Overview

Dataset statistics

Number of variables12
Number of observations181
Missing cells148
Missing cells (%)6.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.0 KiB
Average record size in memory101.7 B

Variable types

Numeric4
Categorical3
Boolean1
Text4

Dataset

Description광주광역시 동구 계약정보시스템 공동도급 데이터입니다. 데이터는 계약대장번호, 주계약업체여부, 거래처순번, 업체명, 대표자, 주소 등으로 구성되어 있습니다.
URLhttps://www.data.go.kr/data/15121115/fileData.do

Alerts

주계약업체여부 has constant value ""Constant
데이터기준일자 has constant value ""Constant
계약대장번호 is highly overall correlated with 순서 and 1 other fieldsHigh correlation
비고 is highly overall correlated with 순서 and 4 other fieldsHigh correlation
순서 is highly overall correlated with 계약대장번호 and 1 other fieldsHigh correlation
거래처순번 is highly overall correlated with 비고High correlation
공동비율 is highly overall correlated with 공동계약금액 and 1 other fieldsHigh correlation
공동계약금액 is highly overall correlated with 공동비율 and 1 other fieldsHigh correlation
계약분야 has 148 (81.8%) missing valuesMissing
순서 has unique valuesUnique
공동비율 has 109 (60.2%) zerosZeros
공동계약금액 has 76 (42.0%) zerosZeros

Reproduction

Analysis started2023-12-12 15:17:42.592180
Analysis finished2023-12-12 15:17:45.664168
Duration3.07 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순서
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct181
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54383.243
Minimum2888
Maximum107424
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-13T00:17:45.752799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2888
5-th percentile9104
Q19157
median52768
Q3104497
95-th percentile107415
Maximum107424
Range104536
Interquartile range (IQR)95340

Descriptive statistics

Standard deviation43539.737
Coefficient of variation (CV)0.80060942
Kurtosis-1.7925738
Mean54383.243
Median Absolute Deviation (MAD)43634
Skewness0.10713729
Sum9843367
Variance1.8957087 × 109
MonotonicityNot monotonic
2023-12-13T00:17:45.942525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9118 1
 
0.6%
85902 1
 
0.6%
81910 1
 
0.6%
78921 1
 
0.6%
107411 1
 
0.6%
85891 1
 
0.6%
104484 1
 
0.6%
83686 1
 
0.6%
104489 1
 
0.6%
104485 1
 
0.6%
Other values (171) 171
94.5%
ValueCountFrequency (%)
2888 1
0.6%
2891 1
0.6%
2895 1
0.6%
2896 1
0.6%
2929 1
0.6%
3595 1
0.6%
9101 1
0.6%
9102 1
0.6%
9103 1
0.6%
9104 1
0.6%
ValueCountFrequency (%)
107424 1
0.6%
107423 1
0.6%
107422 1
0.6%
107421 1
0.6%
107420 1
0.6%
107419 1
0.6%
107418 1
0.6%
107417 1
0.6%
107416 1
0.6%
107415 1
0.6%

계약대장번호
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
202000000000
137 
201000000000
44 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row201000000000
2nd row201000000000
3rd row201000000000
4th row201000000000
5th row201000000000

Common Values

ValueCountFrequency (%)
202000000000 137
75.7%
201000000000 44
 
24.3%

Length

2023-12-13T00:17:46.111845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:17:46.233517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
202000000000 137
75.7%
201000000000 44
 
24.3%

주계약업체여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size313.0 B
False
181 
ValueCountFrequency (%)
False 181
100.0%
2023-12-13T00:17:46.381376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

거래처순번
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.6022099
Minimum1
Maximum11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-13T00:17:46.523559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q12
median2
Q33
95-th percentile5
Maximum11
Range10
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.3730726
Coefficient of variation (CV)0.52765636
Kurtosis15.451364
Mean2.6022099
Median Absolute Deviation (MAD)0
Skewness3.6117981
Sum471
Variance1.8853284
MonotonicityNot monotonic
2023-12-13T00:17:46.702644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
2 124
68.5%
3 37
 
20.4%
4 7
 
3.9%
5 4
 
2.2%
6 3
 
1.7%
7 1
 
0.6%
8 1
 
0.6%
9 1
 
0.6%
10 1
 
0.6%
11 1
 
0.6%
ValueCountFrequency (%)
1 1
 
0.6%
2 124
68.5%
3 37
 
20.4%
4 7
 
3.9%
5 4
 
2.2%
6 3
 
1.7%
7 1
 
0.6%
8 1
 
0.6%
9 1
 
0.6%
10 1
 
0.6%
ValueCountFrequency (%)
11 1
 
0.6%
10 1
 
0.6%
9 1
 
0.6%
8 1
 
0.6%
7 1
 
0.6%
6 3
 
1.7%
5 4
 
2.2%
4 7
 
3.9%
3 37
 
20.4%
2 124
68.5%

업체명
Text

Distinct148
Distinct (%)81.8%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-13T00:17:46.992932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length8.6740331
Min length4

Characters and Unicode

Total characters1570
Distinct characters216
Distinct categories6 ?
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 (%)68.5%

Sample

1st row우성설계감리(주)
2nd row(주)건영엔지니어링
3rd row호진기계
4th row(주)명선조경체육산업
5th row광주전남레미콘공업(협)
ValueCountFrequency (%)
주식회사 21
 
10.2%
하늘천 5
 
2.4%
흥국화재해상보험(주 4
 
2.0%
주)케이비손해보험 4
 
2.0%
공공디자인연구소 3
 
1.5%
주)좋은엔지니어링 3
 
1.5%
광주전남레미콘공업(협 2
 
1.0%
한화손해보험(주 2
 
1.0%
주)도시문화집단씨에스 2
 
1.0%
엔탑엔지니어링 2
 
1.0%
Other values (142) 157
76.6%
2023-12-13T00:17:47.451844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 142
 
9.0%
( 127
 
8.1%
) 127
 
8.1%
사 58
 
3.7%
이 38
 
2.4%
지 34
 
2.2%
엔 33
 
2.1%
스 30
 
1.9%
어 26
 
1.7%
회 25
 
1.6%
Other values (206) 930
59.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1287
82.0%
Open Punctuation 127
 
8.1%
Close Punctuation 127
 
8.1%
Space Separator 24
 
1.5%
Uppercase Letter 3
 
0.2%
Decimal Number 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 142
 
11.0%
사 58
 
4.5%
이 38
 
3.0%
지 34
 
2.6%
엔 33
 
2.6%
스 30
 
2.3%
어 26
 
2.0%
회 25
 
1.9%
식 24
 
1.9%
니 22
 
1.7%
Other values (198) 855
66.4%
Uppercase Letter
ValueCountFrequency (%)
N 1
33.3%
G 1
33.3%
E 1
33.3%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 127
100.0%
Close Punctuation
ValueCountFrequency (%)
) 127
100.0%
Space Separator
ValueCountFrequency (%)
24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1287
82.0%
Common 280
 
17.8%
Latin 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 142
 
11.0%
사 58
 
4.5%
이 38
 
3.0%
지 34
 
2.6%
엔 33
 
2.6%
스 30
 
2.3%
어 26
 
2.0%
회 25
 
1.9%
식 24
 
1.9%
니 22
 
1.7%
Other values (198) 855
66.4%
Common
ValueCountFrequency (%)
( 127
45.4%
) 127
45.4%
24
 
8.6%
2 1
 
0.4%
1 1
 
0.4%
Latin
ValueCountFrequency (%)
N 1
33.3%
G 1
33.3%
E 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1287
82.0%
ASCII 283
 
18.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 142
 
11.0%
사 58
 
4.5%
이 38
 
3.0%
지 34
 
2.6%
엔 33
 
2.6%
스 30
 
2.3%
어 26
 
2.0%
회 25
 
1.9%
식 24
 
1.9%
니 22
 
1.7%
Other values (198) 855
66.4%
ASCII
ValueCountFrequency (%)
( 127
44.9%
) 127
44.9%
24
 
8.5%
N 1
 
0.4%
G 1
 
0.4%
E 1
 
0.4%
2 1
 
0.4%
1 1
 
0.4%

대표자
Text

Distinct150
Distinct (%)82.9%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-13T00:17:47.829837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length3
Mean length3.6298343
Min length2

Characters and Unicode

Total characters657
Distinct characters142
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique125 ?
Unique (%)69.1%

Sample

1st row배용호, 신진걸
2nd row류선영
3rd row호진기계
4th row(주)명선조경체육산업
5th row박정환
ValueCountFrequency (%)
신영태 5
 
2.6%
김기환 4
 
2.1%
권중원 3
 
1.6%
박규남 3
 
1.6%
홍성호 3
 
1.6%
정종운 3
 
1.6%
박윤식 2
 
1.0%
김욱 2
 
1.0%
정성구 2
 
1.0%
박홍주 2
 
1.0%
Other values (146) 163
84.9%
2023-12-13T00:17:48.424893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 35
 
5.3%
박 30
 
4.6%
이 30
 
4.6%
정 23
 
3.5%
성 21
 
3.2%
영 16
 
2.4%
주 16
 
2.4%
수 15
 
2.3%
, 14
 
2.1%
종 14
 
2.1%
Other values (132) 443
67.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 628
95.6%
Other Punctuation 14
 
2.1%
Space Separator 11
 
1.7%
Open Punctuation 2
 
0.3%
Close Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 35
 
5.6%
박 30
 
4.8%
이 30
 
4.8%
정 23
 
3.7%
성 21
 
3.3%
영 16
 
2.5%
주 16
 
2.5%
수 15
 
2.4%
종 14
 
2.2%
호 14
 
2.2%
Other values (128) 414
65.9%
Other Punctuation
ValueCountFrequency (%)
, 14
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 628
95.6%
Common 29
 
4.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 35
 
5.6%
박 30
 
4.8%
이 30
 
4.8%
정 23
 
3.7%
성 21
 
3.3%
영 16
 
2.5%
주 16
 
2.5%
수 15
 
2.4%
종 14
 
2.2%
호 14
 
2.2%
Other values (128) 414
65.9%
Common
ValueCountFrequency (%)
, 14
48.3%
11
37.9%
( 2
 
6.9%
) 2
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 628
95.6%
ASCII 29
 
4.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 35
 
5.6%
박 30
 
4.8%
이 30
 
4.8%
정 23
 
3.7%
성 21
 
3.3%
영 16
 
2.5%
주 16
 
2.5%
수 15
 
2.4%
종 14
 
2.2%
호 14
 
2.2%
Other values (128) 414
65.9%
ASCII
ValueCountFrequency (%)
, 14
48.3%
11
37.9%
( 2
 
6.9%
) 2
 
6.9%

주소
Text

Distinct149
Distinct (%)82.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-13T00:17:48.829680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length36
Mean length25.060773
Min length17

Characters and Unicode

Total characters4536
Distinct characters232
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

Unique124 ?
Unique (%)68.5%

Sample

1st row대구광역시 달서구 두류길8 ,405호 (두류동)
2nd row전라남도 화순군 화순읍 만연리238-2
3rd row인천광역시 계양구 역골로133번길23 (다남동)
4th row전라남도 나주시 금성길18 (남내동)
5th row광주광역시 서구 화정로261 (농성동, 광주은행화정지점 3층)
ValueCountFrequency (%)
전라남도 67
 
8.1%
광주광역시 57
 
6.9%
서울특별시 24
 
2.9%
서구 21
 
2.6%
북구 19
 
2.3%
나주시 16
 
1.9%
담양군 10
 
1.2%
동구 9
 
1.1%
화순군 9
 
1.1%
전라북도 9
 
1.1%
Other values (407) 582
70.7%
2023-12-13T00:17:49.367572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
737
 
16.2%
동 159
 
3.5%
1 156
 
3.4%
시 144
 
3.2%
광 139
 
3.1%
로 128
 
2.8%
) 120
 
2.6%
( 120
 
2.6%
남 110
 
2.4%
구 108
 
2.4%
Other values (222) 2615
57.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2761
60.9%
Space Separator 737
 
16.2%
Decimal Number 708
 
15.6%
Close Punctuation 120
 
2.6%
Open Punctuation 120
 
2.6%
Dash Punctuation 53
 
1.2%
Other Punctuation 32
 
0.7%
Uppercase Letter 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 159
 
5.8%
시 144
 
5.2%
광 139
 
5.0%
로 128
 
4.6%
남 110
 
4.0%
구 108
 
3.9%
도 101
 
3.7%
주 89
 
3.2%
전 85
 
3.1%
길 77
 
2.8%
Other values (204) 1621
58.7%
Decimal Number
ValueCountFrequency (%)
1 156
22.0%
2 101
14.3%
3 78
11.0%
0 70
9.9%
4 66
9.3%
6 60
 
8.5%
5 54
 
7.6%
8 49
 
6.9%
7 39
 
5.5%
9 35
 
4.9%
Uppercase Letter
ValueCountFrequency (%)
A 3
60.0%
M 1
 
20.0%
J 1
 
20.0%
Space Separator
ValueCountFrequency (%)
737
100.0%
Close Punctuation
ValueCountFrequency (%)
) 120
100.0%
Open Punctuation
ValueCountFrequency (%)
( 120
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 53
100.0%
Other Punctuation
ValueCountFrequency (%)
, 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2761
60.9%
Common 1770
39.0%
Latin 5
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 159
 
5.8%
시 144
 
5.2%
광 139
 
5.0%
로 128
 
4.6%
남 110
 
4.0%
구 108
 
3.9%
도 101
 
3.7%
주 89
 
3.2%
전 85
 
3.1%
길 77
 
2.8%
Other values (204) 1621
58.7%
Common
ValueCountFrequency (%)
737
41.6%
1 156
 
8.8%
) 120
 
6.8%
( 120
 
6.8%
2 101
 
5.7%
3 78
 
4.4%
0 70
 
4.0%
4 66
 
3.7%
6 60
 
3.4%
5 54
 
3.1%
Other values (5) 208
 
11.8%
Latin
ValueCountFrequency (%)
A 3
60.0%
M 1
 
20.0%
J 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2761
60.9%
ASCII 1775
39.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
737
41.5%
1 156
 
8.8%
) 120
 
6.8%
( 120
 
6.8%
2 101
 
5.7%
3 78
 
4.4%
0 70
 
3.9%
4 66
 
3.7%
6 60
 
3.4%
5 54
 
3.0%
Other values (8) 213
 
12.0%
Hangul
ValueCountFrequency (%)
동 159
 
5.8%
시 144
 
5.2%
광 139
 
5.0%
로 128
 
4.6%
남 110
 
4.0%
구 108
 
3.9%
도 101
 
3.7%
주 89
 
3.2%
전 85
 
3.1%
길 77
 
2.8%
Other values (204) 1621
58.7%

공동비율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct47
Distinct (%)26.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.5029669
Minimum0
Maximum70
Zeros109
Zeros (%)60.2%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-13T00:17:49.548355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q318
95-th percentile38.4
Maximum70
Range70
Interquartile range (IQR)18

Descriptive statistics

Standard deviation13.313549
Coefficient of variation (CV)1.5657534
Kurtosis2.5771075
Mean8.5029669
Median Absolute Deviation (MAD)0
Skewness1.6682518
Sum1539.037
Variance177.25059
MonotonicityNot monotonic
2023-12-13T00:17:49.734413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
0.0 109
60.2%
10.0 7
 
3.9%
20.0 6
 
3.3%
18.0 5
 
2.8%
40.0 5
 
2.8%
15.0 3
 
1.7%
30.0 3
 
1.7%
18.6 2
 
1.1%
19.0 2
 
1.1%
21.0 2
 
1.1%
Other values (37) 37
 
20.4%
ValueCountFrequency (%)
0.0 109
60.2%
2.0 1
 
0.6%
3.0 1
 
0.6%
3.12 1
 
0.6%
4.0 1
 
0.6%
4.19 1
 
0.6%
5.1 1
 
0.6%
5.62 1
 
0.6%
5.64 1
 
0.6%
6.0 1
 
0.6%
ValueCountFrequency (%)
70.0 1
 
0.6%
50.0 1
 
0.6%
45.0 1
 
0.6%
40.0 5
2.8%
39.8 1
 
0.6%
38.4 1
 
0.6%
37.62 1
 
0.6%
36.35 1
 
0.6%
35.26 1
 
0.6%
35.2 1
 
0.6%

계약분야
Text

MISSING 

Distinct28
Distinct (%)84.8%
Missing148
Missing (%)81.8%
Memory size1.5 KiB
2023-12-13T00:17:49.994552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length10
Mean length7.6060606
Min length2

Characters and Unicode

Total characters251
Distinct characters59
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row전기
2nd row조경
3rd row보존처리
4th row기계,전기,소방
5th row건축
ValueCountFrequency (%)
전기 6
 
13.0%
소방 5
 
10.9%
설계업(전력전문설계1종 4
 
8.7%
전기,통신,소방 3
 
6.5%
통신 3
 
6.5%
조경 2
 
4.3%
정보통신 2
 
4.3%
기계 2
 
4.3%
간판디자인 1
 
2.2%
폐기물중간처분업(지정폐기물 1
 
2.2%
Other values (17) 17
37.0%
2023-12-13T00:17:50.392010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
전 19
 
7.6%
, 19
 
7.6%
기 19
 
7.6%
계 13
 
5.2%
13
 
5.2%
소 11
 
4.4%
방 10
 
4.0%
설 10
 
4.0%
업 9
 
3.6%
신 9
 
3.6%
Other values (49) 119
47.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 205
81.7%
Other Punctuation 19
 
7.6%
Space Separator 13
 
5.2%
Open Punctuation 6
 
2.4%
Close Punctuation 4
 
1.6%
Decimal Number 4
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 19
 
9.3%
기 19
 
9.3%
계 13
 
6.3%
소 11
 
5.4%
방 10
 
4.9%
설 10
 
4.9%
업 9
 
4.4%
신 9
 
4.4%
통 9
 
4.4%
사 6
 
2.9%
Other values (44) 90
43.9%
Other Punctuation
ValueCountFrequency (%)
, 19
100.0%
Space Separator
ValueCountFrequency (%)
13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Decimal Number
ValueCountFrequency (%)
1 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 205
81.7%
Common 46
 
18.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 19
 
9.3%
기 19
 
9.3%
계 13
 
6.3%
소 11
 
5.4%
방 10
 
4.9%
설 10
 
4.9%
업 9
 
4.4%
신 9
 
4.4%
통 9
 
4.4%
사 6
 
2.9%
Other values (44) 90
43.9%
Common
ValueCountFrequency (%)
, 19
41.3%
13
28.3%
( 6
 
13.0%
) 4
 
8.7%
1 4
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 205
81.7%
ASCII 46
 
18.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
전 19
 
9.3%
기 19
 
9.3%
계 13
 
6.3%
소 11
 
5.4%
방 10
 
4.9%
설 10
 
4.9%
업 9
 
4.4%
신 9
 
4.4%
통 9
 
4.4%
사 6
 
2.9%
Other values (44) 90
43.9%
ASCII
ValueCountFrequency (%)
, 19
41.3%
13
28.3%
( 6
 
13.0%
) 4
 
8.7%
1 4
 
8.7%

공동계약금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct102
Distinct (%)56.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26346748
Minimum0
Maximum6.4 × 108
Zeros76
Zeros (%)42.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-13T00:17:50.538233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2954500
Q313461800
95-th percentile78840000
Maximum6.4 × 108
Range6.4 × 108
Interquartile range (IQR)13461800

Descriptive statistics

Standard deviation84349201
Coefficient of variation (CV)3.2015033
Kurtosis27.874485
Mean26346748
Median Absolute Deviation (MAD)2954500
Skewness5.1058609
Sum4.7687614 × 109
Variance7.1147877 × 1015
MonotonicityNot monotonic
2023-12-13T00:17:50.722043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 76
42.0%
3300000 2
 
1.1%
360000000 2
 
1.1%
8400000 2
 
1.1%
364320000 2
 
1.1%
1632400 1
 
0.6%
5013590 1
 
0.6%
9000000 1
 
0.6%
3000000 1
 
0.6%
1459190 1
 
0.6%
Other values (92) 92
50.8%
ValueCountFrequency (%)
0 76
42.0%
400000 1
 
0.6%
1100000 1
 
0.6%
1108000 1
 
0.6%
1375000 1
 
0.6%
1459190 1
 
0.6%
1526110 1
 
0.6%
1632400 1
 
0.6%
1672000 1
 
0.6%
2041000 1
 
0.6%
ValueCountFrequency (%)
640000000 1
0.6%
546480000 1
0.6%
364320000 2
1.1%
360000000 2
1.1%
310887780 1
0.6%
98956000 1
0.6%
82260000 1
0.6%
78840000 1
0.6%
77600000 1
0.6%
61904500 1
0.6%

비고
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
계약분야데이터 미보유
148 
<NA>
33 

Length

Max length11
Median length11
Mean length9.7237569
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row계약분야데이터 미보유
4th row계약분야데이터 미보유
5th row계약분야데이터 미보유

Common Values

ValueCountFrequency (%)
계약분야데이터 미보유 148
81.8%
<NA> 33
 
18.2%

Length

2023-12-13T00:17:50.916276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:17:51.067668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
계약분야데이터 148
45.0%
미보유 148
45.0%
na 33
 
10.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-08-29
181 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-29
2nd row2023-08-29
3rd row2023-08-29
4th row2023-08-29
5th row2023-08-29

Common Values

ValueCountFrequency (%)
2023-08-29 181
100.0%

Length

2023-12-13T00:17:51.222988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:17:51.358291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-29 181
100.0%

Interactions

2023-12-13T00:17:44.819129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:17:43.221938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:17:43.682883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:17:44.410806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:17:44.930080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:17:43.338039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:17:43.799437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:17:44.505050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:17:45.038224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:17:43.442178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:17:43.887529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:17:44.609057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:17:45.163359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:17:43.580089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:17:43.984613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:17:44.699355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:17:51.453308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순서계약대장번호거래처순번공동비율계약분야공동계약금액
순서1.0000.8240.0000.0000.5060.000
계약대장번호0.8241.0000.4800.2031.0000.025
거래처순번0.0000.4801.0000.0000.7130.200
공동비율0.0000.2030.0001.0000.4200.506
계약분야0.5061.0000.7130.4201.0001.000
공동계약금액0.0000.0250.2000.5061.0001.000
2023-12-13T00:17:51.592552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
계약대장번호비고
계약대장번호1.0001.000
비고1.0001.000
2023-12-13T00:17:51.721717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순서거래처순번공동비율공동계약금액계약대장번호비고
순서1.000-0.1850.0650.0520.6461.000
거래처순번-0.1851.000-0.1620.0080.3601.000
공동비율0.065-0.1621.0000.5620.1951.000
공동계약금액0.0520.0080.5621.0000.0131.000
계약대장번호0.6460.3600.1950.0131.0001.000
비고1.0001.0001.0001.0001.0001.000

Missing values

2023-12-13T00:17:45.352784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:17:45.583259image/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

순서계약대장번호주계약업체여부거래처순번업체명대표자주소공동비율계약분야공동계약금액비고데이터기준일자
09118201000000000N2우성설계감리(주)배용호, 신진걸대구광역시 달서구 두류길8 ,405호 (두류동)0.0전기2200000<NA>2023-08-29
19119201000000000N3(주)건영엔지니어링류선영전라남도 화순군 화순읍 만연리238-20.0조경3300000<NA>2023-08-29
29112201000000000N2호진기계호진기계인천광역시 계양구 역골로133번길23 (다남동)0.0<NA>0계약분야데이터 미보유2023-08-29
39164201000000000N2(주)명선조경체육산업(주)명선조경체육산업전라남도 나주시 금성길18 (남내동)0.0<NA>1108000계약분야데이터 미보유2023-08-29
49165201000000000N3광주전남레미콘공업(협)박정환광주광역시 서구 화정로261 (농성동, 광주은행화정지점 3층)0.0<NA>1526110계약분야데이터 미보유2023-08-29
59166201000000000N4(주)명선조경체육산업(주)명선조경체육산업전라남도 나주시 금성길18 (남내동)0.0<NA>3030000계약분야데이터 미보유2023-08-29
69167201000000000N5(유)코리아레포츠채윤자전라남도 화순군 도곡면 도곡농공길29-40.0<NA>5577000계약분야데이터 미보유2023-08-29
79168201000000000N6(주)에이치에스파트너스최병술전라남도 영암군 군서면 군서공단로60-100.0<NA>8320000계약분야데이터 미보유2023-08-29
89169201000000000N7(주)엡스코어박성철전라남도 나주시 동수농공단지길30-89 (운곡동)0.0<NA>14433600계약분야데이터 미보유2023-08-29
99170201000000000N8(유)코리아레포츠채윤자전라남도 화순군 도곡면 도곡농공길29-40.0<NA>22883000계약분야데이터 미보유2023-08-29
순서계약대장번호주계약업체여부거래처순번업체명대표자주소공동비율계약분야공동계약금액비고데이터기준일자
171107406202000000000N2(주)한국전산정동익대구광역시 동구 신암남로 160 (신암동), 오베이스타운2층40.0<NA>57200000계약분야데이터 미보유2023-08-29
172107408202000000000N2(주)케이비손해보험김기환서울특별시 강남구 테헤란로 117(역삼동)0.0<NA>0계약분야데이터 미보유2023-08-29
173107409202000000000N2(주)새터이엔지나경주광주광역시 서구 유림로98번길 41, 402호(동천동)5.64<NA>20000000계약분야데이터 미보유2023-08-29
174107417202000000000N2(주)더시선건축사사무소길종일광주광역시 북구 첨단과기로208번길 43-22 (오룡동), A동 6층 604A호15.3<NA>51249000계약분야데이터 미보유2023-08-29
175107418202000000000N3(주)좋은엔지니어링박규남광주광역시 서구 대남대로 473-2(농성동)894 (쌍촌동)15.0<NA>50244150계약분야데이터 미보유2023-08-29
176107422202000000000N2종합건축사사무소메카강형선광주광역시 서구 화정로 293102호(농성동, 광신빌딩4층)0.0<NA>0계약분야데이터 미보유2023-08-29
177104490202000000000N3(주)만송엔지니어링이주립전라남도 순천시 풍덕주택1길 34(풍덕동)0.0<NA>0계약분야데이터 미보유2023-08-29
178104495202000000000N1(주)케이제이구조기술사사무소김정수전라남도 담양군 담양읍 객사2길 7-13층0.0<NA>8400000계약분야데이터 미보유2023-08-29
179107414202000000000N2(주)새터이엔지나경주광주광역시 서구 유림로98번길 41, 402호(동천동)0.0<NA>0계약분야데이터 미보유2023-08-29
180107424202000000000N2(주)카스김태인광주광역시 광산구 사암로 810(도천동)0.0<NA>0계약분야데이터 미보유2023-08-29