Overview

Dataset statistics

Number of variables12
Number of observations3799
Missing cells29
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory374.8 KiB
Average record size in memory101.0 B

Variable types

Numeric4
Categorical5
Text3

Dataset

Description경상남도_하자검사관리 데이터입니다. 공사년도, 공사구분, 공사번호, 순번, 검사년월일, 검사부분, 검사자, 검사감독관, 하자발생등의 데이터를 포함하고있습니다.
Author경상남도
URLhttps://www.data.go.kr/data/15049512/fileData.do

Alerts

부서코드 has constant value ""Constant
공사구분 is highly overall correlated with 검사구분High correlation
검사구분 is highly overall correlated with 공사구분High correlation
검사감독관 is highly overall correlated with 조치사항High correlation
조치사항 is highly overall correlated with 검사감독관High correlation
공사구분 is highly imbalanced (99.6%)Imbalance
검사감독관 is highly imbalanced (99.6%)Imbalance
조치사항 is highly imbalanced (96.0%)Imbalance

Reproduction

Analysis started2023-12-12 05:58:44.937731
Analysis finished2023-12-12 05:58:48.065988
Duration3.13 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

공사년도
Real number (ℝ)

Distinct16
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2002.1248
Minimum1994
Maximum2009
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.5 KiB
2023-12-12T14:58:48.124733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1994
5-th percentile1997
Q12000
median2002
Q32004
95-th percentile2007
Maximum2009
Range15
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.9921285
Coefficient of variation (CV)0.0014944765
Kurtosis-0.45214396
Mean2002.1248
Median Absolute Deviation (MAD)2
Skewness-0.20253211
Sum7606072
Variance8.9528329
MonotonicityIncreasing
2023-12-12T14:58:48.253327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
2003 601
15.8%
2004 478
12.6%
2001 444
11.7%
2002 433
11.4%
2000 299
7.9%
2006 257
6.8%
2005 256
6.7%
1999 253
6.7%
2007 190
 
5.0%
1997 183
 
4.8%
Other values (6) 405
10.7%
ValueCountFrequency (%)
1994 3
 
0.1%
1995 31
 
0.8%
1996 113
 
3.0%
1997 183
 
4.8%
1998 177
 
4.7%
1999 253
6.7%
2000 299
7.9%
2001 444
11.7%
2002 433
11.4%
2003 601
15.8%
ValueCountFrequency (%)
2009 28
 
0.7%
2008 53
 
1.4%
2007 190
 
5.0%
2006 257
6.8%
2005 256
6.7%
2004 478
12.6%
2003 601
15.8%
2002 433
11.4%
2001 444
11.7%
2000 299
7.9%

공사구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.8 KiB
공사
3798 
기타
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
공사 3798
> 99.9%
기타 1
 
< 0.1%

Length

2023-12-12T14:58:48.402861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:58:48.523242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공사 3798
> 99.9%
기타 1
 
< 0.1%

공사번호
Real number (ℝ)

Distinct138
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54.975257
Minimum1
Maximum148
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.5 KiB
2023-12-12T14:58:48.654335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7
Q127
median55
Q380
95-th percentile109
Maximum148
Range147
Interquartile range (IQR)53

Descriptive statistics

Standard deviation31.98358
Coefficient of variation (CV)0.58178136
Kurtosis-0.73245597
Mean54.975257
Median Absolute Deviation (MAD)26
Skewness0.22681865
Sum208851
Variance1022.9494
MonotonicityNot monotonic
2023-12-12T14:58:48.846678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
53 77
 
2.0%
58 70
 
1.8%
54 61
 
1.6%
21 60
 
1.6%
64 59
 
1.6%
27 58
 
1.5%
65 57
 
1.5%
81 55
 
1.4%
55 55
 
1.4%
11 54
 
1.4%
Other values (128) 3193
84.0%
ValueCountFrequency (%)
1 25
0.7%
2 35
0.9%
3 33
0.9%
4 26
0.7%
5 16
 
0.4%
6 33
0.9%
7 44
1.2%
8 39
1.0%
9 31
0.8%
10 38
1.0%
ValueCountFrequency (%)
148 4
0.1%
147 3
0.1%
145 5
0.1%
142 1
 
< 0.1%
141 1
 
< 0.1%
140 1
 
< 0.1%
138 2
 
0.1%
137 2
 
0.1%
131 6
0.2%
129 1
 
< 0.1%

부서코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size29.8 KiB
1
3799 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 3799
100.0%

Length

2023-12-12T14:58:49.089401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:58:49.211438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 3799
100.0%

하자순번
Real number (ℝ)

Distinct10
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1313504
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.5 KiB
2023-12-12T14:58:49.350153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile2
Maximum10
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.56617304
Coefficient of variation (CV)0.50044006
Kurtosis82.904652
Mean1.1313504
Median Absolute Deviation (MAD)0
Skewness7.6882504
Sum4298
Variance0.32055191
MonotonicityNot monotonic
2023-12-12T14:58:49.485106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 3477
91.5%
2 232
 
6.1%
3 56
 
1.5%
4 15
 
0.4%
5 6
 
0.2%
6 4
 
0.1%
7 3
 
0.1%
10 2
 
0.1%
8 2
 
0.1%
9 2
 
0.1%
ValueCountFrequency (%)
1 3477
91.5%
2 232
 
6.1%
3 56
 
1.5%
4 15
 
0.4%
5 6
 
0.2%
6 4
 
0.1%
7 3
 
0.1%
8 2
 
0.1%
9 2
 
0.1%
10 2
 
0.1%
ValueCountFrequency (%)
10 2
 
0.1%
9 2
 
0.1%
8 2
 
0.1%
7 3
 
0.1%
6 4
 
0.1%
5 6
 
0.2%
4 15
 
0.4%
3 56
 
1.5%
2 232
 
6.1%
1 3477
91.5%

순번
Real number (ℝ)

Distinct29
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.7730982
Minimum1
Maximum29
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.5 KiB
2023-12-12T14:58:49.652796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q36
95-th percentile12
Maximum29
Range28
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.9355795
Coefficient of variation (CV)0.82453354
Kurtosis4.7848708
Mean4.7730982
Median Absolute Deviation (MAD)2
Skewness1.8468914
Sum18133
Variance15.488786
MonotonicityNot monotonic
2023-12-12T14:58:49.843928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
1 689
18.1%
2 616
16.2%
3 518
13.6%
4 418
11.0%
5 343
9.0%
6 292
7.7%
7 236
 
6.2%
8 141
 
3.7%
9 120
 
3.2%
10 107
 
2.8%
Other values (19) 319
8.4%
ValueCountFrequency (%)
1 689
18.1%
2 616
16.2%
3 518
13.6%
4 418
11.0%
5 343
9.0%
6 292
7.7%
7 236
 
6.2%
8 141
 
3.7%
9 120
 
3.2%
10 107
 
2.8%
ValueCountFrequency (%)
29 1
 
< 0.1%
28 1
 
< 0.1%
27 2
 
0.1%
26 3
 
0.1%
25 3
 
0.1%
24 3
 
0.1%
23 4
0.1%
22 7
0.2%
21 7
0.2%
20 9
0.2%

검사년월일
Text

Distinct441
Distinct (%)11.7%
Missing29
Missing (%)0.8%
Memory size29.8 KiB
2023-12-12T14:58:50.145473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.6668435
Min length6

Characters and Unicode

Total characters36444
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

Unique154 ?
Unique (%)4.1%

Sample

1st row2004-12-17
2nd row2004-07-26
3rd row2004-02-16
4th row2004-02-16
5th row2006-01-12
ValueCountFrequency (%)
2004-02-16 144
 
3.8%
2005-02-03 111
 
2.9%
2007-07-27 72
 
1.9%
2006-07-20 64
 
1.7%
2006-01-11 62
 
1.6%
2004-07-27 53
 
1.4%
2009-07-08 52
 
1.4%
2006-01-12 50
 
1.3%
2005-01-15 46
 
1.2%
2007-01-15 43
 
1.1%
Other values (431) 3073
81.5%
2023-12-12T14:58:50.619854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12232
33.6%
- 6910
19.0%
2 5695
15.6%
1 3396
 
9.3%
7 2558
 
7.0%
8 1237
 
3.4%
6 1174
 
3.2%
5 1020
 
2.8%
4 872
 
2.4%
9 721
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 29534
81.0%
Dash Punctuation 6910
 
19.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12232
41.4%
2 5695
19.3%
1 3396
 
11.5%
7 2558
 
8.7%
8 1237
 
4.2%
6 1174
 
4.0%
5 1020
 
3.5%
4 872
 
3.0%
9 721
 
2.4%
3 629
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 6910
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 36444
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12232
33.6%
- 6910
19.0%
2 5695
15.6%
1 3396
 
9.3%
7 2558
 
7.0%
8 1237
 
3.4%
6 1174
 
3.2%
5 1020
 
2.8%
4 872
 
2.4%
9 721
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 36444
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12232
33.6%
- 6910
19.0%
2 5695
15.6%
1 3396
 
9.3%
7 2558
 
7.0%
8 1237
 
3.4%
6 1174
 
3.2%
5 1020
 
2.8%
4 872
 
2.4%
9 721
 
2.0%

검사구분
Categorical

HIGH CORRELATION 

Distinct45
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size29.8 KiB
05년하
315 
06년상
315 
07년상
300 
04년하
299 
04년상
290 
Other values (40)
2280 

Length

Max length9
Median length4
Mean length3.8720716
Min length1

Unique

Unique7 ?
Unique (%)0.2%

Sample

1st row기간만료
2nd row04년상
3rd row정기
4th row정기분
5th row05년하

Common Values

ValueCountFrequency (%)
05년하 315
 
8.3%
06년상 315
 
8.3%
07년상 300
 
7.9%
04년하 299
 
7.9%
04년상 290
 
7.6%
05년상 263
 
6.9%
07년하 262
 
6.9%
정기검사 242
 
6.4%
06년하 233
 
6.1%
08년상 226
 
5.9%
Other values (35) 1054
27.7%

Length

2023-12-12T14:58:50.788311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
05년하 315
 
8.3%
06년상 315
 
8.3%
07년상 300
 
7.9%
04년하 299
 
7.9%
04년상 290
 
7.6%
05년상 263
 
6.9%
07년하 262
 
6.9%
정기검사 242
 
6.4%
06년하 233
 
6.1%
08년상 226
 
5.9%
Other values (37) 1060
27.9%

검사자
Text

Distinct170
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size29.8 KiB
2023-12-12T14:58:51.112098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length2.9905238
Min length1

Characters and Unicode

Total characters11361
Distinct characters131
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

Unique33 ?
Unique (%)0.9%

Sample

1st row이동열
2nd row이동열
3rd row이종술
4th row차영대
5th row이동열
ValueCountFrequency (%)
유승룡 142
 
3.7%
김중섭 131
 
3.4%
김영삼 123
 
3.2%
장재룡 114
 
3.0%
황성규 108
 
2.8%
김경열 105
 
2.8%
강병천 104
 
2.7%
추진우 87
 
2.3%
이동열 82
 
2.2%
이정환 81
 
2.1%
Other values (160) 2724
71.7%
2023-12-12T14:58:51.585935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 886
 
7.8%
정 430
 
3.8%
이 404
 
3.6%
영 333
 
2.9%
강 307
 
2.7%
룡 284
 
2.5%
석 260
 
2.3%
경 249
 
2.2%
환 240
 
2.1%
진 222
 
2.0%
Other values (121) 7746
68.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11338
99.8%
Dash Punctuation 14
 
0.1%
Other Punctuation 7
 
0.1%
Space Separator 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 886
 
7.8%
정 430
 
3.8%
이 404
 
3.6%
영 333
 
2.9%
강 307
 
2.7%
룡 284
 
2.5%
석 260
 
2.3%
경 249
 
2.2%
환 240
 
2.1%
진 222
 
2.0%
Other values (118) 7723
68.1%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11338
99.8%
Common 23
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 886
 
7.8%
정 430
 
3.8%
이 404
 
3.6%
영 333
 
2.9%
강 307
 
2.7%
룡 284
 
2.5%
석 260
 
2.3%
경 249
 
2.2%
환 240
 
2.1%
진 222
 
2.0%
Other values (118) 7723
68.1%
Common
ValueCountFrequency (%)
- 14
60.9%
, 7
30.4%
2
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11338
99.8%
ASCII 23
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 886
 
7.8%
정 430
 
3.8%
이 404
 
3.6%
영 333
 
2.9%
강 307
 
2.7%
룡 284
 
2.5%
석 260
 
2.3%
경 249
 
2.2%
환 240
 
2.1%
진 222
 
2.0%
Other values (118) 7723
68.1%
ASCII
ValueCountFrequency (%)
- 14
60.9%
, 7
30.4%
2
 
8.7%

검사감독관
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.8 KiB
-
3797 
서정표
 
1
고명석
 
1

Length

Max length3
Median length1
Mean length1.0010529
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st row-
2nd row-
3rd row-
4th row-
5th row-

Common Values

ValueCountFrequency (%)
- 3797
99.9%
서정표 1
 
< 0.1%
고명석 1
 
< 0.1%

Length

2023-12-12T14:58:51.754059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:58:51.876107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3797
99.9%
서정표 1
 
< 0.1%
고명석 1
 
< 0.1%

하자발생내용
Text

Distinct51
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size29.8 KiB
2023-12-12T14:58:52.030244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length4
Mean length4.2566465
Min length1

Characters and Unicode

Total characters16171
Distinct characters140
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)0.9%

Sample

1st row이상없음
2nd row이상없음
3rd row이상없음
4th row이상없음
5th row이상없음
ValueCountFrequency (%)
이상없음 3587
91.4%
검사불가 80
 
2.0%
검사불가(관련방침참조 47
 
1.2%
선단부 18
 
0.5%
침하발생(하자아님 15
 
0.4%
12
 
0.3%
2∼3cm 11
 
0.3%
방파제 9
 
0.2%
정도 9
 
0.2%
접속슬래브 8
 
0.2%
Other values (74) 127
 
3.2%
2023-12-12T14:58:52.372604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 3595
22.2%
상 3591
22.2%
음 3590
22.2%
없 3589
22.2%
사 138
 
0.9%
불 138
 
0.9%
검 129
 
0.8%
가 128
 
0.8%
125
 
0.8%
침 80
 
0.5%
Other values (130) 1068
 
6.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15809
97.8%
Space Separator 125
 
0.8%
Close Punctuation 66
 
0.4%
Open Punctuation 66
 
0.4%
Decimal Number 42
 
0.3%
Lowercase Letter 35
 
0.2%
Math Symbol 16
 
0.1%
Dash Punctuation 12
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 3595
22.7%
상 3591
22.7%
음 3590
22.7%
없 3589
22.7%
사 138
 
0.9%
불 138
 
0.9%
검 129
 
0.8%
가 128
 
0.8%
침 80
 
0.5%
방 62
 
0.4%
Other values (114) 769
 
4.9%
Decimal Number
ValueCountFrequency (%)
3 14
33.3%
2 12
28.6%
5 7
16.7%
0 3
 
7.1%
1 3
 
7.1%
9 1
 
2.4%
7 1
 
2.4%
8 1
 
2.4%
Lowercase Letter
ValueCountFrequency (%)
m 19
54.3%
c 16
45.7%
Math Symbol
ValueCountFrequency (%)
∼ 15
93.8%
~ 1
 
6.2%
Space Separator
ValueCountFrequency (%)
125
100.0%
Close Punctuation
ValueCountFrequency (%)
) 66
100.0%
Open Punctuation
ValueCountFrequency (%)
( 66
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15809
97.8%
Common 327
 
2.0%
Latin 35
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 3595
22.7%
상 3591
22.7%
음 3590
22.7%
없 3589
22.7%
사 138
 
0.9%
불 138
 
0.9%
검 129
 
0.8%
가 128
 
0.8%
침 80
 
0.5%
방 62
 
0.4%
Other values (114) 769
 
4.9%
Common
ValueCountFrequency (%)
125
38.2%
) 66
20.2%
( 66
20.2%
∼ 15
 
4.6%
3 14
 
4.3%
- 12
 
3.7%
2 12
 
3.7%
5 7
 
2.1%
0 3
 
0.9%
1 3
 
0.9%
Other values (4) 4
 
1.2%
Latin
ValueCountFrequency (%)
m 19
54.3%
c 16
45.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15809
97.8%
ASCII 347
 
2.1%
Math Operators 15
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 3595
22.7%
상 3591
22.7%
음 3590
22.7%
없 3589
22.7%
사 138
 
0.9%
불 138
 
0.9%
검 129
 
0.8%
가 128
 
0.8%
침 80
 
0.5%
방 62
 
0.4%
Other values (114) 769
 
4.9%
ASCII
ValueCountFrequency (%)
125
36.0%
) 66
19.0%
( 66
19.0%
m 19
 
5.5%
c 16
 
4.6%
3 14
 
4.0%
- 12
 
3.5%
2 12
 
3.5%
5 7
 
2.0%
0 3
 
0.9%
Other values (5) 7
 
2.0%
Math Operators
ValueCountFrequency (%)
∼ 15
100.0%

조치사항
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct31
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size29.8 KiB
-
3734 
침하완료후 보수 시행
 
9
압밀침하 진행중으로 침하완료 보수실시
 
9
하자보수지시(농산물유통과4953)
 
7
하자보수조치
 
5
Other values (26)
 
35

Length

Max length44
Median length1
Mean length1.2216373
Min length1

Unique

Unique20 ?
Unique (%)0.5%

Sample

1st row-
2nd row-
3rd row-
4th row-
5th row-

Common Values

ValueCountFrequency (%)
- 3734
98.3%
침하완료후 보수 시행 9
 
0.2%
압밀침하 진행중으로 침하완료 보수실시 9
 
0.2%
하자보수지시(농산물유통과4953) 7
 
0.2%
하자보수조치 5
 
0.1%
하자보수 완료 4
 
0.1%
시공사 하자보수 조치(07.8.10) 3
 
0.1%
침하완료 후 하자보수 지시 2
 
0.1%
하자보수요청 2
 
0.1%
하자보수지시 2
 
0.1%
Other values (21) 22
 
0.6%

Length

2023-12-12T14:58:52.518157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
3734
96.2%
하자보수 15
 
0.4%
침하완료 11
 
0.3%
보수 9
 
0.2%
압밀침하 9
 
0.2%
진행중으로 9
 
0.2%
보수실시 9
 
0.2%
침하완료후 9
 
0.2%
시행 9
 
0.2%
하자보수지시(농산물유통과4953 7
 
0.2%
Other values (32) 61
 
1.6%

Interactions

2023-12-12T14:58:47.332963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:58:45.942641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:58:46.396905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:58:46.932592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:58:47.435496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:58:46.030967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:58:46.497765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:58:47.022057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:58:47.535760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:58:46.152294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:58:46.637951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:58:47.125058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:58:47.637817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:58:46.275069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:58:46.754175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:58:47.224147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:58:52.617480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공사년도공사구분공사번호하자순번순번검사구분검사감독관하자발생내용조치사항
공사년도1.0000.0670.5060.3240.3790.7150.0000.3450.226
공사구분0.0671.0000.0000.0000.0000.6720.0000.0000.000
공사번호0.5060.0001.0000.1960.1640.3510.0000.2960.268
하자순번0.3240.0000.1961.0000.5080.0000.4280.6940.397
순번0.3790.0000.1640.5081.0000.5430.0000.3250.341
검사구분0.7150.6720.3510.0000.5431.0000.0000.8060.000
검사감독관0.0000.0000.0000.4280.0000.0001.0000.9080.876
하자발생내용0.3450.0000.2960.6940.3250.8060.9081.0000.996
조치사항0.2260.0000.2680.3970.3410.0000.8760.9961.000
2023-12-12T14:58:52.792432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
조치사항검사감독관검사구분공사구분
조치사항1.0000.7020.0000.000
검사감독관0.7021.0000.0000.000
검사구분0.0000.0001.0000.567
공사구분0.0000.0000.5671.000
2023-12-12T14:58:52.936012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공사년도공사번호하자순번순번공사구분검사구분검사감독관조치사항
공사년도1.0000.0600.080-0.2310.0510.3310.0000.081
공사번호0.0601.0000.005-0.0630.0000.1250.0000.097
하자순번0.0800.0051.0000.2540.0000.0000.2840.150
순번-0.231-0.0630.2541.0000.0000.2150.0000.100
공사구분0.0510.0000.0000.0001.0000.5670.0000.000
검사구분0.3310.1250.0000.2150.5671.0000.0000.000
검사감독관0.0000.0000.2840.0000.0000.0001.0000.702
조치사항0.0810.0970.1500.1000.0000.0000.7021.000

Missing values

2023-12-12T14:58:47.791205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:58:47.986195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

공사년도공사구분공사번호부서코드하자순번순번검사년월일검사구분검사자검사감독관하자발생내용조치사항
01994공사781132004-12-17기간만료이동열-이상없음-
11994공사781122004-07-2604년상이동열-이상없음-
21994공사781112004-02-16정기이종술-이상없음-
31995공사11112004-02-16정기분차영대-이상없음-
41995공사471152006-01-1205년하이동열-이상없음-
51995공사471142005-07-1405년상김영삼-이상없음-
61995공사471132005-02-0304년하김영삼-이상없음-
71995공사471162006-06-09최종최문수-이상없음-
81995공사471112004-02-16정기분정영귀-이상없음-
91995공사471122004-08-0504년상김영삼-이상없음-
공사년도공사구분공사번호부서코드하자순번순번검사년월일검사구분검사자검사감독관하자발생내용조치사항
37892009공사901112009-07-16정기검사김종찬-이상없음-
37902009공사901122010-01-08정기검사이진환-이상없음-
37912009공사1021112010-01-06정기검사이진환-이상없음-
37922009공사1051122010-01-15정기검사김홍규-이상없음-
37932009공사1051112009-07-24정기검사김홍규-이상없음-
37942009공사1171112010-01-11정기검사김용일-이상없음-
37952009공사1291112010-02-21정기검사마태원-이상없음-
37962009공사1311112010-01-14정기검사허진영-이상없음-
37972009공사1401112010-01-06정기검사김용일-이상없음-
37982009공사1411112010-07-20-김명욱-이상없음-