Overview

Dataset statistics

Number of variables8
Number of observations75
Missing cells5
Missing cells (%)0.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.0 KiB
Average record size in memory68.8 B

Variable types

Numeric2
Categorical3
Text1
DateTime2

Dataset

Description서울시설공단에서 관리(감독) 중인 서울시 기계/전기공사에 대해 년도, 공사유형, 공사명, 총공사비, 착공일, 준공일, 발주처 정보를 제공합니다.
Author서울시설공단
URLhttps://www.data.go.kr/data/15069120/fileData.do

Alerts

연번 is highly overall correlated with 년도High correlation
년도 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
발주처 is highly overall correlated with 년도High correlation
연번 has 1 (1.3%) missing valuesMissing
공사명 has 1 (1.3%) missing valuesMissing
총공사비(백만원) has 1 (1.3%) missing valuesMissing
착공일 has 1 (1.3%) missing valuesMissing
준공일 has 1 (1.3%) missing valuesMissing

Reproduction

Analysis started2023-12-12 23:20:00.858146
Analysis finished2023-12-12 23:20:02.414672
Duration1.56 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct74
Distinct (%)100.0%
Missing1
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean37.5
Minimum1
Maximum74
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size807.0 B
2023-12-13T08:20:02.496932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.65
Q119.25
median37.5
Q355.75
95-th percentile70.35
Maximum74
Range73
Interquartile range (IQR)36.5

Descriptive statistics

Standard deviation21.505813
Coefficient of variation (CV)0.57348835
Kurtosis-1.2
Mean37.5
Median Absolute Deviation (MAD)18.5
Skewness0
Sum2775
Variance462.5
MonotonicityStrictly increasing
2023-12-13T08:20:02.671401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.3%
57 1
 
1.3%
55 1
 
1.3%
54 1
 
1.3%
53 1
 
1.3%
52 1
 
1.3%
51 1
 
1.3%
50 1
 
1.3%
49 1
 
1.3%
48 1
 
1.3%
Other values (64) 64
85.3%
ValueCountFrequency (%)
1 1
1.3%
2 1
1.3%
3 1
1.3%
4 1
1.3%
5 1
1.3%
6 1
1.3%
7 1
1.3%
8 1
1.3%
9 1
1.3%
10 1
1.3%
ValueCountFrequency (%)
74 1
1.3%
73 1
1.3%
72 1
1.3%
71 1
1.3%
70 1
1.3%
69 1
1.3%
68 1
1.3%
67 1
1.3%
66 1
1.3%
65 1
1.3%

년도
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size732.0 B
2015
45 
2014
29 
<NA>
 
1

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique1 ?
Unique (%)1.3%

Sample

1st row2014
2nd row2014
3rd row2014
4th row2014
5th row2014

Common Values

ValueCountFrequency (%)
2015 45
60.0%
2014 29
38.7%
<NA> 1
 
1.3%

Length

2023-12-13T08:20:02.824346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:20:02.924341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2015 45
60.0%
2014 29
38.7%
na 1
 
1.3%

공사유형
Categorical

Distinct6
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size732.0 B
조명설비
30 
기계설비
21 
전력간선/동력설비
12 
통신설비/CCTV설비
7 
조명설비
4 

Length

Max length13
Median length6
Mean length7.32
Min length4

Unique

Unique1 ?
Unique (%)1.3%

Sample

1st row 전력간선/동력설비
2nd row 통신설비/CCTV설비
3rd row 통신설비/CCTV설비
4th row 기계설비
5th row 조명설비

Common Values

ValueCountFrequency (%)
조명설비 30
40.0%
기계설비 21
28.0%
전력간선/동력설비 12
 
16.0%
통신설비/CCTV설비 7
 
9.3%
조명설비 4
 
5.3%
<NA> 1
 
1.3%

Length

2023-12-13T08:20:03.031546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:20:03.158455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
조명설비 34
45.3%
기계설비 21
28.0%
전력간선/동력설비 12
 
16.0%
통신설비/cctv설비 7
 
9.3%
na 1
 
1.3%

공사명
Text

MISSING 

Distinct67
Distinct (%)90.5%
Missing1
Missing (%)1.3%
Memory size732.0 B
2023-12-13T08:20:03.425641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length25
Mean length20.067568
Min length13

Characters and Unicode

Total characters1485
Distinct characters182
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)81.1%

Sample

1st row 도심권 인생이모작 지원센터 전기공사
2nd row 도심권 인생이모작 지원센터 통신공사
3rd row 어린이대공원 놀이동산 영상감시설비 구매설치
4th row 2014년 한강공원 야외수영장 설비보수공사
5th row 한강공원 옥수나들목 신설 전기공사
ValueCountFrequency (%)
가로등 20
 
7.3%
전기공사 16
 
5.9%
개량공사 12
 
4.4%
외 5
 
1.8%
한강공원 5
 
1.8%
2015년 5
 
1.8%
통신공사 4
 
1.5%
서울특별시 4
 
1.5%
공사 4
 
1.5%
조성 4
 
1.5%
Other values (130) 194
71.1%
2023-12-13T08:20:03.801073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
341
23.0%
공 90
 
6.1%
사 76
 
5.1%
로 47
 
3.2%
설 31
 
2.1%
기 30
 
2.0%
전 26
 
1.8%
시 24
 
1.6%
지 23
 
1.5%
가 23
 
1.5%
Other values (172) 774
52.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1077
72.5%
Space Separator 341
 
23.0%
Decimal Number 49
 
3.3%
Open Punctuation 7
 
0.5%
Close Punctuation 7
 
0.5%
Other Punctuation 3
 
0.2%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 90
 
8.4%
사 76
 
7.1%
로 47
 
4.4%
설 31
 
2.9%
기 30
 
2.8%
전 26
 
2.4%
시 24
 
2.2%
지 23
 
2.1%
가 23
 
2.1%
등 22
 
2.0%
Other values (160) 685
63.6%
Decimal Number
ValueCountFrequency (%)
1 16
32.7%
2 12
24.5%
0 9
18.4%
5 6
 
12.2%
4 4
 
8.2%
3 2
 
4.1%
Other Punctuation
ValueCountFrequency (%)
, 2
66.7%
· 1
33.3%
Space Separator
ValueCountFrequency (%)
341
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1077
72.5%
Common 408
 
27.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 90
 
8.4%
사 76
 
7.1%
로 47
 
4.4%
설 31
 
2.9%
기 30
 
2.8%
전 26
 
2.4%
시 24
 
2.2%
지 23
 
2.1%
가 23
 
2.1%
등 22
 
2.0%
Other values (160) 685
63.6%
Common
ValueCountFrequency (%)
341
83.6%
1 16
 
3.9%
2 12
 
2.9%
0 9
 
2.2%
( 7
 
1.7%
) 7
 
1.7%
5 6
 
1.5%
4 4
 
1.0%
3 2
 
0.5%
, 2
 
0.5%
Other values (2) 2
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1077
72.5%
ASCII 407
 
27.4%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
341
83.8%
1 16
 
3.9%
2 12
 
2.9%
0 9
 
2.2%
( 7
 
1.7%
) 7
 
1.7%
5 6
 
1.5%
4 4
 
1.0%
3 2
 
0.5%
, 2
 
0.5%
Hangul
ValueCountFrequency (%)
공 90
 
8.4%
사 76
 
7.1%
로 47
 
4.4%
설 31
 
2.9%
기 30
 
2.8%
전 26
 
2.4%
시 24
 
2.2%
지 23
 
2.1%
가 23
 
2.1%
등 22
 
2.0%
Other values (160) 685
63.6%
None
ValueCountFrequency (%)
· 1
100.0%

총공사비(백만원)
Real number (ℝ)

MISSING 

Distinct69
Distinct (%)93.2%
Missing1
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean398.56757
Minimum8
Maximum3691
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size807.0 B
2023-12-13T08:20:03.929136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile60.5
Q1119.25
median214
Q3328
95-th percentile1423.5
Maximum3691
Range3683
Interquartile range (IQR)208.75

Descriptive statistics

Standard deviation674.58182
Coefficient of variation (CV)1.6925156
Kurtosis14.716542
Mean398.56757
Median Absolute Deviation (MAD)101.5
Skewness3.798808
Sum29494
Variance455060.63
MonotonicityNot monotonic
2023-12-13T08:20:04.035665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
133 2
 
2.7%
111 2
 
2.7%
109 2
 
2.7%
328 2
 
2.7%
129 2
 
2.7%
138 1
 
1.3%
237 1
 
1.3%
394 1
 
1.3%
98 1
 
1.3%
415 1
 
1.3%
Other values (59) 59
78.7%
ValueCountFrequency (%)
8 1
1.3%
19 1
1.3%
45 1
1.3%
54 1
1.3%
64 1
1.3%
70 1
1.3%
80 1
1.3%
83 1
1.3%
98 1
1.3%
100 1
1.3%
ValueCountFrequency (%)
3691 1
1.3%
3518 1
1.3%
2555 1
1.3%
2340 1
1.3%
930 1
1.3%
855 1
1.3%
744 1
1.3%
696 1
1.3%
664 1
1.3%
640 1
1.3%

착공일
Date

MISSING 

Distinct54
Distinct (%)73.0%
Missing1
Missing (%)1.3%
Memory size732.0 B
Minimum2012-12-27 00:00:00
Maximum2016-01-04 00:00:00
2023-12-13T08:20:04.163857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:20:04.286538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

준공일
Date

MISSING 

Distinct56
Distinct (%)75.7%
Missing1
Missing (%)1.3%
Memory size732.0 B
Minimum2014-04-30 00:00:00
Maximum2017-01-03 00:00:00
2023-12-13T08:20:04.390190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:20:04.495285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

발주처
Categorical

HIGH CORRELATION 

Distinct32
Distinct (%)42.7%
Missing0
Missing (%)0.0%
Memory size732.0 B
도시기반시설본부
13 
송파구
5 
한강사업본부
5 
한강사업본부
5 
서울특별시 서북병원
 
4
Other values (27)
43 

Length

Max length12
Median length11
Mean length6.5066667
Min length3

Unique

Unique16 ?
Unique (%)21.3%

Sample

1st row 도시기반시설본부
2nd row 도시기반시설본부
3rd row 동부공원녹지사업소
4th row 한강사업본부
5th row 한강사업본부

Common Values

ValueCountFrequency (%)
도시기반시설본부 13
17.3%
송파구 5
 
6.7%
한강사업본부 5
 
6.7%
한강사업본부 5
 
6.7%
서울특별시 서북병원 4
 
5.3%
마포구 4
 
5.3%
용산구 4
 
5.3%
강남구 3
 
4.0%
동작구청 2
 
2.7%
서부도로사업소 2
 
2.7%
Other values (22) 28
37.3%

Length

2023-12-13T08:20:04.597151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
도시기반시설본부 15
19.0%
한강사업본부 10
12.7%
송파구 6
 
7.6%
서울특별시 4
 
5.1%
서북병원 4
 
5.1%
마포구 4
 
5.1%
용산구 4
 
5.1%
강남구 4
 
5.1%
구로구 3
 
3.8%
남부도로사업소 2
 
2.5%
Other values (16) 23
29.1%

Interactions

2023-12-13T08:20:01.713116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:20:01.506861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:20:01.837910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:20:01.605625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:20:04.663424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번년도공사유형공사명총공사비(백만원)착공일준공일발주처
연번1.0000.9990.7490.8340.6090.8940.9430.834
년도0.9991.0000.0660.0000.0460.7680.9880.800
공사유형0.7490.0661.0000.8830.3850.7850.4980.626
공사명0.8340.0000.8831.0000.0001.0000.9770.989
총공사비(백만원)0.6090.0460.3850.0001.0000.8350.8030.000
착공일0.8940.7680.7851.0000.8351.0000.9890.986
준공일0.9430.9880.4980.9770.8030.9891.0000.993
발주처0.8340.8000.6260.9890.0000.9860.9931.000
2023-12-13T08:20:04.750443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도공사유형발주처
년도1.0000.0740.545
공사유형0.0741.0000.270
발주처0.5450.2701.000
2023-12-13T08:20:04.827205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번총공사비(백만원)년도공사유형발주처
연번1.0000.4110.9160.3890.386
총공사비(백만원)0.4111.0000.0480.1490.000
년도0.9160.0481.0000.0740.545
공사유형0.3890.1490.0741.0000.270
발주처0.3860.0000.5450.2701.000

Missing values

2023-12-13T08:20:01.973450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:20:02.142325image/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.
2023-12-13T08:20:02.309125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연번년도공사유형공사명총공사비(백만원)착공일준공일발주처
012014전력간선/동력설비도심권 인생이모작 지원센터 전기공사1332014-01-152014-05-14도시기반시설본부
122014통신설비/CCTV설비도심권 인생이모작 지원센터 통신공사642014-01-152014-05-14도시기반시설본부
232014통신설비/CCTV설비어린이대공원 놀이동산 영상감시설비 구매설치1902014-02-252014-04-30동부공원녹지사업소
342014기계설비2014년 한강공원 야외수영장 설비보수공사6962014-03-122014-09-30한강사업본부
452014조명설비한강공원 옥수나들목 신설 전기공사832014-03-142015-09-30한강사업본부
562014조명설비금호나들목 외 5개소 조명등 교체공사2122014-03-172014-06-14한강사업본부
672014기계설비망원2 빗물 펌프장 개량공사82014-03-172014-06-14마포구
782014전력간선/동력설비선정릉 빗물저류조설치 전기공사3282014-04-072014-12-31강남구
892014조명설비신정이펜하우스~남부순환로 가로등 개량공사1182014-04-112014-08-26양천구
9102014기계설비안양천 물놀이장 설치공사1442014-04-142014-07-12구로구
연번년도공사유형공사명총공사비(백만원)착공일준공일발주처
65662015조명설비성암로 가로등 개량공사2592015-06-022015-12-21마포구
66672015조명설비토정로 가로등 개량공사3702015-06-022015-12-21마포구
67682015조명설비다산로 가로등 개량공사5172015-06-242015-12-17중구청
68692015기계설비송정 사근 빗물펌프장 증설기계공사25552012-12-272015-01-30도시기반시설본부
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