Overview

Dataset statistics

Number of variables7
Number of observations166
Missing cells2
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.5 KiB
Average record size in memory58.8 B

Variable types

Numeric2
Categorical2
Text2
DateTime1

Dataset

Description보령시에서 공사를 하도급 계약한 정보(관서명, 계약방법 ,계약명, 계약금액, 계약일, 계약상대자)에 관한 현황입니다.
Author충청남도 보령시
URLhttps://www.data.go.kr/data/15090095/fileData.do

Alerts

관서명 is highly imbalanced (93.3%)Imbalance
계약상대자 has 2 (1.2%) missing valuesMissing
번호 has unique valuesUnique
계약명 has unique valuesUnique
계약금액 has unique valuesUnique

Reproduction

Analysis started2024-03-15 00:55:07.391889
Analysis finished2024-03-15 00:55:09.561539
Duration2.17 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct166
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean83.5
Minimum1
Maximum166
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-03-15T09:55:09.770706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9.25
Q142.25
median83.5
Q3124.75
95-th percentile157.75
Maximum166
Range165
Interquartile range (IQR)82.5

Descriptive statistics

Standard deviation48.064193
Coefficient of variation (CV)0.57561908
Kurtosis-1.2
Mean83.5
Median Absolute Deviation (MAD)41.5
Skewness0
Sum13861
Variance2310.1667
MonotonicityStrictly increasing
2024-03-15T09:55:10.111364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.6%
106 1
 
0.6%
108 1
 
0.6%
109 1
 
0.6%
110 1
 
0.6%
111 1
 
0.6%
112 1
 
0.6%
113 1
 
0.6%
114 1
 
0.6%
115 1
 
0.6%
Other values (156) 156
94.0%
ValueCountFrequency (%)
1 1
0.6%
2 1
0.6%
3 1
0.6%
4 1
0.6%
5 1
0.6%
6 1
0.6%
7 1
0.6%
8 1
0.6%
9 1
0.6%
10 1
0.6%
ValueCountFrequency (%)
166 1
0.6%
165 1
0.6%
164 1
0.6%
163 1
0.6%
162 1
0.6%
161 1
0.6%
160 1
0.6%
159 1
0.6%
158 1
0.6%
157 1
0.6%

관서명
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
본청
164 
농업기술센터
 
1
보건소
 
1

Length

Max length6
Median length2
Mean length2.0301205
Min length2

Unique

Unique2 ?
Unique (%)1.2%

Sample

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

Common Values

ValueCountFrequency (%)
본청 164
98.8%
농업기술센터 1
 
0.6%
보건소 1
 
0.6%

Length

2024-03-15T09:55:10.528420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T09:55:10.893815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
본청 164
98.8%
농업기술센터 1
 
0.6%
보건소 1
 
0.6%

계약방법
Categorical

Distinct3
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
제한경쟁
115 
수의2인이상견적
39 
일반경쟁
12 

Length

Max length8
Median length4
Mean length4.939759
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제한경쟁 115
69.3%
수의2인이상견적 39
 
23.5%
일반경쟁 12
 
7.2%

Length

2024-03-15T09:55:11.282359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T09:55:11.490578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제한경쟁 115
69.3%
수의2인이상견적 39
 
23.5%
일반경쟁 12
 
7.2%

계약명
Text

UNIQUE 

Distinct166
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-03-15T09:55:12.345977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length29
Mean length20.39759
Min length9

Characters and Unicode

Total characters3386
Distinct characters279
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique166 ?
Unique (%)100.0%

Sample

1st row대천1지구 우수저류시설 설치사업
2nd row신흑동 이주단지 재해위험시설 정비공사
3rd row간치 자연재해위험개선지구 정비사업(1차,2차)
4th row신구소하천 정비공사
5th row시도17호(성연~죽림) 도로확포장공사
ValueCountFrequency (%)
조성공사 15
 
2.8%
농어촌도로 15
 
2.8%
개설공사 11
 
2.1%
도시계획도로 10
 
1.9%
확포장공사 9
 
1.7%
정비공사 7
 
1.3%
정비사업 6
 
1.1%
보령시 6
 
1.1%
보령 6
 
1.1%
및 6
 
1.1%
Other values (330) 439
82.8%
2024-03-15T09:55:13.520705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
364
 
10.8%
사 181
 
5.3%
공 152
 
4.5%
( 122
 
3.6%
) 122
 
3.6%
도 99
 
2.9%
장 64
 
1.9%
2 61
 
1.8%
업 61
 
1.8%
성 58
 
1.7%
Other values (269) 2102
62.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2573
76.0%
Space Separator 364
 
10.8%
Decimal Number 173
 
5.1%
Open Punctuation 122
 
3.6%
Close Punctuation 122
 
3.6%
Dash Punctuation 16
 
0.5%
Other Punctuation 9
 
0.3%
Math Symbol 5
 
0.1%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 181
 
7.0%
공 152
 
5.9%
도 99
 
3.8%
장 64
 
2.5%
업 61
 
2.4%
성 58
 
2.3%
시 57
 
2.2%
차 56
 
2.2%
로 56
 
2.2%
축 54
 
2.1%
Other values (249) 1735
67.4%
Decimal Number
ValueCountFrequency (%)
2 61
35.3%
1 34
19.7%
3 20
 
11.6%
0 19
 
11.0%
6 12
 
6.9%
4 8
 
4.6%
9 6
 
3.5%
8 6
 
3.5%
5 4
 
2.3%
7 3
 
1.7%
Other Punctuation
ValueCountFrequency (%)
, 8
88.9%
/ 1
 
11.1%
Math Symbol
ValueCountFrequency (%)
~ 4
80.0%
+ 1
 
20.0%
Uppercase Letter
ValueCountFrequency (%)
I 1
50.0%
C 1
50.0%
Space Separator
ValueCountFrequency (%)
364
100.0%
Open Punctuation
ValueCountFrequency (%)
( 122
100.0%
Close Punctuation
ValueCountFrequency (%)
) 122
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2573
76.0%
Common 811
 
24.0%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 181
 
7.0%
공 152
 
5.9%
도 99
 
3.8%
장 64
 
2.5%
업 61
 
2.4%
성 58
 
2.3%
시 57
 
2.2%
차 56
 
2.2%
로 56
 
2.2%
축 54
 
2.1%
Other values (249) 1735
67.4%
Common
ValueCountFrequency (%)
364
44.9%
( 122
 
15.0%
) 122
 
15.0%
2 61
 
7.5%
1 34
 
4.2%
3 20
 
2.5%
0 19
 
2.3%
- 16
 
2.0%
6 12
 
1.5%
4 8
 
1.0%
Other values (8) 33
 
4.1%
Latin
ValueCountFrequency (%)
I 1
50.0%
C 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2573
76.0%
ASCII 813
 
24.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
364
44.8%
( 122
 
15.0%
) 122
 
15.0%
2 61
 
7.5%
1 34
 
4.2%
3 20
 
2.5%
0 19
 
2.3%
- 16
 
2.0%
6 12
 
1.5%
4 8
 
1.0%
Other values (10) 35
 
4.3%
Hangul
ValueCountFrequency (%)
사 181
 
7.0%
공 152
 
5.9%
도 99
 
3.8%
장 64
 
2.5%
업 61
 
2.4%
성 58
 
2.3%
시 57
 
2.2%
차 56
 
2.2%
로 56
 
2.2%
축 54
 
2.1%
Other values (249) 1735
67.4%

계약금액
Real number (ℝ)

UNIQUE 

Distinct166
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2695667 × 109
Minimum34490000
Maximum1.3025797 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-03-15T09:55:13.948349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34490000
5-th percentile1.0586928 × 108
Q13.1361625 × 108
median5.98371 × 108
Q31.338789 × 109
95-th percentile5.3484956 × 109
Maximum1.3025797 × 1010
Range1.2991307 × 1010
Interquartile range (IQR)1.0251728 × 109

Descriptive statistics

Standard deviation2.022309 × 109
Coefficient of variation (CV)1.5929128
Kurtosis13.727465
Mean1.2695667 × 109
Median Absolute Deviation (MAD)3.903245 × 108
Skewness3.5214309
Sum2.1074807 × 1011
Variance4.0897339 × 1018
MonotonicityNot monotonic
2024-03-15T09:55:14.410632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13025797000 1
 
0.6%
1100421000 1
 
0.6%
1274125000 1
 
0.6%
112624000 1
 
0.6%
1813133000 1
 
0.6%
421442000 1
 
0.6%
99753000 1
 
0.6%
602560000 1
 
0.6%
2555067000 1
 
0.6%
280939000 1
 
0.6%
Other values (156) 156
94.0%
ValueCountFrequency (%)
34490000 1
0.6%
73964000 1
0.6%
81272000 1
0.6%
85200000 1
0.6%
87082530 1
0.6%
99753000 1
0.6%
102358000 1
0.6%
102424000 1
0.6%
103617700 1
0.6%
112624000 1
0.6%
ValueCountFrequency (%)
13025797000 1
0.6%
11240400000 1
0.6%
10053717000 1
0.6%
9179100000 1
0.6%
8063556000 1
0.6%
7784983400 1
0.6%
6012500000 1
0.6%
5573179000 1
0.6%
5376834740 1
0.6%
5263478000 1
0.6%

계약일
Date

Distinct154
Distinct (%)92.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Minimum2014-01-16 00:00:00
Maximum2023-09-12 00:00:00
2024-03-15T09:55:14.912220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:55:15.391366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

계약상대자
Text

MISSING 

Distinct125
Distinct (%)76.2%
Missing2
Missing (%)1.2%
Memory size1.4 KiB
2024-03-15T09:55:16.603071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length8.5731707
Min length4

Characters and Unicode

Total characters1406
Distinct characters120
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique96 ?
Unique (%)58.5%

Sample

1st row(주)라온토건
2nd row새한건설주식회사
3rd row네오서진건설 주식회사(neo)
4th row동광건설(주)
5th row(주)지안스건설
ValueCountFrequency (%)
주식회사 52
 
23.9%
케이티씨건설 6
 
2.8%
서림종합건설(주 4
 
1.8%
영화종합건설 3
 
1.4%
대운건설(주 3
 
1.4%
호정주식회사 3
 
1.4%
지수종합건설 3
 
1.4%
대하건설 2
 
0.9%
주)태광 2
 
0.9%
케이에이치건설(주 2
 
0.9%
Other values (118) 138
63.3%
2024-03-15T09:55:18.376413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 152
 
10.8%
건 135
 
9.6%
설 125
 
8.9%
( 78
 
5.5%
) 78
 
5.5%
사 75
 
5.3%
회 75
 
5.3%
식 73
 
5.2%
합 55
 
3.9%
54
 
3.8%
Other values (110) 506
36.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1193
84.9%
Open Punctuation 78
 
5.5%
Close Punctuation 78
 
5.5%
Space Separator 54
 
3.8%
Lowercase Letter 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 152
 
12.7%
건 135
 
11.3%
설 125
 
10.5%
사 75
 
6.3%
회 75
 
6.3%
식 73
 
6.1%
합 55
 
4.6%
종 54
 
4.5%
이 34
 
2.8%
대 22
 
1.8%
Other values (104) 393
32.9%
Lowercase Letter
ValueCountFrequency (%)
o 1
33.3%
e 1
33.3%
n 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 78
100.0%
Close Punctuation
ValueCountFrequency (%)
) 78
100.0%
Space Separator
ValueCountFrequency (%)
54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1193
84.9%
Common 210
 
14.9%
Latin 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 152
 
12.7%
건 135
 
11.3%
설 125
 
10.5%
사 75
 
6.3%
회 75
 
6.3%
식 73
 
6.1%
합 55
 
4.6%
종 54
 
4.5%
이 34
 
2.8%
대 22
 
1.8%
Other values (104) 393
32.9%
Common
ValueCountFrequency (%)
( 78
37.1%
) 78
37.1%
54
25.7%
Latin
ValueCountFrequency (%)
o 1
33.3%
e 1
33.3%
n 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1193
84.9%
ASCII 213
 
15.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 152
 
12.7%
건 135
 
11.3%
설 125
 
10.5%
사 75
 
6.3%
회 75
 
6.3%
식 73
 
6.1%
합 55
 
4.6%
종 54
 
4.5%
이 34
 
2.8%
대 22
 
1.8%
Other values (104) 393
32.9%
ASCII
ValueCountFrequency (%)
( 78
36.6%
) 78
36.6%
54
25.4%
o 1
 
0.5%
e 1
 
0.5%
n 1
 
0.5%

Interactions

2024-03-15T09:55:08.417517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:55:07.902755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:55:08.672726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:55:08.155080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T09:55:18.653559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호관서명계약방법계약금액
번호1.0000.0470.4220.347
관서명0.0471.0000.4410.000
계약방법0.4220.4411.0000.615
계약금액0.3470.0000.6151.000
2024-03-15T09:55:18.926207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관서명계약방법
관서명1.0000.169
계약방법0.1691.000
2024-03-15T09:55:19.172052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호계약금액관서명계약방법
번호1.0000.0810.0000.270
계약금액0.0811.0000.0000.451
관서명0.0000.0001.0000.169
계약방법0.2700.4510.1691.000

Missing values

2024-03-15T09:55:08.974032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T09:55:09.417204image/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

번호관서명계약방법계약명계약금액계약일계약상대자
01본청일반경쟁대천1지구 우수저류시설 설치사업130257970002014-01-16(주)라온토건
12본청제한경쟁신흑동 이주단지 재해위험시설 정비공사7064600002015-06-23새한건설주식회사
23본청제한경쟁간치 자연재해위험개선지구 정비사업(1차,2차)60125000002016-04-29네오서진건설 주식회사(neo)
34본청일반경쟁신구소하천 정비공사12843000002016-05-03동광건설(주)
45본청제한경쟁시도17호(성연~죽림) 도로확포장공사13077600002016-06-17(주)지안스건설
56농업기술센터일반경쟁미생물 배양시설 신축공사(건축)3200400002016-07-05(주)명성종합건설
67본청일반경쟁한내여중길~국도36호선 도시계획도로개설공사55731790002016-11-25명헌건설(주)
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