Overview

Dataset statistics

Number of variables25
Number of observations2800
Missing cells11431
Missing cells (%)16.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory571.6 KiB
Average record size in memory209.0 B

Variable types

Numeric8
Categorical3
Text14

Dataset

Description경상남도 공사계약대장시스템의 하도급관리 데이터입니다. 공사년도, 변경날짜, 하도부분금액, 하도금액 등의 데이터를 포함하고있습니다.
Author경상남도
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15049515

Alerts

부서코드 has constant value ""Constant
공사구분 is highly imbalanced (98.7%)Imbalance
지급방법 is highly imbalanced (59.3%)Imbalance
변경계약일자 has 1697 (60.6%) missing valuesMissing
신고일자 has 195 (7.0%) missing valuesMissing
변경신고일자 has 1695 (60.5%) missing valuesMissing
하도부분금액 has 150 (5.4%) missing valuesMissing
변경하도부분금액 has 1704 (60.9%) missing valuesMissing
하도금액 has 113 (4.0%) missing valuesMissing
변경하도금액 has 1708 (61.0%) missing valuesMissing
하도비율 has 122 (4.4%) missing valuesMissing
공사시작일 has 138 (4.9%) missing valuesMissing
공사종료일 has 136 (4.9%) missing valuesMissing
변경공사시작일 has 1903 (68.0%) missing valuesMissing
변경공사종료일 has 1870 (66.8%) missing valuesMissing
하도금액 is highly skewed (γ1 = 46.65013525)Skewed
변경하도금액 is highly skewed (γ1 = 21.07140764)Skewed
변경하도부분금액 has 45 (1.6%) zerosZeros

Reproduction

Analysis started2023-12-11 00:00:17.696263
Analysis finished2023-12-11 00:00:18.759259
Duration1.06 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

공사년도
Real number (ℝ)

Distinct25
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2007.895
Minimum1990
Maximum2019
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.7 KiB
2023-12-11T09:00:18.811745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1990
5-th percentile1999
Q12004
median2008
Q32012
95-th percentile2018
Maximum2019
Range29
Interquartile range (IQR)8

Descriptive statistics

Standard deviation5.403515
Coefficient of variation (CV)0.0026911342
Kurtosis-0.75602135
Mean2007.895
Median Absolute Deviation (MAD)4
Skewness0.12355359
Sum5622106
Variance29.197974
MonotonicityNot monotonic
2023-12-11T09:00:18.922564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
2003 228
 
8.1%
2010 216
 
7.7%
2007 191
 
6.8%
2009 191
 
6.8%
2004 164
 
5.9%
2005 160
 
5.7%
2011 160
 
5.7%
2006 150
 
5.4%
2013 142
 
5.1%
2012 139
 
5.0%
Other values (15) 1059
37.8%
ValueCountFrequency (%)
1990 1
 
< 0.1%
1992 2
 
0.1%
1997 2
 
0.1%
1998 54
 
1.9%
1999 93
3.3%
2000 118
4.2%
2001 100
3.6%
2002 99
3.5%
2003 228
8.1%
2004 164
5.9%
ValueCountFrequency (%)
2019 42
 
1.5%
2018 105
3.8%
2017 69
 
2.5%
2016 67
 
2.4%
2015 102
3.6%
2014 68
 
2.4%
2013 142
5.1%
2012 139
5.0%
2011 160
5.7%
2010 216
7.7%

공사구분
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.0 KiB
공사
2795 
용역
 
4
구매
 
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 2795
99.8%
용역 4
 
0.1%
구매 1
 
< 0.1%

Length

2023-12-11T09:00:19.054739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:00:19.156961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공사 2795
99.8%
용역 4
 
0.1%
구매 1
 
< 0.1%

공사번호
Real number (ℝ)

Distinct284
Distinct (%)10.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean94.5475
Minimum1
Maximum629
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.7 KiB
2023-12-11T09:00:19.278553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7
Q133
median62
Q3104
95-th percentile431
Maximum629
Range628
Interquartile range (IQR)71

Descriptive statistics

Standard deviation111.88691
Coefficient of variation (CV)1.1833936
Kurtosis5.8415848
Mean94.5475
Median Absolute Deviation (MAD)35
Skewness2.5089914
Sum264733
Variance12518.681
MonotonicityNot monotonic
2023-12-11T09:00:19.653051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
105 48
 
1.7%
22 46
 
1.6%
60 37
 
1.3%
97 37
 
1.3%
7 36
 
1.3%
51 36
 
1.3%
21 34
 
1.2%
103 33
 
1.2%
40 33
 
1.2%
49 32
 
1.1%
Other values (274) 2428
86.7%
ValueCountFrequency (%)
1 22
0.8%
2 20
0.7%
3 21
0.8%
4 15
0.5%
5 20
0.7%
6 15
0.5%
7 36
1.3%
8 13
 
0.5%
9 13
 
0.5%
10 14
 
0.5%
ValueCountFrequency (%)
629 2
0.1%
618 1
 
< 0.1%
617 1
 
< 0.1%
596 1
 
< 0.1%
594 1
 
< 0.1%
543 1
 
< 0.1%
530 2
0.1%
529 3
0.1%
527 2
0.1%
524 2
0.1%

부서코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size22.0 KiB
1
2800 

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 2800
100.0%

Length

2023-12-11T09:00:19.776391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:00:19.859408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 2800
100.0%

순번
Real number (ℝ)

Distinct36
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.8117857
Minimum1
Maximum36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.7 KiB
2023-12-11T09:00:19.943481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile10
Maximum36
Range35
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.7798383
Coefficient of variation (CV)1.3442839
Kurtosis20.458348
Mean2.8117857
Median Absolute Deviation (MAD)1
Skewness4.0449093
Sum7873
Variance14.287178
MonotonicityNot monotonic
2023-12-11T09:00:20.101833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
1 1352
48.3%
2 664
23.7%
3 271
 
9.7%
4 139
 
5.0%
5 79
 
2.8%
6 61
 
2.2%
7 40
 
1.4%
8 28
 
1.0%
9 21
 
0.8%
10 17
 
0.6%
Other values (26) 128
 
4.6%
ValueCountFrequency (%)
1 1352
48.3%
2 664
23.7%
3 271
 
9.7%
4 139
 
5.0%
5 79
 
2.8%
6 61
 
2.2%
7 40
 
1.4%
8 28
 
1.0%
9 21
 
0.8%
10 17
 
0.6%
ValueCountFrequency (%)
36 1
< 0.1%
35 1
< 0.1%
34 1
< 0.1%
33 1
< 0.1%
32 1
< 0.1%
31 1
< 0.1%
30 1
< 0.1%
29 1
< 0.1%
28 1
< 0.1%
27 2
0.1%

업체명
Text

Distinct1073
Distinct (%)38.3%
Missing0
Missing (%)0.0%
Memory size22.0 KiB
2023-12-11T09:00:20.417802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length7
Mean length7.335
Min length1

Characters and Unicode

Total characters20538
Distinct characters320
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique618 ?
Unique (%)22.1%

Sample

1st row(주)태광산업
2nd row흥한산업(주)
3rd row영남건설
4th row효승건설(주)
5th row효승건설(주)
ValueCountFrequency (%)
대호건업(주 42
 
1.5%
합)대광건설 41
 
1.4%
대호건설(주 41
 
1.4%
우진건설(주 36
 
1.3%
송평건설(주 33
 
1.2%
대영해상개발(주 32
 
1.1%
안정해양개발(주 28
 
1.0%
흥한산업(주 26
 
0.9%
호진건설(주 25
 
0.9%
풍도건설(주 25
 
0.9%
Other values (1074) 2499
88.4%
2023-12-11T09:00:20.882393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 2693
 
13.1%
( 2689
 
13.1%
주 2610
 
12.7%
건 1785
 
8.7%
설 1501
 
7.3%
대 409
 
2.0%
업 303
 
1.5%
개 294
 
1.4%
발 291
 
1.4%
산 286
 
1.4%
Other values (310) 7677
37.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15024
73.2%
Close Punctuation 2693
 
13.1%
Open Punctuation 2689
 
13.1%
Uppercase Letter 41
 
0.2%
Decimal Number 30
 
0.1%
Space Separator 28
 
0.1%
Other Punctuation 23
 
0.1%
Math Symbol 8
 
< 0.1%
Connector Punctuation 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 2610
 
17.4%
건 1785
 
11.9%
설 1501
 
10.0%
대 409
 
2.7%
업 303
 
2.0%
개 294
 
2.0%
발 291
 
1.9%
산 286
 
1.9%
성 224
 
1.5%
토 214
 
1.4%
Other values (282) 7107
47.3%
Uppercase Letter
ValueCountFrequency (%)
S 8
19.5%
P 5
12.2%
C 5
12.2%
R 4
9.8%
K 3
 
7.3%
F 3
 
7.3%
E 3
 
7.3%
Y 3
 
7.3%
T 2
 
4.9%
L 1
 
2.4%
Other values (4) 4
9.8%
Decimal Number
ValueCountFrequency (%)
1 9
30.0%
0 8
26.7%
2 8
26.7%
3 3
 
10.0%
8 2
 
6.7%
Other Punctuation
ValueCountFrequency (%)
. 22
95.7%
, 1
 
4.3%
Math Symbol
ValueCountFrequency (%)
> 7
87.5%
→ 1
 
12.5%
Close Punctuation
ValueCountFrequency (%)
) 2693
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2689
100.0%
Space Separator
ValueCountFrequency (%)
28
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15024
73.2%
Common 5473
 
26.6%
Latin 41
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 2610
 
17.4%
건 1785
 
11.9%
설 1501
 
10.0%
대 409
 
2.7%
업 303
 
2.0%
개 294
 
2.0%
발 291
 
1.9%
산 286
 
1.9%
성 224
 
1.5%
토 214
 
1.4%
Other values (282) 7107
47.3%
Common
ValueCountFrequency (%)
) 2693
49.2%
( 2689
49.1%
28
 
0.5%
. 22
 
0.4%
1 9
 
0.2%
0 8
 
0.1%
2 8
 
0.1%
> 7
 
0.1%
3 3
 
0.1%
8 2
 
< 0.1%
Other values (4) 4
 
0.1%
Latin
ValueCountFrequency (%)
S 8
19.5%
P 5
12.2%
C 5
12.2%
R 4
9.8%
K 3
 
7.3%
F 3
 
7.3%
E 3
 
7.3%
Y 3
 
7.3%
T 2
 
4.9%
L 1
 
2.4%
Other values (4) 4
9.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15024
73.2%
ASCII 5513
 
26.8%
Arrows 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 2693
48.8%
( 2689
48.8%
28
 
0.5%
. 22
 
0.4%
1 9
 
0.2%
0 8
 
0.1%
2 8
 
0.1%
S 8
 
0.1%
> 7
 
0.1%
P 5
 
0.1%
Other values (17) 36
 
0.7%
Hangul
ValueCountFrequency (%)
주 2610
 
17.4%
건 1785
 
11.9%
설 1501
 
10.0%
대 409
 
2.7%
업 303
 
2.0%
개 294
 
2.0%
발 291
 
1.9%
산 286
 
1.9%
성 224
 
1.5%
토 214
 
1.4%
Other values (282) 7107
47.3%
Arrows
ValueCountFrequency (%)
→ 1
100.0%

공종
Text

Distinct589
Distinct (%)21.0%
Missing0
Missing (%)0.0%
Memory size22.0 KiB
2023-12-11T09:00:21.164902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length24
Mean length3.9442857
Min length1

Characters and Unicode

Total characters11044
Distinct characters288
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

Unique445 ?
Unique (%)15.9%

Sample

1st row-
2nd row-
3rd row-
4th row-
5th row-
ValueCountFrequency (%)
807
25.2%
토공 224
 
7.0%
철콘 149
 
4.6%
토공사 145
 
4.5%
철근콘크리트공사 116
 
3.6%
및 99
 
3.1%
석공 92
 
2.9%
수중 77
 
2.4%
구조물 67
 
2.1%
철근콘크리트 62
 
1.9%
Other values (629) 1369
42.7%
2023-12-11T09:00:21.685539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
공 1522
 
13.8%
사 850
 
7.7%
- 807
 
7.3%
토 485
 
4.4%
철 431
 
3.9%
콘 414
 
3.7%
412
 
3.7%
수 284
 
2.6%
리 253
 
2.3%
조 240
 
2.2%
Other values (278) 5346
48.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9211
83.4%
Dash Punctuation 807
 
7.3%
Space Separator 412
 
3.7%
Uppercase Letter 240
 
2.2%
Decimal Number 169
 
1.5%
Open Punctuation 73
 
0.7%
Close Punctuation 73
 
0.7%
Other Punctuation 35
 
0.3%
Lowercase Letter 24
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 1522
 
16.5%
사 850
 
9.2%
토 485
 
5.3%
철 431
 
4.7%
콘 414
 
4.5%
수 284
 
3.1%
리 253
 
2.7%
조 240
 
2.6%
설 240
 
2.6%
트 236
 
2.6%
Other values (232) 4256
46.2%
Uppercase Letter
ValueCountFrequency (%)
P 41
17.1%
C 29
12.1%
A 21
8.8%
E 21
8.8%
I 20
8.3%
B 20
8.3%
M 16
 
6.7%
S 14
 
5.8%
R 13
 
5.4%
F 7
 
2.9%
Other values (11) 38
15.8%
Lowercase Letter
ValueCountFrequency (%)
e 8
33.3%
o 2
 
8.3%
r 2
 
8.3%
a 2
 
8.3%
m 2
 
8.3%
x 2
 
8.3%
d 1
 
4.2%
i 1
 
4.2%
b 1
 
4.2%
n 1
 
4.2%
Other values (2) 2
 
8.3%
Decimal Number
ValueCountFrequency (%)
2 57
33.7%
1 42
24.9%
0 36
21.3%
3 30
17.8%
8 2
 
1.2%
4 1
 
0.6%
6 1
 
0.6%
Other Punctuation
ValueCountFrequency (%)
. 29
82.9%
/ 6
 
17.1%
Dash Punctuation
ValueCountFrequency (%)
- 807
100.0%
Space Separator
ValueCountFrequency (%)
412
100.0%
Open Punctuation
ValueCountFrequency (%)
( 73
100.0%
Close Punctuation
ValueCountFrequency (%)
) 73
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9211
83.4%
Common 1569
 
14.2%
Latin 264
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 1522
 
16.5%
사 850
 
9.2%
토 485
 
5.3%
철 431
 
4.7%
콘 414
 
4.5%
수 284
 
3.1%
리 253
 
2.7%
조 240
 
2.6%
설 240
 
2.6%
트 236
 
2.6%
Other values (232) 4256
46.2%
Latin
ValueCountFrequency (%)
P 41
15.5%
C 29
11.0%
A 21
 
8.0%
E 21
 
8.0%
I 20
 
7.6%
B 20
 
7.6%
M 16
 
6.1%
S 14
 
5.3%
R 13
 
4.9%
e 8
 
3.0%
Other values (23) 61
23.1%
Common
ValueCountFrequency (%)
- 807
51.4%
412
26.3%
( 73
 
4.7%
) 73
 
4.7%
2 57
 
3.6%
1 42
 
2.7%
0 36
 
2.3%
3 30
 
1.9%
. 29
 
1.8%
/ 6
 
0.4%
Other values (3) 4
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9211
83.4%
ASCII 1833
 
16.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
공 1522
 
16.5%
사 850
 
9.2%
토 485
 
5.3%
철 431
 
4.7%
콘 414
 
4.5%
수 284
 
3.1%
리 253
 
2.7%
조 240
 
2.6%
설 240
 
2.6%
트 236
 
2.6%
Other values (232) 4256
46.2%
ASCII
ValueCountFrequency (%)
- 807
44.0%
412
22.5%
( 73
 
4.0%
) 73
 
4.0%
2 57
 
3.1%
1 42
 
2.3%
P 41
 
2.2%
0 36
 
2.0%
3 30
 
1.6%
. 29
 
1.6%
Other values (36) 233
 
12.7%

업태
Text

Distinct185
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Memory size22.0 KiB
2023-12-11T09:00:21.880067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16
Mean length2.75
Min length1

Characters and Unicode

Total characters7700
Distinct characters138
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

Unique112 ?
Unique (%)4.0%

Sample

1st row철.콘
2nd row철.콘
3rd row구조물공
4th row토공
5th row철.콘
ValueCountFrequency (%)
828
29.3%
전문 494
17.5%
전문건설 228
 
8.1%
건설업 212
 
7.5%
건설 168
 
5.9%
토공사업 112
 
4.0%
철.콘 90
 
3.2%
토공 82
 
2.9%
철근콘크리트공사업 65
 
2.3%
토공사 39
 
1.4%
Other values (171) 511
18.1%
2023-12-11T09:00:22.267782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 828
10.8%
전 773
10.0%
문 755
9.8%
설 682
 
8.9%
건 652
 
8.5%
공 636
 
8.3%
업 629
 
8.2%
사 453
 
5.9%
토 287
 
3.7%
철 279
 
3.6%
Other values (128) 1726
22.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6713
87.2%
Dash Punctuation 828
 
10.8%
Other Punctuation 112
 
1.5%
Space Separator 29
 
0.4%
Decimal Number 14
 
0.2%
Close Punctuation 2
 
< 0.1%
Open Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 773
11.5%
문 755
11.2%
설 682
10.2%
건 652
9.7%
공 636
9.5%
업 629
9.4%
사 453
 
6.7%
토 287
 
4.3%
철 279
 
4.2%
콘 244
 
3.6%
Other values (113) 1323
19.7%
Decimal Number
ValueCountFrequency (%)
1 5
35.7%
9 4
28.6%
4 1
 
7.1%
0 1
 
7.1%
7 1
 
7.1%
6 1
 
7.1%
2 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
. 94
83.9%
, 12
 
10.7%
/ 5
 
4.5%
: 1
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 828
100.0%
Space Separator
ValueCountFrequency (%)
29
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6713
87.2%
Common 987
 
12.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 773
11.5%
문 755
11.2%
설 682
10.2%
건 652
9.7%
공 636
9.5%
업 629
9.4%
사 453
 
6.7%
토 287
 
4.3%
철 279
 
4.2%
콘 244
 
3.6%
Other values (113) 1323
19.7%
Common
ValueCountFrequency (%)
- 828
83.9%
. 94
 
9.5%
29
 
2.9%
, 12
 
1.2%
1 5
 
0.5%
/ 5
 
0.5%
9 4
 
0.4%
) 2
 
0.2%
( 2
 
0.2%
4 1
 
0.1%
Other values (5) 5
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6713
87.2%
ASCII 987
 
12.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 828
83.9%
. 94
 
9.5%
29
 
2.9%
, 12
 
1.2%
1 5
 
0.5%
/ 5
 
0.5%
9 4
 
0.4%
) 2
 
0.2%
( 2
 
0.2%
4 1
 
0.1%
Other values (5) 5
 
0.5%
Hangul
ValueCountFrequency (%)
전 773
11.5%
문 755
11.2%
설 682
10.2%
건 652
9.7%
공 636
9.5%
업 629
9.4%
사 453
 
6.7%
토 287
 
4.3%
철 279
 
4.2%
콘 244
 
3.6%
Other values (113) 1323
19.7%

종목
Text

Distinct384
Distinct (%)13.7%
Missing0
Missing (%)0.0%
Memory size22.0 KiB
2023-12-11T09:00:22.541301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length3.4042857
Min length1

Characters and Unicode

Total characters9532
Distinct characters188
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique264 ?
Unique (%)9.4%

Sample

1st row철근콘크리트
2nd row철근콘크리트
3rd row구조물
4th row토공사
5th row철근콘크리트
ValueCountFrequency (%)
895
30.4%
토공 245
 
8.3%
철근콘크리트 161
 
5.5%
토공사 149
 
5.1%
철콘 117
 
4.0%
석공 79
 
2.7%
토공사업 77
 
2.6%
철근콘크리트공 62
 
2.1%
철근콘크리트공사업 54
 
1.8%
건설 53
 
1.8%
Other values (368) 1053
35.8%
2023-12-11T09:00:22.965439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
공 1415
14.8%
- 895
 
9.4%
사 768
 
8.1%
토 558
 
5.9%
철 519
 
5.4%
콘 497
 
5.2%
업 350
 
3.7%
리 343
 
3.6%
크 330
 
3.5%
트 330
 
3.5%
Other values (178) 3527
37.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8403
88.2%
Dash Punctuation 895
 
9.4%
Space Separator 145
 
1.5%
Other Punctuation 27
 
0.3%
Decimal Number 22
 
0.2%
Uppercase Letter 16
 
0.2%
Close Punctuation 12
 
0.1%
Open Punctuation 12
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 1415
16.8%
사 768
 
9.1%
토 558
 
6.6%
철 519
 
6.2%
콘 497
 
5.9%
업 350
 
4.2%
리 343
 
4.1%
크 330
 
3.9%
트 330
 
3.9%
근 328
 
3.9%
Other values (151) 2965
35.3%
Uppercase Letter
ValueCountFrequency (%)
M 2
12.5%
A 2
12.5%
S 2
12.5%
P 1
 
6.2%
L 1
 
6.2%
I 1
 
6.2%
N 1
 
6.2%
H 1
 
6.2%
O 1
 
6.2%
E 1
 
6.2%
Other values (3) 3
18.8%
Decimal Number
ValueCountFrequency (%)
0 8
36.4%
2 6
27.3%
1 4
18.2%
7 2
 
9.1%
3 1
 
4.5%
4 1
 
4.5%
Other Punctuation
ValueCountFrequency (%)
. 13
48.1%
, 11
40.7%
/ 2
 
7.4%
· 1
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 895
100.0%
Space Separator
ValueCountFrequency (%)
145
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8403
88.2%
Common 1113
 
11.7%
Latin 16
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 1415
16.8%
사 768
 
9.1%
토 558
 
6.6%
철 519
 
6.2%
콘 497
 
5.9%
업 350
 
4.2%
리 343
 
4.1%
크 330
 
3.9%
트 330
 
3.9%
근 328
 
3.9%
Other values (151) 2965
35.3%
Common
ValueCountFrequency (%)
- 895
80.4%
145
 
13.0%
. 13
 
1.2%
) 12
 
1.1%
( 12
 
1.1%
, 11
 
1.0%
0 8
 
0.7%
2 6
 
0.5%
1 4
 
0.4%
7 2
 
0.2%
Other values (4) 5
 
0.4%
Latin
ValueCountFrequency (%)
M 2
12.5%
A 2
12.5%
S 2
12.5%
P 1
 
6.2%
L 1
 
6.2%
I 1
 
6.2%
N 1
 
6.2%
H 1
 
6.2%
O 1
 
6.2%
E 1
 
6.2%
Other values (3) 3
18.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8402
88.1%
ASCII 1128
 
11.8%
None 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
공 1415
16.8%
사 768
 
9.1%
토 558
 
6.6%
철 519
 
6.2%
콘 497
 
5.9%
업 350
 
4.2%
리 343
 
4.1%
크 330
 
3.9%
트 330
 
3.9%
근 328
 
3.9%
Other values (150) 2964
35.3%
ASCII
ValueCountFrequency (%)
- 895
79.3%
145
 
12.9%
. 13
 
1.2%
) 12
 
1.1%
( 12
 
1.1%
, 11
 
1.0%
0 8
 
0.7%
2 6
 
0.5%
1 4
 
0.4%
7 2
 
0.2%
Other values (16) 20
 
1.8%
None
ValueCountFrequency (%)
· 1
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅈ 1
100.0%

계약일자
Text

Distinct1515
Distinct (%)54.1%
Missing0
Missing (%)0.0%
Memory size22.0 KiB
2023-12-11T09:00:23.263226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.6003571
Min length1

Characters and Unicode

Total characters21281
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique877 ?
Unique (%)31.3%

Sample

1st row19911106
2nd row19920415
3rd row19920401
4th row19980116
5th row19980116
ValueCountFrequency (%)
157
 
5.6%
20090115 14
 
0.5%
20030415 11
 
0.4%
20110503 10
 
0.4%
20090119 10
 
0.4%
20040510 9
 
0.3%
20090205 9
 
0.3%
20060403 9
 
0.3%
20010702 9
 
0.3%
20070423 8
 
0.3%
Other values (1506) 2555
91.2%
2023-12-11T09:00:23.785446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7703
36.2%
2 4244
19.9%
1 3520
16.5%
3 945
 
4.4%
9 932
 
4.4%
5 914
 
4.3%
4 826
 
3.9%
6 713
 
3.4%
7 663
 
3.1%
8 658
 
3.1%
Other values (3) 163
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21118
99.2%
Dash Punctuation 157
 
0.7%
Space Separator 5
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7703
36.5%
2 4244
20.1%
1 3520
16.7%
3 945
 
4.5%
9 932
 
4.4%
5 914
 
4.3%
4 826
 
3.9%
6 713
 
3.4%
7 663
 
3.1%
8 658
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 157
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 21281
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7703
36.2%
2 4244
19.9%
1 3520
16.5%
3 945
 
4.4%
9 932
 
4.4%
5 914
 
4.3%
4 826
 
3.9%
6 713
 
3.4%
7 663
 
3.1%
8 658
 
3.1%
Other values (3) 163
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21281
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7703
36.2%
2 4244
19.9%
1 3520
16.5%
3 945
 
4.4%
9 932
 
4.4%
5 914
 
4.3%
4 826
 
3.9%
6 713
 
3.4%
7 663
 
3.1%
8 658
 
3.1%
Other values (3) 163
 
0.8%

변경계약일자
Text

MISSING 

Distinct566
Distinct (%)51.3%
Missing1697
Missing (%)60.6%
Memory size22.0 KiB
2023-12-11T09:00:24.160131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9365367
Min length4

Characters and Unicode

Total characters10960
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

Unique303 ?
Unique (%)27.5%

Sample

1st row2005-08-01
2nd row2006-05-30
3rd row2005-07-31
4th row2005-08-01
5th row2005-08-01
ValueCountFrequency (%)
2013-03-12 15
 
1.4%
2008-04-30 15
 
1.4%
2008-01-16 13
 
1.2%
2011-05-30 10
 
0.9%
2006-05-30 9
 
0.8%
2012-12-31 8
 
0.7%
2009-12-31 8
 
0.7%
2018-10-12 8
 
0.7%
2007-12-31 8
 
0.7%
2011-10-06 7
 
0.6%
Other values (556) 1002
90.8%
2023-12-11T09:00:24.689520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2902
26.5%
- 2172
19.8%
2 1875
17.1%
1 1778
16.2%
3 500
 
4.6%
8 329
 
3.0%
9 326
 
3.0%
5 318
 
2.9%
7 275
 
2.5%
6 270
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8788
80.2%
Dash Punctuation 2172
 
19.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2902
33.0%
2 1875
21.3%
1 1778
20.2%
3 500
 
5.7%
8 329
 
3.7%
9 326
 
3.7%
5 318
 
3.6%
7 275
 
3.1%
6 270
 
3.1%
4 215
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 2172
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10960
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2902
26.5%
- 2172
19.8%
2 1875
17.1%
1 1778
16.2%
3 500
 
4.6%
8 329
 
3.0%
9 326
 
3.0%
5 318
 
2.9%
7 275
 
2.5%
6 270
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10960
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2902
26.5%
- 2172
19.8%
2 1875
17.1%
1 1778
16.2%
3 500
 
4.6%
8 329
 
3.0%
9 326
 
3.0%
5 318
 
2.9%
7 275
 
2.5%
6 270
 
2.5%

신고일자
Text

MISSING 

Distinct1439
Distinct (%)55.2%
Missing195
Missing (%)7.0%
Memory size22.0 KiB
2023-12-11T09:00:25.078217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9869482
Min length6

Characters and Unicode

Total characters26016
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

Unique798 ?
Unique (%)30.6%

Sample

1st row1991-12-31
2nd row1992-12-31
3rd row1992-12-31
4th row1998-12-16
5th row1998-12-16
ValueCountFrequency (%)
2009-01-23 15
 
0.6%
2005-04-20 12
 
0.5%
2009-02-18 11
 
0.4%
2001-07-18 10
 
0.4%
2011-06-01 10
 
0.4%
2010-04-28 9
 
0.3%
2006-06-23 9
 
0.3%
2003-05-09 9
 
0.3%
2018-06-04 9
 
0.3%
2015-11-16 8
 
0.3%
Other values (1429) 2503
96.1%
2023-12-11T09:00:25.572496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7456
28.7%
- 5192
20.0%
2 4202
16.2%
1 3485
13.4%
3 942
 
3.6%
9 889
 
3.4%
5 879
 
3.4%
4 806
 
3.1%
6 726
 
2.8%
7 721
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20824
80.0%
Dash Punctuation 5192
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7456
35.8%
2 4202
20.2%
1 3485
16.7%
3 942
 
4.5%
9 889
 
4.3%
5 879
 
4.2%
4 806
 
3.9%
6 726
 
3.5%
7 721
 
3.5%
8 718
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 5192
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 26016
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7456
28.7%
- 5192
20.0%
2 4202
16.2%
1 3485
13.4%
3 942
 
3.6%
9 889
 
3.4%
5 879
 
3.4%
4 806
 
3.1%
6 726
 
2.8%
7 721
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26016
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7456
28.7%
- 5192
20.0%
2 4202
16.2%
1 3485
13.4%
3 942
 
3.6%
9 889
 
3.4%
5 879
 
3.4%
4 806
 
3.1%
6 726
 
2.8%
7 721
 
2.8%

변경신고일자
Text

MISSING 

Distinct556
Distinct (%)50.3%
Missing1695
Missing (%)60.5%
Memory size22.0 KiB
2023-12-11T09:00:25.895952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9909502
Min length5

Characters and Unicode

Total characters11040
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

Unique278 ?
Unique (%)25.2%

Sample

1st row2005-08-26
2nd row2006-07-05
3rd row2005-08-26
4th row2005-08-26
5th row2005-08-26
ValueCountFrequency (%)
2008-05-29 13
 
1.2%
2013-06-26 11
 
1.0%
2011-06-24 11
 
1.0%
2013-12-05 11
 
1.0%
2018-11-05 10
 
0.9%
2008-02-11 9
 
0.8%
2006-07-05 8
 
0.7%
2010-12-22 8
 
0.7%
2005-08-26 8
 
0.7%
2015-12-24 7
 
0.6%
Other values (546) 1009
91.3%
2023-12-11T09:00:26.503641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2932
26.6%
- 2204
20.0%
2 1907
17.3%
1 1739
15.8%
3 384
 
3.5%
9 365
 
3.3%
8 351
 
3.2%
5 337
 
3.1%
6 321
 
2.9%
7 263
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8836
80.0%
Dash Punctuation 2204
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2932
33.2%
2 1907
21.6%
1 1739
19.7%
3 384
 
4.3%
9 365
 
4.1%
8 351
 
4.0%
5 337
 
3.8%
6 321
 
3.6%
7 263
 
3.0%
4 237
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 2204
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11040
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2932
26.6%
- 2204
20.0%
2 1907
17.3%
1 1739
15.8%
3 384
 
3.5%
9 365
 
3.3%
8 351
 
3.2%
5 337
 
3.1%
6 321
 
2.9%
7 263
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11040
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2932
26.6%
- 2204
20.0%
2 1907
17.3%
1 1739
15.8%
3 384
 
3.5%
9 365
 
3.3%
8 351
 
3.2%
5 337
 
3.1%
6 321
 
2.9%
7 263
 
2.4%

하도부분금액
Real number (ℝ)

MISSING 

Distinct2527
Distinct (%)95.4%
Missing150
Missing (%)5.4%
Infinite0
Infinite (%)0.0%
Mean1.1799819 × 109
Minimum0
Maximum7.8571742 × 1010
Zeros2
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size24.7 KiB
2023-12-11T09:00:26.712406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile32494750
Q11.5828092 × 108
median3.5141 × 108
Q37.5138318 × 108
95-th percentile4.2589958 × 109
Maximum7.8571742 × 1010
Range7.8571742 × 1010
Interquartile range (IQR)5.9310226 × 108

Descriptive statistics

Standard deviation3.7910841 × 109
Coefficient of variation (CV)3.2128324
Kurtosis118.27848
Mean1.1799819 × 109
Median Absolute Deviation (MAD)2.4008343 × 108
Skewness9.1824549
Sum3.1269521 × 1012
Variance1.4372319 × 1019
MonotonicityNot monotonic
2023-12-11T09:00:26.915704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1328000000 6
 
0.2%
1654000000 6
 
0.2%
22000000 3
 
0.1%
321000000 3
 
0.1%
1092289000 3
 
0.1%
32000000 2
 
0.1%
611600000 2
 
0.1%
0 2
 
0.1%
678700000 2
 
0.1%
267000000 2
 
0.1%
Other values (2517) 2619
93.5%
(Missing) 150
 
5.4%
ValueCountFrequency (%)
0 2
0.1%
107360 1
< 0.1%
1058800 1
< 0.1%
2159520 1
< 0.1%
2251700 1
< 0.1%
3124000 1
< 0.1%
4950000 1
< 0.1%
5335000 1
< 0.1%
6490000 1
< 0.1%
7297032 1
< 0.1%
ValueCountFrequency (%)
78571741607 1
< 0.1%
47499369078 1
< 0.1%
47073440062 1
< 0.1%
46365000000 1
< 0.1%
44557242189 1
< 0.1%
42020000000 1
< 0.1%
39420370000 1
< 0.1%
33409200000 1
< 0.1%
33164834684 1
< 0.1%
32651300000 1
< 0.1%

변경하도부분금액
Real number (ℝ)

MISSING  ZEROS 

Distinct997
Distinct (%)91.0%
Missing1704
Missing (%)60.9%
Infinite0
Infinite (%)0.0%
Mean4.6132227 × 1010
Minimum0
Maximum1.84 × 1013
Zeros45
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size24.7 KiB
2023-12-11T09:00:27.126238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile19432119
Q12.001406 × 108
median4.8574548 × 108
Q31.145285 × 109
95-th percentile8.8755358 × 109
Maximum1.84 × 1013
Range1.84 × 1013
Interquartile range (IQR)9.451444 × 108

Descriptive statistics

Standard deviation8.5729641 × 1011
Coefficient of variation (CV)18.58346
Kurtosis393.53469
Mean4.6132227 × 1010
Median Absolute Deviation (MAD)3.629015 × 108
Skewness19.704772
Sum5.0560921 × 1013
Variance7.3495713 × 1023
MonotonicityNot monotonic
2023-12-11T09:00:27.288444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 45
 
1.6%
1812000000 5
 
0.2%
1455000000 5
 
0.2%
57970000 5
 
0.2%
1859000000 2
 
0.1%
434750655 2
 
0.1%
1217920645 2
 
0.1%
19911735 2
 
0.1%
631156447 2
 
0.1%
88827036 2
 
0.1%
Other values (987) 1024
36.6%
(Missing) 1704
60.9%
ValueCountFrequency (%)
0 45
1.6%
6130000 1
 
< 0.1%
7485000 1
 
< 0.1%
8657000 1
 
< 0.1%
8835000 1
 
< 0.1%
9196000 1
 
< 0.1%
11099000 1
 
< 0.1%
15180000 1
 
< 0.1%
17067000 1
 
< 0.1%
18222080 1
 
< 0.1%
ValueCountFrequency (%)
18400000000000 1
< 0.1%
17600000000000 1
< 0.1%
12600000000000 1
< 0.1%
66806718691 1
< 0.1%
52669919218 1
< 0.1%
47493369078 1
< 0.1%
47073440062 1
< 0.1%
35697825422 1
< 0.1%
33342000000 1
< 0.1%
32547700000 1
< 0.1%

하도금액
Real number (ℝ)

MISSING  SKEWED 

Distinct2335
Distinct (%)86.9%
Missing113
Missing (%)4.0%
Infinite0
Infinite (%)0.0%
Mean2.3608819 × 1010
Minimum0
Maximum4.66 × 1013
Zeros3
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size24.7 KiB
2023-12-11T09:00:27.472863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile29299300
Q11.4155 × 108
median3.09 × 108
Q36.4359075 × 108
95-th percentile4.01676 × 109
Maximum4.66 × 1013
Range4.66 × 1013
Interquartile range (IQR)5.0204075 × 108

Descriptive statistics

Standard deviation9.3967865 × 1011
Coefficient of variation (CV)39.802019
Kurtosis2268.5416
Mean2.3608819 × 1010
Median Absolute Deviation (MAD)2.10033 × 108
Skewness46.650135
Sum6.3436896 × 1013
Variance8.8299596 × 1023
MonotonicityNot monotonic
2023-12-11T09:00:27.644108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
110000000 7
 
0.2%
1169000000 6
 
0.2%
176000000 6
 
0.2%
165000000 6
 
0.2%
159500000 6
 
0.2%
594000000 5
 
0.2%
198000000 5
 
0.2%
1456000000 5
 
0.2%
572000000 5
 
0.2%
374000000 5
 
0.2%
Other values (2325) 2631
94.0%
(Missing) 113
 
4.0%
ValueCountFrequency (%)
0 3
0.1%
1158000 1
 
< 0.1%
1848330 1
 
< 0.1%
2783000 1
 
< 0.1%
3740000 1
 
< 0.1%
4801000 1
 
< 0.1%
4950000 1
 
< 0.1%
5720000 1
 
< 0.1%
6200000 1
 
< 0.1%
6809000 1
 
< 0.1%
ValueCountFrequency (%)
46600000000000 1
< 0.1%
14200000000000 1
< 0.1%
39866750000 1
< 0.1%
38649600000 1
< 0.1%
38203000000 1
< 0.1%
37143480000 1
< 0.1%
28397600000 1
< 0.1%
26796550000 1
< 0.1%
26493500000 1
< 0.1%
26172300000 1
< 0.1%

변경하도금액
Real number (ℝ)

MISSING  SKEWED 

Distinct996
Distinct (%)91.2%
Missing1708
Missing (%)61.0%
Infinite0
Infinite (%)0.0%
Mean6.4852719 × 1010
Minimum0
Maximum3.02 × 1013
Zeros20
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size24.7 KiB
2023-12-11T09:00:27.796391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile34409650
Q11.925 × 108
median4.46292 × 108
Q31.0028535 × 109
95-th percentile7.4588476 × 109
Maximum3.02 × 1013
Range3.02 × 1013
Interquartile range (IQR)8.103535 × 108

Descriptive statistics

Standard deviation1.1427066 × 1012
Coefficient of variation (CV)17.620027
Kurtosis493.32807
Mean6.4852719 × 1010
Median Absolute Deviation (MAD)3.18859 × 108
Skewness21.071408
Sum7.0819169 × 1013
Variance1.3057784 × 1024
MonotonicityNot monotonic
2023-12-11T09:00:27.977101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 20
 
0.7%
1281000000 5
 
0.2%
1594000000 5
 
0.2%
572000000 3
 
0.1%
192500000 3
 
0.1%
37400000 3
 
0.1%
1184810000 2
 
0.1%
320760000 2
 
0.1%
2043800000 2
 
0.1%
956600000 2
 
0.1%
Other values (986) 1045
37.3%
(Missing) 1708
61.0%
ValueCountFrequency (%)
0 20
0.7%
5517000 1
 
< 0.1%
6683000 1
 
< 0.1%
7328000 1
 
< 0.1%
8195000 1
 
< 0.1%
8800000 1
 
< 0.1%
9988000 1
 
< 0.1%
13090000 1
 
< 0.1%
14000000 1
 
< 0.1%
15000000 1
 
< 0.1%
ValueCountFrequency (%)
30200000000000 1
< 0.1%
14300000000000 2
0.1%
10400000000000 1
< 0.1%
39866750000 1
< 0.1%
38649600000 1
< 0.1%
30081920000 1
< 0.1%
27234900000 1
< 0.1%
26753100000 1
< 0.1%
26177800000 1
< 0.1%
26159100000 1
< 0.1%

하도비율
Real number (ℝ)

MISSING 

Distinct1211
Distinct (%)45.2%
Missing122
Missing (%)4.4%
Infinite0
Infinite (%)0.0%
Mean88.539414
Minimum0
Maximum304
Zeros8
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size24.7 KiB
2023-12-11T09:00:28.154864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile80.8725
Q183.36
median87.985
Q391.45
95-th percentile100.0405
Maximum304
Range304
Interquartile range (IQR)8.09

Descriptive statistics

Standard deviation13.843656
Coefficient of variation (CV)0.15635586
Kurtosis71.11515
Mean88.539414
Median Absolute Deviation (MAD)4.05
Skewness4.2098528
Sum237108.55
Variance191.64682
MonotonicityNot monotonic
2023-12-11T09:00:28.344976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
90.0 86
 
3.1%
85.0 39
 
1.4%
100.0 39
 
1.4%
83.0 38
 
1.4%
88.0 29
 
1.0%
95.0 28
 
1.0%
82.0 23
 
0.8%
89.0 20
 
0.7%
92.0 17
 
0.6%
84.99 16
 
0.6%
Other values (1201) 2343
83.7%
(Missing) 122
 
4.4%
ValueCountFrequency (%)
0.0 8
0.3%
8.82 1
 
< 0.1%
9.11 1
 
< 0.1%
10.22 1
 
< 0.1%
17.92 1
 
< 0.1%
36.13 1
 
< 0.1%
40.6 1
 
< 0.1%
41.85 1
 
< 0.1%
44.0 2
 
0.1%
45.07 1
 
< 0.1%
ValueCountFrequency (%)
304.0 1
< 0.1%
298.26 1
< 0.1%
284.81 1
< 0.1%
218.01 1
< 0.1%
188.88 1
< 0.1%
186.45 1
< 0.1%
177.47 1
< 0.1%
175.06 1
< 0.1%
174.91 1
< 0.1%
171.47 1
< 0.1%

공사시작일
Text

MISSING 

Distinct1483
Distinct (%)55.7%
Missing138
Missing (%)4.9%
Memory size22.0 KiB
2023-12-11T09:00:28.674566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9943651
Min length6

Characters and Unicode

Total characters26605
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

Unique840 ?
Unique (%)31.6%

Sample

1st row1998-11-17
2nd row1998-11-17
3rd row1999-01-29
4th row1998-12-11
5th row1998-12-05
ValueCountFrequency (%)
2009-01-15 17
 
0.6%
2011-05-03 10
 
0.4%
2009-02-05 10
 
0.4%
2000-06-26 8
 
0.3%
2011-03-07 8
 
0.3%
2015-11-18 8
 
0.3%
2004-05-10 8
 
0.3%
2011-03-21 8
 
0.3%
2010-04-01 7
 
0.3%
2014-08-28 7
 
0.3%
Other values (1473) 2571
96.6%
2023-12-11T09:00:29.158393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7865
29.6%
- 5312
20.0%
2 4200
15.8%
1 3502
13.2%
5 978
 
3.7%
3 912
 
3.4%
9 908
 
3.4%
4 818
 
3.1%
6 751
 
2.8%
7 698
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21293
80.0%
Dash Punctuation 5312
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7865
36.9%
2 4200
19.7%
1 3502
16.4%
5 978
 
4.6%
3 912
 
4.3%
9 908
 
4.3%
4 818
 
3.8%
6 751
 
3.5%
7 698
 
3.3%
8 661
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 5312
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 26605
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7865
29.6%
- 5312
20.0%
2 4200
15.8%
1 3502
13.2%
5 978
 
3.7%
3 912
 
3.4%
9 908
 
3.4%
4 818
 
3.1%
6 751
 
2.8%
7 698
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26605
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7865
29.6%
- 5312
20.0%
2 4200
15.8%
1 3502
13.2%
5 978
 
3.7%
3 912
 
3.4%
9 908
 
3.4%
4 818
 
3.1%
6 751
 
2.8%
7 698
 
2.6%

공사종료일
Text

MISSING 

Distinct1119
Distinct (%)42.0%
Missing136
Missing (%)4.9%
Memory size22.0 KiB
2023-12-11T09:00:29.570259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9928679
Min length1

Characters and Unicode

Total characters26621
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

Unique535 ?
Unique (%)20.1%

Sample

1st row1999-02-25
2nd row1999-02-25
3rd row1999-05-30
4th row1999-10-02
5th row1999-10-01
ValueCountFrequency (%)
2011-12-31 36
 
1.4%
2009-12-31 33
 
1.2%
2010-11-30 31
 
1.2%
2008-02-28 20
 
0.8%
2004-03-04 19
 
0.7%
2006-12-31 18
 
0.7%
2008-12-31 16
 
0.6%
2013-12-31 15
 
0.6%
2000-12-31 14
 
0.5%
2008-03-31 13
 
0.5%
Other values (1109) 2449
91.9%
2023-12-11T09:00:30.042619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7408
27.8%
- 5320
20.0%
2 4474
16.8%
1 3925
14.7%
3 1578
 
5.9%
9 826
 
3.1%
4 722
 
2.7%
8 613
 
2.3%
5 608
 
2.3%
6 600
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21301
80.0%
Dash Punctuation 5320
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7408
34.8%
2 4474
21.0%
1 3925
18.4%
3 1578
 
7.4%
9 826
 
3.9%
4 722
 
3.4%
8 613
 
2.9%
5 608
 
2.9%
6 600
 
2.8%
7 547
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 5320
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 26621
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7408
27.8%
- 5320
20.0%
2 4474
16.8%
1 3925
14.7%
3 1578
 
5.9%
9 826
 
3.1%
4 722
 
2.7%
8 613
 
2.3%
5 608
 
2.3%
6 600
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26621
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7408
27.8%
- 5320
20.0%
2 4474
16.8%
1 3925
14.7%
3 1578
 
5.9%
9 826
 
3.1%
4 722
 
2.7%
8 613
 
2.3%
5 608
 
2.3%
6 600
 
2.3%

변경공사시작일
Text

MISSING 

Distinct548
Distinct (%)61.1%
Missing1903
Missing (%)68.0%
Memory size22.0 KiB
2023-12-11T09:00:30.358262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9710145
Min length1

Characters and Unicode

Total characters8944
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

Unique334 ?
Unique (%)37.2%

Sample

1st row2000-06-18
2nd row2003-04-03
3rd row2000-07-04
4th row1999-11-30
5th row2000-07-04
ValueCountFrequency (%)
2009-01-15 12
 
1.3%
2004-05-06 7
 
0.8%
2004-05-10 6
 
0.7%
2015-03-05 6
 
0.7%
2005-11-01 6
 
0.7%
2018-05-16 6
 
0.7%
2011-03-07 6
 
0.7%
2005-04-28 6
 
0.7%
2010-04-05 5
 
0.6%
2014-08-28 5
 
0.6%
Other values (538) 832
92.8%
2023-12-11T09:00:30.771810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2653
29.7%
- 1780
19.9%
2 1431
16.0%
1 1196
13.4%
5 337
 
3.8%
3 324
 
3.6%
4 307
 
3.4%
8 248
 
2.8%
7 238
 
2.7%
6 230
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7164
80.1%
Dash Punctuation 1780
 
19.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2653
37.0%
2 1431
20.0%
1 1196
16.7%
5 337
 
4.7%
3 324
 
4.5%
4 307
 
4.3%
8 248
 
3.5%
7 238
 
3.3%
6 230
 
3.2%
9 200
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 1780
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8944
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2653
29.7%
- 1780
19.9%
2 1431
16.0%
1 1196
13.4%
5 337
 
3.8%
3 324
 
3.6%
4 307
 
3.4%
8 248
 
2.8%
7 238
 
2.7%
6 230
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8944
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2653
29.7%
- 1780
19.9%
2 1431
16.0%
1 1196
13.4%
5 337
 
3.8%
3 324
 
3.6%
4 307
 
3.4%
8 248
 
2.8%
7 238
 
2.7%
6 230
 
2.6%

변경공사종료일
Text

MISSING 

Distinct414
Distinct (%)44.5%
Missing1870
Missing (%)66.8%
Memory size22.0 KiB
2023-12-11T09:00:31.108767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9956989
Min length8

Characters and Unicode

Total characters9296
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

Unique213 ?
Unique (%)22.9%

Sample

1st row2005-12-31
2nd row2006-12-31
3rd row2005-07-31
4th row2005-12-31
5th row2006-03-04
ValueCountFrequency (%)
2013-12-31 33
 
3.5%
2014-12-31 20
 
2.2%
2008-05-31 19
 
2.0%
2010-11-30 19
 
2.0%
2011-12-31 18
 
1.9%
2009-12-31 14
 
1.5%
2011-07-20 10
 
1.1%
2006-12-31 10
 
1.1%
2013-07-09 9
 
1.0%
2016-12-31 9
 
1.0%
Other values (404) 769
82.7%
2023-12-11T09:00:31.600437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2301
24.8%
- 1856
20.0%
1 1629
17.5%
2 1597
17.2%
3 609
 
6.6%
5 262
 
2.8%
8 259
 
2.8%
4 215
 
2.3%
9 206
 
2.2%
7 181
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7440
80.0%
Dash Punctuation 1856
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2301
30.9%
1 1629
21.9%
2 1597
21.5%
3 609
 
8.2%
5 262
 
3.5%
8 259
 
3.5%
4 215
 
2.9%
9 206
 
2.8%
7 181
 
2.4%
6 181
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 1856
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9296
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2301
24.8%
- 1856
20.0%
1 1629
17.5%
2 1597
17.2%
3 609
 
6.6%
5 262
 
2.8%
8 259
 
2.8%
4 215
 
2.3%
9 206
 
2.2%
7 181
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9296
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2301
24.8%
- 1856
20.0%
1 1629
17.5%
2 1597
17.2%
3 609
 
6.6%
5 262
 
2.8%
8 259
 
2.8%
4 215
 
2.3%
9 206
 
2.2%
7 181
 
1.9%

지급보증서
Text

Distinct131
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size22.0 KiB
2023-12-11T09:00:32.111420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length1
Mean length2.2914286
Min length1

Characters and Unicode

Total characters6416
Distinct characters107
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67 ?
Unique (%)2.4%

Sample

1st row-
2nd row-
3rd row-
4th row첨부(공제조합)
5th row첨부(공제조합)
ValueCountFrequency (%)
1769
62.0%
제출 248
 
8.7%
미첨부 85
 
3.0%
신용등급a 68
 
2.4%
계약보증서 62
 
2.2%
a등급 57
 
2.0%
지급보증서 57
 
2.0%
전문건설공제조합 40
 
1.4%
면제 39
 
1.4%
첨부 24
 
0.8%
Other values (128) 402
 
14.1%
2023-12-11T09:00:32.471068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1770
27.6%
제 399
 
6.2%
급 343
 
5.3%
출 269
 
4.2%
보 231
 
3.6%
증 230
 
3.6%
A 229
 
3.6%
서 199
 
3.1%
등 184
 
2.9%
신 153
 
2.4%
Other values (97) 2409
37.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3888
60.6%
Dash Punctuation 1770
27.6%
Decimal Number 278
 
4.3%
Uppercase Letter 234
 
3.6%
Open Punctuation 96
 
1.5%
Close Punctuation 83
 
1.3%
Space Separator 51
 
0.8%
Other Punctuation 9
 
0.1%
Math Symbol 5
 
0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 399
 
10.3%
급 343
 
8.8%
출 269
 
6.9%
보 231
 
5.9%
증 230
 
5.9%
서 199
 
5.1%
등 184
 
4.7%
신 153
 
3.9%
용 152
 
3.9%
부 138
 
3.5%
Other values (79) 1590
40.9%
Decimal Number
ValueCountFrequency (%)
0 110
39.6%
1 59
21.2%
2 53
19.1%
5 23
 
8.3%
3 14
 
5.0%
4 7
 
2.5%
8 4
 
1.4%
7 4
 
1.4%
6 4
 
1.4%
Uppercase Letter
ValueCountFrequency (%)
A 229
97.9%
E 5
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 1770
100.0%
Open Punctuation
ValueCountFrequency (%)
( 96
100.0%
Close Punctuation
ValueCountFrequency (%)
) 83
100.0%
Space Separator
ValueCountFrequency (%)
51
100.0%
Other Punctuation
ValueCountFrequency (%)
. 9
100.0%
Math Symbol
ValueCountFrequency (%)
+ 5
100.0%
Lowercase Letter
ValueCountFrequency (%)
a 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3888
60.6%
Common 2292
35.7%
Latin 236
 
3.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 399
 
10.3%
급 343
 
8.8%
출 269
 
6.9%
보 231
 
5.9%
증 230
 
5.9%
서 199
 
5.1%
등 184
 
4.7%
신 153
 
3.9%
용 152
 
3.9%
부 138
 
3.5%
Other values (79) 1590
40.9%
Common
ValueCountFrequency (%)
- 1770
77.2%
0 110
 
4.8%
( 96
 
4.2%
) 83
 
3.6%
1 59
 
2.6%
2 53
 
2.3%
51
 
2.2%
5 23
 
1.0%
3 14
 
0.6%
. 9
 
0.4%
Other values (5) 24
 
1.0%
Latin
ValueCountFrequency (%)
A 229
97.0%
E 5
 
2.1%
a 2
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3888
60.6%
ASCII 2528
39.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1770
70.0%
A 229
 
9.1%
0 110
 
4.4%
( 96
 
3.8%
) 83
 
3.3%
1 59
 
2.3%
2 53
 
2.1%
51
 
2.0%
5 23
 
0.9%
3 14
 
0.6%
Other values (8) 40
 
1.6%
Hangul
ValueCountFrequency (%)
제 399
 
10.3%
급 343
 
8.8%
출 269
 
6.9%
보 231
 
5.9%
증 230
 
5.9%
서 199
 
5.1%
등 184
 
4.7%
신 153
 
3.9%
용 152
 
3.9%
부 138
 
3.5%
Other values (79) 1590
40.9%

직불합의서
Text

Distinct89
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size22.0 KiB
2023-12-11T09:00:32.813664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length16
Mean length1.9371429
Min length1

Characters and Unicode

Total characters5424
Distinct characters98
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

Unique50 ?
Unique (%)1.8%

Sample

1st row-
2nd row-
3rd row-
4th row-
5th row-
ValueCountFrequency (%)
1157
40.7%
제출 1024
36.0%
합의 143
 
5.0%
첨부 124
 
4.4%
직불합의 87
 
3.1%
직불 77
 
2.7%
쌍방합의 16
 
0.6%
직불동의 15
 
0.5%
합의서 14
 
0.5%
부 12
 
0.4%
Other values (87) 175
 
6.2%
2023-12-11T09:00:33.322370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1158
21.3%
제 1048
19.3%
출 1042
19.2%
의 335
 
6.2%
합 302
 
5.6%
불 228
 
4.2%
직 223
 
4.1%
부 144
 
2.7%
첨 131
 
2.4%
0 83
 
1.5%
Other values (88) 730
13.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3842
70.8%
Dash Punctuation 1158
 
21.3%
Decimal Number 255
 
4.7%
Close Punctuation 46
 
0.8%
Open Punctuation 46
 
0.8%
Space Separator 44
 
0.8%
Other Punctuation 26
 
0.5%
Uppercase Letter 6
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 1048
27.3%
출 1042
27.1%
의 335
 
8.7%
합 302
 
7.9%
불 228
 
5.9%
직 223
 
5.8%
부 144
 
3.7%
첨 131
 
3.4%
서 34
 
0.9%
방 34
 
0.9%
Other values (71) 321
 
8.4%
Decimal Number
ValueCountFrequency (%)
0 83
32.5%
2 60
23.5%
1 53
20.8%
5 16
 
6.3%
3 11
 
4.3%
4 9
 
3.5%
9 9
 
3.5%
7 6
 
2.4%
6 5
 
2.0%
8 3
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 1158
100.0%
Close Punctuation
ValueCountFrequency (%)
) 46
100.0%
Open Punctuation
ValueCountFrequency (%)
( 46
100.0%
Space Separator
ValueCountFrequency (%)
44
100.0%
Other Punctuation
ValueCountFrequency (%)
. 26
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 6
100.0%
Math Symbol
ValueCountFrequency (%)
> 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3842
70.8%
Common 1576
29.1%
Latin 6
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 1048
27.3%
출 1042
27.1%
의 335
 
8.7%
합 302
 
7.9%
불 228
 
5.9%
직 223
 
5.8%
부 144
 
3.7%
첨 131
 
3.4%
서 34
 
0.9%
방 34
 
0.9%
Other values (71) 321
 
8.4%
Common
ValueCountFrequency (%)
- 1158
73.5%
0 83
 
5.3%
2 60
 
3.8%
1 53
 
3.4%
) 46
 
2.9%
( 46
 
2.9%
44
 
2.8%
. 26
 
1.6%
5 16
 
1.0%
3 11
 
0.7%
Other values (6) 33
 
2.1%
Latin
ValueCountFrequency (%)
A 6
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3842
70.8%
ASCII 1582
29.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1158
73.2%
0 83
 
5.2%
2 60
 
3.8%
1 53
 
3.4%
) 46
 
2.9%
( 46
 
2.9%
44
 
2.8%
. 26
 
1.6%
5 16
 
1.0%
3 11
 
0.7%
Other values (7) 39
 
2.5%
Hangul
ValueCountFrequency (%)
제 1048
27.3%
출 1042
27.1%
의 335
 
8.7%
합 302
 
7.9%
불 228
 
5.9%
직 223
 
5.8%
부 144
 
3.7%
첨 131
 
3.4%
서 34
 
0.9%
방 34
 
0.9%
Other values (71) 321
 
8.4%

지급방법
Categorical

IMBALANCE 

Distinct43
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size22.0 KiB
직불
1420 
-
657 
대지급
337 
직접지급
146 
원청지급
 
47
Other values (38)
193 

Length

Max length16
Median length2
Mean length2.2164286
Min length1

Unique

Unique20 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
직불 1420
50.7%
- 657
23.5%
대지급 337
 
12.0%
직접지급 146
 
5.2%
원청지급 47
 
1.7%
지급보증 41
 
1.5%
지급보증서 35
 
1.2%
하도급직불 26
 
0.9%
직불합의 19
 
0.7%
원청 11
 
0.4%
Other values (33) 61
 
2.2%

Length

2023-12-11T09:00:33.498211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
직불 1420
50.4%
657
23.3%
대지급 337
 
12.0%
직접지급 146
 
5.2%
원청지급 47
 
1.7%
지급보증 41
 
1.5%
지급보증서 36
 
1.3%
하도급직불 26
 
0.9%
직불합의 19
 
0.7%
원청 11
 
0.4%
Other values (43) 77
 
2.7%

Sample

공사년도공사구분공사번호부서코드순번업체명공종업태종목계약일자변경계약일자신고일자변경신고일자하도부분금액변경하도부분금액하도금액변경하도금액하도비율공사시작일공사종료일변경공사시작일변경공사종료일지급보증서직불합의서지급방법
01990공사8811(주)태광산업-철.콘철근콘크리트19911106<NA>1991-12-31<NA>75460000<NA><NA><NA><NA><NA><NA><NA><NA>---
11992공사811흥한산업(주)-철.콘철근콘크리트19920415<NA>1992-12-31<NA>165000000<NA><NA><NA><NA><NA><NA><NA><NA>---
21992공사1011영남건설-구조물공구조물19920401<NA>1992-12-31<NA>100900000<NA><NA><NA><NA><NA><NA><NA><NA>---
31997공사8512효승건설(주)-토공토공사19980116<NA>1998-12-16<NA>343812659<NA>316170000<NA>92.01998-11-171999-02-25<NA><NA>첨부(공제조합)--
41997공사8511효승건설(주)-철.콘철근콘크리트19980116<NA>1998-12-16<NA>254701246<NA>234310000<NA>92.01998-11-171999-02-25<NA><NA>첨부(공제조합)--
51998공사111(주)대운건설-토공토공사19990129<NA>1999-02-01<NA><NA><NA>47872000<NA><NA>1999-01-291999-05-30<NA><NA>합의 직불-직불
61998공사1211(주)정후토건-철.콘구조물공사19981211<NA>1998-12-24<NA>115896000<NA>104500000<NA>90.21998-12-111999-10-02<NA><NA>첨부(공제조합)--
71998공사1212(주)신아지오 컨설턴트-토목계측토목계측관리-<NA>1998-12-24<NA>148279000<NA>131923000<NA>89.61998-12-051999-10-01<NA><NA>첨부(공제조합)--
81998공사1811조일건설(주)--구조물공사19980509<NA>1998-11-03<NA>284933000<NA>172744000<NA>60.61998-05-111998-12-31<NA><NA>A등급--
91998공사1812국제기건(주)--말뚝공사19980923<NA><NA><NA>944185000<NA>415393000<NA>44.01998-09-241999-04-30<NA><NA>A등급--
공사년도공사구분공사번호부서코드순번업체명공종업태종목계약일자변경계약일자신고일자변경신고일자하도부분금액변경하도부분금액하도금액변경하도금액하도비율공사시작일공사종료일변경공사시작일변경공사종료일지급보증서직불합의서지급방법
27902019공사9311포엠(주)시설물유지관리업건설건설20190708<NA>2019-07-09<NA>231380000<NA>189735000<NA>82.02019-07-082019-11-04<NA><NA>-제출직불
27912019공사9211(주)성후해양수중건설건설20190709<NA>2019-07-09<NA>352480000<NA>313700000<NA>89.02019-07-092019-11-04<NA><NA>-제출직불
27922017공사13212석진건설(주)석공사--201805162018-10-122018-06-042018-11-05533500061300004801000551700090.02018-05-162018-10-192018-05-162019-11-28계약보증서합의직불
27932017공사13213송평건설(주)철근콘크리트공사--201805162018-10-122018-06-042018-11-05185081200026449750001628640000238039900090.02017-12-182018-10-192017-12-182019-11-28계약보증서합의직불
27942017공사13214송평건설(주)토공사--201805162018-10-122018-06-042018-11-05161425000018922350001419905000170298000090.02017-12-182018-10-192017-12-182019-11-28계약보증서합의직불
27952017공사13211협진산업(주)금속공사--201805162018-10-122018-06-042018-11-0514620500015137400013158400013623500090.02018-05-162018-10-192018-05-162019-11-28계약보증서합의직불
27962017공사7212미산건설(주)토공및구조물공(2공구)--20181218<NA>2018-12-19<NA>692948300<NA>601957400<NA>86.872017-04-052018-12-31<NA><NA>-합의직불
27972018공사7311미산건설(주)토공및구조물 1공구--201804272018-12-182018-05-142018-12-1921875480047835810019365610044653290093.352018-04-272018-12-31<NA><NA>계약보증서합의직불
27982018공사7312미산건설(주)토공 및 구조물공(2공구)--201804272018-12-182018-05-142018-12-192151138001272308400182604400106910320084.032018-04-272018-12-31<NA><NA>계약보증서합의직불
27992017공사7211미산건설(주)토공및구조물공(1공구)--20181218<NA>2018-12-19<NA>1628976800<NA>1404527300<NA>86.222017-04-052018-12-31<NA><NA>-합의직불