Overview

Dataset statistics

Number of variables7
Number of observations164
Missing cells2
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.4 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
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=327&beforeMenuCd=DOM_000000201001001000&publicdatapk=15090095

Alerts

관서명 is highly imbalanced (93.2%)Imbalance
계약상대자 has 2 (1.2%) missing valuesMissing
번호 has unique valuesUnique
계약명 has unique valuesUnique
계약금액 has unique valuesUnique

Reproduction

Analysis started2024-01-09 22:28:27.788818
Analysis finished2024-01-09 22:28:28.842940
Duration1.05 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct164
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean82.5
Minimum1
Maximum164
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-01-10T07:28:28.900293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9.15
Q141.75
median82.5
Q3123.25
95-th percentile155.85
Maximum164
Range163
Interquartile range (IQR)81.5

Descriptive statistics

Standard deviation47.48684
Coefficient of variation (CV)0.57559806
Kurtosis-1.2
Mean82.5
Median Absolute Deviation (MAD)41
Skewness0
Sum13530
Variance2255
MonotonicityStrictly increasing
2024-01-10T07:28:29.030620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.6%
105 1
 
0.6%
107 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%
Other values (154) 154
93.9%
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 (%)
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%
156 1
0.6%
155 1
0.6%

관서명
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
본청
162 
농업기술센터
 
1
보건소
 
1

Length

Max length6
Median length2
Mean length2.0304878
Min length2

Unique

Unique2 ?
Unique (%)1.2%

Sample

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

Common Values

ValueCountFrequency (%)
본청 162
98.8%
농업기술센터 1
 
0.6%
보건소 1
 
0.6%

Length

2024-01-10T07:28:29.186360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:28:29.285501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
본청 162
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
114 
수의2인이상견적
38 
일반경쟁
12 

Length

Max length8
Median length4
Mean length4.9268293
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제한경쟁 114
69.5%
수의2인이상견적 38
 
23.2%
일반경쟁 12
 
7.3%

Length

2024-01-10T07:28:29.410863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:28:29.521774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제한경쟁 114
69.5%
수의2인이상견적 38
 
23.2%
일반경쟁 12
 
7.3%

계약명
Text

UNIQUE 

Distinct164
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-01-10T07:28:29.755682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length29
Mean length20.432927
Min length9

Characters and Unicode

Total characters3351
Distinct characters278
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

Unique164 ?
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 (%)
농어촌도로 15
 
2.9%
조성공사 15
 
2.9%
개설공사 11
 
2.1%
도시계획도로 10
 
1.9%
확포장공사 9
 
1.7%
정비공사 7
 
1.3%
보령 6
 
1.1%
및 6
 
1.1%
정비사업 6
 
1.1%
보령시 6
 
1.1%
Other values (326) 434
82.7%
2024-01-10T07:28:30.127742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
361
 
10.8%
사 179
 
5.3%
공 149
 
4.4%
) 120
 
3.6%
( 120
 
3.6%
도 99
 
3.0%
장 64
 
1.9%
2 61
 
1.8%
업 59
 
1.8%
성 56
 
1.7%
Other values (268) 2083
62.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2545
75.9%
Space Separator 361
 
10.8%
Decimal Number 173
 
5.2%
Close Punctuation 120
 
3.6%
Open Punctuation 120
 
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 179
 
7.0%
공 149
 
5.9%
도 99
 
3.9%
장 64
 
2.5%
업 59
 
2.3%
성 56
 
2.2%
로 56
 
2.2%
시 56
 
2.2%
차 55
 
2.2%
축 54
 
2.1%
Other values (248) 1718
67.5%
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 (%)
361
100.0%
Close Punctuation
ValueCountFrequency (%)
) 120
100.0%
Open Punctuation
ValueCountFrequency (%)
( 120
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2545
75.9%
Common 804
 
24.0%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 179
 
7.0%
공 149
 
5.9%
도 99
 
3.9%
장 64
 
2.5%
업 59
 
2.3%
성 56
 
2.2%
로 56
 
2.2%
시 56
 
2.2%
차 55
 
2.2%
축 54
 
2.1%
Other values (248) 1718
67.5%
Common
ValueCountFrequency (%)
361
44.9%
) 120
 
14.9%
( 120
 
14.9%
2 61
 
7.6%
1 34
 
4.2%
3 20
 
2.5%
0 19
 
2.4%
- 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 2545
75.9%
ASCII 806
 
24.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
361
44.8%
) 120
 
14.9%
( 120
 
14.9%
2 61
 
7.6%
1 34
 
4.2%
3 20
 
2.5%
0 19
 
2.4%
- 16
 
2.0%
6 12
 
1.5%
4 8
 
1.0%
Other values (10) 35
 
4.3%
Hangul
ValueCountFrequency (%)
사 179
 
7.0%
공 149
 
5.9%
도 99
 
3.9%
장 64
 
2.5%
업 59
 
2.3%
성 56
 
2.2%
로 56
 
2.2%
시 56
 
2.2%
차 55
 
2.2%
축 54
 
2.1%
Other values (248) 1718
67.5%

계약금액
Real number (ℝ)

UNIQUE 

Distinct164
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.272301 × 109
Minimum34490000
Maximum1.3025797 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-01-10T07:28:30.250421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34490000
5-th percentile1.0496864 × 108
Q13.1030825 × 108
median5.93717 × 108
Q31.3297065 × 109
95-th percentile5.3598312 × 109
Maximum1.3025797 × 1010
Range1.2991307 × 1010
Interquartile range (IQR)1.0193982 × 109

Descriptive statistics

Standard deviation2.0336844 × 109
Coefficient of variation (CV)1.5984303
Kurtosis13.543856
Mean1.272301 × 109
Median Absolute Deviation (MAD)3.86861 × 108
Skewness3.5016961
Sum2.0865736 × 1011
Variance4.1358724 × 1018
MonotonicityNot monotonic
2024-01-10T07:28:30.379431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13025797000 1
 
0.6%
403772000 1
 
0.6%
463412000 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%
Other values (154) 154
93.9%
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

Distinct152
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Minimum2014-01-16 00:00:00
Maximum2023-08-09 00:00:00
2024-01-10T07:28:30.523490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:28:30.656343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

계약상대자
Text

MISSING 

Distinct123
Distinct (%)75.9%
Missing2
Missing (%)1.2%
Memory size1.4 KiB
2024-01-10T07:28:30.845649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length8.5864198
Min length4

Characters and Unicode

Total characters1391
Distinct characters118
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

Unique94 ?
Unique (%)58.0%

Sample

1st row(주)라온토건
2nd row새한건설주식회사
3rd row네오서진건설 주식회사(neo)
4th row동광건설(주)
5th row(주)지안스건설
ValueCountFrequency (%)
주식회사 52
 
24.1%
케이티씨건설 6
 
2.8%
서림종합건설(주 4
 
1.9%
지수종합건설 3
 
1.4%
호정주식회사 3
 
1.4%
대운건설(주 3
 
1.4%
영화종합건설 3
 
1.4%
대일종합건설 2
 
0.9%
지엠건설 2
 
0.9%
제이에이치종합건설(주 2
 
0.9%
Other values (116) 136
63.0%
2024-01-10T07:28:31.176076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 150
 
10.8%
건 134
 
9.6%
설 124
 
8.9%
) 77
 
5.5%
( 77
 
5.5%
사 74
 
5.3%
회 74
 
5.3%
식 72
 
5.2%
합 55
 
4.0%
54
 
3.9%
Other values (108) 500
35.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1180
84.8%
Close Punctuation 77
 
5.5%
Open Punctuation 77
 
5.5%
Space Separator 54
 
3.9%
Lowercase Letter 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 150
 
12.7%
건 134
 
11.4%
설 124
 
10.5%
사 74
 
6.3%
회 74
 
6.3%
식 72
 
6.1%
합 55
 
4.7%
종 54
 
4.6%
이 34
 
2.9%
대 22
 
1.9%
Other values (102) 387
32.8%
Lowercase Letter
ValueCountFrequency (%)
o 1
33.3%
e 1
33.3%
n 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 77
100.0%
Open Punctuation
ValueCountFrequency (%)
( 77
100.0%
Space Separator
ValueCountFrequency (%)
54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1180
84.8%
Common 208
 
15.0%
Latin 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 150
 
12.7%
건 134
 
11.4%
설 124
 
10.5%
사 74
 
6.3%
회 74
 
6.3%
식 72
 
6.1%
합 55
 
4.7%
종 54
 
4.6%
이 34
 
2.9%
대 22
 
1.9%
Other values (102) 387
32.8%
Common
ValueCountFrequency (%)
) 77
37.0%
( 77
37.0%
54
26.0%
Latin
ValueCountFrequency (%)
o 1
33.3%
e 1
33.3%
n 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1180
84.8%
ASCII 211
 
15.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 150
 
12.7%
건 134
 
11.4%
설 124
 
10.5%
사 74
 
6.3%
회 74
 
6.3%
식 72
 
6.1%
합 55
 
4.7%
종 54
 
4.6%
이 34
 
2.9%
대 22
 
1.9%
Other values (102) 387
32.8%
ASCII
ValueCountFrequency (%)
) 77
36.5%
( 77
36.5%
54
25.6%
o 1
 
0.5%
e 1
 
0.5%
n 1
 
0.5%

Interactions

2024-01-10T07:28:28.245500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:28:28.080913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:28:28.324446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:28:28.163322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T07:28:31.263245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호관서명계약방법계약금액
번호1.0000.0000.4200.344
관서명0.0001.0000.4400.000
계약방법0.4200.4401.0000.612
계약금액0.3440.0000.6121.000
2024-01-10T07:28:31.340832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
계약방법관서명
계약방법1.0000.168
관서명0.1681.000
2024-01-10T07:28:31.409934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호계약금액관서명계약방법
번호1.0000.0730.0000.272
계약금액0.0731.0000.0000.448
관서명0.0000.0001.0000.168
계약방법0.2720.4480.1681.000

Missing values

2024-01-10T07:28:28.424071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:28:28.807228image/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
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