.16787022
Sum1.0681598 × 1015
Variance1.3899135 × 1021
MonotonicityNot monotonic
2024-04-16T20:46:15.483969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20131223183309 1
 
1.9%
20130220141225 1
 
1.9%
20200525135138 1
 
1.9%
20111124132650 1
 
1.9%
20131227090648 1
 
1.9%
20121224125237 1
 
1.9%
20170622103735 1
 
1.9%
20130220141105 1
 
1.9%
20170802155326 1
 
1.9%
20200612151604 1
 
1.9%
Other values (43) 43
81.1%
ValueCountFrequency (%)
20081208114557 1
1.9%
20090402165054 1
1.9%
20090424105548 1
1.9%
20090504162114 1
1.9%
20101223143229 1
1.9%
20111028102249 1
1.9%
20111124131610 1
1.9%
20111124131936 1
1.9%
20111124132650 1
1.9%
20111124133742 1
1.9%
ValueCountFrequency (%)
20210422093022 1
1.9%
20210405111350 1
1.9%
20210209160215 1
1.9%
20201222162537 1
1.9%
20201126110506 1
1.9%
20201012102102 1
1.9%
20200612151604 1
1.9%
20200525135138 1
1.9%
20200312122707 1
1.9%
20191122164037 1
1.9%

데이터갱신구분
Categorical

Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size556.0 B
I
40 
U
13 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 40
75.5%
U 13
 
24.5%

Length

2024-04-16T20:46:15.591094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:46:15.676598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 40
75.5%
u 13
 
24.5%

데이터갱신일자
Date

Distinct14
Distinct (%)26.4%
Missing0
Missing (%)0.0%
Memory size556.0 B
Minimum2018-08-31 23:59:59
Maximum2021-04-24 02:40:00
2024-04-16T20:46:15.756245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T20:46:15.853982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing53
Missing (%)100.0%
Memory size609.0 B

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct48
Distinct (%)92.3%
Missing1
Missing (%)1.9%
Infinite0
Infinite (%)0.0%
Mean378784.13
Minimum366283.76
Maximum404935.13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2024-04-16T20:46:15.967836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum366283.76
5-th percentile366536.76
Q1371800.38
median379478.07
Q3380781.06
95-th percentile395272.06
Maximum404935.13
Range38651.369
Interquartile range (IQR)8980.6797

Descriptive statistics

Standard deviation8813.3344
Coefficient of variation (CV)0.023267433
Kurtosis1.19709
Mean378784.13
Median Absolute Deviation (MAD)1670.5735
Skewness0.9368999
Sum19696775
Variance77674862
MonotonicityNot monotonic
2024-04-16T20:46:16.085673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
368332.893732899 2
 
3.8%
378413.574560936 2
 
3.8%
379478.073383396 2
 
3.8%
371800.38350847 2
 
3.8%
392659.272186462 1
 
1.9%
380424.626814252 1
 
1.9%
380662.221300304 1
 
1.9%
380421.27471075 1
 
1.9%
379681.412491666 1
 
1.9%
380179.253802645 1
 
1.9%
Other values (38) 38
71.7%
ValueCountFrequency (%)
366283.763436367 1
1.9%
366339.309102189 1
1.9%
366508.430641887 1
1.9%
366559.944406805 1
1.9%
366820.624748879 1
1.9%
368332.893732899 2
3.8%
368809.131108164 1
1.9%
369138.00073361 1
1.9%
369205.300369499 1
1.9%
370980.505870352 1
1.9%
ValueCountFrequency (%)
404935.132929677 1
1.9%
401571.529104974 1
1.9%
397424.5377 1
1.9%
393510.950917748 1
1.9%
393047.761414082 1
1.9%
392659.272186462 1
1.9%
392611.231858214 1
1.9%
381380.797313785 1
1.9%
381309.137499976 1
1.9%
380988.15621424 1
1.9%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct48
Distinct (%)92.3%
Missing1
Missing (%)1.9%
Infinite0
Infinite (%)0.0%
Mean184782.11
Minimum174047.05
Maximum210694.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2024-04-16T20:46:16.198270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum174047.05
5-th percentile175305.14
Q1179182.29
median184424.91
Q3188770.1
95-th percentile194573.69
Maximum210694.5
Range36647.456
Interquartile range (IQR)9587.8194

Descriptive statistics

Standard deviation7084.9597
Coefficient of variation (CV)0.038342239
Kurtosis2.9421675
Mean184782.11
Median Absolute Deviation (MAD)4520.2362
Skewness1.1788028
Sum9608669.5
Variance50196654
MonotonicityNot monotonic
2024-04-16T20:46:16.548398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
179182.285025321 2
 
3.8%
175266.882245717 2
 
3.8%
183851.624687518 2
 
3.8%
179167.833899393 2
 
3.8%
180879.100680878 1
 
1.9%
188607.731311688 1
 
1.9%
184377.881592412 1
 
1.9%
188899.976931052 1
 
1.9%
183568.234731376 1
 
1.9%
189413.798368555 1
 
1.9%
Other values (38) 38
71.7%
ValueCountFrequency (%)
174047.04848343 1
1.9%
175266.882245717 2
3.8%
175336.448679095 1
1.9%
175608.897194753 1
1.9%
175824.972895513 1
1.9%
175897.724166058 1
1.9%
178558.543841281 1
1.9%
178670.641502038 1
1.9%
178820.014655955 1
1.9%
179167.833899393 2
3.8%
ValueCountFrequency (%)
210694.504433192 1
1.9%
204577.937815 1
1.9%
195031.174650049 1
1.9%
194199.382353559 1
1.9%
192010.138424136 1
1.9%
190729.150048601 1
1.9%
190461.558005079 1
1.9%
189413.798368555 1
1.9%
188953.493284539 1
1.9%
188936.794366248 1
1.9%

저장설비위치
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing52
Missing (%)98.1%
Memory size556.0 B
2024-04-16T20:46:16.696791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5
Distinct characters5
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row동 번지내
ValueCountFrequency (%)
동 1
50.0%
번지내 1
50.0%
2024-04-16T20:46:16.919130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 1
20.0%
1
20.0%
번 1
20.0%
지 1
20.0%
내 1
20.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4
80.0%
Space Separator 1
 
20.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1
25.0%
번 1
25.0%
지 1
25.0%
내 1
25.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4
80.0%
Common 1
 
20.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1
25.0%
번 1
25.0%
지 1
25.0%
내 1
25.0%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4
80.0%
ASCII 1
 
20.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 1
25.0%
번 1
25.0%
지 1
25.0%
내 1
25.0%
ASCII
ValueCountFrequency (%)
1
100.0%

용기저장실면적
Categorical

Distinct4
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size556.0 B
0.0
38 
<NA>
13 
52.0
 
1
551.1
 
1

Length

Max length5
Median length3
Mean length3.3018868
Min length3

Unique

Unique2 ?
Unique (%)3.8%

Sample

1st row0.0
2nd row0.0
3rd row<NA>
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 38
71.7%
<NA> 13
 
24.5%
52.0 1
 
1.9%
551.1 1
 
1.9%

Length

2024-04-16T20:46:17.036301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:46:17.130839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 38
71.7%
na 13
 
24.5%
52.0 1
 
1.9%
551.1 1
 
1.9%

차고지면적
Categorical

Distinct3
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size556.0 B
0
39 
<NA>
13 
24
 
1

Length

Max length4
Median length1
Mean length1.754717
Min length1

Unique

Unique1 ?
Unique (%)1.9%

Sample

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

Common Values

ValueCountFrequency (%)
0 39
73.6%
<NA> 13
 
24.5%
24 1
 
1.9%

Length

2024-04-16T20:46:17.219971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:46:17.301948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 39
73.6%
na 13
 
24.5%
24 1
 
1.9%

사무실면적
Categorical

Distinct3
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size556.0 B
0
39 
<NA>
13 
50
 
1

Length

Max length4
Median length1
Mean length1.754717
Min length1

Unique

Unique1 ?
Unique (%)1.9%

Sample

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

Common Values

ValueCountFrequency (%)
0 39
73.6%
<NA> 13
 
24.5%
50 1
 
1.9%

Length

2024-04-16T20:46:17.394551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:46:17.484875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 39
73.6%
na 13
 
24.5%
50 1
 
1.9%

배관설치장소
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing52
Missing (%)98.1%
Memory size556.0 B
2024-04-16T20:46:17.566123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row부지내
ValueCountFrequency (%)
부지내 1
100.0%
2024-04-16T20:46:17.755548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
부 1
33.3%
지 1
33.3%
내 1
33.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 1
33.3%
지 1
33.3%
내 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 1
33.3%
지 1
33.3%
내 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
부 1
33.3%
지 1
33.3%
내 1
33.3%

길이변경내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing53
Missing (%)100.0%
Memory size609.0 B

취급가스용량
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing53
Missing (%)100.0%
Memory size609.0 B

가스용품종류명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing53
Missing (%)100.0%
Memory size609.0 B

설비명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing53
Missing (%)100.0%
Memory size609.0 B

물품규격
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing53
Missing (%)100.0%
Memory size609.0 B

면제범위
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing53
Missing (%)100.0%
Memory size609.0 B

Unnamed: 39
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing53
Missing (%)100.0%
Memory size609.0 B

Sample

번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)저장설비위치용기저장실면적차고지면적사무실면적배관설치장소길이변경내용취급가스용량가스용품종류명설비명물품규격면제범위Unnamed: 39
01액화석유가스용품제조업체09_28_09_P33100002000331001604100023-0000120001102<NA>3폐업3폐지20100721<NA><NA><NA>051 6113680<NA><NA>부산광역시 남구 용호동 ***번지 * 호부산광역시 남구 용호로***번길 ** (용호동)<NA>(주)삼정지텍20131223183309I2018-08-31 23:59:59.0<NA>392659.272186180879.100681<NA>0.000<NA><NA><NA><NA><NA><NA><NA><NA>
12액화석유가스용품제조업체09_28_09_P33300001980333001504100001-0000119800502<NA>3폐업3폐지20160921<NA><NA><NA>051 5231225<NA><NA>부산광역시 해운대구 반여동 ****번지 반여*동부산광역시 해운대구 반여로**번길 ** (반여동)<NA>(주)성철사20180105144520I2018-08-31 23:59:59.0<NA>393047.761414190729.150049<NA>0.000<NA><NA><NA><NA><NA><NA><NA><NA>
23액화석유가스용품제조업체09_28_09_P33400002013334000004100001-0000120130412<NA>1영업/정상1신규<NA><NA><NA><NA><NA><NA><NA><NA>부산광역시 사하구 홍티로 *** (다대동)<NA>부영CST(주)20130513172124I2018-08-31 23:59:59.0<NA>378706.672591175608.897195<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
34액화석유가스용품제조업체09_28_09_P33400002011334008004100002-0000120111227<NA>3폐업3폐지20111227<NA><NA><NA><NA><NA><NA>부산광역시 사하구 다대*동 ****번지 *호부산광역시 사하구 다대로 *** (다대동)<NA>(주)진원에너지20210422093022U2021-04-24 02:40:00.0<NA>378961.382513174047.048483<NA>0.000<NA><NA><NA><NA><NA><NA><NA><NA>
45액화석유가스용품제조업체09_28_09_P33400000000334000004100001-0000119980508<NA>3폐업3폐지20130820<NA><NA><NA><NA><NA><NA>부산광역시 사하구 다대동 ****번지 *호부산광역시 사하구 다산로***번길 ** (다대동)<NA>삼주이엔지(주)20130902162033I2018-08-31 23:59:59.0<NA>378376.888163175897.724166<NA>0.000<NA><NA><NA><NA><NA><NA><NA><NA>
56액화석유가스용품제조업체09_28_09_P33400002008334006604100002-0000120081216<NA>3폐업3폐지20090424<NA><NA><NA><NA><NA><NA>부산광역시 사하구 다대동 ****번지 *호부산광역시 사하구 다산로**번길 ** (다대동)<NA>주식회사 동강금속20090424105548I2018-08-31 23:59:59.0<NA>378413.574561175266.882246<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
67액화석유가스용품제조업체09_28_09_P33400002014334008004100001-0000120140314<NA>1영업/정상5개시<NA><NA><NA><NA><NA><NA><NA>부산광역시 사하구 다대동 ****번지 *호부산광역시 사하구 다산로**번길 ** (다대동)<NA>(주)동강금속20170124181159I2018-08-31 23:59:59.0<NA>378413.574561175266.882246<NA>0.000<NA><NA><NA><NA><NA><NA><NA><NA>
78액화석유가스용품제조업체09_28_09_P33400002014334008004100002-0000120140715<NA>1영업/정상5개시<NA><NA><NA><NA><NA><NA><NA>부산광역시 사하구 다대동 ****번지 *호부산광역시 사하구 다산로***번길 ** (다대동)<NA>(주)아미인터내셔널20150401085405I2018-08-31 23:59:59.0<NA>378565.368291175824.972896<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
89액화석유가스용품제조업체09_28_09_P33400002015334008004100001-0000120150610<NA>1영업/정상5개시<NA><NA><NA><NA><NA><NA><NA>부산광역시 사하구 다대동 ****번지 *호부산광역시 사하구 다산로 ** (다대동)<NA>(주)코밸20160405183357I2018-08-31 23:59:59.0<NA>378627.693913175336.448679<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
910액화석유가스용품제조업체09_28_09_P33500001996335000004100004-0000120090713<NA>1영업/정상1신규<NA><NA><NA><NA><NA><NA><NA>부산광역시 금정구 회동동 ***번지부산광역시 금정구 동대로 ** (회동동)<NA>우영종합주방설비20131226110824I2018-08-31 23:59:59.0<NA>393510.950918194199.382354동 번지내52.02450부지내<NA><NA><NA><NA><NA><NA><NA>
번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)저장설비위치용기저장실면적차고지면적사무실면적배관설치장소길이변경내용취급가스용량가스용품종류명설비명물품규격면제범위Unnamed: 39
4344액화석유가스용품제조업체09_28_09_P33900002008339006604100001-0000120081219<NA>3폐업3폐지20170802<NA><NA><NA><NA><NA><NA>부산광역시 사상구 감전동 ***번지 **호부산광역시 사상구 새벽시장로 **-** (감전동)<NA>(주)승리사20170802155247I2018-08-31 23:59:59.0<NA>380032.766091186018.266944<NA>0.000<NA><NA><NA><NA><NA><NA><NA><NA>
4445액화석유가스용품제조업체09_28_09_P33900002012339008304100002-0000120120801<NA>3폐업3폐지20130320<NA><NA><NA><NA><NA><NA>부산광역시 사상구 삼락동 ***번지 **호부산광역시 사상구 낙동대로****번길 ** (삼락동)<NA>씨.에이.브이20130320144918I2018-08-31 23:59:59.0<NA>380250.818153188010.542154<NA>551.100<NA><NA><NA><NA><NA><NA><NA><NA>
4546액화석유가스용품제조업체09_28_09_P33900002012339008304100001-0000120120511<NA>1영업/정상4휴지사업재개<NA><NA><NA>20140710<NA><NA><NA>부산광역시 사상구 감전동 ***번지 **호부산광역시 사상구 학감대로 ***-** (감전동)<NA>에스씨알엔디20170628152919I2018-08-31 23:59:59.0<NA>381380.797314185266.398486<NA>0.000<NA><NA><NA><NA><NA><NA><NA><NA>
4647액화석유가스용품제조업체09_28_09_P33900002020339009104100001-0000120200312<NA>1영업/정상BBBB<NA><NA><NA><NA><NA><NA><NA><NA>부산광역시 사상구 모라동 ***번지 *호 에이동부산광역시 사상구 모덕로**번길 **, 에이동 (모라동)46925(주)극동이엔지20200312122707I2020-03-15 00:23:23.0<NA>380962.194828188936.794366<NA>0.000<NA><NA><NA><NA><NA><NA><NA><NA>
4748액화석유가스용품제조업체09_28_09_P33900001987339000004100001-0000119870210<NA>1영업/정상BBBB<NA><NA><NA><NA><NA><NA><NA><NA>부산광역시 사상구 감전동 ***번지 **호부산광역시 사상구 낙동대로 *** (감전동)<NA>동아공업사20111124133742I2018-08-31 23:59:59.0<NA>379478.073383183851.624688<NA>0.000<NA><NA><NA><NA><NA><NA><NA><NA>
4849액화석유가스용품제조업체09_28_09_P33900001990339000004100001-0000119900903<NA>1영업/정상BBBB<NA><NA><NA><NA><NA><NA><NA><NA>부산광역시 사상구 학장동 ***번지 *호부산광역시 사상구 학장로 *** (학장동)<NA>(주)MS이엔지20201126110506U2020-11-28 02:40:00.0<NA>380847.349925184429.806177<NA>0.000<NA><NA><NA><NA><NA><NA><NA><NA>
4950액화석유가스용품제조업체09_28_09_P33900002002339000004100003-0000120021115<NA>1영업/정상BBBB<NA><NA><NA><NA><NA><NA><NA><NA>부산광역시 사상구 감전동 ***번지 **호부산광역시 사상구 낙동대로 *** (감전동)<NA>세원엔지니어링20111124131936I2018-08-31 23:59:59.0<NA>379478.073383183851.624688<NA>0.000<NA><NA><NA><NA><NA><NA><NA><NA>
5051액화석유가스용품제조업체09_28_09_P34000001999340000004100001-0000120090504<NA>3폐업3폐지20090514<NA><NA><NA><NA><NA><NA>부산광역시 기장군 기장읍 청강리 ***번지 *호부산광역시 기장군 기장읍 기장대로***번길 **<NA>태연기계(주)20090504162114I2018-08-31 23:59:59.0<NA>401571.529105195031.17465<NA>0.000<NA><NA><NA><NA><NA><NA><NA><NA>
5152액화석유가스용품제조업체09_28_09_P34000002013340004404100002-0000120130923<NA>1영업/정상5개시<NA><NA><NA><NA><NA><NA><NA>부산광역시 기장군 정관면 매학리 ***번지 *호부산광역시 기장군 정관면 정관상곡*길 **-**<NA>성화퓨렌텍(주)20171109133028I2018-08-31 23:59:59.0<NA>397424.5377204577.937815<NA>0.000<NA><NA><NA><NA><NA><NA><NA><NA>
5253액화석유가스용품제조업체09_28_09_P34000002017340010904100002-0000120171222<NA>1영업/정상BBBB<NA><NA><NA><NA><NA><NA><NA><NA>부산광역시 기장군 장안읍 명례리 ***번지 **호부산광역시 기장군 장안읍 명례산단*로 ***46028케이티엘㈜20181107112158U2018-11-09 02:37:59.0<NA>404935.13293210694.504433<NA>0.000<NA><NA><NA><NA><NA><NA><NA><NA>