Overview

Dataset statistics

Number of variables11
Number of observations903
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory79.5 KiB
Average record size in memory90.1 B

Variable types

Numeric2
Categorical4
DateTime4
Text1

Dataset

Description2024년 1월 26일 기준 한국데이터산업진흥원에서 운영 중인 데이터 아키텍처, 데이터 분석, SQL 등 데이터 자격검정 시험 정보(시험일정, 장소 등)를 제공합니다.해당 데이터가 보유한 컬럼은 다음과 같습니다.칼럼명 : 순번, 시험명, 시험구분, 회차, 시험일, 시험시작시간, 접수시작일, 접수마감일, 시험장소, 합격자발표일, 시험유형
Author한국데이터산업진흥원
URLhttps://www.data.go.kr/data/15062838/fileData.do

Alerts

순번 is highly overall correlated with 회차High correlation
회차 is highly overall correlated with 순번High correlation
시험명 is highly overall correlated with 시험유형High correlation
시험유형 is highly overall correlated with 시험명High correlation
시험구분 is highly imbalanced (77.5%)Imbalance
시험시작시간 is highly imbalanced (62.7%)Imbalance
시험유형 is highly imbalanced (72.9%)Imbalance
순번 has unique valuesUnique

Reproduction

Analysis started2024-03-14 20:50:11.392817
Analysis finished2024-03-14 20:50:13.778560
Duration2.39 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct903
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean452
Minimum1
Maximum903
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.1 KiB
2024-03-15T05:50:13.911998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile46.1
Q1226.5
median452
Q3677.5
95-th percentile857.9
Maximum903
Range902
Interquartile range (IQR)451

Descriptive statistics

Standard deviation260.81794
Coefficient of variation (CV)0.57703085
Kurtosis-1.2
Mean452
Median Absolute Deviation (MAD)226
Skewness0
Sum408156
Variance68026
MonotonicityStrictly increasing
2024-03-15T05:50:14.240260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
622 1
 
0.1%
596 1
 
0.1%
597 1
 
0.1%
598 1
 
0.1%
599 1
 
0.1%
600 1
 
0.1%
601 1
 
0.1%
602 1
 
0.1%
603 1
 
0.1%
Other values (893) 893
98.9%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
903 1
0.1%
902 1
0.1%
901 1
0.1%
900 1
0.1%
899 1
0.1%
898 1
0.1%
897 1
0.1%
896 1
0.1%
895 1
0.1%
894 1
0.1%

시험명
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
SQLD(국가공인 SQL 개발자)
168 
SQLP(국가공인 SQL 전문가)
157 
ADsP(국가공인 데이터분석 준전문가)
157 
DAsP(데이터아키텍처 준전문가)
140 
DAP(국가공인 데이터아키텍처 전문가)
125 
Other values (11)
156 

Length

Max length21
Median length18
Mean length18.925803
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDAsP(데이터아키텍처 준전문가)
2nd rowDAP(국가공인 데이터아키텍처 전문가)
3rd rowDAsP(데이터아키텍처 준전문가)
4th rowDAP(국가공인 데이터아키텍처 전문가)
5th rowDAsP(데이터아키텍처 준전문가)

Common Values

ValueCountFrequency (%)
SQLD(국가공인 SQL 개발자) 168
18.6%
SQLP(국가공인 SQL 전문가) 157
17.4%
ADsP(국가공인 데이터분석 준전문가) 157
17.4%
DAsP(데이터아키텍처 준전문가) 140
15.5%
DAP(국가공인 데이터아키텍처 전문가) 125
13.8%
ADP(국가공인 데이터분석 전문가) 122
13.5%
국가기술 빅데이터분석기사 12
 
1.3%
데이터분석 준전문가(ADsP) 4
 
0.4%
SQL 개발자(SQLD) 4
 
0.4%
데이터분석 전문가(ADP)-필기 2
 
0.2%
Other values (6) 12
 
1.3%

Length

2024-03-15T05:50:14.656178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전문가 404
15.9%
sql 331
13.1%
준전문가 297
11.7%
데이터분석 285
11.3%
sqld(국가공인 168
6.6%
개발자 168
6.6%
sqlp(국가공인 157
 
6.2%
adsp(국가공인 157
 
6.2%
dasp(데이터아키텍처 140
 
5.5%
데이터아키텍처 129
 
5.1%
Other values (15) 297
11.7%

시험구분
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
일반검정
854 
특별검정
 
30
전환검정
 
19

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반검정 854
94.6%
특별검정 30
 
3.3%
전환검정 19
 
2.1%

Length

2024-03-15T05:50:14.977602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:50:15.139596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반검정 854
94.6%
특별검정 30
 
3.3%
전환검정 19
 
2.1%

회차
Real number (ℝ)

HIGH CORRELATION 

Distinct62
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.183832
Minimum1
Maximum62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.1 KiB
2024-03-15T05:50:15.370564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q110
median20
Q331
95-th percentile45.9
Maximum62
Range61
Interquartile range (IQR)21

Descriptive statistics

Standard deviation13.340645
Coefficient of variation (CV)0.62975602
Kurtosis-0.33845049
Mean21.183832
Median Absolute Deviation (MAD)10
Skewness0.51893484
Sum19129
Variance177.97282
MonotonicityNot monotonic
2024-03-15T05:50:15.620655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19 28
 
3.1%
5 27
 
3.0%
15 26
 
2.9%
6 26
 
2.9%
7 25
 
2.8%
17 25
 
2.8%
10 25
 
2.8%
32 24
 
2.7%
23 24
 
2.7%
20 24
 
2.7%
Other values (52) 649
71.9%
ValueCountFrequency (%)
1 19
2.1%
2 24
2.7%
3 22
2.4%
4 22
2.4%
5 27
3.0%
6 26
2.9%
7 25
2.8%
8 23
2.5%
9 24
2.7%
10 25
2.8%
ValueCountFrequency (%)
62 1
 
0.1%
61 1
 
0.1%
60 1
 
0.1%
59 1
 
0.1%
58 1
 
0.1%
57 2
0.2%
56 2
0.2%
55 3
0.3%
54 3
0.3%
53 3
0.3%

시험일
Date

Distinct221
Distinct (%)24.5%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
Minimum2006-03-25 00:00:00
Maximum2024-11-30 00:00:00
2024-03-15T05:50:15.938750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:50:16.307650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

시험시작시간
Categorical

IMBALANCE 

Distinct11
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
13:00
604 
10:00
223 
09:00
62 
18:00
 
3
18:30
 
2
Other values (6)
 
9

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row09:00
2nd row09:00
3rd row09:00
4th row09:00
5th row09:00

Common Values

ValueCountFrequency (%)
13:00 604
66.9%
10:00 223
 
24.7%
09:00 62
 
6.9%
18:00 3
 
0.3%
18:30 2
 
0.2%
11:00 2
 
0.2%
15:00 2
 
0.2%
14:00 2
 
0.2%
17:00 1
 
0.1%
19:00 1
 
0.1%

Length

2024-03-15T05:50:16.588865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
13:00 604
66.9%
10:00 223
 
24.7%
09:00 62
 
6.9%
18:00 3
 
0.3%
18:30 2
 
0.2%
11:00 2
 
0.2%
15:00 2
 
0.2%
14:00 2
 
0.2%
17:00 1
 
0.1%
19:00 1
 
0.1%

접수시작일
Date

Distinct211
Distinct (%)23.4%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
Minimum2005-12-26 00:00:00
Maximum2024-10-28 00:00:00
2024-03-15T05:50:16.957300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:50:17.520093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

접수마감일
Date

Distinct224
Distinct (%)24.8%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
Minimum2006-01-25 00:00:00
Maximum2024-11-01 00:00:00
2024-03-15T05:50:17.886041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:50:18.124215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

시험장소
Text

Distinct879
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
2024-03-15T05:50:19.027126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length108
Median length62
Mean length29.90144
Min length15

Characters and Unicode

Total characters27001
Distinct characters230
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

Unique855 ?
Unique (%)94.7%

Sample

1st row제1회 DAsP : (서울)연세대학교 법과대학
2nd row제1회 DAP : (서울)연세대학교 법과대학
3rd row제2회 DAsP : (서울)연세대학교 법과대학
4th row제2회 DAP : (서울)연세대학교 법과대학
5th row제3회 DAsP : (서울)연세대학교 법과대학
ValueCountFrequency (%)
419
 
7.9%
서울 191
 
3.6%
부산 160
 
3.0%
sqld 151
 
2.8%
sqlp 143
 
2.7%
adsp 142
 
2.7%
동국대학교 139
 
2.6%
dasp 124
 
2.3%
대전 122
 
2.3%
문화관 116
 
2.2%
Other values (440) 3604
67.9%
2024-03-15T05:50:20.447193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4449
 
16.5%
대 1010
 
3.7%
) 964
 
3.6%
( 963
 
3.6%
회 962
 
3.6%
제 944
 
3.5%
: 766
 
2.8%
2 760
 
2.8%
학 748
 
2.8%
D 737
 
2.7%
Other values (220) 14698
54.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12510
46.3%
Space Separator 4449
 
16.5%
Decimal Number 3360
 
12.4%
Uppercase Letter 3293
 
12.2%
Close Punctuation 1004
 
3.7%
Open Punctuation 1004
 
3.7%
Other Punctuation 933
 
3.5%
Lowercase Letter 301
 
1.1%
Dash Punctuation 89
 
0.3%
Math Symbol 58
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 1010
 
8.1%
회 962
 
7.7%
제 944
 
7.5%
학 748
 
6.0%
교 555
 
4.4%
관 515
 
4.1%
전 377
 
3.0%
층 360
 
2.9%
호 276
 
2.2%
서 263
 
2.1%
Other values (181) 6500
52.0%
Uppercase Letter
ValueCountFrequency (%)
D 737
22.4%
P 715
21.7%
A 620
18.8%
S 368
11.2%
L 365
11.1%
Q 365
11.1%
B 47
 
1.4%
C 15
 
0.5%
T 15
 
0.5%
F 14
 
0.4%
Other values (6) 32
 
1.0%
Decimal Number
ValueCountFrequency (%)
2 760
22.6%
1 660
19.6%
3 520
15.5%
0 327
9.7%
4 297
 
8.8%
5 263
 
7.8%
8 172
 
5.1%
9 141
 
4.2%
6 112
 
3.3%
7 108
 
3.2%
Other Punctuation
ValueCountFrequency (%)
: 766
82.1%
, 151
 
16.2%
/ 15
 
1.6%
. 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 964
96.0%
] 40
 
4.0%
Open Punctuation
ValueCountFrequency (%)
( 963
95.9%
[ 41
 
4.1%
Math Symbol
ValueCountFrequency (%)
~ 57
98.3%
+ 1
 
1.7%
Space Separator
ValueCountFrequency (%)
4449
100.0%
Lowercase Letter
ValueCountFrequency (%)
s 301
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 89
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12510
46.3%
Common 10897
40.4%
Latin 3594
 
13.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 1010
 
8.1%
회 962
 
7.7%
제 944
 
7.5%
학 748
 
6.0%
교 555
 
4.4%
관 515
 
4.1%
전 377
 
3.0%
층 360
 
2.9%
호 276
 
2.2%
서 263
 
2.1%
Other values (181) 6500
52.0%
Common
ValueCountFrequency (%)
4449
40.8%
) 964
 
8.8%
( 963
 
8.8%
: 766
 
7.0%
2 760
 
7.0%
1 660
 
6.1%
3 520
 
4.8%
0 327
 
3.0%
4 297
 
2.7%
5 263
 
2.4%
Other values (12) 928
 
8.5%
Latin
ValueCountFrequency (%)
D 737
20.5%
P 715
19.9%
A 620
17.3%
S 368
10.2%
L 365
10.2%
Q 365
10.2%
s 301
8.4%
B 47
 
1.3%
C 15
 
0.4%
T 15
 
0.4%
Other values (7) 46
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14491
53.7%
Hangul 12510
46.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4449
30.7%
) 964
 
6.7%
( 963
 
6.6%
: 766
 
5.3%
2 760
 
5.2%
D 737
 
5.1%
P 715
 
4.9%
1 660
 
4.6%
A 620
 
4.3%
3 520
 
3.6%
Other values (29) 3337
23.0%
Hangul
ValueCountFrequency (%)
대 1010
 
8.1%
회 962
 
7.7%
제 944
 
7.5%
학 748
 
6.0%
교 555
 
4.4%
관 515
 
4.1%
전 377
 
3.0%
층 360
 
2.9%
호 276
 
2.2%
서 263
 
2.1%
Other values (181) 6500
52.0%

합격자발표일
Date

Distinct221
Distinct (%)24.5%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
Minimum2006-04-25 00:00:00
Maximum2024-12-20 00:00:00
2024-03-15T05:50:20.802939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:50:21.062819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

시험유형
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
필기
861 
실기
 
42

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
필기 861
95.3%
실기 42
 
4.7%

Length

2024-03-15T05:50:21.284722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:50:21.543428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
필기 861
95.3%
실기 42
 
4.7%

Interactions

2024-03-15T05:50:12.530865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:50:12.032316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:50:12.825328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:50:12.279983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T05:50:21.723793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시험명시험구분회차시험시작시간시험유형
순번1.0000.4850.4710.7710.6400.342
시험명0.4851.0000.4510.6780.3870.710
시험구분0.4710.4511.0000.3840.6140.019
회차0.7710.6780.3841.0000.4690.105
시험시작시간0.6400.3870.6140.4691.0000.016
시험유형0.3420.7100.0190.1050.0161.000
2024-03-15T05:50:22.006928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시험구분시험시작시간시험명시험유형
시험구분1.0000.4460.2750.032
시험시작시간0.4461.0000.1560.015
시험명0.2750.1561.0000.565
시험유형0.0320.0150.5651.000
2024-03-15T05:50:22.278258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번회차시험명시험구분시험시작시간시험유형
순번1.0000.6440.2120.3200.3370.261
회차0.6441.0000.3440.2490.2200.080
시험명0.2120.3441.0000.2750.1560.565
시험구분0.3200.2490.2751.0000.4460.032
시험시작시간0.3370.2200.1560.4461.0000.015
시험유형0.2610.0800.5650.0320.0151.000

Missing values

2024-03-15T05:50:13.222853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T05:50:13.674141image/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

순번시험명시험구분회차시험일시험시작시간접수시작일접수마감일시험장소합격자발표일시험유형
01DAsP(데이터아키텍처 준전문가)일반검정12006-03-2509:002005-12-262006-01-25제1회 DAsP : (서울)연세대학교 법과대학2006-04-25필기
12DAP(국가공인 데이터아키텍처 전문가)일반검정12006-03-2509:002005-12-262006-01-25제1회 DAP : (서울)연세대학교 법과대학2006-04-25필기
23DAsP(데이터아키텍처 준전문가)일반검정22006-07-1509:002006-03-262006-05-15제2회 DAsP : (서울)연세대학교 법과대학2006-08-15필기
34DAP(국가공인 데이터아키텍처 전문가)일반검정22006-07-1509:002006-03-262006-05-15제2회 DAP : (서울)연세대학교 법과대학2006-08-15필기
45DAsP(데이터아키텍처 준전문가)일반검정32006-11-1109:002006-07-162006-09-11제3회 DAsP : (서울)연세대학교 법과대학2006-12-11필기
56DAP(국가공인 데이터아키텍처 전문가)일반검정32006-11-1109:002006-07-162006-09-11제3회 DAP : (서울)연세대학교 법과대학2006-12-11필기
67DAP(국가공인 데이터아키텍처 전문가)일반검정42007-03-1709:002006-11-122007-01-17제4회 DAP : (서울)연세대학교 법과대학2007-04-17필기
78DAsP(데이터아키텍처 준전문가)일반검정42007-03-1709:002006-11-122007-01-17제4회 DAsP : 동국대학교 사회과학관(동국관) 4층2007-04-17필기
89DAsP(데이터아키텍처 준전문가)일반검정52007-07-1409:002007-03-182007-05-14제5회 DAsP : (부산) 부경대학교 종합강의동2007-08-14필기
910DAsP(데이터아키텍처 준전문가)일반검정52007-07-1409:002007-03-182007-05-14제5회 DAsP : (서울) 동국대학교 법학관(만해관)2층2007-08-14필기
순번시험명시험구분회차시험일시험시작시간접수시작일접수마감일시험장소합격자발표일시험유형
893894데이터분석 준전문가(ADsP)일반검정422024-08-1010:002024-07-012024-07-05제42회 데이터분석 준전문가(ADsP)2024-09-06필기
894895SQL 전문가(SQLP)일반검정512024-08-2410:002024-07-222024-07-26제51회 SQL 전문가(SQLP)2024-09-27필기
895896SQL 개발자(SQLD)일반검정542024-08-2410:002024-07-222024-07-26제54회 SQL 개발자(SQLD)2024-09-20필기
896897빅데이터분석기사-필기일반검정92024-09-0710:002024-08-052024-08-09제9회 빅데이터분석기사-필기2024-09-27필기
897898데이터아키텍처 전문가(DAP)일반검정622024-09-2810:002024-08-262024-08-30제62회 데이터아키텍처 전문가(DAP)2024-11-01필기
898899데이터아키텍처 준전문가(DAsP)일반검정572024-09-2810:002024-08-262024-08-30제57회 데이터아키텍처 준전문가(DAsP)2024-10-25필기
899900데이터 분석 전문가(ADP)-실기일반검정332024-10-1210:002024-09-092024-09-13제33회 데이터 분석 전문가(ADP)-실기2024-11-15실기
900901데이터분석 준전문가(ADsP)일반검정432024-11-0310:002024-09-302024-10-04제43회 데이터분석 준전문가(ADsP)2024-11-29필기
901902SQL 개발자(SQLD)일반검정552024-11-1710:002024-10-142024-10-18제55회 SQL 개발자(SQLD)2024-12-13필기
902903빅데이터분석기사-실기일반검정92024-11-3010:002024-10-282024-11-01제9회 빅데이터분석기사-실기2024-12-20실기