Overview

Dataset statistics

Number of variables6
Number of observations103
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.0 KiB
Average record size in memory49.3 B

Variable types

Categorical4
Text2

Dataset

Description서울주택도시공사의 공사영역 발주계획입니다 발주년도,발주월,공종,계약방법,공사명,발주도급금액(단위:천원), 부서명 으로 구분 됩니다 * 발주계획은 언제든 변경 될 수 있습니다
URLhttps://www.data.go.kr/data/15065997/fileData.do

Alerts

계약방법 is highly overall correlated with 부서명High correlation
부서명 is highly overall correlated with 계약방법High correlation

Reproduction

Analysis started2023-12-12 20:03:47.274023
Analysis finished2023-12-12 20:03:48.302652
Duration1.03 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

발주월
Categorical

Distinct9
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size956.0 B
2023-03
22 
2023-04
20 
2023-07
20 
2023-08
11 
2023-06
9 
Other values (4)
21 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-02
2nd row2023-03
3rd row2023-03
4th row2023-02
5th row2023-01

Common Values

ValueCountFrequency (%)
2023-03 22
21.4%
2023-04 20
19.4%
2023-07 20
19.4%
2023-08 11
10.7%
2023-06 9
8.7%
2023-05 7
 
6.8%
2023-02 5
 
4.9%
2023-01 5
 
4.9%
2023-09 4
 
3.9%

Length

2023-12-13T05:03:48.387543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:03:48.523668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-03 22
21.4%
2023-04 20
19.4%
2023-07 20
19.4%
2023-08 11
10.7%
2023-06 9
8.7%
2023-05 7
 
6.8%
2023-02 5
 
4.9%
2023-01 5
 
4.9%
2023-09 4
 
3.9%

공종
Categorical

Distinct12
Distinct (%)11.7%
Missing0
Missing (%)0.0%
Memory size956.0 B
공사
63 
건축
16 
공사
 
5
전기
 
5
정보통신
 
5
Other values (7)
9 

Length

Max length4
Median length2
Mean length2.184466
Min length2

Unique

Unique5 ?
Unique (%)4.9%

Sample

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

Common Values

ValueCountFrequency (%)
공사 63
61.2%
건축 16
 
15.5%
공사 5
 
4.9%
전기 5
 
4.9%
정보통신 5
 
4.9%
조경 2
 
1.9%
소방 2
 
1.9%
기계 1
 
1.0%
통신 1
 
1.0%
토목 1
 
1.0%
Other values (2) 2
 
1.9%

Length

2023-12-13T05:03:48.671269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
공사 68
66.0%
건축 16
 
15.5%
전기 5
 
4.9%
정보통신 5
 
4.9%
조경 2
 
1.9%
소방 2
 
1.9%
기계 1
 
1.0%
통신 1
 
1.0%
토목 1
 
1.0%
전문공사 1
 
1.0%

계약방법
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size956.0 B
경쟁계약
76 
수의계약
26 
경쟁계약
 
1

Length

Max length5
Median length4
Mean length4.0097087
Min length4

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
경쟁계약 76
73.8%
수의계약 26
 
25.2%
경쟁계약 1
 
1.0%

Length

2023-12-13T05:03:48.809007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:03:48.904813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경쟁계약 77
74.8%
수의계약 26
 
25.2%

공사명
Text

Distinct91
Distinct (%)88.3%
Missing0
Missing (%)0.0%
Memory size956.0 B
2023-12-13T05:03:49.152332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length26
Mean length21.048544
Min length9

Characters and Unicode

Total characters2168
Distinct characters222
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique79 ?
Unique (%)76.7%

Sample

1st row마곡도시개발사업지구 10-2단지 아파트 건설공사
2nd row고덕강일 공공주택지구 3단지 아파트 건설공사
3rd row안암 어울림센터 건설공사
4th row자양동 10-34,46 주택건설사업 철거공사
5th row강일육교 보수보강공사
ValueCountFrequency (%)
임대아파트 24
 
5.4%
2023년 18
 
4.0%
교체공사 17
 
3.8%
공사 16
 
3.6%
및 13
 
2.9%
아파트 12
 
2.7%
3단지 10
 
2.2%
건설공사 9
 
2.0%
공공주택지구 8
 
1.8%
고덕강일 8
 
1.8%
Other values (172) 312
69.8%
2023-12-13T05:03:49.583882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
352
 
16.2%
공 121
 
5.6%
사 116
 
5.4%
지 64
 
3.0%
2 45
 
2.1%
트 41
 
1.9%
파 37
 
1.7%
대 36
 
1.7%
아 36
 
1.7%
주 34
 
1.6%
Other values (212) 1286
59.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1632
75.3%
Space Separator 352
 
16.2%
Decimal Number 130
 
6.0%
Uppercase Letter 16
 
0.7%
Dash Punctuation 13
 
0.6%
Close Punctuation 10
 
0.5%
Open Punctuation 10
 
0.5%
Other Punctuation 5
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 121
 
7.4%
사 116
 
7.1%
지 64
 
3.9%
트 41
 
2.5%
파 37
 
2.3%
대 36
 
2.2%
아 36
 
2.2%
주 34
 
2.1%
교 32
 
2.0%
보 32
 
2.0%
Other values (197) 1083
66.4%
Decimal Number
ValueCountFrequency (%)
2 45
34.6%
0 30
23.1%
3 29
22.3%
1 14
 
10.8%
6 6
 
4.6%
4 5
 
3.8%
7 1
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
C 8
50.0%
V 4
25.0%
T 4
25.0%
Space Separator
ValueCountFrequency (%)
352
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1632
75.3%
Common 520
 
24.0%
Latin 16
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 121
 
7.4%
사 116
 
7.1%
지 64
 
3.9%
트 41
 
2.5%
파 37
 
2.3%
대 36
 
2.2%
아 36
 
2.2%
주 34
 
2.1%
교 32
 
2.0%
보 32
 
2.0%
Other values (197) 1083
66.4%
Common
ValueCountFrequency (%)
352
67.7%
2 45
 
8.7%
0 30
 
5.8%
3 29
 
5.6%
1 14
 
2.7%
- 13
 
2.5%
) 10
 
1.9%
( 10
 
1.9%
6 6
 
1.2%
, 5
 
1.0%
Other values (2) 6
 
1.2%
Latin
ValueCountFrequency (%)
C 8
50.0%
V 4
25.0%
T 4
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1632
75.3%
ASCII 536
 
24.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
352
65.7%
2 45
 
8.4%
0 30
 
5.6%
3 29
 
5.4%
1 14
 
2.6%
- 13
 
2.4%
) 10
 
1.9%
( 10
 
1.9%
C 8
 
1.5%
6 6
 
1.1%
Other values (5) 19
 
3.5%
Hangul
ValueCountFrequency (%)
공 121
 
7.4%
사 116
 
7.1%
지 64
 
3.9%
트 41
 
2.5%
파 37
 
2.3%
대 36
 
2.2%
아 36
 
2.2%
주 34
 
2.1%
교 32
 
2.0%
보 32
 
2.0%
Other values (197) 1083
66.4%

발주도급금액(천원)
Text

Distinct77
Distinct (%)74.8%
Missing0
Missing (%)0.0%
Memory size956.0 B
2023-12-13T05:03:49.878078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length7.2815534
Min length2

Characters and Unicode

Total characters750
Distinct characters13
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

Unique63 ?
Unique (%)61.2%

Sample

1st row167000000
2nd row304669000
3rd row1854130
4th row113376
5th row490000
ValueCountFrequency (%)
20000 7
 
6.8%
50000 7
 
6.8%
500000 3
 
2.9%
2000000 3
 
2.9%
490000 2
 
1.9%
미정 2
 
1.9%
240000 2
 
1.9%
280000 2
 
1.9%
100000 2
 
1.9%
1854130 2
 
1.9%
Other values (66) 71
68.9%
2023-12-13T05:03:50.329541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 366
48.8%
103
 
13.7%
2 49
 
6.5%
1 47
 
6.3%
5 38
 
5.1%
4 29
 
3.9%
7 28
 
3.7%
3 26
 
3.5%
6 24
 
3.2%
9 20
 
2.7%
Other values (3) 20
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 643
85.7%
Space Separator 103
 
13.7%
Other Letter 4
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 366
56.9%
2 49
 
7.6%
1 47
 
7.3%
5 38
 
5.9%
4 29
 
4.5%
7 28
 
4.4%
3 26
 
4.0%
6 24
 
3.7%
9 20
 
3.1%
8 16
 
2.5%
Other Letter
ValueCountFrequency (%)
미 2
50.0%
정 2
50.0%
Space Separator
ValueCountFrequency (%)
103
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 746
99.5%
Hangul 4
 
0.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 366
49.1%
103
 
13.8%
2 49
 
6.6%
1 47
 
6.3%
5 38
 
5.1%
4 29
 
3.9%
7 28
 
3.8%
3 26
 
3.5%
6 24
 
3.2%
9 20
 
2.7%
Hangul
ValueCountFrequency (%)
미 2
50.0%
정 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 746
99.5%
Hangul 4
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 366
49.1%
103
 
13.8%
2 49
 
6.6%
1 47
 
6.3%
5 38
 
5.1%
4 29
 
3.9%
7 28
 
3.8%
3 26
 
3.5%
6 24
 
3.2%
9 20
 
2.7%
Hangul
ValueCountFrequency (%)
미 2
50.0%
정 2
50.0%

부서명
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)22.3%
Missing0
Missing (%)0.0%
Memory size956.0 B
기전설계부
15 
시설관리부
13 
구로,금천주거안심종합센터
12 
시설계획부
9 
빈집사업부
6 
Other values (18)
48 

Length

Max length13
Median length5
Mean length6.6796117
Min length3

Unique

Unique7 ?
Unique (%)6.8%

Sample

1st row건축설계부
2nd row건축설계부
3rd row공공설계부
4th row공동체주택사업부
5th row기반시설부

Common Values

ValueCountFrequency (%)
기전설계부 15
14.6%
시설관리부 13
12.6%
구로,금천주거안심종합센터 12
11.7%
시설계획부 9
 
8.7%
빈집사업부 6
 
5.8%
강동주거안심종합센터 6
 
5.8%
기반시설부 5
 
4.9%
구로주거안심종합센터 5
 
4.9%
시설계획부 5
 
4.9%
건축설계부 4
 
3.9%
Other values (13) 23
22.3%

Length

2023-12-13T05:03:50.481984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
시설관리부 16
15.5%
기전설계부 15
14.6%
시설계획부 14
13.6%
구로,금천주거안심종합센터 12
11.7%
빈집사업부 6
 
5.8%
강동주거안심종합센터 6
 
5.8%
기반시설부 5
 
4.9%
구로주거안심종합센터 5
 
4.9%
건축설계부 4
 
3.9%
공공설계부 4
 
3.9%
Other values (11) 16
15.5%

Correlations

2023-12-13T05:03:50.590502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
발주월공종계약방법공사명발주도급금액(천원)부서명
발주월1.0000.6040.3360.8360.7000.791
공종0.6041.0000.4250.9630.8690.484
계약방법0.3360.4251.0001.0001.0000.867
공사명0.8360.9631.0001.0000.9970.997
발주도급금액(천원)0.7000.8691.0000.9971.0000.891
부서명0.7910.4840.8670.9970.8911.000
2023-12-13T05:03:50.704540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공종부서명발주월계약방법
공종1.0000.1660.3010.200
부서명0.1661.0000.4180.631
발주월0.3010.4181.0000.150
계약방법0.2000.6310.1501.000
2023-12-13T05:03:51.094393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
발주월공종계약방법부서명
발주월1.0000.3010.1500.418
공종0.3011.0000.2000.166
계약방법0.1500.2001.0000.631
부서명0.4180.1660.6311.000

Missing values

2023-12-13T05:03:48.127440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:03:48.251759image/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

발주월공종계약방법공사명발주도급금액(천원)부서명
02023-02공사경쟁계약마곡도시개발사업지구 10-2단지 아파트 건설공사167000000건축설계부
12023-03공사경쟁계약고덕강일 공공주택지구 3단지 아파트 건설공사304669000건축설계부
22023-03공사경쟁계약안암 어울림센터 건설공사1854130공공설계부
32023-02공사경쟁계약자양동 10-34,46 주택건설사업 철거공사113376공동체주택사업부
42023-01공사경쟁계약강일육교 보수보강공사490000기반시설부
52023-01공사경쟁계약동부간선 진출램프교 보수공사220000기반시설부
62023-03공사경쟁계약중랑 패션봉제 스마트앵커 전기공사2722256기전설계부
72023-03공사경쟁계약중랑 패션봉제 스마트앵커 정보통신공사912150기전설계부
82023-03공사경쟁계약중랑 패션봉제 스마트앵커 건설공사1280434기전설계부
92023-03공사경쟁계약고덕강일 공공주택지구 3단지 공동주택 전기공사30790000기전설계부
발주월공종계약방법공사명발주도급금액(천원)부서명
932023-07전문공사경쟁계약구 금천경찰서 이전부지 석면해체 및 건축물 철거공사1620080도시환경부
942023-09건축경쟁계약마포 출판인쇄 스마트앵커 건립사업11054400복합설계부
952023-09건축경쟁계약2023년 임대아파트 재도장공사7526000시설관리부
962023-07기계설비경쟁계약대치1상가 급수개선공사100000시설관리부
972023-07정보통신경쟁계약2023년 임대아파트 CCTV 교체공사370000시설관리부
982023-07정보통신경쟁계약2023년 임대아파트 CCTV 교체공사480000시설관리부
992023-07전기경쟁계약2023년 임대아파트 보안등 교체공사240000시설관리부
1002023-07정보통신경쟁계약2023년 소규모주택 CCTV 설치공사101860시설관리부
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