Overview

Dataset statistics

Number of variables40
Number of observations2748
Missing cells30677
Missing cells (%)27.9%
Duplicate rows55
Duplicate rows (%)2.0%
Total size in memory888.4 KiB
Average record size in memory331.0 B

Variable types

Text8
Categorical21
Numeric7
DateTime3
Unsupported1

Dataset

Description조달실적을 종합적으로 분석한 정보 국가를 당사자로 하는 계약에 관한 법률 등에 따라 국가(공공)기관, 지방자치단체에서 발주하는 입찰공고에 대한 개찰결과 및 최종낙찰결과 정보
Author조달청
URLhttps://www.data.go.kr/data/15023681/standard.do

Alerts

Dataset has 55 (2.0%) duplicate rowsDuplicates
입찰공고차수 is highly imbalanced (76.3%)Imbalance
계약체결형태명 is highly imbalanced (89.7%)Imbalance
낙찰하한율 is highly imbalanced (51.8%)Imbalance
기초금액 is highly imbalanced (64.0%)Imbalance
개찰결과구분명 is highly imbalanced (86.0%)Imbalance
투찰일자 is highly imbalanced (62.9%)Imbalance
최종낙찰일자 is highly imbalanced (78.6%)Imbalance
최종낙찰업체담당자명 is highly imbalanced (68.9%)Imbalance
최종낙찰업체주소 is highly imbalanced (68.9%)Imbalance
추정가격 has 1970 (71.7%) missing valuesMissing
예정가격 has 1970 (71.7%) missing valuesMissing
개찰순위 has 2073 (75.4%) missing valuesMissing
투찰업체사업자등록번호 has 1967 (71.6%) missing valuesMissing
투찰업체명 has 1967 (71.6%) missing valuesMissing
투찰업체대표자명 has 1967 (71.6%) missing valuesMissing
투찰금액 has 1968 (71.6%) missing valuesMissing
투찰율 has 2248 (81.8%) missing valuesMissing
투찰시각 has 1968 (71.6%) missing valuesMissing
부적격사유 has 2748 (100.0%) missing valuesMissing
최종낙찰금액 has 1910 (69.5%) missing valuesMissing
최종낙찰율 has 2191 (79.7%) missing valuesMissing
최종낙찰업체명 has 1910 (69.5%) missing valuesMissing
최종낙찰업체대표자명 has 1910 (69.5%) missing valuesMissing
최종낙찰업체사업자등록번호 has 1910 (69.5%) missing valuesMissing
추정가격 is highly skewed (γ1 = 22.88220915)Skewed
예정가격 is highly skewed (γ1 = 22.89088697)Skewed
투찰금액 is highly skewed (γ1 = 22.94957432)Skewed
최종낙찰금액 is highly skewed (γ1 = 23.5404289)Skewed
부적격사유 is an unsupported type, check if it needs cleaning or further analysisUnsupported
개찰순위 has 245 (8.9%) zerosZeros

Reproduction

Analysis started2023-12-12 09:19:49.035567
Analysis finished2023-12-12 09:19:50.728795
Duration1.69 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct1876
Distinct (%)68.3%
Missing0
Missing (%)0.0%
Memory size21.6 KiB
2023-12-12T18:19:50.871356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length10
Mean length10.89083
Min length8

Characters and Unicode

Total characters29928
Distinct characters23
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

Unique1753 ?
Unique (%)63.8%

Sample

1st row2019073110
2nd row2019073107
3rd row2019080625
4th row2019071725
5th row2019071725
ValueCountFrequency (%)
e012008363 487
 
17.7%
202008140101 62
 
2.3%
202008060106 42
 
1.5%
202008262602 32
 
1.2%
202008141603 28
 
1.0%
202008190101 27
 
1.0%
202008210504 14
 
0.5%
202008210502 12
 
0.4%
202008275602 12
 
0.4%
202008270503 8
 
0.3%
Other values (1866) 2024
73.7%
2023-12-12T18:19:51.295926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9039
30.2%
2 4681
15.6%
1 4427
14.8%
3 1707
 
5.7%
8 1394
 
4.7%
9 1362
 
4.6%
E 1281
 
4.3%
6 1165
 
3.9%
7 790
 
2.6%
K 748
 
2.5%
Other values (13) 3334
 
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 25725
86.0%
Uppercase Letter 4203
 
14.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 1281
30.5%
K 748
17.8%
C 505
 
12.0%
O 500
 
11.9%
N 500
 
11.9%
A 332
 
7.9%
S 157
 
3.7%
I 75
 
1.8%
P 52
 
1.2%
L 39
 
0.9%
Other values (3) 14
 
0.3%
Decimal Number
ValueCountFrequency (%)
0 9039
35.1%
2 4681
18.2%
1 4427
17.2%
3 1707
 
6.6%
8 1394
 
5.4%
9 1362
 
5.3%
6 1165
 
4.5%
7 790
 
3.1%
4 606
 
2.4%
5 554
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Common 25725
86.0%
Latin 4203
 
14.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 1281
30.5%
K 748
17.8%
C 505
 
12.0%
O 500
 
11.9%
N 500
 
11.9%
A 332
 
7.9%
S 157
 
3.7%
I 75
 
1.8%
P 52
 
1.2%
L 39
 
0.9%
Other values (3) 14
 
0.3%
Common
ValueCountFrequency (%)
0 9039
35.1%
2 4681
18.2%
1 4427
17.2%
3 1707
 
6.6%
8 1394
 
5.4%
9 1362
 
5.3%
6 1165
 
4.5%
7 790
 
3.1%
4 606
 
2.4%
5 554
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 29928
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9039
30.2%
2 4681
15.6%
1 4427
14.8%
3 1707
 
5.7%
8 1394
 
4.7%
9 1362
 
4.6%
E 1281
 
4.3%
6 1165
 
3.9%
7 790
 
2.6%
K 748
 
2.5%
Other values (13) 3334
 
11.1%

입찰공고차수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size21.6 KiB
<NA>
2410 
1
301 
2
 
29
3
 
6
6
 
1

Length

Max length4
Median length4
Mean length3.6310044
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 2410
87.7%
1 301
 
11.0%
2 29
 
1.1%
3 6
 
0.2%
6 1
 
< 0.1%
4 1
 
< 0.1%

Length

2023-12-12T18:19:51.468753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:19:51.620149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2410
87.7%
1 301
 
11.0%
2 29
 
1.1%
3 6
 
0.2%
6 1
 
< 0.1%
4 1
 
< 0.1%
Distinct1725
Distinct (%)62.8%
Missing0
Missing (%)0.0%
Memory size21.6 KiB
2023-12-12T18:19:51.998719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length94
Median length59
Mean length24.141921
Min length3

Characters and Unicode

Total characters66342
Distinct characters662
Distinct categories15 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1504 ?
Unique (%)54.7%

Sample

1st row2019 중앙통제소 윈도우 운영체제 구매
2nd row2019 경제경영연구소 STATA 통계프로그램 구매
3rd row2019 하반기 신입사원 기초연수 연수복 구매
4th row2019 인천생산기지 1공장 공기압축기 4기 구매
5th row2019 인천생산기지 1공장 공기압축기 4기 구매
ValueCountFrequency (%)
대체 488
 
3.6%
서소문s/s 487
 
3.6%
가스변압기 487
 
3.6%
공사(일반 487
 
3.6%
용역 304
 
2.3%
288
 
2.1%
구매 277
 
2.1%
268
 
2.0%
구매(긴급 79
 
0.6%
2019 76
 
0.6%
Other values (3986) 10252
76.0%
2023-12-12T18:19:52.600682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10762
 
16.2%
1450
 
2.2%
1435
 
2.2%
S 1362
 
2.1%
) 1232
 
1.9%
( 1232
 
1.9%
1120
 
1.7%
1016
 
1.5%
986
 
1.5%
1 901
 
1.4%
Other values (652) 44846
67.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 40746
61.4%
Space Separator 10762
 
16.2%
Uppercase Letter 4592
 
6.9%
Decimal Number 3678
 
5.5%
Lowercase Letter 2870
 
4.3%
Close Punctuation 1253
 
1.9%
Open Punctuation 1253
 
1.9%
Other Punctuation 882
 
1.3%
Dash Punctuation 174
 
0.3%
Connector Punctuation 49
 
0.1%
Other values (5) 83
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1450
 
3.6%
1435
 
3.5%
1120
 
2.7%
1016
 
2.5%
986
 
2.4%
751
 
1.8%
709
 
1.7%
707
 
1.7%
705
 
1.7%
654
 
1.6%
Other values (565) 31213
76.6%
Uppercase Letter
ValueCountFrequency (%)
S 1362
29.7%
P 307
 
6.7%
C 277
 
6.0%
A 273
 
5.9%
E 196
 
4.3%
T 190
 
4.1%
G 182
 
4.0%
D 180
 
3.9%
I 170
 
3.7%
R 165
 
3.6%
Other values (16) 1290
28.1%
Lowercase Letter
ValueCountFrequency (%)
e 361
12.6%
r 270
 
9.4%
o 252
 
8.8%
a 237
 
8.3%
i 231
 
8.0%
t 206
 
7.2%
n 188
 
6.6%
l 167
 
5.8%
u 118
 
4.1%
s 114
 
4.0%
Other values (16) 726
25.3%
Decimal Number
ValueCountFrequency (%)
1 901
24.5%
2 896
24.4%
0 787
21.4%
9 240
 
6.5%
3 202
 
5.5%
8 157
 
4.3%
7 147
 
4.0%
4 142
 
3.9%
5 120
 
3.3%
6 86
 
2.3%
Other Punctuation
ValueCountFrequency (%)
/ 640
72.6%
, 137
 
15.5%
· 60
 
6.8%
. 27
 
3.1%
: 7
 
0.8%
' 5
 
0.6%
& 5
 
0.6%
@ 1
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 29
72.5%
+ 5
 
12.5%
4
 
10.0%
= 1
 
2.5%
1
 
2.5%
Close Punctuation
ValueCountFrequency (%)
) 1232
98.3%
] 21
 
1.7%
Open Punctuation
ValueCountFrequency (%)
( 1232
98.3%
[ 21
 
1.7%
Initial Punctuation
ValueCountFrequency (%)
18
94.7%
1
 
5.3%
Space Separator
ValueCountFrequency (%)
10762
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 174
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 49
100.0%
Final Punctuation
ValueCountFrequency (%)
18
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 5
100.0%
Other Symbol
ValueCountFrequency (%)
° 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 40744
61.4%
Common 18134
27.3%
Latin 7462
 
11.2%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1450
 
3.6%
1435
 
3.5%
1120
 
2.7%
1016
 
2.5%
986
 
2.4%
751
 
1.8%
709
 
1.7%
707
 
1.7%
705
 
1.7%
654
 
1.6%
Other values (564) 31211
76.6%
Latin
ValueCountFrequency (%)
S 1362
 
18.3%
e 361
 
4.8%
P 307
 
4.1%
C 277
 
3.7%
A 273
 
3.7%
r 270
 
3.6%
o 252
 
3.4%
a 237
 
3.2%
i 231
 
3.1%
t 206
 
2.8%
Other values (42) 3686
49.4%
Common
ValueCountFrequency (%)
10762
59.3%
) 1232
 
6.8%
( 1232
 
6.8%
1 901
 
5.0%
2 896
 
4.9%
0 787
 
4.3%
/ 640
 
3.5%
9 240
 
1.3%
3 202
 
1.1%
- 174
 
1.0%
Other values (25) 1068
 
5.9%
Han
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 40743
61.4%
ASCII 25493
38.4%
None 61
 
0.1%
Punctuation 37
 
0.1%
Math Operators 5
 
< 0.1%
CJK 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10762
42.2%
S 1362
 
5.3%
) 1232
 
4.8%
( 1232
 
4.8%
1 901
 
3.5%
2 896
 
3.5%
0 787
 
3.1%
/ 640
 
2.5%
e 361
 
1.4%
P 307
 
1.2%
Other values (70) 7013
27.5%
Hangul
ValueCountFrequency (%)
1450
 
3.6%
1435
 
3.5%
1120
 
2.7%
1016
 
2.5%
986
 
2.4%
751
 
1.8%
709
 
1.7%
707
 
1.7%
705
 
1.7%
654
 
1.6%
Other values (563) 31210
76.6%
None
ValueCountFrequency (%)
· 60
98.4%
° 1
 
1.6%
Punctuation
ValueCountFrequency (%)
18
48.6%
18
48.6%
1
 
2.7%
Math Operators
ValueCountFrequency (%)
4
80.0%
1
 
20.0%
CJK
ValueCountFrequency (%)
2
100.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

업무구분명
Categorical

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size21.6 KiB
물품
1165 
공사
849 
용역
723 
외자
 
10
기타
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
물품 1165
42.4%
공사 849
30.9%
용역 723
26.3%
외자 10
 
0.4%
기타 1
 
< 0.1%

Length

2023-12-12T18:19:52.799625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:19:52.939912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
물품 1165
42.4%
공사 849
30.9%
용역 723
26.3%
외자 10
 
0.4%
기타 1
 
< 0.1%

계약체결형태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.6 KiB
총액계약
2711 
단가계약
 
37

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
총액계약 2711
98.7%
단가계약 37
 
1.3%

Length

2023-12-12T18:19:53.088031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:19:53.229342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
총액계약 2711
98.7%
단가계약 37
 
1.3%
Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.6 KiB
제한경쟁
1099 
일반경쟁
1024 
수의계약
590 
지명경쟁
 
35

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제한경쟁 1099
40.0%
일반경쟁 1024
37.3%
수의계약 590
21.5%
지명경쟁 35
 
1.3%

Length

2023-12-12T18:19:53.370183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:19:53.492315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제한경쟁 1099
40.0%
일반경쟁 1024
37.3%
수의계약 590
21.5%
지명경쟁 35
 
1.3%
Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size21.6 KiB
<NA>
1910 
적격심사제
637 
최저가 낙찰제
 
186
2단계 경쟁 및 규격·가격동시입찰
 
11
협상에 의한 계약
 
4

Length

Max length18
Median length4
Mean length4.4981805
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 1910
69.5%
적격심사제 637
 
23.2%
최저가 낙찰제 186
 
6.8%
2단계 경쟁 및 규격·가격동시입찰 11
 
0.4%
협상에 의한 계약 4
 
0.1%

Length

2023-12-12T18:19:53.655841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:19:53.797168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1910
64.2%
적격심사제 637
 
21.4%
최저가 186
 
6.3%
낙찰제 186
 
6.3%
2단계 11
 
0.4%
경쟁 11
 
0.4%
11
 
0.4%
규격·가격동시입찰 11
 
0.4%
협상에 4
 
0.1%
의한 4
 
0.1%

공고기관명
Categorical

Distinct7
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size21.6 KiB
한국석유공사
500 
한국전력공사
500 
한국수력원자력㈜
500 
한국전자통신연구원
500 
한국가스공사
410 
Other values (2)
338 

Length

Max length9
Median length6
Mean length6.6844978
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
한국석유공사 500
18.2%
한국전력공사 500
18.2%
한국수력원자력㈜ 500
18.2%
한국전자통신연구원 500
18.2%
한국가스공사 410
14.9%
강원랜드 281
10.2%
한전KDN 57
 
2.1%

Length

2023-12-12T18:19:53.953572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:19:54.093889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한국석유공사 500
18.2%
한국전력공사 500
18.2%
한국수력원자력㈜ 500
18.2%
한국전자통신연구원 500
18.2%
한국가스공사 410
14.9%
강원랜드 281
10.2%
한전kdn 57
 
2.1%
Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.6 KiB
<NA>
1910 
B410002
500 
Z003620
281 
B552059
 
57

Length

Max length7
Median length4
Mean length4.9148472
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 1910
69.5%
B410002 500
 
18.2%
Z003620 281
 
10.2%
B552059 57
 
2.1%

Length

2023-12-12T18:19:54.239972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:19:54.432685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1910
69.5%
b410002 500
 
18.2%
z003620 281
 
10.2%
b552059 57
 
2.1%

수요기관명
Categorical

Distinct7
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size21.6 KiB
한국석유공사
500 
한국전력공사
500 
한국수력원자력㈜
500 
한국전자통신연구원
500 
한국가스공사
410 
Other values (2)
338 

Length

Max length9
Median length6
Mean length6.6844978
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
한국석유공사 500
18.2%
한국전력공사 500
18.2%
한국수력원자력㈜ 500
18.2%
한국전자통신연구원 500
18.2%
한국가스공사 410
14.9%
강원랜드 281
10.2%
한전KDN 57
 
2.1%

Length

2023-12-12T18:19:54.613222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:19:54.783637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한국석유공사 500
18.2%
한국전력공사 500
18.2%
한국수력원자력㈜ 500
18.2%
한국전자통신연구원 500
18.2%
한국가스공사 410
14.9%
강원랜드 281
10.2%
한전kdn 57
 
2.1%
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.6 KiB
<NA>
1967 
B410002
500 
Z003620
281 

Length

Max length7
Median length4
Mean length4.8526201
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 1967
71.6%
B410002 500
 
18.2%
Z003620 281
 
10.2%

Length

2023-12-12T18:19:54.999442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:19:55.147950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1967
71.6%
b410002 500
 
18.2%
z003620 281
 
10.2%

낙찰하한율
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size21.6 KiB
<NA>
1974 
87.745
536 
88.0
 
97
80.495
 
91
87.995
 
47

Length

Max length6
Median length4
Mean length4.4894469
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 1974
71.8%
87.745 536
 
19.5%
88.0 97
 
3.5%
80.495 91
 
3.3%
87.995 47
 
1.7%
0.0 3
 
0.1%

Length

2023-12-12T18:19:55.328397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:19:55.470700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1974
71.8%
87.745 536
 
19.5%
88.0 97
 
3.5%
80.495 91
 
3.3%
87.995 47
 
1.7%
0.0 3
 
0.1%

추정가격
Real number (ℝ)

MISSING  SKEWED 

Distinct29
Distinct (%)3.7%
Missing1970
Missing (%)71.7%
Infinite0
Infinite (%)0.0%
Mean2.0366661 × 108
Minimum2740000
Maximum2.5101163 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.3 KiB
2023-12-12T18:19:55.641727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2740000
5-th percentile49438400
Q11.4682506 × 108
median1.4682506 × 108
Q31.4682506 × 108
95-th percentile3.210735 × 108
Maximum2.5101163 × 1010
Range2.5098423 × 1010
Interquartile range (IQR)0

Descriptive statistics

Standard deviation9.8239592 × 108
Coefficient of variation (CV)4.8235493
Kurtosis553.44545
Mean2.0366661 × 108
Median Absolute Deviation (MAD)0
Skewness22.882209
Sum1.5845262 × 1011
Variance9.6510175 × 1017
MonotonicityNot monotonic
2023-12-12T18:19:55.825575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
146825056 487
 
17.7%
258544000 62
 
2.3%
116300000 42
 
1.5%
109120000 32
 
1.2%
49438400 28
 
1.0%
321073500 27
 
1.0%
427636000 14
 
0.5%
223016000 12
 
0.4%
127373000 12
 
0.4%
60137000 8
 
0.3%
Other values (19) 54
 
2.0%
(Missing) 1970
71.7%
ValueCountFrequency (%)
2740000 1
 
< 0.1%
16287287 7
 
0.3%
24970055 4
 
0.1%
33583000 3
 
0.1%
45614281 6
 
0.2%
49073750 6
 
0.2%
49438400 28
1.0%
54618000 2
 
0.1%
60137000 8
 
0.3%
61050000 3
 
0.1%
ValueCountFrequency (%)
25101163128 1
 
< 0.1%
11336276694 1
 
< 0.1%
987560000 1
 
< 0.1%
523951230 1
 
< 0.1%
427636000 14
 
0.5%
321073500 27
1.0%
264000000 2
 
0.1%
258544000 62
2.3%
223016000 12
 
0.4%
212279980 1
 
< 0.1%

예정가격
Real number (ℝ)

MISSING  SKEWED 

Distinct29
Distinct (%)3.7%
Missing1970
Missing (%)71.7%
Infinite0
Infinite (%)0.0%
Mean2.1294473 × 108
Minimum2732275
Maximum2.5101163 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.3 KiB
2023-12-12T18:19:56.019574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2732275
5-th percentile49170033
Q11.6150978 × 108
median1.6150978 × 108
Q31.6150978 × 108
95-th percentile3.2142932 × 108
Maximum2.5101163 × 1010
Range2.5098431 × 1010
Interquartile range (IQR)0

Descriptive statistics

Standard deviation9.8186569 × 108
Coefficient of variation (CV)4.6108945
Kurtosis553.77811
Mean2.1294473 × 108
Median Absolute Deviation (MAD)0
Skewness22.890887
Sum1.65671 × 1011
Variance9.6406024 × 1017
MonotonicityNot monotonic
2023-12-12T18:19:56.200945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
161509778 487
 
17.7%
259233778 62
 
2.3%
115898813 42
 
1.5%
109125548 32
 
1.2%
49170033 28
 
1.0%
321429317 27
 
1.0%
429320916 14
 
0.5%
224614968 12
 
0.4%
126677552 12
 
0.4%
60111317 8
 
0.3%
Other values (19) 54
 
2.0%
(Missing) 1970
71.7%
ValueCountFrequency (%)
2732275 1
 
< 0.1%
17846513 7
 
0.3%
24763089 4
 
0.1%
33538682 3
 
0.1%
48965073 6
 
0.2%
49170033 28
1.0%
50447399 6
 
0.2%
54685962 2
 
0.1%
60111317 8
 
0.3%
61453868 3
 
0.1%
ValueCountFrequency (%)
25101163128 1
 
< 0.1%
11336276694 1
 
< 0.1%
957933200 1
 
< 0.1%
523951230 1
 
< 0.1%
429320916 14
 
0.5%
321429317 27
1.0%
261671808 2
 
0.1%
259233778 62
2.3%
224614968 12
 
0.4%
211000000 1
 
< 0.1%

기초금액
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.6 KiB
<NA>
2248 
161507561
487 
17916015
 
7
50175709
 
6

Length

Max length9
Median length4
Mean length4.9050218
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 2248
81.8%
161507561 487
 
17.7%
17916015 7
 
0.3%
50175709 6
 
0.2%

Length

2023-12-12T18:19:56.372652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:19:56.495237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2248
81.8%
161507561 487
 
17.7%
17916015 7
 
0.3%
50175709 6
 
0.2%
Distinct527
Distinct (%)19.2%
Missing0
Missing (%)0.0%
Memory size21.6 KiB
Minimum2017-01-03 00:00:00
Maximum2020-10-12 00:00:00
2023-12-12T18:19:56.652902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:19:56.847792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct383
Distinct (%)13.9%
Missing0
Missing (%)0.0%
Memory size21.6 KiB
Minimum2023-12-12 01:07:00
Maximum2023-12-12 20:40:00
2023-12-12T18:19:57.014663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:19:57.183541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

개찰결과구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.6 KiB
개찰완료
2659 
유찰
 
79
재입찰
 
10

Length

Max length4
Median length4
Mean length3.9388646
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개찰완료 2659
96.8%
유찰 79
 
2.9%
재입찰 10
 
0.4%

Length

2023-12-12T18:19:57.359881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:19:57.495767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개찰완료 2659
96.8%
유찰 79
 
2.9%
재입찰 10
 
0.4%

개찰순위
Real number (ℝ)

MISSING  ZEROS 

Distinct262
Distinct (%)38.8%
Missing2073
Missing (%)75.4%
Infinite0
Infinite (%)0.0%
Mean109.72
Minimum0
Maximum568
Zeros245
Zeros (%)8.9%
Negative0
Negative (%)0.0%
Memory size24.3 KiB
2023-12-12T18:19:57.618203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6
Q3176.5
95-th percentile497.2
Maximum568
Range568
Interquartile range (IQR)176.5

Descriptive statistics

Standard deviation173.39729
Coefficient of variation (CV)1.5803617
Kurtosis0.3591178
Mean109.72
Median Absolute Deviation (MAD)6
Skewness1.3737909
Sum74061
Variance30066.62
MonotonicityNot monotonic
2023-12-12T18:19:57.768795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 245
 
8.9%
1 29
 
1.1%
2 21
 
0.8%
3 16
 
0.6%
4 11
 
0.4%
6 10
 
0.4%
5 9
 
0.3%
11 7
 
0.3%
9 7
 
0.3%
7 7
 
0.3%
Other values (252) 313
 
11.4%
(Missing) 2073
75.4%
ValueCountFrequency (%)
0 245
8.9%
1 29
 
1.1%
2 21
 
0.8%
3 16
 
0.6%
4 11
 
0.4%
5 9
 
0.3%
6 10
 
0.4%
7 7
 
0.3%
8 6
 
0.2%
9 7
 
0.3%
ValueCountFrequency (%)
568 1
< 0.1%
567 1
< 0.1%
564 1
< 0.1%
562 1
< 0.1%
560 1
< 0.1%
559 1
< 0.1%
554 1
< 0.1%
553 1
< 0.1%
552 1
< 0.1%
551 1
< 0.1%
Distinct743
Distinct (%)95.1%
Missing1967
Missing (%)71.6%
Memory size21.6 KiB
2023-12-12T18:19:58.043901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters9372
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique710 ?
Unique (%)90.9%

Sample

1st row849-86-01145
2nd row137-87-01049
3rd row221-81-07157
4th row409-81-98603
5th row327-86-00613
ValueCountFrequency (%)
131-35-35805 3
 
0.4%
222-81-27627 3
 
0.4%
589-87-00649 3
 
0.4%
224-81-53330 3
 
0.4%
231-81-04517 3
 
0.4%
326-81-01031 2
 
0.3%
403-81-59276 2
 
0.3%
287-35-00292 2
 
0.3%
440-88-01675 2
 
0.3%
310-81-11193 2
 
0.3%
Other values (733) 756
96.8%
2023-12-12T18:19:58.861097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1562
16.7%
1 1473
15.7%
8 1068
11.4%
0 1006
10.7%
2 972
10.4%
6 607
 
6.5%
4 590
 
6.3%
5 556
 
5.9%
7 539
 
5.8%
3 533
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7810
83.3%
Dash Punctuation 1562
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1473
18.9%
8 1068
13.7%
0 1006
12.9%
2 972
12.4%
6 607
7.8%
4 590
7.6%
5 556
 
7.1%
7 539
 
6.9%
3 533
 
6.8%
9 466
 
6.0%
Dash Punctuation
ValueCountFrequency (%)
- 1562
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9372
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1562
16.7%
1 1473
15.7%
8 1068
11.4%
0 1006
10.7%
2 972
10.4%
6 607
 
6.5%
4 590
 
6.3%
5 556
 
5.9%
7 539
 
5.8%
3 533
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9372
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1562
16.7%
1 1473
15.7%
8 1068
11.4%
0 1006
10.7%
2 972
10.4%
6 607
 
6.5%
4 590
 
6.3%
5 556
 
5.9%
7 539
 
5.8%
3 533
 
5.7%

투찰업체명
Text

MISSING 

Distinct743
Distinct (%)95.1%
Missing1967
Missing (%)71.6%
Memory size21.6 KiB
2023-12-12T18:19:59.239077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length14
Mean length8.262484
Min length2

Characters and Unicode

Total characters6453
Distinct characters354
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique710 ?
Unique (%)90.9%

Sample

1st row근도종합건설(주)
2nd row에스씨건설(주)_01049
3rd row주식회사 진양
4th row주식회사 우진씨엔씨
5th row(주)부태종합건설
ValueCountFrequency (%)
주식회사 257
 
24.2%
10
 
0.9%
에스에이리테일 3
 
0.3%
에이트 3
 
0.3%
덕신전기상사(주 3
 
0.3%
주)태인 3
 
0.3%
빅스타건설(주 3
 
0.3%
오스타건설(주 2
 
0.2%
주안유통 2
 
0.2%
협동조합 2
 
0.2%
Other values (747) 773
72.9%
2023-12-12T18:19:59.788844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
647
 
10.0%
370
 
5.7%
325
 
5.0%
323
 
5.0%
) 314
 
4.9%
( 313
 
4.9%
283
 
4.4%
258
 
4.0%
243
 
3.8%
140
 
2.2%
Other values (344) 3237
50.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5445
84.4%
Close Punctuation 315
 
4.9%
Open Punctuation 313
 
4.9%
Space Separator 283
 
4.4%
Decimal Number 58
 
0.9%
Uppercase Letter 22
 
0.3%
Connector Punctuation 11
 
0.2%
Other Punctuation 3
 
< 0.1%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
647
 
11.9%
370
 
6.8%
325
 
6.0%
323
 
5.9%
258
 
4.7%
243
 
4.5%
140
 
2.6%
110
 
2.0%
108
 
2.0%
95
 
1.7%
Other values (309) 2826
51.9%
Uppercase Letter
ValueCountFrequency (%)
L 3
13.6%
E 2
 
9.1%
T 2
 
9.1%
C 2
 
9.1%
R 2
 
9.1%
G 2
 
9.1%
M 1
 
4.5%
J 1
 
4.5%
K 1
 
4.5%
O 1
 
4.5%
Other values (5) 5
22.7%
Decimal Number
ValueCountFrequency (%)
0 14
24.1%
1 9
15.5%
2 7
12.1%
8 6
10.3%
5 5
 
8.6%
3 4
 
6.9%
6 4
 
6.9%
9 4
 
6.9%
7 3
 
5.2%
4 2
 
3.4%
Lowercase Letter
ValueCountFrequency (%)
d 1
33.3%
t 1
33.3%
o 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 314
99.7%
1
 
0.3%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
, 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 313
100.0%
Space Separator
ValueCountFrequency (%)
283
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5436
84.2%
Common 983
 
15.2%
Latin 25
 
0.4%
Han 9
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
647
 
11.9%
370
 
6.8%
325
 
6.0%
323
 
5.9%
258
 
4.7%
243
 
4.5%
140
 
2.6%
110
 
2.0%
108
 
2.0%
95
 
1.7%
Other values (301) 2817
51.8%
Latin
ValueCountFrequency (%)
L 3
 
12.0%
E 2
 
8.0%
T 2
 
8.0%
C 2
 
8.0%
R 2
 
8.0%
G 2
 
8.0%
M 1
 
4.0%
J 1
 
4.0%
K 1
 
4.0%
O 1
 
4.0%
Other values (8) 8
32.0%
Common
ValueCountFrequency (%)
) 314
31.9%
( 313
31.8%
283
28.8%
0 14
 
1.4%
_ 11
 
1.1%
1 9
 
0.9%
2 7
 
0.7%
8 6
 
0.6%
5 5
 
0.5%
3 4
 
0.4%
Other values (7) 17
 
1.7%
Han
ValueCountFrequency (%)
2
22.2%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5436
84.2%
ASCII 1007
 
15.6%
CJK 9
 
0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
647
 
11.9%
370
 
6.8%
325
 
6.0%
323
 
5.9%
258
 
4.7%
243
 
4.5%
140
 
2.6%
110
 
2.0%
108
 
2.0%
95
 
1.7%
Other values (301) 2817
51.8%
ASCII
ValueCountFrequency (%)
) 314
31.2%
( 313
31.1%
283
28.1%
0 14
 
1.4%
_ 11
 
1.1%
1 9
 
0.9%
2 7
 
0.7%
8 6
 
0.6%
5 5
 
0.5%
3 4
 
0.4%
Other values (24) 41
 
4.1%
CJK
ValueCountFrequency (%)
2
22.2%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
None
ValueCountFrequency (%)
1
100.0%
Distinct733
Distinct (%)93.9%
Missing1967
Missing (%)71.6%
Memory size21.6 KiB
2023-12-12T18:20:00.299640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length3
Mean length3.0422535
Min length2

Characters and Unicode

Total characters2376
Distinct characters204
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique691 ?
Unique (%)88.5%

Sample

1st row김은미
2nd row박우연
3rd row홍순희
4th row정성희
5th row양명화
ValueCountFrequency (%)
이현정 3
 
0.4%
정종길 3
 
0.4%
정내희 3
 
0.4%
김동미 3
 
0.4%
전영규 3
 
0.4%
태은경 3
 
0.4%
조민구 2
 
0.3%
이상원 2
 
0.3%
차상호 2
 
0.3%
이영두 2
 
0.3%
Other values (727) 759
96.7%
2023-12-12T18:20:00.904435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
151
 
6.4%
128
 
5.4%
99
 
4.2%
63
 
2.7%
58
 
2.4%
48
 
2.0%
47
 
2.0%
45
 
1.9%
41
 
1.7%
41
 
1.7%
Other values (194) 1655
69.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2354
99.1%
Uppercase Letter 12
 
0.5%
Space Separator 4
 
0.2%
Other Punctuation 4
 
0.2%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
151
 
6.4%
128
 
5.4%
99
 
4.2%
63
 
2.7%
58
 
2.5%
48
 
2.0%
47
 
2.0%
45
 
1.9%
41
 
1.7%
41
 
1.7%
Other values (182) 1633
69.4%
Uppercase Letter
ValueCountFrequency (%)
A 2
16.7%
N 2
16.7%
O 2
16.7%
G 2
16.7%
D 1
8.3%
J 1
8.3%
I 1
8.3%
H 1
8.3%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2354
99.1%
Latin 12
 
0.5%
Common 10
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
151
 
6.4%
128
 
5.4%
99
 
4.2%
63
 
2.7%
58
 
2.5%
48
 
2.0%
47
 
2.0%
45
 
1.9%
41
 
1.7%
41
 
1.7%
Other values (182) 1633
69.4%
Latin
ValueCountFrequency (%)
A 2
16.7%
N 2
16.7%
O 2
16.7%
G 2
16.7%
D 1
8.3%
J 1
8.3%
I 1
8.3%
H 1
8.3%
Common
ValueCountFrequency (%)
4
40.0%
, 4
40.0%
) 1
 
10.0%
( 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2354
99.1%
ASCII 22
 
0.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
151
 
6.4%
128
 
5.4%
99
 
4.2%
63
 
2.7%
58
 
2.5%
48
 
2.0%
47
 
2.0%
45
 
1.9%
41
 
1.7%
41
 
1.7%
Other values (182) 1633
69.4%
ASCII
ValueCountFrequency (%)
4
18.2%
, 4
18.2%
A 2
9.1%
N 2
9.1%
O 2
9.1%
G 2
9.1%
D 1
 
4.5%
J 1
 
4.5%
I 1
 
4.5%
) 1
 
4.5%
Other values (2) 2
9.1%

투찰금액
Real number (ℝ)

MISSING  SKEWED 

Distinct780
Distinct (%)100.0%
Missing1968
Missing (%)71.6%
Infinite0
Infinite (%)0.0%
Mean1.9141488 × 108
Minimum107000
Maximum2.505096 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.3 KiB
2023-12-12T18:20:01.104817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum107000
5-th percentile43659421
Q11.4190186 × 108
median1.428421 × 108
Q31.4367137 × 108
95-th percentile2.584049 × 108
Maximum2.505096 × 1010
Range2.5050853 × 1010
Interquartile range (IQR)1769514.8

Descriptive statistics

Standard deviation9.792852 × 108
Coefficient of variation (CV)5.116035
Kurtosis555.87637
Mean1.9141488 × 108
Median Absolute Deviation (MAD)879095
Skewness22.949574
Sum1.493036 × 1011
Variance9.589995 × 1017
MonotonicityNot monotonic
2023-12-12T18:20:01.328158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
142269430 1
 
< 0.1%
142168677 1
 
< 0.1%
142580720 1
 
< 0.1%
143034000 1
 
< 0.1%
144263500 1
 
< 0.1%
143964100 1
 
< 0.1%
143707700 1
 
< 0.1%
142736950 1
 
< 0.1%
145610108 1
 
< 0.1%
144034000 1
 
< 0.1%
Other values (770) 770
 
28.0%
(Missing) 1968
71.6%
ValueCountFrequency (%)
107000 1
< 0.1%
110900 1
< 0.1%
133000 1
< 0.1%
2730000 1
< 0.1%
15707700 1
< 0.1%
15739400 1
< 0.1%
15741000 1
< 0.1%
15770000 1
< 0.1%
15775800 1
< 0.1%
15802000 1
< 0.1%
ValueCountFrequency (%)
25050960000 1
< 0.1%
11333400000 1
< 0.1%
948057000 1
< 0.1%
522500000 1
< 0.1%
427636000 1
< 0.1%
379451000 1
< 0.1%
376845700 1
< 0.1%
376716993 1
< 0.1%
376563430 1
< 0.1%
375892580 1
< 0.1%

투찰율
Real number (ℝ)

MISSING 

Distinct415
Distinct (%)83.0%
Missing2248
Missing (%)81.8%
Infinite0
Infinite (%)0.0%
Mean88.501234
Minimum87.272
Maximum94.19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.3 KiB
2023-12-12T18:20:01.531931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum87.272
5-th percentile87.8311
Q188.203
median88.487
Q388.78125
95-th percentile89.2004
Maximum94.19
Range6.918
Interquartile range (IQR)0.57825

Descriptive statistics

Standard deviation0.50172727
Coefficient of variation (CV)0.0056691556
Kurtosis32.129504
Mean88.501234
Median Absolute Deviation (MAD)0.288
Skewness2.9241745
Sum44250.617
Variance0.25173025
MonotonicityNot monotonic
2023-12-12T18:20:01.724312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
88.016 4
 
0.1%
88.333 4
 
0.1%
87.91 3
 
0.1%
88.235 3
 
0.1%
88.268 3
 
0.1%
88.096 3
 
0.1%
88.343 3
 
0.1%
88.586 3
 
0.1%
88.754 3
 
0.1%
88.978 2
 
0.1%
Other values (405) 469
 
17.1%
(Missing) 2248
81.8%
ValueCountFrequency (%)
87.272 1
< 0.1%
87.301 1
< 0.1%
87.434 1
< 0.1%
87.45 1
< 0.1%
87.456 1
< 0.1%
87.488 1
< 0.1%
87.57 1
< 0.1%
87.585 1
< 0.1%
87.643 1
< 0.1%
87.663 1
< 0.1%
ValueCountFrequency (%)
94.19 1
< 0.1%
90.156 1
< 0.1%
89.554 1
< 0.1%
89.544 1
< 0.1%
89.484 1
< 0.1%
89.482 1
< 0.1%
89.413 1
< 0.1%
89.41 1
< 0.1%
89.406 1
< 0.1%
89.392 1
< 0.1%

투찰일자
Categorical

IMBALANCE 

Distinct25
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size21.6 KiB
<NA>
1968 
2020-10-06
248 
2020-10-05
 
143
2020-08-21
 
99
2020-10-07
 
99
Other values (20)
 
191

Length

Max length10
Median length4
Mean length5.7030568
Min length4

Unique

Unique4 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 1968
71.6%
2020-10-06 248
 
9.0%
2020-10-05 143
 
5.2%
2020-08-21 99
 
3.6%
2020-10-07 99
 
3.6%
2020-08-12 41
 
1.5%
2020-09-01 33
 
1.2%
2020-08-25 29
 
1.1%
2020-08-27 27
 
1.0%
2020-09-02 23
 
0.8%
Other values (15) 38
 
1.4%

Length

2023-12-12T18:20:01.931579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1968
71.6%
2020-10-06 248
 
9.0%
2020-10-05 143
 
5.2%
2020-08-21 99
 
3.6%
2020-10-07 99
 
3.6%
2020-08-12 41
 
1.5%
2020-09-01 33
 
1.2%
2020-08-25 29
 
1.1%
2020-08-27 27
 
1.0%
2020-09-02 23
 
0.8%
Other values (15) 38
 
1.4%

투찰시각
Date

MISSING 

Distinct176
Distinct (%)22.6%
Missing1968
Missing (%)71.6%
Memory size21.6 KiB
Minimum2023-12-12 00:10:00
Maximum2023-12-12 23:10:00
2023-12-12T18:20:02.126891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:20:02.304081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

낙찰여부
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.6 KiB
1967 
N
752 
Y
 
29

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1967
71.6%
N 752
 
27.4%
Y 29
 
1.1%

Length

2023-12-12T18:20:02.472733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:20:02.604361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 752
96.3%
y 29
 
3.7%

부적격사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2748
Missing (%)100.0%
Memory size24.3 KiB

최종낙찰금액
Real number (ℝ)

MISSING  SKEWED 

Distinct86
Distinct (%)10.3%
Missing1910
Missing (%)69.5%
Infinite0
Infinite (%)0.0%
Mean1.8934366 × 108
Minimum107000
Maximum2.505096 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.3 KiB
2023-12-12T18:20:02.768727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum107000
5-th percentile43291123
Q11.404323 × 108
median1.4291892 × 108
Q31.4291892 × 108
95-th percentile2.58779 × 108
Maximum2.505096 × 1010
Range2.5050853 × 1010
Interquartile range (IQR)2486615

Descriptive statistics

Standard deviation9.4821375 × 108
Coefficient of variation (CV)5.007898
Kurtosis588.66112
Mean1.8934366 × 108
Median Absolute Deviation (MAD)0
Skewness23.540429
Sum1.5866999 × 1011
Variance8.9910931 × 1017
MonotonicityNot monotonic
2023-12-12T18:20:03.005934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
142918915 487
 
17.7%
208739338 62
 
2.3%
102050000 42
 
1.5%
96094191 32
 
1.2%
43319220 28
 
1.0%
258779000 27
 
1.0%
376716993 14
 
0.5%
111504480 12
 
0.4%
198840000 12
 
0.4%
52804624 8
 
0.3%
Other values (76) 114
 
4.1%
(Missing) 1910
69.5%
ValueCountFrequency (%)
107000 3
0.1%
348315 1
 
< 0.1%
2730000 1
 
< 0.1%
11126400 1
 
< 0.1%
11365200 1
 
< 0.1%
11400000 1
 
< 0.1%
12878000 1
 
< 0.1%
14080000 1
 
< 0.1%
15707700 7
0.3%
16890940 1
 
< 0.1%
ValueCountFrequency (%)
25050960000 1
 
< 0.1%
11333400000 1
 
< 0.1%
1999800000 1
 
< 0.1%
1045000000 1
 
< 0.1%
948057000 1
 
< 0.1%
850890403 1
 
< 0.1%
545965200 1
 
< 0.1%
522500000 1
 
< 0.1%
404316000 1
 
< 0.1%
376716993 14
0.5%

최종낙찰율
Real number (ℝ)

MISSING 

Distinct49
Distinct (%)8.8%
Missing2191
Missing (%)79.7%
Infinite0
Infinite (%)0.0%
Mean88.708327
Minimum76.035
Maximum97.44
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.3 KiB
2023-12-12T18:20:03.198164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum76.035
5-th percentile88.489
Q188.489
median88.489
Q388.489
95-th percentile91
Maximum97.44
Range21.405
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.3159832
Coefficient of variation (CV)0.014834946
Kurtosis39.47053
Mean88.708327
Median Absolute Deviation (MAD)0
Skewness-0.83678618
Sum49410.538
Variance1.7318118
MonotonicityNot monotonic
2023-12-12T18:20:03.367054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
88.489 487
 
17.7%
88.016 7
 
0.3%
91.0 6
 
0.2%
88.062 6
 
0.2%
90.999 3
 
0.1%
86.999 2
 
0.1%
90.869 2
 
0.1%
91.999 2
 
0.1%
92.0 2
 
0.1%
76.035 1
 
< 0.1%
Other values (39) 39
 
1.4%
(Missing) 2191
79.7%
ValueCountFrequency (%)
76.035 1
 
< 0.1%
76.046 1
 
< 0.1%
86.356 1
 
< 0.1%
86.976 1
 
< 0.1%
86.999 2
 
0.1%
87.994 1
 
< 0.1%
88.016 7
 
0.3%
88.062 6
 
0.2%
88.489 487
17.7%
88.526 1
 
< 0.1%
ValueCountFrequency (%)
97.44 1
< 0.1%
95.999 1
< 0.1%
95.513 1
< 0.1%
94.999 1
< 0.1%
94.994 1
< 0.1%
94.868 1
< 0.1%
93.5 1
< 0.1%
93.009 1
< 0.1%
92.753 1
< 0.1%
92.701 1
< 0.1%

최종낙찰일자
Categorical

IMBALANCE 

Distinct21
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size21.6 KiB
<NA>
2191 
2020-10-13
487 
2020-08-28
 
8
2020-10-12
 
7
2020-08-13
 
7
Other values (16)
 
48

Length

Max length10
Median length4
Mean length5.2161572
Min length4

Unique

Unique4 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 2191
79.7%
2020-10-13 487
 
17.7%
2020-08-28 8
 
0.3%
2020-10-12 7
 
0.3%
2020-08-13 7
 
0.3%
2020-10-14 6
 
0.2%
2020-08-26 5
 
0.2%
2020-08-06 5
 
0.2%
2020-08-18 4
 
0.1%
2020-08-10 4
 
0.1%
Other values (11) 24
 
0.9%

Length

2023-12-12T18:20:03.549708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2191
79.7%
2020-10-13 487
 
17.7%
2020-08-28 8
 
0.3%
2020-10-12 7
 
0.3%
2020-08-13 7
 
0.3%
2020-10-14 6
 
0.2%
2020-08-26 5
 
0.2%
2020-08-06 5
 
0.2%
2020-08-18 4
 
0.1%
2020-08-10 4
 
0.1%
Other values (11) 24
 
0.9%

최종낙찰업체명
Text

MISSING 

Distinct82
Distinct (%)9.8%
Missing1910
Missing (%)69.5%
Memory size21.6 KiB
2023-12-12T18:20:03.785121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length10.019093
Min length3

Characters and Unicode

Total characters8396
Distinct characters185
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

Unique56 ?
Unique (%)6.7%

Sample

1st row주식회사 운산아이에스
2nd row(주)에이바이트
3rd row주식회사 플랜잇파트너스
4th row(주)투비젠
5th row베스핀글로벌 주식회사
ValueCountFrequency (%)
주식회사 514
36.0%
신화티앤에스 487
34.2%
에스케이엠앤서비스(주 62
 
4.3%
43
 
3.0%
세일냉열 42
 
2.9%
한국자동차유리 32
 
2.2%
윤스 28
 
2.0%
리테일 28
 
2.0%
주)에이치케이씨 27
 
1.9%
주)부태종합건설 14
 
1.0%
Other values (78) 149
 
10.4%
2023-12-12T18:20:04.248563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
740
 
8.8%
664
 
7.9%
591
 
7.0%
588
 
7.0%
555
 
6.6%
549
 
6.5%
537
 
6.4%
535
 
6.4%
505
 
6.0%
493
 
5.9%
Other values (175) 2639
31.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7364
87.7%
Space Separator 588
 
7.0%
Open Punctuation 204
 
2.4%
Close Punctuation 204
 
2.4%
Decimal Number 30
 
0.4%
Connector Punctuation 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
740
10.0%
664
 
9.0%
591
 
8.0%
555
 
7.5%
549
 
7.5%
537
 
7.3%
535
 
7.3%
505
 
6.9%
493
 
6.7%
489
 
6.6%
Other values (167) 1706
23.2%
Decimal Number
ValueCountFrequency (%)
1 12
40.0%
2 6
20.0%
7 6
20.0%
0 6
20.0%
Space Separator
ValueCountFrequency (%)
588
100.0%
Open Punctuation
ValueCountFrequency (%)
( 204
100.0%
Close Punctuation
ValueCountFrequency (%)
) 204
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7364
87.7%
Common 1032
 
12.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
740
10.0%
664
 
9.0%
591
 
8.0%
555
 
7.5%
549
 
7.5%
537
 
7.3%
535
 
7.3%
505
 
6.9%
493
 
6.7%
489
 
6.6%
Other values (167) 1706
23.2%
Common
ValueCountFrequency (%)
588
57.0%
( 204
 
19.8%
) 204
 
19.8%
1 12
 
1.2%
_ 6
 
0.6%
2 6
 
0.6%
7 6
 
0.6%
0 6
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7364
87.7%
ASCII 1032
 
12.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
740
10.0%
664
 
9.0%
591
 
8.0%
555
 
7.5%
549
 
7.5%
537
 
7.3%
535
 
7.3%
505
 
6.9%
493
 
6.7%
489
 
6.6%
Other values (167) 1706
23.2%
ASCII
ValueCountFrequency (%)
588
57.0%
( 204
 
19.8%
) 204
 
19.8%
1 12
 
1.2%
_ 6
 
0.6%
2 6
 
0.6%
7 6
 
0.6%
0 6
 
0.6%
Distinct81
Distinct (%)9.7%
Missing1910
Missing (%)69.5%
Memory size21.6 KiB
2023-12-12T18:20:04.499390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.0107399
Min length3

Characters and Unicode

Total characters2523
Distinct characters90
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)6.6%

Sample

1st row송창규
2nd row나성일
3rd row정성일
4th row이재훈
5th row이해민,이존한주
ValueCountFrequency (%)
이용철 488
58.2%
박윤택 62
 
7.4%
전영만 42
 
5.0%
류승현 32
 
3.8%
김민호 28
 
3.3%
채희관 27
 
3.2%
양명화 14
 
1.7%
김석원 12
 
1.4%
정명희 12
 
1.4%
김은자 8
 
1.0%
Other values (71) 113
 
13.5%
2023-12-12T18:20:04.929739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
526
20.8%
506
20.1%
489
19.4%
70
 
2.8%
67
 
2.7%
65
 
2.6%
62
 
2.5%
49
 
1.9%
44
 
1.7%
43
 
1.7%
Other values (80) 602
23.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2521
99.9%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
526
20.9%
506
20.1%
489
19.4%
70
 
2.8%
67
 
2.7%
65
 
2.6%
62
 
2.5%
49
 
1.9%
44
 
1.7%
43
 
1.7%
Other values (79) 600
23.8%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2521
99.9%
Common 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
526
20.9%
506
20.1%
489
19.4%
70
 
2.8%
67
 
2.7%
65
 
2.6%
62
 
2.5%
49
 
1.9%
44
 
1.7%
43
 
1.7%
Other values (79) 600
23.8%
Common
ValueCountFrequency (%)
, 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2521
99.9%
ASCII 2
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
526
20.9%
506
20.1%
489
19.4%
70
 
2.8%
67
 
2.7%
65
 
2.6%
62
 
2.5%
49
 
1.9%
44
 
1.7%
43
 
1.7%
Other values (79) 600
23.8%
ASCII
ValueCountFrequency (%)
, 2
100.0%

최종낙찰업체담당자명
Categorical

IMBALANCE 

Distinct31
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size21.6 KiB
<NA>
1967 
이용철
487 
염한탁
 
62
류현자
 
42
류승현
 
32
Other values (26)
 
158

Length

Max length4
Median length4
Mean length3.7157933
Min length3

Unique

Unique8 ?
Unique (%)0.3%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 1967
71.6%
이용철 487
 
17.7%
염한탁 62
 
2.3%
류현자 42
 
1.5%
류승현 32
 
1.2%
김민호 28
 
1.0%
채기훈 27
 
1.0%
양희태 14
 
0.5%
김석원 12
 
0.4%
정명희 12
 
0.4%
Other values (21) 65
 
2.4%

Length

2023-12-12T18:20:05.081833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1967
71.6%
이용철 487
 
17.7%
염한탁 62
 
2.3%
류현자 42
 
1.5%
류승현 32
 
1.2%
김민호 28
 
1.0%
채기훈 27
 
1.0%
양희태 14
 
0.5%
김석원 12
 
0.4%
정명희 12
 
0.4%
Other values (21) 65
 
2.4%
Distinct82
Distinct (%)9.8%
Missing1910
Missing (%)69.5%
Memory size21.6 KiB
2023-12-12T18:20:05.278322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters10056
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)6.7%

Sample

1st row114-86-89763
2nd row408-86-15055
3rd row129-86-63988
4th row206-86-32782
5th row638-87-00223
ValueCountFrequency (%)
206-68-68612 487
58.1%
220-81-76893 62
 
7.4%
224-81-13361 42
 
5.0%
224-10-25718 32
 
3.8%
341-66-00265 28
 
3.3%
311-81-22413 27
 
3.2%
327-86-00613 14
 
1.7%
225-02-60732 12
 
1.4%
608-81-33283 12
 
1.4%
129-81-72430 8
 
1.0%
Other values (72) 114
 
13.6%
2023-12-12T18:20:05.656699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 2310
23.0%
- 1676
16.7%
2 1564
15.6%
8 1408
14.0%
1 1136
11.3%
0 858
 
8.5%
3 383
 
3.8%
4 213
 
2.1%
7 203
 
2.0%
5 164
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8380
83.3%
Dash Punctuation 1676
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 2310
27.6%
2 1564
18.7%
8 1408
16.8%
1 1136
13.6%
0 858
 
10.2%
3 383
 
4.6%
4 213
 
2.5%
7 203
 
2.4%
5 164
 
2.0%
9 141
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 1676
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10056
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 2310
23.0%
- 1676
16.7%
2 1564
15.6%
8 1408
14.0%
1 1136
11.3%
0 858
 
8.5%
3 383
 
3.8%
4 213
 
2.1%
7 203
 
2.0%
5 164
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10056
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 2310
23.0%
- 1676
16.7%
2 1564
15.6%
8 1408
14.0%
1 1136
11.3%
0 858
 
8.5%
3 383
 
3.8%
4 213
 
2.1%
7 203
 
2.0%
5 164
 
1.6%

최종낙찰업체주소
Categorical

IMBALANCE 

Distinct31
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size21.6 KiB
<NA>
1967 
서울특별시 성동구 성수이로
487 
04569 서울특별시 중구 퇴계로 385 11층 (흥인동, 준타워)
 
62
220040 강원 원주시 명륜동 279-12
 
42
26411 강원도 원주시 원문로 107-10 단계동 (단계동)
 
32
Other values (26)
 
158

Length

Max length55
Median length4
Mean length9.0232897
Min length4

Unique

Unique8 ?
Unique (%)0.3%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 1967
71.6%
서울특별시 성동구 성수이로 487
 
17.7%
04569 서울특별시 중구 퇴계로 385 11층 (흥인동, 준타워) 62
 
2.3%
220040 강원 원주시 명륜동 279-12 42
 
1.5%
26411 강원도 원주시 원문로 107-10 단계동 (단계동) 32
 
1.2%
21679 인천광역시 남동구 앵고개로815번길 22 302-705 (논현동, 소래휴먼시아3단지) 28
 
1.0%
33435 충청남도 보령시 큰오랏1길 94-7 2층 (동대동, 서울학원) 27
 
1.0%
24210 강원도 춘천시 동면 소양강로 344-12 14
 
0.5%
26229 강원도 영월군 영월읍 영월로 2103 12
 
0.4%
24635 강원도 인제군 인제읍 인제로 216-1 2층 제2호 12
 
0.4%
Other values (21) 65
 
2.4%

Length

2023-12-12T18:20:05.842851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1967
36.0%
서울특별시 561
 
10.3%
성동구 489
 
9.0%
성수이로 487
 
8.9%
강원도 101
 
1.8%
원주시 74
 
1.4%
단계동 64
 
1.2%
385 62
 
1.1%
퇴계로 62
 
1.1%
04569 62
 
1.1%
Other values (150) 1532
28.1%
Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size21.6 KiB
<NA>
1967 
02-249-9948
487 
000-0000-0000
281 
02-256-6394
 
7
043-383-3856
 
6

Length

Max length13
Median length4
Mean length6.1961426
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 1967
71.6%
02-249-9948 487
 
17.7%
000-0000-0000 281
 
10.2%
02-256-6394 7
 
0.3%
043-383-3856 6
 
0.2%

Length

2023-12-12T18:20:06.015720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:20:06.180368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1967
71.6%
02-249-9948 487
 
17.7%
000-0000-0000 281
 
10.2%
02-256-6394 7
 
0.3%
043-383-3856 6
 
0.2%
Distinct7
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size21.6 KiB
2020-10-19
500 
2020-10-20
500 
2020-09-20
500 
2020-09-30
500 
2020-03-31
410 
Other values (2)
338 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-03-31
2nd row2020-03-31
3rd row2020-03-31
4th row2020-03-31
5th row2020-03-31

Common Values

ValueCountFrequency (%)
2020-10-19 500
18.2%
2020-10-20 500
18.2%
2020-09-20 500
18.2%
2020-09-30 500
18.2%
2020-03-31 410
14.9%
2020-09-29 281
10.2%
2020-09-25 57
 
2.1%

Length

2023-12-12T18:20:06.336076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:20:06.479310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-10-19 500
18.2%
2020-10-20 500
18.2%
2020-09-20 500
18.2%
2020-09-30 500
18.2%
2020-03-31 410
14.9%
2020-09-29 281
10.2%
2020-09-25 57
 
2.1%
Distinct7
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size21.6 KiB
B410005
500 
B410002
500 
B552041
500 
B551963
500 
B551210
410 
Other values (2)
338 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowB551210
2nd rowB551210
3rd rowB551210
4th rowB551210
5th rowB551210

Common Values

ValueCountFrequency (%)
B410005 500
18.2%
B410002 500
18.2%
B552041 500
18.2%
B551963 500
18.2%
B551210 410
14.9%
B552525 281
10.2%
B552059 57
 
2.1%

Length

2023-12-12T18:20:06.647366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:20:06.818424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
b410005 500
18.2%
b410002 500
18.2%
b552041 500
18.2%
b551963 500
18.2%
b551210 410
14.9%
b552525 281
10.2%
b552059 57
 
2.1%

제공기관명
Categorical

Distinct7
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size21.6 KiB
한국석유공사
500 
한국전력공사
500 
한국수력원자력(주)
500 
한국전자통신연구원
500 
한국가스공사
410 
Other values (2)
338 

Length

Max length10
Median length6
Mean length7.4173945
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
한국석유공사 500
18.2%
한국전력공사 500
18.2%
한국수력원자력(주) 500
18.2%
한국전자통신연구원 500
18.2%
한국가스공사 410
14.9%
(주)강원랜드 281
10.2%
한전KDN(주) 57
 
2.1%

Length

2023-12-12T18:20:07.030954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:20:07.222065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한국석유공사 500
18.2%
한국전력공사 500
18.2%
한국수력원자력(주 500
18.2%
한국전자통신연구원 500
18.2%
한국가스공사 410
14.9%
주)강원랜드 281
10.2%
한전kdn(주 57
 
2.1%

Sample

입찰공고번호입찰공고차수입찰공고명업무구분명계약체결형태명계약체결방법명낙찰자결정방법명공고기관명공고기관코드수요기관명수요기관코드낙찰하한율추정가격예정가격기초금액개찰일자개찰시각개찰결과구분명개찰순위투찰업체사업자등록번호투찰업체명투찰업체대표자명투찰금액투찰율투찰일자투찰시각낙찰여부부적격사유최종낙찰금액최종낙찰율최종낙찰일자최종낙찰업체명최종낙찰업체대표자명최종낙찰업체담당자명최종낙찰업체사업자등록번호최종낙찰업체주소최종낙찰업체연락전화번호데이터기준일자제공기관코드제공기관명
02019073110<NA>2019 중앙통제소 윈도우 운영체제 구매물품총액계약수의계약<NA>한국가스공사<NA>한국가스공사<NA><NA><NA><NA><NA>2019-08-0614:12개찰완료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020-03-31B551210한국가스공사
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22019080625<NA>2019 하반기 신입사원 기초연수 연수복 구매물품총액계약수의계약<NA>한국가스공사<NA>한국가스공사<NA><NA><NA><NA><NA>2019-08-0711:05개찰완료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020-03-31B551210한국가스공사
32019071725<NA>2019 인천생산기지 1공장 공기압축기 4기 구매물품총액계약제한경쟁<NA>한국가스공사<NA>한국가스공사<NA><NA><NA><NA><NA>2019-08-0818:14개찰완료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020-03-31B551210한국가스공사
42019071725<NA>2019 인천생산기지 1공장 공기압축기 4기 구매물품총액계약제한경쟁<NA>한국가스공사<NA>한국가스공사<NA><NA><NA><NA><NA>2019-08-0818:14개찰완료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020-03-31B551210한국가스공사
52019080517<NA>(재공고)2019 AutoCAD Mechanical 외 2종 라이선스 갱신물품총액계약제한경쟁<NA>한국가스공사<NA>한국가스공사<NA><NA><NA><NA><NA>2019-08-1211:28개찰완료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020-03-31B551210한국가스공사
62019080221<NA>2019 평택 2기지· 통영기지 계측제어시스템 정보보안 강화용 자재구매물품총액계약수의계약<NA>한국가스공사<NA>한국가스공사<NA><NA><NA><NA><NA>2019-08-0818:48개찰완료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020-03-31B551210한국가스공사
72019080221<NA>2019 평택 2기지· 통영기지 계측제어시스템 정보보안 강화용 자재구매물품총액계약수의계약<NA>한국가스공사<NA>한국가스공사<NA><NA><NA><NA><NA>2019-08-0818:48개찰완료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020-03-31B551210한국가스공사
82019081606<NA>2019 보안기획부 노트북 구매물품총액계약수의계약<NA>한국가스공사<NA>한국가스공사<NA><NA><NA><NA><NA>2019-08-2910:22개찰완료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020-03-31B551210한국가스공사
92019082926<NA>2019 전자조달시스템 파일관리솔루션 구매물품총액계약수의계약<NA>한국가스공사<NA>한국가스공사<NA><NA><NA><NA><NA>2019-09-0314:13개찰완료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020-03-31B551210한국가스공사
입찰공고번호입찰공고차수입찰공고명업무구분명계약체결형태명계약체결방법명낙찰자결정방법명공고기관명공고기관코드수요기관명수요기관코드낙찰하한율추정가격예정가격기초금액개찰일자개찰시각개찰결과구분명개찰순위투찰업체사업자등록번호투찰업체명투찰업체대표자명투찰금액투찰율투찰일자투찰시각낙찰여부부적격사유최종낙찰금액최종낙찰율최종낙찰일자최종낙찰업체명최종낙찰업체대표자명최종낙찰업체담당자명최종낙찰업체사업자등록번호최종낙찰업체주소최종낙찰업체연락전화번호데이터기준일자제공기관코드제공기관명
2738EA20202322<NA>저지연 이산 푸리에 변환기 제작용역총액계약일반경쟁<NA>한국전자통신연구원<NA>한국전자통신연구원<NA><NA><NA><NA><NA>2020-09-1415:00개찰완료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020-09-30B551963한국전자통신연구원
2739EA20202311<NA>Ouster OS1-128 외 1건물품총액계약수의계약<NA>한국전자통신연구원<NA>한국전자통신연구원<NA><NA><NA><NA><NA>2020-09-0916:30개찰완료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020-09-30B551963한국전자통신연구원
2740EA20202315<NA>딥러닝 기반 행동 탐지 및 인식 인터페이스 개발용역총액계약일반경쟁<NA>한국전자통신연구원<NA>한국전자통신연구원<NA><NA><NA><NA><NA>2020-09-1112:00개찰완료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020-09-30B551963한국전자통신연구원
2741EA20202288<NA>Dell Kit, NVIDIA Tesla V100 32G Passive GPU for DSS8440물품총액계약일반경쟁<NA>한국전자통신연구원<NA>한국전자통신연구원<NA><NA><NA><NA><NA>2020-09-1110:00개찰완료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020-09-30B551963한국전자통신연구원
2742EE20201250<NA>ASUS Processor Kit 외 10건물품총액계약일반경쟁<NA>한국전자통신연구원<NA>한국전자통신연구원<NA><NA><NA><NA><NA>2020-09-1109:30개찰완료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020-09-30B551963한국전자통신연구원
2743EE20201251<NA>비정형 데이터 및 영상 처리 시스템 부속품 - HLT003S-001 외 6건물품총액계약일반경쟁<NA>한국전자통신연구원<NA>한국전자통신연구원<NA><NA><NA><NA><NA>2020-09-1109:30개찰완료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020-09-30B551963한국전자통신연구원
2744EE20201252<NA>QNAP TS-832X-2G (8베이) Case물품총액계약일반경쟁<NA>한국전자통신연구원<NA>한국전자통신연구원<NA><NA><NA><NA><NA>2020-09-1109:30개찰완료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020-09-30B551963한국전자통신연구원
2745EA20202302<NA>웹 기반 스마트온실 표준장비규격 및 시험관리규격 관리 기능 개발용역총액계약일반경쟁<NA>한국전자통신연구원<NA>한국전자통신연구원<NA><NA><NA><NA><NA>2020-09-1415:00개찰완료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020-09-30B551963한국전자통신연구원
2746EE20201253<NA>머신러닝용 워크스테이션물품총액계약일반경쟁<NA>한국전자통신연구원<NA>한국전자통신연구원<NA><NA><NA><NA><NA>2020-09-1018:00개찰완료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020-09-30B551963한국전자통신연구원
2747EA20202158<NA>ATSC 3.0 Lite Rx 외 1건물품총액계약제한경쟁<NA>한국전자통신연구원<NA>한국전자통신연구원<NA><NA><NA><NA><NA>2020-09-1414:00개찰완료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020-09-30B551963한국전자통신연구원

Duplicate rows

Most frequently occurring

입찰공고번호입찰공고차수입찰공고명업무구분명계약체결형태명계약체결방법명낙찰자결정방법명공고기관명공고기관코드수요기관명수요기관코드낙찰하한율추정가격예정가격기초금액개찰일자개찰시각개찰결과구분명개찰순위투찰업체사업자등록번호투찰업체명투찰업체대표자명투찰금액투찰율투찰일자투찰시각낙찰여부최종낙찰금액최종낙찰율최종낙찰일자최종낙찰업체명최종낙찰업체대표자명최종낙찰업체담당자명최종낙찰업체사업자등록번호최종낙찰업체주소최종낙찰업체연락전화번호데이터기준일자제공기관코드제공기관명# duplicates
132019041625<NA>2019년 공급관리소용 보안시스템 구매물품총액계약제한경쟁<NA>한국가스공사<NA>한국가스공사<NA><NA><NA><NA><NA>2019-05-2417:24개찰완료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020-03-31B551210한국가스공사5
152019050307<NA>`19년 가스누출경보기 구매물품총액계약일반경쟁<NA>한국가스공사<NA>한국가스공사<NA><NA><NA><NA><NA>2019-05-1311:07개찰완료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020-03-31B551210한국가스공사4
12019021418<NA>발전용 요금제도 개선 연구용역용역총액계약제한경쟁<NA>한국가스공사<NA>한국가스공사<NA><NA><NA><NA><NA>2019-03-0416:05개찰완료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020-03-31B551210한국가스공사3
52019032510<NA>2019년 매설배관 충격 및 누출감지시스템 구매물품총액계약제한경쟁<NA>한국가스공사<NA>한국가스공사<NA><NA><NA><NA><NA>2019-04-0510:15개찰완료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020-03-31B551210한국가스공사3
92019040316<NA>2019년 생산기지 건축물 내진성능평가 용역용역총액계약제한경쟁<NA>한국가스공사<NA>한국가스공사<NA><NA><NA><NA><NA>2019-04-1111:27개찰완료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020-03-31B551210한국가스공사3
182019050926<NA>중장기감사전략 재정립 및 감사체계 고도화 용역용역총액계약수의계약<NA>한국가스공사<NA>한국가스공사<NA><NA><NA><NA><NA>2019-05-1015:02개찰완료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020-03-31B551210한국가스공사3
272019060510<NA>2019년 KOGAS 홍보영상 콘텐츠 제작용역용역총액계약제한경쟁<NA>한국가스공사<NA>한국가스공사<NA><NA><NA><NA><NA>2019-06-2710:01개찰완료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020-03-31B551210한국가스공사3
352019081913<NA>상임감사 및 감사인 역량진단과 전문성 향상 방안 용역용역총액계약수의계약<NA>한국가스공사<NA>한국가스공사<NA><NA><NA><NA><NA>2019-08-2109:39개찰완료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020-03-31B551210한국가스공사3
452019110708<NA>북미LNG사업 진출모델 도출 및 후보사업 평가용역총액계약일반경쟁<NA>한국가스공사<NA>한국가스공사<NA><NA><NA><NA><NA>2019-12-0513:30개찰완료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020-03-31B551210한국가스공사3
02019013108<NA>인천기지 초저온 LNG 밸브 제어용 Pneumatic Actuator(TK-204/205/206) 구매물품총액계약제한경쟁<NA>한국가스공사<NA>한국가스공사<NA><NA><NA><NA><NA>2019-03-1309:42개찰완료<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020-03-31B551210한국가스공사2