Overview

Dataset statistics

Number of variables52
Number of observations82
Missing cells1794
Missing cells (%)42.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory36.5 KiB
Average record size in memory455.6 B

Variable types

Numeric20
Categorical13
Unsupported12
Text6
DateTime1

Dataset

Description2021-06-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123165

Alerts

개방서비스명 has constant value ""Constant
개방서비스id has constant value ""Constant
개방자치단체코드 has constant value ""Constant
사업장구분명 has constant value ""Constant
실험실도로명주소건물부번호 is highly imbalanced (66.2%)Imbalance
인허가취소일자 has 82 (100.0%) missing valuesMissing
폐업일자 has 41 (50.0%) missing valuesMissing
휴업시작일자 has 82 (100.0%) missing valuesMissing
휴업종료일자 has 82 (100.0%) missing valuesMissing
재개업일자 has 82 (100.0%) missing valuesMissing
소재지전화 has 75 (91.5%) missing valuesMissing
소재지면적 has 82 (100.0%) missing valuesMissing
소재지우편번호 has 22 (26.8%) missing valuesMissing
소재지전체주소 has 21 (25.6%) missing valuesMissing
도로명우편번호 has 12 (14.6%) missing valuesMissing
업태구분명 has 82 (100.0%) missing valuesMissing
좌표정보(x) has 3 (3.7%) missing valuesMissing
좌표정보(y) has 3 (3.7%) missing valuesMissing
실험실면적 has 63 (76.8%) missing valuesMissing
영업소면적 has 82 (100.0%) missing valuesMissing
위탁업체명 has 82 (100.0%) missing valuesMissing
실험실지역코드 has 47 (57.3%) missing valuesMissing
실험실우편번호 has 47 (57.3%) missing valuesMissing
실험실번지 has 47 (57.3%) missing valuesMissing
실험실호 has 52 (63.4%) missing valuesMissing
실험실통 has 82 (100.0%) missing valuesMissing
실험실반 has 82 (100.0%) missing valuesMissing
실험실특수주소 has 73 (89.0%) missing valuesMissing
실험실특수주소동 has 82 (100.0%) missing valuesMissing
실험실특수주소호 has 80 (97.6%) missing valuesMissing
실험실도로명주소시군구코드 has 31 (37.8%) missing valuesMissing
실험실도로명주소읍면동코드 has 31 (37.8%) missing valuesMissing
실험실도로명주소코드 has 31 (37.8%) missing valuesMissing
실험실도로명특수주소 has 69 (84.1%) missing valuesMissing
실험실도로명주소건물본번호 has 31 (37.8%) missing valuesMissing
실험실도로명주소우편번호 has 31 (37.8%) missing valuesMissing
Unnamed: 51 has 82 (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
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
소재지면적 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
영업소면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
위탁업체명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
실험실통 is an unsupported type, check if it needs cleaning or further analysisUnsupported
실험실반 is an unsupported type, check if it needs cleaning or further analysisUnsupported
실험실특수주소동 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 51 is an unsupported type, check if it needs cleaning or further analysisUnsupported
실험실면적 has 1 (1.2%) zerosZeros

Reproduction

Analysis started2024-04-17 20:04:22.175462
Analysis finished2024-04-17 20:04:22.640174
Duration0.46 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct82
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41.5
Minimum1
Maximum82
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2024-04-18T05:04:22.696023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.05
Q121.25
median41.5
Q361.75
95-th percentile77.95
Maximum82
Range81
Interquartile range (IQR)40.5

Descriptive statistics

Standard deviation23.815261
Coefficient of variation (CV)0.57386172
Kurtosis-1.2
Mean41.5
Median Absolute Deviation (MAD)20.5
Skewness0
Sum3403
Variance567.16667
MonotonicityStrictly increasing
2024-04-18T05:04:22.802322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.2%
63 1
 
1.2%
61 1
 
1.2%
60 1
 
1.2%
59 1
 
1.2%
58 1
 
1.2%
57 1
 
1.2%
56 1
 
1.2%
55 1
 
1.2%
54 1
 
1.2%
Other values (72) 72
87.8%
ValueCountFrequency (%)
1 1
1.2%
2 1
1.2%
3 1
1.2%
4 1
1.2%
5 1
1.2%
6 1
1.2%
7 1
1.2%
8 1
1.2%
9 1
1.2%
10 1
1.2%
ValueCountFrequency (%)
82 1
1.2%
81 1
1.2%
80 1
1.2%
79 1
1.2%
78 1
1.2%
77 1
1.2%
76 1
1.2%
75 1
1.2%
74 1
1.2%
73 1
1.2%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size788.0 B
환경측정대행업
82 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
환경측정대행업 82
100.0%

Length

2024-04-18T05:04:22.903652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:04:22.981242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
환경측정대행업 82
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size788.0 B
09_30_17_P
82 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row09_30_17_P
2nd row09_30_17_P
3rd row09_30_17_P
4th row09_30_17_P
5th row09_30_17_P

Common Values

ValueCountFrequency (%)
09_30_17_P 82
100.0%

Length

2024-04-18T05:04:23.054080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:04:23.123701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_30_17_p 82
100.0%

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size788.0 B
6260000
82 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row6260000
2nd row6260000
3rd row6260000
4th row6260000
5th row6260000

Common Values

ValueCountFrequency (%)
6260000 82
100.0%

Length

2024-04-18T05:04:23.197342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:04:23.272089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
6260000 82
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct82
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.2600001 × 1017
Minimum6.2600001 × 1017
Maximum6.2600001 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2024-04-18T05:04:23.355965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6.2600001 × 1017
5-th percentile6.2600001 × 1017
Q16.2600001 × 1017
median6.2600001 × 1017
Q36.2600001 × 1017
95-th percentile6.2600001 × 1017
Maximum6.2600001 × 1017
Range1500000
Interquartile range (IQR)1200000

Descriptive statistics

Standard deviation581786.02
Coefficient of variation (CV)9.2937062 × 10-13
Kurtosis-1.7484956
Mean6.2600001 × 1017
Median Absolute Deviation (MAD)649984
Skewness0.018166844
Sum-4.0082315 × 1018
Variance3.3847497 × 1011
MonotonicityNot monotonic
2024-04-18T05:04:23.461811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
626000008200600018 1
 
1.2%
626000008202000007 1
 
1.2%
626000008201900002 1
 
1.2%
626000008201900006 1
 
1.2%
626000008201900001 1
 
1.2%
626000008200700003 1
 
1.2%
626000008200700002 1
 
1.2%
626000008200700001 1
 
1.2%
626000008200600019 1
 
1.2%
626000008200600015 1
 
1.2%
Other values (72) 72
87.8%
ValueCountFrequency (%)
626000008200600001 1
1.2%
626000008200600002 1
1.2%
626000008200600003 1
1.2%
626000008200600004 1
1.2%
626000008200600005 1
1.2%
626000008200600006 1
1.2%
626000008200600007 1
1.2%
626000008200600008 1
1.2%
626000008200600009 1
1.2%
626000008200600010 1
1.2%
ValueCountFrequency (%)
626000008202100001 1
1.2%
626000008202000017 1
1.2%
626000008202000016 1
1.2%
626000008202000015 1
1.2%
626000008202000014 1
1.2%
626000008202000013 1
1.2%
626000008202000012 1
1.2%
626000008202000011 1
1.2%
626000008202000010 1
1.2%
626000008202000009 1
1.2%

인허가일자
Real number (ℝ)

Distinct68
Distinct (%)82.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20170264
Minimum20060728
Maximum20210423
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2024-04-18T05:04:23.570982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20060728
5-th percentile20081477
Q120131204
median20195160
Q320210202
95-th percentile20210412
Maximum20210423
Range149695
Interquartile range (IQR)78997.25

Descriptive statistics

Standard deviation46784.525
Coefficient of variation (CV)0.0023194801
Kurtosis-0.57034054
Mean20170264
Median Absolute Deviation (MAD)15162.5
Skewness-0.96395555
Sum1.6539616 × 109
Variance2.1887918 × 109
MonotonicityNot monotonic
2024-04-18T05:04:23.679528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190218 3
 
3.7%
20210423 3
 
3.7%
20200204 3
 
3.7%
20210309 2
 
2.4%
20210406 2
 
2.4%
20200103 2
 
2.4%
20210324 2
 
2.4%
20160829 2
 
2.4%
20210302 2
 
2.4%
20210404 2
 
2.4%
Other values (58) 59
72.0%
ValueCountFrequency (%)
20060728 1
1.2%
20070607 1
1.2%
20070705 1
1.2%
20070911 1
1.2%
20081022 1
1.2%
20090121 1
1.2%
20090302 1
1.2%
20090310 1
1.2%
20100120 1
1.2%
20100122 1
1.2%
ValueCountFrequency (%)
20210423 3
3.7%
20210413 1
 
1.2%
20210412 1
 
1.2%
20210408 1
 
1.2%
20210406 2
2.4%
20210404 2
2.4%
20210324 2
2.4%
20210322 1
 
1.2%
20210311 1
 
1.2%
20210309 2
2.4%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing82
Missing (%)100.0%
Memory size870.0 B

영업상태구분코드
Categorical

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size788.0 B
3
52 
1
30 

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 52
63.4%
1 30
36.6%

Length

2024-04-18T05:04:23.779376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:04:23.865679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 52
63.4%
1 30
36.6%

영업상태명
Categorical

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size788.0 B
폐업
52 
영업/정상
30 

Length

Max length5
Median length2
Mean length3.097561
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 52
63.4%
영업/정상 30
36.6%

Length

2024-04-18T05:04:23.948100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:04:24.025879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 52
63.4%
영업/정상 30
36.6%

상세영업상태코드
Categorical

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size788.0 B
Q
52 
N
30 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
Q 52
63.4%
N 30
36.6%

Length

2024-04-18T05:04:24.101586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:04:24.174611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
q 52
63.4%
n 30
36.6%

상세영업상태명
Categorical

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size788.0 B
폐업
52 
신규
30 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 52
63.4%
신규 30
36.6%

Length

2024-04-18T05:04:24.253585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:04:24.325497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 52
63.4%
신규 30
36.6%

폐업일자
Real number (ℝ)

MISSING 

Distinct33
Distinct (%)80.5%
Missing41
Missing (%)50.0%
Infinite0
Infinite (%)0.0%
Mean20143694
Minimum20070406
Maximum20210128
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2024-04-18T05:04:24.415081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20070406
5-th percentile20080609
Q120100830
median20150330
Q320181024
95-th percentile20200218
Maximum20210128
Range139722
Interquartile range (IQR)80194

Descriptive statistics

Standard deviation43421.922
Coefficient of variation (CV)0.0021556086
Kurtosis-1.5690521
Mean20143694
Median Absolute Deviation (MAD)39889
Skewness-0.11717851
Sum8.2589147 × 108
Variance1.8854633 × 109
MonotonicityNot monotonic
2024-04-18T05:04:24.535370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
20190219 5
 
6.1%
20181024 3
 
3.7%
20180109 3
 
3.7%
20110331 1
 
1.2%
20110802 1
 
1.2%
20181019 1
 
1.2%
20180523 1
 
1.2%
20190131 1
 
1.2%
20181105 1
 
1.2%
20200218 1
 
1.2%
Other values (23) 23
28.0%
(Missing) 41
50.0%
ValueCountFrequency (%)
20070406 1
1.2%
20070625 1
1.2%
20080609 1
1.2%
20090217 1
1.2%
20090729 1
1.2%
20100122 1
1.2%
20100407 1
1.2%
20100527 1
1.2%
20100706 1
1.2%
20100714 1
1.2%
ValueCountFrequency (%)
20210128 1
 
1.2%
20200424 1
 
1.2%
20200218 1
 
1.2%
20190219 5
6.1%
20190131 1
 
1.2%
20181105 1
 
1.2%
20181024 3
3.7%
20181019 1
 
1.2%
20180523 1
 
1.2%
20180109 3
3.7%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing82
Missing (%)100.0%
Memory size870.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing82
Missing (%)100.0%
Memory size870.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing82
Missing (%)100.0%
Memory size870.0 B

소재지전화
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)100.0%
Missing75
Missing (%)91.5%
Infinite0
Infinite (%)0.0%
Mean5.1488528 × 108
Minimum5.1201996 × 108
Maximum5.1912897 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2024-04-18T05:04:24.619980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.1201996 × 108
5-th percentile5.1202191 × 108
Q15.1233494 × 108
median5.1502012 × 108
Q35.16679 × 108
95-th percentile5.1852219 × 108
Maximum5.1912897 × 108
Range7109009
Interquartile range (IQR)4344057.5

Descriptive statistics

Standard deviation2775971
Coefficient of variation (CV)0.005391436
Kurtosis-1.3794851
Mean5.1488528 × 108
Median Absolute Deviation (MAD)2376693
Skewness0.34663122
Sum3.6041969 × 109
Variance7.7060149 × 1012
MonotonicityNot monotonic
2024-04-18T05:04:24.725143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
516251618 1
 
1.2%
512019961 1
 
1.2%
517106379 1
 
1.2%
515020123 1
 
1.2%
512643430 1
 
1.2%
512026452 1
 
1.2%
519128970 1
 
1.2%
(Missing) 75
91.5%
ValueCountFrequency (%)
512019961 1
1.2%
512026452 1
1.2%
512643430 1
1.2%
515020123 1
1.2%
516251618 1
1.2%
517106379 1
1.2%
519128970 1
1.2%
ValueCountFrequency (%)
519128970 1
1.2%
517106379 1
1.2%
516251618 1
1.2%
515020123 1
1.2%
512643430 1
1.2%
512026452 1
1.2%
512019961 1
1.2%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing82
Missing (%)100.0%
Memory size870.0 B

소재지우편번호
Real number (ℝ)

MISSING 

Distinct39
Distinct (%)65.0%
Missing22
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean470237.93
Minimum46213
Maximum619952
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2024-04-18T05:04:25.107436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46213
5-th percentile46677.65
Q1463129.25
median607840
Q3612050
95-th percentile618860.45
Maximum619952
Range573739
Interquartile range (IQR)148920.75

Descriptive statistics

Standard deviation246185.19
Coefficient of variation (CV)0.52353324
Kurtosis-0.61958109
Mean470237.93
Median Absolute Deviation (MAD)6415
Skewness-1.1833306
Sum28214276
Variance6.0607147 × 1010
MonotonicityNot monotonic
2024-04-18T05:04:25.199209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
607840 5
 
6.1%
609817 3
 
3.7%
607823 3
 
3.7%
609843 3
 
3.7%
619952 3
 
3.7%
612050 2
 
2.4%
609806 2
 
2.4%
618803 2
 
2.4%
617809 2
 
2.4%
617819 2
 
2.4%
Other values (29) 33
40.2%
(Missing) 22
26.8%
ValueCountFrequency (%)
46213 2
2.4%
46253 1
1.2%
46700 1
1.2%
46916 2
2.4%
46917 1
1.2%
46980 1
1.2%
47295 1
1.2%
47505 1
1.2%
47829 1
1.2%
48288 1
1.2%
ValueCountFrequency (%)
619952 3
3.7%
618803 2
2.4%
618270 1
 
1.2%
617819 2
2.4%
617809 2
2.4%
617801 1
 
1.2%
616853 2
2.4%
614836 1
 
1.2%
612050 2
2.4%
609843 3
3.7%

소재지전체주소
Text

MISSING 

Distinct45
Distinct (%)73.8%
Missing21
Missing (%)25.6%
Memory size788.0 B
2024-04-18T05:04:25.432365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length34
Mean length25.852459
Min length18

Characters and Unicode

Total characters1577
Distinct characters96
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)55.7%

Sample

1st row부산광역시 동구 초량3동 1158번지 7호
2nd row부산광역시 강서구 송정동 1569번지 8호
3rd row부산광역시 금정구 부곡2동 280번지 2호
4th row부산광역시 사하구 하단동 1158번지 106동 2호
5th row부산광역시 연제구 거제동 121-14 화신빌딩 304호호
ValueCountFrequency (%)
부산광역시 61
 
20.1%
금정구 16
 
5.3%
동래구 11
 
3.6%
사상구 9
 
3.0%
사하구 8
 
2.6%
2호 7
 
2.3%
온천3동 5
 
1.7%
1379-14 5
 
1.7%
청룡동 5
 
1.7%
강서구 4
 
1.3%
Other values (110) 172
56.8%
2024-04-18T05:04:25.774040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
329
20.9%
부 73
 
4.6%
동 73
 
4.6%
산 70
 
4.4%
1 69
 
4.4%
2 62
 
3.9%
광 61
 
3.9%
역 61
 
3.9%
시 61
 
3.9%
구 61
 
3.9%
Other values (86) 657
41.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 898
56.9%
Space Separator 329
 
20.9%
Decimal Number 319
 
20.2%
Dash Punctuation 23
 
1.5%
Other Punctuation 8
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 73
 
8.1%
동 73
 
8.1%
산 70
 
7.8%
광 61
 
6.8%
역 61
 
6.8%
시 61
 
6.8%
구 61
 
6.8%
지 46
 
5.1%
번 43
 
4.8%
호 37
 
4.1%
Other values (72) 312
34.7%
Decimal Number
ValueCountFrequency (%)
1 69
21.6%
2 62
19.4%
3 32
10.0%
8 32
10.0%
4 29
9.1%
5 29
9.1%
0 25
 
7.8%
7 16
 
5.0%
9 13
 
4.1%
6 12
 
3.8%
Other Punctuation
ValueCountFrequency (%)
, 7
87.5%
. 1
 
12.5%
Space Separator
ValueCountFrequency (%)
329
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 898
56.9%
Common 679
43.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 73
 
8.1%
동 73
 
8.1%
산 70
 
7.8%
광 61
 
6.8%
역 61
 
6.8%
시 61
 
6.8%
구 61
 
6.8%
지 46
 
5.1%
번 43
 
4.8%
호 37
 
4.1%
Other values (72) 312
34.7%
Common
ValueCountFrequency (%)
329
48.5%
1 69
 
10.2%
2 62
 
9.1%
3 32
 
4.7%
8 32
 
4.7%
4 29
 
4.3%
5 29
 
4.3%
0 25
 
3.7%
- 23
 
3.4%
7 16
 
2.4%
Other values (4) 33
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 898
56.9%
ASCII 679
43.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
329
48.5%
1 69
 
10.2%
2 62
 
9.1%
3 32
 
4.7%
8 32
 
4.7%
4 29
 
4.3%
5 29
 
4.3%
0 25
 
3.7%
- 23
 
3.4%
7 16
 
2.4%
Other values (4) 33
 
4.9%
Hangul
ValueCountFrequency (%)
부 73
 
8.1%
동 73
 
8.1%
산 70
 
7.8%
광 61
 
6.8%
역 61
 
6.8%
시 61
 
6.8%
구 61
 
6.8%
지 46
 
5.1%
번 43
 
4.8%
호 37
 
4.1%
Other values (72) 312
34.7%

도로명전체주소
Text

Distinct57
Distinct (%)69.5%
Missing0
Missing (%)0.0%
Memory size788.0 B
2024-04-18T05:04:26.075959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length41
Mean length29.817073
Min length17

Characters and Unicode

Total characters2445
Distinct characters152
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

Unique42 ?
Unique (%)51.2%

Sample

1st row부산광역시 동구 중앙대로 298, 1층 (초량동,부산YWCA)
2nd row부산광역시 강서구 녹산산단261로31번길 10 (송정동)
3rd row부산광역시 금정구 금강로 298-1, A동 102호 (장전동)
4th row부산광역시 동래구 아시아드대로255번길 9, B동 2층 1호 (온천동,미도빌딩)
5th row부산광역시 강서구 대저로29번길 54 (대저1동)
ValueCountFrequency (%)
부산광역시 81
 
17.8%
금정구 21
 
4.6%
동래구 12
 
2.6%
사상구 10
 
2.2%
사하구 9
 
2.0%
중앙대로 8
 
1.8%
부곡동 8
 
1.8%
온천동 7
 
1.5%
37 7
 
1.5%
강서구 7
 
1.5%
Other values (163) 284
62.6%
2024-04-18T05:04:26.447107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
372
 
15.2%
동 105
 
4.3%
부 100
 
4.1%
산 100
 
4.1%
시 83
 
3.4%
광 82
 
3.4%
로 82
 
3.4%
역 81
 
3.3%
구 80
 
3.3%
1 78
 
3.2%
Other values (142) 1282
52.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1460
59.7%
Decimal Number 400
 
16.4%
Space Separator 372
 
15.2%
Open Punctuation 75
 
3.1%
Close Punctuation 75
 
3.1%
Other Punctuation 49
 
2.0%
Uppercase Letter 7
 
0.3%
Dash Punctuation 6
 
0.2%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 105
 
7.2%
부 100
 
6.8%
산 100
 
6.8%
시 83
 
5.7%
광 82
 
5.6%
로 82
 
5.6%
역 81
 
5.5%
구 80
 
5.5%
번 44
 
3.0%
길 41
 
2.8%
Other values (120) 662
45.3%
Decimal Number
ValueCountFrequency (%)
1 78
19.5%
2 63
15.8%
3 63
15.8%
7 41
10.2%
5 34
8.5%
0 31
 
7.8%
9 30
 
7.5%
4 24
 
6.0%
8 20
 
5.0%
6 16
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
B 2
28.6%
A 2
28.6%
W 1
14.3%
Y 1
14.3%
C 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 48
98.0%
. 1
 
2.0%
Space Separator
ValueCountFrequency (%)
372
100.0%
Open Punctuation
ValueCountFrequency (%)
( 75
100.0%
Close Punctuation
ValueCountFrequency (%)
) 75
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1460
59.7%
Common 978
40.0%
Latin 7
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 105
 
7.2%
부 100
 
6.8%
산 100
 
6.8%
시 83
 
5.7%
광 82
 
5.6%
로 82
 
5.6%
역 81
 
5.5%
구 80
 
5.5%
번 44
 
3.0%
길 41
 
2.8%
Other values (120) 662
45.3%
Common
ValueCountFrequency (%)
372
38.0%
1 78
 
8.0%
( 75
 
7.7%
) 75
 
7.7%
2 63
 
6.4%
3 63
 
6.4%
, 48
 
4.9%
7 41
 
4.2%
5 34
 
3.5%
0 31
 
3.2%
Other values (7) 98
 
10.0%
Latin
ValueCountFrequency (%)
B 2
28.6%
A 2
28.6%
W 1
14.3%
Y 1
14.3%
C 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1460
59.7%
ASCII 985
40.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
372
37.8%
1 78
 
7.9%
( 75
 
7.6%
) 75
 
7.6%
2 63
 
6.4%
3 63
 
6.4%
, 48
 
4.9%
7 41
 
4.2%
5 34
 
3.5%
0 31
 
3.1%
Other values (12) 105
 
10.7%
Hangul
ValueCountFrequency (%)
동 105
 
7.2%
부 100
 
6.8%
산 100
 
6.8%
시 83
 
5.7%
광 82
 
5.6%
로 82
 
5.6%
역 81
 
5.5%
구 80
 
5.5%
번 44
 
3.0%
길 41
 
2.8%
Other values (120) 662
45.3%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct40
Distinct (%)57.1%
Missing12
Missing (%)14.6%
Infinite0
Infinite (%)0.0%
Mean370093.01
Minimum46020
Maximum619952
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2024-04-18T05:04:26.550313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46020
5-th percentile46231
Q146980
median607830
Q3609853
95-th percentile619434.95
Maximum619952
Range573932
Interquartile range (IQR)562873

Descriptive statistics

Standard deviation281654.44
Coefficient of variation (CV)0.76103691
Kurtosis-1.9696101
Mean370093.01
Median Absolute Deviation (MAD)10973
Skewness-0.29450705
Sum25906511
Variance7.9329225 × 1010
MonotonicityNot monotonic
2024-04-18T05:04:26.645047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
607837 6
 
7.3%
609817 4
 
4.9%
619952 4
 
4.9%
46257 3
 
3.7%
46700 3
 
3.7%
607823 3
 
3.7%
46607 3
 
3.7%
617819 2
 
2.4%
612050 2
 
2.4%
618803 2
 
2.4%
Other values (30) 38
46.3%
(Missing) 12
 
14.6%
ValueCountFrequency (%)
46020 1
 
1.2%
46023 1
 
1.2%
46213 2
2.4%
46253 1
 
1.2%
46257 3
3.7%
46607 3
3.7%
46700 3
3.7%
46916 2
2.4%
46917 1
 
1.2%
46980 2
2.4%
ValueCountFrequency (%)
619952 4
4.9%
618803 2
2.4%
618270 1
 
1.2%
617819 2
2.4%
617809 2
2.4%
617801 1
 
1.2%
616853 2
2.4%
612050 2
2.4%
612020 1
 
1.2%
609853 2
2.4%

사업장명
Text

Distinct57
Distinct (%)69.5%
Missing0
Missing (%)0.0%
Memory size788.0 B
2024-04-18T05:04:26.796329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length17
Mean length9.9512195
Min length4

Characters and Unicode

Total characters816
Distinct characters124
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)54.9%

Sample

1st row(주)한국환경기술연구원
2nd row부산녹산표면처리사업협동조합
3rd row(유)동성기건
4th row(주)대한생활환경시험원
5th row천호환경(주)
ValueCountFrequency (%)
주)대성기술단 5
 
5.4%
주)대한환경이엔지 5
 
5.4%
천호환경(주 4
 
4.3%
한국종합환경산업(주 3
 
3.2%
세영환경산업주식회사 3
 
3.2%
그린컨기술(주 3
 
3.2%
주)고성인텍 3
 
3.2%
금호환경(주 3
 
3.2%
주식회사 3
 
3.2%
주)유림환경기술연구소 2
 
2.2%
Other values (55) 59
63.4%
2024-04-18T05:04:27.083164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 71
 
8.7%
( 69
 
8.5%
) 69
 
8.5%
경 46
 
5.6%
환 43
 
5.3%
기 23
 
2.8%
술 22
 
2.7%
산 21
 
2.6%
한 18
 
2.2%
대 17
 
2.1%
Other values (114) 417
51.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 662
81.1%
Open Punctuation 69
 
8.5%
Close Punctuation 69
 
8.5%
Space Separator 11
 
1.3%
Uppercase Letter 3
 
0.4%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 71
 
10.7%
경 46
 
6.9%
환 43
 
6.5%
기 23
 
3.5%
술 22
 
3.3%
산 21
 
3.2%
한 18
 
2.7%
대 17
 
2.6%
엔 17
 
2.6%
지 17
 
2.6%
Other values (107) 367
55.4%
Uppercase Letter
ValueCountFrequency (%)
G 1
33.3%
E 1
33.3%
N 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 69
100.0%
Close Punctuation
ValueCountFrequency (%)
) 69
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 662
81.1%
Common 151
 
18.5%
Latin 3
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 71
 
10.7%
경 46
 
6.9%
환 43
 
6.5%
기 23
 
3.5%
술 22
 
3.3%
산 21
 
3.2%
한 18
 
2.7%
대 17
 
2.6%
엔 17
 
2.6%
지 17
 
2.6%
Other values (107) 367
55.4%
Common
ValueCountFrequency (%)
( 69
45.7%
) 69
45.7%
11
 
7.3%
, 2
 
1.3%
Latin
ValueCountFrequency (%)
G 1
33.3%
E 1
33.3%
N 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 662
81.1%
ASCII 154
 
18.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 71
 
10.7%
경 46
 
6.9%
환 43
 
6.5%
기 23
 
3.5%
술 22
 
3.3%
산 21
 
3.2%
한 18
 
2.7%
대 17
 
2.6%
엔 17
 
2.6%
지 17
 
2.6%
Other values (107) 367
55.4%
ASCII
ValueCountFrequency (%)
( 69
44.8%
) 69
44.8%
11
 
7.1%
, 2
 
1.3%
G 1
 
0.6%
E 1
 
0.6%
N 1
 
0.6%

최종수정시점
Real number (ℝ)

UNIQUE 

Distinct82
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0175172 × 1013
Minimum2.0070502 × 1013
Maximum2.0210423 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2024-04-18T05:04:27.208610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0070502 × 1013
5-th percentile2.0100626 × 1013
Q12.0150616 × 1013
median2.0200223 × 1013
Q32.0210202 × 1013
95-th percentile2.0210412 × 1013
Maximum2.0210423 × 1013
Range1.3992104 × 1011
Interquartile range (IQR)5.958583 × 1010

Descriptive statistics

Standard deviation4.2421773 × 1010
Coefficient of variation (CV)0.0021026722
Kurtosis-0.34038054
Mean2.0175172 × 1013
Median Absolute Deviation (MAD)1.0183457 × 1010
Skewness-1.0728686
Sum1.6543641 × 1015
Variance1.7996068 × 1021
MonotonicityNot monotonic
2024-04-18T05:04:27.321411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20210309170032 1
 
1.2%
20200401145054 1
 
1.2%
20190219110928 1
 
1.2%
20200226153534 1
 
1.2%
20190219110315 1
 
1.2%
20150514095155 1
 
1.2%
20090217152815 1
 
1.2%
20140107173231 1
 
1.2%
20070706132119 1
 
1.2%
20111006173418 1
 
1.2%
Other values (72) 72
87.8%
ValueCountFrequency (%)
20070502140747 1
1.2%
20070706132119 1
1.2%
20090217152815 1
1.2%
20090701100844 1
1.2%
20100622174553 1
1.2%
20100707141204 1
1.2%
20100813171031 1
1.2%
20100830171842 1
1.2%
20110321142404 1
1.2%
20110321142518 1
1.2%
ValueCountFrequency (%)
20210423185426 1
1.2%
20210423184524 1
1.2%
20210423183920 1
1.2%
20210413140450 1
1.2%
20210412171139 1
1.2%
20210408131417 1
1.2%
20210406145613 1
1.2%
20210406095025 1
1.2%
20210404170524 1
1.2%
20210404164832 1
1.2%

데이터갱신구분
Categorical

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size788.0 B
U
45 
I
37 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 45
54.9%
I 37
45.1%

Length

2024-04-18T05:04:27.425794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:04:27.508876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 45
54.9%
i 37
45.1%

데이터갱신일자
Date

Distinct41
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size788.0 B
Minimum2018-10-07 02:37:41
Maximum2021-04-25 02:40:00
2024-04-18T05:04:27.590789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T05:04:27.694848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing82
Missing (%)100.0%
Memory size870.0 B

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct51
Distinct (%)64.6%
Missing3
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean387341.31
Minimum368156.79
Maximum405926.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2024-04-18T05:04:27.837451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum368156.79
5-th percentile378272.57
Q1380891.01
median388316.45
Q3390624.26
95-th percentile401602.65
Maximum405926.8
Range37770.011
Interquartile range (IQR)9733.2413

Descriptive statistics

Standard deviation7196.4362
Coefficient of variation (CV)0.018579057
Kurtosis0.66418175
Mean387341.31
Median Absolute Deviation (MAD)5142.4537
Skewness0.43115601
Sum30599963
Variance51788694
MonotonicityNot monotonic
2024-04-18T05:04:27.943781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
388316.452069542 5
 
6.1%
390635.137540559 4
 
4.9%
380903.012198435 4
 
4.9%
390144.111432534 3
 
3.7%
382672.631194153 3
 
3.7%
405397.470560958 3
 
3.7%
385468.443590649 3
 
3.7%
393386.0 3
 
3.7%
390367.318070624 2
 
2.4%
390624.256291267 2
 
2.4%
Other values (41) 47
57.3%
(Missing) 3
 
3.7%
ValueCountFrequency (%)
368156.792775172 1
1.2%
378026.0 2
2.4%
378144.813953837 1
1.2%
378286.764936367 1
1.2%
378295.67187469 1
1.2%
378304.006203882 1
1.2%
378638.300284091 1
1.2%
378688.012044293 1
1.2%
379122.254409162 1
1.2%
379240.573215267 1
1.2%
ValueCountFrequency (%)
405926.804044414 1
 
1.2%
405397.470560958 3
3.7%
401181.0 1
 
1.2%
398326.0 1
 
1.2%
394035.249095 1
 
1.2%
393852.668534593 1
 
1.2%
393753.865371337 1
 
1.2%
393561.58646018 2
2.4%
393458.905760378 1
 
1.2%
393386.0 3
3.7%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct51
Distinct (%)64.6%
Missing3
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean191447.35
Minimum176725.71
Maximum206746.79
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2024-04-18T05:04:28.045349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum176725.71
5-th percentile178544.32
Q1187772.34
median191178.01
Q3194734.19
95-th percentile205196.18
Maximum206746.79
Range30021.083
Interquartile range (IQR)6961.8494

Descriptive statistics

Standard deviation6915.8504
Coefficient of variation (CV)0.036124034
Kurtosis0.28014946
Mean191447.35
Median Absolute Deviation (MAD)3614.3652
Skewness0.067365715
Sum15124340
Variance47828987
MonotonicityNot monotonic
2024-04-18T05:04:28.142689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
191178.011028057 5
 
6.1%
195758.9159577 4
 
4.9%
190017.436488015 4
 
4.9%
190453.524937101 3
 
3.7%
193516.569100917 3
 
3.7%
206746.790462324 3
 
3.7%
192213.626512424 3
 
3.7%
194676.0 3
 
3.7%
199349.001778398 2
 
2.4%
193959.335175462 2
 
2.4%
Other values (41) 47
57.3%
(Missing) 3
 
3.7%
ValueCountFrequency (%)
176725.707798423 1
1.2%
176872.406241001 1
1.2%
177979.117100246 1
1.2%
178241.088617495 1
1.2%
178578.014065165 1
1.2%
179262.158331989 1
1.2%
181228.694796122 1
1.2%
181413.478007094 1
1.2%
181434.090196654 1
1.2%
182353.593813228 1
1.2%
ValueCountFrequency (%)
206746.790462324 3
3.7%
206457.785803911 1
 
1.2%
205056.0 1
 
1.2%
204522.0 1
 
1.2%
199385.436227116 1
 
1.2%
199349.001778398 2
2.4%
199344.588896397 2
2.4%
199255.499468693 1
 
1.2%
195960.376067716 2
2.4%
195760.835575276 1
 
1.2%

실험실면적
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)52.6%
Missing63
Missing (%)76.8%
Infinite0
Infinite (%)0.0%
Mean108.01
Minimum0
Maximum392
Zeros1
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size870.0 B
2024-04-18T05:04:28.229170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile41.58
Q166.5
median83.38
Q3117.43
95-th percentile269.375
Maximum392
Range392
Interquartile range (IQR)50.93

Descriptive statistics

Standard deviation85.880439
Coefficient of variation (CV)0.79511563
Kurtosis6.629934
Mean108.01
Median Absolute Deviation (MAD)16.88
Skewness2.3798271
Sum2052.19
Variance7375.4498
MonotonicityNot monotonic
2024-04-18T05:04:28.318625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
66.5 5
 
6.1%
138.61 3
 
3.7%
83.38 3
 
3.7%
93.48 2
 
2.4%
0.0 1
 
1.2%
96.25 1
 
1.2%
392.0 1
 
1.2%
76.56 1
 
1.2%
46.2 1
 
1.2%
255.75 1
 
1.2%
(Missing) 63
76.8%
ValueCountFrequency (%)
0.0 1
 
1.2%
46.2 1
 
1.2%
66.5 5
6.1%
76.56 1
 
1.2%
83.38 3
3.7%
93.48 2
 
2.4%
96.25 1
 
1.2%
138.61 3
3.7%
255.75 1
 
1.2%
392.0 1
 
1.2%
ValueCountFrequency (%)
392.0 1
 
1.2%
255.75 1
 
1.2%
138.61 3
3.7%
96.25 1
 
1.2%
93.48 2
 
2.4%
83.38 3
3.7%
76.56 1
 
1.2%
66.5 5
6.1%
46.2 1
 
1.2%
0.0 1
 
1.2%

사업장구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size788.0 B
측정대행업
82 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
측정대행업 82
100.0%

Length

2024-04-18T05:04:28.439468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:04:28.516660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
측정대행업 82
100.0%

영업소면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing82
Missing (%)100.0%
Memory size870.0 B

위탁업체명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing82
Missing (%)100.0%
Memory size870.0 B

실험실지역코드
Real number (ℝ)

MISSING 

Distinct17
Distinct (%)48.6%
Missing47
Missing (%)57.3%
Infinite0
Infinite (%)0.0%
Mean2.6402404 × 109
Minimum2.6230108 × 109
Maximum2.6710253 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2024-04-18T05:04:28.606746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.6230108 × 109
5-th percentile2.6260106 × 109
Q12.6260108 × 109
median2.6410107 × 109
Q32.6440105 × 109
95-th percentile2.6710253 × 109
Maximum2.6710253 × 109
Range48014531
Interquartile range (IQR)17999700

Descriptive statistics

Standard deviation13406335
Coefficient of variation (CV)0.0050776948
Kurtosis0.33448837
Mean2.6402404 × 109
Median Absolute Deviation (MAD)11999500
Skewness0.82317436
Sum9.2408415 × 1010
Variance1.7972982 × 1014
MonotonicityNot monotonic
2024-04-18T05:04:28.717854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
2626010800 6
 
7.3%
2641010900 5
 
6.1%
2671025331 3
 
3.7%
2626010600 3
 
3.7%
2653010200 2
 
2.4%
2641010700 2
 
2.4%
2638010500 2
 
2.4%
2644010100 2
 
2.4%
2653010400 2
 
2.4%
2638010400 1
 
1.2%
Other values (7) 7
 
8.5%
(Missing) 47
57.3%
ValueCountFrequency (%)
2623010800 1
 
1.2%
2626010600 3
3.7%
2626010800 6
7.3%
2626010900 1
 
1.2%
2632010200 1
 
1.2%
2638010400 1
 
1.2%
2638010500 2
 
2.4%
2641010300 1
 
1.2%
2641010400 1
 
1.2%
2641010700 2
 
2.4%
ValueCountFrequency (%)
2671025331 3
3.7%
2653010500 1
 
1.2%
2653010400 2
 
2.4%
2653010200 2
 
2.4%
2644010900 1
 
1.2%
2644010100 2
 
2.4%
2641010900 5
6.1%
2641010700 2
 
2.4%
2641010400 1
 
1.2%
2641010300 1
 
1.2%

실험실우편번호
Real number (ℝ)

MISSING 

Distinct23
Distinct (%)65.7%
Missing47
Missing (%)57.3%
Infinite0
Infinite (%)0.0%
Mean514953.57
Minimum46253
Maximum619952
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2024-04-18T05:04:28.821782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46253
5-th percentile46851.2
Q1607823
median609310
Q3615844.5
95-th percentile619952
Maximum619952
Range573699
Interquartile range (IQR)8021.5

Descriptive statistics

Standard deviation215848.13
Coefficient of variation (CV)0.41916037
Kurtosis1.3954691
Mean514953.57
Median Absolute Deviation (MAD)4464
Skewness-1.8208384
Sum18023375
Variance4.6590416 × 1010
MonotonicityNot monotonic
2024-04-18T05:04:28.930270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
607842 5
 
6.1%
609817 3
 
3.7%
607823 3
 
3.7%
619952 3
 
3.7%
609310 2
 
2.4%
617809 2
 
2.4%
49478 1
 
1.2%
616853 1
 
1.2%
46253 1
 
1.2%
46917 1
 
1.2%
Other values (13) 13
 
15.9%
(Missing) 47
57.3%
ValueCountFrequency (%)
46253 1
 
1.2%
46700 1
 
1.2%
46916 1
 
1.2%
46917 1
 
1.2%
47829 1
 
1.2%
49478 1
 
1.2%
604834 1
 
1.2%
604846 1
 
1.2%
607823 3
3.7%
607837 1
 
1.2%
ValueCountFrequency (%)
619952 3
3.7%
618803 1
 
1.2%
618270 1
 
1.2%
617809 2
2.4%
617801 1
 
1.2%
616853 1
 
1.2%
614836 1
 
1.2%
609843 1
 
1.2%
609817 3
3.7%
609815 1
 
1.2%

실험실산
Categorical

Distinct3
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size788.0 B
<NA>
45 
1
31 
0
6 

Length

Max length4
Median length4
Mean length2.6463415
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row1
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 45
54.9%
1 31
37.8%
0 6
 
7.3%

Length

2024-04-18T05:04:29.049803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:04:29.129072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 45
54.9%
1 31
37.8%
0 6
 
7.3%

실험실번지
Real number (ℝ)

MISSING 

Distinct20
Distinct (%)57.1%
Missing47
Missing (%)57.3%
Infinite0
Infinite (%)0.0%
Mean718.71429
Minimum15
Maximum2377
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2024-04-18T05:04:29.206550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15
5-th percentile15
Q180
median580
Q31379
95-th percentile1794
Maximum2377
Range2362
Interquartile range (IQR)1299

Descriptive statistics

Standard deviation677.35049
Coefficient of variation (CV)0.94244751
Kurtosis-0.14267296
Mean718.71429
Median Absolute Deviation (MAD)540
Skewness0.79439128
Sum25155
Variance458803.68
MonotonicityNot monotonic
2024-04-18T05:04:29.291332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
15 5
 
6.1%
1379 5
 
6.1%
850 3
 
3.7%
40 3
 
3.7%
80 2
 
2.4%
420 2
 
2.4%
580 2
 
2.4%
2377 1
 
1.2%
161 1
 
1.2%
627 1
 
1.2%
Other values (10) 10
 
12.2%
(Missing) 47
57.3%
ValueCountFrequency (%)
15 5
6.1%
40 3
3.7%
80 2
 
2.4%
137 1
 
1.2%
161 1
 
1.2%
282 1
 
1.2%
283 1
 
1.2%
420 2
 
2.4%
580 2
 
2.4%
581 1
 
1.2%
ValueCountFrequency (%)
2377 1
 
1.2%
2319 1
 
1.2%
1569 1
 
1.2%
1550 1
 
1.2%
1428 1
 
1.2%
1379 5
6.1%
1089 1
 
1.2%
952 1
 
1.2%
850 3
3.7%
627 1
 
1.2%

실험실호
Real number (ℝ)

MISSING 

Distinct15
Distinct (%)50.0%
Missing52
Missing (%)63.4%
Infinite0
Infinite (%)0.0%
Mean14.433333
Minimum1
Maximum53
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2024-04-18T05:04:29.370747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.45
Q14
median13
Q321.75
95-th percentile44.45
Maximum53
Range52
Interquartile range (IQR)17.75

Descriptive statistics

Standard deviation13.512914
Coefficient of variation (CV)0.93622962
Kurtosis2.7885873
Mean14.433333
Median Absolute Deviation (MAD)9
Skewness1.6071852
Sum433
Variance182.59885
MonotonicityNot monotonic
2024-04-18T05:04:29.458616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
14 6
 
7.3%
2 4
 
4.9%
22 4
 
4.9%
1 2
 
2.4%
12 2
 
2.4%
4 2
 
2.4%
53 2
 
2.4%
8 1
 
1.2%
25 1
 
1.2%
11 1
 
1.2%
Other values (5) 5
 
6.1%
(Missing) 52
63.4%
ValueCountFrequency (%)
1 2
 
2.4%
2 4
4.9%
3 1
 
1.2%
4 2
 
2.4%
5 1
 
1.2%
6 1
 
1.2%
8 1
 
1.2%
11 1
 
1.2%
12 2
 
2.4%
14 6
7.3%
ValueCountFrequency (%)
53 2
 
2.4%
34 1
 
1.2%
25 1
 
1.2%
22 4
4.9%
21 1
 
1.2%
14 6
7.3%
12 2
 
2.4%
11 1
 
1.2%
8 1
 
1.2%
6 1
 
1.2%

실험실통
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing82
Missing (%)100.0%
Memory size870.0 B

실험실반
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing82
Missing (%)100.0%
Memory size870.0 B

실험실특수주소
Text

MISSING 

Distinct6
Distinct (%)66.7%
Missing73
Missing (%)89.0%
Memory size788.0 B
2024-04-18T05:04:29.583970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length11
Mean length9
Min length2

Characters and Unicode

Total characters81
Distinct characters29
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)44.4%

Sample

1st row신대성빌딩
2nd row금호환경산업사
3rd row장안일반산업단지
4th row혜인빌딩 2,4,5층
5th row3층
ValueCountFrequency (%)
장안일반산업단지 3
25.0%
대성빌딩 2
16.7%
15-25신대성빌딩 2
16.7%
신대성빌딩 1
 
8.3%
금호환경산업사 1
 
8.3%
혜인빌딩 1
 
8.3%
2,4,5층 1
 
8.3%
3층 1
 
8.3%
2024-04-18T05:04:29.802379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
빌 6
 
7.4%
딩 6
 
7.4%
성 5
 
6.2%
5 5
 
6.2%
대 5
 
6.2%
산 4
 
4.9%
업 4
 
4.9%
, 4
 
4.9%
안 3
 
3.7%
3
 
3.7%
Other values (19) 36
44.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 60
74.1%
Decimal Number 12
 
14.8%
Other Punctuation 4
 
4.9%
Space Separator 3
 
3.7%
Dash Punctuation 2
 
2.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
빌 6
 
10.0%
딩 6
 
10.0%
성 5
 
8.3%
대 5
 
8.3%
산 4
 
6.7%
업 4
 
6.7%
안 3
 
5.0%
장 3
 
5.0%
신 3
 
5.0%
지 3
 
5.0%
Other values (11) 18
30.0%
Decimal Number
ValueCountFrequency (%)
5 5
41.7%
2 3
25.0%
1 2
 
16.7%
4 1
 
8.3%
3 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 60
74.1%
Common 21
 
25.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
빌 6
 
10.0%
딩 6
 
10.0%
성 5
 
8.3%
대 5
 
8.3%
산 4
 
6.7%
업 4
 
6.7%
안 3
 
5.0%
장 3
 
5.0%
신 3
 
5.0%
지 3
 
5.0%
Other values (11) 18
30.0%
Common
ValueCountFrequency (%)
5 5
23.8%
, 4
19.0%
3
14.3%
2 3
14.3%
1 2
 
9.5%
- 2
 
9.5%
4 1
 
4.8%
3 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 60
74.1%
ASCII 21
 
25.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
빌 6
 
10.0%
딩 6
 
10.0%
성 5
 
8.3%
대 5
 
8.3%
산 4
 
6.7%
업 4
 
6.7%
안 3
 
5.0%
장 3
 
5.0%
신 3
 
5.0%
지 3
 
5.0%
Other values (11) 18
30.0%
ASCII
ValueCountFrequency (%)
5 5
23.8%
, 4
19.0%
3
14.3%
2 3
14.3%
1 2
 
9.5%
- 2
 
9.5%
4 1
 
4.8%
3 1
 
4.8%

실험실특수주소동
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing82
Missing (%)100.0%
Memory size870.0 B

실험실특수주소호
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing80
Missing (%)97.6%
Memory size788.0 B
2024-04-18T05:04:29.908239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2
Min length1

Characters and Unicode

Total characters4
Distinct characters3
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

Unique2 ?
Unique (%)100.0%

Sample

1st row.
2nd row101
ValueCountFrequency (%)
1
50.0%
101 1
50.0%
2024-04-18T05:04:30.090636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2
50.0%
. 1
25.0%
0 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3
75.0%
Other Punctuation 1
 
25.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2
66.7%
0 1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2
50.0%
. 1
25.0%
0 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2
50.0%
. 1
25.0%
0 1
25.0%

실험실도로명주소시군구코드
Real number (ℝ)

MISSING 

Distinct10
Distinct (%)19.6%
Missing31
Missing (%)37.8%
Infinite0
Infinite (%)0.0%
Mean26415.294
Minimum26170
Maximum26710
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2024-04-18T05:04:30.175848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum26170
5-th percentile26260
Q126320
median26410
Q326440
95-th percentile26710
Maximum26710
Range540
Interquartile range (IQR)120

Descriptive statistics

Standard deviation136.65069
Coefficient of variation (CV)0.0051731657
Kurtosis0.42065122
Mean26415.294
Median Absolute Deviation (MAD)90
Skewness0.84832534
Sum1347180
Variance18673.412
MonotonicityNot monotonic
2024-04-18T05:04:30.258751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
26410 15
18.3%
26260 10
 
12.2%
26440 6
 
7.3%
26710 6
 
7.3%
26530 4
 
4.9%
26320 4
 
4.9%
26350 2
 
2.4%
26380 2
 
2.4%
26170 1
 
1.2%
26500 1
 
1.2%
(Missing) 31
37.8%
ValueCountFrequency (%)
26170 1
 
1.2%
26260 10
12.2%
26320 4
 
4.9%
26350 2
 
2.4%
26380 2
 
2.4%
26410 15
18.3%
26440 6
 
7.3%
26500 1
 
1.2%
26530 4
 
4.9%
26710 6
 
7.3%
ValueCountFrequency (%)
26710 6
 
7.3%
26530 4
 
4.9%
26500 1
 
1.2%
26440 6
 
7.3%
26410 15
18.3%
26380 2
 
2.4%
26350 2
 
2.4%
26320 4
 
4.9%
26260 10
12.2%
26170 1
 
1.2%

실험실도로명주소읍면동코드
Real number (ℝ)

MISSING 

Distinct22
Distinct (%)43.1%
Missing31
Missing (%)37.8%
Infinite0
Infinite (%)0.0%
Mean2.6415418 × 109
Minimum2.6170101 × 109
Maximum2.6710256 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2024-04-18T05:04:30.344380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.6170101 × 109
5-th percentile2.6260106 × 109
Q12.6320103 × 109
median2.6410109 × 109
Q32.6440101 × 109
95-th percentile2.6710253 × 109
Maximum2.6710256 × 109
Range54015500
Interquartile range (IQR)11999800

Descriptive statistics

Standard deviation13668873
Coefficient of variation (CV)0.0051745813
Kurtosis0.42204786
Mean2.6415418 × 109
Median Absolute Deviation (MAD)8999400
Skewness0.84910074
Sum1.3471863 × 1011
Variance1.8683808 × 1014
MonotonicityNot monotonic
2024-04-18T05:04:30.436901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
2641010900 8
 
9.8%
2626010800 6
 
7.3%
2644010100 5
 
6.1%
2671025300 4
 
4.9%
2626010600 3
 
3.7%
2641011200 3
 
3.7%
2632010300 3
 
3.7%
2641010700 2
 
2.4%
2653010200 2
 
2.4%
2635010400 2
 
2.4%
Other values (12) 13
15.9%
(Missing) 31
37.8%
ValueCountFrequency (%)
2617010100 1
 
1.2%
2626010600 3
3.7%
2626010800 6
7.3%
2626010900 1
 
1.2%
2632010200 1
 
1.2%
2632010300 3
3.7%
2635010400 2
 
2.4%
2638010500 1
 
1.2%
2638010600 1
 
1.2%
2641010300 1
 
1.2%
ValueCountFrequency (%)
2671025600 2
 
2.4%
2671025300 4
4.9%
2653010500 1
 
1.2%
2653010400 1
 
1.2%
2653010200 2
 
2.4%
2650010300 1
 
1.2%
2644010900 1
 
1.2%
2644010100 5
6.1%
2641011200 3
 
3.7%
2641010900 8
9.8%

실험실도로명주소읍면동구분
Categorical

Distinct3
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size788.0 B
1
45 
<NA>
31 
0
6 

Length

Max length4
Median length1
Mean length2.1341463
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 45
54.9%
<NA> 31
37.8%
0 6
 
7.3%

Length

2024-04-18T05:04:30.539618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:04:30.620522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 45
54.9%
na 31
37.8%
0 6
 
7.3%

실험실도로명주소코드
Real number (ℝ)

MISSING 

Distinct28
Distinct (%)54.9%
Missing31
Missing (%)37.8%
Infinite0
Infinite (%)0.0%
Mean3673470.2
Minimum2000010
Maximum4217302
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2024-04-18T05:04:30.701129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2000010
5-th percentile2006009
Q13137019
median4190380
Q34205268
95-th percentile4212767
Maximum4217302
Range2217292
Interquartile range (IQR)1068249

Descriptive statistics

Standard deviation698484.51
Coefficient of variation (CV)0.19014296
Kurtosis0.11547043
Mean3673470.2
Median Absolute Deviation (MAD)17882
Skewness-1.0312576
Sum1.8734698 × 108
Variance4.878806 × 1011
MonotonicityNot monotonic
2024-04-18T05:04:30.791816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
4190380 5
 
6.1%
4205396 5
 
6.1%
3140067 4
 
4.9%
4190406 3
 
3.7%
4196163 3
 
3.7%
3135057 3
 
3.7%
4205140 2
 
2.4%
3135025 2
 
2.4%
2000010 2
 
2.4%
2006009 2
 
2.4%
Other values (18) 20
24.4%
(Missing) 31
37.8%
ValueCountFrequency (%)
2000010 2
2.4%
2006009 2
2.4%
3130022 1
 
1.2%
3130025 1
 
1.2%
3134008 1
 
1.2%
3135025 2
2.4%
3135057 3
3.7%
3136036 1
 
1.2%
3138002 1
 
1.2%
3139012 1
 
1.2%
ValueCountFrequency (%)
4217302 1
 
1.2%
4217274 1
 
1.2%
4217272 1
 
1.2%
4208262 2
 
2.4%
4208257 2
 
2.4%
4208193 1
 
1.2%
4205396 5
6.1%
4205140 2
 
2.4%
4202202 1
 
1.2%
4196379 1
 
1.2%

실험실도로명특수주소
Text

MISSING 

Distinct9
Distinct (%)69.2%
Missing69
Missing (%)84.1%
Memory size788.0 B
2024-04-18T05:04:30.919384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length8
Mean length7.2307692
Min length4

Characters and Unicode

Total characters94
Distinct characters39
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

Unique6 ?
Unique (%)46.2%

Sample

1st row신도시빌딩
2nd row미도빌딩
3rd row신대성빌딩
4th row금호환경산업사
5th row비즈빌딩
ValueCountFrequency (%)
회동첨단산업단지브이원타워 3
23.1%
센텀아이에스타워 2
15.4%
일성빌딩 2
15.4%
신도시빌딩 1
 
7.7%
미도빌딩 1
 
7.7%
신대성빌딩 1
 
7.7%
금호환경산업사 1
 
7.7%
비즈빌딩 1
 
7.7%
노루표페인트 1
 
7.7%
2024-04-18T05:04:31.146835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
빌 6
 
6.4%
딩 6
 
6.4%
단 6
 
6.4%
타 5
 
5.3%
이 5
 
5.3%
워 5
 
5.3%
산 4
 
4.3%
업 4
 
4.3%
동 3
 
3.2%
성 3
 
3.2%
Other values (29) 47
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 94
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
빌 6
 
6.4%
딩 6
 
6.4%
단 6
 
6.4%
타 5
 
5.3%
이 5
 
5.3%
워 5
 
5.3%
산 4
 
4.3%
업 4
 
4.3%
동 3
 
3.2%
성 3
 
3.2%
Other values (29) 47
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 94
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
빌 6
 
6.4%
딩 6
 
6.4%
단 6
 
6.4%
타 5
 
5.3%
이 5
 
5.3%
워 5
 
5.3%
산 4
 
4.3%
업 4
 
4.3%
동 3
 
3.2%
성 3
 
3.2%
Other values (29) 47
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 94
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
빌 6
 
6.4%
딩 6
 
6.4%
단 6
 
6.4%
타 5
 
5.3%
이 5
 
5.3%
워 5
 
5.3%
산 4
 
4.3%
업 4
 
4.3%
동 3
 
3.2%
성 3
 
3.2%
Other values (29) 47
50.0%

실험실도로명주소건물층구분
Categorical

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size788.0 B
0
51 
<NA>
31 

Length

Max length4
Median length1
Mean length2.1341463
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 51
62.2%
<NA> 31
37.8%

Length

2024-04-18T05:04:31.249758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:04:31.328505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 51
62.2%
na 31
37.8%

실험실도로명주소건물본번호
Real number (ℝ)

MISSING 

Distinct28
Distinct (%)54.9%
Missing31
Missing (%)37.8%
Infinite0
Infinite (%)0.0%
Mean157.5098
Minimum1
Maximum2139
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2024-04-18T05:04:31.402206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q112
median37
Q381
95-th percentile611.5
Maximum2139
Range2138
Interquartile range (IQR)69

Descriptive statistics

Standard deviation388.03651
Coefficient of variation (CV)2.4635705
Kurtosis17.612994
Mean157.5098
Median Absolute Deviation (MAD)26
Skewness4.1194028
Sum8033
Variance150572.33
MonotonicityNot monotonic
2024-04-18T05:04:31.787270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
37 5
 
6.1%
33 4
 
4.9%
9 3
 
3.7%
54 3
 
3.7%
12 3
 
3.7%
11 3
 
3.7%
1 3
 
3.7%
273 3
 
3.7%
60 2
 
2.4%
210 2
 
2.4%
Other values (18) 20
24.4%
(Missing) 31
37.8%
ValueCountFrequency (%)
1 3
3.7%
3 1
 
1.2%
4 1
 
1.2%
9 3
3.7%
10 1
 
1.2%
11 3
3.7%
12 3
3.7%
14 2
2.4%
20 1
 
1.2%
29 1
 
1.2%
ValueCountFrequency (%)
2139 1
 
1.2%
1663 1
 
1.2%
925 1
 
1.2%
298 1
 
1.2%
273 3
3.7%
246 1
 
1.2%
230 1
 
1.2%
210 2
2.4%
183 1
 
1.2%
92 1
 
1.2%

실험실도로명주소건물부번호
Categorical

IMBALANCE 

Distinct5
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size788.0 B
<NA>
71 
0
 
6
20
 
3
7
 
1
1
 
1

Length

Max length4
Median length4
Mean length3.6341463
Min length1

Unique

Unique2 ?
Unique (%)2.4%

Sample

1st row7
2nd row<NA>
3rd row1
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 71
86.6%
0 6
 
7.3%
20 3
 
3.7%
7 1
 
1.2%
1 1
 
1.2%

Length

2024-04-18T05:04:31.881923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:04:31.967570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 71
86.6%
0 6
 
7.3%
20 3
 
3.7%
7 1
 
1.2%
1 1
 
1.2%

실험실도로명주소우편번호
Real number (ℝ)

MISSING 

Distinct29
Distinct (%)56.9%
Missing31
Missing (%)37.8%
Infinite0
Infinite (%)0.0%
Mean324602.76
Minimum46020
Maximum619952
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2024-04-18T05:04:32.045935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46020
5-th percentile46255
Q146916.5
median49514
Q3609852.5
95-th percentile619952
Maximum619952
Range573932
Interquartile range (IQR)562936

Descriptive statistics

Standard deviation285672
Coefficient of variation (CV)0.88006644
Kurtosis-2.0810066
Mean324602.76
Median Absolute Deviation (MAD)3494
Skewness0.040797251
Sum16554741
Variance8.1608492 × 1010
MonotonicityNot monotonic
2024-04-18T05:04:32.130761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
47838 5
 
6.1%
609817 4
 
4.9%
619952 4
 
4.9%
46700 3
 
3.7%
607823 3
 
3.7%
46257 3
 
3.7%
46607 3
 
3.7%
609822 2
 
2.4%
609853 2
 
2.4%
612050 2
 
2.4%
Other values (19) 20
24.4%
(Missing) 31
37.8%
ValueCountFrequency (%)
46020 1
 
1.2%
46023 1
 
1.2%
46253 1
 
1.2%
46257 3
3.7%
46607 3
3.7%
46700 3
3.7%
46916 1
 
1.2%
46917 1
 
1.2%
46980 1
 
1.2%
47829 1
 
1.2%
ValueCountFrequency (%)
619952 4
4.9%
618803 2
2.4%
618270 1
 
1.2%
617809 1
 
1.2%
616853 1
 
1.2%
612050 2
2.4%
609853 2
2.4%
609852 1
 
1.2%
609843 1
 
1.2%
609838 1
 
1.2%

Unnamed: 51
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing82
Missing (%)100.0%
Memory size870.0 B

Sample

번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)실험실면적사업장구분명영업소면적위탁업체명실험실지역코드실험실우편번호실험실산실험실번지실험실호실험실통실험실반실험실특수주소실험실특수주소동실험실특수주소호실험실도로명주소시군구코드실험실도로명주소읍면동코드실험실도로명주소읍면동구분실험실도로명주소코드실험실도로명특수주소실험실도로명주소건물층구분실험실도로명주소건물본번호실험실도로명주소건물부번호실험실도로명주소우편번호Unnamed: 51
01환경측정대행업09_30_17_P626000062600000820060001820210309<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA>601837부산광역시 동구 초량3동 1158번지 7호부산광역시 동구 중앙대로 298, 1층 (초량동,부산YWCA)601837(주)한국환경기술연구원20210309170032U2021-03-11 02:40:00.0<NA>386287.078883182353.5938130.0측정대행업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>26170261701010014181429신도시빌딩03748730<NA>
12환경측정대행업09_30_17_P626000062600000820070000520210302<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA>618270부산광역시 강서구 송정동 1569번지 8호부산광역시 강서구 녹산산단261로31번길 10 (송정동)618270부산녹산표면처리사업협동조합20210302135525U2021-03-04 02:40:00.0<NA>368156.792775178578.014065<NA>측정대행업<NA><NA>2644010900618270115698<NA><NA><NA><NA><NA>26440264401090014208193<NA>010<NA>618270<NA>
23환경측정대행업09_30_17_P626000062600000820140000120180611<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA><NA><NA>부산광역시 금정구 금강로 298-1, A동 102호 (장전동)609838(유)동성기건20180611112637I2019-03-23 02:20:03.0<NA>389849.026837194792.376186<NA>측정대행업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>26410264101080013130022<NA>02981609838<NA>
34환경측정대행업09_30_17_P626000062600000820170000220210404<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA><NA><NA>부산광역시 동래구 아시아드대로255번길 9, B동 2층 1호 (온천동,미도빌딩)47846(주)대한생활환경시험원20210404164832U2021-04-06 02:40:00.0<NA>388251.75583191670.47233196.25측정대행업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>26260262601080014190338미도빌딩09<NA>47846<NA>
45환경측정대행업09_30_17_P626000062600000820060001020210423<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA><NA><NA>부산광역시 강서구 대저로29번길 54 (대저1동)46700천호환경(주)20210423185426U2021-04-25 02:40:00.0<NA>378026.0192626.093.48측정대행업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>26440264401010014208262<NA>054<NA>46700<NA>
56환경측정대행업09_30_17_P626000062600000820060000120210205<NA>1영업/정상N신규<NA><NA><NA><NA>516251618<NA>609822부산광역시 금정구 부곡2동 280번지 2호부산광역시 금정구 동부곡로23번길 30 (부곡동)609822(주)한신환경20210205163916U2021-02-07 02:40:00.0<NA>390624.256291193959.335175<NA>측정대행업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>26410264101090014205140<NA>030<NA>609822<NA>
67환경측정대행업09_30_17_P626000062600000820190000720200604<NA>1영업/정상N신규<NA><NA><NA><NA>512019961<NA>49301부산광역시 사하구 하단동 1158번지 106동 2호부산광역시 사하구 하신번영로 395 (하단동)49301제이앤제이 엔지니어링20200604190356U2020-06-06 02:40:00.0<NA>378638.300284181434.090197<NA>측정대행업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
78환경측정대행업09_30_17_P626000062600000820190000820200422<NA>1영업/정상N신규<NA><NA><NA><NA>517106379<NA>47505부산광역시 연제구 거제동 121-14 화신빌딩 304호호부산광역시 연제구 중앙대로 1229, 화신빌딩 304호 (거제동)47505(주)누리환경 ENG20200422162731U2020-04-24 02:40:00.0<NA>389285.021844190624.483213<NA>측정대행업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
89환경측정대행업09_30_17_P626000062600000820200000520210423<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA>607823부산광역시 동래구 수안동 40번지 2호부산광역시 동래구 온천천로319번길 12 (수안동)607823한국종합환경산업(주)20210423183920U2021-04-25 02:40:00.0<NA>390144.111433190453.524937<NA>측정대행업<NA><NA>26260106006078231402<NA><NA><NA><NA><NA>26260262601060014190406<NA>012<NA>607823<NA>
910환경측정대행업09_30_17_P626000062600000820200000820210423<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA>46213부산광역시 금정구 청룡동 87번지부산광역시 금정구 중앙대로 2140, 5층 (청룡동)46213(주)유림환경기술연구소20210423184524U2021-04-25 02:40:00.0<NA>390367.318071199349.001778<NA>측정대행업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)실험실면적사업장구분명영업소면적위탁업체명실험실지역코드실험실우편번호실험실산실험실번지실험실호실험실통실험실반실험실특수주소실험실특수주소동실험실특수주소호실험실도로명주소시군구코드실험실도로명주소읍면동코드실험실도로명주소읍면동구분실험실도로명주소코드실험실도로명특수주소실험실도로명주소건물층구분실험실도로명주소건물본번호실험실도로명주소건물부번호실험실도로명주소우편번호Unnamed: 51
7273환경측정대행업09_30_17_P626000062600000820100000620180111<NA>3폐업Q폐업20181024<NA><NA><NA><NA><NA>619952부산광역시 기장군 장안읍 반룡리 850번지 장안일반산업단지부산광역시 기장군 장안읍 장안산단1로 11619952그린컨기술(주)20181024134538I2018-10-26 02:37:25.0<NA>405397.470561206746.790462<NA>측정대행업<NA><NA>26710253316199521850<NA><NA><NA>장안일반산업단지<NA><NA>26710267102530003140067<NA>011<NA>619952<NA>
7374환경측정대행업09_30_17_P626000062600000820160000120160829<NA>3폐업Q폐업20181024<NA><NA><NA><NA><NA>46916부산광역시 사상구 모라동 282-6 금호환경산업사부산광역시 사상구 사상로539번길 39, 금호환경산업사 (모라동)46916금호환경(주)20181024135957I2018-10-26 02:37:25.0<NA>380903.012198190017.436488<NA>측정대행업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
7475환경측정대행업09_30_17_P626000062600000820060000220200103<NA>3폐업Q폐업<NA><NA><NA><NA><NA><NA>607823부산광역시 동래구 수안동 40번지 2호부산광역시 동래구 온천천로319번길 12 (수안동)607823한국종합환경산업(주)20200226161907U2020-02-28 02:40:00.0<NA>390144.111433190453.524937<NA>측정대행업<NA><NA>26260106006078231402<NA><NA><NA><NA><NA>26260262601060014190406<NA>012<NA>607823<NA>
7576환경측정대행업09_30_17_P626000062600000820060001620200113<NA>3폐업Q폐업<NA><NA><NA><NA><NA><NA>609817부산광역시 금정구 부곡3동 15번지 22호 대성빌딩, 15-25신대성빌딩부산광역시 금정구 중앙대로1778번길 33 (부곡동)609817(주)대성기술단20201215194636U2020-12-17 02:40:00.0<NA>390635.137541195758.915958<NA>측정대행업<NA><NA>264101090060981711522<NA><NA>대성빌딩, 15-25신대성빌딩<NA><NA>26410264101090014205396<NA>033<NA>609817<NA>
7677환경측정대행업09_30_17_P626000062600000820100000520180502<NA>3폐업Q폐업20181105<NA><NA><NA><NA><NA>619952부산광역시 기장군 장안읍 반룡리 850번지 장안일반산업단지부산광역시 기장군 장안읍 장안산단1로 11619952그린컨기술(주)20181105153919U2018-11-07 02:37:55.0<NA>405397.470561206746.790462<NA>측정대행업<NA><NA>26710253316199521850<NA><NA><NA>장안일반산업단지<NA><NA>26710267102530003140067<NA>011<NA>619952<NA>
7778환경측정대행업09_30_17_P626000062600000820160000220160829<NA>3폐업Q폐업20180109<NA><NA><NA><NA><NA><NA><NA>부산시 금정구 부곡온천천로210<NA>부경엔지니어링20181005124419I2018-10-07 02:37:41.0<NA><NA><NA><NA>측정대행업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
7879환경측정대행업09_30_17_P626000062600000820090000620170811<NA>3폐업Q폐업20180109<NA><NA><NA><NA><NA>609806부산광역시 금정구 구서1동 420-5번지 일성빌딩 2,4층부산광역시 금정구 부곡온천천로 210, 4층 (구서동,일성빌딩)609853(주)부경엔지니어링20181005124614I2018-10-07 02:37:41.0<NA>390371.42551195960.376068<NA>측정대행업<NA><NA>2641010700609310142053<NA><NA><NA><NA><NA>26410264101070013135025일성빌딩0210<NA>609853<NA>
7980환경측정대행업09_30_17_P626000062600000820060002020181121<NA>3폐업Q폐업20190131<NA><NA><NA><NA><NA>609806부산광역시 금정구 구서1동 420-5번지 일성빌딩 2,4층부산광역시 금정구 부곡온천천로 210, 4층 (구서동,일성빌딩)609853(주)명신환경연구소20190207171815U2019-02-09 02:40:00.0<NA>390371.42551195960.376068<NA>측정대행업<NA><NA>2641010700609310142053<NA><NA><NA><NA><NA>26410264101070013135025일성빌딩0210<NA>609853<NA>
8081환경측정대행업09_30_17_P626000062600000820070000420170804<NA>3폐업Q폐업20180523<NA><NA><NA><NA><NA><NA><NA>부산광역시 기장군 정관읍 구연2로 1446023티엘엔지니어링 건축사사무소(주)20181017141703I2018-10-19 02:37:43.0<NA>398326.0204522.0<NA>측정대행업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>26710267102560003140005<NA>014<NA>46023<NA>
8182환경측정대행업09_30_17_P626000062600000820100000120181017<NA>3폐업Q폐업20181019<NA><NA><NA><NA><NA>609817부산광역시 금정구 부곡3동 15번지 22호부산광역시 금정구 중앙대로1778번길 33 (부곡동)609817(주)대성기술단20181019142507U2018-10-21 02:37:54.0<NA>390635.137541195758.915958<NA>측정대행업<NA><NA>264101090060981711522<NA><NA><NA><NA><NA>26410264101090014205396<NA>033<NA>609817<NA>