Overview

Dataset statistics

Number of variables29
Number of observations26
Missing cells234
Missing cells (%)31.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.5 KiB
Average record size in memory257.1 B

Variable types

Numeric7
Categorical10
Unsupported8
Text3
DateTime1

Dataset

Description22년09월_6270000_대구광역시_07_22_16_P_용기냉동기특정설비
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000096630&dataSetDetailId=DDI_0000096640&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
재개업일자 is highly imbalanced (70.5%)Imbalance
인허가취소일자 has 26 (100.0%) missing valuesMissing
폐업일자 has 18 (69.2%) missing valuesMissing
휴업시작일자 has 26 (100.0%) missing valuesMissing
휴업종료일자 has 26 (100.0%) missing valuesMissing
소재지전화 has 26 (100.0%) missing valuesMissing
소재지면적 has 26 (100.0%) missing valuesMissing
소재지우편번호 has 26 (100.0%) missing valuesMissing
소재지전체주소 has 3 (11.5%) missing valuesMissing
도로명전체주소 has 5 (19.2%) missing valuesMissing
업태구분명 has 26 (100.0%) missing valuesMissing
설비규격 has 26 (100.0%) missing valuesMissing
번호 has unique valuesUnique
관리번호 has unique valuesUnique
최종수정시점 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
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
소재지우편번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
설비규격 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 19:07:42.967273
Analysis finished2023-12-10 19:07:43.357795
Duration0.39 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.5
Minimum1
Maximum26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-11T04:07:43.470798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.25
Q17.25
median13.5
Q319.75
95-th percentile24.75
Maximum26
Range25
Interquartile range (IQR)12.5

Descriptive statistics

Standard deviation7.6485293
Coefficient of variation (CV)0.56655772
Kurtosis-1.2
Mean13.5
Median Absolute Deviation (MAD)6.5
Skewness0
Sum351
Variance58.5
MonotonicityStrictly increasing
2023-12-11T04:07:43.673130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1 1
 
3.8%
15 1
 
3.8%
26 1
 
3.8%
25 1
 
3.8%
24 1
 
3.8%
23 1
 
3.8%
22 1
 
3.8%
21 1
 
3.8%
20 1
 
3.8%
19 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
1 1
3.8%
2 1
3.8%
3 1
3.8%
4 1
3.8%
5 1
3.8%
6 1
3.8%
7 1
3.8%
8 1
3.8%
9 1
3.8%
10 1
3.8%
ValueCountFrequency (%)
26 1
3.8%
25 1
3.8%
24 1
3.8%
23 1
3.8%
22 1
3.8%
21 1
3.8%
20 1
3.8%
19 1
3.8%
18 1
3.8%
17 1
3.8%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size340.0 B
용기냉동기특정설비
26 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
용기냉동기특정설비 26
100.0%

Length

2023-12-11T04:07:43.946997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:07:44.169731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
용기냉동기특정설비 26
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size340.0 B
07_22_16_P
26 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row07_22_16_P
2nd row07_22_16_P
3rd row07_22_16_P
4th row07_22_16_P
5th row07_22_16_P

Common Values

ValueCountFrequency (%)
07_22_16_P 26
100.0%

Length

2023-12-11T04:07:44.373624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:07:44.526688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_16_p 26
100.0%

개방자치단체코드
Categorical

Distinct5
Distinct (%)19.2%
Missing0
Missing (%)0.0%
Memory size340.0 B
3450000
9 
3480000
8 
3470000
6 
3420000
2 
3430000
1 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique1 ?
Unique (%)3.8%

Sample

1st row3420000
2nd row3420000
3rd row3430000
4th row3450000
5th row3450000

Common Values

ValueCountFrequency (%)
3450000 9
34.6%
3480000 8
30.8%
3470000 6
23.1%
3420000 2
 
7.7%
3430000 1
 
3.8%

Length

2023-12-11T04:07:44.682375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:07:44.847518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3450000 9
34.6%
3480000 8
30.8%
3470000 6
23.1%
3420000 2
 
7.7%
3430000 1
 
3.8%

관리번호
Real number (ℝ)

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0131153 × 1018
Minimum2.003347 × 1018
Maximum2.022348 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-11T04:07:45.025482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.003347 × 1018
5-th percentile2.0053458 × 1018
Q12.0078455 × 1018
median2.0128465 × 1018
Q32.019097 × 1018
95-th percentile2.021348 × 1018
Maximum2.022348 × 1018
Range1.9001025 × 1016
Interquartile range (IQR)1.1251508 × 1016

Descriptive statistics

Standard deviation6.028876 × 1015
Coefficient of variation (CV)0.0029947991
Kurtosis-1.359258
Mean2.0131153 × 1018
Median Absolute Deviation (MAD)6.001004 × 1015
Skewness0.033356323
Sum-2.9992337 × 1018
Variance3.6347346 × 1031
MonotonicityNot monotonic
2023-12-11T04:07:45.216255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
2006342013516500001 1
 
3.8%
2010347012416500001 1
 
3.8%
2021348036516500001 1
 
3.8%
2005348028916500003 1
 
3.8%
2005348028916500001 1
 
3.8%
2020348036516500001 1
 
3.8%
2022348036516500001 1
 
3.8%
2012348031216500001 1
 
3.8%
2021348036516500002 1
 
3.8%
2009348029116500001 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
2003347011716500000 1
3.8%
2005345009916500001 1
3.8%
2005348028916500001 1
3.8%
2005348028916500003 1
3.8%
2006342013516500001 1
3.8%
2006345009916500001 1
3.8%
2007345009916500001 1
3.8%
2009347011716500001 1
3.8%
2009348029116500001 1
3.8%
2010345009916500001 1
3.8%
ValueCountFrequency (%)
2022348036516500001 1
3.8%
2021348036516500002 1
3.8%
2021348036516500001 1
3.8%
2020348036516500001 1
3.8%
2020345016016500002 1
3.8%
2020345016016500001 1
3.8%
2019347018016500001 1
3.8%
2018347018016500001 1
3.8%
2016342013516500001 1
3.8%
2015343009516500017 1
3.8%

인허가일자
Real number (ℝ)

Distinct24
Distinct (%)92.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20117252
Minimum19870330
Maximum20220817
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-11T04:07:45.431127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19870330
5-th percentile20033039
Q120063016
median20120818
Q320188583
95-th percentile20210979
Maximum20220817
Range350487
Interquartile range (IQR)125566.75

Descriptive statistics

Standard deviation78931.621
Coefficient of variation (CV)0.0039235786
Kurtosis2.2913585
Mean20117252
Median Absolute Deviation (MAD)60459.5
Skewness-1.0566705
Sum5.2304856 × 108
Variance6.2302007 × 109
MonotonicityNot monotonic
2023-12-11T04:07:45.639811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
20140718 2
 
7.7%
20200521 2
 
7.7%
20060110 1
 
3.8%
20191101 1
 
3.8%
20210831 1
 
3.8%
20040315 1
 
3.8%
20050428 1
 
3.8%
20201210 1
 
3.8%
20220817 1
 
3.8%
20120522 1
 
3.8%
Other values (14) 14
53.8%
ValueCountFrequency (%)
19870330 1
3.8%
20030614 1
3.8%
20040315 1
3.8%
20050428 1
3.8%
20051121 1
3.8%
20060110 1
3.8%
20060621 1
3.8%
20070202 1
3.8%
20090908 1
3.8%
20091223 1
3.8%
ValueCountFrequency (%)
20220817 1
3.8%
20211028 1
3.8%
20210831 1
3.8%
20201210 1
3.8%
20200521 2
7.7%
20191101 1
3.8%
20181029 1
3.8%
20160811 1
3.8%
20140718 2
7.7%
20130429 1
3.8%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing26
Missing (%)100.0%
Memory size366.0 B

영업상태구분코드
Categorical

Distinct2
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size340.0 B
1
18 
3
8 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 18
69.2%
3 8
30.8%

Length

2023-12-11T04:07:45.866718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:07:46.024082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 18
69.2%
3 8
30.8%

영업상태명
Categorical

Distinct2
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size340.0 B
영업/정상
18 
폐업
8 

Length

Max length5
Median length5
Mean length4.0769231
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 18
69.2%
폐업 8
30.8%

Length

2023-12-11T04:07:46.182569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:07:46.334613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 18
69.2%
폐업 8
30.8%

상세영업상태코드
Categorical

Distinct2
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size340.0 B
1
18 
3
8 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 18
69.2%
3 8
30.8%

Length

2023-12-11T04:07:46.481095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:07:46.621695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 18
69.2%
3 8
30.8%

상세영업상태명
Categorical

Distinct2
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size340.0 B
영업중
18 
폐업
8 

Length

Max length3
Median length3
Mean length2.6923077
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 18
69.2%
폐업 8
30.8%

Length

2023-12-11T04:07:46.803383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:07:46.959708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 18
69.2%
폐업 8
30.8%

폐업일자
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)87.5%
Missing18
Missing (%)69.2%
Infinite0
Infinite (%)0.0%
Mean20158285
Minimum20120409
Maximum20201101
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-11T04:07:47.111142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20120409
5-th percentile20120546
Q120135516
median20160704
Q320171094
95-th percentile20201073
Maximum20201101
Range80692
Interquartile range (IQR)35577.5

Descriptive statistics

Standard deviation31254.676
Coefficient of variation (CV)0.001550463
Kurtosis-1.0087477
Mean20158285
Median Absolute Deviation (MAD)30093
Skewness0.27380934
Sum1.6126628 × 108
Variance9.7685475 × 108
MonotonicityNot monotonic
2023-12-11T04:07:47.277085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
20160704 2
 
7.7%
20120409 1
 
3.8%
20161118 1
 
3.8%
20140421 1
 
3.8%
20201101 1
 
3.8%
20201020 1
 
3.8%
20120801 1
 
3.8%
(Missing) 18
69.2%
ValueCountFrequency (%)
20120409 1
3.8%
20120801 1
3.8%
20140421 1
3.8%
20160704 2
7.7%
20161118 1
3.8%
20201020 1
3.8%
20201101 1
3.8%
ValueCountFrequency (%)
20201101 1
3.8%
20201020 1
3.8%
20161118 1
3.8%
20160704 2
7.7%
20140421 1
3.8%
20120801 1
3.8%
20120409 1
3.8%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing26
Missing (%)100.0%
Memory size366.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing26
Missing (%)100.0%
Memory size366.0 B

재개업일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Memory size340.0 B
<NA>
24 
20150108
 
1
20110915
 
1

Length

Max length8
Median length4
Mean length4.3076923
Min length4

Unique

Unique2 ?
Unique (%)7.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 24
92.3%
20150108 1
 
3.8%
20110915 1
 
3.8%

Length

2023-12-11T04:07:47.513660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:07:47.694151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 24
92.3%
20150108 1
 
3.8%
20110915 1
 
3.8%

소재지전화
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing26
Missing (%)100.0%
Memory size366.0 B

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing26
Missing (%)100.0%
Memory size366.0 B

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing26
Missing (%)100.0%
Memory size366.0 B

소재지전체주소
Text

MISSING 

Distinct19
Distinct (%)82.6%
Missing3
Missing (%)11.5%
Memory size340.0 B
2023-12-11T04:07:47.927536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length21.565217
Min length17

Characters and Unicode

Total characters496
Distinct characters47
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

Unique15 ?
Unique (%)65.2%

Sample

1st row대구광역시 북구 침산동 791
2nd row대구광역시 북구 검단동 777-58
3rd row대구광역시 북구 검단동 777-58
4th row대구광역시 북구 침산동 790-1
5th row대구광역시 북구 검단동 887-167
ValueCountFrequency (%)
대구광역시 23
22.5%
북구 9
 
8.8%
달성군 8
 
7.8%
검단동 6
 
5.9%
달서구 6
 
5.9%
논공읍 5
 
4.9%
본리리 4
 
3.9%
침산동 3
 
2.9%
700-15 2
 
2.0%
세천리 2
 
2.0%
Other values (29) 34
33.3%
2023-12-11T04:07:48.460465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
102
20.6%
구 39
 
7.9%
대 23
 
4.6%
광 23
 
4.6%
역 23
 
4.6%
시 23
 
4.6%
- 21
 
4.2%
1 20
 
4.0%
7 20
 
4.0%
동 17
 
3.4%
Other values (37) 185
37.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 267
53.8%
Decimal Number 106
 
21.4%
Space Separator 102
 
20.6%
Dash Punctuation 21
 
4.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 39
14.6%
대 23
 
8.6%
광 23
 
8.6%
역 23
 
8.6%
시 23
 
8.6%
동 17
 
6.4%
달 14
 
5.2%
리 12
 
4.5%
북 10
 
3.7%
군 8
 
3.0%
Other values (25) 75
28.1%
Decimal Number
ValueCountFrequency (%)
1 20
18.9%
7 20
18.9%
8 15
14.2%
0 13
12.3%
9 9
8.5%
5 9
8.5%
2 8
 
7.5%
6 7
 
6.6%
4 3
 
2.8%
3 2
 
1.9%
Space Separator
ValueCountFrequency (%)
102
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 267
53.8%
Common 229
46.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 39
14.6%
대 23
 
8.6%
광 23
 
8.6%
역 23
 
8.6%
시 23
 
8.6%
동 17
 
6.4%
달 14
 
5.2%
리 12
 
4.5%
북 10
 
3.7%
군 8
 
3.0%
Other values (25) 75
28.1%
Common
ValueCountFrequency (%)
102
44.5%
- 21
 
9.2%
1 20
 
8.7%
7 20
 
8.7%
8 15
 
6.6%
0 13
 
5.7%
9 9
 
3.9%
5 9
 
3.9%
2 8
 
3.5%
6 7
 
3.1%
Other values (2) 5
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 267
53.8%
ASCII 229
46.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
102
44.5%
- 21
 
9.2%
1 20
 
8.7%
7 20
 
8.7%
8 15
 
6.6%
0 13
 
5.7%
9 9
 
3.9%
5 9
 
3.9%
2 8
 
3.5%
6 7
 
3.1%
Other values (2) 5
 
2.2%
Hangul
ValueCountFrequency (%)
구 39
14.6%
대 23
 
8.6%
광 23
 
8.6%
역 23
 
8.6%
시 23
 
8.6%
동 17
 
6.4%
달 14
 
5.2%
리 12
 
4.5%
북 10
 
3.7%
군 8
 
3.0%
Other values (25) 75
28.1%

도로명전체주소
Text

MISSING 

Distinct19
Distinct (%)90.5%
Missing5
Missing (%)19.2%
Memory size340.0 B
2023-12-11T04:07:48.756756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length30
Mean length24.857143
Min length22

Characters and Unicode

Total characters522
Distinct characters60
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

Unique17 ?
Unique (%)81.0%

Sample

1st row대구광역시 동구 안심로59길 8 (각산동)
2nd row대구광역시 동구 안심로59길 13 (동호동)
3rd row대구광역시 서구 팔달로2길 29 (비산동)
4th row대구광역시 북구 침산로 285 (침산동)
5th row대구광역시 북구 검단동로 5, 101호 (검단동, 검단테크노벨리)
ValueCountFrequency (%)
대구광역시 21
 
18.8%
북구 8
 
7.1%
달성군 7
 
6.2%
검단동 5
 
4.5%
논공읍 4
 
3.6%
달서구 3
 
2.7%
침산로 3
 
2.7%
침산동 3
 
2.7%
검단동로 3
 
2.7%
5 2
 
1.8%
Other values (45) 53
47.3%
2023-12-11T04:07:49.324140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
95
18.2%
구 36
 
6.9%
대 22
 
4.2%
동 22
 
4.2%
로 22
 
4.2%
시 21
 
4.0%
광 21
 
4.0%
역 21
 
4.0%
) 14
 
2.7%
( 14
 
2.7%
Other values (50) 234
44.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 323
61.9%
Space Separator 95
 
18.2%
Decimal Number 68
 
13.0%
Close Punctuation 14
 
2.7%
Open Punctuation 14
 
2.7%
Other Punctuation 6
 
1.1%
Dash Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 36
 
11.1%
대 22
 
6.8%
동 22
 
6.8%
로 22
 
6.8%
시 21
 
6.5%
광 21
 
6.5%
역 21
 
6.5%
단 13
 
4.0%
달 13
 
4.0%
검 12
 
3.7%
Other values (35) 120
37.2%
Decimal Number
ValueCountFrequency (%)
1 14
20.6%
5 10
14.7%
2 9
13.2%
4 7
10.3%
9 6
8.8%
7 6
8.8%
8 6
8.8%
6 4
 
5.9%
0 3
 
4.4%
3 3
 
4.4%
Space Separator
ValueCountFrequency (%)
95
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 323
61.9%
Common 199
38.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 36
 
11.1%
대 22
 
6.8%
동 22
 
6.8%
로 22
 
6.8%
시 21
 
6.5%
광 21
 
6.5%
역 21
 
6.5%
단 13
 
4.0%
달 13
 
4.0%
검 12
 
3.7%
Other values (35) 120
37.2%
Common
ValueCountFrequency (%)
95
47.7%
) 14
 
7.0%
( 14
 
7.0%
1 14
 
7.0%
5 10
 
5.0%
2 9
 
4.5%
4 7
 
3.5%
9 6
 
3.0%
7 6
 
3.0%
, 6
 
3.0%
Other values (5) 18
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 323
61.9%
ASCII 199
38.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
95
47.7%
) 14
 
7.0%
( 14
 
7.0%
1 14
 
7.0%
5 10
 
5.0%
2 9
 
4.5%
4 7
 
3.5%
9 6
 
3.0%
7 6
 
3.0%
, 6
 
3.0%
Other values (5) 18
 
9.0%
Hangul
ValueCountFrequency (%)
구 36
 
11.1%
대 22
 
6.8%
동 22
 
6.8%
로 22
 
6.8%
시 21
 
6.5%
광 21
 
6.5%
역 21
 
6.5%
단 13
 
4.0%
달 13
 
4.0%
검 12
 
3.7%
Other values (35) 120
37.2%

도로명우편번호
Categorical

Distinct6
Distinct (%)23.1%
Missing0
Missing (%)0.0%
Memory size340.0 B
<NA>
20 
42921
 
2
41508
 
1
41510
 
1
42712
 
1

Length

Max length5
Median length4
Mean length4.2307692
Min length4

Unique

Unique4 ?
Unique (%)15.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 20
76.9%
42921 2
 
7.7%
41508 1
 
3.8%
41510 1
 
3.8%
42712 1
 
3.8%
43013 1
 
3.8%

Length

2023-12-11T04:07:49.528361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:07:49.675798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 20
76.9%
42921 2
 
7.7%
41508 1
 
3.8%
41510 1
 
3.8%
42712 1
 
3.8%
43013 1
 
3.8%

사업장명
Text

Distinct20
Distinct (%)76.9%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-11T04:07:49.915587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length9
Mean length7.7307692
Min length5

Characters and Unicode

Total characters201
Distinct characters64
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)53.8%

Sample

1st row(주)케이·피·씨
2nd row(주)케이·피·씨
3rd row화성밸브(주)
4th row(주)삼창이엔지
5th row미래에너지
ValueCountFrequency (%)
주)덕산코트랜 3
 
10.3%
주)케이·피·씨 2
 
6.9%
성서공장 2
 
6.9%
주)미래에너지 2
 
6.9%
주)이노컴 2
 
6.9%
주)삼창이엔지 2
 
6.9%
미래에너지 2
 
6.9%
주)벡트론 1
 
3.4%
주)금강밸브 1
 
3.4%
2공장 1
 
3.4%
Other values (11) 11
37.9%
2023-12-11T04:07:50.369658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 23
 
11.4%
) 23
 
11.4%
주 23
 
11.4%
이 9
 
4.5%
지 7
 
3.5%
에 6
 
3.0%
공 5
 
2.5%
너 5
 
2.5%
성 4
 
2.0%
미 4
 
2.0%
Other values (54) 92
45.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 144
71.6%
Open Punctuation 23
 
11.4%
Close Punctuation 23
 
11.4%
Other Punctuation 4
 
2.0%
Space Separator 3
 
1.5%
Uppercase Letter 3
 
1.5%
Decimal Number 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 23
 
16.0%
이 9
 
6.2%
지 7
 
4.9%
에 6
 
4.2%
공 5
 
3.5%
너 5
 
3.5%
성 4
 
2.8%
미 4
 
2.8%
래 4
 
2.8%
트 4
 
2.8%
Other values (46) 73
50.7%
Uppercase Letter
ValueCountFrequency (%)
G 1
33.3%
N 1
33.3%
E 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Other Punctuation
ValueCountFrequency (%)
· 4
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 144
71.6%
Common 54
 
26.9%
Latin 3
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 23
 
16.0%
이 9
 
6.2%
지 7
 
4.9%
에 6
 
4.2%
공 5
 
3.5%
너 5
 
3.5%
성 4
 
2.8%
미 4
 
2.8%
래 4
 
2.8%
트 4
 
2.8%
Other values (46) 73
50.7%
Common
ValueCountFrequency (%)
( 23
42.6%
) 23
42.6%
· 4
 
7.4%
3
 
5.6%
2 1
 
1.9%
Latin
ValueCountFrequency (%)
G 1
33.3%
N 1
33.3%
E 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 144
71.6%
ASCII 53
 
26.4%
None 4
 
2.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 23
43.4%
) 23
43.4%
3
 
5.7%
2 1
 
1.9%
G 1
 
1.9%
N 1
 
1.9%
E 1
 
1.9%
Hangul
ValueCountFrequency (%)
주 23
 
16.0%
이 9
 
6.2%
지 7
 
4.9%
에 6
 
4.2%
공 5
 
3.5%
너 5
 
3.5%
성 4
 
2.8%
미 4
 
2.8%
래 4
 
2.8%
트 4
 
2.8%
Other values (46) 73
50.7%
None
ValueCountFrequency (%)
· 4
100.0%

최종수정시점
Real number (ℝ)

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0167252 × 1013
Minimum2.0080123 × 1013
Maximum2.022083 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-11T04:07:50.541474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0080123 × 1013
5-th percentile2.0085198 × 1013
Q12.013345 × 1013
median2.0165759 × 1013
Q32.0200968 × 1013
95-th percentile2.0218321 × 1013
Maximum2.022083 × 1013
Range1.4070693 × 1011
Interquartile range (IQR)6.7518168 × 1010

Descriptive statistics

Standard deviation4.2475328 × 1010
Coefficient of variation (CV)0.0021061535
Kurtosis-0.57286283
Mean2.0167252 × 1013
Median Absolute Deviation (MAD)3.4951007 × 1010
Skewness-0.62177937
Sum5.2434855 × 1014
Variance1.8041535 × 1021
MonotonicityNot monotonic
2023-12-11T04:07:50.726417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
20160810134204 1
 
3.8%
20200806093127 1
 
3.8%
20210923154313 1
 
3.8%
20131126191151 1
 
3.8%
20131126191445 1
 
3.8%
20210830110702 1
 
3.8%
20220830100545 1
 
3.8%
20131126191002 1
 
3.8%
20211125163154 1
 
3.8%
20180125142600 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
20080123174020 1
3.8%
20080123175306 1
3.8%
20100421094058 1
3.8%
20120409161607 1
3.8%
20131126191002 1
3.8%
20131126191151 1
3.8%
20131126191445 1
3.8%
20140421154453 1
3.8%
20160325144035 1
3.8%
20160705154003 1
3.8%
ValueCountFrequency (%)
20220830100545 1
3.8%
20220719090636 1
3.8%
20211125163154 1
3.8%
20210923154313 1
3.8%
20210830110702 1
3.8%
20201109164843 1
3.8%
20201022102124 1
3.8%
20200806093127 1
3.8%
20200710105717 1
3.8%
20200710105657 1
3.8%

데이터갱신구분
Categorical

Distinct2
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size340.0 B
I
15 
U
11 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 15
57.7%
U 11
42.3%

Length

2023-12-11T04:07:50.917925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:07:51.067574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 15
57.7%
u 11
42.3%

데이터갱신일자
Date

Distinct11
Distinct (%)42.3%
Missing0
Missing (%)0.0%
Memory size340.0 B
Minimum2018-08-31 23:59:59
Maximum2022-09-01 02:40:00
2023-12-11T04:07:51.521749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T04:07:51.642474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing26
Missing (%)100.0%
Memory size366.0 B

좌표정보(X)
Real number (ℝ)

Distinct22
Distinct (%)84.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean339561.79
Minimum328629.75
Maximum355172.29
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-11T04:07:51.795818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum328629.75
5-th percentile332538.69
Q1333272.39
median336837.37
Q3345881.85
95-th percentile352970.91
Maximum355172.29
Range26542.54
Interquartile range (IQR)12609.452

Descriptive statistics

Standard deviation7365.0123
Coefficient of variation (CV)0.021689756
Kurtosis-0.59529402
Mean339561.79
Median Absolute Deviation (MAD)4281.96
Skewness0.60589818
Sum8828606.6
Variance54243406
MonotonicityNot monotonic
2023-12-11T04:07:51.954449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
343350.170921 2
 
7.7%
346717.496771 2
 
7.7%
332810.712481 2
 
7.7%
346516.586796 2
 
7.7%
355172.287752 1
 
3.8%
336848.363465 1
 
3.8%
333259.339551 1
 
3.8%
332668.14931 1
 
3.8%
328629.747792 1
 
3.8%
332588.853667 1
 
3.8%
Other values (12) 12
46.2%
ValueCountFrequency (%)
328629.747792 1
3.8%
332521.974134 1
3.8%
332588.853667 1
3.8%
332668.14931 1
3.8%
332810.712481 2
7.7%
333259.339551 1
3.8%
333311.559734 1
3.8%
333990.414376 1
3.8%
334119.085397 1
3.8%
334836.27161 1
3.8%
ValueCountFrequency (%)
355172.287752 1
3.8%
355055.374436 1
3.8%
346717.496771 2
7.7%
346516.586796 2
7.7%
345951.38555 1
3.8%
345673.22831 1
3.8%
343350.170921 2
7.7%
343339.805929 1
3.8%
339820.111985 1
3.8%
336848.363465 1
3.8%

좌표정보(Y)
Real number (ℝ)

Distinct22
Distinct (%)84.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean261370.89
Minimum237979.75
Maximum269526.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-11T04:07:52.108561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum237979.75
5-th percentile248978.24
Q1260119.19
median264383.35
Q3267960.62
95-th percentile269506.46
Maximum269526.1
Range31546.35
Interquartile range (IQR)7841.4322

Descriptive statistics

Standard deviation8512.04
Coefficient of variation (CV)0.032566901
Kurtosis0.71638794
Mean261370.89
Median Absolute Deviation (MAD)4149.6658
Skewness-1.1675365
Sum6795643.3
Variance72454824
MonotonicityNot monotonic
2023-12-11T04:07:52.251398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
267944.353451 2
 
7.7%
269165.84039 2
 
7.7%
264459.599437 2
 
7.7%
269526.100412 2
 
7.7%
264358.544592 1
 
3.8%
260777.789003 1
 
3.8%
250220.231056 1
 
3.8%
249020.786504 1
 
3.8%
237979.750002 1
 
3.8%
250047.070636 1
 
3.8%
Other values (12) 12
46.2%
ValueCountFrequency (%)
237979.750002 1
3.8%
248964.055507 1
3.8%
249020.786504 1
3.8%
250047.070636 1
3.8%
250220.231056 1
3.8%
250292.61784 1
3.8%
260004.695223 1
3.8%
260462.664203 1
3.8%
260540.004454 1
3.8%
260777.789003 1
3.8%
ValueCountFrequency (%)
269526.100412 2
7.7%
269447.530191 1
3.8%
269234.207448 1
3.8%
269165.84039 2
7.7%
267966.041735 1
3.8%
267944.353451 2
7.7%
266838.935634 1
3.8%
264459.599437 2
7.7%
264408.146423 1
3.8%
264358.544592 1
3.8%

설비규격
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing26
Missing (%)100.0%
Memory size366.0 B

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)설비규격
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910용기냉동기특정설비07_22_16_P3450000200534500991650000120051121<NA>1영업/정상1영업중<NA><NA><NA><NA><NA><NA><NA>대구광역시 북구 침산동 791대구광역시 북구 침산로 285 (침산동)<NA>(주)삼창이엔지20080123175306I2018-08-31 23:59:59.0<NA>343350.170921267944.353451<NA>
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2021용기냉동기특정설비07_22_16_P3480000201234803121650000120120522<NA>1영업/정상1영업중<NA><NA><NA><NA><NA><NA><NA>대구광역시 달성군 논공읍 본리리 29-98대구광역시 달성군 논공읍 논공로71길 9<NA>(주)카이오에너지20131126191002I2018-08-31 23:59:59.0<NA>332588.853667250047.070636<NA>
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