Overview

Dataset statistics

Number of variables32
Number of observations54
Missing cells546
Missing cells (%)31.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.7 KiB
Average record size in memory279.4 B

Variable types

Numeric9
Categorical10
Text5
Unsupported8

Dataset

Description22년10월_6270000_대구광역시_09_29_01_P_지하수시공업체
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000096862&dataSetDetailId=DDI_0000096883&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
인허가취소일자 has 41 (75.9%) missing valuesMissing
폐업일자 has 54 (100.0%) missing valuesMissing
휴업시작일자 has 54 (100.0%) missing valuesMissing
휴업종료일자 has 54 (100.0%) missing valuesMissing
재개업일자 has 54 (100.0%) missing valuesMissing
소재지전화 has 54 (100.0%) missing valuesMissing
소재지면적 has 54 (100.0%) missing valuesMissing
소재지우편번호 has 54 (100.0%) missing valuesMissing
소재지전체주소 has 6 (11.1%) missing valuesMissing
도로명전체주소 has 3 (5.6%) missing valuesMissing
도로명우편번호 has 37 (68.5%) missing valuesMissing
업태구분명 has 54 (100.0%) missing valuesMissing
좌표정보(X) has 2 (3.7%) missing valuesMissing
좌표정보(Y) has 2 (3.7%) missing valuesMissing
시설장비 has 23 (42.6%) missing valuesMissing
번호 has unique valuesUnique
최종수정시점 has unique valuesUnique
폐업일자 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
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
자본금 has 1 (1.9%) zerosZeros

Reproduction

Analysis started2024-04-17 04:05:58.715951
Analysis finished2024-04-17 04:05:59.291154
Duration0.58 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct54
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.5
Minimum1
Maximum54
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2024-04-17T13:05:59.361485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.65
Q114.25
median27.5
Q340.75
95-th percentile51.35
Maximum54
Range53
Interquartile range (IQR)26.5

Descriptive statistics

Standard deviation15.732133
Coefficient of variation (CV)0.57207755
Kurtosis-1.2
Mean27.5
Median Absolute Deviation (MAD)13.5
Skewness0
Sum1485
Variance247.5
MonotonicityStrictly increasing
2024-04-17T13:05:59.530047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.9%
42 1
 
1.9%
31 1
 
1.9%
32 1
 
1.9%
33 1
 
1.9%
34 1
 
1.9%
35 1
 
1.9%
36 1
 
1.9%
37 1
 
1.9%
38 1
 
1.9%
Other values (44) 44
81.5%
ValueCountFrequency (%)
1 1
1.9%
2 1
1.9%
3 1
1.9%
4 1
1.9%
5 1
1.9%
6 1
1.9%
7 1
1.9%
8 1
1.9%
9 1
1.9%
10 1
1.9%
ValueCountFrequency (%)
54 1
1.9%
53 1
1.9%
52 1
1.9%
51 1
1.9%
50 1
1.9%
49 1
1.9%
48 1
1.9%
47 1
1.9%
46 1
1.9%
45 1
1.9%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size564.0 B
지하수시공업체
54 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지하수시공업체 54
100.0%

Length

2024-04-17T13:05:59.650086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T13:05:59.728634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지하수시공업체 54
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size564.0 B
09_29_01_P
54 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row09_29_01_P
2nd row09_29_01_P
3rd row09_29_01_P
4th row09_29_01_P
5th row09_29_01_P

Common Values

ValueCountFrequency (%)
09_29_01_P 54
100.0%

Length

2024-04-17T13:05:59.805649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T13:05:59.873713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_29_01_p 54
100.0%

개방자치단체코드
Real number (ℝ)

Distinct6
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3463888.9
Minimum3420000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2024-04-17T13:05:59.936001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3420000
5-th percentile3420000
Q13450000
median3470000
Q33480000
95-th percentile3480000
Maximum3480000
Range60000
Interquartile range (IQR)30000

Descriptive statistics

Standard deviation19944.893
Coefficient of variation (CV)0.0057579482
Kurtosis0.15177959
Mean3463888.9
Median Absolute Deviation (MAD)10000
Skewness-1.0968501
Sum1.8705 × 108
Variance3.9779874 × 108
MonotonicityIncreasing
2024-04-17T13:06:00.025211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3480000 26
48.1%
3460000 9
 
16.7%
3450000 7
 
13.0%
3420000 6
 
11.1%
3470000 4
 
7.4%
3440000 2
 
3.7%
ValueCountFrequency (%)
3420000 6
 
11.1%
3440000 2
 
3.7%
3450000 7
 
13.0%
3460000 9
 
16.7%
3470000 4
 
7.4%
3480000 26
48.1%
ValueCountFrequency (%)
3480000 26
48.1%
3470000 4
 
7.4%
3460000 9
 
16.7%
3450000 7
 
13.0%
3440000 2
 
3.7%
3420000 6
 
11.1%

관리번호
Text

Distinct50
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Memory size564.0 B
2024-04-17T13:06:00.195291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters1026
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)85.2%

Sample

1st rowC001748110011934L00
2nd rowC001752110004691L00
3rd rowC007202151767711000
4th rowC001760110053360L00
5th rowC005011467044000000
ValueCountFrequency (%)
c002301110069623l00 2
 
3.7%
c001701110060799l00 2
 
3.7%
c001744110004474l00 2
 
3.7%
c001751110023057l00 2
 
3.7%
c001715110012725l00 1
 
1.9%
c005140245437000000 1
 
1.9%
c005131470260000000 1
 
1.9%
c005142388902000000 1
 
1.9%
c001752110054050l00 1
 
1.9%
c007404202682714000 1
 
1.9%
Other values (40) 40
74.1%
2024-04-17T13:06:00.462715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 402
39.2%
1 184
17.9%
7 70
 
6.8%
4 58
 
5.7%
C 54
 
5.3%
5 45
 
4.4%
2 44
 
4.3%
6 43
 
4.2%
3 38
 
3.7%
L 37
 
3.6%
Other values (2) 51
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 935
91.1%
Uppercase Letter 91
 
8.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 402
43.0%
1 184
19.7%
7 70
 
7.5%
4 58
 
6.2%
5 45
 
4.8%
2 44
 
4.7%
6 43
 
4.6%
3 38
 
4.1%
8 28
 
3.0%
9 23
 
2.5%
Uppercase Letter
ValueCountFrequency (%)
C 54
59.3%
L 37
40.7%

Most occurring scripts

ValueCountFrequency (%)
Common 935
91.1%
Latin 91
 
8.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 402
43.0%
1 184
19.7%
7 70
 
7.5%
4 58
 
6.2%
5 45
 
4.8%
2 44
 
4.7%
6 43
 
4.6%
3 38
 
4.1%
8 28
 
3.0%
9 23
 
2.5%
Latin
ValueCountFrequency (%)
C 54
59.3%
L 37
40.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1026
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 402
39.2%
1 184
17.9%
7 70
 
6.8%
4 58
 
5.7%
C 54
 
5.3%
5 45
 
4.4%
2 44
 
4.3%
6 43
 
4.2%
3 38
 
3.7%
L 37
 
3.6%
Other values (2) 51
 
5.0%

인허가일자
Real number (ℝ)

Distinct51
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20105181
Minimum19980124
Maximum20220613
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2024-04-17T13:06:00.578675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19980124
5-th percentile19980284
Q120025802
median20110822
Q320167903
95-th percentile20220223
Maximum20220613
Range240489
Interquartile range (IQR)142101

Descriptive statistics

Standard deviation81668.537
Coefficient of variation (CV)0.0040620643
Kurtosis-1.2421504
Mean20105181
Median Absolute Deviation (MAD)69654.5
Skewness-0.25237274
Sum1.0856798 × 109
Variance6.6697499 × 109
MonotonicityNot monotonic
2024-04-17T13:06:00.684568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20150918 2
 
3.7%
19980408 2
 
3.7%
20200122 2
 
3.7%
19990826 1
 
1.9%
20140929 1
 
1.9%
20090220 1
 
1.9%
20100528 1
 
1.9%
20210122 1
 
1.9%
20160308 1
 
1.9%
20220228 1
 
1.9%
Other values (41) 41
75.9%
ValueCountFrequency (%)
19980124 1
1.9%
19980213 1
1.9%
19980224 1
1.9%
19980317 1
1.9%
19980402 1
1.9%
19980408 2
3.7%
19980605 1
1.9%
19990826 1
1.9%
19991215 1
1.9%
20001208 1
1.9%
ValueCountFrequency (%)
20220613 1
1.9%
20220511 1
1.9%
20220228 1
1.9%
20220221 1
1.9%
20220119 1
1.9%
20210122 1
1.9%
20200122 2
3.7%
20200102 1
1.9%
20191231 1
1.9%
20190207 1
1.9%

인허가취소일자
Real number (ℝ)

MISSING 

Distinct13
Distinct (%)100.0%
Missing41
Missing (%)75.9%
Infinite0
Infinite (%)0.0%
Mean20119731
Minimum20070612
Maximum20200428
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2024-04-17T13:06:00.774439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20070612
5-th percentile20076427
Q120100423
median20110825
Q320130225
95-th percentile20182355
Maximum20200428
Range129816
Interquartile range (IQR)29802

Descriptive statistics

Standard deviation35865.984
Coefficient of variation (CV)0.0017826274
Kurtosis0.94726493
Mean20119731
Median Absolute Deviation (MAD)10409
Skewness1.0273902
Sum2.6155651 × 108
Variance1.2863688 × 109
MonotonicityNot monotonic
2024-04-17T13:06:00.864490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
20120709 1
 
1.9%
20110920 1
 
1.9%
20100416 1
 
1.9%
20130225 1
 
1.9%
20070612 1
 
1.9%
20110825 1
 
1.9%
20080304 1
 
1.9%
20110314 1
 
1.9%
20150311 1
 
1.9%
20170307 1
 
1.9%
Other values (3) 3
 
5.6%
(Missing) 41
75.9%
ValueCountFrequency (%)
20070612 1
1.9%
20080304 1
1.9%
20100416 1
1.9%
20100423 1
1.9%
20100715 1
1.9%
20110314 1
1.9%
20110825 1
1.9%
20110920 1
1.9%
20120709 1
1.9%
20130225 1
1.9%
ValueCountFrequency (%)
20200428 1
1.9%
20170307 1
1.9%
20150311 1
1.9%
20130225 1
1.9%
20120709 1
1.9%
20110920 1
1.9%
20110825 1
1.9%
20110314 1
1.9%
20100715 1
1.9%
20100423 1
1.9%

영업상태구분코드
Categorical

Distinct2
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size564.0 B
1
41 
3
13 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 41
75.9%
3 13
 
24.1%

Length

2024-04-17T13:06:00.968014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T13:06:01.039933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 41
75.9%
3 13
 
24.1%

영업상태명
Categorical

Distinct2
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size564.0 B
영업/정상
41 
폐업
13 

Length

Max length5
Median length5
Mean length4.2777778
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 41
75.9%
폐업 13
 
24.1%

Length

2024-04-17T13:06:01.120900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T13:06:01.197736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 41
75.9%
폐업 13
 
24.1%

상세영업상태코드
Categorical

Distinct2
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size564.0 B
1
41 
2
13 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 41
75.9%
2 13
 
24.1%

Length

2024-04-17T13:06:01.274208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T13:06:01.352772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 41
75.9%
2 13
 
24.1%

상세영업상태명
Categorical

Distinct2
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size564.0 B
영업
41 
취소정지업체
13 

Length

Max length6
Median length2
Mean length2.962963
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row취소정지업체
2nd row영업
3rd row영업
4th row영업
5th row영업

Common Values

ValueCountFrequency (%)
영업 41
75.9%
취소정지업체 13
 
24.1%

Length

2024-04-17T13:06:01.440492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T13:06:01.535117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 41
75.9%
취소정지업체 13
 
24.1%

폐업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing54
Missing (%)100.0%
Memory size618.0 B

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing54
Missing (%)100.0%
Memory size618.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing54
Missing (%)100.0%
Memory size618.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing54
Missing (%)100.0%
Memory size618.0 B

소재지전화
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing54
Missing (%)100.0%
Memory size618.0 B

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing54
Missing (%)100.0%
Memory size618.0 B

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing54
Missing (%)100.0%
Memory size618.0 B

소재지전체주소
Text

MISSING 

Distinct48
Distinct (%)100.0%
Missing6
Missing (%)11.1%
Memory size564.0 B
2024-04-17T13:06:01.763952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length29
Mean length24.4375
Min length19

Characters and Unicode

Total characters1173
Distinct characters100
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

Unique48 ?
Unique (%)100.0%

Sample

1st row대구광역시 동구 신천동 366-6번지
2nd row대구광역시 동구 효목동 441-1번지
3rd row대구광역시 동구 지묘동 333 801호
4th row대구광역시 동구 상매동 521-2번지
5th row대구광역시 동구 불로동 823-1번지
ValueCountFrequency (%)
대구광역시 45
 
19.5%
달성군 18
 
7.8%
수성구 9
 
3.9%
북구 7
 
3.0%
가창면 6
 
2.6%
동구 6
 
2.6%
하빈면 5
 
2.2%
용계리 5
 
2.2%
달서구 4
 
1.7%
관음동 3
 
1.3%
Other values (106) 123
53.2%
2024-04-17T13:06:02.126349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
231
19.7%
구 74
 
6.3%
1 50
 
4.3%
대 49
 
4.2%
역 47
 
4.0%
시 47
 
4.0%
광 45
 
3.8%
2 39
 
3.3%
동 37
 
3.2%
- 35
 
3.0%
Other values (90) 519
44.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 682
58.1%
Space Separator 231
 
19.7%
Decimal Number 224
 
19.1%
Dash Punctuation 35
 
3.0%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 74
 
10.9%
대 49
 
7.2%
역 47
 
6.9%
시 47
 
6.9%
광 45
 
6.6%
동 37
 
5.4%
지 35
 
5.1%
성 34
 
5.0%
번 32
 
4.7%
달 22
 
3.2%
Other values (77) 260
38.1%
Decimal Number
ValueCountFrequency (%)
1 50
22.3%
2 39
17.4%
3 24
10.7%
5 20
 
8.9%
6 19
 
8.5%
4 19
 
8.5%
8 16
 
7.1%
7 14
 
6.2%
0 12
 
5.4%
9 11
 
4.9%
Space Separator
ValueCountFrequency (%)
231
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 35
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 682
58.1%
Common 490
41.8%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 74
 
10.9%
대 49
 
7.2%
역 47
 
6.9%
시 47
 
6.9%
광 45
 
6.6%
동 37
 
5.4%
지 35
 
5.1%
성 34
 
5.0%
번 32
 
4.7%
달 22
 
3.2%
Other values (77) 260
38.1%
Common
ValueCountFrequency (%)
231
47.1%
1 50
 
10.2%
2 39
 
8.0%
- 35
 
7.1%
3 24
 
4.9%
5 20
 
4.1%
6 19
 
3.9%
4 19
 
3.9%
8 16
 
3.3%
7 14
 
2.9%
Other values (2) 23
 
4.7%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 682
58.1%
ASCII 491
41.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
231
47.0%
1 50
 
10.2%
2 39
 
7.9%
- 35
 
7.1%
3 24
 
4.9%
5 20
 
4.1%
6 19
 
3.9%
4 19
 
3.9%
8 16
 
3.3%
7 14
 
2.9%
Other values (3) 24
 
4.9%
Hangul
ValueCountFrequency (%)
구 74
 
10.9%
대 49
 
7.2%
역 47
 
6.9%
시 47
 
6.9%
광 45
 
6.6%
동 37
 
5.4%
지 35
 
5.1%
성 34
 
5.0%
번 32
 
4.7%
달 22
 
3.2%
Other values (77) 260
38.1%

도로명전체주소
Text

MISSING 

Distinct47
Distinct (%)92.2%
Missing3
Missing (%)5.6%
Memory size564.0 B
2024-04-17T13:06:02.385732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length31
Mean length25.803922
Min length20

Characters and Unicode

Total characters1316
Distinct characters117
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)86.3%

Sample

1st row대구광역시 동구 화랑로9길 61 (신천동)
2nd row대구광역시 동구 효목로7길 31 (효목동)
3rd row대구광역시 동구 아양로47길 45, 102호 (신암동)
4th row대구광역시 동구 율암로 149-6 (상매동)
5th row대구광역시 동구 공항로 190-1 (불로동)
ValueCountFrequency (%)
대구광역시 49
 
17.7%
달성군 24
 
8.7%
수성구 9
 
3.2%
가창면 7
 
2.5%
하빈면 6
 
2.2%
동구 6
 
2.2%
가창로 5
 
1.8%
북구 5
 
1.8%
화원읍 5
 
1.8%
달서구 4
 
1.4%
Other values (128) 157
56.7%
2024-04-17T13:06:02.757179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
226
 
17.2%
구 79
 
6.0%
대 58
 
4.4%
역 51
 
3.9%
시 51
 
3.9%
광 49
 
3.7%
성 48
 
3.6%
로 46
 
3.5%
1 46
 
3.5%
동 41
 
3.1%
Other values (107) 621
47.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 795
60.4%
Space Separator 226
 
17.2%
Decimal Number 210
 
16.0%
Close Punctuation 28
 
2.1%
Open Punctuation 28
 
2.1%
Other Punctuation 15
 
1.1%
Dash Punctuation 13
 
1.0%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 79
 
9.9%
대 58
 
7.3%
역 51
 
6.4%
시 51
 
6.4%
광 49
 
6.2%
성 48
 
6.0%
로 46
 
5.8%
동 41
 
5.2%
달 32
 
4.0%
군 25
 
3.1%
Other values (91) 315
39.6%
Decimal Number
ValueCountFrequency (%)
1 46
21.9%
2 31
14.8%
5 26
12.4%
4 23
11.0%
0 22
10.5%
6 16
 
7.6%
3 14
 
6.7%
9 13
 
6.2%
8 10
 
4.8%
7 9
 
4.3%
Space Separator
ValueCountFrequency (%)
226
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Other Punctuation
ValueCountFrequency (%)
, 15
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 795
60.4%
Common 520
39.5%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 79
 
9.9%
대 58
 
7.3%
역 51
 
6.4%
시 51
 
6.4%
광 49
 
6.2%
성 48
 
6.0%
로 46
 
5.8%
동 41
 
5.2%
달 32
 
4.0%
군 25
 
3.1%
Other values (91) 315
39.6%
Common
ValueCountFrequency (%)
226
43.5%
1 46
 
8.8%
2 31
 
6.0%
) 28
 
5.4%
( 28
 
5.4%
5 26
 
5.0%
4 23
 
4.4%
0 22
 
4.2%
6 16
 
3.1%
, 15
 
2.9%
Other values (5) 59
 
11.3%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 795
60.4%
ASCII 521
39.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
226
43.4%
1 46
 
8.8%
2 31
 
6.0%
) 28
 
5.4%
( 28
 
5.4%
5 26
 
5.0%
4 23
 
4.4%
0 22
 
4.2%
6 16
 
3.1%
, 15
 
2.9%
Other values (6) 60
 
11.5%
Hangul
ValueCountFrequency (%)
구 79
 
9.9%
대 58
 
7.3%
역 51
 
6.4%
시 51
 
6.4%
광 49
 
6.2%
성 48
 
6.0%
로 46
 
5.8%
동 41
 
5.2%
달 32
 
4.0%
군 25
 
3.1%
Other values (91) 315
39.6%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct15
Distinct (%)88.2%
Missing37
Missing (%)68.5%
Infinite0
Infinite (%)0.0%
Mean42403.059
Minimum41059
Maximum43004
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2024-04-17T13:06:02.857845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41059
5-th percentile41411
Q142037
median42691
Q342929
95-th percentile42973.6
Maximum43004
Range1945
Interquartile range (IQR)892

Descriptive statistics

Standard deviation633.22256
Coefficient of variation (CV)0.014933417
Kurtosis-0.57126174
Mean42403.059
Median Absolute Deviation (MAD)275
Skewness-0.88112205
Sum720852
Variance400970.81
MonotonicityNot monotonic
2024-04-17T13:06:02.949017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
41587 2
 
3.7%
42929 2
 
3.7%
41059 1
 
1.9%
41499 1
 
1.9%
42189 1
 
1.9%
42260 1
 
1.9%
42037 1
 
1.9%
42691 1
 
1.9%
42655 1
 
1.9%
42721 1
 
1.9%
Other values (5) 5
 
9.3%
(Missing) 37
68.5%
ValueCountFrequency (%)
41059 1
1.9%
41499 1
1.9%
41587 2
3.7%
42037 1
1.9%
42189 1
1.9%
42260 1
1.9%
42655 1
1.9%
42691 1
1.9%
42721 1
1.9%
42900 1
1.9%
ValueCountFrequency (%)
43004 1
1.9%
42966 1
1.9%
42934 1
1.9%
42929 2
3.7%
42905 1
1.9%
42900 1
1.9%
42721 1
1.9%
42691 1
1.9%
42655 1
1.9%
42260 1
1.9%

사업장명
Text

Distinct51
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Memory size564.0 B
2024-04-17T13:06:03.143006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length6.7592593
Min length3

Characters and Unicode

Total characters365
Distinct characters100
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)88.9%

Sample

1st row㈜경창지오컨설탄트
2nd row㈜거암
3rd row우진개발
4th row범환지오텍 주식회사
5th row한일수중펌프
ValueCountFrequency (%)
주식회사 3
 
5.2%
주)용현건설 2
 
3.4%
㈜국제지오컨설팅 2
 
3.4%
주)성수개발 2
 
3.4%
이앤씨 1
 
1.7%
허선생엔지니어링 1
 
1.7%
대림이앤씨 1
 
1.7%
광성엔지니어링 1
 
1.7%
뉴지오텍(주 1
 
1.7%
신화산업개발(주 1
 
1.7%
Other values (43) 43
74.1%
2024-04-17T13:06:03.448935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 28
 
7.7%
( 24
 
6.6%
) 24
 
6.6%
지 19
 
5.2%
개 16
 
4.4%
발 16
 
4.4%
수 10
 
2.7%
㈜ 10
 
2.7%
건 9
 
2.5%
설 8
 
2.2%
Other values (90) 201
55.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 303
83.0%
Open Punctuation 24
 
6.6%
Close Punctuation 24
 
6.6%
Other Symbol 10
 
2.7%
Space Separator 4
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 28
 
9.2%
지 19
 
6.3%
개 16
 
5.3%
발 16
 
5.3%
수 10
 
3.3%
건 9
 
3.0%
설 8
 
2.6%
이 7
 
2.3%
사 7
 
2.3%
오 6
 
2.0%
Other values (86) 177
58.4%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 10
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 313
85.8%
Common 52
 
14.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 28
 
8.9%
지 19
 
6.1%
개 16
 
5.1%
발 16
 
5.1%
수 10
 
3.2%
㈜ 10
 
3.2%
건 9
 
2.9%
설 8
 
2.6%
이 7
 
2.2%
사 7
 
2.2%
Other values (87) 183
58.5%
Common
ValueCountFrequency (%)
( 24
46.2%
) 24
46.2%
4
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 303
83.0%
ASCII 52
 
14.2%
None 10
 
2.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 28
 
9.2%
지 19
 
6.3%
개 16
 
5.3%
발 16
 
5.3%
수 10
 
3.3%
건 9
 
3.0%
설 8
 
2.6%
이 7
 
2.3%
사 7
 
2.3%
오 6
 
2.0%
Other values (86) 177
58.4%
ASCII
ValueCountFrequency (%)
( 24
46.2%
) 24
46.2%
4
 
7.7%
None
ValueCountFrequency (%)
㈜ 10
100.0%

최종수정시점
Real number (ℝ)

UNIQUE 

Distinct54
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0164832 × 1013
Minimum2.0091207 × 1013
Maximum2.0220823 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2024-04-17T13:06:03.561249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0091207 × 1013
5-th percentile2.0100413 × 1013
Q12.0113451 × 1013
median2.0170719 × 1013
Q32.0210122 × 1013
95-th percentile2.0220721 × 1013
Maximum2.0220823 × 1013
Range1.2961602 × 1011
Interquartile range (IQR)9.6671525 × 1010

Descriptive statistics

Standard deviation4.678338 × 1010
Coefficient of variation (CV)0.0023200481
Kurtosis-1.5231798
Mean2.0164832 × 1013
Median Absolute Deviation (MAD)4.9450977 × 1010
Skewness-0.24203446
Sum1.0889009 × 1015
Variance2.1886847 × 1021
MonotonicityNot monotonic
2024-04-17T13:06:03.688188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20120712093722 1
 
1.9%
20180827085428 1
 
1.9%
20220727145851 1
 
1.9%
20210122141606 1
 
1.9%
20210122110603 1
 
1.9%
20160308124852 1
 
1.9%
20220624161005 1
 
1.9%
20200102113713 1
 
1.9%
20131213190937 1
 
1.9%
20160906140656 1
 
1.9%
Other values (44) 44
81.5%
ValueCountFrequency (%)
20091207134008 1
1.9%
20100108103432 1
1.9%
20100407165657 1
1.9%
20100416141535 1
1.9%
20100423101658 1
1.9%
20100423102134 1
1.9%
20100423102257 1
1.9%
20100423103017 1
1.9%
20100908132447 1
1.9%
20100913090347 1
1.9%
ValueCountFrequency (%)
20220823155307 1
1.9%
20220727145851 1
1.9%
20220727145028 1
1.9%
20220718142704 1
1.9%
20220708155030 1
1.9%
20220624172907 1
1.9%
20220624161005 1
1.9%
20220511182003 1
1.9%
20220223120055 1
1.9%
20220221094623 1
1.9%

데이터갱신구분
Categorical

Distinct2
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size564.0 B
I
39 
U
15 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 39
72.2%
U 15
 
27.8%

Length

2024-04-17T13:06:03.823306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T13:06:03.909608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 39
72.2%
u 15
 
27.8%

데이터갱신일자
Categorical

Distinct21
Distinct (%)38.9%
Missing0
Missing (%)0.0%
Memory size564.0 B
2018-08-31 23:59:59.0
31 
2022-06-26 02:40:00.0
 
2
2021-01-24 00:23:04.0
 
2
2022-07-29 02:40:00.0
 
2
2022-07-12 02:40:00.0
 
1
Other values (16)
16 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique17 ?
Unique (%)31.5%

Sample

1st row2018-08-31 23:59:59.0
2nd row2018-08-31 23:59:59.0
3rd row2022-07-12 02:40:00.0
4th row2018-12-09 02:40:00.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 31
57.4%
2022-06-26 02:40:00.0 2
 
3.7%
2021-01-24 00:23:04.0 2
 
3.7%
2022-07-29 02:40:00.0 2
 
3.7%
2022-07-12 02:40:00.0 1
 
1.9%
2018-12-09 02:40:00.0 1
 
1.9%
2022-01-21 00:22:39.0 1
 
1.9%
2022-07-20 02:40:00.0 1
 
1.9%
2021-03-05 00:23:00.0 1
 
1.9%
2022-02-25 00:22:37.0 1
 
1.9%
Other values (11) 11
 
20.4%

Length

2024-04-17T13:06:03.987288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 31
28.7%
23:59:59.0 31
28.7%
02:40:00.0 15
13.9%
2021-01-24 3
 
2.8%
2022-06-26 2
 
1.9%
00:23:04.0 2
 
1.9%
2022-07-29 2
 
1.9%
00:23:25.0 1
 
0.9%
2022-05-13 1
 
0.9%
00:22:32.0 1
 
0.9%
Other values (19) 19
17.6%

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing54
Missing (%)100.0%
Memory size618.0 B

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct47
Distinct (%)90.4%
Missing2
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean338450.65
Minimum202057
Maximum356476.35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2024-04-17T13:06:04.078411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum202057
5-th percentile326126.02
Q1335091.36
median342081.71
Q3347206.13
95-th percentile353585.93
Maximum356476.35
Range154419.35
Interquartile range (IQR)12114.771

Descriptive statistics

Standard deviation20954.278
Coefficient of variation (CV)0.061912359
Kurtosis36.471286
Mean338450.65
Median Absolute Deviation (MAD)5773.8885
Skewness-5.5801245
Sum17599434
Variance4.3908177 × 108
MonotonicityNot monotonic
2024-04-17T13:06:04.188505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
343680.311178 2
 
3.7%
335091.359493 2
 
3.7%
327254.926809 2
 
3.7%
336337.15808 2
 
3.7%
326126.020934 2
 
3.7%
348571.853503 1
 
1.9%
346954.000598 1
 
1.9%
335043.586174 1
 
1.9%
346547.013083 1
 
1.9%
330791.0 1
 
1.9%
Other values (37) 37
68.5%
(Missing) 2
 
3.7%
ValueCountFrequency (%)
202057.0 1
1.9%
326088.0 1
1.9%
326126.020934 2
3.7%
327254.926809 2
3.7%
327779.952612 1
1.9%
328528.282371 1
1.9%
330334.973904 1
1.9%
330791.0 1
1.9%
334703.341974 1
1.9%
335043.586174 1
1.9%
ValueCountFrequency (%)
356476.348442 1
1.9%
354396.957671108 1
1.9%
353814.465572 1
1.9%
353398.94358 1
1.9%
350924.05011 1
1.9%
348571.853503 1
1.9%
348355.00624 1
1.9%
348073.107864 1
1.9%
347901.216988 1
1.9%
347900.495986 1
1.9%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct47
Distinct (%)90.4%
Missing2
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean265441.8
Minimum244374
Maximum418616
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2024-04-17T13:06:04.319663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum244374
5-th percentile252214.24
Q1256970.54
median263325.02
Q3265487.38
95-th percentile272486.37
Maximum418616
Range174242
Interquartile range (IQR)8516.831

Descriptive statistics

Standard deviation22973.934
Coefficient of variation (CV)0.086549795
Kurtosis40.526174
Mean265441.8
Median Absolute Deviation (MAD)3528.3337
Skewness6.0588706
Sum13802974
Variance5.2780163 × 108
MonotonicityNot monotonic
2024-04-17T13:06:04.435353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
265487.37503 2
 
3.7%
264527.918012 2
 
3.7%
265496.191813 2
 
3.7%
256834.407501 2
 
3.7%
264094.22627 2
 
3.7%
254734.026287 1
 
1.9%
248747.854959 1
 
1.9%
264551.182967 1
 
1.9%
256972.131063 1
 
1.9%
244374.0 1
 
1.9%
Other values (37) 37
68.5%
(Missing) 2
 
3.7%
ValueCountFrequency (%)
244374.0 1
1.9%
248747.854959 1
1.9%
251030.651509 1
1.9%
253182.624098 1
1.9%
254734.026287 1
1.9%
256487.780188 1
1.9%
256543.731992 1
1.9%
256670.659942 1
1.9%
256678.726194 1
1.9%
256834.407501 2
3.7%
ValueCountFrequency (%)
418616.0 1
1.9%
298253.092977182 1
1.9%
272641.451378 1
1.9%
272359.486675 1
1.9%
272038.257658 1
1.9%
271949.097056 1
1.9%
267828.470136 1
1.9%
267759.588837 1
1.9%
266821.012792 1
1.9%
266715.697771 1
1.9%

전문인력총수
Categorical

Distinct4
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size564.0 B
2
43 
3
5 
4
5 
7
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.9%

Sample

1st row3
2nd row2
3rd row3
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 43
79.6%
3 5
 
9.3%
4 5
 
9.3%
7 1
 
1.9%

Length

2024-04-17T13:06:04.534944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T13:06:04.606104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 43
79.6%
3 5
 
9.3%
4 5
 
9.3%
7 1
 
1.9%

자본금
Real number (ℝ)

ZEROS 

Distinct32
Distinct (%)59.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0133932 × 108
Minimum0
Maximum6.19 × 108
Zeros1
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size618.0 B
2024-04-17T13:06:04.686054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile30000000
Q150000000
median1.8 × 108
Q33.0804875 × 108
95-th percentile5.05 × 108
Maximum6.19 × 108
Range6.19 × 108
Interquartile range (IQR)2.5804875 × 108

Descriptive statistics

Standard deviation1.7080987 × 108
Coefficient of variation (CV)0.84836814
Kurtosis-0.37480211
Mean2.0133932 × 108
Median Absolute Deviation (MAD)1.3 × 108
Skewness0.79596935
Sum1.0872323 × 1010
Variance2.917601 × 1016
MonotonicityNot monotonic
2024-04-17T13:06:04.776937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
50000000 5
 
9.3%
30000000 5
 
9.3%
200000000 4
 
7.4%
310000000 3
 
5.6%
250000000 3
 
5.6%
105000000 3
 
5.6%
100000000 2
 
3.7%
500000000 2
 
3.7%
410000000 2
 
3.7%
505000000 2
 
3.7%
Other values (22) 23
42.6%
ValueCountFrequency (%)
0 1
 
1.9%
305000 1
 
1.9%
30000000 5
9.3%
30093000 1
 
1.9%
31000000 1
 
1.9%
34800000 1
 
1.9%
50000000 5
9.3%
50536103 1
 
1.9%
57155000 1
 
1.9%
63000000 1
 
1.9%
ValueCountFrequency (%)
619000000 1
 
1.9%
600003856 1
 
1.9%
505000000 2
3.7%
500000000 2
3.7%
410000000 2
3.7%
405000000 1
 
1.9%
400000000 2
3.7%
310000000 3
5.6%
302195000 1
 
1.9%
300000000 1
 
1.9%

시설장비
Text

MISSING 

Distinct28
Distinct (%)90.3%
Missing23
Missing (%)42.6%
Memory size564.0 B
2024-04-17T13:06:04.957787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length90
Median length31
Mean length23.903226
Min length6

Characters and Unicode

Total characters741
Distinct characters105
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)80.6%

Sample

1st row1. 시추기 1
2nd row1. 시추기 2 2. 공기압축기 1
3rd row· 시추기 SD600 1대, TBM 1대 보유 · 공기압축기 27㎡/min 임대 · 5t 2대, 3.5t 1대, 1t 트럭 1대 보유 · 사무실 116.2㎡ 임대
4th row시추기 : HI-1001 1대 임대 공기압축기 : XRVS487CD(29.8㎥/min) 1대 임대
5th row천공기-등록번호:대구22-5125 형식:17W 규격:30M/min
ValueCountFrequency (%)
1대 20
13.9%
1 19
 
13.2%
공기압축기 15
 
10.4%
시추기 11
 
7.6%
2 8
 
5.6%
6
 
4.2%
천공기 5
 
3.5%
임대 5
 
3.5%
· 4
 
2.8%
보유 2
 
1.4%
Other values (47) 49
34.0%
2024-04-17T13:06:05.235444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
92
 
12.4%
기 70
 
9.4%
1 57
 
7.7%
2 35
 
4.7%
대 34
 
4.6%
공 31
 
4.2%
. 23
 
3.1%
22
 
3.0%
0 22
 
3.0%
압 18
 
2.4%
Other values (95) 337
45.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 302
40.8%
Decimal Number 163
22.0%
Space Separator 92
 
12.4%
Other Punctuation 47
 
6.3%
Uppercase Letter 45
 
6.1%
Control 22
 
3.0%
Lowercase Letter 20
 
2.7%
Open Punctuation 17
 
2.3%
Close Punctuation 17
 
2.3%
Dash Punctuation 12
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 70
23.2%
대 34
11.3%
공 31
10.3%
압 18
 
6.0%
축 17
 
5.6%
추 14
 
4.6%
시 14
 
4.6%
천 13
 
4.3%
임 9
 
3.0%
착 8
 
2.6%
Other values (47) 74
24.5%
Uppercase Letter
ValueCountFrequency (%)
D 5
 
11.1%
T 4
 
8.9%
C 4
 
8.9%
H 3
 
6.7%
O 3
 
6.7%
M 3
 
6.7%
S 3
 
6.7%
A 3
 
6.7%
X 2
 
4.4%
P 2
 
4.4%
Other values (11) 13
28.9%
Decimal Number
ValueCountFrequency (%)
1 57
35.0%
2 35
21.5%
0 22
 
13.5%
5 16
 
9.8%
3 10
 
6.1%
7 7
 
4.3%
4 5
 
3.1%
8 4
 
2.5%
9 4
 
2.5%
6 3
 
1.8%
Other Punctuation
ValueCountFrequency (%)
. 23
48.9%
: 7
 
14.9%
, 7
 
14.9%
/ 5
 
10.6%
· 4
 
8.5%
* 1
 
2.1%
Lowercase Letter
ValueCountFrequency (%)
m 9
45.0%
i 4
20.0%
n 4
20.0%
t 3
 
15.0%
Other Symbol
ValueCountFrequency (%)
㎥ 2
50.0%
㎡ 2
50.0%
Space Separator
ValueCountFrequency (%)
92
100.0%
Control
ValueCountFrequency (%)
22
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 374
50.5%
Hangul 302
40.8%
Latin 65
 
8.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 70
23.2%
대 34
11.3%
공 31
10.3%
압 18
 
6.0%
축 17
 
5.6%
추 14
 
4.6%
시 14
 
4.6%
천 13
 
4.3%
임 9
 
3.0%
착 8
 
2.6%
Other values (47) 74
24.5%
Latin
ValueCountFrequency (%)
m 9
 
13.8%
D 5
 
7.7%
T 4
 
6.2%
C 4
 
6.2%
i 4
 
6.2%
n 4
 
6.2%
H 3
 
4.6%
t 3
 
4.6%
O 3
 
4.6%
M 3
 
4.6%
Other values (15) 23
35.4%
Common
ValueCountFrequency (%)
92
24.6%
1 57
15.2%
2 35
 
9.4%
. 23
 
6.1%
22
 
5.9%
0 22
 
5.9%
( 17
 
4.5%
) 17
 
4.5%
5 16
 
4.3%
- 12
 
3.2%
Other values (13) 61
16.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 431
58.2%
Hangul 302
40.8%
None 4
 
0.5%
CJK Compat 4
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
92
21.3%
1 57
13.2%
2 35
 
8.1%
. 23
 
5.3%
22
 
5.1%
0 22
 
5.1%
( 17
 
3.9%
) 17
 
3.9%
5 16
 
3.7%
- 12
 
2.8%
Other values (35) 118
27.4%
Hangul
ValueCountFrequency (%)
기 70
23.2%
대 34
11.3%
공 31
10.3%
압 18
 
6.0%
축 17
 
5.6%
추 14
 
4.6%
시 14
 
4.6%
천 13
 
4.3%
임 9
 
3.0%
착 8
 
2.6%
Other values (47) 74
24.5%
None
ValueCountFrequency (%)
· 4
100.0%
CJK Compat
ValueCountFrequency (%)
㎥ 2
50.0%
㎡ 2
50.0%

타기관이전여부
Categorical

Distinct2
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size564.0 B
0
44 
1
10 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row0
4th row0
5th row1

Common Values

ValueCountFrequency (%)
0 44
81.5%
1 10
 
18.5%

Length

2024-04-17T13:06:05.337377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T13:06:05.407914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 44
81.5%
1 10
 
18.5%

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)전문인력총수자본금시설장비타기관이전여부
01지하수시공업체09_29_01_P3420000C001748110011934L0019990826201207093폐업2취소정지업체<NA><NA><NA><NA><NA><NA><NA>대구광역시 동구 신천동 366-6번지대구광역시 동구 화랑로9길 61 (신천동)<NA>㈜경창지오컨설탄트20120712093722I2018-08-31 23:59:59.0<NA>347127.396363264691.39183631000000001. 시추기 10
12지하수시공업체09_29_01_P3420000C001752110004691L0020160608<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>대구광역시 동구 효목동 441-1번지대구광역시 동구 효목로7길 31 (효목동)<NA>㈜거암20160704163144I2018-08-31 23:59:59.0<NA>347764.014973265264.76225322000000001. 시추기 2 2. 공기압축기 11
23지하수시공업체09_29_01_P3420000C00720215176771100020160405<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>대구광역시 동구 지묘동 333 801호대구광역시 동구 아양로47길 45, 102호 (신암동)<NA>우진개발20220708155030U2022-07-12 02:40:00.0<NA>347900.495986272359.486675377250000· 시추기 SD600 1대, TBM 1대 보유 · 공기압축기 27㎡/min 임대 · 5t 2대, 3.5t 1대, 1t 트럭 1대 보유 · 사무실 116.2㎡ 임대0
34지하수시공업체09_29_01_P3420000C001760110053360L0020141205<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>대구광역시 동구 상매동 521-2번지대구광역시 동구 율암로 149-6 (상매동)41059범환지오텍 주식회사20181207110947U2018-12-09 02:40:00.0<NA>353814.465572266715.697771250000000<NA>0
45지하수시공업체09_29_01_P3420000C00501146704400000020040714<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>대구광역시 동구 불로동 823-1번지대구광역시 동구 공항로 190-1 (불로동)<NA>한일수중펌프20170208172332I2018-08-31 23:59:59.0<NA>347526.586815267828.4701362600003856시추기 : HI-1001 1대 임대 공기압축기 : XRVS487CD(29.8㎥/min) 1대 임대1
56지하수시공업체09_29_01_P3420000C001701110367426L0020090128201109203폐업2취소정지업체<NA><NA><NA><NA><NA><NA><NA>대구광역시 동구 괴전동 133-4번지대구광역시 동구 동내로 6 (괴전동)<NA>(주)신서20120712094521I2018-08-31 23:59:59.0<NA>356476.348442264941.7601172255000000천공기-등록번호:대구22-5125 형식:17W 규격:30M/min0
67지하수시공업체09_29_01_P3440000C001714110005300L0019991215<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>대구광역시 남구 대명동 2033-28번지대구광역시 남구 명덕로 212-1 (대명동)<NA>수창개발(주)20100924150753I2018-08-31 23:59:59.0<NA>343857.119506262989.31777221050000001. 시추기 10
78지하수시공업체09_29_01_P3440000C001747110014211L0020020831<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>경상북도 영천시 야사동 415-1 번지<NA><NA>(주)태흥개발20100908132447I2018-08-31 23:59:59.0<NA><NA><NA>41050000001. 시추기 1 2. 공기압축기 10
89지하수시공업체09_29_01_P3450000C001744110000703L0019980124201004163폐업2취소정지업체<NA><NA><NA><NA><NA><NA><NA>대구광역시 북구 서변동 1784-3 번지<NA><NA>창암건설㈜20100416141535I2018-08-31 23:59:59.0<NA><NA><NA>23050001. 시추기 1 2. 공기압축기 10
910지하수시공업체09_29_01_P3450000C00504017767200000020001208201302253폐업2취소정지업체<NA><NA><NA><NA><NA><NA><NA>대구광역시 북구 관음동 1245-22번지<NA><NA>경북지하수20130225161504I2018-08-31 23:59:59.0<NA>339224.243031272641.451378230093000<NA>0
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