Overview

Dataset statistics

Number of variables15
Number of observations10000
Missing cells2
Missing cells (%)< 0.1%
Duplicate rows34
Duplicate rows (%)0.3%
Total size in memory1.3 MiB
Average record size in memory132.0 B

Variable types

DateTime1
Text5
Numeric4
Categorical5

Dataset

Description방위사업청 및 각 군이 국내에서 조달하는 군수품에 대한 입찰결과 정보를 제공합니다.견적서제출마감일시,판단번호,공고번호,입찰건명 등 수록
Author방위사업청
URLhttps://www.data.go.kr/data/15050918/fileData.do

Alerts

Dataset has 34 (0.3%) duplicate rowsDuplicates
예산금액 is highly overall correlated with 기초예비가격 and 1 other fieldsHigh correlation
기초예비가격 is highly overall correlated with 예산금액 and 1 other fieldsHigh correlation
예정가격 is highly overall correlated with 예산금액 and 1 other fieldsHigh correlation
낙찰자결정방법 is highly overall correlated with 집행유형High correlation
집행유형 is highly overall correlated with 낙찰자결정방법High correlation
계약방법 is highly imbalanced (99.7%)Imbalance
낙찰자결정방법 is highly imbalanced (84.7%)Imbalance
입찰방법 is highly imbalanced (91.3%)Imbalance
집행유형 is highly imbalanced (81.5%)Imbalance
입찰결과 is highly imbalanced (52.7%)Imbalance
예정가격 has 1961 (19.6%) zerosZeros

Reproduction

Analysis started2024-03-16 04:17:57.470848
Analysis finished2024-03-16 04:18:05.009986
Duration7.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

견적서제출마감일시
Date

Distinct2791
Distinct (%)27.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2017-01-09 10:00:00
Maximum2023-09-27 13:30:00
2024-03-16T13:18:05.156344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:05.528109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

판단번호
Text

Distinct8897
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-16T13:18:06.047633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.7563
Min length1

Characters and Unicode

Total characters47563
Distinct characters20
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7921 ?
Unique (%)79.2%

Sample

1st row37731
2nd row24371
3rd row37303
4th row39890
5th row15862
ValueCountFrequency (%)
9630 5
 
< 0.1%
6370 5
 
< 0.1%
4013b 4
 
< 0.1%
4701 4
 
< 0.1%
4180 4
 
< 0.1%
4950a 4
 
< 0.1%
6877 4
 
< 0.1%
7107 4
 
< 0.1%
160 4
 
< 0.1%
8507 4
 
< 0.1%
Other values (8887) 9958
99.6%
2024-03-16T13:18:07.278635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 6191
13.0%
1 6129
12.9%
2 5610
11.8%
4 5526
11.6%
5 4323
9.1%
0 4115
8.7%
8 4005
8.4%
7 3911
8.2%
6 3844
8.1%
9 3804
8.0%
Other values (10) 105
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 47458
99.8%
Uppercase Letter 105
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 6191
13.0%
1 6129
12.9%
2 5610
11.8%
4 5526
11.6%
5 4323
9.1%
0 4115
8.7%
8 4005
8.4%
7 3911
8.2%
6 3844
8.1%
9 3804
8.0%
Uppercase Letter
ValueCountFrequency (%)
A 57
54.3%
B 17
 
16.2%
G 13
 
12.4%
D 6
 
5.7%
C 5
 
4.8%
Z 3
 
2.9%
F 1
 
1.0%
M 1
 
1.0%
O 1
 
1.0%
J 1
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
Common 47458
99.8%
Latin 105
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
3 6191
13.0%
1 6129
12.9%
2 5610
11.8%
4 5526
11.6%
5 4323
9.1%
0 4115
8.7%
8 4005
8.4%
7 3911
8.2%
6 3844
8.1%
9 3804
8.0%
Latin
ValueCountFrequency (%)
A 57
54.3%
B 17
 
16.2%
G 13
 
12.4%
D 6
 
5.7%
C 5
 
4.8%
Z 3
 
2.9%
F 1
 
1.0%
M 1
 
1.0%
O 1
 
1.0%
J 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47563
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 6191
13.0%
1 6129
12.9%
2 5610
11.8%
4 5526
11.6%
5 4323
9.1%
0 4115
8.7%
8 4005
8.4%
7 3911
8.2%
6 3844
8.1%
9 3804
8.0%
Other values (10) 105
 
0.2%

공고번호
Text

Distinct7040
Distinct (%)70.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-16T13:18:07.847531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters90000
Distinct characters36
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4905 ?
Unique (%)49.0%

Sample

1st rowHCL0093-1
2nd rowSDQ0049-1
3rd rowSCF0283-1
4th rowMCX0042-1
5th rowSDQ0043-2
ValueCountFrequency (%)
scr0043-1 7
 
0.1%
scr0020-1 7
 
0.1%
scr0010-1 7
 
0.1%
scr0050-1 6
 
0.1%
scr0053-1 6
 
0.1%
scr0030-1 6
 
0.1%
scf0026-1 6
 
0.1%
scr0039-1 6
 
0.1%
sdq0036-1 6
 
0.1%
scr0054-1 6
 
0.1%
Other values (7030) 9937
99.4%
2024-03-16T13:18:08.555629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 19861
22.1%
1 13592
15.1%
- 10000
11.1%
S 5504
 
6.1%
C 5383
 
6.0%
2 3600
 
4.0%
L 3126
 
3.5%
F 2652
 
2.9%
3 2434
 
2.7%
4 2148
 
2.4%
Other values (26) 21700
24.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 49618
55.1%
Uppercase Letter 30382
33.8%
Dash Punctuation 10000
 
11.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 5504
18.1%
C 5383
17.7%
L 3126
10.3%
F 2652
8.7%
H 2131
 
7.0%
D 1882
 
6.2%
M 1618
 
5.3%
G 1404
 
4.6%
Q 1004
 
3.3%
N 985
 
3.2%
Other values (15) 4693
15.4%
Decimal Number
ValueCountFrequency (%)
0 19861
40.0%
1 13592
27.4%
2 3600
 
7.3%
3 2434
 
4.9%
4 2148
 
4.3%
5 1909
 
3.8%
6 1735
 
3.5%
7 1520
 
3.1%
8 1420
 
2.9%
9 1399
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 59618
66.2%
Latin 30382
33.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 5504
18.1%
C 5383
17.7%
L 3126
10.3%
F 2652
8.7%
H 2131
 
7.0%
D 1882
 
6.2%
M 1618
 
5.3%
G 1404
 
4.6%
Q 1004
 
3.3%
N 985
 
3.2%
Other values (15) 4693
15.4%
Common
ValueCountFrequency (%)
0 19861
33.3%
1 13592
22.8%
- 10000
16.8%
2 3600
 
6.0%
3 2434
 
4.1%
4 2148
 
3.6%
5 1909
 
3.2%
6 1735
 
2.9%
7 1520
 
2.5%
8 1420
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 19861
22.1%
1 13592
15.1%
- 10000
11.1%
S 5504
 
6.1%
C 5383
 
6.0%
2 3600
 
4.0%
L 3126
 
3.5%
F 2652
 
2.9%
3 2434
 
2.7%
4 2148
 
2.4%
Other values (26) 21700
24.1%

입찰건명
Text

Distinct9252
Distinct (%)92.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-16T13:18:09.008658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length35
Mean length16.5322
Min length2

Characters and Unicode

Total characters165322
Distinct characters932
Distinct categories16 ?
Distinct scripts4 ?
Distinct blocks10 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8670 ?
Unique (%)86.7%

Sample

1st row항-17-068,069 진공체혈바늘 등 86종
2nd row21-45-회로카드 조립체 등 8종
3rd row모니터, 텔레비전식 1종 구매
4th row소방기구(분말소화기 등 13종) 구매
5th row콘센트릭 밸브 조립체 등 21종
ValueCountFrequency (%)
구매 4995
 
12.9%
등 4805
 
12.4%
2종 440
 
1.1%
납품 324
 
0.8%
00부대 279
 
0.7%
1종 276
 
0.7%
3종 276
 
0.7%
및 272
 
0.7%
22년 226
 
0.6%
23년 210
 
0.5%
Other values (11246) 26508
68.7%
2024-03-16T13:18:09.952304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
28661
 
17.3%
구 6660
 
4.0%
매 6263
 
3.8%
등 4967
 
3.0%
2 4567
 
2.8%
종 4394
 
2.7%
1 4268
 
2.6%
품 2970
 
1.8%
) 2921
 
1.8%
( 2914
 
1.8%
Other values (922) 96737
58.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 102330
61.9%
Space Separator 28661
 
17.3%
Decimal Number 21067
 
12.7%
Close Punctuation 3048
 
1.8%
Open Punctuation 3042
 
1.8%
Uppercase Letter 2746
 
1.7%
Dash Punctuation 2009
 
1.2%
Other Punctuation 1603
 
1.0%
Lowercase Letter 724
 
0.4%
Math Symbol 46
 
< 0.1%
Other values (6) 46
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 6660
 
6.5%
매 6263
 
6.1%
등 4967
 
4.9%
종 4394
 
4.3%
품 2970
 
2.9%
기 2640
 
2.6%
용 1944
 
1.9%
대 1515
 
1.5%
전 1407
 
1.4%
장 1238
 
1.2%
Other values (831) 68332
66.8%
Uppercase Letter
ValueCountFrequency (%)
C 296
 
10.8%
A 256
 
9.3%
P 237
 
8.6%
S 182
 
6.6%
E 179
 
6.5%
D 176
 
6.4%
T 176
 
6.4%
V 132
 
4.8%
L 132
 
4.8%
K 114
 
4.2%
Other values (16) 866
31.5%
Lowercase Letter
ValueCountFrequency (%)
e 91
12.6%
o 58
 
8.0%
t 50
 
6.9%
a 49
 
6.8%
i 49
 
6.8%
r 49
 
6.8%
n 46
 
6.4%
m 40
 
5.5%
l 39
 
5.4%
s 38
 
5.2%
Other values (15) 215
29.7%
Other Punctuation
ValueCountFrequency (%)
, 1185
73.9%
/ 299
 
18.7%
. 58
 
3.6%
' 34
 
2.1%
· 8
 
0.5%
% 6
 
0.4%
: 6
 
0.4%
* 3
 
0.2%
& 2
 
0.1%
# 1
 
0.1%
Decimal Number
ValueCountFrequency (%)
2 4567
21.7%
1 4268
20.3%
0 2795
13.3%
3 2315
11.0%
4 1483
 
7.0%
5 1241
 
5.9%
7 1165
 
5.5%
8 1088
 
5.2%
9 1074
 
5.1%
6 1071
 
5.1%
Open Punctuation
ValueCountFrequency (%)
( 2914
95.8%
[ 127
 
4.2%
「 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 44
95.7%
∼ 1
 
2.2%
+ 1
 
2.2%
Other Symbol
ValueCountFrequency (%)
○ 2
50.0%
㎜ 1
25.0%
㎡ 1
25.0%
Close Punctuation
ValueCountFrequency (%)
) 2921
95.8%
] 127
 
4.2%
Final Punctuation
ValueCountFrequency (%)
’ 5
83.3%
” 1
 
16.7%
Space Separator
ValueCountFrequency (%)
28661
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2009
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 27
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 3
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 102329
61.9%
Common 59521
36.0%
Latin 3471
 
2.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 6660
 
6.5%
매 6263
 
6.1%
등 4967
 
4.9%
종 4394
 
4.3%
품 2970
 
2.9%
기 2640
 
2.6%
용 1944
 
1.9%
대 1515
 
1.5%
전 1407
 
1.4%
장 1238
 
1.2%
Other values (830) 68331
66.8%
Latin
ValueCountFrequency (%)
C 296
 
8.5%
A 256
 
7.4%
P 237
 
6.8%
S 182
 
5.2%
E 179
 
5.2%
D 176
 
5.1%
T 176
 
5.1%
V 132
 
3.8%
L 132
 
3.8%
K 114
 
3.3%
Other values (42) 1591
45.8%
Common
ValueCountFrequency (%)
28661
48.2%
2 4567
 
7.7%
1 4268
 
7.2%
) 2921
 
4.9%
( 2914
 
4.9%
0 2795
 
4.7%
3 2315
 
3.9%
- 2009
 
3.4%
4 1483
 
2.5%
5 1241
 
2.1%
Other values (29) 6347
 
10.7%
Han
ValueCountFrequency (%)
必 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 102314
61.9%
ASCII 62968
38.1%
Compat Jamo 15
 
< 0.1%
None 9
 
< 0.1%
Punctuation 9
 
< 0.1%
Geometric Shapes 2
 
< 0.1%
CJK Compat 2
 
< 0.1%
Math Operators 1
 
< 0.1%
CJK 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
28661
45.5%
2 4567
 
7.3%
1 4268
 
6.8%
) 2921
 
4.6%
( 2914
 
4.6%
0 2795
 
4.4%
3 2315
 
3.7%
- 2009
 
3.2%
4 1483
 
2.4%
5 1241
 
2.0%
Other values (71) 9794
 
15.6%
Hangul
ValueCountFrequency (%)
구 6660
 
6.5%
매 6263
 
6.1%
등 4967
 
4.9%
종 4394
 
4.3%
품 2970
 
2.9%
기 2640
 
2.6%
용 1944
 
1.9%
대 1515
 
1.5%
전 1407
 
1.4%
장 1238
 
1.2%
Other values (828) 68316
66.8%
Compat Jamo
ValueCountFrequency (%)
ㆍ 11
73.3%
ㅇ 4
 
26.7%
None
ValueCountFrequency (%)
· 8
88.9%
「 1
 
11.1%
Punctuation
ValueCountFrequency (%)
’ 5
55.6%
‘ 3
33.3%
” 1
 
11.1%
Geometric Shapes
ValueCountFrequency (%)
○ 2
100.0%
Math Operators
ValueCountFrequency (%)
∼ 1
100.0%
CJK
ValueCountFrequency (%)
必 1
100.0%
CJK Compat
ValueCountFrequency (%)
㎜ 1
50.0%
㎡ 1
50.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

발주기관
Text

Distinct217
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-16T13:18:10.380922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length7
Mean length7.6081
Min length4

Characters and Unicode

Total characters76081
Distinct characters139
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)0.2%

Sample

1st row공군사관학교
2nd row해군제2수리창
3rd row해군군수사령부
4th row자운대근무지원단
5th row해군제2수리창
ValueCountFrequency (%)
해군군수사령부 744
 
7.0%
제8385부대 332
 
3.1%
해군작전사령부 326
 
3.1%
제9911부대 324
 
3.1%
해군교육사령부 324
 
3.1%
해군제3함대사령부 307
 
2.9%
제7001부대 295
 
2.8%
해군제1수리창 244
 
2.3%
해군제2수리창 236
 
2.2%
제5738부대 216
 
2.0%
Other values (213) 7214
68.3%
2024-03-16T13:18:11.011055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
부 6873
 
9.0%
제 5848
 
7.7%
군 5711
 
7.5%
대 4774
 
6.3%
1 4226
 
5.6%
사 3599
 
4.7%
9 2899
 
3.8%
해 2621
 
3.4%
령 2375
 
3.1%
8 2328
 
3.1%
Other values (129) 34827
45.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 55044
72.3%
Decimal Number 19384
 
25.5%
Other Punctuation 633
 
0.8%
Space Separator 594
 
0.8%
Close Punctuation 213
 
0.3%
Open Punctuation 213
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 6873
 
12.5%
제 5848
 
10.6%
군 5711
 
10.4%
대 4774
 
8.7%
사 3599
 
6.5%
해 2621
 
4.8%
령 2375
 
4.3%
단 1727
 
3.1%
수 1626
 
3.0%
육 1385
 
2.5%
Other values (114) 18505
33.6%
Decimal Number
ValueCountFrequency (%)
1 4226
21.8%
9 2899
15.0%
8 2328
12.0%
3 2064
10.6%
2 2005
10.3%
0 1783
9.2%
7 1607
 
8.3%
6 1222
 
6.3%
5 1210
 
6.2%
4 40
 
0.2%
Other Punctuation
ValueCountFrequency (%)
. 422
66.7%
: 211
33.3%
Space Separator
ValueCountFrequency (%)
594
100.0%
Close Punctuation
ValueCountFrequency (%)
) 213
100.0%
Open Punctuation
ValueCountFrequency (%)
( 213
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 55044
72.3%
Common 21037
 
27.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 6873
 
12.5%
제 5848
 
10.6%
군 5711
 
10.4%
대 4774
 
8.7%
사 3599
 
6.5%
해 2621
 
4.8%
령 2375
 
4.3%
단 1727
 
3.1%
수 1626
 
3.0%
육 1385
 
2.5%
Other values (114) 18505
33.6%
Common
ValueCountFrequency (%)
1 4226
20.1%
9 2899
13.8%
8 2328
11.1%
3 2064
9.8%
2 2005
9.5%
0 1783
8.5%
7 1607
 
7.6%
6 1222
 
5.8%
5 1210
 
5.8%
594
 
2.8%
Other values (5) 1099
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 55044
72.3%
ASCII 21037
 
27.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
부 6873
 
12.5%
제 5848
 
10.6%
군 5711
 
10.4%
대 4774
 
8.7%
사 3599
 
6.5%
해 2621
 
4.8%
령 2375
 
4.3%
단 1727
 
3.1%
수 1626
 
3.0%
육 1385
 
2.5%
Other values (114) 18505
33.6%
ASCII
ValueCountFrequency (%)
1 4226
20.1%
9 2899
13.8%
8 2328
11.1%
3 2064
9.8%
2 2005
9.5%
0 1783
8.5%
7 1607
 
7.6%
6 1222
 
5.8%
5 1210
 
5.8%
594
 
2.8%
Other values (5) 1099
 
5.2%

예산금액
Real number (ℝ)

HIGH CORRELATION 

Distinct8261
Distinct (%)82.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22566520
Minimum1
Maximum2.83 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-16T13:18:11.289005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1999926
Q18000000
median18000000
Q332500250
95-th percentile56089100
Maximum2.83 × 108
Range2.83 × 108
Interquartile range (IQR)24500250

Descriptive statistics

Standard deviation18934514
Coefficient of variation (CV)0.83905334
Kurtosis5.619852
Mean22566520
Median Absolute Deviation (MAD)11497985
Skewness1.5811993
Sum2.256652 × 1011
Variance3.5851582 × 1014
MonotonicityNot monotonic
2024-03-16T13:18:11.610722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30000000.0 36
 
0.4%
10000000.0 21
 
0.2%
20000000.0 20
 
0.2%
8000000.0 17
 
0.2%
50000000.0 16
 
0.2%
15000000.0 15
 
0.1%
12000000.0 15
 
0.1%
6000000.0 13
 
0.1%
4000000.0 13
 
0.1%
21000000.0 12
 
0.1%
Other values (8251) 9822
98.2%
ValueCountFrequency (%)
1.0 4
< 0.1%
2500.0 1
 
< 0.1%
7390.0 1
 
< 0.1%
76000.0 1
 
< 0.1%
78000.0 1
 
< 0.1%
90000.0 1
 
< 0.1%
114000.0 2
< 0.1%
158760.0 1
 
< 0.1%
165500.0 1
 
< 0.1%
194000.0 1
 
< 0.1%
ValueCountFrequency (%)
283000000.0 1
< 0.1%
109984680.0 1
< 0.1%
109030000.0 1
< 0.1%
108792160.0 1
< 0.1%
108294860.0 1
< 0.1%
108040120.0 1
< 0.1%
107900000.0 1
< 0.1%
107671730.0 1
< 0.1%
107100000.0 1
< 0.1%
106945280.0 1
< 0.1%

계약방법
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
수의계약
9995 
일반경쟁
 
3
제한경쟁
 
1
2단계경쟁(동시)
 
1

Length

Max length9
Median length4
Mean length4.0005
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
수의계약 9995
> 99.9%
일반경쟁 3
 
< 0.1%
제한경쟁 1
 
< 0.1%
2단계경쟁(동시) 1
 
< 0.1%

Length

2024-03-16T13:18:11.930724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T13:18:12.122614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수의계약 9995
> 99.9%
일반경쟁 3
 
< 0.1%
제한경쟁 1
 
< 0.1%
2단계경쟁(동시 1
 
< 0.1%

낙찰자결정방법
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
최저가격제
9618 
협상
 
368
<NA>
 
14

Length

Max length5
Median length5
Mean length4.8882
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
최저가격제 9618
96.2%
협상 368
 
3.7%
<NA> 14
 
0.1%

Length

2024-03-16T13:18:12.392123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T13:18:12.638408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
최저가격제 9618
96.2%
협상 368
 
3.7%
na 14
 
0.1%

입찰방법
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
총액제
9890 
단가제
 
110

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
총액제 9890
98.9%
단가제 110
 
1.1%

Length

2024-03-16T13:18:12.815907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T13:18:12.975918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
총액제 9890
98.9%
단가제 110
 
1.1%

집행유형
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
구매
9147 
제조
 
570
제조/구매
 
250
기타
 
14
리스
 
11
Other values (2)
 
8

Length

Max length6
Median length2
Mean length2.1011
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
구매 9147
91.5%
제조 570
 
5.7%
제조/구매 250
 
2.5%
기타 14
 
0.1%
리스 11
 
0.1%
공사 6
 
0.1%
공급 2
 
< 0.1%

Length

2024-03-16T13:18:13.160210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T13:18:13.355175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
구매 9147
91.5%
제조 570
 
5.7%
제조/구매 250
 
2.5%
기타 14
 
0.1%
리스 11
 
0.1%
공사 6
 
0.1%
공급 2
 
< 0.1%

입찰결과
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
낙찰
8000 
유찰
1961 
순위확정
 
39

Length

Max length4
Median length2
Mean length2.0078
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row유찰
2nd row낙찰
3rd row낙찰
4th row낙찰
5th row낙찰

Common Values

ValueCountFrequency (%)
낙찰 8000
80.0%
유찰 1961
 
19.6%
순위확정 39
 
0.4%

Length

2024-03-16T13:18:13.616081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T13:18:13.835527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
낙찰 8000
80.0%
유찰 1961
 
19.6%
순위확정 39
 
0.4%

기초예비가격
Real number (ℝ)

HIGH CORRELATION 

Distinct7365
Distinct (%)73.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21881691
Minimum0
Maximum1.36377 × 108
Zeros36
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-16T13:18:14.022422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1600000
Q17500000
median17216796
Q331597000
95-th percentile55310218
Maximum1.36377 × 108
Range1.36377 × 108
Interquartile range (IQR)24097000

Descriptive statistics

Standard deviation18650089
Coefficient of variation (CV)0.85231481
Kurtosis2.4944196
Mean21881691
Median Absolute Deviation (MAD)11304484
Skewness1.3998024
Sum2.1881691 × 1011
Variance3.4782582 × 1014
MonotonicityNot monotonic
2024-03-16T13:18:14.254438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 36
 
0.4%
10000000.0 24
 
0.2%
8000000.0 23
 
0.2%
30000000.0 18
 
0.2%
12000000.0 17
 
0.2%
5000000.0 17
 
0.2%
20000000.0 17
 
0.2%
6000000.0 16
 
0.2%
8800000.0 16
 
0.2%
15000000.0 16
 
0.2%
Other values (7355) 9800
98.0%
ValueCountFrequency (%)
0.0 36
0.4%
90.0 2
 
< 0.1%
184.0 1
 
< 0.1%
340.0 2
 
< 0.1%
350.0 1
 
< 0.1%
500.0 1
 
< 0.1%
510.0 2
 
< 0.1%
553.0 1
 
< 0.1%
580.0 1
 
< 0.1%
590.0 1
 
< 0.1%
ValueCountFrequency (%)
136377000.0 1
< 0.1%
133000000.0 1
< 0.1%
129798000.0 1
< 0.1%
112659000.0 1
< 0.1%
109984680.0 1
< 0.1%
108680000.0 1
< 0.1%
108040120.0 1
< 0.1%
107900000.0 1
< 0.1%
107671730.0 1
< 0.1%
107100000.0 1
< 0.1%

사정율
Text

Distinct58
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-16T13:18:14.672089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length4
Mean length3.9754
Min length3

Characters and Unicode

Total characters39754
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

Unique25 ?
Unique (%)0.2%

Sample

1st row-3~3
2nd row-2~0
3rd row-2~0
4th row-2~2
5th row-3~0
ValueCountFrequency (%)
2~2 4304
43.0%
3~0 2270
22.7%
2~0 1601
 
16.0%
3~3 1030
 
10.3%
0~1 307
 
3.1%
1~1 109
 
1.1%
3~1 94
 
0.9%
3~2 77
 
0.8%
2~1 70
 
0.7%
0~0 42
 
0.4%
Other values (46) 96
 
1.0%
2024-03-16T13:18:15.183189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 10410
26.2%
~ 10000
25.2%
- 9636
24.2%
3 4563
11.5%
0 4279
10.8%
1 733
 
1.8%
. 83
 
0.2%
5 18
 
< 0.1%
6 8
 
< 0.1%
4 8
 
< 0.1%
Other values (3) 16
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20035
50.4%
Math Symbol 10000
25.2%
Dash Punctuation 9636
24.2%
Other Punctuation 83
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 10410
52.0%
3 4563
22.8%
0 4279
21.4%
1 733
 
3.7%
5 18
 
0.1%
6 8
 
< 0.1%
4 8
 
< 0.1%
8 6
 
< 0.1%
7 6
 
< 0.1%
9 4
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 10000
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9636
100.0%
Other Punctuation
ValueCountFrequency (%)
. 83
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39754
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 10410
26.2%
~ 10000
25.2%
- 9636
24.2%
3 4563
11.5%
0 4279
10.8%
1 733
 
1.8%
. 83
 
0.2%
5 18
 
< 0.1%
6 8
 
< 0.1%
4 8
 
< 0.1%
Other values (3) 16
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39754
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 10410
26.2%
~ 10000
25.2%
- 9636
24.2%
3 4563
11.5%
0 4279
10.8%
1 733
 
1.8%
. 83
 
0.2%
5 18
 
< 0.1%
6 8
 
< 0.1%
4 8
 
< 0.1%
Other values (3) 16
 
< 0.1%

낙찰하한율
Real number (ℝ)

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean87.588483
Minimum0
Maximum90
Zeros54
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-16T13:18:15.384708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile88
Q188
median88
Q388
95-th percentile88
Maximum90
Range90
Interquartile range (IQR)0

Descriptive statistics

Standard deviation6.4640731
Coefficient of variation (CV)0.073800492
Kurtosis179.16302
Mean87.588483
Median Absolute Deviation (MAD)0
Skewness-13.436471
Sum875884.83
Variance41.784241
MonotonicityNot monotonic
2024-03-16T13:18:15.547662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
88.0 9589
95.9%
90.0 323
 
3.2%
0.0 54
 
0.5%
87.995 17
 
0.2%
87.745 16
 
0.2%
82.995 1
 
< 0.1%
ValueCountFrequency (%)
0.0 54
 
0.5%
82.995 1
 
< 0.1%
87.745 16
 
0.2%
87.995 17
 
0.2%
88.0 9589
95.9%
90.0 323
 
3.2%
ValueCountFrequency (%)
90.0 323
 
3.2%
88.0 9589
95.9%
87.995 17
 
0.2%
87.745 16
 
0.2%
82.995 1
 
< 0.1%
0.0 54
 
0.5%

예정가격
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct8003
Distinct (%)80.0%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean17871091
Minimum0
Maximum1.298943 × 108
Zeros1961
Zeros (%)19.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-16T13:18:15.738158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12508152.2
median12287192
Q327852310
95-th percentile51931224
Maximum1.298943 × 108
Range1.298943 × 108
Interquartile range (IQR)25344158

Descriptive statistics

Standard deviation18682530
Coefficient of variation (CV)1.0454052
Kurtosis2.4864851
Mean17871091
Median Absolute Deviation (MAD)11883028
Skewness1.4434132
Sum1.7867517 × 1011
Variance3.4903694 × 1014
MonotonicityNot monotonic
2024-03-16T13:18:16.033835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1961
 
19.6%
9623532.0 2
 
< 0.1%
47268731.0 2
 
< 0.1%
28465175.0 2
 
< 0.1%
6244354.0 2
 
< 0.1%
5420408.0 2
 
< 0.1%
34993177.0 2
 
< 0.1%
3941310.0 2
 
< 0.1%
25195702.0 2
 
< 0.1%
5360353.0 2
 
< 0.1%
Other values (7993) 8019
80.2%
ValueCountFrequency (%)
0.0 1961
19.6%
181.33 1
 
< 0.1%
345.93 1
 
< 0.1%
487.16 1
 
< 0.1%
504.52 1
 
< 0.1%
505.83 1
 
< 0.1%
571.35 1
 
< 0.1%
585.37 1
 
< 0.1%
825.0 1
 
< 0.1%
967.24 1
 
< 0.1%
ValueCountFrequency (%)
129894299.0 1
< 0.1%
112640713.0 1
< 0.1%
109662978.0 1
< 0.1%
108569894.0 1
< 0.1%
107332429.0 1
< 0.1%
106725358.0 1
< 0.1%
106715666.0 1
< 0.1%
106621299.0 1
< 0.1%
106521875.0 1
< 0.1%
105832579.0 1
< 0.1%

Interactions

2024-03-16T13:18:03.604835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:01.324136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:02.212010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:02.835081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:03.749561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:01.629226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:02.387490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:03.015180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:03.949384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:01.843465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:02.551953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:03.274124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:04.094736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:02.007421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:02.687247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:03.461354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-16T13:18:16.219587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
예산금액계약방법낙찰자결정방법입찰방법집행유형입찰결과기초예비가격사정율낙찰하한율예정가격
예산금액1.0000.0000.1030.0420.1240.0000.9760.2260.0000.939
계약방법0.0001.0000.0000.0000.0140.0250.0000.5850.2340.000
낙찰자결정방법0.1030.0001.0000.0240.5170.1450.2120.6560.0860.140
입찰방법0.0420.0000.0241.0000.0970.0770.1380.0000.0000.126
집행유형0.1240.0140.5170.0971.0000.2050.1480.3260.0690.063
입찰결과0.0000.0250.1450.0770.2051.0000.0780.2740.0770.492
기초예비가격0.9760.0000.2120.1380.1480.0781.0000.2600.0590.969
사정율0.2260.5850.6560.0000.3260.2740.2601.0000.8930.263
낙찰하한율0.0000.2340.0860.0000.0690.0770.0590.8931.0000.061
예정가격0.9390.0000.1400.1260.0630.4920.9690.2630.0611.000
2024-03-16T13:18:16.431787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
낙찰자결정방법입찰결과입찰방법계약방법집행유형
낙찰자결정방법1.0000.2390.0150.0000.555
입찰결과0.2391.0000.1280.0230.140
입찰방법0.0150.1281.0000.0000.104
계약방법0.0000.0230.0001.0000.010
집행유형0.5550.1400.1040.0101.000
2024-03-16T13:18:16.614853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
예산금액기초예비가격낙찰하한율예정가격계약방법낙찰자결정방법입찰방법집행유형입찰결과
예산금액1.0000.963-0.0880.6600.0000.1260.0520.0790.000
기초예비가격0.9631.000-0.0510.6880.0000.1630.1060.0750.046
낙찰하한율-0.088-0.0511.0000.0040.1550.0550.0000.0740.128
예정가격0.6600.6880.0041.0000.0000.1070.0960.0320.340
계약방법0.0000.0000.1550.0001.0000.0000.0000.0100.023
낙찰자결정방법0.1260.1630.0550.1070.0001.0000.0150.5550.239
입찰방법0.0520.1060.0000.0960.0000.0151.0000.1040.128
집행유형0.0790.0750.0740.0320.0100.5550.1041.0000.140
입찰결과0.0000.0460.1280.3400.0230.2390.1280.1401.000

Missing values

2024-03-16T13:18:04.316479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-16T13:18:04.830577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

견적서제출마감일시판단번호공고번호입찰건명발주기관예산금액계약방법낙찰자결정방법입찰방법집행유형입찰결과기초예비가격사정율낙찰하한율예정가격
36612017-11-06 10:0037731HCL0093-1항-17-068,069 진공체혈바늘 등 86종공군사관학교48380520.0수의계약최저가격제총액제구매유찰46971370.0-3~388.00.0
189812021-06-21 10:0024371SDQ0049-121-45-회로카드 조립체 등 8종해군제2수리창8468100.0수의계약최저가격제총액제구매낙찰8468100.0-2~088.08395368.0
158532020-09-11 10:0037303SCF0283-1모니터, 텔레비전식 1종 구매해군군수사령부14800000.0수의계약최저가격제총액제구매낙찰14800000.0-2~088.014687375.0
239322022-10-04 10:0039890MCX0042-1소방기구(분말소화기 등 13종) 구매자운대근무지원단4467000.0수의계약최저가격제총액제구매낙찰4379410.0-2~288.04412549.0
61312018-05-24 10:0015862SDQ0043-2콘센트릭 밸브 조립체 등 21종해군제2수리창25957740.0수의계약최저가격제총액제구매낙찰25950000.0-3~088.025463134.0
163082020-10-27 10:0042789SFM0102-1쿼드콘(QUADCON) 구매제3170부대94200000.0수의계약최저가격제총액제구매낙찰94200000.0-2~088.093451980.0
279842023-08-25 10:0036386LCZ0043-100부대 치장창고 물자 구매(파레트)동원전력사령부22000000.0수의계약최저가격제총액제구매낙찰21568627.0-2~288.021743088.0
43232017-12-08 10:0044433LMQ0005-1취사식당신축 알루미늄창호 제조설치제7297부대22197850.0수의계약최저가격제총액제구매낙찰22197850.0-3~088.021908639.0
96832019-04-08 10:0010375LHR0039-119년 석면 건축물 DB구축 용역제5019부대9553000.0수의계약최저가격제총액제구매낙찰9553000.0-3~088.09395739.0
259722023-03-30 10:0011011DSS0029-1레이저 거리측정기 등 7종 6세트 구매국군제1068부대3630000.0수의계약최저가격제총액제구매낙찰3627000.0-2~288.03631768.0
견적서제출마감일시판단번호공고번호입찰건명발주기관예산금액계약방법낙찰자결정방법입찰방법집행유형입찰결과기초예비가격사정율낙찰하한율예정가격
219552022-04-19 10:3013007SCG0056-1모조지 80g 등 41종 구매해군본부33325560.0수의계약최저가격제총액제구매낙찰32650000.0-2~288.032783397.0
191792021-07-13 10:0029231SCP0115-1안전모 충격 체험장치 등 4종 구매제8385부대6500000.0수의계약최저가격제총액제구매낙찰6300000.0-2~288.06352642.0
243262022-10-31 10:0044604SFL0086-1도서(역행자 등 455종) 구매제3283부대11642100.0수의계약최저가격제총액제구매낙찰11642100.00~190.011676932.0
244582022-11-09 10:0042443SCK0115-2다지인양슬링 1세트 구매해군교육사령부6185000.0수의계약최저가격제총액제구매유찰6060000.0-2~288.00.0
181192021-04-20 10:0013827SCP0074-1철띠 등 35종 구매제8385부대15256000.0수의계약최저가격제총액제구매낙찰15200000.0-2~088.015084288.0
264932023-05-02 10:0016038SDQ0032-1시험기,경도계 등 10종 구매해군제2수리창24584900.0수의계약최저가격제총액제구매낙찰24580000.0-2~288.024550927.0
72012018-08-14 10:0028725LGN0014-118-3차 여단 전산용품 구매제5925부대10410800.0수의계약최저가격제총액제구매낙찰10107570.0-3~388.010063285.0
227632022-06-15 10:0022924LPK0022-122년 대대급 안전보호세트 구매제8기동사단63710000.0수의계약최저가격제총액제구매낙찰62460780.0-2~288.062601035.0
13592017-05-01 10:0013947SFL0060-1헬멧 등 10품목 구매제3283부대57703000.0수의계약최저가격제총액제구매낙찰56022329.0-3~388.055876701.0
127112019-11-25 10:0045070SCG0116-1포토용지 등 178종해군본부32582450.0수의계약최저가격제총액제구매낙찰30389000.0-2~288.030316651.0

Duplicate rows

Most frequently occurring

견적서제출마감일시판단번호공고번호입찰건명발주기관예산금액계약방법낙찰자결정방법입찰방법집행유형입찰결과기초예비가격사정율낙찰하한율예정가격# duplicates
02017-08-17 10:0027531SCF0315-2인쇄회로판 1종해군군수사령부4178000.0수의계약최저가격제총액제구매낙찰4170000.0-3~088.04085831.02
12017-09-21 10:0032403HDL0011-117-170,171,172,177(자동차 타이어 등 197품목)공군제16전투비행단35726380.0수의계약최저가격제총액제구매낙찰34685800.0-3~388.034555541.02
22017-10-27 10:0036108LHD0022-1의약품 및 의무장비 소모품 구매(16차)제7162부대7553570.0수의계약최저가격제총액제구매낙찰7553570.0-3~088.07437024.02
32018-02-12 10:303558HDG0001-1에폭시 등 33종(18-10)공군제10전투비행단11281250.0수의계약최저가격제총액제구매낙찰11281250.0-3~088.011164289.02
42018-06-07 10:0019107SCF0254-1회로 차단기 1종해군군수사령부4980000.0수의계약최저가격제총액제구매낙찰4700000.0-3~388.04742740.02
52018-06-12 10:0019839SCF0270-1개스킷 등 2종해군군수사령부4050000.0수의계약최저가격제총액제구매낙찰4000000.0-3~088.03941310.02
62018-06-21 10:0021343SFG0110-1언어의 온도 등 57품목(도서)제9181부대45405400.0수의계약최저가격제총액제구매낙찰45405400.00~190.045571670.02
72018-06-27 10:0022571MDS0033-1항온항습기 필터 납품제3707부대15972000.0수의계약최저가격제총액제구매낙찰15505592.0-3~388.015261292.02
82018-08-16 10:0029008SCF0404-1브래킷 설치용 등 2종해군군수사령부2222800.0수의계약최저가격제총액제구매낙찰2200000.0-3~088.02174293.02
92019-03-15 10:007012SCF0101-1조명등,전기식 1종해군군수사령부6400000.0수의계약최저가격제총액제구매낙찰6400000.0-3~088.06299890.02