Overview

Dataset statistics

Number of variables30
Number of observations51
Missing cells425
Missing cells (%)27.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.0 KiB
Average record size in memory261.5 B

Variable types

Numeric10
Categorical8
Unsupported6
Text5
DateTime1

Dataset

Description22년06월_6270000_대구광역시_09_28_03_P_계량기제조업
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000093851&dataSetDetailId=DDI_0000093872&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
폐업일자 is highly imbalanced (76.2%)Imbalance
인허가취소일자 has 51 (100.0%) missing valuesMissing
휴업시작일자 has 51 (100.0%) missing valuesMissing
휴업종료일자 has 51 (100.0%) missing valuesMissing
재개업일자 has 51 (100.0%) missing valuesMissing
소재지전화 has 7 (13.7%) missing valuesMissing
소재지면적 has 51 (100.0%) missing valuesMissing
소재지우편번호 has 16 (31.4%) missing valuesMissing
소재지전체주소 has 3 (5.9%) missing valuesMissing
도로명전체주소 has 13 (25.5%) missing valuesMissing
도로명우편번호 has 26 (51.0%) missing valuesMissing
업태구분명 has 51 (100.0%) missing valuesMissing
좌표정보(X) has 15 (29.4%) missing valuesMissing
좌표정보(Y) has 15 (29.4%) missing valuesMissing
사무소전화번호 has 7 (13.7%) missing valuesMissing
사업장전화번호 has 17 (33.3%) 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

Reproduction

Analysis started2024-04-21 08:39:25.702661
Analysis finished2024-04-21 08:39:26.365921
Duration0.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26
Minimum1
Maximum51
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size587.0 B
2024-04-21T17:39:26.560692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.5
Q113.5
median26
Q338.5
95-th percentile48.5
Maximum51
Range50
Interquartile range (IQR)25

Descriptive statistics

Standard deviation14.866069
Coefficient of variation (CV)0.57177187
Kurtosis-1.2
Mean26
Median Absolute Deviation (MAD)13
Skewness0
Sum1326
Variance221
MonotonicityStrictly increasing
2024-04-21T17:39:26.998146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
2.0%
2 1
 
2.0%
29 1
 
2.0%
30 1
 
2.0%
31 1
 
2.0%
32 1
 
2.0%
33 1
 
2.0%
34 1
 
2.0%
35 1
 
2.0%
36 1
 
2.0%
Other values (41) 41
80.4%
ValueCountFrequency (%)
1 1
2.0%
2 1
2.0%
3 1
2.0%
4 1
2.0%
5 1
2.0%
6 1
2.0%
7 1
2.0%
8 1
2.0%
9 1
2.0%
10 1
2.0%
ValueCountFrequency (%)
51 1
2.0%
50 1
2.0%
49 1
2.0%
48 1
2.0%
47 1
2.0%
46 1
2.0%
45 1
2.0%
44 1
2.0%
43 1
2.0%
42 1
2.0%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size536.0 B
계량기제조업
51 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
계량기제조업 51
100.0%

Length

2024-04-21T17:39:27.401146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T17:39:27.690648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
계량기제조업 51
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size536.0 B
09_28_03_P
51 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row09_28_03_P
2nd row09_28_03_P
3rd row09_28_03_P
4th row09_28_03_P
5th row09_28_03_P

Common Values

ValueCountFrequency (%)
09_28_03_P 51
100.0%

Length

2024-04-21T17:39:28.000226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T17:39:28.294345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_28_03_p 51
100.0%

개방자치단체코드
Real number (ℝ)

Distinct7
Distinct (%)13.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4892549
Minimum3420000
Maximum6270000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size587.0 B
2024-04-21T17:39:28.545693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3420000
5-th percentile3425000
Q13470000
median6270000
Q36270000
95-th percentile6270000
Maximum6270000
Range2850000
Interquartile range (IQR)2800000

Descriptive statistics

Standard deviation1418775.3
Coefficient of variation (CV)0.28998694
Kurtosis-2.0811807
Mean4892549
Median Absolute Deviation (MAD)0
Skewness-0.040718076
Sum2.4952 × 108
Variance2.0129234 × 1012
MonotonicityIncreasing
2024-04-21T17:39:28.880441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
6270000 26
51.0%
3480000 7
 
13.7%
3470000 6
 
11.8%
3450000 5
 
9.8%
3420000 3
 
5.9%
3460000 3
 
5.9%
3430000 1
 
2.0%
ValueCountFrequency (%)
3420000 3
 
5.9%
3430000 1
 
2.0%
3450000 5
 
9.8%
3460000 3
 
5.9%
3470000 6
 
11.8%
3480000 7
 
13.7%
6270000 26
51.0%
ValueCountFrequency (%)
6270000 26
51.0%
3480000 7
 
13.7%
3470000 6
 
11.8%
3460000 3
 
5.9%
3450000 5
 
9.8%
3430000 1
 
2.0%
3420000 3
 
5.9%

관리번호
Real number (ℝ)

UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0884957 × 1018
Minimum1.967627 × 1017
Maximum2.022345 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size587.0 B
2024-04-21T17:39:29.266876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.967627 × 1017
5-th percentile1.986627 × 1017
Q12.004127 × 1017
median2.011627 × 1017
Q32.012347 × 1018
95-th percentile2.021348 × 1018
Maximum2.022345 × 1018
Range1.8255823 × 1018
Interquartile range (IQR)1.8119343 × 1018

Descriptive statistics

Standard deviation9.15098 × 1017
Coefficient of variation (CV)0.84069969
Kurtosis-2.0814745
Mean1.0884957 × 1018
Median Absolute Deviation (MAD)4.4 × 1015
Skewness0.040522171
Sum1.7304831 × 1017
Variance8.3740434 × 1035
MonotonicityNot monotonic
2024-04-21T17:39:29.715474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2017342013506500002 1
 
2.0%
2006342000006500002 1
 
2.0%
198662700009100001 1
 
2.0%
199562700009100001 1
 
2.0%
199862700009100001 1
 
2.0%
200262700009100001 1
 
2.0%
200362700009100002 1
 
2.0%
200462700009100002 1
 
2.0%
200562700009100001 1
 
2.0%
200562700009100002 1
 
2.0%
Other values (41) 41
80.4%
ValueCountFrequency (%)
196762700009100001 1
2.0%
197262700009100001 1
2.0%
198662700009100001 1
2.0%
198662700009100002 1
2.0%
199162700009100001 1
2.0%
199562700009100001 1
2.0%
199662700009100001 1
2.0%
199862700009100001 1
2.0%
200062700009100001 1
2.0%
200162700009100001 1
2.0%
ValueCountFrequency (%)
2022345016006500002 1
2.0%
2022345016006500001 1
2.0%
2021348036506500003 1
2.0%
2021348036506500001 1
2.0%
2020348036506500001 1
2.0%
2019348036506500003 1
2.0%
2019348036506500001 1
2.0%
2019347018106500002 1
2.0%
2018346014006500001 1
2.0%
2017342013506500002 1
2.0%

인허가일자
Real number (ℝ)

Distinct43
Distinct (%)84.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20063592
Minimum19670428
Maximum20220608
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size587.0 B
2024-04-21T17:39:30.123550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19670428
5-th percentile19860320
Q120030663
median20060817
Q320120572
95-th percentile20210656
Maximum20220608
Range550180
Interquartile range (IQR)89909

Descriptive statistics

Standard deviation114556.07
Coefficient of variation (CV)0.0057096491
Kurtosis2.8127436
Mean20063592
Median Absolute Deviation (MAD)59304
Skewness-1.3685606
Sum1.0232432 × 109
Variance1.3123093 × 1010
MonotonicityNot monotonic
2024-04-21T17:39:30.540045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
20060817 3
 
5.9%
20050118 2
 
3.9%
20011106 2
 
3.9%
20120121 2
 
3.9%
20050801 2
 
3.9%
20051209 2
 
3.9%
20030820 2
 
3.9%
20030506 1
 
2.0%
19950227 1
 
2.0%
19980929 1
 
2.0%
Other values (33) 33
64.7%
ValueCountFrequency (%)
19670428 1
2.0%
19721108 1
2.0%
19860212 1
2.0%
19860428 1
2.0%
19910520 1
2.0%
19931220 1
2.0%
19950227 1
2.0%
19980929 1
2.0%
20000128 1
2.0%
20011106 2
3.9%
ValueCountFrequency (%)
20220608 1
2.0%
20220307 1
2.0%
20210903 1
2.0%
20210408 1
2.0%
20200604 1
2.0%
20191120 1
2.0%
20190902 1
2.0%
20181207 1
2.0%
20170411 1
2.0%
20170125 1
2.0%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing51
Missing (%)100.0%
Memory size587.0 B

영업상태구분코드
Categorical

Distinct2
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size536.0 B
1
39 
3
12 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 39
76.5%
3 12
 
23.5%

Length

2024-04-21T17:39:30.936267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T17:39:31.235469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 39
76.5%
3 12
 
23.5%

영업상태명
Categorical

Distinct2
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size536.0 B
영업/정상
39 
폐업
12 

Length

Max length5
Median length5
Mean length4.2941176
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 39
76.5%
폐업 12
 
23.5%

Length

2024-04-21T17:39:31.568532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T17:39:31.880092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 39
76.5%
폐업 12
 
23.5%

상세영업상태코드
Categorical

Distinct2
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size536.0 B
1
39 
3
12 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 39
76.5%
3 12
 
23.5%

Length

2024-04-21T17:39:32.197161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T17:39:32.499376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 39
76.5%
3 12
 
23.5%

상세영업상태명
Categorical

Distinct3
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size536.0 B
영업중
20 
등록
19 
폐업
12 

Length

Max length3
Median length2
Mean length2.3921569
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업중
2nd row영업중
3rd row영업중
4th row폐업
5th row영업중

Common Values

ValueCountFrequency (%)
영업중 20
39.2%
등록 19
37.3%
폐업 12
23.5%

Length

2024-04-21T17:39:32.832409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T17:39:33.153718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 20
39.2%
등록 19
37.3%
폐업 12
23.5%

폐업일자
Categorical

IMBALANCE 

Distinct5
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Memory size536.0 B
<NA>
47 
20160824
 
1
20120229
 
1
20151207
 
1
20200409
 
1

Length

Max length8
Median length4
Mean length4.3137255
Min length4

Unique

Unique4 ?
Unique (%)7.8%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row20160824
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 47
92.2%
20160824 1
 
2.0%
20120229 1
 
2.0%
20151207 1
 
2.0%
20200409 1
 
2.0%

Length

2024-04-21T17:39:33.524925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T17:39:33.867569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 47
92.2%
20160824 1
 
2.0%
20120229 1
 
2.0%
20151207 1
 
2.0%
20200409 1
 
2.0%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing51
Missing (%)100.0%
Memory size587.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing51
Missing (%)100.0%
Memory size587.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing51
Missing (%)100.0%
Memory size587.0 B

소재지전화
Text

MISSING 

Distinct37
Distinct (%)84.1%
Missing7
Missing (%)13.7%
Memory size536.0 B
2024-04-21T17:39:34.535594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.477273
Min length7

Characters and Unicode

Total characters461
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)68.2%

Sample

1st row031 883 5400
2nd row0539536303
3rd row053 383 7181
4th row0539438359
5th row053 742 3398
ValueCountFrequency (%)
053 11
 
16.2%
0533246154 2
 
2.9%
238 2
 
2.9%
0539536303 2
 
2.9%
0533811740 2
 
2.9%
0535923771 2
 
2.9%
0535861800 2
 
2.9%
0536322225 2
 
2.9%
4600 2
 
2.9%
0539438359 2
 
2.9%
Other values (39) 39
57.4%
2024-04-21T17:39:35.636440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 89
19.3%
3 83
18.0%
5 79
17.1%
1 42
9.1%
8 28
 
6.1%
2 26
 
5.6%
9 25
 
5.4%
24
 
5.2%
7 23
 
5.0%
4 21
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 437
94.8%
Space Separator 24
 
5.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 89
20.4%
3 83
19.0%
5 79
18.1%
1 42
9.6%
8 28
 
6.4%
2 26
 
5.9%
9 25
 
5.7%
7 23
 
5.3%
4 21
 
4.8%
6 21
 
4.8%
Space Separator
ValueCountFrequency (%)
24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 461
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 89
19.3%
3 83
18.0%
5 79
17.1%
1 42
9.1%
8 28
 
6.1%
2 26
 
5.6%
9 25
 
5.4%
24
 
5.2%
7 23
 
5.0%
4 21
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 461
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 89
19.3%
3 83
18.0%
5 79
17.1%
1 42
9.1%
8 28
 
6.1%
2 26
 
5.6%
9 25
 
5.4%
24
 
5.2%
7 23
 
5.0%
4 21
 
4.6%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing51
Missing (%)100.0%
Memory size587.0 B

소재지우편번호
Real number (ℝ)

MISSING 

Distinct26
Distinct (%)74.3%
Missing16
Missing (%)31.4%
Infinite0
Infinite (%)0.0%
Mean704306.66
Minimum701140
Maximum711858
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size587.0 B
2024-04-21T17:39:35.930027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum701140
5-th percentile701957.5
Q1702815
median702873
Q3704900.5
95-th percentile711845.9
Maximum711858
Range10718
Interquartile range (IQR)2085.5

Descriptive statistics

Standard deviation2706.273
Coefficient of variation (CV)0.003842464
Kurtosis3.3067169
Mean704306.66
Median Absolute Deviation (MAD)955
Skewness1.8803997
Sum24650733
Variance7323913.5
MonotonicityNot monotonic
2024-04-21T17:39:36.151977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
702815 3
 
5.9%
702835 3
 
5.9%
704240 2
 
3.9%
702862 2
 
3.9%
703828 2
 
3.9%
706140 2
 
3.9%
702120 2
 
3.9%
704200 1
 
2.0%
702290 1
 
2.0%
702864 1
 
2.0%
Other values (16) 16
31.4%
(Missing) 16
31.4%
ValueCountFrequency (%)
701140 1
 
2.0%
701835 1
 
2.0%
702010 1
 
2.0%
702120 2
3.9%
702290 1
 
2.0%
702813 1
 
2.0%
702815 3
5.9%
702835 3
5.9%
702850 1
 
2.0%
702862 2
3.9%
ValueCountFrequency (%)
711858 1
2.0%
711855 1
2.0%
711842 1
2.0%
706819 1
2.0%
706140 2
3.9%
705805 1
2.0%
704919 1
2.0%
704901 1
2.0%
704900 1
2.0%
704828 1
2.0%

소재지전체주소
Text

MISSING 

Distinct47
Distinct (%)97.9%
Missing3
Missing (%)5.9%
Memory size536.0 B
2024-04-21T17:39:37.132580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length39
Mean length25.208333
Min length19

Characters and Unicode

Total characters1210
Distinct characters104
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)95.8%

Sample

1st row대구광역시 북구 서변동 1724번지 31통 3반 서변그린타운 103동 806호
2nd row경상북도 포항시 남구 대잠동 986번지 5호
3rd row대구광역시 서구 원대동3가 990번지 7호
4th row경상북도 김천시 감문면 문무리 978
5th row대구광역시 북구 침산1동 1025번지 6호
ValueCountFrequency (%)
대구광역시 46
 
19.1%
북구 17
 
7.1%
달서구 10
 
4.1%
달성군 9
 
3.7%
수성구 5
 
2.1%
노원3가 4
 
1.7%
1호 4
 
1.7%
6호 3
 
1.2%
구지면 3
 
1.2%
2호 3
 
1.2%
Other values (111) 137
56.8%
2024-04-21T17:39:38.359466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
274
22.6%
구 87
 
7.2%
대 54
 
4.5%
1 50
 
4.1%
시 48
 
4.0%
지 47
 
3.9%
광 46
 
3.8%
역 46
 
3.8%
번 43
 
3.6%
동 39
 
3.2%
Other values (94) 476
39.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 688
56.9%
Space Separator 274
 
22.6%
Decimal Number 233
 
19.3%
Dash Punctuation 13
 
1.1%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 87
 
12.6%
대 54
 
7.8%
시 48
 
7.0%
지 47
 
6.8%
광 46
 
6.7%
역 46
 
6.7%
번 43
 
6.2%
동 39
 
5.7%
호 29
 
4.2%
달 20
 
2.9%
Other values (80) 229
33.3%
Decimal Number
ValueCountFrequency (%)
1 50
21.5%
2 33
14.2%
3 29
12.4%
0 23
9.9%
7 21
9.0%
9 19
 
8.2%
6 19
 
8.2%
5 16
 
6.9%
8 13
 
5.6%
4 10
 
4.3%
Space Separator
ValueCountFrequency (%)
274
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 688
56.9%
Common 522
43.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 87
 
12.6%
대 54
 
7.8%
시 48
 
7.0%
지 47
 
6.8%
광 46
 
6.7%
역 46
 
6.7%
번 43
 
6.2%
동 39
 
5.7%
호 29
 
4.2%
달 20
 
2.9%
Other values (80) 229
33.3%
Common
ValueCountFrequency (%)
274
52.5%
1 50
 
9.6%
2 33
 
6.3%
3 29
 
5.6%
0 23
 
4.4%
7 21
 
4.0%
9 19
 
3.6%
6 19
 
3.6%
5 16
 
3.1%
- 13
 
2.5%
Other values (4) 25
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 688
56.9%
ASCII 522
43.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
274
52.5%
1 50
 
9.6%
2 33
 
6.3%
3 29
 
5.6%
0 23
 
4.4%
7 21
 
4.0%
9 19
 
3.6%
6 19
 
3.6%
5 16
 
3.1%
- 13
 
2.5%
Other values (4) 25
 
4.8%
Hangul
ValueCountFrequency (%)
구 87
 
12.6%
대 54
 
7.8%
시 48
 
7.0%
지 47
 
6.8%
광 46
 
6.7%
역 46
 
6.7%
번 43
 
6.2%
동 39
 
5.7%
호 29
 
4.2%
달 20
 
2.9%
Other values (80) 229
33.3%

도로명전체주소
Text

MISSING 

Distinct31
Distinct (%)81.6%
Missing13
Missing (%)25.5%
Memory size536.0 B
2024-04-21T17:39:39.318670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length27.5
Mean length25.5
Min length20

Characters and Unicode

Total characters969
Distinct characters110
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)63.2%

Sample

1st row대구광역시 동구 신평로 84, 2층 (신평동)
2nd row대구광역시 동구 동촌로 425 (용계동)
3rd row경상북도 포항시 남구 대이로67번길 5 (대잠동)
4th row대구광역시 서구 옥산로 8 (원대동3가)
5th row경상북도 김천시 감문면 문화로 429-19
ValueCountFrequency (%)
대구광역시 36
 
18.5%
북구 11
 
5.6%
달서구 9
 
4.6%
달성군 7
 
3.6%
수성구 5
 
2.6%
산격동 4
 
2.1%
구지면 3
 
1.5%
신당동 3
 
1.5%
동구 3
 
1.5%
성서공단로21길 2
 
1.0%
Other values (85) 112
57.4%
2024-04-21T17:39:40.674683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
157
 
16.2%
구 70
 
7.2%
대 50
 
5.2%
동 43
 
4.4%
시 40
 
4.1%
로 38
 
3.9%
광 36
 
3.7%
역 36
 
3.7%
( 31
 
3.2%
) 31
 
3.2%
Other values (100) 437
45.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 602
62.1%
Space Separator 157
 
16.2%
Decimal Number 139
 
14.3%
Open Punctuation 31
 
3.2%
Close Punctuation 31
 
3.2%
Dash Punctuation 5
 
0.5%
Other Punctuation 4
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 70
 
11.6%
대 50
 
8.3%
동 43
 
7.1%
시 40
 
6.6%
로 38
 
6.3%
광 36
 
6.0%
역 36
 
6.0%
길 24
 
4.0%
달 18
 
3.0%
성 17
 
2.8%
Other values (85) 230
38.2%
Decimal Number
ValueCountFrequency (%)
2 25
18.0%
1 22
15.8%
5 19
13.7%
4 14
10.1%
3 13
9.4%
7 13
9.4%
6 12
8.6%
8 9
 
6.5%
9 8
 
5.8%
0 4
 
2.9%
Space Separator
ValueCountFrequency (%)
157
100.0%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Close Punctuation
ValueCountFrequency (%)
) 31
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 602
62.1%
Common 367
37.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 70
 
11.6%
대 50
 
8.3%
동 43
 
7.1%
시 40
 
6.6%
로 38
 
6.3%
광 36
 
6.0%
역 36
 
6.0%
길 24
 
4.0%
달 18
 
3.0%
성 17
 
2.8%
Other values (85) 230
38.2%
Common
ValueCountFrequency (%)
157
42.8%
( 31
 
8.4%
) 31
 
8.4%
2 25
 
6.8%
1 22
 
6.0%
5 19
 
5.2%
4 14
 
3.8%
3 13
 
3.5%
7 13
 
3.5%
6 12
 
3.3%
Other values (5) 30
 
8.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 602
62.1%
ASCII 367
37.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
157
42.8%
( 31
 
8.4%
) 31
 
8.4%
2 25
 
6.8%
1 22
 
6.0%
5 19
 
5.2%
4 14
 
3.8%
3 13
 
3.5%
7 13
 
3.5%
6 12
 
3.3%
Other values (5) 30
 
8.2%
Hangul
ValueCountFrequency (%)
구 70
 
11.6%
대 50
 
8.3%
동 43
 
7.1%
시 40
 
6.6%
로 38
 
6.3%
광 36
 
6.0%
역 36
 
6.0%
길 24
 
4.0%
달 18
 
3.0%
성 17
 
2.8%
Other values (85) 230
38.2%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct20
Distinct (%)80.0%
Missing26
Missing (%)51.0%
Infinite0
Infinite (%)0.0%
Mean386525.64
Minimum37684
Maximum711842
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size587.0 B
2024-04-21T17:39:41.034153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37684
5-th percentile39832.2
Q142725
median701835
Q3704240
95-th percentile706683.2
Maximum711842
Range674158
Interquartile range (IQR)661515

Descriptive statistics

Standard deviation337901.57
Coefficient of variation (CV)0.8742022
Kurtosis-2.1737071
Mean386525.64
Median Absolute Deviation (MAD)10007
Skewness-0.085202195
Sum9663141
Variance1.1417747 × 1011
MonotonicityNot monotonic
2024-04-21T17:39:41.410847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
43008 3
 
5.9%
43023 2
 
3.9%
42725 2
 
3.9%
704240 2
 
3.9%
706819 1
 
2.0%
711842 1
 
2.0%
704919 1
 
2.0%
704900 1
 
2.0%
704920 1
 
2.0%
41133 1
 
2.0%
Other values (10) 10
 
19.6%
(Missing) 26
51.0%
ValueCountFrequency (%)
37684 1
 
2.0%
39507 1
 
2.0%
41133 1
 
2.0%
42184 1
 
2.0%
42250 1
 
2.0%
42725 2
3.9%
43008 3
5.9%
43023 2
3.9%
701835 1
 
2.0%
702010 1
 
2.0%
ValueCountFrequency (%)
711842 1
2.0%
706819 1
2.0%
706140 1
2.0%
704920 1
2.0%
704919 1
2.0%
704900 1
2.0%
704240 2
3.9%
703828 1
2.0%
702120 1
2.0%
702050 1
2.0%

사업장명
Text

Distinct36
Distinct (%)70.6%
Missing0
Missing (%)0.0%
Memory size536.0 B
2024-04-21T17:39:42.220973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length7.6666667
Min length4

Characters and Unicode

Total characters391
Distinct characters100
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

Unique24 ?
Unique (%)47.1%

Sample

1st row옴니시스템(주) 대구지점
2nd row신라계기제작소
3rd row(주)우리기술
4th row대성계기제작소
5th row주식회사 태성콘텍
ValueCountFrequency (%)
파워플러스콤(주 3
 
5.5%
대경계량시스템 3
 
5.5%
한국유체기술(주 3
 
5.5%
주)카라 2
 
3.6%
주)지텍산업 2
 
3.6%
태성산업 2
 
3.6%
대성계기제작소 2
 
3.6%
에이앤디판매(주 2
 
3.6%
주)한국센서 2
 
3.6%
신라계기제작소 2
 
3.6%
Other values (30) 32
58.2%
2024-04-21T17:39:43.408805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 33
 
8.4%
( 31
 
7.9%
) 31
 
7.9%
스 16
 
4.1%
기 14
 
3.6%
대 13
 
3.3%
계 12
 
3.1%
이 9
 
2.3%
시 8
 
2.0%
템 7
 
1.8%
Other values (90) 217
55.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 325
83.1%
Open Punctuation 31
 
7.9%
Close Punctuation 31
 
7.9%
Space Separator 4
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 33
 
10.2%
스 16
 
4.9%
기 14
 
4.3%
대 13
 
4.0%
계 12
 
3.7%
이 9
 
2.8%
시 8
 
2.5%
템 7
 
2.2%
량 7
 
2.2%
성 7
 
2.2%
Other values (87) 199
61.2%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Close Punctuation
ValueCountFrequency (%)
) 31
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 325
83.1%
Common 66
 
16.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 33
 
10.2%
스 16
 
4.9%
기 14
 
4.3%
대 13
 
4.0%
계 12
 
3.7%
이 9
 
2.8%
시 8
 
2.5%
템 7
 
2.2%
량 7
 
2.2%
성 7
 
2.2%
Other values (87) 199
61.2%
Common
ValueCountFrequency (%)
( 31
47.0%
) 31
47.0%
4
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 325
83.1%
ASCII 66
 
16.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 33
 
10.2%
스 16
 
4.9%
기 14
 
4.3%
대 13
 
4.0%
계 12
 
3.7%
이 9
 
2.8%
시 8
 
2.5%
템 7
 
2.2%
량 7
 
2.2%
성 7
 
2.2%
Other values (87) 199
61.2%
ASCII
ValueCountFrequency (%)
( 31
47.0%
) 31
47.0%
4
 
6.1%

최종수정시점
Real number (ℝ)

UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0128737 × 1013
Minimum2.0060906 × 1013
Maximum2.0220609 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size587.0 B
2024-04-21T17:39:43.949433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0060906 × 1013
5-th percentile2.0070514 × 1013
Q12.0091221 × 1013
median2.0111103 × 1013
Q32.0175516 × 1013
95-th percentile2.0215606 × 1013
Maximum2.0220609 × 1013
Range1.5970299 × 1011
Interquartile range (IQR)8.4294964 × 1010

Descriptive statistics

Standard deviation5.0068404 × 1010
Coefficient of variation (CV)0.0024874091
Kurtosis-1.0103633
Mean2.0128737 × 1013
Median Absolute Deviation (MAD)2.0095917 × 1010
Skewness0.60062633
Sum1.0265656 × 1015
Variance2.5068451 × 1021
MonotonicityNot monotonic
2024-04-21T17:39:44.210686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20170412142833 1
 
2.0%
20120120123540 1
 
2.0%
20110325134306 1
 
2.0%
20070814102826 1
 
2.0%
20091009145342 1
 
2.0%
20091007174950 1
 
2.0%
20110930170950 1
 
2.0%
20070514143038 1
 
2.0%
20091008130914 1
 
2.0%
20101229135516 1
 
2.0%
Other values (41) 41
80.4%
ValueCountFrequency (%)
20060906164413 1
2.0%
20060906164715 1
2.0%
20070514132606 1
2.0%
20070514132630 1
2.0%
20070514132802 1
2.0%
20070514132904 1
2.0%
20070514143038 1
2.0%
20070814102826 1
2.0%
20091007174950 1
2.0%
20091008130914 1
2.0%
ValueCountFrequency (%)
20220609150913 1
2.0%
20220315092605 1
2.0%
20220308145955 1
2.0%
20210903170344 1
2.0%
20210408105533 1
2.0%
20200917120033 1
2.0%
20200713130229 1
2.0%
20200413180229 1
2.0%
20200217104750 1
2.0%
20200121090648 1
2.0%

데이터갱신구분
Categorical

Distinct2
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size536.0 B
I
45 
U
6 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 45
88.2%
U 6
 
11.8%

Length

2024-04-21T17:39:44.452057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T17:39:44.615371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 45
88.2%
u 6
 
11.8%

데이터갱신일자
Date

Distinct14
Distinct (%)27.5%
Missing0
Missing (%)0.0%
Memory size536.0 B
Minimum2018-08-31 23:59:59
Maximum2022-06-11 00:22:30
2024-04-21T17:39:44.762622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T17:39:44.955140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing51
Missing (%)100.0%
Memory size587.0 B

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct31
Distinct (%)86.1%
Missing15
Missing (%)29.4%
Infinite0
Infinite (%)0.0%
Mean341908.02
Minimum328379.72
Maximum410879.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size587.0 B
2024-04-21T17:39:45.161319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum328379.72
5-th percentile328785.22
Q1334592.14
median340755.1
Q3344350.67
95-th percentile353836.75
Maximum410879.2
Range82499.477
Interquartile range (IQR)9758.5245

Descriptive statistics

Standard deviation13830.136
Coefficient of variation (CV)0.040449873
Kurtosis17.924556
Mean341908.02
Median Absolute Deviation (MAD)5703.3838
Skewness3.6486902
Sum12308689
Variance1.9127267 × 108
MonotonicityNot monotonic
2024-04-21T17:39:45.360245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
344336.370692 2
 
3.9%
342579.66225 2
 
3.9%
336351.455034 2
 
3.9%
333939.000276 2
 
3.9%
353836.746083 2
 
3.9%
340163.889208 1
 
2.0%
329321.218502 1
 
2.0%
335002.250164 1
 
2.0%
341407.038519 1
 
2.0%
334504.894957 1
 
2.0%
Other values (21) 21
41.2%
(Missing) 15
29.4%
ValueCountFrequency (%)
328379.724398 1
2.0%
328584.225853 1
2.0%
328852.21644 1
2.0%
329012.978226 1
2.0%
329321.218502 1
2.0%
332580.0 1
2.0%
333939.000276 2
3.9%
334504.894957 1
2.0%
334621.225167 1
2.0%
335002.250164 1
2.0%
ValueCountFrequency (%)
410879.20095308 1
2.0%
353836.746083 2
3.9%
352149.518987 1
2.0%
351544.53618 1
2.0%
347993.559844 1
2.0%
347017.91799 1
2.0%
344756.70508 1
2.0%
344393.55643 1
2.0%
344336.370692 2
3.9%
344244.890305 1
2.0%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct31
Distinct (%)86.1%
Missing15
Missing (%)29.4%
Infinite0
Infinite (%)0.0%
Mean262110.96
Minimum239248.53
Maximum282589.46
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size587.0 B
2024-04-21T17:39:45.581889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum239248.53
5-th percentile239899.15
Q1260206.32
median262569.19
Q3267755.95
95-th percentile271256.58
Maximum282589.46
Range43340.932
Interquartile range (IQR)7549.6278

Descriptive statistics

Standard deviation9485.6949
Coefficient of variation (CV)0.036189616
Kurtosis1.4019129
Mean262110.96
Median Absolute Deviation (MAD)5033.9078
Skewness-1.030844
Sum9435994.5
Variance89978408
MonotonicityNot monotonic
2024-04-21T17:39:45.796690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
268235.526925 2
 
3.9%
267680.129055 2
 
3.9%
259291.199101 2
 
3.9%
260767.276686 2
 
3.9%
261866.995362 2
 
3.9%
272183.092133 1
 
2.0%
254362.898509 1
 
2.0%
260935.231246 1
 
2.0%
267642.754528 1
 
2.0%
262211.930975 1
 
2.0%
Other values (21) 21
41.2%
(Missing) 15
29.4%
ValueCountFrequency (%)
239248.529887 1
2.0%
239889.968036 1
2.0%
239902.20599 1
2.0%
243305.0 1
2.0%
251098.043305 1
2.0%
254362.898509 1
2.0%
259291.199101 2
3.9%
259405.796434 1
2.0%
260473.166165 1
2.0%
260767.276686 2
3.9%
ValueCountFrequency (%)
282589.461631938 1
2.0%
272183.092133 1
2.0%
270947.744861 1
2.0%
270704.837615 1
2.0%
270372.281141 1
2.0%
268235.526925 2
3.9%
268048.514857 1
2.0%
267983.419022 1
2.0%
267680.129055 2
3.9%
267642.754528 1
2.0%

사무소전화번호
Text

MISSING 

Distinct37
Distinct (%)84.1%
Missing7
Missing (%)13.7%
Memory size536.0 B
2024-04-21T17:39:46.399679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.477273
Min length7

Characters and Unicode

Total characters461
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)68.2%

Sample

1st row031 883 5400
2nd row0539536303
3rd row053 383 7181
4th row0539438359
5th row053 742 3398
ValueCountFrequency (%)
053 11
 
16.2%
0533246154 2
 
2.9%
238 2
 
2.9%
0539536303 2
 
2.9%
0533811740 2
 
2.9%
0535923771 2
 
2.9%
0535861800 2
 
2.9%
0536322225 2
 
2.9%
4600 2
 
2.9%
0539438359 2
 
2.9%
Other values (39) 39
57.4%
2024-04-21T17:39:47.221827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 89
19.3%
3 83
18.0%
5 79
17.1%
1 42
9.1%
8 28
 
6.1%
2 26
 
5.6%
9 25
 
5.4%
24
 
5.2%
7 23
 
5.0%
4 21
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 437
94.8%
Space Separator 24
 
5.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 89
20.4%
3 83
19.0%
5 79
18.1%
1 42
9.6%
8 28
 
6.4%
2 26
 
5.9%
9 25
 
5.7%
7 23
 
5.3%
4 21
 
4.8%
6 21
 
4.8%
Space Separator
ValueCountFrequency (%)
24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 461
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 89
19.3%
3 83
18.0%
5 79
17.1%
1 42
9.1%
8 28
 
6.1%
2 26
 
5.6%
9 25
 
5.4%
24
 
5.2%
7 23
 
5.0%
4 21
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 461
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 89
19.3%
3 83
18.0%
5 79
17.1%
1 42
9.1%
8 28
 
6.1%
2 26
 
5.6%
9 25
 
5.4%
24
 
5.2%
7 23
 
5.0%
4 21
 
4.6%

사업장전화번호
Real number (ℝ)

MISSING 

Distinct23
Distinct (%)67.6%
Missing17
Missing (%)33.3%
Infinite0
Infinite (%)0.0%
Mean5.3528638 × 108
Minimum5.32552 × 108
Maximum5.3983694 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size587.0 B
2024-04-21T17:39:47.437110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.32552 × 108
5-th percentile5.3291687 × 108
Q15.3357298 × 108
median5.3585434 × 108
Q35.360935 × 108
95-th percentile5.3953692 × 108
Maximum5.3983694 × 108
Range7284939
Interquartile range (IQR)2520514.2

Descriptive statistics

Standard deviation2033960.1
Coefficient of variation (CV)0.0037997605
Kurtosis0.21160921
Mean5.3528638 × 108
Median Absolute Deviation (MAD)2023995.5
Skewness0.84228721
Sum1.8199737 × 1010
Variance4.1369936 × 1012
MonotonicityNot monotonic
2024-04-21T17:39:47.673666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
535920373 2
 
3.9%
533521727 2
 
3.9%
533829120 2
 
3.9%
536150072 2
 
3.9%
535923771 2
 
3.9%
539536303 2
 
3.9%
535861800 2
 
3.9%
533831561 2
 
3.9%
536163693 2
 
3.9%
533516008 2
 
3.9%
Other values (13) 14
27.5%
(Missing) 17
33.3%
ValueCountFrequency (%)
532552004 1
2.0%
532552503 1
2.0%
533113060 1
2.0%
533143800 1
2.0%
533516008 2
3.9%
533521727 2
3.9%
533571117 1
2.0%
533578579 1
2.0%
533593382 1
2.0%
533829120 2
3.9%
ValueCountFrequency (%)
539836943 1
2.0%
539538075 1
2.0%
539536303 2
3.9%
536276500 1
2.0%
536163693 2
3.9%
536150072 2
3.9%
535923771 2
3.9%
535920373 2
3.9%
535911119 1
2.0%
535861800 2
3.9%

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)사무소전화번호사업장전화번호
01계량기제조업09_28_03_P3420000201734201350650000220170411<NA>1영업/정상1영업중<NA><NA><NA><NA>031 883 5400<NA><NA><NA>대구광역시 동구 신평로 84, 2층 (신평동)41133옴니시스템(주) 대구지점20170412142833I2018-10-11 15:46:28.0<NA>351544.53618265604.874007031 883 5400<NA>
12계량기제조업09_28_03_P3420000200634200000650000220120120<NA>1영업/정상1영업중<NA><NA><NA><NA>0539536303<NA><NA>대구광역시 북구 서변동 1724번지 31통 3반 서변그린타운 103동 806호대구광역시 동구 동촌로 425 (용계동)701835신라계기제작소20120120123540I2018-10-11 15:46:28.0<NA>344029.924271270947.7448610539536303539536303
23계량기제조업09_28_03_P3420000201534201350650000320150915<NA>1영업/정상1영업중<NA><NA><NA><NA>053 383 7181<NA><NA>경상북도 포항시 남구 대잠동 986번지 5호경상북도 포항시 남구 대이로67번길 5 (대잠동)37684(주)우리기술20220315092605U2022-03-17 02:40:00.0<NA>410879.200953282589.461632053 383 7181<NA>
34계량기제조업09_28_03_P3430000200634300000650000420120131<NA>3폐업3폐업20160824<NA><NA><NA>0539438359<NA>703828대구광역시 서구 원대동3가 990번지 7호대구광역시 서구 옥산로 8 (원대동3가)703828대성계기제작소20160824174747I2018-10-11 15:46:28.0<NA>342312.897137266350.3592380539438359533521727
45계량기제조업09_28_03_P3450000202234501600650000120220307<NA>1영업/정상1영업중<NA><NA><NA><NA><NA><NA><NA>경상북도 김천시 감문면 문무리 978경상북도 김천시 감문면 문화로 429-1939507주식회사 태성콘텍20220308145955I2022-03-10 13:22:36.0<NA><NA><NA><NA><NA>
56계량기제조업09_28_03_P3450000200334500000650000220030820<NA>1영업/정상1영업중<NA><NA><NA><NA>053 742 3398<NA>702862대구광역시 북구 침산1동 1025번지 6호대구광역시 북구 노원로 182 (침산동)702050에이앤디판매(주)20180620094922I2018-10-11 15:46:28.0<NA>342579.66225267680.129055053 742 3398533516008
67계량기제조업09_28_03_P3450000200534500000650000120050118<NA>1영업/정상1영업중<NA><NA><NA><NA>053 954 4600<NA>702120대구광역시 북구 동변동 200번지 2호대구광역시 북구 동변로24길 58-1 (동변동)702120한국유체기술(주)20200121090648U2020-01-23 02:40:00.0<NA>344393.55643270704.837615053 954 4600536163693
78계량기제조업09_28_03_P3450000200534500000650000220050801<NA>1영업/정상1영업중<NA><NA><NA><NA>0533811740<NA>702010대구광역시 북구 산격동 646번지 20호대구광역시 북구 동북로 43 (산격동)702010카스대구점20111222134702I2018-10-11 15:46:28.0<NA>344244.890305268048.5148570533811740533831561
89계량기제조업09_28_03_P3450000202234501600650000220220608<NA>1영업/정상1영업중<NA><NA><NA><NA>0539540100<NA><NA>대구광역시 수성구 대흥동 857-5대구광역시 수성구 알파시티1로31길 17(대흥동)42250(주)한맥아이피에스20220609150913I2022-06-11 00:22:30.0<NA><NA><NA>0539540100<NA>
910계량기제조업09_28_03_P3460000201834601400650000120181207<NA>1영업/정상1영업중<NA><NA><NA><NA>070 77880136<NA><NA>대구광역시 수성구 지산동 1019-12대구광역시 수성구 무학로35길 76 (지산동)42184(주)엔케이 어드벤스20200917120033U2020-09-19 02:40:00.0<NA>347017.91799260473.166165070 77880136<NA>
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)사무소전화번호사업장전화번호
4142계량기제조업09_28_03_P627000020016270000910000120011106<NA>1영업/정상1등록<NA><NA><NA><NA>0535923771<NA>704828대구광역시 달서구 월성2동 86-1번지 월성아파트형공장 5층 503호<NA><NA>파워플러스콤(주)20100707174854I2018-08-31 23:59:59.0<NA><NA><NA>0535923771535923771
4243계량기제조업09_28_03_P627000020066270000910000220060112<NA>1영업/정상1등록<NA><NA><NA><NA>0539536303<NA>701835대구광역시 동구 용계동 936번지대구광역시 동구 동촌로 425 (용계동)<NA>신라계기제작소20060906164715I2018-08-31 23:59:59.0<NA>352149.518987265228.7058130539536303539536303
4344계량기제조업09_28_03_P627000020066270000910000420061221<NA>1영업/정상1등록<NA><NA><NA><NA>0539438359<NA>703828대구광역시 서구 원대3가 990-7번지<NA><NA>대성계기제작소20091008131300I2018-08-31 23:59:59.0<NA><NA><NA>0539438359533521727
4445계량기제조업09_28_03_P627000019726270000910000119721108<NA>3폐업3폐업<NA><NA><NA><NA>0533578579<NA>702815대구광역시 북구 노원3가 305번지대구광역시 북구 노원로9길 17 (노원동3가)<NA>대원도량형기제작소20091221155050I2018-08-31 23:59:59.0<NA>341346.308825267094.6644410533578579533578579
4546계량기제조업09_28_03_P627000020006270000910000120000128<NA>3폐업3폐업<NA><NA><NA><NA>0532552503<NA>702815대구광역시 북구 노원3가 239-8번지<NA><NA>서진종합상사20091221155009I2018-08-31 23:59:59.0<NA><NA><NA>0532552503532552503
4647계량기제조업09_28_03_P627000020066270000910000320060817<NA>3폐업3폐업<NA><NA><NA><NA>0533246154<NA>702835대구광역시 북구 산격2동 671번지대구광역시 북구 연암로42길 37 (산격동)<NA>대경계량시스템20070514132904I2018-08-31 23:59:59.0<NA>344336.370692268235.5269250533246154533829120
4748계량기제조업09_28_03_P627000019866270000910000219860212<NA>3폐업3폐업<NA><NA><NA><NA><NA><NA>705805대구광역시 남구 대명9동 882-4번지<NA><NA>화성설비계량공사20070514132606I2018-08-31 23:59:59.0<NA><NA><NA><NA>536276500
4849계량기제조업09_28_03_P627000019676270000910000119670428<NA>3폐업3폐업<NA><NA><NA><NA><NA><NA>702873대구광역시 북구 산격1동 517번지대구광역시 북구 동북로 92 (산격동)<NA>상수도사업본부 시설관리소20070514132630I2018-08-31 23:59:59.0<NA>344756.70508267983.419022<NA>539538075
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