Overview

Dataset statistics

Number of variables6
Number of observations909
Missing cells148
Missing cells (%)2.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory45.4 KiB
Average record size in memory51.1 B

Variable types

Categorical2
DateTime1
Numeric2
Text1

Dataset

Description경상남도 공사계약 설계변경 현황 데이터로, 공사년도, 공사구분, 설계변경일, 증감액, 최종변경액, 설계변경사유에 대한 정보를 포함하고 있습니다.
Author경상남도
URLhttps://www.data.go.kr/data/15049520/fileData.do

Alerts

공사구분 has constant value ""Constant
증감액 has 38 (4.2%) missing valuesMissing
설계변경사유 has 110 (12.1%) missing valuesMissing

Reproduction

Analysis started2023-12-12 05:18:31.553570
Analysis finished2023-12-12 05:18:32.565640
Duration1.01 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

공사년도
Categorical

Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
2020
241 
2021
218 
2022
213 
2019
196 
2023
41 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019
2nd row2019
3rd row2019
4th row2019
5th row2019

Common Values

ValueCountFrequency (%)
2020 241
26.5%
2021 218
24.0%
2022 213
23.4%
2019 196
21.6%
2023 41
 
4.5%

Length

2023-12-12T14:18:32.649739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:18:32.780483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 241
26.5%
2021 218
24.0%
2022 213
23.4%
2019 196
21.6%
2023 41
 
4.5%

공사구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
공사
909 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공사 909
100.0%

Length

2023-12-12T14:18:32.905372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:18:32.992282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공사 909
100.0%

설계변경일자
Date

Distinct514
Distinct (%)56.5%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
Minimum2019-03-11 00:00:00
Maximum2023-08-17 00:00:00
2023-12-12T14:18:33.091485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:18:33.501541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

증감액
Real number (ℝ)

MISSING 

Distinct868
Distinct (%)99.7%
Missing38
Missing (%)4.2%
Infinite0
Infinite (%)0.0%
Mean78141836
Minimum-6.254663 × 109
Maximum2.2387 × 1010
Zeros0
Zeros (%)0.0%
Negative549
Negative (%)60.4%
Memory size8.1 KiB
2023-12-12T14:18:33.695847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-6.254663 × 109
5-th percentile-2.990735 × 108
Q1-21901490
median-2251260
Q331504000
95-th percentile4.43251 × 108
Maximum2.2387 × 1010
Range2.8641663 × 1010
Interquartile range (IQR)53405490

Descriptive statistics

Standard deviation1.1351908 × 109
Coefficient of variation (CV)14.527311
Kurtosis219.8974
Mean78141836
Median Absolute Deviation (MAD)23330740
Skewness12.445686
Sum6.8061539 × 1010
Variance1.2886581 × 1018
MonotonicityNot monotonic
2023-12-12T14:18:33.839446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-500000000 2
 
0.2%
-5700000 2
 
0.2%
-1945000 2
 
0.2%
160013810 1
 
0.1%
32077800 1
 
0.1%
6890800 1
 
0.1%
-62285400 1
 
0.1%
-770000 1
 
0.1%
19291950 1
 
0.1%
-90161800 1
 
0.1%
Other values (858) 858
94.4%
(Missing) 38
 
4.2%
ValueCountFrequency (%)
-6254663000 1
0.1%
-3920000000 1
0.1%
-3590240000 1
0.1%
-3498886790 1
0.1%
-3386790000 1
0.1%
-2633800000 1
0.1%
-2184600000 1
0.1%
-2148300000 1
0.1%
-1984900000 1
0.1%
-1382558000 1
0.1%
ValueCountFrequency (%)
22387000000 1
0.1%
15290000000 1
0.1%
11111000000 1
0.1%
4559610000 1
0.1%
4465400000 1
0.1%
3570710000 1
0.1%
3063259000 1
0.1%
2830000000 1
0.1%
2719900000 1
0.1%
2687727350 1
0.1%

최종변경액
Real number (ℝ)

Distinct890
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0502319 × 109
Minimum3707000
Maximum3.8457 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.1 KiB
2023-12-12T14:18:34.032606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3707000
5-th percentile28500504
Q11.77898 × 108
median8.878 × 108
Q32.4 × 109
95-th percentile7.267 × 109
Maximum3.8457 × 1010
Range3.8453293 × 1010
Interquartile range (IQR)2.222102 × 109

Descriptive statistics

Standard deviation3.7743185 × 109
Coefficient of variation (CV)1.8409227
Kurtosis42.254028
Mean2.0502319 × 109
Median Absolute Deviation (MAD)8.122652 × 108
Skewness5.508296
Sum1.8636608 × 1012
Variance1.424548 × 1019
MonotonicityNot monotonic
2023-12-12T14:18:34.189791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35067000000 3
 
0.3%
4642698000 2
 
0.2%
7267000000 2
 
0.2%
934471000 2
 
0.2%
2096263000 2
 
0.2%
100000000 2
 
0.2%
1601023000 2
 
0.2%
1383720000 2
 
0.2%
3260140000 2
 
0.2%
2777280000 2
 
0.2%
Other values (880) 888
97.7%
ValueCountFrequency (%)
3707000 1
0.1%
4561000 1
0.1%
4795660 1
0.1%
5520880 1
0.1%
6133740 1
0.1%
6677000 1
0.1%
6933770 1
0.1%
7096330 1
0.1%
7242400 1
0.1%
7581000 1
0.1%
ValueCountFrequency (%)
38457000000 1
 
0.1%
37587000000 1
 
0.1%
35067000000 3
0.3%
33097302000 1
 
0.1%
17807302000 1
 
0.1%
16596920000 1
 
0.1%
15906898410 1
 
0.1%
15474698410 1
 
0.1%
15397398410 1
 
0.1%
14025300000 1
 
0.1%

설계변경사유
Text

MISSING 

Distinct424
Distinct (%)53.1%
Missing110
Missing (%)12.1%
Memory size7.2 KiB
2023-12-12T14:18:34.534869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length85
Median length49
Mean length17.475594
Min length3

Characters and Unicode

Total characters13963
Distinct characters314
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique356 ?
Unique (%)44.6%

Sample

1st row보험료 정산
2nd row현장여건 반영
3rd row보험료 정산
4th row현장여건 반영
5th row보험료 등 제경비 정산
ValueCountFrequency (%)
등 398
 
10.4%
정산 362
 
9.5%
반영 329
 
8.6%
보험료 222
 
5.8%
및 159
 
4.2%
조정 132
 
3.5%
현장여건 129
 
3.4%
변경 125
 
3.3%
따른 96
 
2.5%
차수간 94
 
2.5%
Other values (639) 1767
46.3%
2023-12-12T14:18:35.025049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3112
22.3%
정 742
 
5.3%
보 449
 
3.2%
등 436
 
3.1%
산 404
 
2.9%
반 379
 
2.7%
영 365
 
2.6%
료 342
 
2.4%
험 333
 
2.4%
변 317
 
2.3%
Other values (304) 7084
50.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10467
75.0%
Space Separator 3112
 
22.3%
Other Punctuation 173
 
1.2%
Decimal Number 54
 
0.4%
Close Punctuation 49
 
0.4%
Open Punctuation 49
 
0.4%
Uppercase Letter 49
 
0.4%
Lowercase Letter 5
 
< 0.1%
Math Symbol 4
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
정 742
 
7.1%
보 449
 
4.3%
등 436
 
4.2%
산 404
 
3.9%
반 379
 
3.6%
영 365
 
3.5%
료 342
 
3.3%
험 333
 
3.2%
변 317
 
3.0%
물 317
 
3.0%
Other values (277) 6383
61.0%
Decimal Number
ValueCountFrequency (%)
1 22
40.7%
2 9
16.7%
3 8
 
14.8%
0 5
 
9.3%
5 4
 
7.4%
4 3
 
5.6%
8 2
 
3.7%
9 1
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
S 19
38.8%
E 18
36.7%
C 4
 
8.2%
P 3
 
6.1%
V 2
 
4.1%
T 1
 
2.0%
K 1
 
2.0%
B 1
 
2.0%
Lowercase Letter
ValueCountFrequency (%)
c 2
40.0%
v 1
20.0%
t 1
20.0%
u 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 168
97.1%
. 5
 
2.9%
Space Separator
ValueCountFrequency (%)
3112
100.0%
Close Punctuation
ValueCountFrequency (%)
) 49
100.0%
Open Punctuation
ValueCountFrequency (%)
( 49
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10467
75.0%
Common 3442
 
24.7%
Latin 54
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
정 742
 
7.1%
보 449
 
4.3%
등 436
 
4.2%
산 404
 
3.9%
반 379
 
3.6%
영 365
 
3.5%
료 342
 
3.3%
험 333
 
3.2%
변 317
 
3.0%
물 317
 
3.0%
Other values (277) 6383
61.0%
Common
ValueCountFrequency (%)
3112
90.4%
, 168
 
4.9%
) 49
 
1.4%
( 49
 
1.4%
1 22
 
0.6%
2 9
 
0.3%
3 8
 
0.2%
. 5
 
0.1%
0 5
 
0.1%
~ 4
 
0.1%
Other values (5) 11
 
0.3%
Latin
ValueCountFrequency (%)
S 19
35.2%
E 18
33.3%
C 4
 
7.4%
P 3
 
5.6%
c 2
 
3.7%
V 2
 
3.7%
T 1
 
1.9%
K 1
 
1.9%
B 1
 
1.9%
v 1
 
1.9%
Other values (2) 2
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10467
75.0%
ASCII 3496
 
25.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3112
89.0%
, 168
 
4.8%
) 49
 
1.4%
( 49
 
1.4%
1 22
 
0.6%
S 19
 
0.5%
E 18
 
0.5%
2 9
 
0.3%
3 8
 
0.2%
. 5
 
0.1%
Other values (17) 37
 
1.1%
Hangul
ValueCountFrequency (%)
정 742
 
7.1%
보 449
 
4.3%
등 436
 
4.2%
산 404
 
3.9%
반 379
 
3.6%
영 365
 
3.5%
료 342
 
3.3%
험 333
 
3.2%
변 317
 
3.0%
물 317
 
3.0%
Other values (277) 6383
61.0%

Interactions

2023-12-12T14:18:32.028759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:18:31.837704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:18:32.130742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:18:31.928321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:18:35.117870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공사년도증감액최종변경액
공사년도1.0000.0400.116
증감액0.0401.0000.901
최종변경액0.1160.9011.000
2023-12-12T14:18:35.219024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
증감액최종변경액공사년도
증감액1.0000.1020.000
최종변경액0.1021.0000.074
공사년도0.0000.0741.000

Missing values

2023-12-12T14:18:32.275380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:18:32.382509image/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.
2023-12-12T14:18:32.502004image/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

공사년도공사구분설계변경일자증감액최종변경액설계변경사유
02019공사2019-06-11-13628000276683000보험료 정산
12019공사2019-05-154704000290311000현장여건 반영
22019공사2019-06-25-15220800306776000보험료 정산
32019공사2019-05-27-2316000321996800현장여건 반영
42019공사2019-12-20-370270001436273000보험료 등 제경비 정산
52019공사2019-12-0213000001473300000주민건의사항 및 현장여건 반
62019공사2019-07-25-215923801365407620보험료 정산
72019공사2019-06-04-323000001387000000현지여건반영
82019공사2019-07-04589980002173716950물량증감 및 물가변동
92019공사2019-12-24-1074400002066276950보험료 등 정산
공사년도공사구분설계변경일자증감액최종변경액설계변경사유
8992023공사2023-07-17-22210600224670000보험료 등 정산 반영 변경
9002023공사2023-05-02-111000041990000보험료 등 정산 반영 변경
9012023공사2023-06-14<NA>2391312000실정보고 승인사항 반영, 차수간 공정물량 조정
9022023공사2023-06-21<NA>1269663000차수간 흙깍기 발파공법 및 토공 물량 조정
9032023공사2023-05-25-284361081601000보험료 등 정산 반영 변경
9042023공사2023-07-10-11487100134784600보험료 등 정산 반영 변경
9052023공사2023-05-24-122100009534110000차수간 공정계획 조정
9062023공사2023-06-28-418100094498000보험료 등 정산 반영 변경
9072023공사2023-07-28<NA>2550000000차수간 공정계획 조정
9082023공사2023-08-179330000002551000000예산 확보에 따른 시공물량 추가