Overview

Dataset statistics

Number of variables14
Number of observations35
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.2 KiB
Average record size in memory122.8 B

Variable types

Categorical5
Numeric7
Text2

Dataset

Description인천광역시 동구에서 진행된 협상에 의한 계약 현황 데이터로, 관서명, 부서명, 사업명, 평가일, 업체순서, 평가대상업체, 위원점수, 최고최저합계, 평균, 정량적평가분약, 소계, 가격평가, 합계, 순위의 항목 제공하고 있습니다.
Author인천광역시 동구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15120255&srcSe=7661IVAWM27C61E190

Alerts

관서명 has constant value ""Constant
평가일 is highly overall correlated with 평균 and 2 other fieldsHigh correlation
사업명 is highly overall correlated with 평균 and 2 other fieldsHigh correlation
업체순서 is highly overall correlated with 평균High correlation
최고최저제외합계 is highly overall correlated with 평균 and 2 other fieldsHigh correlation
평균 is highly overall correlated with 업체순서 and 5 other fieldsHigh correlation
소계 is highly overall correlated with 최고최저제외합계 and 3 other fieldsHigh correlation
합계 is highly overall correlated with 최고최저제외합계 and 3 other fieldsHigh correlation
부서명 is highly overall correlated with 사업명 and 1 other fieldsHigh correlation
순위 is highly overall correlated with 소계 and 1 other fieldsHigh correlation
최고최저제외합계 has 2 (5.7%) zerosZeros
평균 has 2 (5.7%) zerosZeros
소계 has 2 (5.7%) zerosZeros
합계 has 2 (5.7%) zerosZeros

Reproduction

Analysis started2024-01-28 11:53:50.016046
Analysis finished2024-01-28 11:53:54.726476
Duration4.71 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관서명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
인천광역시 동구
35 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row인천광역시 동구
2nd row인천광역시 동구
3rd row인천광역시 동구
4th row인천광역시 동구
5th row인천광역시 동구

Common Values

ValueCountFrequency (%)
인천광역시 동구 35
100.0%

Length

2024-01-28T20:53:54.780816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T20:53:54.856755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천광역시 35
50.0%
동구 35
50.0%

부서명
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)25.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
도시정비과
8 
도시전략실
7 
문화홍보체육실
4 
기획감사실
4 
홍보문화실
4 
Other values (4)
8 

Length

Max length7
Median length5
Mean length5.0571429
Min length3

Unique

Unique1 ?
Unique (%)2.9%

Sample

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

Common Values

ValueCountFrequency (%)
도시정비과 8
22.9%
도시전략실 7
20.0%
문화홍보체육실 4
11.4%
기획감사실 4
11.4%
홍보문화실 4
11.4%
총무과 3
 
8.6%
민원지적과 2
 
5.7%
주민자치과 2
 
5.7%
관광체육과 1
 
2.9%

Length

2024-01-28T20:53:54.947725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T20:53:55.059170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
도시정비과 8
22.9%
도시전략실 7
20.0%
문화홍보체육실 4
11.4%
기획감사실 4
11.4%
홍보문화실 4
11.4%
총무과 3
 
8.6%
민원지적과 2
 
5.7%
주민자치과 2
 
5.7%
관광체육과 1
 
2.9%

사업명
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Memory size412.0 B
오손도손 송미로 사람들 더불어 마을사업 정비계획 수립 용역
7 
송림골 근대로 발자취 탐방루트 상징조형물 제작·설치
5 
제34회 화도진축제 행사 대행
4 
동구문화체육센터 통합운영관리시스템 구축용역
3 
2023년 오피니언 리더 역량강화 워크숍
3 
Other values (9)
13 

Length

Max length32
Median length27
Mean length24.4
Min length16

Unique

Unique5 ?
Unique (%)14.3%

Sample

1st row오손도손 송미로 사람들 더불어 마을사업 정비계획 수립 용역
2nd row오손도손 송미로 사람들 더불어 마을사업 정비계획 수립 용역
3rd row오손도손 송미로 사람들 더불어 마을사업 정비계획 수립 용역
4th row오손도손 송미로 사람들 더불어 마을사업 정비계획 수립 용역
5th row오손도손 송미로 사람들 더불어 마을사업 정비계획 수립 용역

Common Values

ValueCountFrequency (%)
오손도손 송미로 사람들 더불어 마을사업 정비계획 수립 용역 7
20.0%
송림골 근대로 발자취 탐방루트 상징조형물 제작·설치 5
14.3%
제34회 화도진축제 행사 대행 4
11.4%
동구문화체육센터 통합운영관리시스템 구축용역 3
8.6%
2023년 오피니언 리더 역량강화 워크숍 3
8.6%
동구 지적재조사기반 증강현실(AR)플랫폼 구축 사업 2
 
5.7%
2022년 오피니언 리더 강화 워크숍 2
 
5.7%
인천광역시 동구 홈페이지 전면 개편 사업 2
 
5.7%
인천광역시 동구 통합성과관리시스템 구축 2
 
5.7%
송림골 근대로 발자취 탐방루트 개발 용역 1
 
2.9%
Other values (4) 4
11.4%

Length

2024-01-28T20:53:55.201469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
용역 9
 
4.8%
수립 8
 
4.3%
오손도손 7
 
3.7%
정비계획 7
 
3.7%
동구 7
 
3.7%
송미로 7
 
3.7%
마을사업 7
 
3.7%
사람들 7
 
3.7%
더불어 7
 
3.7%
송림골 6
 
3.2%
Other values (39) 116
61.7%

평가일
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)37.1%
Missing0
Missing (%)0.0%
Memory size412.0 B
2021-02-17
7 
2022-07-26
5 
2023-03-03
4 
2021-06-09
3 
2023-04-25
3 
Other values (8)
13 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique4 ?
Unique (%)11.4%

Sample

1st row2021-02-17
2nd row2021-02-17
3rd row2021-02-17
4th row2021-02-17
5th row2021-02-17

Common Values

ValueCountFrequency (%)
2021-02-17 7
20.0%
2022-07-26 5
14.3%
2023-03-03 4
11.4%
2021-06-09 3
8.6%
2023-04-25 3
8.6%
2023-04-28 3
8.6%
2022-08-17 2
 
5.7%
2022-09-05 2
 
5.7%
2023-01-10 2
 
5.7%
2022-02-25 1
 
2.9%
Other values (3) 3
8.6%

Length

2024-01-28T20:53:55.317569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2021-02-17 7
20.0%
2022-07-26 5
14.3%
2023-03-03 4
11.4%
2021-06-09 3
8.6%
2023-04-25 3
8.6%
2023-04-28 3
8.6%
2022-08-17 2
 
5.7%
2022-09-05 2
 
5.7%
2023-01-10 2
 
5.7%
2022-02-25 1
 
2.9%
Other values (3) 3
8.6%

업체순서
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3428571
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-01-28T20:53:55.395206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile5.3
Maximum7
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.5893553
Coefficient of variation (CV)0.67838338
Kurtosis1.2158015
Mean2.3428571
Median Absolute Deviation (MAD)1
Skewness1.3072743
Sum82
Variance2.5260504
MonotonicityNot monotonic
2024-01-28T20:53:55.481524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 14
40.0%
2 9
25.7%
3 5
 
14.3%
4 3
 
8.6%
5 2
 
5.7%
6 1
 
2.9%
7 1
 
2.9%
ValueCountFrequency (%)
1 14
40.0%
2 9
25.7%
3 5
 
14.3%
4 3
 
8.6%
5 2
 
5.7%
6 1
 
2.9%
7 1
 
2.9%
ValueCountFrequency (%)
7 1
 
2.9%
6 1
 
2.9%
5 2
 
5.7%
4 3
 
8.6%
3 5
 
14.3%
2 9
25.7%
1 14
40.0%

평가대상업체
Text

Distinct29
Distinct (%)82.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
2024-01-28T20:53:55.664635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length14
Mean length9.5428571
Min length2

Characters and Unicode

Total characters334
Distinct characters109
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

Unique23 ?
Unique (%)65.7%

Sample

1st row이락
2nd row(주)아이오아이
3rd row나루
4th row(주)빛정원
5th row(주)지일
ValueCountFrequency (%)
주)온커뮤니케이션 2
 
5.1%
주)고려아카데미컨설팅 2
 
5.1%
주)빛정원 2
 
5.1%
나루 2
 
5.1%
주)지일 2
 
5.1%
주)아이오아이 2
 
5.1%
obs 1
 
2.6%
주)ocs도시건축사사무소/인하대학교 1
 
2.6%
산학협력단/송정회계법인 1
 
2.6%
주)에스포컴퍼니 1
 
2.6%
Other values (23) 23
59.0%
2024-01-28T20:53:55.973643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 32
 
9.6%
( 31
 
9.3%
) 31
 
9.3%
이 15
 
4.5%
스 12
 
3.6%
아 9
 
2.7%
인 6
 
1.8%
5
 
1.5%
컨 5
 
1.5%
원 5
 
1.5%
Other values (99) 183
54.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 252
75.4%
Open Punctuation 31
 
9.3%
Close Punctuation 31
 
9.3%
Uppercase Letter 11
 
3.3%
Space Separator 5
 
1.5%
Other Punctuation 4
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 32
 
12.7%
이 15
 
6.0%
스 12
 
4.8%
아 9
 
3.6%
인 6
 
2.4%
컨 5
 
2.0%
원 5
 
2.0%
정 5
 
2.0%
팅 5
 
2.0%
설 5
 
2.0%
Other values (86) 153
60.7%
Uppercase Letter
ValueCountFrequency (%)
S 3
27.3%
C 2
18.2%
O 2
18.2%
B 1
 
9.1%
T 1
 
9.1%
V 1
 
9.1%
I 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
/ 2
50.0%
, 1
25.0%
& 1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Close Punctuation
ValueCountFrequency (%)
) 31
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 252
75.4%
Common 71
 
21.3%
Latin 11
 
3.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 32
 
12.7%
이 15
 
6.0%
스 12
 
4.8%
아 9
 
3.6%
인 6
 
2.4%
컨 5
 
2.0%
원 5
 
2.0%
정 5
 
2.0%
팅 5
 
2.0%
설 5
 
2.0%
Other values (86) 153
60.7%
Latin
ValueCountFrequency (%)
S 3
27.3%
C 2
18.2%
O 2
18.2%
B 1
 
9.1%
T 1
 
9.1%
V 1
 
9.1%
I 1
 
9.1%
Common
ValueCountFrequency (%)
( 31
43.7%
) 31
43.7%
5
 
7.0%
/ 2
 
2.8%
, 1
 
1.4%
& 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 252
75.4%
ASCII 82
 
24.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 32
 
12.7%
이 15
 
6.0%
스 12
 
4.8%
아 9
 
3.6%
인 6
 
2.4%
컨 5
 
2.0%
원 5
 
2.0%
정 5
 
2.0%
팅 5
 
2.0%
설 5
 
2.0%
Other values (86) 153
60.7%
ASCII
ValueCountFrequency (%)
( 31
37.8%
) 31
37.8%
5
 
6.1%
S 3
 
3.7%
C 2
 
2.4%
O 2
 
2.4%
/ 2
 
2.4%
B 1
 
1.2%
T 1
 
1.2%
, 1
 
1.2%
Other values (3) 3
 
3.7%

위원점수
Text

Distinct31
Distinct (%)88.6%
Missing0
Missing (%)0.0%
Memory size412.0 B
2024-01-28T20:53:56.138699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length21
Mean length22.971429
Min length21

Characters and Unicode

Total characters804
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)77.1%

Sample

1st row47/45/48/55/38/56/50/
2nd row51/52/49/48/55/42/38/
3rd row44/50/51/51/48/48/53/
4th row20/40/14/44/43/38/27/
5th row40/58/38/43/48/53/30/
ValueCountFrequency (%)
44/50/51/51/48/48/53 2
 
5.7%
51/52/49/48/55/42/38 2
 
5.7%
20/40/14/44/43/38/27 2
 
5.7%
40/58/38/43/48/53/30 2
 
5.7%
44/49/44/44/48/51/52 1
 
2.9%
54/53/54/55/52/51/55 1
 
2.9%
51/55/40/57/35/54/54 1
 
2.9%
67/66/64/63/67/66/62/64 1
 
2.9%
49/54/48/49/46/49/51 1
 
2.9%
48/42/50/42/40/40/32/34 1
 
2.9%
Other values (21) 21
60.0%
2024-01-28T20:53:56.414536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 252
31.3%
4 124
15.4%
5 120
14.9%
6 64
 
8.0%
0 50
 
6.2%
3 49
 
6.1%
8 37
 
4.6%
2 29
 
3.6%
1 26
 
3.2%
. 24
 
3.0%
Other values (4) 29
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 522
64.9%
Other Punctuation 276
34.3%
Other Letter 6
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 124
23.8%
5 120
23.0%
6 64
12.3%
0 50
9.6%
3 49
 
9.4%
8 37
 
7.1%
2 29
 
5.6%
1 26
 
5.0%
7 12
 
2.3%
9 11
 
2.1%
Other Punctuation
ValueCountFrequency (%)
/ 252
91.3%
. 24
 
8.7%
Other Letter
ValueCountFrequency (%)
불 3
50.0%
참 3
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 798
99.3%
Hangul 6
 
0.7%

Most frequent character per script

Common
ValueCountFrequency (%)
/ 252
31.6%
4 124
15.5%
5 120
15.0%
6 64
 
8.0%
0 50
 
6.3%
3 49
 
6.1%
8 37
 
4.6%
2 29
 
3.6%
1 26
 
3.3%
. 24
 
3.0%
Other values (2) 23
 
2.9%
Hangul
ValueCountFrequency (%)
불 3
50.0%
참 3
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 798
99.3%
Hangul 6
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 252
31.6%
4 124
15.5%
5 120
15.0%
6 64
 
8.0%
0 50
 
6.3%
3 49
 
6.1%
8 37
 
4.6%
2 29
 
3.6%
1 26
 
3.3%
. 24
 
3.0%
Other values (2) 23
 
2.9%
Hangul
ValueCountFrequency (%)
불 3
50.0%
참 3
50.0%

최고최저제외합계
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean237.19429
Minimum0
Maximum390
Zeros2
Zeros (%)5.7%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-01-28T20:53:56.544806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile117.6
Q1227.5
median243
Q3257
95-th percentile329.85
Maximum390
Range390
Interquartile range (IQR)29.5

Descriptive statistics

Standard deviation73.772687
Coefficient of variation (CV)0.31102219
Kurtosis5.3260554
Mean237.19429
Median Absolute Deviation (MAD)17
Skewness-1.6008405
Sum8301.8
Variance5442.4094
MonotonicityNot monotonic
2024-01-28T20:53:56.659508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
248.0 2
 
5.7%
168.0 2
 
5.7%
222.0 2
 
5.7%
0.0 2
 
5.7%
254.0 2
 
5.7%
242.0 2
 
5.7%
246.0 2
 
5.7%
245.0 1
 
2.9%
272.0 1
 
2.9%
226.0 1
 
2.9%
Other values (18) 18
51.4%
ValueCountFrequency (%)
0.0 2
5.7%
168.0 2
5.7%
195.0 1
2.9%
216.3 1
2.9%
222.0 2
5.7%
226.0 1
2.9%
229.0 1
2.9%
232.0 1
2.9%
234.0 1
2.9%
236.0 1
2.9%
ValueCountFrequency (%)
390.0 1
2.9%
364.5 1
2.9%
315.0 1
2.9%
307.0 1
2.9%
294.0 1
2.9%
286.0 1
2.9%
272.0 1
2.9%
268.0 1
2.9%
260.0 1
2.9%
254.0 2
5.7%

평균
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean68.243343
Minimum0
Maximum245
Zeros2
Zeros (%)5.7%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-01-28T20:53:56.784599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile23.52
Q144.8665
median49.6
Q360.685
95-th percentile236.7
Maximum245
Range245
Interquartile range (IQR)15.8185

Descriptive statistics

Standard deviation62.384129
Coefficient of variation (CV)0.91414233
Kurtosis4.119886
Mean68.243343
Median Absolute Deviation (MAD)9.2
Skewness2.2779397
Sum2388.517
Variance3891.7795
MonotonicityNot monotonic
2024-01-28T20:53:56.898541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
49.6 2
 
5.7%
33.6 2
 
5.7%
44.4 2
 
5.7%
0.0 2
 
5.7%
65.0 2
 
5.7%
50.8 2
 
5.7%
48.4 2
 
5.7%
245.0 1
 
2.9%
47.667 1
 
2.9%
41.0 1
 
2.9%
Other values (18) 18
51.4%
ValueCountFrequency (%)
0.0 2
5.7%
33.6 2
5.7%
37.667 1
2.9%
39.0 1
2.9%
41.0 1
2.9%
44.4 2
5.7%
45.333 1
2.9%
45.8 1
2.9%
46.4 1
2.9%
47.2 1
2.9%
ValueCountFrequency (%)
245.0 1
2.9%
243.0 1
2.9%
234.0 1
2.9%
216.3 1
2.9%
65.0 2
5.7%
63.0 1
2.9%
61.4 1
2.9%
60.75 1
2.9%
60.62 1
2.9%
59.38 1
2.9%

정량적평가분야
Real number (ℝ)

Distinct21
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.934
Minimum10
Maximum27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-01-28T20:53:56.993376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile10.6
Q115
median18
Q319
95-th percentile20
Maximum27
Range17
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.4818759
Coefficient of variation (CV)0.2056145
Kurtosis1.1093724
Mean16.934
Median Absolute Deviation (MAD)1.4
Skewness-0.072992235
Sum592.69
Variance12.12346
MonotonicityNot monotonic
2024-01-28T20:53:57.090695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
18.0 5
14.3%
20.0 3
 
8.6%
12.0 3
 
8.6%
17.0 2
 
5.7%
10.6 2
 
5.7%
17.6 2
 
5.7%
19.0 2
 
5.7%
15.0 2
 
5.7%
19.4 2
 
5.7%
17.74 1
 
2.9%
Other values (11) 11
31.4%
ValueCountFrequency (%)
10.0 1
 
2.9%
10.6 2
5.7%
12.0 3
8.6%
13.0 1
 
2.9%
14.0 1
 
2.9%
15.0 2
5.7%
15.8 1
 
2.9%
17.0 2
5.7%
17.5 1
 
2.9%
17.6 2
5.7%
ValueCountFrequency (%)
27.0 1
 
2.9%
20.0 3
8.6%
19.5 1
 
2.9%
19.4 2
 
5.7%
19.35 1
 
2.9%
19.0 2
 
5.7%
18.8 1
 
2.9%
18.5 1
 
2.9%
18.3 1
 
2.9%
18.0 5
14.3%

소계
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct29
Distinct (%)82.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62.954486
Minimum0
Maximum84.4
Zeros2
Zeros (%)5.7%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-01-28T20:53:57.202606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile30.94
Q160.4
median64.9
Q372.7
95-th percentile82.54
Maximum84.4
Range84.4
Interquartile range (IQR)12.3

Descriptive statistics

Standard deviation18.462779
Coefficient of variation (CV)0.29327185
Kurtosis6.5278905
Mean62.954486
Median Absolute Deviation (MAD)6.9
Skewness-2.3269796
Sum2203.407
Variance340.87419
MonotonicityNot monotonic
2024-01-28T20:53:57.555471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
66.6 2
 
5.7%
44.2 2
 
5.7%
62.4 2
 
5.7%
0.0 2
 
5.7%
60.4 2
 
5.7%
64.8 2
 
5.7%
66.74 1
 
2.9%
65.667 1
 
2.9%
57.667 1
 
2.9%
58.5 1
 
2.9%
Other values (19) 19
54.3%
ValueCountFrequency (%)
0.0 2
5.7%
44.2 2
5.7%
51.0 1
2.9%
57.2 1
2.9%
57.667 1
2.9%
58.5 1
2.9%
60.4 2
5.7%
62.4 2
5.7%
63.8 1
2.9%
64.2 1
2.9%
ValueCountFrequency (%)
84.4 1
2.9%
83.8 1
2.9%
82.0 1
2.9%
80.75 1
2.9%
78.22 1
2.9%
76.98 1
2.9%
76.55 1
2.9%
73.8 1
2.9%
73.0 1
2.9%
72.4 1
2.9%

입찰가격평가
Real number (ℝ)

Distinct19
Distinct (%)54.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.374514
Minimum9.0909
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-01-28T20:53:57.641914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9.0909
5-th percentile9.80707
Q110
median18.87
Q319.7365
95-th percentile20
Maximum20
Range10.9091
Interquartile range (IQR)9.7365

Descriptive statistics

Standard deviation4.2864678
Coefficient of variation (CV)0.26177679
Kurtosis-1.1678613
Mean16.374514
Median Absolute Deviation (MAD)1.13
Skewness-0.83994927
Sum573.108
Variance18.373806
MonotonicityNot monotonic
2024-01-28T20:53:57.733093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
20.0 8
22.9%
10.0 6
17.1%
19.14 2
 
5.7%
17.04 2
 
5.7%
17.33 2
 
5.7%
17.13 2
 
5.7%
9.8401 1
 
2.9%
19.66 1
 
2.9%
18.87 1
 
2.9%
19.505 1
 
2.9%
Other values (9) 9
25.7%
ValueCountFrequency (%)
9.0909 1
 
2.9%
9.73 1
 
2.9%
9.8401 1
 
2.9%
9.98 1
 
2.9%
10.0 6
17.1%
17.04 2
 
5.7%
17.13 2
 
5.7%
17.33 2
 
5.7%
18.311 1
 
2.9%
18.87 1
 
2.9%
ValueCountFrequency (%)
20.0 8
22.9%
19.813 1
 
2.9%
19.66 1
 
2.9%
19.526 1
 
2.9%
19.505 1
 
2.9%
19.39 1
 
2.9%
19.14 2
 
5.7%
19.13 1
 
2.9%
18.982 1
 
2.9%
18.87 1
 
2.9%

합계
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct30
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean78.263483
Minimum0
Maximum94.24
Zeros2
Zeros (%)5.7%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-01-28T20:53:57.835243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile42.868
Q177.53
median84.359
Q387.17
95-th percentile93.234
Maximum94.24
Range94.24
Interquartile range (IQR)9.64

Descriptive statistics

Standard deviation21.092842
Coefficient of variation (CV)0.26951064
Kurtosis10.110666
Mean78.263483
Median Absolute Deviation (MAD)5.859
Skewness-3.1339206
Sum2739.2219
Variance444.90797
MonotonicityNot monotonic
2024-01-28T20:53:57.932147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
85.74 2
 
5.7%
61.24 2
 
5.7%
79.73 2
 
5.7%
0.0 2
 
5.7%
77.53 2
 
5.7%
86.74 1
 
2.9%
84.2 1
 
2.9%
77.48 1
 
2.9%
78.5 1
 
2.9%
84.359 1
 
2.9%
Other values (20) 20
57.1%
ValueCountFrequency (%)
0.0 2
5.7%
61.24 2
5.7%
70.13 1
2.9%
73.8 1
2.9%
76.07 1
2.9%
77.48 1
2.9%
77.53 2
5.7%
78.5 1
2.9%
79.73 2
5.7%
80.8909 1
2.9%
ValueCountFrequency (%)
94.24 1
2.9%
93.78 1
2.9%
93.0 1
2.9%
92.4 1
2.9%
92.0 1
2.9%
90.8 1
2.9%
90.75 1
2.9%
88.22 1
2.9%
87.6 1
2.9%
86.74 1
2.9%

순위
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size412.0 B
1
15 
2
8 
3
5 
5
2 
0
2 
Other values (2)
3 

Length

Max length5
Median length1
Mean length1.1142857
Min length1

Unique

Unique1 ?
Unique (%)2.9%

Sample

1st row1
2nd row3
3rd row1
4th row5
5th row2

Common Values

ValueCountFrequency (%)
1 15
42.9%
2 8
22.9%
3 5
 
14.3%
5 2
 
5.7%
0 2
 
5.7%
4 2
 
5.7%
협상부적격 1
 
2.9%

Length

2024-01-28T20:53:58.049045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T20:53:58.149880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 15
42.9%
2 8
22.9%
3 5
 
14.3%
5 2
 
5.7%
0 2
 
5.7%
4 2
 
5.7%
협상부적격 1
 
2.9%

Interactions

2024-01-28T20:53:53.852101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:50.492563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:50.978507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:51.510983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:52.283415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:52.785317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:53.273227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:53.948420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:50.560419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:51.052860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:51.586816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:52.355289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:52.850294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:53.366066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:54.037973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:50.635851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:51.129783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:51.667295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:52.438125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:52.924623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:53.455411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:54.116096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:50.699498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:51.210254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:51.999259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:52.506936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:52.985793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:53.525101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:54.210866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:50.771994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:51.284713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:52.073240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:52.580855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:53.057537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:53.609601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:54.298848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:50.835013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:51.361443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:52.135494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:52.648147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:53.116157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:53.698914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:54.379091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:50.908884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:51.431090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:52.213132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:52.719471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:53.195011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:53:53.777954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T20:53:58.225768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부서명사업명평가일업체순서평가대상업체위원점수최고최저제외합계평균정량적평가분야소계입찰가격평가합계순위
부서명1.0001.0000.9780.0000.8310.9420.4980.1450.2810.4660.6270.0000.000
사업명1.0001.0001.0000.0000.9160.9730.7840.8480.7810.5330.6970.0000.000
평가일0.9781.0001.0000.0000.8850.9670.7010.8420.7240.5180.6630.0000.000
업체순서0.0000.0000.0001.0000.9761.0000.8500.6340.0000.7210.6610.7310.870
평가대상업체0.8310.9160.8850.9761.0001.0000.9931.0000.9840.9891.0000.9810.994
위원점수0.9420.9730.9671.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
최고최저제외합계0.4980.7840.7010.8500.9931.0001.0000.6660.6100.7430.4220.7640.864
평균0.1450.8480.8420.6341.0001.0000.6661.0000.1890.7400.4290.8720.662
정량적평가분야0.2810.7810.7240.0000.9841.0000.6100.1891.0000.5020.4100.5480.637
소계0.4660.5330.5180.7210.9891.0000.7430.7400.5021.0000.7540.8370.831
입찰가격평가0.6270.6970.6630.6611.0001.0000.4220.4290.4100.7541.0000.4520.540
합계0.0000.0000.0000.7310.9811.0000.7640.8720.5480.8370.4521.0000.909
순위0.0000.0000.0000.8700.9941.0000.8640.6620.6370.8310.5400.9091.000
2024-01-28T20:53:58.334763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순위평가일사업명부서명
순위1.0000.0000.0000.000
평가일0.0001.0000.9770.843
사업명0.0000.9771.0000.899
부서명0.0000.8430.8991.000
2024-01-28T20:53:58.416248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업체순서최고최저제외합계평균정량적평가분야소계입찰가격평가합계부서명사업명평가일순위
업체순서1.000-0.217-0.514-0.132-0.390-0.144-0.3430.0000.0000.0000.481
최고최저제외합계-0.2171.0000.5890.1580.704-0.1030.6890.2660.3420.3580.472
평균-0.5140.5891.0000.2490.884-0.1340.8320.0000.5370.5620.484
정량적평가분야-0.1320.1580.2491.0000.4060.1340.4180.1400.3370.3780.246
소계-0.3900.7040.8840.4061.000-0.2830.9160.2230.2270.2280.666
입찰가격평가-0.144-0.103-0.1340.134-0.2831.0000.0400.4110.3800.3710.376
합계-0.3430.6890.8320.4180.9160.0401.0000.0000.0000.0000.832
부서명0.0000.2660.0000.1400.2230.4110.0001.0000.8990.8430.000
사업명0.0000.3420.5370.3370.2270.3800.0000.8991.0000.9770.000
평가일0.0000.3580.5620.3780.2280.3710.0000.8430.9771.0000.000
순위0.4810.4720.4840.2460.6660.3760.8320.0000.0000.0001.000

Missing values

2024-01-28T20:53:54.488145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T20:53:54.666642image/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

관서명부서명사업명평가일업체순서평가대상업체위원점수최고최저제외합계평균정량적평가분야소계입찰가격평가합계순위
0인천광역시 동구도시정비과오손도손 송미로 사람들 더불어 마을사업 정비계획 수립 용역2021-02-171이락47/45/48/55/38/56/50/245.0245.017.7466.7420.086.741
1인천광역시 동구도시정비과오손도손 송미로 사람들 더불어 마을사업 정비계획 수립 용역2021-02-172(주)아이오아이51/52/49/48/55/42/38/242.048.412.060.417.1377.533
2인천광역시 동구도시정비과오손도손 송미로 사람들 더불어 마을사업 정비계획 수립 용역2021-02-173나루44/50/51/51/48/48/53/248.049.617.066.619.1485.741
3인천광역시 동구도시정비과오손도손 송미로 사람들 더불어 마을사업 정비계획 수립 용역2021-02-174(주)빛정원20/40/14/44/43/38/27/168.033.610.644.217.0461.245
4인천광역시 동구도시정비과오손도손 송미로 사람들 더불어 마을사업 정비계획 수립 용역2021-02-175(주)지일40/58/38/43/48/53/30/222.044.418.062.417.3379.732
5인천광역시 동구도시정비과오손도손 송미로 사람들 더불어 마을사업 정비계획 수립 용역2021-02-176인지어스 유한회사42/60/48/57/35/48/40/42/0.00.020.00.018.9820.00
6인천광역시 동구도시정비과오손도손 송미로 사람들 더불어 마을사업 정비계획 수립 용역2021-02-177(주)케이잡스25/51/42/42/40/42/46/35/0.00.018.00.018.3110.00
7인천광역시 동구문화홍보체육실동구문화체육센터 통합운영관리시스템 구축용역2021-06-091(주)리버스아이티57.5/62.5/67.5/61/60.5/61.5/242.560.6217.678.2210.088.222
8인천광역시 동구문화홍보체육실동구문화체육센터 통합운영관리시스템 구축용역2021-06-092(주)혁산정보시스템64.5/65/70/64.5/66/64.5/260.065.018.883.89.9893.781
9인천광역시 동구문화홍보체육실동구문화체육센터 통합운영관리시스템 구축용역2021-06-093(주)대양CIS55/59/66/52.5/60/63.5/237.559.3817.676.989.7386.713
관서명부서명사업명평가일업체순서평가대상업체위원점수최고최저제외합계평균정량적평가분야소계입찰가격평가합계순위
25인천광역시 동구홍보문화실제34회 화도진축제 행사 대행2023-03-031(주)에스포컴퍼니38/40/36/38/38/36/36/50/226.037.66720.057.66719.81377.484
26인천광역시 동구홍보문화실제34회 화도진축제 행사 대행2023-03-032(주)월드커뮤니케이션48/42/50/42/40/40/32/34/246.041.017.558.520.078.53
27인천광역시 동구홍보문화실제34회 화도진축제 행사 대행2023-03-033(주)온커뮤니케이션56/50/50/36/40/48/48/30/272.045.33319.564.83319.52684.3592
28인천광역시 동구홍보문화실제34회 화도진축제 행사 대행2023-03-034OBS 경인TV 주식회사48/40/46/54/50/40/52/50/286.047.66718.065.66719.50585.1721
29인천광역시 동구총무과2023년 오피니언 리더 역량강화 워크숍2023-04-251(주)엑스퍼트컨설팅49/54/48/49/46/49/51/246.049.215.064.220.084.22
30인천광역시 동구총무과2023년 오피니언 리더 역량강화 워크숍2023-04-252(주)맨액웍스컨설팅44/49/44/44/48/51/52/236.047.210.057.218.8776.073
31인천광역시 동구총무과2023년 오피니언 리더 역량강화 워크숍2023-04-253(주)고려아카데미컨설팅51/55/40/57/35/54/54/254.050.814.064.819.6684.461
32인천광역시 동구관광체육과2023년박물관기획전시실감콘텐츠제작·설치2023-04-281(주)피플리54/53/54/55/52/51/55/268.053.619.473.020.093.01
33인천광역시 동구기획감사실인천광역시 동구 통합성과관리시스템 구축2023-04-281디원비씨에스(주)44/52/43/43/54/45/45/229.045.818.063.810.073.8협상부적격
34인천광역시 동구기획감사실인천광역시 동구 통합성과관리시스템 구축2023-04-282(주)넥스가이드,(주)한국미래정책연구원58/60/63/64/60/63/61/307.061.419.3580.7510.090.751