Overview

Dataset statistics

Number of variables20
Number of observations218
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory35.3 KiB
Average record size in memory165.6 B

Variable types

Numeric5
Text5
Categorical5
DateTime5

Dataset

Description시흥도시공사에서 체결한 500만원 이상의 용역계약 현황입니다. 각종 시스템 및 장비, 설비의 유지관리계약을 비롯하여 연구용역, 고객만족도 조사 등과 관련된 계약이 포함됩니다. 계약시기 및 지출금액 등이 기재되어 있습니다.
Author시흥도시공사
URLhttps://www.data.go.kr/data/15098958/fileData.do

Alerts

수요기관명 has constant value ""Constant
계약기관 has constant value ""Constant
용역현장 has constant value ""Constant
계약금액 is highly overall correlated with 낙찰률 and 2 other fieldsHigh correlation
낙찰률 is highly overall correlated with 계약금액 and 1 other fieldsHigh correlation
낙찰금액 is highly overall correlated with 계약금액 and 3 other fieldsHigh correlation
신규장기구분 is highly overall correlated with 낙찰금액High correlation
계약방법 is highly overall correlated with 계약금액 and 1 other fieldsHigh correlation
신규장기구분 is highly imbalanced (89.5%)Imbalance
계약방법 is highly imbalanced (61.1%)Imbalance
번호 has unique valuesUnique
계약번호 has unique valuesUnique
용역명 has unique valuesUnique
낙찰률 has 176 (80.7%) zerosZeros
낙찰금액 has 177 (81.2%) zerosZeros

Reproduction

Analysis started2024-03-23 05:26:28.142132
Analysis finished2024-03-23 05:26:41.000173
Duration12.86 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct218
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean109.5
Minimum1
Maximum218
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-03-23T05:26:41.216951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile11.85
Q155.25
median109.5
Q3163.75
95-th percentile207.15
Maximum218
Range217
Interquartile range (IQR)108.5

Descriptive statistics

Standard deviation63.075352
Coefficient of variation (CV)0.57603061
Kurtosis-1.2
Mean109.5
Median Absolute Deviation (MAD)54.5
Skewness0
Sum23871
Variance3978.5
MonotonicityStrictly increasing
2024-03-23T05:26:41.606629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
151 1
 
0.5%
140 1
 
0.5%
141 1
 
0.5%
142 1
 
0.5%
143 1
 
0.5%
144 1
 
0.5%
145 1
 
0.5%
146 1
 
0.5%
147 1
 
0.5%
Other values (208) 208
95.4%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
218 1
0.5%
217 1
0.5%
216 1
0.5%
215 1
0.5%
214 1
0.5%
213 1
0.5%
212 1
0.5%
211 1
0.5%
210 1
0.5%
209 1
0.5%

계약번호
Text

UNIQUE 

Distinct218
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-03-23T05:26:42.212749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length10.889908
Min length8

Characters and Unicode

Total characters2374
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique218 ?
Unique (%)100.0%

Sample

1st row20201218118
2nd row2021010077E
3rd row202101007AF
4th row202101007C3
5th row202101020C8
ValueCountFrequency (%)
20201218118 1
 
0.5%
2023010189c 1
 
0.5%
20230107346 1
 
0.5%
20230112af7 1
 
0.5%
20230107491 1
 
0.5%
20230107529 1
 
0.5%
20230107730 1
 
0.5%
20230109051 1
 
0.5%
20230109ac9 1
 
0.5%
2023010a352 1
 
0.5%
Other values (208) 208
95.4%
2024-03-23T05:26:43.251835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 630
26.5%
2 618
26.0%
1 258
10.9%
3 166
 
7.0%
5 87
 
3.7%
4 72
 
3.0%
7 69
 
2.9%
6 57
 
2.4%
E 57
 
2.4%
A 56
 
2.4%
Other values (8) 304
12.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2063
86.9%
Uppercase Letter 297
 
12.5%
Other Punctuation 7
 
0.3%
Math Symbol 7
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 630
30.5%
2 618
30.0%
1 258
12.5%
3 166
 
8.0%
5 87
 
4.2%
4 72
 
3.5%
7 69
 
3.3%
6 57
 
2.8%
9 56
 
2.7%
8 50
 
2.4%
Uppercase Letter
ValueCountFrequency (%)
E 57
19.2%
A 56
18.9%
B 50
16.8%
C 47
15.8%
D 44
14.8%
F 43
14.5%
Other Punctuation
ValueCountFrequency (%)
. 7
100.0%
Math Symbol
ValueCountFrequency (%)
+ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2077
87.5%
Latin 297
 
12.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 630
30.3%
2 618
29.8%
1 258
12.4%
3 166
 
8.0%
5 87
 
4.2%
4 72
 
3.5%
7 69
 
3.3%
6 57
 
2.7%
9 56
 
2.7%
8 50
 
2.4%
Other values (2) 14
 
0.7%
Latin
ValueCountFrequency (%)
E 57
19.2%
A 56
18.9%
B 50
16.8%
C 47
15.8%
D 44
14.8%
F 43
14.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2374
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 630
26.5%
2 618
26.0%
1 258
10.9%
3 166
 
7.0%
5 87
 
3.7%
4 72
 
3.0%
7 69
 
2.9%
6 57
 
2.4%
E 57
 
2.4%
A 56
 
2.4%
Other values (8) 304
12.8%

용역명
Text

UNIQUE 

Distinct218
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-03-23T05:26:43.784607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length37
Mean length26.756881
Min length12

Characters and Unicode

Total characters5833
Distinct characters372
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

Unique218 ?
Unique (%)100.0%

Sample

1st row2021년 시흥도시공사 정화조 및 오수처리시설 관리용역(통합)_긴급
2nd row2021년 시흥그린센터 비산재 고형화물 위탁처리 용역(일반매립)
3rd row2021년 시흥그린센터 바닥재 최종처분 용역(일반매립)
4th row2021년 시흥그린센터 바닥재 위탁처리 용역(재활용)_재공고
5th row2021년 상반기 공공청사 왁스걸레 교체용역
ValueCountFrequency (%)
용역 124
 
10.3%
2023년 46
 
3.8%
및 42
 
3.5%
시흥그린센터 33
 
2.7%
2022년 27
 
2.2%
시흥도시공사 26
 
2.2%
2021년 25
 
2.1%
공사 18
 
1.5%
환경미화타운 17
 
1.4%
위탁처리 15
 
1.2%
Other values (491) 830
69.0%
2024-03-23T05:26:44.938548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
985
 
16.9%
2 243
 
4.2%
용 206
 
3.5%
역 193
 
3.3%
시 172
 
2.9%
0 106
 
1.8%
공 103
 
1.8%
년 101
 
1.7%
사 96
 
1.6%
리 79
 
1.4%
Other values (362) 3549
60.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4190
71.8%
Space Separator 985
 
16.9%
Decimal Number 460
 
7.9%
Uppercase Letter 60
 
1.0%
Open Punctuation 57
 
1.0%
Close Punctuation 56
 
1.0%
Other Punctuation 15
 
0.3%
Dash Punctuation 5
 
0.1%
Connector Punctuation 2
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
용 206
 
4.9%
역 193
 
4.6%
시 172
 
4.1%
공 103
 
2.5%
년 101
 
2.4%
사 96
 
2.3%
리 79
 
1.9%
흥 78
 
1.9%
지 60
 
1.4%
기 60
 
1.4%
Other values (320) 3042
72.6%
Uppercase Letter
ValueCountFrequency (%)
B 13
21.7%
C 9
15.0%
A 7
11.7%
S 4
 
6.7%
P 4
 
6.7%
L 4
 
6.7%
Q 4
 
6.7%
V 3
 
5.0%
F 2
 
3.3%
T 2
 
3.3%
Other values (8) 8
13.3%
Decimal Number
ValueCountFrequency (%)
2 243
52.8%
0 106
23.0%
3 53
 
11.5%
1 50
 
10.9%
4 3
 
0.7%
5 2
 
0.4%
6 2
 
0.4%
8 1
 
0.2%
Other Punctuation
ValueCountFrequency (%)
, 7
46.7%
: 4
26.7%
. 2
 
13.3%
# 2
 
13.3%
Open Punctuation
ValueCountFrequency (%)
( 54
94.7%
[ 2
 
3.5%
「 1
 
1.8%
Close Punctuation
ValueCountFrequency (%)
) 53
94.6%
] 2
 
3.6%
」 1
 
1.8%
Lowercase Letter
ValueCountFrequency (%)
l 1
50.0%
c 1
50.0%
Space Separator
ValueCountFrequency (%)
985
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4190
71.8%
Common 1581
 
27.1%
Latin 62
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
용 206
 
4.9%
역 193
 
4.6%
시 172
 
4.1%
공 103
 
2.5%
년 101
 
2.4%
사 96
 
2.3%
리 79
 
1.9%
흥 78
 
1.9%
지 60
 
1.4%
기 60
 
1.4%
Other values (320) 3042
72.6%
Common
ValueCountFrequency (%)
985
62.3%
2 243
 
15.4%
0 106
 
6.7%
( 54
 
3.4%
) 53
 
3.4%
3 53
 
3.4%
1 50
 
3.2%
, 7
 
0.4%
- 5
 
0.3%
: 4
 
0.3%
Other values (12) 21
 
1.3%
Latin
ValueCountFrequency (%)
B 13
21.0%
C 9
14.5%
A 7
11.3%
S 4
 
6.5%
P 4
 
6.5%
L 4
 
6.5%
Q 4
 
6.5%
V 3
 
4.8%
F 2
 
3.2%
T 2
 
3.2%
Other values (10) 10
16.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4190
71.8%
ASCII 1641
 
28.1%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
985
60.0%
2 243
 
14.8%
0 106
 
6.5%
( 54
 
3.3%
) 53
 
3.2%
3 53
 
3.2%
1 50
 
3.0%
B 13
 
0.8%
C 9
 
0.5%
A 7
 
0.4%
Other values (30) 68
 
4.1%
Hangul
ValueCountFrequency (%)
용 206
 
4.9%
역 193
 
4.6%
시 172
 
4.1%
공 103
 
2.5%
년 101
 
2.4%
사 96
 
2.3%
리 79
 
1.9%
흥 78
 
1.9%
지 60
 
1.4%
기 60
 
1.4%
Other values (320) 3042
72.6%
None
ValueCountFrequency (%)
「 1
50.0%
」 1
50.0%

수요기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
시흥도시공사
218 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
시흥도시공사 218
100.0%

Length

2024-03-23T05:26:45.384456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T05:26:45.847645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
시흥도시공사 218
100.0%

계약기관
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
시흥도시공사
218 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
시흥도시공사 218
100.0%

Length

2024-03-23T05:26:46.307993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T05:26:46.720220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
시흥도시공사 218
100.0%

신규장기구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
신규(단년도)
215 
장기·초년도
 
3

Length

Max length7
Median length7
Mean length6.9862385
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row신규(단년도)
2nd row신규(단년도)
3rd row신규(단년도)
4th row신규(단년도)
5th row신규(단년도)

Common Values

ValueCountFrequency (%)
신규(단년도) 215
98.6%
장기·초년도 3
 
1.4%

Length

2024-03-23T05:26:47.138574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T05:26:47.568141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신규(단년도 215
98.6%
장기·초년도 3
 
1.4%

대표자명
Text

Distinct159
Distinct (%)72.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-03-23T05:26:48.580052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.9954128
Min length2

Characters and Unicode

Total characters653
Distinct characters126
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique124 ?
Unique (%)56.9%

Sample

1st row정보민
2nd row정종천
3rd row이준길
4th row오인석
5th row이예지
ValueCountFrequency (%)
하태년 5
 
2.3%
안상홍 5
 
2.3%
김영신 4
 
1.8%
김경성 4
 
1.8%
서미영 4
 
1.8%
박설희 4
 
1.8%
곽영진 3
 
1.4%
김현수 3
 
1.4%
권진아 3
 
1.4%
김미성 3
 
1.4%
Other values (149) 180
82.6%
2024-03-23T05:26:50.048888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 50
 
7.7%
이 30
 
4.6%
영 25
 
3.8%
성 19
 
2.9%
원 16
 
2.5%
종 15
 
2.3%
현 15
 
2.3%
미 14
 
2.1%
홍 14
 
2.1%
태 13
 
2.0%
Other values (116) 442
67.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 653
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 50
 
7.7%
이 30
 
4.6%
영 25
 
3.8%
성 19
 
2.9%
원 16
 
2.5%
종 15
 
2.3%
현 15
 
2.3%
미 14
 
2.1%
홍 14
 
2.1%
태 13
 
2.0%
Other values (116) 442
67.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 653
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 50
 
7.7%
이 30
 
4.6%
영 25
 
3.8%
성 19
 
2.9%
원 16
 
2.5%
종 15
 
2.3%
현 15
 
2.3%
미 14
 
2.1%
홍 14
 
2.1%
태 13
 
2.0%
Other values (116) 442
67.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 653
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 50
 
7.7%
이 30
 
4.6%
영 25
 
3.8%
성 19
 
2.9%
원 16
 
2.5%
종 15
 
2.3%
현 15
 
2.3%
미 14
 
2.1%
홍 14
 
2.1%
태 13
 
2.0%
Other values (116) 442
67.7%

계약방법
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
수의계약
186 
제한경쟁
22 
일반경쟁
 
6
지명경쟁
 
4

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
수의계약 186
85.3%
제한경쟁 22
 
10.1%
일반경쟁 6
 
2.8%
지명경쟁 4
 
1.8%

Length

2024-03-23T05:26:50.624835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T05:26:51.175301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수의계약 186
85.3%
제한경쟁 22
 
10.1%
일반경쟁 6
 
2.8%
지명경쟁 4
 
1.8%

계약일자
Date

Distinct158
Distinct (%)72.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum2021-01-01 00:00:00
Maximum2023-11-28 00:00:00
2024-03-23T05:26:51.790217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:26:52.680820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

계약금액
Real number (ℝ)

HIGH CORRELATION 

Distinct194
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean82234941
Minimum5000000
Maximum1.5312 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-03-23T05:26:53.419934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5000000
5-th percentile5946800
Q18622750
median18000000
Q340764750
95-th percentile3.8934803 × 108
Maximum1.5312 × 109
Range1.5262 × 109
Interquartile range (IQR)32142000

Descriptive statistics

Standard deviation2.256553 × 108
Coefficient of variation (CV)2.7440319
Kurtosis20.800867
Mean82234941
Median Absolute Deviation (MAD)10166305
Skewness4.4439605
Sum1.7927217 × 1010
Variance5.0920315 × 1016
MonotonicityNot monotonic
2024-03-23T05:26:54.111085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19800000 8
 
3.7%
18000000 4
 
1.8%
9900000 3
 
1.4%
7000000 3
 
1.4%
7700000 2
 
0.9%
6600000 2
 
0.9%
13200000 2
 
0.9%
8800000 2
 
0.9%
19300000 2
 
0.9%
11968000 2
 
0.9%
Other values (184) 188
86.2%
ValueCountFrequency (%)
5000000 1
0.5%
5126000 1
0.5%
5280000 1
0.5%
5400000 2
0.9%
5408700 1
0.5%
5500000 1
0.5%
5570000 1
0.5%
5654000 1
0.5%
5730000 1
0.5%
5940000 1
0.5%
ValueCountFrequency (%)
1531200000 1
0.5%
1500000000 1
0.5%
1130000000 1
0.5%
1045000000 1
0.5%
1003237000 1
0.5%
1000000000 1
0.5%
967000000 1
0.5%
754650000 1
0.5%
740800000 1
0.5%
551000000 1
0.5%

사업자등록번호
Real number (ℝ)

Distinct163
Distinct (%)74.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.8039451 × 109
Minimum1.0181473 × 109
Maximum8.7187003 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-03-23T05:26:54.824286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.0181473 × 109
5-th percentile1.0754473 × 109
Q11.3381281 × 109
median1.41 × 109
Q33.3419004 × 109
95-th percentile8.0522814 × 109
Maximum8.7187003 × 109
Range7.7005529 × 109
Interquartile range (IQR)2.0037723 × 109

Descriptive statistics

Standard deviation2.2957066 × 109
Coefficient of variation (CV)0.81874161
Kurtosis0.55130539
Mean2.8039451 × 109
Median Absolute Deviation (MAD)3.7089032 × 108
Skewness1.4057765
Sum6.1126004 × 1011
Variance5.2702686 × 1018
MonotonicityNot monotonic
2024-03-23T05:26:55.302923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1340000000 7
 
3.2%
1018651015 5
 
2.3%
1360000000 5
 
2.3%
1408125915 4
 
1.8%
3208701210 4
 
1.8%
1410000000 3
 
1.4%
1138132864 3
 
1.4%
2120000000 3
 
1.4%
1340690340 3
 
1.4%
2158204604 3
 
1.4%
Other values (153) 178
81.7%
ValueCountFrequency (%)
1018147345 1
 
0.5%
1018616997 2
 
0.9%
1018651015 5
2.3%
1020000000 1
 
0.5%
1058219358 1
 
0.5%
1060000000 1
 
0.5%
1078173292 1
 
0.5%
1080000000 1
 
0.5%
1088141833 1
 
0.5%
1120000000 1
 
0.5%
ValueCountFrequency (%)
8718700290 1
0.5%
8695300711 1
0.5%
8640000000 1
0.5%
8298801320 1
0.5%
8278802468 1
0.5%
8258800620 1
0.5%
8218800249 1
0.5%
8080000000 1
0.5%
8078200237 1
0.5%
8072000113 2
0.9%

낙찰업체명
Text

Distinct155
Distinct (%)71.1%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-03-23T05:26:56.095290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length18
Mean length10.183486
Min length2

Characters and Unicode

Total characters2220
Distinct characters243
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique118 ?
Unique (%)54.1%

Sample

1st row주식회사 푸름엔지니어링
2nd row주식회사보림씨에스
3rd row인선이엔티 주식회사 사천지점
4th row유창테크
5th row예송그린
ValueCountFrequency (%)
주식회사 104
29.3%
파킹클라우드 5
 
1.4%
수호 5
 
1.4%
건강한세상 4
 
1.1%
주)원일화학엔환경 4
 
1.1%
더블유알에스 4
 
1.1%
w.r.s 4
 
1.1%
co 4
 
1.1%
ltd 4
 
1.1%
인크루트 4
 
1.1%
Other values (164) 213
60.0%
2024-03-23T05:26:57.577038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 165
 
7.4%
사 148
 
6.7%
137
 
6.2%
회 117
 
5.3%
식 110
 
5.0%
( 67
 
3.0%
) 67
 
3.0%
이 58
 
2.6%
스 50
 
2.3%
에 36
 
1.6%
Other values (233) 1265
57.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1846
83.2%
Space Separator 137
 
6.2%
Open Punctuation 67
 
3.0%
Close Punctuation 67
 
3.0%
Uppercase Letter 60
 
2.7%
Other Punctuation 28
 
1.3%
Lowercase Letter 15
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 165
 
8.9%
사 148
 
8.0%
회 117
 
6.3%
식 110
 
6.0%
이 58
 
3.1%
스 50
 
2.7%
에 36
 
2.0%
한 34
 
1.8%
지 33
 
1.8%
아 28
 
1.5%
Other values (213) 1067
57.8%
Uppercase Letter
ValueCountFrequency (%)
E 10
16.7%
N 9
15.0%
I 7
11.7%
R 7
11.7%
C 6
10.0%
G 6
10.0%
L 5
8.3%
W 4
 
6.7%
S 4
 
6.7%
T 1
 
1.7%
Other Punctuation
ValueCountFrequency (%)
. 22
78.6%
, 5
 
17.9%
& 1
 
3.6%
Lowercase Letter
ValueCountFrequency (%)
d 5
33.3%
o 5
33.3%
t 5
33.3%
Space Separator
ValueCountFrequency (%)
137
100.0%
Open Punctuation
ValueCountFrequency (%)
( 67
100.0%
Close Punctuation
ValueCountFrequency (%)
) 67
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1846
83.2%
Common 299
 
13.5%
Latin 75
 
3.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 165
 
8.9%
사 148
 
8.0%
회 117
 
6.3%
식 110
 
6.0%
이 58
 
3.1%
스 50
 
2.7%
에 36
 
2.0%
한 34
 
1.8%
지 33
 
1.8%
아 28
 
1.5%
Other values (213) 1067
57.8%
Latin
ValueCountFrequency (%)
E 10
13.3%
N 9
12.0%
I 7
9.3%
R 7
9.3%
C 6
8.0%
G 6
8.0%
d 5
6.7%
o 5
6.7%
L 5
6.7%
t 5
6.7%
Other values (4) 10
13.3%
Common
ValueCountFrequency (%)
137
45.8%
( 67
22.4%
) 67
22.4%
. 22
 
7.4%
, 5
 
1.7%
& 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1846
83.2%
ASCII 374
 
16.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 165
 
8.9%
사 148
 
8.0%
회 117
 
6.3%
식 110
 
6.0%
이 58
 
3.1%
스 50
 
2.7%
에 36
 
2.0%
한 34
 
1.8%
지 33
 
1.8%
아 28
 
1.5%
Other values (213) 1067
57.8%
ASCII
ValueCountFrequency (%)
137
36.6%
( 67
17.9%
) 67
17.9%
. 22
 
5.9%
E 10
 
2.7%
N 9
 
2.4%
I 7
 
1.9%
R 7
 
1.9%
C 6
 
1.6%
G 6
 
1.6%
Other values (10) 36
 
9.6%

대표업체주소
Text

Distinct165
Distinct (%)75.7%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-03-23T05:26:58.390482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length74
Median length53
Mean length42.784404
Min length27

Characters and Unicode

Total characters9327
Distinct characters303
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

Unique133 ?
Unique (%)61.0%

Sample

1st row(14912) 경기도 시흥시 비둘기공원6길 25, 4층 401호(대야동, 견우프라자)
2nd row(33521) 충청남도 보령시 웅천읍 대창증산로 166
3rd row(52535) 경상남도 사천시 사남면 외국기업로 217-0 (방지리)
4th row(22665) 인천광역시 서구 검단천로 153 (오류동)
5th row(14904) 경기도 시흥시 문화마을로16번길 23-1 (신천동)
ValueCountFrequency (%)
경기도 146
 
9.1%
시흥시 59
 
3.7%
서울특별시 55
 
3.4%
안양시 19
 
1.2%
동안구 18
 
1.1%
정왕동 17
 
1.1%
안산시 14
 
0.9%
단원구 14
 
0.9%
14998 11
 
0.7%
서초구 10
 
0.6%
Other values (751) 1249
77.5%
2024-03-23T05:26:59.703866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1394
 
14.9%
1 542
 
5.8%
) 421
 
4.5%
( 420
 
4.5%
0 420
 
4.5%
시 298
 
3.2%
4 289
 
3.1%
2 279
 
3.0%
동 261
 
2.8%
3 237
 
2.5%
Other values (293) 4766
51.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4147
44.5%
Decimal Number 2597
27.8%
Space Separator 1394
 
14.9%
Close Punctuation 421
 
4.5%
Open Punctuation 420
 
4.5%
Other Punctuation 176
 
1.9%
Dash Punctuation 121
 
1.3%
Uppercase Letter 49
 
0.5%
Math Symbol 1
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 298
 
7.2%
동 261
 
6.3%
로 219
 
5.3%
기 168
 
4.1%
도 161
 
3.9%
경 156
 
3.8%
호 134
 
3.2%
구 134
 
3.2%
서 104
 
2.5%
길 91
 
2.2%
Other values (260) 2421
58.4%
Uppercase Letter
ValueCountFrequency (%)
B 11
22.4%
A 6
12.2%
T 5
10.2%
I 5
10.2%
S 4
 
8.2%
K 4
 
8.2%
L 3
 
6.1%
M 2
 
4.1%
W 2
 
4.1%
C 1
 
2.0%
Other values (6) 6
12.2%
Decimal Number
ValueCountFrequency (%)
1 542
20.9%
0 420
16.2%
4 289
11.1%
2 279
10.7%
3 237
9.1%
5 213
 
8.2%
6 170
 
6.5%
9 162
 
6.2%
7 161
 
6.2%
8 124
 
4.8%
Space Separator
ValueCountFrequency (%)
1394
100.0%
Close Punctuation
ValueCountFrequency (%)
) 421
100.0%
Open Punctuation
ValueCountFrequency (%)
( 420
100.0%
Other Punctuation
ValueCountFrequency (%)
, 176
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 121
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅳ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5130
55.0%
Hangul 4147
44.5%
Latin 50
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 298
 
7.2%
동 261
 
6.3%
로 219
 
5.3%
기 168
 
4.1%
도 161
 
3.9%
경 156
 
3.8%
호 134
 
3.2%
구 134
 
3.2%
서 104
 
2.5%
길 91
 
2.2%
Other values (260) 2421
58.4%
Latin
ValueCountFrequency (%)
B 11
22.0%
A 6
12.0%
T 5
10.0%
I 5
10.0%
S 4
 
8.0%
K 4
 
8.0%
L 3
 
6.0%
M 2
 
4.0%
W 2
 
4.0%
C 1
 
2.0%
Other values (7) 7
14.0%
Common
ValueCountFrequency (%)
1394
27.2%
1 542
 
10.6%
) 421
 
8.2%
( 420
 
8.2%
0 420
 
8.2%
4 289
 
5.6%
2 279
 
5.4%
3 237
 
4.6%
5 213
 
4.2%
, 176
 
3.4%
Other values (6) 739
14.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5179
55.5%
Hangul 4147
44.5%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1394
26.9%
1 542
 
10.5%
) 421
 
8.1%
( 420
 
8.1%
0 420
 
8.1%
4 289
 
5.6%
2 279
 
5.4%
3 237
 
4.6%
5 213
 
4.1%
, 176
 
3.4%
Other values (22) 788
15.2%
Hangul
ValueCountFrequency (%)
시 298
 
7.2%
동 261
 
6.3%
로 219
 
5.3%
기 168
 
4.1%
도 161
 
3.9%
경 156
 
3.8%
호 134
 
3.2%
구 134
 
3.2%
서 104
 
2.5%
길 91
 
2.2%
Other values (260) 2421
58.4%
Number Forms
ValueCountFrequency (%)
Ⅳ 1
100.0%

착수일자
Date

Distinct149
Distinct (%)68.3%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum2021-01-01 00:00:00
Maximum2023-11-29 00:00:00
2024-03-23T05:27:00.260089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:27:00.971277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

완수일자
Date

Distinct114
Distinct (%)52.3%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum2021-01-31 00:00:00
Maximum2028-06-30 00:00:00
2024-03-23T05:27:01.749595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:27:02.560050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

낙찰률
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct42
Distinct (%)19.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.989872
Minimum0
Maximum100
Zeros176
Zeros (%)80.7%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-03-23T05:27:03.369426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile89.15815
Maximum100
Range100
Interquartile range (IQR)0

Descriptive statistics

Standard deviation34.941814
Coefficient of variation (CV)2.0566262
Kurtosis0.55518979
Mean16.989872
Median Absolute Deviation (MAD)0
Skewness1.5873687
Sum3703.792
Variance1220.9304
MonotonicityNot monotonic
2024-03-23T05:27:04.550409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
0.0 176
80.7%
88.999 2
 
0.9%
87.776 1
 
0.5%
89.722 1
 
0.5%
94.099 1
 
0.5%
88.08 1
 
0.5%
99.192 1
 
0.5%
86.845 1
 
0.5%
87.754 1
 
0.5%
78.008 1
 
0.5%
Other values (32) 32
 
14.7%
ValueCountFrequency (%)
0.0 176
80.7%
78.008 1
 
0.5%
78.09 1
 
0.5%
78.211 1
 
0.5%
78.34 1
 
0.5%
78.419 1
 
0.5%
80.536 1
 
0.5%
81.58 1
 
0.5%
85.699 1
 
0.5%
85.71 1
 
0.5%
ValueCountFrequency (%)
100.0 1
0.5%
99.192 1
0.5%
97.525 1
0.5%
96.851 1
0.5%
96.774 1
0.5%
94.73 1
0.5%
94.099 1
0.5%
93.464 1
0.5%
92.067 1
0.5%
89.722 1
0.5%

낙찰금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct40
Distinct (%)18.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean78492610
Minimum0
Maximum3.68 × 109
Zeros177
Zeros (%)81.2%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-03-23T05:27:05.491594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3.5705 × 108
Maximum3.68 × 109
Range3.68 × 109
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.3418704 × 108
Coefficient of variation (CV)4.2575606
Kurtosis65.990134
Mean78492610
Median Absolute Deviation (MAD)0
Skewness7.2128934
Sum1.7111389 × 1010
Variance1.1168098 × 1017
MonotonicityNot monotonic
2024-03-23T05:27:06.222619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
0 177
81.2%
45600000 2
 
0.9%
297000000 2
 
0.9%
189000 1
 
0.5%
51800000 1
 
0.5%
228000000 1
 
0.5%
355000000 1
 
0.5%
121000000 1
 
0.5%
1000000000 1
 
0.5%
741000000 1
 
0.5%
Other values (30) 30
 
13.8%
ValueCountFrequency (%)
0 177
81.2%
189000 1
 
0.5%
25500000 1
 
0.5%
26300000 1
 
0.5%
30500000 1
 
0.5%
30900000 1
 
0.5%
37100000 1
 
0.5%
38000000 1
 
0.5%
40300000 1
 
0.5%
45600000 2
 
0.9%
ValueCountFrequency (%)
3680000000 1
0.5%
1530000000 1
0.5%
1500000000 1
0.5%
1130000000 1
0.5%
1100000000 1
0.5%
1050000000 1
0.5%
1000000000 1
0.5%
967000000 1
0.5%
755000000 1
0.5%
741000000 1
0.5%

입찰일자
Date

Distinct165
Distinct (%)75.7%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum2020-12-24 00:00:00
Maximum2023-11-28 00:00:00
2024-03-23T05:27:06.930983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:27:07.725288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

실제완수일자
Date

Distinct116
Distinct (%)53.2%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum2021-01-31 00:00:00
Maximum2028-06-30 00:00:00
2024-03-23T05:27:08.318605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:27:08.816617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

용역현장
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
경기도 시흥시
218 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도 시흥시
2nd row경기도 시흥시
3rd row경기도 시흥시
4th row경기도 시흥시
5th row경기도 시흥시

Common Values

ValueCountFrequency (%)
경기도 시흥시 218
100.0%

Length

2024-03-23T05:27:09.327112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T05:27:09.732405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 218
50.0%
시흥시 218
50.0%

Interactions

2024-03-23T05:26:37.917908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:26:30.498987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:26:32.612101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:26:34.445826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:26:36.192966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:26:38.230169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:26:31.036406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:26:32.972805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:26:34.770673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:26:36.501520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:26:38.611257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:26:31.332660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:26:33.402396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:26:35.144853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:26:36.806563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:26:38.882256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:26:31.702270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:26:33.778098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:26:35.546772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:26:37.186030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:26:39.139242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:26:32.210128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:26:34.036589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:26:35.890235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:26:37.602943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T05:27:09.943639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호신규장기구분계약방법계약금액사업자등록번호낙찰률낙찰금액
번호1.0000.0000.2570.0000.2790.1360.000
신규장기구분0.0001.0000.3810.2880.1570.3630.464
계약방법0.2570.3811.0000.9500.2470.8380.648
계약금액0.0000.2880.9501.0000.2830.8640.920
사업자등록번호0.2790.1570.2470.2831.0000.0430.247
낙찰률0.1360.3630.8380.8640.0431.0000.536
낙찰금액0.0000.4640.6480.9200.2470.5361.000
2024-03-23T05:27:10.317589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
계약방법신규장기구분
계약방법1.0000.254
신규장기구분0.2541.000
2024-03-23T05:27:10.522689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호계약금액사업자등록번호낙찰률낙찰금액신규장기구분계약방법
번호1.000-0.137-0.007-0.058-0.0650.0000.153
계약금액-0.1371.0000.1250.5990.6280.2130.701
사업자등록번호-0.0070.1251.0000.0000.0160.1190.148
낙찰률-0.0580.5990.0001.0000.9590.2420.487
낙찰금액-0.0650.6280.0160.9591.0000.5600.577
신규장기구분0.0000.2130.1190.2420.5601.0000.254
계약방법0.1530.7010.1480.4870.5770.2541.000

Missing values

2024-03-23T05:26:39.637665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T05:26:40.597111image/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

번호계약번호용역명수요기관명계약기관신규장기구분대표자명계약방법계약일자계약금액사업자등록번호낙찰업체명대표업체주소착수일자완수일자낙찰률낙찰금액입찰일자실제완수일자용역현장
01202012181182021년 시흥도시공사 정화조 및 오수처리시설 관리용역(통합)_긴급시흥도시공사시흥도시공사신규(단년도)정보민제한경쟁2021-01-01370805007100000000주식회사 푸름엔지니어링(14912) 경기도 시흥시 비둘기공원6길 25, 4층 401호(대야동, 견우프라자)2021-01-012021-12-3189.077371000002020-12-242021-12-31경기도 시흥시
122021010077E2021년 시흥그린센터 비산재 고형화물 위탁처리 용역(일반매립)시흥도시공사시흥도시공사신규(단년도)정종천제한경쟁2021-01-0411300000003140000000주식회사보림씨에스(33521) 충청남도 보령시 웅천읍 대창증산로 1662021-01-042021-12-3178.21111300000002020-12-282021-12-31경기도 시흥시
23202101007AF2021년 시흥그린센터 바닥재 최종처분 용역(일반매립)시흥도시공사시흥도시공사신규(단년도)이준길제한경쟁2021-01-042970000007940000000인선이엔티 주식회사 사천지점(52535) 경상남도 사천시 사남면 외국기업로 217-0 (방지리)2021-01-042021-12-3187.1772970000002020-12-242021-12-31경기도 시흥시
34202101007C32021년 시흥그린센터 바닥재 위탁처리 용역(재활용)_재공고시흥도시공사시흥도시공사신규(단년도)오인석제한경쟁2021-01-0415000000001330000000유창테크(22665) 인천광역시 서구 검단천로 153 (오류동)2021-01-042021-12-3178.41915000000002020-12-242021-12-31경기도 시흥시
45202101020C82021년 상반기 공공청사 왁스걸레 교체용역시흥도시공사시흥도시공사신규(단년도)이예지수의계약2021-01-0660120001400000000예송그린(14904) 경기도 시흥시 문화마을로16번길 23-1 (신천동)2021-01-062021-07-050.002021-01-062021-07-05경기도 시흥시
5620210109EDC2021년 시흥그린센터 대기자가측정(1월 3~4주차) 용역시흥도시공사시흥도시공사신규(단년도)유희선수의계약2021-01-20215402002140000000(주)진덕환경엔지니어링(14119) 경기도 안양시 동안구 엘에스로91번길 16-39, 505호(호계동, 안양IT밸리)2021-01-202021-01-310.002021-01-202021-01-31경기도 시흥시
67202101119F32021년 환경미화타운 폐매트리스 위탁처리 용역시흥도시공사시흥도시공사신규(단년도)심원용수의계약2021-02-01550000003370000000주식회사 더블유알에스 (W.R.S. Co., Ltd.)(15431) 경기도 안산시 단원구 산단로 326-0 (원곡동)18동 303호2021-02-012021-12-310.002021-02-012021-12-31경기도 시흥시
7820210202514은계어울림센터-1 건립공사 건설폐기물 처리용역시흥도시공사시흥도시공사장기·초년도박승혜수의계약2021-02-09217400003930000000다온개발 주식회사(15090) 경기도 시흥시 공단1대로 204 (정왕동)2021-03-012021-12-3188.52802021-01-252021-12-31경기도 시흥시
89202102050A12021년 시흥그린센터 대기 자가측정 용역시흥도시공사시흥도시공사신규(단년도)서병원제한경쟁2021-02-052970000001340000000(주)대현환경(14057) 경기도 안양시 동안구 시민대로 401(관양동,대륭테크노타운15차 2107호,2103호,1712호,401호)2021-02-052021-12-3186.892970000002021-02-032021-12-31경기도 시흥시
9102021020C2B1은계어울림센터-1 건설공사 감독권한대행 등 건설사업관리 용역(PQ후 지명경쟁)시흥도시공사시흥도시공사신규(단년도)이을재지명경쟁2021-02-245510000002120000000(주)토문엔지니어링 건축사사무소(05839) 서울특별시 송파구 충민로 52, 8층(문정동, 가든파이브 웍스 디동)2021-03-152021-12-2278.0911000000002021-02-052021-12-22경기도 시흥시
번호계약번호용역명수요기관명계약기관신규장기구분대표자명계약방법계약일자계약금액사업자등록번호낙찰업체명대표업체주소착수일자완수일자낙찰률낙찰금액입찰일자실제완수일자용역현장
2082092023080C3882023년 환경미화타운 폐매트리스 위탁처리 용역시흥도시공사시흥도시공사신규(단년도)권진아수의계약2023-08-22160000003368700157주식회사 더블유알에스 (W.R.S. Co., Ltd.)(15431) 경기도 안산시 단원구 산단로 326 (원곡동)18동 303호2023-08-222023-12-310.002023-08-222023-12-31경기도 시흥시
20921020230811EAB전 직원 워크숍 차량 임차 계약시흥도시공사시흥도시공사신규(단년도)이필순수의계약2023-08-29143000001278621906주식회사 베스트하나관광(12160) 경기도 남양주시 화도읍 비룡로 142-352023-08-302023-09-190.002023-08-292023-09-19경기도 시흥시
210211202309002962023년 ABC행복학습타운 외벽청소 용역 계약시흥도시공사시흥도시공사신규(단년도)박설희수의계약2023-09-0180000001340690340건강한세상(15002) 경기도 시흥시 황고개로 531-0 (장곡동) 509호2023-09-112023-09-300.002023-09-012023-09-30경기도 시흥시
211212202309021C22023년 시흥도시공사 워크숍 수련관 임차시흥도시공사시흥도시공사신규(단년도)함승우수의계약2023-09-05352100001208711971(주)케이와이엠(32155) 충청남도 태안군 남면 안면대로 1308-02023-09-142023-09-190.002023-09-052023-09-19경기도 시흥시
212213202309036C6그린환경부 폐기물 반입장 크레인 크랩 버켓 메인 힌지 브라켓 수리 용역시흥도시공사시흥도시공사신규(단년도)정보현수의계약2023-09-0679090001378173139부천기업 주식회사(10003) 경기도 김포시 월곶면 애기봉로 250-02023-09-132023-09-220.002023-09-062023-09-22경기도 시흥시
21321420230904050소각장 콤프레셔(C번 100HP) 수리 용역시흥도시공사시흥도시공사신규(단년도)정균수의계약2023-09-0765450001348611819주식회사 하나티이씨(31736) 충청남도 당진시 송악읍 순성로 822-722023-09-112023-09-250.002023-09-072023-09-25경기도 시흥시
2142152023100B8D5시흥장현 B10BL(지하주차장 구조 안전 점검 용역)시흥도시공사시흥도시공사신규(단년도)김형준수의계약2023-10-19132000008028100502(주)정도안전기술단(16942) 경기도 용인시 수지구 광교중앙로 338 (상현동) C동 805호 광교우미뉴브2023-10-232023-12-210.002023-10-192023-12-21경기도 시흥시
215216202311057AD2023년 시흥도시공사 직급별 역량강화 위탁 교육시흥도시공사시흥도시공사신규(단년도)목영만수의계약2023-11-0863800001058219358지방공기업평가원(06716) 서울특별시 서초구 반포대로 30길 12-62023-11-102023-11-130.002023-11-082023-11-13경기도 시흥시
2162172023111412E중앙제어실 항온항습기 이전 설치시흥도시공사시흥도시공사신규(단년도)한영모수의계약2023-11-2388000001338125483(주)에이알(15104) 경기도 시흥시 공단1대로260번안길 21, 시화공단3다709 (정왕동)2023-11-292023-12-080.002023-11-232023-12-08경기도 시흥시
21721820231117A06체육시설3부(시흥어울림국민체육센터) 보일러 급수배관 보수 및 펌프증설시흥도시공사시흥도시공사신규(단년도)유상문수의계약2023-11-2896800003261501109에스엠테크(15103) 경기도 시흥시 공단1대로 244, 7동 325호 (정왕동, 공구상가)2023-11-282023-12-150.002023-11-282023-12-15경기도 시흥시