Overview

Dataset statistics

Number of variables8
Number of observations3636
Missing cells126
Missing cells (%)0.4%
Duplicate rows35
Duplicate rows (%)1.0%
Total size in memory241.6 KiB
Average record size in memory68.0 B

Variable types

Numeric3
Categorical2
Text3

Dataset

Description경상남도_대금지급상세 데이터입니다. 공사년도, 공사구분, 지급일자, 적요, 지급금액 비고 등의 데이터를 포함하고있습니다.
Author경상남도
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15049523

Alerts

부서코드 has constant value ""Constant
Dataset has 35 (1.0%) duplicate rowsDuplicates
공사구분 is highly imbalanced (95.7%)Imbalance
지급일자 has 126 (3.5%) missing valuesMissing

Reproduction

Analysis started2023-12-11 00:37:21.797250
Analysis finished2023-12-11 00:37:24.101892
Duration2.3 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

공사년도
Real number (ℝ)

Distinct17
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2006.4323
Minimum2002
Maximum2019
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size32.1 KiB
2023-12-11T09:37:24.162799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2002
5-th percentile2003
Q12005
median2006
Q32008
95-th percentile2011
Maximum2019
Range17
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.6405137
Coefficient of variation (CV)0.0013160243
Kurtosis1.7350968
Mean2006.4323
Median Absolute Deviation (MAD)2
Skewness1.0475212
Sum7295388
Variance6.9723126
MonotonicityNot monotonic
2023-12-11T09:37:24.292572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
2007 568
15.6%
2006 556
15.3%
2005 553
15.2%
2003 541
14.9%
2008 446
12.3%
2004 333
9.2%
2009 319
8.8%
2011 86
 
2.4%
2010 86
 
2.4%
2015 51
 
1.4%
Other values (7) 97
 
2.7%
ValueCountFrequency (%)
2002 1
 
< 0.1%
2003 541
14.9%
2004 333
9.2%
2005 553
15.2%
2006 556
15.3%
2007 568
15.6%
2008 446
12.3%
2009 319
8.8%
2010 86
 
2.4%
2011 86
 
2.4%
ValueCountFrequency (%)
2019 1
 
< 0.1%
2017 6
 
0.2%
2016 16
 
0.4%
2015 51
 
1.4%
2014 34
 
0.9%
2013 23
 
0.6%
2012 16
 
0.4%
2011 86
 
2.4%
2010 86
 
2.4%
2009 319
8.8%

공사구분
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.5 KiB
공사
3599 
용역
 
35
기타
 
1
구매
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
공사 3599
99.0%
용역 35
 
1.0%
기타 1
 
< 0.1%
구매 1
 
< 0.1%

Length

2023-12-11T09:37:24.445863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:37:24.547415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공사 3599
99.0%
용역 35
 
1.0%
기타 1
 
< 0.1%
구매 1
 
< 0.1%

공사번호
Real number (ℝ)

Distinct173
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean70
Minimum1
Maximum596
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size32.1 KiB
2023-12-11T09:37:24.656364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q129
median61
Q3103
95-th percentile124
Maximum596
Range595
Interquartile range (IQR)74

Descriptive statistics

Standard deviation70.474021
Coefficient of variation (CV)1.0067717
Kurtosis20.880846
Mean70
Median Absolute Deviation (MAD)35
Skewness3.9378302
Sum254520
Variance4966.5876
MonotonicityNot monotonic
2023-12-11T09:37:24.789602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
103 206
 
5.7%
104 185
 
5.1%
105 150
 
4.1%
61 111
 
3.1%
109 90
 
2.5%
29 88
 
2.4%
1 88
 
2.4%
46 77
 
2.1%
5 76
 
2.1%
7 69
 
1.9%
Other values (163) 2496
68.6%
ValueCountFrequency (%)
1 88
2.4%
2 54
1.5%
3 16
 
0.4%
4 19
 
0.5%
5 76
2.1%
6 14
 
0.4%
7 69
1.9%
8 12
 
0.3%
9 25
 
0.7%
10 10
 
0.3%
ValueCountFrequency (%)
596 2
 
0.1%
530 2
 
0.1%
529 8
0.2%
524 4
 
0.1%
518 2
 
0.1%
514 3
 
0.1%
505 2
 
0.1%
495 4
 
0.1%
489 14
0.4%
447 1
 
< 0.1%

부서코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size28.5 KiB
1
3636 

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 3636
100.0%

Length

2023-12-11T09:37:24.937681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:37:25.060906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 3636
100.0%

지급일자
Text

MISSING 

Distinct570
Distinct (%)16.2%
Missing126
Missing (%)3.5%
Memory size28.5 KiB
2023-12-11T09:37:25.358324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9960114
Min length7

Characters and Unicode

Total characters35086
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique59 ?
Unique (%)1.7%

Sample

1st row2003-10-29
2nd row2005-02-04
3rd row2005-02-04
4th row2005-02-07
5th row2005-02-07
ValueCountFrequency (%)
2009-12-31 55
 
1.6%
2006-09-27 48
 
1.4%
2008-12-29 46
 
1.3%
2005-12-27 38
 
1.1%
2005-12-28 37
 
1.1%
2007-12-28 37
 
1.1%
2009-06-25 36
 
1.0%
2005-03-29 33
 
0.9%
2006-12-27 32
 
0.9%
2005-04-27 29
 
0.8%
Other values (561) 3120
88.9%
2023-12-11T09:37:25.891349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10438
29.7%
- 7008
20.0%
2 6440
18.4%
1 2959
 
8.4%
6 1506
 
4.3%
7 1467
 
4.2%
9 1465
 
4.2%
5 1235
 
3.5%
8 1139
 
3.2%
3 846
 
2.4%
Other values (2) 583
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 28077
80.0%
Dash Punctuation 7008
 
20.0%
Space Separator 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10438
37.2%
2 6440
22.9%
1 2959
 
10.5%
6 1506
 
5.4%
7 1467
 
5.2%
9 1465
 
5.2%
5 1235
 
4.4%
8 1139
 
4.1%
3 846
 
3.0%
4 582
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 7008
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 35086
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10438
29.7%
- 7008
20.0%
2 6440
18.4%
1 2959
 
8.4%
6 1506
 
4.3%
7 1467
 
4.2%
9 1465
 
4.2%
5 1235
 
3.5%
8 1139
 
3.2%
3 846
 
2.4%
Other values (2) 583
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 35086
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10438
29.7%
- 7008
20.0%
2 6440
18.4%
1 2959
 
8.4%
6 1506
 
4.3%
7 1467
 
4.2%
9 1465
 
4.2%
5 1235
 
3.5%
8 1139
 
3.2%
3 846
 
2.4%
Other values (2) 583
 
1.7%

적요
Text

Distinct809
Distinct (%)22.2%
Missing0
Missing (%)0.0%
Memory size28.5 KiB
2023-12-11T09:37:26.163512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23
Mean length8.3594609
Min length1

Characters and Unicode

Total characters30395
Distinct characters244
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique485 ?
Unique (%)13.3%

Sample

1st row전부명령권자 지급
2nd row하도급사 준공
3rd row원도급사 준공
4th row하도급자 기성
5th row원도급자 기성
ValueCountFrequency (%)
기성금 1142
23.5%
준공금 388
 
8.0%
하도급사 231
 
4.8%
원도급사 169
 
3.5%
기성금(농협 152
 
3.1%
기성금(하도급직불 115
 
2.4%
준공금(하도급직불 84
 
1.7%
준공 79
 
1.6%
하도급 72
 
1.5%
기성 72
 
1.5%
Other values (727) 2353
48.4%
2023-12-11T09:37:26.626462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
금 2631
 
8.7%
0 2597
 
8.5%
성 2014
 
6.6%
기 1958
 
6.4%
1 1607
 
5.3%
( 1509
 
5.0%
) 1487
 
4.9%
1222
 
4.0%
도 1001
 
3.3%
급 965
 
3.2%
Other values (234) 13404
44.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16863
55.5%
Decimal Number 9036
29.7%
Open Punctuation 1509
 
5.0%
Close Punctuation 1487
 
4.9%
Space Separator 1222
 
4.0%
Other Punctuation 208
 
0.7%
Dash Punctuation 65
 
0.2%
Math Symbol 3
 
< 0.1%
Connector Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
금 2631
15.6%
성 2014
11.9%
기 1958
 
11.6%
도 1001
 
5.9%
급 965
 
5.7%
공 886
 
5.3%
준 789
 
4.7%
하 730
 
4.3%
사 465
 
2.8%
직 401
 
2.4%
Other values (213) 5023
29.8%
Decimal Number
ValueCountFrequency (%)
0 2597
28.7%
1 1607
17.8%
5 726
 
8.0%
2 717
 
7.9%
7 703
 
7.8%
3 618
 
6.8%
6 583
 
6.5%
8 562
 
6.2%
4 536
 
5.9%
9 387
 
4.3%
Other Punctuation
ValueCountFrequency (%)
% 157
75.5%
. 33
 
15.9%
/ 14
 
6.7%
, 2
 
1.0%
: 2
 
1.0%
Open Punctuation
ValueCountFrequency (%)
( 1509
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1487
100.0%
Space Separator
ValueCountFrequency (%)
1222
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 65
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16863
55.5%
Common 13532
44.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
금 2631
15.6%
성 2014
11.9%
기 1958
 
11.6%
도 1001
 
5.9%
급 965
 
5.7%
공 886
 
5.3%
준 789
 
4.7%
하 730
 
4.3%
사 465
 
2.8%
직 401
 
2.4%
Other values (213) 5023
29.8%
Common
ValueCountFrequency (%)
0 2597
19.2%
1 1607
11.9%
( 1509
11.2%
) 1487
11.0%
1222
9.0%
5 726
 
5.4%
2 717
 
5.3%
7 703
 
5.2%
3 618
 
4.6%
6 583
 
4.3%
Other values (11) 1763
13.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16863
55.5%
ASCII 13532
44.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
금 2631
15.6%
성 2014
11.9%
기 1958
 
11.6%
도 1001
 
5.9%
급 965
 
5.7%
공 886
 
5.3%
준 789
 
4.7%
하 730
 
4.3%
사 465
 
2.8%
직 401
 
2.4%
Other values (213) 5023
29.8%
ASCII
ValueCountFrequency (%)
0 2597
19.2%
1 1607
11.9%
( 1509
11.2%
) 1487
11.0%
1222
9.0%
5 726
 
5.4%
2 717
 
5.3%
7 703
 
5.2%
3 618
 
4.6%
6 583
 
4.3%
Other values (11) 1763
13.0%

지급금액
Real number (ℝ)

Distinct2964
Distinct (%)81.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.5427609 × 108
Minimum0
Maximum1.2285366 × 1010
Zeros30
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size32.1 KiB
2023-12-11T09:37:26.762730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9584250
Q162850000
median1.6360142 × 108
Q33.730113 × 108
95-th percentile1.3428562 × 109
Maximum1.2285366 × 1010
Range1.2285366 × 1010
Interquartile range (IQR)3.101613 × 108

Descriptive statistics

Standard deviation6.4131753 × 108
Coefficient of variation (CV)1.8102196
Kurtosis62.532485
Mean3.5427609 × 108
Median Absolute Deviation (MAD)1.2195392 × 108
Skewness6.0699901
Sum1.2881479 × 1012
Variance4.1128817 × 1017
MonotonicityNot monotonic
2023-12-11T09:37:26.881528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 30
 
0.8%
200000000 9
 
0.2%
400000000 8
 
0.2%
300000000 8
 
0.2%
45000000 7
 
0.2%
150000000 7
 
0.2%
100000000 6
 
0.2%
82600000 6
 
0.2%
13962620 5
 
0.1%
22000000 5
 
0.1%
Other values (2954) 3545
97.5%
ValueCountFrequency (%)
0 30
0.8%
7400 1
 
< 0.1%
56000 1
 
< 0.1%
63000 1
 
< 0.1%
72000 1
 
< 0.1%
105000 1
 
< 0.1%
200000 2
 
0.1%
228680 1
 
< 0.1%
263500 2
 
0.1%
292000 1
 
< 0.1%
ValueCountFrequency (%)
12285366000 1
< 0.1%
8434789792 1
< 0.1%
7168800000 1
< 0.1%
6823280000 1
< 0.1%
6517792112 1
< 0.1%
6142683000 2
0.1%
6010242000 1
< 0.1%
5468273000 1
< 0.1%
5208876400 2
0.1%
4984320000 1
< 0.1%

비고(성명)
Text

Distinct768
Distinct (%)21.1%
Missing0
Missing (%)0.0%
Memory size28.5 KiB
2023-12-11T09:37:27.093968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length13
Mean length4.9650715
Min length1

Characters and Unicode

Total characters18053
Distinct characters276
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique332 ?
Unique (%)9.1%

Sample

1st row장원종합건설(주)
2nd row도림건설
3rd row삼전건설
4th row덕림건설
5th row대건종합건설
ValueCountFrequency (%)
425
 
11.6%
현대건설 65
 
1.8%
삼성물산 62
 
1.7%
대저토건 53
 
1.5%
주)대저토건 51
 
1.4%
삼성물산(주 50
 
1.4%
현대건설(주 43
 
1.2%
주)대우건설 43
 
1.2%
대우건설 38
 
1.0%
흥한건설 36
 
1.0%
Other values (764) 2786
76.3%
2023-12-11T09:37:27.463108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
건 2266
 
12.6%
설 1981
 
11.0%
주 1192
 
6.6%
( 1190
 
6.6%
) 1190
 
6.6%
대 710
 
3.9%
- 425
 
2.4%
산 388
 
2.1%
성 337
 
1.9%
업 329
 
1.8%
Other values (266) 8045
44.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15053
83.4%
Open Punctuation 1190
 
6.6%
Close Punctuation 1190
 
6.6%
Dash Punctuation 425
 
2.4%
Uppercase Letter 81
 
0.4%
Decimal Number 78
 
0.4%
Space Separator 16
 
0.1%
Other Punctuation 13
 
0.1%
Lowercase Letter 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
건 2266
 
15.1%
설 1981
 
13.2%
주 1192
 
7.9%
대 710
 
4.7%
산 388
 
2.6%
성 337
 
2.2%
업 329
 
2.2%
우 312
 
2.1%
종 310
 
2.1%
합 307
 
2.0%
Other values (239) 6921
46.0%
Decimal Number
ValueCountFrequency (%)
1 20
25.6%
0 19
24.4%
2 10
12.8%
3 7
 
9.0%
4 6
 
7.7%
6 4
 
5.1%
5 4
 
5.1%
9 3
 
3.8%
7 3
 
3.8%
8 2
 
2.6%
Other Punctuation
ValueCountFrequency (%)
. 6
46.2%
% 3
23.1%
& 2
 
15.4%
/ 1
 
7.7%
: 1
 
7.7%
Uppercase Letter
ValueCountFrequency (%)
S 24
29.6%
K 23
28.4%
C 18
22.2%
I 16
19.8%
Lowercase Letter
ValueCountFrequency (%)
s 3
42.9%
k 2
28.6%
i 1
 
14.3%
c 1
 
14.3%
Open Punctuation
ValueCountFrequency (%)
( 1190
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1190
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 425
100.0%
Space Separator
ValueCountFrequency (%)
16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15053
83.4%
Common 2912
 
16.1%
Latin 88
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
건 2266
 
15.1%
설 1981
 
13.2%
주 1192
 
7.9%
대 710
 
4.7%
산 388
 
2.6%
성 337
 
2.2%
업 329
 
2.2%
우 312
 
2.1%
종 310
 
2.1%
합 307
 
2.0%
Other values (239) 6921
46.0%
Common
ValueCountFrequency (%)
( 1190
40.9%
) 1190
40.9%
- 425
 
14.6%
1 20
 
0.7%
0 19
 
0.7%
16
 
0.5%
2 10
 
0.3%
3 7
 
0.2%
. 6
 
0.2%
4 6
 
0.2%
Other values (9) 23
 
0.8%
Latin
ValueCountFrequency (%)
S 24
27.3%
K 23
26.1%
C 18
20.5%
I 16
18.2%
s 3
 
3.4%
k 2
 
2.3%
i 1
 
1.1%
c 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15053
83.4%
ASCII 3000
 
16.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
건 2266
 
15.1%
설 1981
 
13.2%
주 1192
 
7.9%
대 710
 
4.7%
산 388
 
2.6%
성 337
 
2.2%
업 329
 
2.2%
우 312
 
2.1%
종 310
 
2.1%
합 307
 
2.0%
Other values (239) 6921
46.0%
ASCII
ValueCountFrequency (%)
( 1190
39.7%
) 1190
39.7%
- 425
 
14.2%
S 24
 
0.8%
K 23
 
0.8%
1 20
 
0.7%
0 19
 
0.6%
C 18
 
0.6%
16
 
0.5%
I 16
 
0.5%
Other values (17) 59
 
2.0%

Interactions

2023-12-11T09:37:23.329586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:37:22.393858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:37:22.708309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:37:23.422793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:37:22.482698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:37:23.007525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:37:23.511755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:37:22.572855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:37:23.218519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:37:27.553196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공사년도공사구분공사번호지급금액
공사년도1.0000.1160.4850.219
공사구분0.1161.0000.3180.000
공사번호0.4850.3181.0000.065
지급금액0.2190.0000.0651.000
2023-12-11T09:37:27.648740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공사년도공사번호지급금액공사구분
공사년도1.000-0.222-0.2720.069
공사번호-0.2221.0000.0380.208
지급금액-0.2720.0381.0000.000
공사구분0.0690.2080.0001.000

Missing values

2023-12-11T09:37:23.932400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:37:24.050761image/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

공사년도공사구분공사번호부서코드지급일자적요지급금액비고(성명)
02002공사5412003-10-29전부명령권자 지급70000000장원종합건설(주)
12003공사2912005-02-04하도급사 준공405000000도림건설
22003공사2912005-02-04원도급사 준공327100000삼전건설
32003공사3412005-02-07하도급자 기성30171190덕림건설
42003공사3412005-02-07원도급자 기성699887810대건종합건설
52003공사5112005-10-26채권압류유보금42045630(주)대능
62003공사9312004-12-28하도급체 직불310156540장안토건(주)
72003공사9312004-12-28전부명령권자 지급217862460장안종합건설(주)
82003공사9312003-12-30전부명령권자 지급264813000장원종합건설(주)
92003공사9312004-09-22전부명령권자 지급376270000장원종합건설(주)
공사년도공사구분공사번호부서코드지급일자적요지급금액비고(성명)
36262016공사11712016-10-13진영건설13585000-
36272016공사14712016-08-09플러스이앤씨164927370-
36282016공사14712016-08-09나한건설158459630-
36292017공사1912016-08-09나한건설158459630-
36302017공사1912016-08-09플러스이앤씨164927370-
36312017공사5912017-04-26석천개발187550000-
36322017공사5912017-04-26한국지오텍153450000-
36332017공사6912017-08-21하자보증금68066800-
36342017공사6912017-08-21세입세출외 현금 보관226451200경합시 공탁 예정
36352019공사5712019-07-18계약금-노무비-보험료 정산206008000-

Duplicate rows

Most frequently occurring

공사년도공사구분공사번호부서코드지급일자적요지급금액비고(성명)# duplicates
312007공사1191<NA>-0-5
242005공사291<NA>-0-3
252005용역501<NA>-0-3
272006공사7112008-01-03준공금584814060-3
322008공사661<NA>-0-3
332008공사1321<NA>-0-3
02003공사9712005-07-29기성금551925000(주)대아건설2
12003공사9712005-07-29기성금2575650000(주)포스코건설2
22003공사10312005-03-29기성금(26%)366340000대림건설(주)2
32003공사10312005-03-29기성금(26%)366340000삼성물산(주)2