Overview

Dataset statistics

Number of variables7
Number of observations8236
Missing cells27
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory466.6 KiB
Average record size in memory58.0 B

Variable types

Numeric2
Categorical2
Text2
DateTime1

Dataset

Description보령시에서 물품을 수의 계약한 정보(관서명, 계약방법 ,계약명, 계약금액, 계약일, 계약상대자)에 관한 현황입니다.
Author충청남도 보령시
URLhttps://www.data.go.kr/data/15090077/fileData.do

Alerts

계약방법 has constant value ""Constant
관서명 is highly imbalanced (55.7%)Imbalance
계약금액 is highly skewed (γ1 = 76.92523066)Skewed
번호 has unique valuesUnique

Reproduction

Analysis started2024-03-14 11:20:46.692527
Analysis finished2024-03-14 11:20:49.683512
Duration2.99 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct8236
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4118.5
Minimum1
Maximum8236
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size72.5 KiB
2024-03-14T20:20:49.892169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile412.75
Q12059.75
median4118.5
Q36177.25
95-th percentile7824.25
Maximum8236
Range8235
Interquartile range (IQR)4117.5

Descriptive statistics

Standard deviation2377.6727
Coefficient of variation (CV)0.57731522
Kurtosis-1.2
Mean4118.5
Median Absolute Deviation (MAD)2059
Skewness0
Sum33919966
Variance5653327.7
MonotonicityStrictly increasing
2024-03-14T20:20:50.336871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
5535 1
 
< 0.1%
5501 1
 
< 0.1%
5500 1
 
< 0.1%
5499 1
 
< 0.1%
5498 1
 
< 0.1%
5497 1
 
< 0.1%
5496 1
 
< 0.1%
5495 1
 
< 0.1%
5494 1
 
< 0.1%
Other values (8226) 8226
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
8236 1
< 0.1%
8235 1
< 0.1%
8234 1
< 0.1%
8233 1
< 0.1%
8232 1
< 0.1%
8231 1
< 0.1%
8230 1
< 0.1%
8229 1
< 0.1%
8228 1
< 0.1%
8227 1
< 0.1%

관서명
Categorical

IMBALANCE 

Distinct23
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size64.5 KiB
본청
5424 
보건소
1280 
농업기술센터
 
221
남포면
 
176
천북면
 
166
Other values (18)
969 

Length

Max length9
Median length2
Mean length2.5528169
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
본청 5424
65.9%
보건소 1280
 
15.5%
농업기술센터 221
 
2.7%
남포면 176
 
2.1%
천북면 166
 
2.0%
대천3동 147
 
1.8%
문화체육관리사업소 103
 
1.3%
대천2동 88
 
1.1%
성주면 79
 
1.0%
주산면 74
 
0.9%
Other values (13) 478
 
5.8%

Length

2024-03-14T20:20:50.783108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
본청 5424
65.9%
보건소 1280
 
15.5%
농업기술센터 221
 
2.7%
남포면 176
 
2.1%
천북면 166
 
2.0%
대천3동 147
 
1.8%
문화체육관리사업소 103
 
1.3%
대천2동 88
 
1.1%
성주면 79
 
1.0%
주산면 74
 
0.9%
Other values (13) 478
 
5.8%

계약방법
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size64.5 KiB
수의1인견적
8236 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row수의1인견적
2nd row수의1인견적
3rd row수의1인견적
4th row수의1인견적
5th row수의1인견적

Common Values

ValueCountFrequency (%)
수의1인견적 8236
100.0%

Length

2024-03-14T20:20:51.198685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T20:20:51.506484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수의1인견적 8236
100.0%

계약명
Text

Distinct7527
Distinct (%)91.4%
Missing0
Missing (%)0.0%
Memory size64.5 KiB
2024-03-14T20:20:52.499607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length44
Mean length20.394366
Min length3

Characters and Unicode

Total characters167968
Distinct characters870
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks9 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7072 ?
Unique (%)85.9%

Sample

1st row2014년 방과후공부방 아동 석식 식자재 구입
2nd row2014년 재가복지 밑반찬 재료비
3rd row세외수입콜센터운영위한 컴퓨터 구입
4th row장고도 위생매립장 음식물 쓰레기 처리기 구입
5th row종량제 규격봉투(일반-100ℓ) 제작
ValueCountFrequency (%)
구입 3466
 
10.4%
및 604
 
1.8%
제작 552
 
1.6%
설치 415
 
1.2%
관급자재 412
 
1.2%
등 284
 
0.8%
물품 196
 
0.6%
설치공사 159
 
0.5%
운영 147
 
0.4%
배수로 143
 
0.4%
Other values (9161) 27079
80.9%
2024-03-14T20:20:54.220740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25222
 
15.0%
구 6168
 
3.7%
입 5213
 
3.1%
( 3341
 
2.0%
) 3338
 
2.0%
관 2898
 
1.7%
사 2775
 
1.7%
자 2474
 
1.5%
기 2212
 
1.3%
공 2009
 
1.2%
Other values (860) 112318
66.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 126449
75.3%
Space Separator 25222
 
15.0%
Decimal Number 5363
 
3.2%
Open Punctuation 3709
 
2.2%
Close Punctuation 3702
 
2.2%
Uppercase Letter 1795
 
1.1%
Other Punctuation 660
 
0.4%
Dash Punctuation 491
 
0.3%
Connector Punctuation 282
 
0.2%
Lowercase Letter 257
 
0.2%
Other values (4) 38
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 6168
 
4.9%
입 5213
 
4.1%
관 2898
 
2.3%
사 2775
 
2.2%
자 2474
 
2.0%
기 2212
 
1.7%
공 2009
 
1.6%
재 2002
 
1.6%
보 1965
 
1.6%
제 1928
 
1.5%
Other values (776) 96805
76.6%
Uppercase Letter
ValueCountFrequency (%)
C 280
15.6%
D 217
12.1%
T 185
10.3%
V 174
9.7%
E 114
 
6.4%
B 108
 
6.0%
P 103
 
5.7%
I 97
 
5.4%
L 88
 
4.9%
A 72
 
4.0%
Other values (14) 357
19.9%
Lowercase Letter
ValueCountFrequency (%)
ℓ 63
24.5%
e 35
13.6%
d 18
 
7.0%
l 17
 
6.6%
c 17
 
6.6%
o 12
 
4.7%
p 11
 
4.3%
a 11
 
4.3%
v 9
 
3.5%
f 9
 
3.5%
Other values (14) 55
21.4%
Decimal Number
ValueCountFrequency (%)
2 1746
32.6%
1 1053
19.6%
0 955
17.8%
3 507
 
9.5%
4 241
 
4.5%
5 217
 
4.0%
9 195
 
3.6%
6 176
 
3.3%
7 148
 
2.8%
8 125
 
2.3%
Other Punctuation
ValueCountFrequency (%)
, 507
76.8%
. 64
 
9.7%
· 45
 
6.8%
" 19
 
2.9%
/ 15
 
2.3%
* 6
 
0.9%
% 2
 
0.3%
; 1
 
0.2%
: 1
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 3341
90.1%
[ 347
 
9.4%
『 16
 
0.4%
「 5
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 3338
90.2%
] 343
 
9.3%
』 16
 
0.4%
」 5
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 20
57.1%
+ 14
40.0%
∼ 1
 
2.9%
Space Separator
ValueCountFrequency (%)
25222
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 491
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 282
100.0%
Modifier Symbol
ValueCountFrequency (%)
˙ 1
100.0%
Other Symbol
ValueCountFrequency (%)
㎥ 1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 126446
75.3%
Common 39529
 
23.5%
Latin 1990
 
1.2%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 6168
 
4.9%
입 5213
 
4.1%
관 2898
 
2.3%
사 2775
 
2.2%
자 2474
 
2.0%
기 2212
 
1.7%
공 2009
 
1.6%
재 2002
 
1.6%
보 1965
 
1.6%
제 1928
 
1.5%
Other values (775) 96802
76.6%
Latin
ValueCountFrequency (%)
C 280
14.1%
D 217
 
10.9%
T 185
 
9.3%
V 174
 
8.7%
E 114
 
5.7%
B 108
 
5.4%
P 103
 
5.2%
I 97
 
4.9%
L 88
 
4.4%
A 72
 
3.6%
Other values (38) 552
27.7%
Common
ValueCountFrequency (%)
25222
63.8%
( 3341
 
8.5%
) 3338
 
8.4%
2 1746
 
4.4%
1 1053
 
2.7%
0 955
 
2.4%
3 507
 
1.3%
, 507
 
1.3%
- 491
 
1.2%
[ 347
 
0.9%
Other values (26) 2022
 
5.1%
Han
ValueCountFrequency (%)
愛 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 126446
75.3%
ASCII 41365
 
24.6%
None 87
 
0.1%
Letterlike Symbols 63
 
< 0.1%
CJK 3
 
< 0.1%
Math Operators 1
 
< 0.1%
Modifier Letters 1
 
< 0.1%
CJK Compat 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25222
61.0%
( 3341
 
8.1%
) 3338
 
8.1%
2 1746
 
4.2%
1 1053
 
2.5%
0 955
 
2.3%
3 507
 
1.2%
, 507
 
1.2%
- 491
 
1.2%
[ 347
 
0.8%
Other values (64) 3858
 
9.3%
Hangul
ValueCountFrequency (%)
구 6168
 
4.9%
입 5213
 
4.1%
관 2898
 
2.3%
사 2775
 
2.2%
자 2474
 
2.0%
기 2212
 
1.7%
공 2009
 
1.6%
재 2002
 
1.6%
보 1965
 
1.6%
제 1928
 
1.5%
Other values (775) 96802
76.6%
Letterlike Symbols
ValueCountFrequency (%)
ℓ 63
100.0%
None
ValueCountFrequency (%)
· 45
51.7%
』 16
 
18.4%
『 16
 
18.4%
」 5
 
5.7%
「 5
 
5.7%
CJK
ValueCountFrequency (%)
愛 3
100.0%
Math Operators
ValueCountFrequency (%)
∼ 1
100.0%
Modifier Letters
ValueCountFrequency (%)
˙ 1
100.0%
CJK Compat
ValueCountFrequency (%)
㎥ 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

계약금액
Real number (ℝ)

SKEWED 

Distinct5175
Distinct (%)62.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15488410
Minimum29880
Maximum1.256075 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size72.5 KiB
2024-03-14T20:20:54.647218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum29880
5-th percentile710000
Q12830700
median5895500
Q312481250
95-th percentile43130000
Maximum1.256075 × 1010
Range1.256072 × 1010
Interquartile range (IQR)9650550

Descriptive statistics

Standard deviation1.4670088 × 108
Coefficient of variation (CV)9.4716552
Kurtosis6508.6146
Mean15488410
Median Absolute Deviation (MAD)3705000
Skewness76.925231
Sum1.2756254 × 1011
Variance2.1521147 × 1016
MonotonicityNot monotonic
2024-03-14T20:20:55.106345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3000000 60
 
0.7%
19800000 45
 
0.5%
2000000 45
 
0.5%
3200000 45
 
0.5%
5000000 41
 
0.5%
18000000 40
 
0.5%
6000000 31
 
0.4%
9000000 31
 
0.4%
2200000 30
 
0.4%
5700000 29
 
0.4%
Other values (5165) 7839
95.2%
ValueCountFrequency (%)
29880 1
< 0.1%
36370 1
< 0.1%
50000 1
< 0.1%
55000 1
< 0.1%
55290 2
< 0.1%
58000 1
< 0.1%
67600 1
< 0.1%
74000 1
< 0.1%
77000 1
< 0.1%
80000 2
< 0.1%
ValueCountFrequency (%)
12560750000 1
< 0.1%
2448000000 1
< 0.1%
1709000000 1
< 0.1%
1226596930 1
< 0.1%
1119000000 1
< 0.1%
923571350 1
< 0.1%
782480000 1
< 0.1%
565412000 1
< 0.1%
534476480 1
< 0.1%
469480000 1
< 0.1%

계약일
Date

Distinct2313
Distinct (%)28.1%
Missing0
Missing (%)0.0%
Memory size64.5 KiB
Minimum2014-01-01 00:00:00
Maximum2024-01-27 00:00:00
2024-03-14T20:20:55.509908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:20:55.944295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

계약상대자
Text

Distinct1608
Distinct (%)19.6%
Missing27
Missing (%)0.3%
Memory size64.5 KiB
2024-03-14T20:20:57.109036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length24
Mean length6.720307
Min length2

Characters and Unicode

Total characters55167
Distinct characters560
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

Unique918 ?
Unique (%)11.2%

Sample

1st row대천농업협동조합
2nd row대천농업협동조합
3rd row조달청
4th row조달청
5th row조달청
ValueCountFrequency (%)
대전지방조달청 1814
 
20.2%
주식회사 377
 
4.2%
주)거산 156
 
1.7%
주)플러스메디칼 125
 
1.4%
안진팜 120
 
1.3%
동일사 95
 
1.1%
자)제중약품 94
 
1.0%
리바트 92
 
1.0%
주)광명프라자 88
 
1.0%
보령사무용가구 88
 
1.0%
Other values (1645) 5929
66.0%
2024-03-14T20:20:58.592557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 2438
 
4.4%
주 2277
 
4.1%
지 2246
 
4.1%
전 2230
 
4.0%
조 2109
 
3.8%
청 2102
 
3.8%
달 1965
 
3.6%
방 1956
 
3.5%
( 1904
 
3.5%
) 1902
 
3.4%
Other values (550) 34038
61.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 50189
91.0%
Open Punctuation 1904
 
3.5%
Close Punctuation 1902
 
3.4%
Space Separator 769
 
1.4%
Uppercase Letter 315
 
0.6%
Other Punctuation 56
 
0.1%
Lowercase Letter 15
 
< 0.1%
Decimal Number 12
 
< 0.1%
Other Symbol 4
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 2438
 
4.9%
주 2277
 
4.5%
지 2246
 
4.5%
전 2230
 
4.4%
조 2109
 
4.2%
청 2102
 
4.2%
달 1965
 
3.9%
방 1956
 
3.9%
사 1342
 
2.7%
이 794
 
1.6%
Other values (511) 30730
61.2%
Uppercase Letter
ValueCountFrequency (%)
N 39
12.4%
S 35
11.1%
E 30
9.5%
B 29
9.2%
C 25
7.9%
G 23
 
7.3%
W 20
 
6.3%
H 20
 
6.3%
A 19
 
6.0%
K 17
 
5.4%
Other values (11) 58
18.4%
Lowercase Letter
ValueCountFrequency (%)
s 4
26.7%
w 4
26.7%
n 2
13.3%
d 2
13.3%
a 2
13.3%
h 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
. 38
67.9%
, 13
 
23.2%
/ 4
 
7.1%
& 1
 
1.8%
Decimal Number
ValueCountFrequency (%)
2 10
83.3%
5 1
 
8.3%
4 1
 
8.3%
Open Punctuation
ValueCountFrequency (%)
( 1904
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1902
100.0%
Space Separator
ValueCountFrequency (%)
769
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 50193
91.0%
Common 4644
 
8.4%
Latin 330
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 2438
 
4.9%
주 2277
 
4.5%
지 2246
 
4.5%
전 2230
 
4.4%
조 2109
 
4.2%
청 2102
 
4.2%
달 1965
 
3.9%
방 1956
 
3.9%
사 1342
 
2.7%
이 794
 
1.6%
Other values (512) 30734
61.2%
Latin
ValueCountFrequency (%)
N 39
11.8%
S 35
10.6%
E 30
9.1%
B 29
 
8.8%
C 25
 
7.6%
G 23
 
7.0%
W 20
 
6.1%
H 20
 
6.1%
A 19
 
5.8%
K 17
 
5.2%
Other values (17) 73
22.1%
Common
ValueCountFrequency (%)
( 1904
41.0%
) 1902
41.0%
769
16.6%
. 38
 
0.8%
, 13
 
0.3%
2 10
 
0.2%
/ 4
 
0.1%
& 1
 
< 0.1%
5 1
 
< 0.1%
- 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 50189
91.0%
ASCII 4974
 
9.0%
None 4
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 2438
 
4.9%
주 2277
 
4.5%
지 2246
 
4.5%
전 2230
 
4.4%
조 2109
 
4.2%
청 2102
 
4.2%
달 1965
 
3.9%
방 1956
 
3.9%
사 1342
 
2.7%
이 794
 
1.6%
Other values (511) 30730
61.2%
ASCII
ValueCountFrequency (%)
( 1904
38.3%
) 1902
38.2%
769
15.5%
N 39
 
0.8%
. 38
 
0.8%
S 35
 
0.7%
E 30
 
0.6%
B 29
 
0.6%
C 25
 
0.5%
G 23
 
0.5%
Other values (28) 180
 
3.6%
None
ValueCountFrequency (%)
㈜ 4
100.0%

Interactions

2024-03-14T20:20:48.494798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:20:47.979034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:20:48.756624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:20:48.228527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T20:20:58.751970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호관서명계약금액
번호1.0000.4010.040
관서명0.4011.0000.000
계약금액0.0400.0001.000
2024-03-14T20:20:58.898959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호계약금액관서명
번호1.0000.0940.160
계약금액0.0941.0000.000
관서명0.1600.0001.000

Missing values

2024-03-14T20:20:49.125951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T20:20:49.516673image/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

번호관서명계약방법계약명계약금액계약일계약상대자
01본청수의1인견적2014년 방과후공부방 아동 석식 식자재 구입374400002014-01-01대천농업협동조합
12본청수의1인견적2014년 재가복지 밑반찬 재료비201600002014-01-01대천농업협동조합
23본청수의1인견적세외수입콜센터운영위한 컴퓨터 구입27145802014-01-03조달청
34본청수의1인견적장고도 위생매립장 음식물 쓰레기 처리기 구입139713002014-01-03조달청
45본청수의1인견적종량제 규격봉투(일반-100ℓ) 제작74922402014-01-03조달청
56대천3동수의1인견적이동식 서가 구입43840002014-01-06대전지방조달청
67대천3동수의1인견적회의실 강연대 및 사회대 구입8947002014-01-06대전지방조달청
78대천3동수의1인견적TV구입21700002014-01-06대전지방조달청
89본청수의1인견적종량제 규격봉투(음식물-20,재사용20)제작117511102014-01-06조달청
910대천3동수의1인견적동장실 집기비품 구입76880002014-01-06대전지방조달청
번호관서명계약방법계약명계약금액계약일계약상대자
82268227본청수의1인견적1월 보령시립도서관 희망도서구입(2023-12월접수분)21793902024-01-16정인문고 서점
82278228본청수의1인견적건축신고팀 방한복 구입14250002024-01-18보령아이더
82288229본청수의1인견적토지이용남북부팀 방한복 구입28500002024-01-18보령아이더
82298230본청수의1인견적한파쉼터 방한이불 구입95000002024-01-18영산업
82308231보건소수의1인견적임산부 건강관리실 운영 물품 구입43600002024-01-18주식회사 이론친구들
82318232본청수의1인견적의회청사 군소음보상 검토실 벽걸이 에어컨 구입12150502024-01-19삼보이엔지(주)
82328233보건소수의1인견적우울증 선별검사 홍보물품 구입72000002024-01-23(주)플러스메디칼
82338234원산출장소수의1인견적트렉터 제설장비 구입194700002024-01-24우리기계상사(대동공업보령대리점)
82348235본청수의1인견적사무용 가구 구입 (홍보미디어실, 새마을공동체과, 해양정책과, 관광과, 열린민원과, 회계과)62130002024-01-24리바트.보령사무용가구
82358236남포면수의1인견적봉덕1리 생활체육시설 설치공사87935002024-01-27대전지방조달청