Overview

Dataset statistics

Number of variables17
Number of observations10000
Missing cells5296
Missing cells (%)3.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 MiB
Average record size in memory150.0 B

Variable types

Numeric6
Text4
Categorical4
DateTime3

Dataset

Description인검증 환경신기술 활용 실적 목록 상세정보(2020-10-26 기준, 실적제출년도, 발주처 구분, 발주형태, 공사명, 공사금액 등)
Author한국환경산업기술원
URLhttps://www.data.go.kr/data/15071530/fileData.do

Alerts

활용실적상세 순번 is highly overall correlated with 활용실적 순번 and 2 other fieldsHigh correlation
활용실적 순번 is highly overall correlated with 활용실적상세 순번 and 2 other fieldsHigh correlation
신청서ID is highly overall correlated with 활용실적상세 순번 and 2 other fieldsHigh correlation
실적제출년도 is highly overall correlated with 활용실적상세 순번 and 2 other fieldsHigh correlation
공사금액 is highly overall correlated with 신기술공사계약금액High correlation
신기술공사계약금액 is highly overall correlated with 공사금액High correlation
공사명 has 245 (2.5%) missing valuesMissing
용량 has 727 (7.3%) missing valuesMissing
원도급자 has 1803 (18.0%) missing valuesMissing
계약일자 has 909 (9.1%) missing valuesMissing
착공일자 has 573 (5.7%) missing valuesMissing
준공일자 has 526 (5.3%) missing valuesMissing
공사금액 has 448 (4.5%) missing valuesMissing
공사금액 is highly skewed (γ1 = 40.91019214)Skewed
신기술공사계약금액 is highly skewed (γ1 = 26.51125824)Skewed
활용실적상세 순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:00:47.511699
Analysis finished2023-12-12 15:00:56.415758
Duration8.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

활용실적상세 순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19123.849
Minimum22
Maximum47806
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T00:00:56.502050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22
5-th percentile1737.5
Q18850.5
median17532.5
Q326455.25
95-th percentile44065.05
Maximum47806
Range47784
Interquartile range (IQR)17604.75

Descriptive statistics

Standard deviation12683.941
Coefficient of variation (CV)0.66325253
Kurtosis-0.62043672
Mean19123.849
Median Absolute Deviation (MAD)8754
Skewness0.53013283
Sum1.9123848 × 108
Variance1.6088236 × 108
MonotonicityNot monotonic
2023-12-13T00:00:56.656759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4903 1
 
< 0.1%
24973 1
 
< 0.1%
33700 1
 
< 0.1%
12313 1
 
< 0.1%
19428 1
 
< 0.1%
25439 1
 
< 0.1%
35029 1
 
< 0.1%
28726 1
 
< 0.1%
15020 1
 
< 0.1%
37432 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
22 1
< 0.1%
23 1
< 0.1%
26 1
< 0.1%
34 1
< 0.1%
40 1
< 0.1%
41 1
< 0.1%
43 1
< 0.1%
45 1
< 0.1%
53 1
< 0.1%
56 1
< 0.1%
ValueCountFrequency (%)
47806 1
< 0.1%
47796 1
< 0.1%
47794 1
< 0.1%
47793 1
< 0.1%
47792 1
< 0.1%
47791 1
< 0.1%
47790 1
< 0.1%
47789 1
< 0.1%
47786 1
< 0.1%
47784 1
< 0.1%

활용실적 순번
Real number (ℝ)

HIGH CORRELATION 

Distinct1416
Distinct (%)14.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2022.7822
Minimum5
Maximum3994
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T00:00:56.794584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile265
Q1808
median1932
Q33280.5
95-th percentile3851
Maximum3994
Range3989
Interquartile range (IQR)2472.5

Descriptive statistics

Standard deviation1249.6745
Coefficient of variation (CV)0.61779982
Kurtosis-1.3855337
Mean2022.7822
Median Absolute Deviation (MAD)1273
Skewness0.018134254
Sum20227822
Variance1561686.3
MonotonicityNot monotonic
2023-12-13T00:00:56.975550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1158 368
 
3.7%
355 185
 
1.8%
308 110
 
1.1%
1054 94
 
0.9%
465 91
 
0.9%
2721 88
 
0.9%
1976 86
 
0.9%
1647 85
 
0.9%
1811 83
 
0.8%
436 80
 
0.8%
Other values (1406) 8730
87.3%
ValueCountFrequency (%)
5 2
 
< 0.1%
6 3
< 0.1%
9 1
 
< 0.1%
10 7
0.1%
12 1
 
< 0.1%
13 4
< 0.1%
14 1
 
< 0.1%
15 1
 
< 0.1%
17 1
 
< 0.1%
18 4
< 0.1%
ValueCountFrequency (%)
3994 2
 
< 0.1%
3993 6
 
0.1%
3992 3
 
< 0.1%
3988 3
 
< 0.1%
3986 11
0.1%
3985 4
 
< 0.1%
3984 9
0.1%
3983 13
0.1%
3982 15
0.1%
3980 1
 
< 0.1%

신청서ID
Real number (ℝ)

HIGH CORRELATION 

Distinct574
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5088.1612
Minimum7
Maximum15703
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T00:00:57.153167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile166
Q1591
median2396
Q39181
95-th percentile15328
Maximum15703
Range15696
Interquartile range (IQR)8590

Descriptive statistics

Standard deviation5252.9396
Coefficient of variation (CV)1.0323847
Kurtosis-0.88122756
Mean5088.1612
Median Absolute Deviation (MAD)2168
Skewness0.77983366
Sum50881612
Variance27593374
MonotonicityNot monotonic
2023-12-13T00:00:57.308127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
870 482
 
4.8%
199 396
 
4.0%
2396 222
 
2.2%
582 192
 
1.9%
321 190
 
1.9%
3719 174
 
1.7%
938 155
 
1.6%
1906 150
 
1.5%
6122 149
 
1.5%
15328 139
 
1.4%
Other values (564) 7751
77.5%
ValueCountFrequency (%)
7 1
 
< 0.1%
9 7
 
0.1%
11 1
 
< 0.1%
12 3
 
< 0.1%
13 8
 
0.1%
15 7
 
0.1%
18 3
 
< 0.1%
21 24
0.2%
24 1
 
< 0.1%
27 3
 
< 0.1%
ValueCountFrequency (%)
15703 2
 
< 0.1%
15625 2
 
< 0.1%
15622 9
0.1%
15621 1
 
< 0.1%
15598 18
0.2%
15596 1
 
< 0.1%
15595 1
 
< 0.1%
15587 9
0.1%
15586 1
 
< 0.1%
15570 4
 
< 0.1%

실적제출년도
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2012.3611
Minimum1999
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T00:00:57.438787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1999
5-th percentile2006
Q12010
median2012
Q32016
95-th percentile2019
Maximum2020
Range21
Interquartile range (IQR)6

Descriptive statistics

Standard deviation4.1840002
Coefficient of variation (CV)0.0020791498
Kurtosis-0.51521805
Mean2012.3611
Median Absolute Deviation (MAD)3
Skewness-0.15138213
Sum20123611
Variance17.505857
MonotonicityNot monotonic
2023-12-13T00:00:57.561623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
2010 1087
10.9%
2012 981
9.8%
2011 882
 
8.8%
2017 811
 
8.1%
2013 770
 
7.7%
2014 680
 
6.8%
2015 624
 
6.2%
2016 585
 
5.9%
2018 580
 
5.8%
2007 555
 
5.5%
Other values (12) 2445
24.4%
ValueCountFrequency (%)
1999 1
 
< 0.1%
2000 14
 
0.1%
2001 31
 
0.3%
2002 71
 
0.7%
2003 82
 
0.8%
2004 97
 
1.0%
2005 155
 
1.6%
2006 388
3.9%
2007 555
5.5%
2008 433
4.3%
ValueCountFrequency (%)
2020 435
4.3%
2019 219
 
2.2%
2018 580
5.8%
2017 811
8.1%
2016 585
5.9%
2015 624
6.2%
2014 680
6.8%
2013 770
7.7%
2012 981
9.8%
2011 882
8.8%

발주처
Text

Distinct4190
Distinct (%)42.0%
Missing20
Missing (%)0.2%
Memory size156.2 KiB
2023-12-13T00:00:57.866240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length40
Mean length7.6366733
Min length1

Characters and Unicode

Total characters76214
Distinct characters541
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2866 ?
Unique (%)28.7%

Sample

1st row인천광역시 옹진군
2nd row서브원
3rd row담양군청
4th row청주시 문화예술체육회관
5th row함양군청
ValueCountFrequency (%)
경상남도 343
 
2.5%
담양군청 312
 
2.3%
경기도 275
 
2.0%
서울특별시 254
 
1.9%
상하수도사업소 245
 
1.8%
한국농어촌공사 183
 
1.3%
인천광역시 134
 
1.0%
부산광역시 122
 
0.9%
한국토지주택공사 114
 
0.8%
충청남도 107
 
0.8%
Other values (3673) 11563
84.7%
2023-12-13T00:00:58.366257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3749
 
4.9%
시 3464
 
4.5%
청 3059
 
4.0%
사 2761
 
3.6%
도 2707
 
3.6%
군 2074
 
2.7%
주 2035
 
2.7%
경 1629
 
2.1%
국 1479
 
1.9%
업 1408
 
1.8%
Other values (531) 51849
68.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68024
89.3%
Space Separator 3749
 
4.9%
Uppercase Letter 830
 
1.1%
Close Punctuation 756
 
1.0%
Open Punctuation 751
 
1.0%
Lowercase Letter 681
 
0.9%
Decimal Number 663
 
0.9%
Other Symbol 644
 
0.8%
Other Punctuation 102
 
0.1%
Dash Punctuation 13
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 3464
 
5.1%
청 3059
 
4.5%
사 2761
 
4.1%
도 2707
 
4.0%
군 2074
 
3.0%
주 2035
 
3.0%
경 1629
 
2.4%
국 1479
 
2.2%
업 1408
 
2.1%
소 1379
 
2.0%
Other values (459) 46029
67.7%
Uppercase Letter
ValueCountFrequency (%)
N 87
10.5%
A 78
9.4%
G 75
9.0%
P 69
 
8.3%
L 64
 
7.7%
S 60
 
7.2%
C 60
 
7.2%
H 59
 
7.1%
T 54
 
6.5%
E 37
 
4.5%
Other values (16) 187
22.5%
Lowercase Letter
ValueCountFrequency (%)
n 105
15.4%
a 78
11.5%
o 63
9.3%
i 59
8.7%
h 55
8.1%
e 46
 
6.8%
r 42
 
6.2%
g 37
 
5.4%
t 37
 
5.4%
s 30
 
4.4%
Other values (15) 129
18.9%
Decimal Number
ValueCountFrequency (%)
1 124
18.7%
2 92
13.9%
7 84
12.7%
0 66
10.0%
5 66
10.0%
3 66
10.0%
9 60
9.0%
6 59
8.9%
8 42
 
6.3%
4 4
 
0.6%
Other Punctuation
ValueCountFrequency (%)
. 59
57.8%
, 29
28.4%
& 7
 
6.9%
/ 5
 
4.9%
· 2
 
2.0%
Space Separator
ValueCountFrequency (%)
3749
100.0%
Close Punctuation
ValueCountFrequency (%)
) 756
100.0%
Open Punctuation
ValueCountFrequency (%)
( 751
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 644
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 68668
90.1%
Common 6035
 
7.9%
Latin 1511
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 3464
 
5.0%
청 3059
 
4.5%
사 2761
 
4.0%
도 2707
 
3.9%
군 2074
 
3.0%
주 2035
 
3.0%
경 1629
 
2.4%
국 1479
 
2.2%
업 1408
 
2.1%
소 1379
 
2.0%
Other values (460) 46673
68.0%
Latin
ValueCountFrequency (%)
n 105
 
6.9%
N 87
 
5.8%
A 78
 
5.2%
a 78
 
5.2%
G 75
 
5.0%
P 69
 
4.6%
L 64
 
4.2%
o 63
 
4.2%
S 60
 
4.0%
C 60
 
4.0%
Other values (41) 772
51.1%
Common
ValueCountFrequency (%)
3749
62.1%
) 756
 
12.5%
( 751
 
12.4%
1 124
 
2.1%
2 92
 
1.5%
7 84
 
1.4%
0 66
 
1.1%
5 66
 
1.1%
3 66
 
1.1%
9 60
 
1.0%
Other values (10) 221
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68024
89.3%
ASCII 7544
 
9.9%
None 646
 
0.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3749
49.7%
) 756
 
10.0%
( 751
 
10.0%
1 124
 
1.6%
n 105
 
1.4%
2 92
 
1.2%
N 87
 
1.2%
7 84
 
1.1%
A 78
 
1.0%
a 78
 
1.0%
Other values (60) 1640
21.7%
Hangul
ValueCountFrequency (%)
시 3464
 
5.1%
청 3059
 
4.5%
사 2761
 
4.1%
도 2707
 
4.0%
군 2074
 
3.0%
주 2035
 
3.0%
경 1629
 
2.4%
국 1479
 
2.2%
업 1408
 
2.1%
소 1379
 
2.0%
Other values (459) 46029
67.7%
None
ValueCountFrequency (%)
㈜ 644
99.7%
· 2
 
0.3%

발주처구분
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
지자체
5300 
민간
1902 
기타공공기관
1297 
정부투자기관
748 
<NA>
 
498
Other values (3)
 
255

Length

Max length16
Median length3
Mean length3.507
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row지자체
2nd row민간
3rd row지자체
4th row기타공공기관
5th row지자체

Common Values

ValueCountFrequency (%)
지자체 5300
53.0%
민간 1902
 
19.0%
기타공공기관 1297
 
13.0%
정부투자기관 748
 
7.5%
<NA> 498
 
5.0%
중앙정부 242
 
2.4%
기타공공기관(군대, 학교 등) 7
 
0.1%
실적없음 6
 
0.1%

Length

2023-12-13T00:00:58.513551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:00:58.632082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지자체 5300
52.9%
민간 1902
 
19.0%
기타공공기관 1297
 
13.0%
정부투자기관 748
 
7.5%
na 498
 
5.0%
중앙정부 242
 
2.4%
기타공공기관(군대 7
 
0.1%
학교 7
 
0.1%
등 7
 
0.1%
실적없음 6
 
0.1%

발주형태
Categorical

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반경쟁
3499 
수의계약
2628 
제한경쟁
1423 
<NA>
967 
기타
680 
Other values (7)
803 

Length

Max length4
Median length4
Mean length3.8606
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일반경쟁
2nd row민간공사
3rd row수의계약
4th row수의계약
5th row수의계약

Common Values

ValueCountFrequency (%)
일반경쟁 3499
35.0%
수의계약 2628
26.3%
제한경쟁 1423
14.2%
<NA> 967
 
9.7%
기타 680
 
6.8%
민간공사 562
 
5.6%
일괄입찰 82
 
0.8%
대안입찰 75
 
0.8%
지명경쟁 48
 
0.5%
BTL 26
 
0.3%
Other values (2) 10
 
0.1%

Length

2023-12-13T00:00:58.763342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반경쟁 3499
35.0%
수의계약 2628
26.3%
제한경쟁 1423
14.2%
na 967
 
9.7%
기타 680
 
6.8%
민간공사 562
 
5.6%
일괄입찰 82
 
0.8%
대안입찰 75
 
0.8%
지명경쟁 48
 
0.5%
btl 26
 
0.3%
Other values (2) 10
 
0.1%

공사명
Text

MISSING 

Distinct8730
Distinct (%)89.5%
Missing245
Missing (%)2.5%
Memory size156.2 KiB
2023-12-13T00:00:59.059994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length79
Median length50
Mean length21.857817
Min length1

Characters and Unicode

Total characters213223
Distinct characters807
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8539 ?
Unique (%)87.5%

Sample

1st rowLGD정밀부품창고 신축공사
2nd row담양군지방상수도확장(통합센터)사업 폐기물처리용역
3rd row예술의전당 체육공원 산책로조성사업 폐기물처리용역
4th row서하(거면2공구)지구기계화경작로 확포장공사 폐기물처리용역
5th row정동34-7번지(동양빌딩)외 기존건물 철거공사
ValueCountFrequency (%)
폐기물처리용역 2154
 
6.2%
처리용역 664
 
1.9%
및 618
 
1.8%
건설폐기물 575
 
1.6%
정비공사 468
 
1.3%
건설폐기물처리용역 431
 
1.2%
폐기물 407
 
1.2%
403
 
1.2%
용역 289
 
0.8%
중 282
 
0.8%
Other values (14393) 28707
82.0%
2023-12-13T00:00:59.502549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25373
 
11.9%
사 8105
 
3.8%
공 7188
 
3.4%
리 6955
 
3.3%
기 5959
 
2.8%
처 5636
 
2.6%
물 5316
 
2.5%
역 5256
 
2.5%
폐 5152
 
2.4%
용 5081
 
2.4%
Other values (797) 133202
62.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 166314
78.0%
Space Separator 25373
 
11.9%
Decimal Number 9858
 
4.6%
Close Punctuation 2466
 
1.2%
Open Punctuation 2461
 
1.2%
Uppercase Letter 2404
 
1.1%
Lowercase Letter 1778
 
0.8%
Dash Punctuation 1496
 
0.7%
Other Punctuation 671
 
0.3%
Math Symbol 361
 
0.2%
Other values (4) 41
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 8105
 
4.9%
공 7188
 
4.3%
리 6955
 
4.2%
기 5959
 
3.6%
처 5636
 
3.4%
물 5316
 
3.2%
역 5256
 
3.2%
폐 5152
 
3.1%
용 5081
 
3.1%
수 4714
 
2.8%
Other values (701) 106952
64.3%
Uppercase Letter
ValueCountFrequency (%)
C 263
10.9%
P 250
10.4%
T 200
 
8.3%
S 196
 
8.2%
B 184
 
7.7%
F 174
 
7.2%
A 145
 
6.0%
L 143
 
5.9%
M 120
 
5.0%
R 119
 
5.0%
Other values (16) 610
25.4%
Lowercase Letter
ValueCountFrequency (%)
e 233
13.1%
i 188
10.6%
r 164
9.2%
t 163
9.2%
a 155
8.7%
n 126
 
7.1%
l 125
 
7.0%
o 114
 
6.4%
s 65
 
3.7%
u 58
 
3.3%
Other values (16) 387
21.8%
Other Punctuation
ValueCountFrequency (%)
, 398
59.3%
. 100
 
14.9%
/ 94
 
14.0%
# 18
 
2.7%
· 17
 
2.5%
: 14
 
2.1%
& 8
 
1.2%
' 6
 
0.9%
＆ 6
 
0.9%
; 5
 
0.7%
Other values (4) 5
 
0.7%
Decimal Number
ValueCountFrequency (%)
1 2434
24.7%
2 2263
23.0%
0 1441
14.6%
3 989
10.0%
4 652
 
6.6%
5 516
 
5.2%
7 447
 
4.5%
6 414
 
4.2%
8 372
 
3.8%
9 330
 
3.3%
Math Symbol
ValueCountFrequency (%)
~ 348
96.4%
+ 6
 
1.7%
> 2
 
0.6%
∼ 2
 
0.6%
< 2
 
0.6%
～ 1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 2420
98.1%
] 44
 
1.8%
」 2
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 2414
98.1%
[ 45
 
1.8%
「 2
 
0.1%
Letter Number
ValueCountFrequency (%)
Ⅲ 2
40.0%
Ⅱ 2
40.0%
Ⅰ 1
20.0%
Space Separator
ValueCountFrequency (%)
25373
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1496
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 23
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 10
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 166336
78.0%
Common 42699
 
20.0%
Latin 4187
 
2.0%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 8105
 
4.9%
공 7188
 
4.3%
리 6955
 
4.2%
기 5959
 
3.6%
처 5636
 
3.4%
물 5316
 
3.2%
역 5256
 
3.2%
폐 5152
 
3.1%
용 5081
 
3.1%
수 4714
 
2.8%
Other values (701) 106974
64.3%
Latin
ValueCountFrequency (%)
C 263
 
6.3%
P 250
 
6.0%
e 233
 
5.6%
T 200
 
4.8%
S 196
 
4.7%
i 188
 
4.5%
B 184
 
4.4%
F 174
 
4.2%
r 164
 
3.9%
t 163
 
3.9%
Other values (45) 2172
51.9%
Common
ValueCountFrequency (%)
25373
59.4%
1 2434
 
5.7%
) 2420
 
5.7%
( 2414
 
5.7%
2 2263
 
5.3%
- 1496
 
3.5%
0 1441
 
3.4%
3 989
 
2.3%
4 652
 
1.5%
5 516
 
1.2%
Other values (30) 2701
 
6.3%
Han
ValueCountFrequency (%)
中 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 166309
78.0%
ASCII 46851
 
22.0%
None 51
 
< 0.1%
Number Forms 5
 
< 0.1%
Compat Jamo 4
 
< 0.1%
Math Operators 2
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25373
54.2%
1 2434
 
5.2%
) 2420
 
5.2%
( 2414
 
5.2%
2 2263
 
4.8%
- 1496
 
3.2%
0 1441
 
3.1%
3 989
 
2.1%
4 652
 
1.4%
5 516
 
1.1%
Other values (76) 6853
 
14.6%
Hangul
ValueCountFrequency (%)
사 8105
 
4.9%
공 7188
 
4.3%
리 6955
 
4.2%
기 5959
 
3.6%
처 5636
 
3.4%
물 5316
 
3.2%
역 5256
 
3.2%
폐 5152
 
3.1%
용 5081
 
3.1%
수 4714
 
2.8%
Other values (697) 106947
64.3%
None
ValueCountFrequency (%)
㈜ 23
45.1%
· 17
33.3%
＆ 6
 
11.8%
「 2
 
3.9%
」 2
 
3.9%
～ 1
 
2.0%
Compat Jamo
ValueCountFrequency (%)
ㅇ 2
50.0%
ㅈ 1
25.0%
ㆍ 1
25.0%
Number Forms
ValueCountFrequency (%)
Ⅲ 2
40.0%
Ⅱ 2
40.0%
Ⅰ 1
20.0%
Math Operators
ValueCountFrequency (%)
∼ 2
100.0%
CJK
ValueCountFrequency (%)
中 1
100.0%

소재지
Categorical

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
경기
2273 
전남
1353 
경남
997 
서울
975 
전북
912 
Other values (20)
3490 

Length

Max length8
Median length2
Mean length2.0436
Min length2

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row인천
2nd row경기
3rd row전남
4th row충북
5th row경남

Common Values

ValueCountFrequency (%)
경기 2273
22.7%
전남 1353
13.5%
경남 997
10.0%
서울 975
9.8%
전북 912
9.1%
충남 755
 
7.5%
충북 445
 
4.5%
경북 445
 
4.5%
인천 420
 
4.2%
강원 394
 
3.9%
Other values (15) 1031
10.3%

Length

2023-12-13T00:00:59.642646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기 2273
22.7%
전남 1353
13.5%
경남 997
10.0%
서울 975
9.8%
전북 912
9.1%
충남 755
 
7.5%
충북 445
 
4.5%
경북 445
 
4.5%
인천 420
 
4.2%
강원 394
 
3.9%
Other values (15) 1031
10.3%

용량
Text

MISSING 

Distinct4420
Distinct (%)47.7%
Missing727
Missing (%)7.3%
Memory size156.2 KiB
2023-12-13T00:01:00.033593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length60
Mean length5.1074086
Min length1

Characters and Unicode

Total characters47361
Distinct characters181
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3625 ?
Unique (%)39.1%

Sample

1st row2074
2nd row5548
3rd row100ton/hr
4th row131
5th row143
ValueCountFrequency (%)
100ton/hr 387
 
3.8%
1 385
 
3.8%
1식 307
 
3.1%
0 187
 
1.9%
184
 
1.8%
200ton/h 125
 
1.2%
150ton/hr 121
 
1.2%
200ton/hr 117
 
1.2%
2 85
 
0.8%
4 63
 
0.6%
Other values (4603) 8104
80.5%
2023-12-13T00:01:00.615702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7050
14.9%
1 5509
 
11.6%
2 3611
 
7.6%
5 2770
 
5.8%
3 2550
 
5.4%
4 2476
 
5.2%
6 2103
 
4.4%
9 2070
 
4.4%
8 2011
 
4.2%
7 1942
 
4.1%
Other values (171) 15269
32.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 32092
67.8%
Lowercase Letter 5745
 
12.1%
Other Punctuation 3071
 
6.5%
Other Letter 2788
 
5.9%
Uppercase Letter 1748
 
3.7%
Space Separator 827
 
1.7%
Math Symbol 369
 
0.8%
Close Punctuation 198
 
0.4%
Open Punctuation 198
 
0.4%
Dash Punctuation 166
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
톤 851
30.5%
식 319
 
11.4%
일 266
 
9.5%
폐 197
 
7.1%
콘 108
 
3.9%
개 104
 
3.7%
소 88
 
3.2%
아 65
 
2.3%
건 58
 
2.1%
트 45
 
1.6%
Other values (108) 687
24.6%
Uppercase Letter
ValueCountFrequency (%)
D 490
28.0%
T 271
15.5%
L 207
11.8%
N 178
 
10.2%
H 131
 
7.5%
O 129
 
7.4%
M 98
 
5.6%
A 80
 
4.6%
E 75
 
4.3%
X 40
 
2.3%
Other values (9) 49
 
2.8%
Lowercase Letter
ValueCountFrequency (%)
m 940
16.4%
n 931
16.2%
h 918
16.0%
o 909
15.8%
r 907
15.8%
t 848
14.8%
e 70
 
1.2%
a 57
 
1.0%
d 52
 
0.9%
s 41
 
0.7%
Other values (7) 72
 
1.3%
Decimal Number
ValueCountFrequency (%)
0 7050
22.0%
1 5509
17.2%
2 3611
11.3%
5 2770
 
8.6%
3 2550
 
7.9%
4 2476
 
7.7%
6 2103
 
6.6%
9 2070
 
6.5%
8 2011
 
6.3%
7 1942
 
6.1%
Other Punctuation
ValueCountFrequency (%)
/ 1422
46.3%
. 763
24.8%
, 697
22.7%
: 149
 
4.9%
* 40
 
1.3%
Math Symbol
ValueCountFrequency (%)
= 217
58.8%
~ 115
31.2%
∼ 24
 
6.5%
× 13
 
3.5%
Other Symbol
ValueCountFrequency (%)
㎥ 137
86.2%
㎡ 18
 
11.3%
㎏ 3
 
1.9%
㎜ 1
 
0.6%
Space Separator
ValueCountFrequency (%)
827
100.0%
Close Punctuation
ValueCountFrequency (%)
) 198
100.0%
Open Punctuation
ValueCountFrequency (%)
( 198
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 166
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 37080
78.3%
Latin 7486
 
15.8%
Hangul 2788
 
5.9%
Greek 7
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
톤 851
30.5%
식 319
 
11.4%
일 266
 
9.5%
폐 197
 
7.1%
콘 108
 
3.9%
개 104
 
3.7%
소 88
 
3.2%
아 65
 
2.3%
건 58
 
2.1%
트 45
 
1.6%
Other values (108) 687
24.6%
Latin
ValueCountFrequency (%)
m 940
12.6%
n 931
12.4%
h 918
12.3%
o 909
12.1%
r 907
12.1%
t 848
11.3%
D 490
6.5%
T 271
 
3.6%
L 207
 
2.8%
N 178
 
2.4%
Other values (25) 887
11.8%
Common
ValueCountFrequency (%)
0 7050
19.0%
1 5509
14.9%
2 3611
9.7%
5 2770
 
7.5%
3 2550
 
6.9%
4 2476
 
6.7%
6 2103
 
5.7%
9 2070
 
5.6%
8 2011
 
5.4%
7 1942
 
5.2%
Other values (17) 4988
13.5%
Greek
ValueCountFrequency (%)
Φ 7
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 44370
93.7%
Hangul 2788
 
5.9%
CJK Compat 159
 
0.3%
Math Operators 24
 
0.1%
None 20
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7050
15.9%
1 5509
12.4%
2 3611
 
8.1%
5 2770
 
6.2%
3 2550
 
5.7%
4 2476
 
5.6%
6 2103
 
4.7%
9 2070
 
4.7%
8 2011
 
4.5%
7 1942
 
4.4%
Other values (46) 12278
27.7%
Hangul
ValueCountFrequency (%)
톤 851
30.5%
식 319
 
11.4%
일 266
 
9.5%
폐 197
 
7.1%
콘 108
 
3.9%
개 104
 
3.7%
소 88
 
3.2%
아 65
 
2.3%
건 58
 
2.1%
트 45
 
1.6%
Other values (108) 687
24.6%
CJK Compat
ValueCountFrequency (%)
㎥ 137
86.2%
㎡ 18
 
11.3%
㎏ 3
 
1.9%
㎜ 1
 
0.6%
Math Operators
ValueCountFrequency (%)
∼ 24
100.0%
None
ValueCountFrequency (%)
× 13
65.0%
Φ 7
35.0%

원도급자
Text

MISSING 

Distinct2262
Distinct (%)27.6%
Missing1803
Missing (%)18.0%
Memory size156.2 KiB
2023-12-13T00:01:00.992724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length31
Mean length6.76589
Min length1

Characters and Unicode

Total characters55460
Distinct characters445
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

Unique1653 ?
Unique (%)20.2%

Sample

1st row대흥에코㈜
2nd row담양군청
3rd row두제산업개발㈜
4th row남양기업(주)
5th row장형기업
ValueCountFrequency (%)
담양군청 279
 
3.2%
인선ent 279
 
3.2%
㈜동양환경 213
 
2.4%
주식회사 188
 
2.1%
남양기업㈜ 153
 
1.7%
㈜원보 102
 
1.2%
두제산업개발㈜ 102
 
1.2%
신화환경개발(주 93
 
1.1%
대흥에코㈜ 93
 
1.1%
유)남해환경 81
 
0.9%
Other values (2319) 7207
82.0%
2023-12-13T00:01:01.491109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 2924
 
5.3%
( 2899
 
5.2%
㈜ 2812
 
5.1%
주 2756
 
5.0%
경 2738
 
4.9%
환 2713
 
4.9%
업 1902
 
3.4%
산 1642
 
3.0%
건 1286
 
2.3%
발 1170
 
2.1%
Other values (435) 32618
58.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 44586
80.4%
Close Punctuation 2924
 
5.3%
Open Punctuation 2899
 
5.2%
Other Symbol 2812
 
5.1%
Uppercase Letter 1101
 
2.0%
Space Separator 604
 
1.1%
Decimal Number 260
 
0.5%
Other Punctuation 226
 
0.4%
Lowercase Letter 25
 
< 0.1%
Dash Punctuation 23
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 2756
 
6.2%
경 2738
 
6.1%
환 2713
 
6.1%
업 1902
 
4.3%
산 1642
 
3.7%
건 1286
 
2.9%
발 1170
 
2.6%
개 1162
 
2.6%
설 1090
 
2.4%
양 980
 
2.2%
Other values (386) 27147
60.9%
Uppercase Letter
ValueCountFrequency (%)
T 325
29.5%
N 314
28.5%
E 309
28.1%
L 24
 
2.2%
H 24
 
2.2%
S 23
 
2.1%
C 16
 
1.5%
K 15
 
1.4%
A 10
 
0.9%
G 10
 
0.9%
Other values (7) 31
 
2.8%
Lowercase Letter
ValueCountFrequency (%)
n 3
12.0%
a 3
12.0%
r 3
12.0%
t 3
12.0%
o 3
12.0%
g 2
8.0%
i 2
8.0%
d 2
8.0%
c 1
 
4.0%
e 1
 
4.0%
Other values (2) 2
8.0%
Decimal Number
ValueCountFrequency (%)
6 34
13.1%
1 32
12.3%
3 30
11.5%
5 29
11.2%
7 28
10.8%
4 28
10.8%
2 27
10.4%
0 22
8.5%
9 16
6.2%
8 14
5.4%
Other Punctuation
ValueCountFrequency (%)
, 110
48.7%
% 77
34.1%
. 24
 
10.6%
/ 12
 
5.3%
& 3
 
1.3%
Close Punctuation
ValueCountFrequency (%)
) 2924
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2899
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2812
100.0%
Space Separator
ValueCountFrequency (%)
604
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 47398
85.5%
Common 6936
 
12.5%
Latin 1126
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 2812
 
5.9%
주 2756
 
5.8%
경 2738
 
5.8%
환 2713
 
5.7%
업 1902
 
4.0%
산 1642
 
3.5%
건 1286
 
2.7%
발 1170
 
2.5%
개 1162
 
2.5%
설 1090
 
2.3%
Other values (387) 28127
59.3%
Latin
ValueCountFrequency (%)
T 325
28.9%
N 314
27.9%
E 309
27.4%
L 24
 
2.1%
H 24
 
2.1%
S 23
 
2.0%
C 16
 
1.4%
K 15
 
1.3%
A 10
 
0.9%
G 10
 
0.9%
Other values (19) 56
 
5.0%
Common
ValueCountFrequency (%)
) 2924
42.2%
( 2899
41.8%
604
 
8.7%
, 110
 
1.6%
% 77
 
1.1%
6 34
 
0.5%
1 32
 
0.5%
3 30
 
0.4%
5 29
 
0.4%
7 28
 
0.4%
Other values (9) 169
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 44586
80.4%
ASCII 8062
 
14.5%
None 2812
 
5.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 2924
36.3%
( 2899
36.0%
604
 
7.5%
T 325
 
4.0%
N 314
 
3.9%
E 309
 
3.8%
, 110
 
1.4%
% 77
 
1.0%
6 34
 
0.4%
1 32
 
0.4%
Other values (38) 434
 
5.4%
None
ValueCountFrequency (%)
㈜ 2812
100.0%
Hangul
ValueCountFrequency (%)
주 2756
 
6.2%
경 2738
 
6.1%
환 2713
 
6.1%
업 1902
 
4.3%
산 1642
 
3.7%
건 1286
 
2.9%
발 1170
 
2.6%
개 1162
 
2.6%
설 1090
 
2.4%
양 980
 
2.2%
Other values (386) 27147
60.9%

계약일자
Date

MISSING 

Distinct3001
Distinct (%)33.0%
Missing909
Missing (%)9.1%
Memory size156.2 KiB
Minimum1905-06-29 00:00:00
Maximum2019-12-31 00:00:00
2023-12-13T00:01:01.626156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:01:01.785058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

착공일자
Date

MISSING 

Distinct3396
Distinct (%)36.0%
Missing573
Missing (%)5.7%
Memory size156.2 KiB
Minimum1899-12-30 00:00:00
Maximum2047-04-17 00:00:00
2023-12-13T00:01:01.938084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:01:02.089625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

준공일자
Date

MISSING 

Distinct3834
Distinct (%)40.5%
Missing526
Missing (%)5.3%
Memory size156.2 KiB
Minimum1899-12-30 00:00:00
Maximum2117-12-20 00:00:00
2023-12-13T00:01:02.269931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:01:02.421383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

계약관계
Categorical

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
용역
3527 
도급
2217 
납품
1228 
<NA>
996 
하도급
622 
Other values (7)
1410 

Length

Max length4
Median length2
Mean length2.2734
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row납품
2nd row용역
3rd row용역
4th row용역
5th row용역

Common Values

ValueCountFrequency (%)
용역 3527
35.3%
도급 2217
22.2%
납품 1228
 
12.3%
<NA> 996
 
10.0%
하도급 622
 
6.2%
조달 610
 
6.1%
계약 287
 
2.9%
협약 168
 
1.7%
수의 158
 
1.6%
직영 85
 
0.9%
Other values (2) 102
 
1.0%

Length

2023-12-13T00:01:02.563881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
용역 3527
35.3%
도급 2217
22.2%
납품 1228
 
12.3%
na 996
 
10.0%
하도급 622
 
6.2%
조달 610
 
6.1%
계약 287
 
2.9%
협약 168
 
1.7%
수의 158
 
1.6%
직영 85
 
0.9%
Other values (2) 102
 
1.0%

공사금액
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED 

Distinct7740
Distinct (%)81.0%
Missing448
Missing (%)4.5%
Infinite0
Infinite (%)0.0%
Mean384631.16
Minimum0
Maximum2.924 × 108
Zeros42
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T00:01:02.715449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile800
Q17216.75
median30000
Q3143000
95-th percentile900992.85
Maximum2.924 × 108
Range2.924 × 108
Interquartile range (IQR)135783.25

Descriptive statistics

Standard deviation4665920.9
Coefficient of variation (CV)12.130897
Kurtosis2112.3591
Mean384631.16
Median Absolute Deviation (MAD)27636
Skewness40.910192
Sum3.6739968 × 109
Variance2.1770818 × 1013
MonotonicityNot monotonic
2023-12-13T00:01:02.853982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 42
 
0.4%
10000 29
 
0.3%
20000 23
 
0.2%
30000 21
 
0.2%
40000 21
 
0.2%
50000 17
 
0.2%
110000 16
 
0.2%
150000 15
 
0.1%
1000 15
 
0.1%
7000 15
 
0.1%
Other values (7730) 9338
93.4%
(Missing) 448
 
4.5%
ValueCountFrequency (%)
0 42
0.4%
18 1
 
< 0.1%
22 1
 
< 0.1%
33 1
 
< 0.1%
35 1
 
< 0.1%
54 1
 
< 0.1%
66 2
 
< 0.1%
71 2
 
< 0.1%
88 2
 
< 0.1%
91 1
 
< 0.1%
ValueCountFrequency (%)
292400000 1
< 0.1%
202399489 1
< 0.1%
127823000 1
< 0.1%
102253800 1
< 0.1%
97094800 1
< 0.1%
94545000 1
< 0.1%
77198000 1
< 0.1%
64274000 1
< 0.1%
63390000 1
< 0.1%
49503300 1
< 0.1%

신기술공사계약금액
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct8020
Distinct (%)80.6%
Missing45
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean219758.23
Minimum0
Maximum63390000
Zeros41
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T00:01:03.313383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile652.6
Q16163.5
median25545
Q3122231
95-th percentile772384.5
Maximum63390000
Range63390000
Interquartile range (IQR)116067.5

Descriptive statistics

Standard deviation1314349
Coefficient of variation (CV)5.9808863
Kurtosis955.30628
Mean219758.23
Median Absolute Deviation (MAD)23727
Skewness26.511258
Sum2.1876932 × 109
Variance1.7275133 × 1012
MonotonicityNot monotonic
2023-12-13T00:01:03.443088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 41
 
0.4%
10000 30
 
0.3%
20000 23
 
0.2%
40000 21
 
0.2%
30000 19
 
0.2%
110000 16
 
0.2%
50000 16
 
0.2%
1000 15
 
0.1%
7000 15
 
0.1%
11000 15
 
0.1%
Other values (8010) 9744
97.4%
(Missing) 45
 
0.4%
ValueCountFrequency (%)
0 41
0.4%
18 1
 
< 0.1%
19 1
 
< 0.1%
22 1
 
< 0.1%
33 1
 
< 0.1%
35 1
 
< 0.1%
54 1
 
< 0.1%
59 1
 
< 0.1%
60 6
 
0.1%
66 2
 
< 0.1%
ValueCountFrequency (%)
63390000 1
< 0.1%
48400000 1
< 0.1%
40173000 1
< 0.1%
39276500 1
< 0.1%
30240000 1
< 0.1%
22741383 1
< 0.1%
22597297 1
< 0.1%
20462000 1
< 0.1%
20020000 1
< 0.1%
19328977 1
< 0.1%

Interactions

2023-12-13T00:00:54.802302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:00:51.324169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:00:52.030860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:00:52.827891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:00:53.521136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:00:54.159136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:00:54.905918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:00:51.466382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:00:52.167903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:00:52.951236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:00:53.636439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:00:54.262658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:00:55.019084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:00:51.597801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:00:52.335464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:00:53.065631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:00:53.769333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:00:54.386352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:00:55.137908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:00:51.710124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:00:52.450931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:00:53.191755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:00:53.874027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:00:54.509269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:00:55.232109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:00:51.799957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:00:52.547171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:00:53.313881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:00:53.961462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:00:54.610980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:00:55.321957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:00:51.905231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:00:52.712238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:00:53.421803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:00:54.057817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:00:54.709475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:01:03.540538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
활용실적상세 순번활용실적 순번신청서ID실적제출년도발주처구분발주형태소재지계약관계공사금액신기술공사계약금액
활용실적상세 순번1.0000.9440.9220.9450.2660.3530.4530.4860.0330.033
활용실적 순번0.9441.0000.8770.9770.2430.3470.3300.4970.0270.028
신청서ID0.9220.8771.0000.8650.1880.3710.4670.4360.0000.000
실적제출년도0.9450.9770.8651.0000.3150.3470.2870.4570.0560.199
발주처구분0.2660.2430.1880.3151.0000.7300.3440.3930.0660.000
발주형태0.3530.3470.3710.3470.7301.0000.5170.6740.2190.175
소재지0.4530.3300.4670.2870.3440.5171.0000.5420.0000.000
계약관계0.4860.4970.4360.4570.3930.6740.5421.0000.1190.043
공사금액0.0330.0270.0000.0560.0660.2190.0000.1191.0000.635
신기술공사계약금액0.0330.0280.0000.1990.0000.1750.0000.0430.6351.000
2023-12-13T00:01:03.702451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
계약관계소재지발주처구분발주형태
계약관계1.0000.2220.2060.257
소재지0.2221.0000.1540.209
발주처구분0.2060.1541.0000.475
발주형태0.2570.2090.4751.000
2023-12-13T00:01:03.796888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
활용실적상세 순번활용실적 순번신청서ID실적제출년도공사금액신기술공사계약금액발주처구분발주형태소재지계약관계
활용실적상세 순번1.0000.9780.9830.9790.0290.0520.1370.1580.1830.231
활용실적 순번0.9781.0000.9600.9970.0290.0520.1250.1550.1270.237
신청서ID0.9830.9601.0000.9610.0250.0500.0960.1670.1900.202
실적제출년도0.9790.9970.9611.0000.0300.0570.1140.1790.1090.246
공사금액0.0290.0290.0250.0301.0000.9700.0230.1090.0000.061
신기술공사계약금액0.0520.0520.0500.0570.9701.0000.0000.0970.0000.023
발주처구분0.1370.1250.0960.1140.0230.0001.0000.4750.1540.206
발주형태0.1580.1550.1670.1790.1090.0970.4751.0000.2090.257
소재지0.1830.1270.1900.1090.0000.0000.1540.2091.0000.222
계약관계0.2310.2370.2020.2460.0610.0230.2060.2570.2221.000

Missing values

2023-12-13T00:00:55.472944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:00:55.700598image/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.
2023-12-13T00:00:56.223251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

활용실적상세 순번활용실적 순번신청서ID실적제출년도발주처발주처구분발주형태공사명소재지용량원도급자계약일자착공일자준공일자계약관계공사금액신기술공사계약금액
831149034653212008인천광역시 옹진군지자체일반경쟁<NA>인천2074<NA>2008-12-15<NA><NA>납품4821748217
2672523754303979402015서브원민간민간공사LGD정밀부품창고 신축공사경기5548대흥에코㈜2015-07-172015-07-172015-11-30용역106414106414
1941216993181123962012담양군청지자체수의계약담양군지방상수도확장(통합센터)사업 폐기물처리용역전남100ton/hr담양군청2012-03-232012-03-232013-03-23용역154154
1111671527655352010청주시 문화예술체육회관기타공공기관수의계약예술의전당 체육공원 산책로조성사업 폐기물처리용역충북131두제산업개발㈜2010-09-282010-09-292011-01-26용역31122153
196521239178851362012함양군청지자체수의계약서하(거면2공구)지구기계화경작로 확포장공사 폐기물처리용역경남143남양기업(주)2012-06-272012-07-032012-08-31용역27002700
30058395953772153282018(주)수경하우징민간민간공사정동34-7번지(동양빌딩)외 기존건물 철거공사서울5000장형기업2018-02-212018-01-102018-03-31계약7040070400
2334021563304251632015한국토지주택공사 서울지역본부기타공공기관일반경쟁하남미사 중2초4, 고1, 초5초6 건설폐기물(파쇄) 위탁처리용역경기161.0ton/hr동부이엔티㈜2015-04-082015-04-082016-08-11용역3299832998
2183729593341796672016경기도교육청 경기도성남교육지원청지자체일반경쟁성남 양지초 외부환경개선공사 폐기물처리용역경기0인선이엔티(주)2016-08-042016-08-042016-12-31용역2663026630
142341169611588702010울산광역시 중구지자체일반경쟁-울산50<NA>2010-11-232010-11-232010-11-23조달<NA>135
2639023941321484242015인천항만공사정부투자기관제한경쟁인천항 국제여객부두(2단계) 건설공사 폐기물처리용역(4차)인천21523아이케이2015-01-282015-01-302015-04-29도급572067572067
활용실적상세 순번활용실적 순번신청서ID실적제출년도발주처발주처구분발주형태공사명소재지용량원도급자계약일자착공일자준공일자계약관계공사금액신기술공사계약금액
2930232167358883112017한솔이엠이주식회사민간민간공사슬러지 건조기 & 배가스 세정탑 납품/설치경기112 ton/day(1 line)장우기계2016-12-212017-11-232018-03-20기타20350002035000
30819383943674136162018경기도 경기도 건설본부지자체일반경쟁2018년 남양주,가평,포천 국지도 및 지방도 포장보수 폐기물처리 용역(단가계약)경기1370톤(유)도성개발2018-05-032018-05-042018-10-30용역338513338513
1595714812192814032012보은국토관리사무소중앙정부일반경쟁국토4호선 대전시계-증약교등 7개소 포장도보수공사 폐기물충북2891동림개발㈜2012-07-302012-07-092013-02-03도급6629066920
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