Overview

Dataset statistics

Number of variables51
Number of observations63
Missing cells1379
Missing cells (%)42.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory27.6 KiB
Average record size in memory448.1 B

Variable types

Numeric19
Categorical15
Unsupported13
Text4

Dataset

Description6270000_대구광역시_09_30_17_P_환경측정대행업_4월
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000089473&dataSetDetailId=DDI_0000089497&provdMethod=FILE

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 (82.4%)Imbalance
인허가취소일자 has 63 (100.0%) missing valuesMissing
폐업일자 has 18 (28.6%) missing valuesMissing
휴업시작일자 has 63 (100.0%) missing valuesMissing
휴업종료일자 has 63 (100.0%) missing valuesMissing
재개업일자 has 63 (100.0%) missing valuesMissing
소재지전화 has 63 (100.0%) missing valuesMissing
소재지면적 has 63 (100.0%) missing valuesMissing
소재지우편번호 has 26 (41.3%) missing valuesMissing
소재지전체주소 has 12 (19.0%) missing valuesMissing
도로명우편번호 has 30 (47.6%) missing valuesMissing
업태구분명 has 63 (100.0%) missing valuesMissing
좌표정보(X) has 20 (31.7%) missing valuesMissing
좌표정보(Y) has 20 (31.7%) missing valuesMissing
실험실면적 has 18 (28.6%) missing valuesMissing
영업소면적 has 63 (100.0%) missing valuesMissing
위탁업체명 has 63 (100.0%) missing valuesMissing
실험실지역코드 has 30 (47.6%) missing valuesMissing
실험실우편번호 has 30 (47.6%) missing valuesMissing
실험실번지 has 30 (47.6%) missing valuesMissing
실험실호 has 39 (61.9%) missing valuesMissing
실험실통 has 63 (100.0%) missing valuesMissing
실험실반 has 63 (100.0%) missing valuesMissing
실험실특수주소 has 60 (95.2%) missing valuesMissing
실험실특수주소동 has 63 (100.0%) missing valuesMissing
실험실특수주소호 has 63 (100.0%) missing valuesMissing
실험실도로명주소시군구코드 has 33 (52.4%) missing valuesMissing
실험실도로명주소읍면동코드 has 33 (52.4%) missing valuesMissing
실험실도로명주소코드 has 33 (52.4%) missing valuesMissing
실험실도로명특수주소 has 61 (96.8%) missing valuesMissing
실험실도로명주소건물본번호 has 33 (52.4%) missing valuesMissing
실험실도로명주소우편번호 has 34 (54.0%) 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
소재지전화 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
실험실특수주소호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
실험실면적 has 2 (3.2%) zerosZeros

Reproduction

Analysis started2023-12-10 18:16:52.673466
Analysis finished2023-12-10 18:16:53.265468
Duration0.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32
Minimum1
Maximum63
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T03:16:53.350731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.1
Q116.5
median32
Q347.5
95-th percentile59.9
Maximum63
Range62
Interquartile range (IQR)31

Descriptive statistics

Standard deviation18.330303
Coefficient of variation (CV)0.57282196
Kurtosis-1.2
Mean32
Median Absolute Deviation (MAD)16
Skewness0
Sum2016
Variance336
MonotonicityStrictly increasing
2023-12-11T03:16:53.539101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.6%
2 1
 
1.6%
35 1
 
1.6%
36 1
 
1.6%
37 1
 
1.6%
38 1
 
1.6%
39 1
 
1.6%
40 1
 
1.6%
41 1
 
1.6%
42 1
 
1.6%
Other values (53) 53
84.1%
ValueCountFrequency (%)
1 1
1.6%
2 1
1.6%
3 1
1.6%
4 1
1.6%
5 1
1.6%
6 1
1.6%
7 1
1.6%
8 1
1.6%
9 1
1.6%
10 1
1.6%
ValueCountFrequency (%)
63 1
1.6%
62 1
1.6%
61 1
1.6%
60 1
1.6%
59 1
1.6%
58 1
1.6%
57 1
1.6%
56 1
1.6%
55 1
1.6%
54 1
1.6%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size636.0 B
환경측정대행업
63 

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 63
100.0%

Length

2023-12-11T03:16:53.699296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:16:53.826664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
환경측정대행업 63
100.0%

개방서비스ID
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size636.0 B
09_30_17_P
63 

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 63
100.0%

Length

2023-12-11T03:16:53.967195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:16:54.092076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_30_17_p 63
100.0%

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size636.0 B
6270000
63 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row6270000
2nd row6270000
3rd row6270000
4th row6270000
5th row6270000

Common Values

ValueCountFrequency (%)
6270000 63
100.0%

Length

2023-12-11T03:16:54.239411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:16:54.424288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
6270000 63
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.2700001 × 1017
Minimum6.2700001 × 1017
Maximum6.2700001 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T03:16:54.676552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6.2700001 × 1017
5-th percentile6.2700001 × 1017
Q16.2700001 × 1017
median6.2700001 × 1017
Q36.2700001 × 1017
95-th percentile6.2700001 × 1017
Maximum6.2700001 × 1017
Range1500000
Interquartile range (IQR)899968

Descriptive statistics

Standard deviation491994.34
Coefficient of variation (CV)7.8467996 × 10-13
Kurtosis-1.3093439
Mean6.2700001 × 1017
Median Absolute Deviation (MAD)499968
Skewness0.044679488
Sum2.6075124 × 1018
Variance2.4205843 × 1011
MonotonicityNot monotonic
2023-12-11T03:16:54.968375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
627000008200600010 1
 
1.6%
627000008201700004 1
 
1.6%
627000008200900003 1
 
1.6%
627000008201100001 1
 
1.6%
627000008201300002 1
 
1.6%
627000008201300003 1
 
1.6%
627000008201400001 1
 
1.6%
627000008201400002 1
 
1.6%
627000008201400003 1
 
1.6%
627000008201400004 1
 
1.6%
Other values (53) 53
84.1%
ValueCountFrequency (%)
627000008200600001 1
1.6%
627000008200600002 1
1.6%
627000008200600003 1
1.6%
627000008200600004 1
1.6%
627000008200600005 1
1.6%
627000008200600006 1
1.6%
627000008200600007 1
1.6%
627000008200600008 1
1.6%
627000008200600009 1
1.6%
627000008200600010 1
1.6%
ValueCountFrequency (%)
627000008202100001 1
1.6%
627000008202000005 1
1.6%
627000008202000004 1
1.6%
627000008202000003 1
1.6%
627000008202000002 1
1.6%
627000008202000001 1
1.6%
627000008201900001 1
1.6%
627000008201800002 1
1.6%
627000008201800001 1
1.6%
627000008201700004 1
1.6%

인허가일자
Real number (ℝ)

Distinct52
Distinct (%)82.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20157481
Minimum20060704
Maximum20210428
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T03:16:55.210577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20060704
5-th percentile20071006
Q120140662
median20150106
Q320210314
95-th percentile20210427
Maximum20210428
Range149724
Interquartile range (IQR)69652

Descriptive statistics

Standard deviation47836.944
Coefficient of variation (CV)0.0023731608
Kurtosis-0.77880671
Mean20157481
Median Absolute Deviation (MAD)49980
Skewness-0.49835185
Sum1.2699213 × 109
Variance2.2883732 × 109
MonotonicityNot monotonic
2023-12-11T03:16:55.471076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20210427 5
 
7.9%
20141013 3
 
4.8%
20141027 2
 
3.2%
20210414 2
 
3.2%
20200210 2
 
3.2%
20141106 2
 
3.2%
20141006 2
 
3.2%
20141014 1
 
1.6%
20120217 1
 
1.6%
20131106 1
 
1.6%
Other values (42) 42
66.7%
ValueCountFrequency (%)
20060704 1
1.6%
20060720 1
1.6%
20060920 1
1.6%
20071004 1
1.6%
20071019 1
1.6%
20071114 1
1.6%
20080218 1
1.6%
20080509 1
1.6%
20091009 1
1.6%
20100126 1
1.6%
ValueCountFrequency (%)
20210428 1
 
1.6%
20210427 5
7.9%
20210419 1
 
1.6%
20210415 1
 
1.6%
20210414 2
 
3.2%
20210409 1
 
1.6%
20210408 1
 
1.6%
20210402 1
 
1.6%
20210323 1
 
1.6%
20210318 1
 
1.6%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing63
Missing (%)100.0%
Memory size699.0 B

영업상태구분코드
Categorical

Distinct2
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size636.0 B
3
45 
1
18 

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 45
71.4%
1 18
 
28.6%

Length

2023-12-11T03:16:55.708025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:16:55.860369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 45
71.4%
1 18
 
28.6%

영업상태명
Categorical

Distinct2
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size636.0 B
폐업
45 
영업/정상
18 

Length

Max length5
Median length2
Mean length2.8571429
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 45
71.4%
영업/정상 18
 
28.6%

Length

2023-12-11T03:16:56.066941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:16:56.226652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 45
71.4%
영업/정상 18
 
28.6%

상세영업상태코드
Categorical

Distinct2
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size636.0 B
Q
45 
N
18 

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 45
71.4%
N 18
 
28.6%

Length

2023-12-11T03:16:56.406626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:16:56.554454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
q 45
71.4%
n 18
 
28.6%

상세영업상태명
Categorical

Distinct2
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size636.0 B
폐업
45 
신규
18 

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 45
71.4%
신규 18
 
28.6%

Length

2023-12-11T03:16:56.738011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:16:56.899183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 45
71.4%
신규 18
 
28.6%

폐업일자
Real number (ℝ)

MISSING 

Distinct27
Distinct (%)60.0%
Missing18
Missing (%)28.6%
Infinite0
Infinite (%)0.0%
Mean20146268
Minimum20060530
Maximum20210319
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T03:16:57.085639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20060530
5-th percentile20070286
Q120140304
median20150205
Q320170928
95-th percentile20200217
Maximum20210319
Range149789
Interquartile range (IQR)30624

Descriptive statistics

Standard deviation38750.546
Coefficient of variation (CV)0.0019234603
Kurtosis0.038470642
Mean20146268
Median Absolute Deviation (MAD)20723
Skewness-0.76154448
Sum9.0658206 × 108
Variance1.5016048 × 109
MonotonicityNot monotonic
2023-12-11T03:16:57.321917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
20150205 7
 
11.1%
20150204 5
 
7.9%
20170928 4
 
6.3%
20080324 2
 
3.2%
20180606 2
 
3.2%
20150206 2
 
3.2%
20150203 2
 
3.2%
20131202 2
 
3.2%
20190909 1
 
1.6%
20180913 1
 
1.6%
Other values (17) 17
27.0%
(Missing) 18
28.6%
ValueCountFrequency (%)
20060530 1
1.6%
20060816 1
1.6%
20070103 1
1.6%
20071019 1
1.6%
20080324 2
3.2%
20100112 1
1.6%
20100126 1
1.6%
20100427 1
1.6%
20131202 2
3.2%
20140304 1
1.6%
ValueCountFrequency (%)
20210319 1
 
1.6%
20201221 1
 
1.6%
20200219 1
 
1.6%
20200210 1
 
1.6%
20190909 1
 
1.6%
20190812 1
 
1.6%
20180913 1
 
1.6%
20180606 2
3.2%
20171031 1
 
1.6%
20170928 4
6.3%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing63
Missing (%)100.0%
Memory size699.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing63
Missing (%)100.0%
Memory size699.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing63
Missing (%)100.0%
Memory size699.0 B

소재지전화
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing63
Missing (%)100.0%
Memory size699.0 B

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing63
Missing (%)100.0%
Memory size699.0 B

소재지우편번호
Real number (ℝ)

MISSING 

Distinct19
Distinct (%)51.4%
Missing26
Missing (%)41.3%
Infinite0
Infinite (%)0.0%
Mean668893.65
Minimum41701
Maximum711841
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T03:16:57.642896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41701
5-th percentile570010.6
Q1703830
median703834
Q3704932
95-th percentile711841
Maximum711841
Range670140
Interquartile range (IQR)1102

Descriptive statistics

Standard deviation151996.44
Coefficient of variation (CV)0.22723558
Kurtosis15.75757
Mean668893.65
Median Absolute Deviation (MAD)406
Skewness-4.1112521
Sum24749065
Variance2.3102918 × 1010
MonotonicityNot monotonic
2023-12-11T03:16:57.840747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
703834 7
 
11.1%
703839 5
 
7.9%
703830 4
 
6.3%
704932 3
 
4.8%
711841 3
 
4.8%
705804 2
 
3.2%
41845 1
 
1.6%
41701 1
 
1.6%
702843 1
 
1.6%
705811 1
 
1.6%
Other values (9) 9
 
14.3%
(Missing) 26
41.3%
ValueCountFrequency (%)
41701 1
 
1.6%
41845 1
 
1.6%
702052 1
 
1.6%
702200 1
 
1.6%
702843 1
 
1.6%
702848 1
 
1.6%
703010 1
 
1.6%
703830 4
6.3%
703833 1
 
1.6%
703834 7
11.1%
ValueCountFrequency (%)
711841 3
4.8%
706852 1
 
1.6%
705811 1
 
1.6%
705804 2
 
3.2%
704932 3
4.8%
704701 1
 
1.6%
704240 1
 
1.6%
703849 1
 
1.6%
703839 5
7.9%
703834 7
11.1%

소재지전체주소
Text

MISSING 

Distinct28
Distinct (%)54.9%
Missing12
Missing (%)19.0%
Memory size636.0 B
2023-12-11T03:16:58.221333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length32
Mean length24.372549
Min length19

Characters and Unicode

Total characters1243
Distinct characters71
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

Unique17 ?
Unique (%)33.3%

Sample

1st row대구광역시 서구 이현동 42번지 450호
2nd row대구광역시 서구 이현동 42번지 292호
3rd row대구광역시 달서구 죽전동 372번지
4th row대구광역시 서구 중리동 1144-1
5th row대구광역시 서구 이현동 192번지 8호
ValueCountFrequency (%)
대구광역시 51
20.4%
서구 27
 
10.8%
이현동 10
 
4.0%
1호 9
 
3.6%
북구 9
 
3.6%
달서구 8
 
3.2%
42번지 7
 
2.8%
평리6동 7
 
2.8%
567번지 6
 
2.4%
292호 5
 
2.0%
Other values (63) 111
44.4%
2023-12-11T03:16:58.913716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
297
23.9%
구 99
 
8.0%
대 55
 
4.4%
광 51
 
4.1%
역 51
 
4.1%
시 51
 
4.1%
지 50
 
4.0%
번 49
 
3.9%
동 48
 
3.9%
1 43
 
3.5%
Other values (61) 449
36.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 700
56.3%
Space Separator 297
23.9%
Decimal Number 244
 
19.6%
Dash Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 99
14.1%
대 55
 
7.9%
광 51
 
7.3%
역 51
 
7.3%
시 51
 
7.3%
지 50
 
7.1%
번 49
 
7.0%
동 48
 
6.9%
호 39
 
5.6%
서 36
 
5.1%
Other values (49) 171
24.4%
Decimal Number
ValueCountFrequency (%)
1 43
17.6%
4 33
13.5%
2 31
12.7%
5 26
10.7%
6 25
10.2%
9 24
9.8%
3 23
9.4%
7 18
7.4%
0 16
 
6.6%
8 5
 
2.0%
Space Separator
ValueCountFrequency (%)
297
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 700
56.3%
Common 543
43.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 99
14.1%
대 55
 
7.9%
광 51
 
7.3%
역 51
 
7.3%
시 51
 
7.3%
지 50
 
7.1%
번 49
 
7.0%
동 48
 
6.9%
호 39
 
5.6%
서 36
 
5.1%
Other values (49) 171
24.4%
Common
ValueCountFrequency (%)
297
54.7%
1 43
 
7.9%
4 33
 
6.1%
2 31
 
5.7%
5 26
 
4.8%
6 25
 
4.6%
9 24
 
4.4%
3 23
 
4.2%
7 18
 
3.3%
0 16
 
2.9%
Other values (2) 7
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 700
56.3%
ASCII 543
43.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
297
54.7%
1 43
 
7.9%
4 33
 
6.1%
2 31
 
5.7%
5 26
 
4.8%
6 25
 
4.6%
9 24
 
4.4%
3 23
 
4.2%
7 18
 
3.3%
0 16
 
2.9%
Other values (2) 7
 
1.3%
Hangul
ValueCountFrequency (%)
구 99
14.1%
대 55
 
7.9%
광 51
 
7.3%
역 51
 
7.3%
시 51
 
7.3%
지 50
 
7.1%
번 49
 
7.0%
동 48
 
6.9%
호 39
 
5.6%
서 36
 
5.1%
Other values (49) 171
24.4%

도로명전체주소
Categorical

Distinct31
Distinct (%)49.2%
Missing0
Missing (%)0.0%
Memory size636.0 B
대구광역시 북구 팔달북로15길 12 (노원동3가)
6 
대구광역시 서구 국채보상로19길 15 (이현동)
6 
대구광역시 서구 북비산로 165 (평리동)
6 
대구광역시 서구 와룡로83길 13 (이현동)
5 
대구광역시 서구 서대구로 230 (평리동)
5 
Other values (26)
35 

Length

Max length34
Median length31
Mean length24.301587
Min length4

Unique

Unique20 ?
Unique (%)31.7%

Sample

1st row대구광역시 서구 와룡로87길 24 (이현동)
2nd row대구광역시 달서구 달구벌대로 1221(3층)
3rd row대구광역시 수성구 동대구로38안길 28, 2층 (범어동)
4th row대구광역시 서구 와룡로83길 13 (이현동)
5th row대구광역시 달서구 평리로 92 (죽전동)

Common Values

ValueCountFrequency (%)
대구광역시 북구 팔달북로15길 12 (노원동3가) 6
 
9.5%
대구광역시 서구 국채보상로19길 15 (이현동) 6
 
9.5%
대구광역시 서구 북비산로 165 (평리동) 6
 
9.5%
대구광역시 서구 와룡로83길 13 (이현동) 5
 
7.9%
대구광역시 서구 서대구로 230 (평리동) 5
 
7.9%
대구광역시 달성군 옥포면 간경길 20 4
 
6.3%
대구광역시 남구 대명남로 160 (대명동) 3
 
4.8%
대구광역시 북구 팔달북로18길 2 (노원동3가) 2
 
3.2%
대구광역시 달서구 평리로 92 (죽전동) 2
 
3.2%
대구광역시 달서구 이곡서로7길 17 (이곡동) 2
 
3.2%
Other values (21) 22
34.9%

Length

2023-12-11T03:16:59.560597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
대구광역시 62
19.8%
서구 32
 
10.2%
평리동 15
 
4.8%
이현동 14
 
4.5%
북구 12
 
3.8%
달서구 8
 
2.6%
노원동3가 8
 
2.6%
12 7
 
2.2%
165 6
 
1.9%
서대구로 6
 
1.9%
Other values (70) 143
45.7%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)36.4%
Missing30
Missing (%)47.6%
Infinite0
Infinite (%)0.0%
Mean623811.79
Minimum41701
Maximum705804
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T03:16:59.744912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41701
5-th percentile41835
Q1703830
median703834
Q3703839
95-th percentile705804
Maximum705804
Range664103
Interquartile range (IQR)9

Descriptive statistics

Standard deviation219480.1
Coefficient of variation (CV)0.35183705
Kurtosis4.1698484
Mean623811.79
Median Absolute Deviation (MAD)4
Skewness-2.4331782
Sum20585789
Variance4.8171515 × 1010
MonotonicityNot monotonic
2023-12-11T03:16:59.949286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
703830 8
 
12.7%
703834 8
 
12.7%
703839 5
 
7.9%
705804 3
 
4.8%
704932 2
 
3.2%
42110 1
 
1.6%
41845 1
 
1.6%
41701 1
 
1.6%
41820 1
 
1.6%
703849 1
 
1.6%
Other values (2) 2
 
3.2%
(Missing) 30
47.6%
ValueCountFrequency (%)
41701 1
 
1.6%
41820 1
 
1.6%
41845 1
 
1.6%
42110 1
 
1.6%
702848 1
 
1.6%
703830 8
12.7%
703833 1
 
1.6%
703834 8
12.7%
703839 5
7.9%
703849 1
 
1.6%
ValueCountFrequency (%)
705804 3
 
4.8%
704932 2
 
3.2%
703849 1
 
1.6%
703839 5
7.9%
703834 8
12.7%
703833 1
 
1.6%
703830 8
12.7%
702848 1
 
1.6%
42110 1
 
1.6%
41845 1
 
1.6%

사업장명
Text

Distinct35
Distinct (%)55.6%
Missing0
Missing (%)0.0%
Memory size636.0 B
2023-12-11T03:17:00.277217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length12
Mean length8.6190476
Min length4

Characters and Unicode

Total characters543
Distinct characters97
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)36.5%

Sample

1st row(주)신라엔텍
2nd row(주)정도환경
3rd row(주)테크월
4th row(주)이화환경지점
5th row대동환경측정
ValueCountFrequency (%)
주)한국이앤씨 5
 
7.6%
현대공해측정(주 5
 
7.6%
주)이화환경지점 5
 
7.6%
케이지엔텍 5
 
7.6%
주)삼안환경화학측정 4
 
6.1%
주)이앤비테크 4
 
6.1%
주)제일랩 2
 
3.0%
주)신라엔텍 2
 
3.0%
로드환경산업 2
 
3.0%
삼한측정(주 2
 
3.0%
Other values (28) 30
45.5%
2023-12-11T03:17:00.912223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 49
 
9.0%
) 49
 
9.0%
주 49
 
9.0%
경 26
 
4.8%
환 25
 
4.6%
이 22
 
4.1%
정 20
 
3.7%
측 19
 
3.5%
대 16
 
2.9%
지 13
 
2.4%
Other values (87) 255
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 436
80.3%
Open Punctuation 49
 
9.0%
Close Punctuation 49
 
9.0%
Uppercase Letter 6
 
1.1%
Space Separator 3
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 49
 
11.2%
경 26
 
6.0%
환 25
 
5.7%
이 22
 
5.0%
정 20
 
4.6%
측 19
 
4.4%
대 16
 
3.7%
지 13
 
3.0%
앤 11
 
2.5%
구 10
 
2.3%
Other values (79) 225
51.6%
Uppercase Letter
ValueCountFrequency (%)
E 2
33.3%
T 1
16.7%
D 1
16.7%
Y 1
16.7%
C 1
16.7%
Open Punctuation
ValueCountFrequency (%)
( 49
100.0%
Close Punctuation
ValueCountFrequency (%)
) 49
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 436
80.3%
Common 101
 
18.6%
Latin 6
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 49
 
11.2%
경 26
 
6.0%
환 25
 
5.7%
이 22
 
5.0%
정 20
 
4.6%
측 19
 
4.4%
대 16
 
3.7%
지 13
 
3.0%
앤 11
 
2.5%
구 10
 
2.3%
Other values (79) 225
51.6%
Latin
ValueCountFrequency (%)
E 2
33.3%
T 1
16.7%
D 1
16.7%
Y 1
16.7%
C 1
16.7%
Common
ValueCountFrequency (%)
( 49
48.5%
) 49
48.5%
3
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 436
80.3%
ASCII 107
 
19.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 49
45.8%
) 49
45.8%
3
 
2.8%
E 2
 
1.9%
T 1
 
0.9%
D 1
 
0.9%
Y 1
 
0.9%
C 1
 
0.9%
Hangul
ValueCountFrequency (%)
주 49
 
11.2%
경 26
 
6.0%
환 25
 
5.7%
이 22
 
5.0%
정 20
 
4.6%
측 19
 
4.4%
대 16
 
3.7%
지 13
 
3.0%
앤 11
 
2.5%
구 10
 
2.3%
Other values (79) 225
51.6%

최종수정시점
Real number (ℝ)

UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0164998 × 1013
Minimum2.0061201 × 1013
Maximum2.0210428 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T03:17:01.148063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0061201 × 1013
5-th percentile2.0072032 × 1013
Q12.0150204 × 1013
median2.0170928 × 1013
Q32.0210318 × 1013
95-th percentile2.0210427 × 1013
Maximum2.0210428 × 1013
Range1.4922693 × 1011
Interquartile range (IQR)6.0113495 × 1010

Descriptive statistics

Standard deviation4.3440786 × 1010
Coefficient of variation (CV)0.0021542668
Kurtosis0.0035178996
Mean2.0164998 × 1013
Median Absolute Deviation (MAD)3.0220918 × 1010
Skewness-0.84342071
Sum1.2703949 × 1015
Variance1.8871019 × 1021
MonotonicityNot monotonic
2023-12-11T03:17:01.393926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20210408112207 1
 
1.6%
20210323085733 1
 
1.6%
20131202134551 1
 
1.6%
20140707174528 1
 
1.6%
20140707172759 1
 
1.6%
20150205162148 1
 
1.6%
20150206144752 1
 
1.6%
20150205154541 1
 
1.6%
20151027181119 1
 
1.6%
20170928092159 1
 
1.6%
Other values (53) 53
84.1%
ValueCountFrequency (%)
20061201170741 1
1.6%
20061213085957 1
1.6%
20070103174533 1
1.6%
20071102115258 1
1.6%
20080402182630 1
1.6%
20080402182701 1
1.6%
20100126174154 1
1.6%
20100427161139 1
1.6%
20101118154145 1
1.6%
20131202134551 1
1.6%
ValueCountFrequency (%)
20210428102820 1
1.6%
20210427151306 1
1.6%
20210427151253 1
1.6%
20210427093347 1
1.6%
20210427093325 1
1.6%
20210427093252 1
1.6%
20210419155735 1
1.6%
20210419151001 1
1.6%
20210415135515 1
1.6%
20210414122207 1
1.6%

데이터갱신구분
Categorical

Distinct2
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size636.0 B
I
40 
U
23 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 40
63.5%
U 23
36.5%

Length

2023-12-11T03:17:01.637893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:17:01.826723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 40
63.5%
u 23
36.5%

데이터갱신일자
Categorical

Distinct21
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size636.0 B
2019-03-23 02:20:03.0
38 
2021-04-29 02:40:00.0
5 
2021-04-21 02:40:00.0
 
2
2021-03-25 02:40:00.0
 
1
2021-03-19 02:40:00.0
 
1
Other values (16)
16 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique18 ?
Unique (%)28.6%

Sample

1st row2021-04-10 02:40:00.0
2nd row2021-03-25 02:40:00.0
3rd row2021-03-19 02:40:00.0
4th row2021-04-29 02:40:00.0
5th row2021-04-04 02:40:00.0

Common Values

ValueCountFrequency (%)
2019-03-23 02:20:03.0 38
60.3%
2021-04-29 02:40:00.0 5
 
7.9%
2021-04-21 02:40:00.0 2
 
3.2%
2021-03-25 02:40:00.0 1
 
1.6%
2021-03-19 02:40:00.0 1
 
1.6%
2021-04-04 02:40:00.0 1
 
1.6%
2021-04-16 02:40:00.0 1
 
1.6%
2020-11-14 02:40:00.0 1
 
1.6%
2021-04-11 02:40:00.0 1
 
1.6%
2021-04-30 02:40:00.0 1
 
1.6%
Other values (11) 11
 
17.5%

Length

2023-12-11T03:17:02.025624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2019-03-23 38
30.2%
02:20:03.0 38
30.2%
02:40:00.0 23
18.3%
2021-04-29 5
 
4.0%
2021-04-21 2
 
1.6%
2020-12-24 1
 
0.8%
2021-04-10 1
 
0.8%
02:37:17.0 1
 
0.8%
2018-10-24 1
 
0.8%
2019-08-14 1
 
0.8%
Other values (15) 15
 
11.9%

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing63
Missing (%)100.0%
Memory size699.0 B

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct21
Distinct (%)48.8%
Missing20
Missing (%)31.7%
Infinite0
Infinite (%)0.0%
Mean339631.08
Minimum332810.96
Maximum346847.04
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T03:17:02.229922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum332810.96
5-th percentile332810.96
Q1339014.34
median339826.43
Q3340371.26
95-th percentile344510.56
Maximum346847.04
Range14036.079
Interquartile range (IQR)1356.9247

Descriptive statistics

Standard deviation3046.1982
Coefficient of variation (CV)0.0089691384
Kurtosis1.7193854
Mean339631.08
Median Absolute Deviation (MAD)696.1258
Skewness-0.37325436
Sum14604136
Variance9279323.2
MonotonicityNot monotonic
2023-12-11T03:17:02.451194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
339130.306851 6
 
9.5%
340008.783916 6
 
9.5%
340371.264862 5
 
7.9%
332810.958572 4
 
6.3%
342283.311178 3
 
4.8%
339826.432647 2
 
3.2%
338615.297418 2
 
3.2%
338701.951391 2
 
3.2%
339371.010099 1
 
1.6%
339429.92372 1
 
1.6%
Other values (11) 11
17.5%
(Missing) 20
31.7%
ValueCountFrequency (%)
332810.958572 4
6.3%
334609.650347 1
 
1.6%
338615.297418 2
 
3.2%
338701.951391 2
 
3.2%
338894.926928 1
 
1.6%
338898.373443 1
 
1.6%
339130.306851 6
9.5%
339371.010099 1
 
1.6%
339429.92372 1
 
1.6%
339633.73096 1
 
1.6%
ValueCountFrequency (%)
346847.037653 1
 
1.6%
346679.82341 1
 
1.6%
344607.11184 1
 
1.6%
343641.586755 1
 
1.6%
342283.311178 3
4.8%
341149.759563 1
 
1.6%
340981.303777 1
 
1.6%
340371.264862 5
7.9%
340320.175876 1
 
1.6%
340008.783916 6
9.5%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct21
Distinct (%)48.8%
Missing20
Missing (%)31.7%
Infinite0
Infinite (%)0.0%
Mean263806.53
Minimum255625.93
Maximum272471.81
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T03:17:02.736758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum255625.93
5-th percentile255625.93
Q1262269.94
median264420.56
Q3265447.98
95-th percentile266801.7
Maximum272471.81
Range16845.878
Interquartile range (IQR)3178.0426

Descriptive statistics

Standard deviation3590.3399
Coefficient of variation (CV)0.013609746
Kurtosis1.732048
Mean263806.53
Median Absolute Deviation (MAD)1027.4275
Skewness-0.48914186
Sum11343681
Variance12890541
MonotonicityNot monotonic
2023-12-11T03:17:03.048706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
264420.555301 6
 
9.5%
265447.982846 6
 
9.5%
265362.721318 5
 
7.9%
255625.932226 4
 
6.3%
260627.073987 3
 
4.8%
272471.810307 2
 
3.2%
264600.197895 2
 
3.2%
262918.244449 2
 
3.2%
265776.464191 1
 
1.6%
266688.381145 1
 
1.6%
Other values (11) 11
17.5%
(Missing) 20
31.7%
ValueCountFrequency (%)
255625.932226 4
6.3%
260627.073987 3
4.8%
260838.991214 1
 
1.6%
260912.780405 1
 
1.6%
262190.918869 1
 
1.6%
262201.871268 1
 
1.6%
262338.009266 1
 
1.6%
262918.244449 2
3.2%
263825.390815 1
 
1.6%
264229.509899 1
 
1.6%
ValueCountFrequency (%)
272471.810307 2
 
3.2%
266803.096272 1
 
1.6%
266789.135119 1
 
1.6%
266688.381145 1
 
1.6%
265776.464191 1
 
1.6%
265750.120961 1
 
1.6%
265447.982846 6
9.5%
265362.721318 5
7.9%
264946.018247 1
 
1.6%
264600.197895 2
 
3.2%

실험실면적
Real number (ℝ)

MISSING  ZEROS 

Distinct18
Distinct (%)40.0%
Missing18
Missing (%)28.6%
Infinite0
Infinite (%)0.0%
Mean109.08778
Minimum0
Maximum311.87
Zeros2
Zeros (%)3.2%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T03:17:03.379071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile46.41
Q179.3
median92.4
Q3133.2
95-th percentile204.816
Maximum311.87
Range311.87
Interquartile range (IQR)53.9

Descriptive statistics

Standard deviation58.87981
Coefficient of variation (CV)0.53974708
Kurtosis2.7082642
Mean109.08778
Median Absolute Deviation (MAD)18.4
Skewness1.2958056
Sum4908.95
Variance3466.832
MonotonicityNot monotonic
2023-12-11T03:17:03.743726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
74.0 7
 
11.1%
133.2 6
 
9.5%
79.3 6
 
9.5%
98.8 5
 
7.9%
184.08 5
 
7.9%
99.65 2
 
3.2%
92.4 2
 
3.2%
0.0 2
 
3.2%
210.0 1
 
1.6%
60.05 1
 
1.6%
Other values (8) 8
12.7%
(Missing) 18
28.6%
ValueCountFrequency (%)
0.0 2
 
3.2%
43.0 1
 
1.6%
60.05 1
 
1.6%
74.0 7
11.1%
79.3 6
9.5%
80.13 1
 
1.6%
82.6 1
 
1.6%
85.0 1
 
1.6%
90.6 1
 
1.6%
92.4 2
 
3.2%
ValueCountFrequency (%)
311.87 1
 
1.6%
255.0 1
 
1.6%
210.0 1
 
1.6%
184.08 5
7.9%
133.2 6
9.5%
99.65 2
 
3.2%
99.2 1
 
1.6%
98.8 5
7.9%
92.4 2
 
3.2%
90.6 1
 
1.6%

사업장구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size636.0 B
측정대행업
63 

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 63
100.0%

Length

2023-12-11T03:17:04.094447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:17:04.271844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
측정대행업 63
100.0%

영업소면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing63
Missing (%)100.0%
Memory size699.0 B

위탁업체명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing63
Missing (%)100.0%
Memory size699.0 B

실험실지역코드
Real number (ℝ)

MISSING 

Distinct11
Distinct (%)33.3%
Missing30
Missing (%)47.6%
Infinite0
Infinite (%)0.0%
Mean2.7240127 × 109
Minimum2.7170102 × 109
Maximum2.771034 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T03:17:04.445214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.7170102 × 109
5-th percentile2.7170103 × 109
Q12.7170103 × 109
median2.7170106 × 109
Q32.7230111 × 109
95-th percentile2.771034 × 109
Maximum2.771034 × 109
Range54023825
Interquartile range (IQR)6000800

Descriptive statistics

Standard deviation15553020
Coefficient of variation (CV)0.0057095991
Kurtosis6.1788128
Mean2.7240127 × 109
Median Absolute Deviation (MAD)300
Skewness2.6986676
Sum8.9892419 × 1010
Variance2.4189644 × 1014
MonotonicityNot monotonic
2023-12-11T03:17:04.669873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
2717010300 12
 
19.0%
2717010600 4
 
6.3%
2720010300 3
 
4.8%
2771034025 3
 
4.8%
2729011200 2
 
3.2%
2717010500 2
 
3.2%
2717010200 2
 
3.2%
2723011800 2
 
3.2%
2723011100 1
 
1.6%
2723010600 1
 
1.6%
(Missing) 30
47.6%
ValueCountFrequency (%)
2717010200 2
 
3.2%
2717010300 12
19.0%
2717010500 2
 
3.2%
2717010600 4
 
6.3%
2720010300 3
 
4.8%
2723010600 1
 
1.6%
2723011100 1
 
1.6%
2723011800 2
 
3.2%
2729010700 1
 
1.6%
2729011200 2
 
3.2%
ValueCountFrequency (%)
2771034025 3
 
4.8%
2729011200 2
 
3.2%
2729010700 1
 
1.6%
2723011800 2
 
3.2%
2723011100 1
 
1.6%
2723010600 1
 
1.6%
2720010300 3
 
4.8%
2717010600 4
 
6.3%
2717010500 2
 
3.2%
2717010300 12
19.0%

실험실우편번호
Real number (ℝ)

MISSING 

Distinct17
Distinct (%)51.5%
Missing30
Missing (%)47.6%
Infinite0
Infinite (%)0.0%
Mean664546.12
Minimum41701
Maximum711841
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T03:17:04.865624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41701
5-th percentile437969.2
Q1703830
median703834
Q3704701
95-th percentile711841
Maximum711841
Range670140
Interquartile range (IQR)871

Descriptive statistics

Standard deviation160655.67
Coefficient of variation (CV)0.24175247
Kurtosis13.727954
Mean664546.12
Median Absolute Deviation (MAD)9
Skewness-3.8592297
Sum21930022
Variance2.5810243 × 1010
MonotonicityNot monotonic
2023-12-11T03:17:05.130483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
703834 6
 
9.5%
703839 5
 
7.9%
703830 4
 
6.3%
711841 3
 
4.8%
705804 2
 
3.2%
704932 2
 
3.2%
41845 1
 
1.6%
41701 1
 
1.6%
702843 1
 
1.6%
705811 1
 
1.6%
Other values (7) 7
 
11.1%
(Missing) 30
47.6%
ValueCountFrequency (%)
41701 1
 
1.6%
41845 1
 
1.6%
702052 1
 
1.6%
702200 1
 
1.6%
702843 1
 
1.6%
702848 1
 
1.6%
703825 1
 
1.6%
703830 4
6.3%
703833 1
 
1.6%
703834 6
9.5%
ValueCountFrequency (%)
711841 3
4.8%
705811 1
 
1.6%
705804 2
 
3.2%
704932 2
 
3.2%
704701 1
 
1.6%
703849 1
 
1.6%
703839 5
7.9%
703834 6
9.5%
703833 1
 
1.6%
703830 4
6.3%

실험실산
Categorical

Distinct3
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size636.0 B
1
31 
<NA>
30 
0
 
2

Length

Max length4
Median length1
Mean length2.4285714
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 31
49.2%
<NA> 30
47.6%
0 2
 
3.2%

Length

2023-12-11T03:17:05.413621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:17:05.650394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 31
49.2%
na 30
47.6%
0 2
 
3.2%

실험실번지
Real number (ℝ)

MISSING 

Distinct18
Distinct (%)54.5%
Missing30
Missing (%)47.6%
Infinite0
Infinite (%)0.0%
Mean812.12121
Minimum42
Maximum3194
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T03:17:05.832845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum42
5-th percentile43.2
Q1567
median719
Q31115
95-th percentile1706.4
Maximum3194
Range3152
Interquartile range (IQR)548

Descriptive statistics

Standard deviation618.49231
Coefficient of variation (CV)0.76157635
Kurtosis6.0792629
Mean812.12121
Median Absolute Deviation (MAD)315
Skewness1.9422446
Sum26800
Variance382532.73
MonotonicityNot monotonic
2023-12-11T03:17:06.078983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
567 5
 
7.9%
719 5
 
7.9%
839 3
 
4.8%
372 2
 
3.2%
44 2
 
3.2%
1206 2
 
3.2%
42 2
 
3.2%
646 2
 
3.2%
1442 1
 
1.6%
295 1
 
1.6%
Other values (8) 8
 
12.7%
(Missing) 30
47.6%
ValueCountFrequency (%)
42 2
 
3.2%
44 2
 
3.2%
295 1
 
1.6%
372 2
 
3.2%
404 1
 
1.6%
567 5
7.9%
646 2
 
3.2%
719 5
7.9%
839 3
4.8%
1000 1
 
1.6%
ValueCountFrequency (%)
3194 1
 
1.6%
2028 1
 
1.6%
1492 1
 
1.6%
1442 1
 
1.6%
1206 2
3.2%
1144 1
 
1.6%
1119 1
 
1.6%
1115 1
 
1.6%
1000 1
 
1.6%
839 3
4.8%

실험실호
Real number (ℝ)

MISSING 

Distinct11
Distinct (%)45.8%
Missing39
Missing (%)61.9%
Infinite0
Infinite (%)0.0%
Mean56.291667
Minimum1
Maximum450
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T03:17:06.328250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median5.5
Q339
95-th percentile399
Maximum450
Range449
Interquartile range (IQR)38

Descriptive statistics

Standard deviation125.3456
Coefficient of variation (CV)2.2267168
Kurtosis7.5891843
Mean56.291667
Median Absolute Deviation (MAD)4.5
Skewness2.8899637
Sum1351
Variance15711.52
MonotonicityNot monotonic
2023-12-11T03:17:06.549159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 7
 
11.1%
3 3
 
4.8%
450 2
 
3.2%
7 2
 
3.2%
19 2
 
3.2%
4 2
 
3.2%
110 2
 
3.2%
56 1
 
1.6%
54 1
 
1.6%
11 1
 
1.6%
(Missing) 39
61.9%
ValueCountFrequency (%)
1 7
11.1%
3 3
4.8%
4 2
 
3.2%
7 2
 
3.2%
11 1
 
1.6%
19 2
 
3.2%
34 1
 
1.6%
54 1
 
1.6%
56 1
 
1.6%
110 2
 
3.2%
ValueCountFrequency (%)
450 2
3.2%
110 2
3.2%
56 1
 
1.6%
54 1
 
1.6%
34 1
 
1.6%
19 2
3.2%
11 1
 
1.6%
7 2
3.2%
4 2
3.2%
3 3
4.8%

실험실통
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing63
Missing (%)100.0%
Memory size699.0 B

실험실반
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing63
Missing (%)100.0%
Memory size699.0 B

실험실특수주소
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing60
Missing (%)95.2%
Memory size636.0 B
2023-12-11T03:17:06.868074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length7
Mean length10.666667
Min length6

Characters and Unicode

Total characters32
Distinct characters24
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
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 row계명대학교성서캠퍼스 첨단산업지원센터
2nd row장원빌딩6층
3rd row장원빌딩 6층
ValueCountFrequency (%)
계명대학교성서캠퍼스 1
20.0%
첨단산업지원센터 1
20.0%
장원빌딩6층 1
20.0%
장원빌딩 1
20.0%
6층 1
20.0%
2023-12-11T03:17:07.450489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 3
 
9.4%
층 2
 
6.2%
6 2
 
6.2%
딩 2
 
6.2%
빌 2
 
6.2%
장 2
 
6.2%
2
 
6.2%
산 1
 
3.1%
터 1
 
3.1%
센 1
 
3.1%
Other values (14) 14
43.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 28
87.5%
Decimal Number 2
 
6.2%
Space Separator 2
 
6.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 3
 
10.7%
층 2
 
7.1%
딩 2
 
7.1%
빌 2
 
7.1%
장 2
 
7.1%
산 1
 
3.6%
터 1
 
3.6%
센 1
 
3.6%
지 1
 
3.6%
업 1
 
3.6%
Other values (12) 12
42.9%
Decimal Number
ValueCountFrequency (%)
6 2
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 28
87.5%
Common 4
 
12.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 3
 
10.7%
층 2
 
7.1%
딩 2
 
7.1%
빌 2
 
7.1%
장 2
 
7.1%
산 1
 
3.6%
터 1
 
3.6%
센 1
 
3.6%
지 1
 
3.6%
업 1
 
3.6%
Other values (12) 12
42.9%
Common
ValueCountFrequency (%)
6 2
50.0%
2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 28
87.5%
ASCII 4
 
12.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 3
 
10.7%
층 2
 
7.1%
딩 2
 
7.1%
빌 2
 
7.1%
장 2
 
7.1%
산 1
 
3.6%
터 1
 
3.6%
센 1
 
3.6%
지 1
 
3.6%
업 1
 
3.6%
Other values (12) 12
42.9%
ASCII
ValueCountFrequency (%)
6 2
50.0%
2
50.0%

실험실특수주소동
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing63
Missing (%)100.0%
Memory size699.0 B

실험실특수주소호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing63
Missing (%)100.0%
Memory size699.0 B

실험실도로명주소시군구코드
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)20.0%
Missing33
Missing (%)52.4%
Infinite0
Infinite (%)0.0%
Mean27204
Minimum27170
Maximum27710
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T03:17:07.675745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum27170
5-th percentile27170
Q127170
median27170
Q327192.5
95-th percentile27290
Maximum27710
Range540
Interquartile range (IQR)22.5

Descriptive statistics

Standard deviation101.72987
Coefficient of variation (CV)0.0037395187
Kurtosis22.685734
Mean27204
Median Absolute Deviation (MAD)0
Skewness4.5675096
Sum816120
Variance10348.966
MonotonicityNot monotonic
2023-12-11T03:17:07.890248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
27170 22
34.9%
27200 3
 
4.8%
27290 2
 
3.2%
27260 1
 
1.6%
27710 1
 
1.6%
27230 1
 
1.6%
(Missing) 33
52.4%
ValueCountFrequency (%)
27170 22
34.9%
27200 3
 
4.8%
27230 1
 
1.6%
27260 1
 
1.6%
27290 2
 
3.2%
27710 1
 
1.6%
ValueCountFrequency (%)
27710 1
 
1.6%
27290 2
 
3.2%
27260 1
 
1.6%
27230 1
 
1.6%
27200 3
 
4.8%
27170 22
34.9%

실험실도로명주소읍면동코드
Real number (ℝ)

MISSING 

Distinct9
Distinct (%)30.0%
Missing33
Missing (%)52.4%
Infinite0
Infinite (%)0.0%
Mean2.7204113 × 109
Minimum2.7170102 × 109
Maximum2.771034 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T03:17:08.121683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.7170102 × 109
5-th percentile2.7170103 × 109
Q12.7170103 × 109
median2.7170106 × 109
Q32.7192604 × 109
95-th percentile2.7290112 × 109
Maximum2.771034 × 109
Range54023800
Interquartile range (IQR)2250075

Descriptive statistics

Standard deviation10177085
Coefficient of variation (CV)0.0037410096
Kurtosis22.690446
Mean2.7204113 × 109
Median Absolute Deviation (MAD)300
Skewness4.5680868
Sum8.1612338 × 1010
Variance1.0357305 × 1014
MonotonicityNot monotonic
2023-12-11T03:17:08.373374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
2717010300 12
 
19.0%
2717010600 8
 
12.7%
2720010300 3
 
4.8%
2729011200 2
 
3.2%
2726010100 1
 
1.6%
2717010500 1
 
1.6%
2771034000 1
 
1.6%
2717010200 1
 
1.6%
2723011800 1
 
1.6%
(Missing) 33
52.4%
ValueCountFrequency (%)
2717010200 1
 
1.6%
2717010300 12
19.0%
2717010500 1
 
1.6%
2717010600 8
12.7%
2720010300 3
 
4.8%
2723011800 1
 
1.6%
2726010100 1
 
1.6%
2729011200 2
 
3.2%
2771034000 1
 
1.6%
ValueCountFrequency (%)
2771034000 1
 
1.6%
2729011200 2
 
3.2%
2726010100 1
 
1.6%
2723011800 1
 
1.6%
2720010300 3
 
4.8%
2717010600 8
12.7%
2717010500 1
 
1.6%
2717010300 12
19.0%
2717010200 1
 
1.6%

실험실도로명주소읍면동구분
Categorical

Distinct3
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
33 
1
29 
0
 
1

Length

Max length4
Median length4
Mean length2.5714286
Min length1

Unique

Unique1 ?
Unique (%)1.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 33
52.4%
1 29
46.0%
0 1
 
1.6%

Length

2023-12-11T03:17:08.606330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:17:08.816887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 33
52.4%
1 29
46.0%
0 1
 
1.6%

실험실도로명주소코드
Real number (ℝ)

MISSING 

Distinct13
Distinct (%)43.3%
Missing33
Missing (%)52.4%
Infinite0
Infinite (%)0.0%
Mean3545085.3
Minimum2145001
Maximum4244035
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T03:17:09.004004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2145001
5-th percentile3143003.9
Q13143006
median3143508.5
Q34229018
95-th percentile4234170.6
Maximum4244035
Range2099034
Interquartile range (IQR)1086012

Descriptive statistics

Standard deviation597528.64
Coefficient of variation (CV)0.16855127
Kurtosis-1.0263393
Mean3545085.3
Median Absolute Deviation (MAD)503.5
Skewness0.0046728554
Sum1.0635256 × 108
Variance3.5704047 × 1011
MonotonicityNot monotonic
2023-12-11T03:17:09.196613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
4229018 6
 
9.5%
3143005 5
 
7.9%
3143006 5
 
7.9%
3144002 3
 
4.8%
4229291 2
 
3.2%
3143015 2
 
3.2%
4238118 1
 
1.6%
4229346 1
 
1.6%
3143003 1
 
1.6%
4244035 1
 
1.6%
Other values (3) 3
 
4.8%
(Missing) 33
52.4%
ValueCountFrequency (%)
2145001 1
 
1.6%
3143003 1
 
1.6%
3143005 5
7.9%
3143006 5
7.9%
3143010 1
 
1.6%
3143015 2
 
3.2%
3144002 3
4.8%
4229018 6
9.5%
4229264 1
 
1.6%
4229291 2
 
3.2%
ValueCountFrequency (%)
4244035 1
 
1.6%
4238118 1
 
1.6%
4229346 1
 
1.6%
4229291 2
 
3.2%
4229264 1
 
1.6%
4229018 6
9.5%
3144002 3
4.8%
3143015 2
 
3.2%
3143010 1
 
1.6%
3143006 5
7.9%

실험실도로명특수주소
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing61
Missing (%)96.8%
Memory size636.0 B
2023-12-11T03:17:09.417901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5
Min length4

Characters and Unicode

Total characters10
Distinct characters10
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

Unique2 ?
Unique (%)100.0%

Sample

1st row오늘환경측정
2nd row장원빌딩
ValueCountFrequency (%)
오늘환경측정 1
50.0%
장원빌딩 1
50.0%
2023-12-11T03:17:10.005721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
오 1
10.0%
늘 1
10.0%
환 1
10.0%
경 1
10.0%
측 1
10.0%
정 1
10.0%
장 1
10.0%
원 1
10.0%
빌 1
10.0%
딩 1
10.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
오 1
10.0%
늘 1
10.0%
환 1
10.0%
경 1
10.0%
측 1
10.0%
정 1
10.0%
장 1
10.0%
원 1
10.0%
빌 1
10.0%
딩 1
10.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
오 1
10.0%
늘 1
10.0%
환 1
10.0%
경 1
10.0%
측 1
10.0%
정 1
10.0%
장 1
10.0%
원 1
10.0%
빌 1
10.0%
딩 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
오 1
10.0%
늘 1
10.0%
환 1
10.0%
경 1
10.0%
측 1
10.0%
정 1
10.0%
장 1
10.0%
원 1
10.0%
빌 1
10.0%
딩 1
10.0%

실험실도로명주소건물층구분
Categorical

Distinct2
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
33 
0
30 

Length

Max length4
Median length4
Mean length2.5714286
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 33
52.4%
0 30
47.6%

Length

2023-12-11T03:17:10.320095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:17:10.540816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 33
52.4%
0 30
47.6%

실험실도로명주소건물본번호
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)40.0%
Missing33
Missing (%)52.4%
Infinite0
Infinite (%)0.0%
Mean118.43333
Minimum12
Maximum525
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T03:17:10.911635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12
5-th percentile13.9
Q116.25
median92
Q3165
95-th percentile230
Maximum525
Range513
Interquartile range (IQR)148.75

Descriptive statistics

Standard deviation112.80795
Coefficient of variation (CV)0.95250168
Kurtosis4.3614365
Mean118.43333
Median Absolute Deviation (MAD)73
Skewness1.6055216
Sum3553
Variance12725.633
MonotonicityNot monotonic
2023-12-11T03:17:11.219068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
15 6
 
9.5%
165 5
 
7.9%
230 5
 
7.9%
92 3
 
4.8%
160 3
 
4.8%
24 2
 
3.2%
28 1
 
1.6%
13 1
 
1.6%
20 1
 
1.6%
12 1
 
1.6%
Other values (2) 2
 
3.2%
(Missing) 33
52.4%
ValueCountFrequency (%)
12 1
 
1.6%
13 1
 
1.6%
15 6
9.5%
20 1
 
1.6%
24 2
 
3.2%
28 1
 
1.6%
86 1
 
1.6%
92 3
4.8%
160 3
4.8%
165 5
7.9%
ValueCountFrequency (%)
525 1
 
1.6%
230 5
7.9%
165 5
7.9%
160 3
4.8%
92 3
4.8%
86 1
 
1.6%
28 1
 
1.6%
24 2
 
3.2%
20 1
 
1.6%
15 6
9.5%

실험실도로명주소건물부번호
Categorical

IMBALANCE 

Distinct4
Distinct (%)6.3%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
60 
10
 
1
0
 
1
1
 
1

Length

Max length4
Median length4
Mean length3.8730159
Min length1

Unique

Unique3 ?
Unique (%)4.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 60
95.2%
10 1
 
1.6%
0 1
 
1.6%
1 1
 
1.6%

Length

2023-12-11T03:17:11.494291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:17:11.704514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 60
95.2%
10 1
 
1.6%
0 1
 
1.6%
1 1
 
1.6%

실험실도로명주소우편번호
Real number (ℝ)

MISSING 

Distinct10
Distinct (%)34.5%
Missing34
Missing (%)54.0%
Infinite0
Infinite (%)0.0%
Mean612773.76
Minimum41701
Maximum705804
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T03:17:11.885093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41701
5-th percentile41830
Q1703830
median703834
Q3703839
95-th percentile705804
Maximum705804
Range664103
Interquartile range (IQR)9

Descriptive statistics

Standard deviation232405.03
Coefficient of variation (CV)0.37926726
Kurtosis3.1229774
Mean612773.76
Median Absolute Deviation (MAD)5
Skewness-2.2162863
Sum17770439
Variance5.4012096 × 1010
MonotonicityNot monotonic
2023-12-11T03:17:12.199073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
703830 8
 
12.7%
703834 6
 
9.5%
703839 5
 
7.9%
705804 3
 
4.8%
704932 2
 
3.2%
42110 1
 
1.6%
41845 1
 
1.6%
41701 1
 
1.6%
41820 1
 
1.6%
702848 1
 
1.6%
(Missing) 34
54.0%
ValueCountFrequency (%)
41701 1
 
1.6%
41820 1
 
1.6%
41845 1
 
1.6%
42110 1
 
1.6%
702848 1
 
1.6%
703830 8
12.7%
703834 6
9.5%
703839 5
7.9%
704932 2
 
3.2%
705804 3
 
4.8%
ValueCountFrequency (%)
705804 3
 
4.8%
704932 2
 
3.2%
703839 5
7.9%
703834 6
9.5%
703830 8
12.7%
702848 1
 
1.6%
42110 1
 
1.6%
41845 1
 
1.6%
41820 1
 
1.6%
41701 1
 
1.6%

Sample

번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)실험실면적사업장구분명영업소면적위탁업체명실험실지역코드실험실우편번호실험실산실험실번지실험실호실험실통실험실반실험실특수주소실험실특수주소동실험실특수주소호실험실도로명주소시군구코드실험실도로명주소읍면동코드실험실도로명주소읍면동구분실험실도로명주소코드실험실도로명특수주소실험실도로명주소건물층구분실험실도로명주소건물본번호실험실도로명주소건물부번호실험실도로명주소우편번호
01환경측정대행업09_30_17_P627000062700000820060001020210408<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA>703830대구광역시 서구 이현동 42번지 450호대구광역시 서구 와룡로87길 24 (이현동)703830(주)신라엔텍20210408112207U2021-04-10 02:40:00.0<NA>338615.297418264600.19789592.4측정대행업<NA><NA>2717010600703830142450<NA><NA><NA><NA><NA>27170271701060014229291<NA>024<NA>703830
12환경측정대행업09_30_17_P627000062700000820170000420210323<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA><NA><NA>대구광역시 달서구 달구벌대로 1221(3층)<NA>(주)정도환경20210323085733U2021-03-25 02:40:00.0<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>
23환경측정대행업09_30_17_P627000062700000820140001720210317<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA><NA><NA>대구광역시 수성구 동대구로38안길 28, 2층 (범어동)42110(주)테크월20210317173006U2021-03-19 02:40:00.0<NA>346847.037653262190.918869<NA>측정대행업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>27260272601010014238118<NA>028<NA>42110
34환경측정대행업09_30_17_P627000062700000820200000220210427<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA><NA>대구광역시 서구 이현동 42번지 292호대구광역시 서구 와룡로83길 13 (이현동)<NA>(주)이화환경지점20210427093347U2021-04-29 02:40:00.0<NA><NA><NA>99.65측정대행업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
45환경측정대행업09_30_17_P627000062700000820200000320210402<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA>704932대구광역시 달서구 죽전동 372번지대구광역시 달서구 평리로 92 (죽전동)704932대동환경측정20210402085824U2021-04-04 02:40:00.0<NA>338701.951391262918.2444490.0측정대행업<NA><NA>27290112007049321372<NA><NA><NA><NA><NA><NA>27290272901120013143015<NA>092<NA>704932
56환경측정대행업09_30_17_P627000062700000820200000420210427<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA>41845대구광역시 서구 중리동 1144-1대구광역시 서구 평리로35길 13-10 (중리동)41845(주)오늘환경측정20210427151253U2021-04-29 02:40:00.0<NA><NA><NA><NA>측정대행업<NA><NA>271701050041845011441<NA><NA><NA><NA><NA>27170271701050014229346오늘환경측정0131041845
67환경측정대행업09_30_17_P627000062700000820150000120210414<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA><NA><NA>대구광역시 남구 대명남로 160 (대명동)705804(주)대영종합환경20210414122207U2021-04-16 02:40:00.0<NA>342283.311178260627.07398760.05측정대행업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>27200272001030013144002<NA>0160<NA>705804
78환경측정대행업09_30_17_P627000062700000820060001420210427<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA><NA>대구광역시 서구 이현동 192번지 8호대구광역시 서구 북비산로17길 9-7 (이현동)<NA>국일공해측정(주)20210427093252U2021-04-29 02:40:00.0<NA><NA><NA>210.0측정대행업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
89환경측정대행업09_30_17_P627000062700000820070000120201112<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA>703834대구광역시 서구 평리6동 404번지 7호대구광역시 서구 달서천로 92 (평리동)703834DYETEC연구원20201112164635U2020-11-14 02:40:00.0<NA>339371.010099265776.464191<NA>측정대행업<NA><NA>271701030070383414047<NA><NA><NA><NA><NA>27170271701030013143003<NA>092<NA>703834
910환경측정대행업09_30_17_P627000062700000820210000120210427<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA><NA><NA>대구광역시 북구 팔달북로15길 12 (노원동3가)<NA>(주)삼안환경측정20210427151306U2021-04-29 02:40:00.0<NA><NA><NA>133.2측정대행업<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)실험실면적사업장구분명영업소면적위탁업체명실험실지역코드실험실우편번호실험실산실험실번지실험실호실험실통실험실반실험실특수주소실험실특수주소동실험실특수주소호실험실도로명주소시군구코드실험실도로명주소읍면동코드실험실도로명주소읍면동구분실험실도로명주소코드실험실도로명특수주소실험실도로명주소건물층구분실험실도로명주소건물본번호실험실도로명주소건물부번호실험실도로명주소우편번호
5354환경측정대행업09_30_17_P627000062700000820140001620141106<NA>3폐업Q폐업20150204<NA><NA><NA><NA><NA>703839대구광역시 서구 평리3동 719번지 1호대구광역시 서구 서대구로 230 (평리동)703839케이지엔텍20170704173307I2019-03-23 02:20:03.0<NA>340371.264862265362.721318184.08측정대행업<NA><NA>271701030070383917191<NA><NA><NA><NA><NA>27170271701030013143006<NA>0230<NA>703839
5455환경측정대행업09_30_17_P627000062700000820160000120161222<NA>3폐업Q폐업20171031<NA><NA><NA><NA><NA><NA>대구광역시 서구 이현동 42번지 292호대구광역시 서구 와룡로83길 13 (이현동)<NA>(주)이화환경지점20171031101021I2019-03-23 02:20:03.0<NA><NA><NA>74.0측정대행업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
5556환경측정대행업09_30_17_P627000062700000820160000220170120<NA>3폐업Q폐업20180606<NA><NA><NA><NA><NA><NA><NA>대구광역시 서구 국채보상로19길 15 (이현동)703830현대공해측정(주)20180606093157I2019-03-23 02:20:03.0<NA>339130.306851264420.55530179.3측정대행업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>27170271701060014229018<NA>015<NA>703830
5657환경측정대행업09_30_17_P627000062700000820170000120141106<NA>3폐업Q폐업20150204<NA><NA><NA><NA><NA>703839대구광역시 서구 평리3동 719번지 1호대구광역시 서구 서대구로 230 (평리동)703839케이지엔텍20150825161029I2019-03-23 02:20:03.0<NA>340371.264862265362.721318184.08측정대행업<NA><NA>271701030070383917191<NA><NA><NA><NA><NA>27170271701030013143006<NA>0230<NA>703839
5758환경측정대행업09_30_17_P627000062700000820190000120210312<NA>3폐업Q폐업20210319<NA><NA><NA><NA><NA><NA><NA>대구광역시 북구 팔달북로15길 12 (노원동3가)<NA>(주)삼안환경측정20210319141311U2021-03-21 02:40:00.0<NA><NA><NA>133.2측정대행업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
5859환경측정대행업09_30_17_P627000062700000820200000120200210<NA>3폐업Q폐업20200210<NA><NA><NA><NA><NA><NA><NA>대구광역시 서구 국채보상로19길 15 (이현동)703830현대공해측정(주)20200210134843I2020-02-12 00:23:23.0<NA>339130.306851264420.55530179.3측정대행업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>27170271701060014229018<NA>015<NA>703830
5960환경측정대행업09_30_17_P627000062700000820060000920200210<NA>3폐업Q폐업20200219<NA><NA><NA><NA><NA><NA>대구광역시 서구 이현동 42번지 292호대구광역시 서구 와룡로83길 13 (이현동)<NA>(주)이화환경지점20200219161035U2020-02-21 02:40:00.0<NA><NA><NA>99.65측정대행업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
6061환경측정대행업09_30_17_P627000062700000820060001220190724<NA>3폐업Q폐업20190812<NA><NA><NA><NA><NA><NA><NA>대구광역시 북구 팔달북로15길 12 (노원동3가)<NA>(주)삼안환경화학측정20190812151626U2019-08-14 02:40:00.0<NA><NA><NA>133.2측정대행업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
6162환경측정대행업09_30_17_P627000062700000820180000120180523<NA>3폐업Q폐업20180913<NA><NA><NA><NA><NA><NA>대구광역시 달서구 이곡동 531번지 3호대구광역시 달서구 이곡서로7길 17 (이곡동)<NA>삼한측정(주)20181022205232I2018-10-24 02:37:17.0<NA><NA><NA>74.0측정대행업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
6263환경측정대행업09_30_17_P627000062700000820060000720190405<NA>3폐업Q폐업20190909<NA><NA><NA><NA><NA>704932대구광역시 달서구 죽전동 372번지대구광역시 달서구 평리로 92 (죽전동)704932대동환경측정(주)20191002160911U2019-10-04 02:40:00.0<NA>338701.951391262918.24444980.13측정대행업<NA><NA>27290112007049321372<NA><NA><NA><NA><NA><NA>27290272901120013143015<NA>092<NA>704932