Overview

Dataset statistics

Number of variables7
Number of observations124
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.2 KiB
Average record size in memory59.1 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 (91.5%)Imbalance
번호 has unique valuesUnique
계약명 has unique valuesUnique
계약금액 has unique valuesUnique

Reproduction

Analysis started2024-01-09 22:28:23.655787
Analysis finished2024-01-09 22:28:24.446723
Duration0.79 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct124
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62.5
Minimum1
Maximum124
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-01-10T07:28:24.529380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7.15
Q131.75
median62.5
Q393.25
95-th percentile117.85
Maximum124
Range123
Interquartile range (IQR)61.5

Descriptive statistics

Standard deviation35.939764
Coefficient of variation (CV)0.57503623
Kurtosis-1.2
Mean62.5
Median Absolute Deviation (MAD)31
Skewness0
Sum7750
Variance1291.6667
MonotonicityStrictly increasing
2024-01-10T07:28:24.689287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.8%
80 1
 
0.8%
93 1
 
0.8%
92 1
 
0.8%
91 1
 
0.8%
90 1
 
0.8%
89 1
 
0.8%
88 1
 
0.8%
87 1
 
0.8%
86 1
 
0.8%
Other values (114) 114
91.9%
ValueCountFrequency (%)
1 1
0.8%
2 1
0.8%
3 1
0.8%
4 1
0.8%
5 1
0.8%
6 1
0.8%
7 1
0.8%
8 1
0.8%
9 1
0.8%
10 1
0.8%
ValueCountFrequency (%)
124 1
0.8%
123 1
0.8%
122 1
0.8%
121 1
0.8%
120 1
0.8%
119 1
0.8%
118 1
0.8%
117 1
0.8%
116 1
0.8%
115 1
0.8%

관서명
Categorical

IMBALANCE 

Distinct3
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
본청
122 
농업기술센터
 
1
보건소
 
1

Length

Max length6
Median length2
Mean length2.0403226
Min length2

Unique

Unique2 ?
Unique (%)1.6%

Sample

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

Common Values

ValueCountFrequency (%)
본청 122
98.4%
농업기술센터 1
 
0.8%
보건소 1
 
0.8%

Length

2024-01-10T07:28:24.819500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:28:24.929012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
본청 122
98.4%
농업기술센터 1
 
0.8%
보건소 1
 
0.8%

계약방법
Categorical

Distinct4
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
제한경쟁
78 
수의2인이상견적
31 
일반경쟁
12 
수의1인견적
 
3

Length

Max length8
Median length4
Mean length5.0483871
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제한경쟁 78
62.9%
수의2인이상견적 31
 
25.0%
일반경쟁 12
 
9.7%
수의1인견적 3
 
2.4%

Length

2024-01-10T07:28:25.052119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:28:25.185232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제한경쟁 78
62.9%
수의2인이상견적 31
 
25.0%
일반경쟁 12
 
9.7%
수의1인견적 3
 
2.4%

계약명
Text

UNIQUE 

Distinct124
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-01-10T07:28:25.422814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length28.5
Mean length20.241935
Min length9

Characters and Unicode

Total characters2510
Distinct characters242
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

Unique124 ?
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 12
 
3.0%
농어촌도로 10
 
2.5%
개설공사 10
 
2.5%
도시계획도로 9
 
2.3%
확포장공사 8
 
2.0%
정비공사 7
 
1.8%
공사 4
 
1.0%
장고도 4
 
1.0%
설치공사 4
 
1.0%
및 4
 
1.0%
Other values (258) 324
81.8%
2024-01-10T07:28:25.771504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
272
 
10.8%
사 134
 
5.3%
공 118
 
4.7%
도 84
 
3.3%
( 80
 
3.2%
) 80
 
3.2%
장 51
 
2.0%
성 47
 
1.9%
로 46
 
1.8%
시 43
 
1.7%
Other values (232) 1555
62.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1910
76.1%
Space Separator 272
 
10.8%
Decimal Number 137
 
5.5%
Open Punctuation 80
 
3.2%
Close Punctuation 80
 
3.2%
Dash Punctuation 15
 
0.6%
Other Punctuation 9
 
0.4%
Math Symbol 5
 
0.2%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 134
 
7.0%
공 118
 
6.2%
도 84
 
4.4%
장 51
 
2.7%
성 47
 
2.5%
로 46
 
2.4%
시 43
 
2.3%
설 43
 
2.3%
업 39
 
2.0%
차 36
 
1.9%
Other values (212) 1269
66.4%
Decimal Number
ValueCountFrequency (%)
2 41
29.9%
1 28
20.4%
3 19
13.9%
0 14
 
10.2%
6 11
 
8.0%
8 6
 
4.4%
9 6
 
4.4%
4 5
 
3.6%
5 4
 
2.9%
7 3
 
2.2%
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 (%)
272
100.0%
Open Punctuation
ValueCountFrequency (%)
( 80
100.0%
Close Punctuation
ValueCountFrequency (%)
) 80
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1910
76.1%
Common 598
 
23.8%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 134
 
7.0%
공 118
 
6.2%
도 84
 
4.4%
장 51
 
2.7%
성 47
 
2.5%
로 46
 
2.4%
시 43
 
2.3%
설 43
 
2.3%
업 39
 
2.0%
차 36
 
1.9%
Other values (212) 1269
66.4%
Common
ValueCountFrequency (%)
272
45.5%
( 80
 
13.4%
) 80
 
13.4%
2 41
 
6.9%
1 28
 
4.7%
3 19
 
3.2%
- 15
 
2.5%
0 14
 
2.3%
6 11
 
1.8%
, 8
 
1.3%
Other values (8) 30
 
5.0%
Latin
ValueCountFrequency (%)
I 1
50.0%
C 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1910
76.1%
ASCII 600
 
23.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
272
45.3%
( 80
 
13.3%
) 80
 
13.3%
2 41
 
6.8%
1 28
 
4.7%
3 19
 
3.2%
- 15
 
2.5%
0 14
 
2.3%
6 11
 
1.8%
, 8
 
1.3%
Other values (10) 32
 
5.3%
Hangul
ValueCountFrequency (%)
사 134
 
7.0%
공 118
 
6.2%
도 84
 
4.4%
장 51
 
2.7%
성 47
 
2.5%
로 46
 
2.4%
시 43
 
2.3%
설 43
 
2.3%
업 39
 
2.0%
차 36
 
1.9%
Other values (212) 1269
66.4%

계약금액
Real number (ℝ)

UNIQUE 

Distinct124
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1817546 × 109
Minimum34490000
Maximum1.3025797 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-01-10T07:28:25.929097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34490000
5-th percentile1.023679 × 108
Q12.684975 × 108
median4.786365 × 108
Q31.121775 × 109
95-th percentile5.5267238 × 109
Maximum1.3025797 × 1010
Range1.2991307 × 1010
Interquartile range (IQR)8.532775 × 108

Descriptive statistics

Standard deviation2.078811 × 109
Coefficient of variation (CV)1.7590885
Kurtosis15.028773
Mean1.1817546 × 109
Median Absolute Deviation (MAD)2.8771735 × 108
Skewness3.7333107
Sum1.4653757 × 1011
Variance4.321455 × 1018
MonotonicityNot monotonic
2024-01-10T07:28:26.086959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13025797000 1
 
0.8%
3459440000 1
 
0.8%
246300000 1
 
0.8%
468394000 1
 
0.8%
85200000 1
 
0.8%
595777000 1
 
0.8%
408938110 1
 
0.8%
1860335000 1
 
0.8%
73964000 1
 
0.8%
452806000 1
 
0.8%
Other values (114) 114
91.9%
ValueCountFrequency (%)
34490000 1
0.8%
73964000 1
0.8%
81272000 1
0.8%
85200000 1
0.8%
87082530 1
0.8%
99753000 1
0.8%
102358000 1
0.8%
102424000 1
0.8%
103617700 1
0.8%
112624000 1
0.8%
ValueCountFrequency (%)
13025797000 1
0.8%
11277800000 1
0.8%
8991903000 1
0.8%
8095590000 1
0.8%
8063556000 1
0.8%
6012500000 1
0.8%
5573179000 1
0.8%
5263478000 1
0.8%
3459440000 1
0.8%
2982726700 1
0.8%

계약일
Date

Distinct114
Distinct (%)91.9%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2014-01-16 00:00:00
Maximum2021-06-02 00:00:00
2024-01-10T07:28:26.207408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:28:26.326307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

계약상대자
Text

Distinct96
Distinct (%)77.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-01-10T07:28:26.527483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length8.5483871
Min length4

Characters and Unicode

Total characters1060
Distinct characters106
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

Unique76 ?
Unique (%)61.3%

Sample

1st row(주)라온토건
2nd row새한건설주식회사
3rd row네오서진건설 주식회사(neo)
4th row동광건설(주)
5th row(주)지안스건설
ValueCountFrequency (%)
주식회사 34
 
21.4%
케이티씨건설 5
 
3.1%
서림종합건설(주 4
 
2.5%
대운건설(주 3
 
1.9%
지수종합건설 3
 
1.9%
영화종합건설 3
 
1.9%
제이에이치종합건설(주 2
 
1.3%
영일종합건설(주 2
 
1.3%
주)다경종합건설 2
 
1.3%
삼주종합건설(주 2
 
1.3%
Other values (88) 99
62.3%
2024-01-10T07:28:26.907735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 116
 
10.9%
건 107
 
10.1%
설 98
 
9.2%
) 69
 
6.5%
( 69
 
6.5%
회 47
 
4.4%
사 47
 
4.4%
식 46
 
4.3%
합 45
 
4.2%
종 44
 
4.2%
Other values (96) 372
35.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 884
83.4%
Close Punctuation 69
 
6.5%
Open Punctuation 69
 
6.5%
Space Separator 35
 
3.3%
Lowercase Letter 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 116
 
13.1%
건 107
 
12.1%
설 98
 
11.1%
회 47
 
5.3%
사 47
 
5.3%
식 46
 
5.2%
합 45
 
5.1%
종 44
 
5.0%
이 29
 
3.3%
에 15
 
1.7%
Other values (90) 290
32.8%
Lowercase Letter
ValueCountFrequency (%)
n 1
33.3%
e 1
33.3%
o 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 69
100.0%
Open Punctuation
ValueCountFrequency (%)
( 69
100.0%
Space Separator
ValueCountFrequency (%)
35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 884
83.4%
Common 173
 
16.3%
Latin 3
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 116
 
13.1%
건 107
 
12.1%
설 98
 
11.1%
회 47
 
5.3%
사 47
 
5.3%
식 46
 
5.2%
합 45
 
5.1%
종 44
 
5.0%
이 29
 
3.3%
에 15
 
1.7%
Other values (90) 290
32.8%
Common
ValueCountFrequency (%)
) 69
39.9%
( 69
39.9%
35
20.2%
Latin
ValueCountFrequency (%)
n 1
33.3%
e 1
33.3%
o 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 884
83.4%
ASCII 176
 
16.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 116
 
13.1%
건 107
 
12.1%
설 98
 
11.1%
회 47
 
5.3%
사 47
 
5.3%
식 46
 
5.2%
합 45
 
5.1%
종 44
 
5.0%
이 29
 
3.3%
에 15
 
1.7%
Other values (90) 290
32.8%
ASCII
ValueCountFrequency (%)
) 69
39.2%
( 69
39.2%
35
19.9%
n 1
 
0.6%
e 1
 
0.6%
o 1
 
0.6%

Interactions

2024-01-10T07:28:24.121539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:28:23.982594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:28:24.192943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:28:24.049403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T07:28:26.998659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호관서명계약방법계약금액계약상대자
번호1.0000.0050.4420.1890.602
관서명0.0051.0000.1360.0001.000
계약방법0.4420.1361.0000.4730.000
계약금액0.1890.0000.4731.0000.940
계약상대자0.6021.0000.0000.9401.000
2024-01-10T07:28:27.080898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
계약방법관서명
계약방법1.0000.127
관서명0.1271.000
2024-01-10T07:28:27.155560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호계약금액관서명계약방법
번호1.000-0.1350.0000.271
계약금액-0.1351.0000.0000.341
관서명0.0000.0001.0000.127
계약방법0.2710.3410.1271.000

Missing values

2024-01-10T07:28:24.293282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:28:24.399688image/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
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