Overview

Dataset statistics

Number of variables10
Number of observations145
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.0 KiB
Average record size in memory84.9 B

Variable types

Numeric3
Categorical7

Dataset

Description보건교육사 1급 국가시험 응시자의 현황을 분석할 수 있는 정보(연도, 직종, 회차, 성별, 연령대, 응시지역, 졸업여부, 합격여부, 학교소재지)를 개인을 식별할 수 없는 형태로 제공합니다.
URLhttps://www.data.go.kr/data/15083490/fileData.do

Alerts

직종 has constant value ""Constant
연도 is highly overall correlated with 회차 and 2 other fieldsHigh correlation
회차 is highly overall correlated with 연도 and 2 other fieldsHigh correlation
일련번호 is highly overall correlated with 연도 and 2 other fieldsHigh correlation
응시지역 is highly overall correlated with 학교소재지High correlation
졸업여부 is highly overall correlated with 연도 and 2 other fieldsHigh correlation
학교소재지 is highly overall correlated with 응시지역High correlation
일련번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 00:43:17.110337
Analysis finished2023-12-12 00:43:18.404231
Duration1.29 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2017.1724
Minimum2011
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T09:43:18.457291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2011
5-th percentile2011
Q12013
median2018
Q32021
95-th percentile2023
Maximum2023
Range12
Interquartile range (IQR)8

Descriptive statistics

Standard deviation3.9199363
Coefficient of variation (CV)0.0019432827
Kurtosis-1.2258306
Mean2017.1724
Median Absolute Deviation (MAD)3
Skewness-0.25721843
Sum292490
Variance15.3659
MonotonicityIncreasing
2023-12-12T09:43:18.539840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2012 21
14.5%
2019 21
14.5%
2018 18
12.4%
2017 17
11.7%
2021 17
11.7%
2011 14
9.7%
2022 13
9.0%
2023 10
6.9%
2013 6
 
4.1%
2015 3
 
2.1%
Other values (2) 5
 
3.4%
ValueCountFrequency (%)
2011 14
9.7%
2012 21
14.5%
2013 6
 
4.1%
2014 2
 
1.4%
2015 3
 
2.1%
2016 3
 
2.1%
2017 17
11.7%
2018 18
12.4%
2019 21
14.5%
2021 17
11.7%
ValueCountFrequency (%)
2023 10
6.9%
2022 13
9.0%
2021 17
11.7%
2019 21
14.5%
2018 18
12.4%
2017 17
11.7%
2016 3
 
2.1%
2015 3
 
2.1%
2014 2
 
1.4%
2013 6
 
4.1%

직종
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
보건교육사 1급
145 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row보건교육사 1급
2nd row보건교육사 1급
3rd row보건교육사 1급
4th row보건교육사 1급
5th row보건교육사 1급

Common Values

ValueCountFrequency (%)
보건교육사 1급 145
100.0%

Length

2023-12-12T09:43:18.632187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:43:18.707043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
보건교육사 145
50.0%
1급 145
50.0%

회차
Real number (ℝ)

HIGH CORRELATION 

Distinct13
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.6965517
Minimum2
Maximum14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T09:43:18.776114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q15
median10
Q312
95-th percentile14
Maximum14
Range12
Interquartile range (IQR)7

Descriptive statistics

Standard deviation3.9128069
Coefficient of variation (CV)0.44992624
Kurtosis-1.1127568
Mean8.6965517
Median Absolute Deviation (MAD)2
Skewness-0.53118105
Sum1261
Variance15.310057
MonotonicityNot monotonic
2023-12-12T09:43:18.869574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
11 21
14.5%
10 18
12.4%
9 17
11.7%
12 17
11.7%
3 15
10.3%
2 14
9.7%
13 13
9.0%
14 10
6.9%
4 6
 
4.1%
5 6
 
4.1%
Other values (3) 8
 
5.5%
ValueCountFrequency (%)
2 14
9.7%
3 15
10.3%
4 6
 
4.1%
5 6
 
4.1%
6 2
 
1.4%
7 3
 
2.1%
8 3
 
2.1%
9 17
11.7%
10 18
12.4%
11 21
14.5%
ValueCountFrequency (%)
14 10
6.9%
13 13
9.0%
12 17
11.7%
11 21
14.5%
10 18
12.4%
9 17
11.7%
8 3
 
2.1%
7 3
 
2.1%
6 2
 
1.4%
5 6
 
4.1%

일련번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct145
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73
Minimum1
Maximum145
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T09:43:18.975389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.2
Q137
median73
Q3109
95-th percentile137.8
Maximum145
Range144
Interquartile range (IQR)72

Descriptive statistics

Standard deviation42.001984
Coefficient of variation (CV)0.57536964
Kurtosis-1.2
Mean73
Median Absolute Deviation (MAD)36
Skewness0
Sum10585
Variance1764.1667
MonotonicityNot monotonic
2023-12-12T09:43:19.110579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
110 1
 
0.7%
94 1
 
0.7%
95 1
 
0.7%
96 1
 
0.7%
97 1
 
0.7%
98 1
 
0.7%
99 1
 
0.7%
100 1
 
0.7%
101 1
 
0.7%
Other values (135) 135
93.1%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
145 1
0.7%
144 1
0.7%
143 1
0.7%
142 1
0.7%
141 1
0.7%
140 1
0.7%
139 1
0.7%
138 1
0.7%
137 1
0.7%
136 1
0.7%

성별
Categorical

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
113 
32 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
113
77.9%
32
 
22.1%

Length

2023-12-12T09:43:19.237613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:43:19.324442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
113
77.9%
32
 
22.1%

연령대
Categorical

Distinct5
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
30
52 
40
49 
50
28 
20
10 
60

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row30
2nd row40
3rd row40
4th row30
5th row40

Common Values

ValueCountFrequency (%)
30 52
35.9%
40 49
33.8%
50 28
19.3%
20 10
 
6.9%
60 6
 
4.1%

Length

2023-12-12T09:43:19.415952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:43:19.511702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
30 52
35.9%
40 49
33.8%
50 28
19.3%
20 10
 
6.9%
60 6
 
4.1%

응시지역
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
서울특별시
66 
부산광역시
25 
대구광역시
18 
대전광역시
14 
광주광역시
12 

Length

Max length5
Median length5
Mean length4.7931034
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울특별시
2nd row서울특별시
3rd row서울특별시
4th row서울특별시
5th row부산광역시

Common Values

ValueCountFrequency (%)
서울특별시 66
45.5%
부산광역시 25
 
17.2%
대구광역시 18
 
12.4%
대전광역시 14
 
9.7%
광주광역시 12
 
8.3%
전주 10
 
6.9%

Length

2023-12-12T09:43:19.625300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:43:19.742599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 66
45.5%
부산광역시 25
 
17.2%
대구광역시 18
 
12.4%
대전광역시 14
 
9.7%
광주광역시 12
 
8.3%
전주 10
 
6.9%

졸업여부
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
졸업
118 
졸업예정
27 

Length

Max length4
Median length2
Mean length2.3724138
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row졸업
2nd row졸업
3rd row졸업
4th row졸업예정
5th row졸업예정

Common Values

ValueCountFrequency (%)
졸업 118
81.4%
졸업예정 27
 
18.6%

Length

2023-12-12T09:43:19.915352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:43:20.099303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
졸업 118
81.4%
졸업예정 27
 
18.6%

합격여부
Categorical

Distinct4
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
불합격
87 
합격
38 
결시
18 
응시결격
 
2

Length

Max length4
Median length3
Mean length2.6275862
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row불합격
2nd row불합격
3rd row합격
4th row불합격
5th row결시

Common Values

ValueCountFrequency (%)
불합격 87
60.0%
합격 38
26.2%
결시 18
 
12.4%
응시결격 2
 
1.4%

Length

2023-12-12T09:43:20.233898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:43:20.396732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
불합격 87
60.0%
합격 38
26.2%
결시 18
 
12.4%
응시결격 2
 
1.4%

학교소재지
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
서울특별시
44 
기타
31 
광주광역시
10 
대구광역시
경상남도
Other values (9)
42 

Length

Max length5
Median length5
Mean length4.0137931
Min length2

Unique

Unique3 ?
Unique (%)2.1%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시 44
30.3%
기타 31
21.4%
광주광역시 10
 
6.9%
대구광역시 9
 
6.2%
경상남도 9
 
6.2%
경기도 8
 
5.5%
전라북도 8
 
5.5%
충청남도 8
 
5.5%
경상북도 6
 
4.1%
부산광역시 5
 
3.4%
Other values (4) 7
 
4.8%

Length

2023-12-12T09:43:20.554152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울특별시 44
30.3%
기타 31
21.4%
광주광역시 10
 
6.9%
대구광역시 9
 
6.2%
경상남도 9
 
6.2%
경기도 8
 
5.5%
전라북도 8
 
5.5%
충청남도 8
 
5.5%
경상북도 6
 
4.1%
부산광역시 5
 
3.4%
Other values (4) 7
 
4.8%

Interactions

2023-12-12T09:43:17.929118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:43:17.518608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:43:17.711548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:43:18.006631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:43:17.580717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:43:17.775270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:43:18.089296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:43:17.645663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:43:17.839499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:43:20.683650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도회차일련번호성별연령대응시지역졸업여부합격여부학교소재지
연도1.0001.0000.8960.0000.1960.2450.5060.2580.378
회차1.0001.0000.9700.0000.3470.3040.8870.3090.467
일련번호0.8960.9701.0000.0000.3260.4920.8900.2650.604
성별0.0000.0000.0001.0000.2420.3340.0000.1550.417
연령대0.1960.3470.3260.2421.0000.2500.0000.1260.663
응시지역0.2450.3040.4920.3340.2501.0000.4590.1190.871
졸업여부0.5060.8870.8900.0000.0000.4591.0000.2680.477
합격여부0.2580.3090.2650.1550.1260.1190.2681.0000.134
학교소재지0.3780.4670.6040.4170.6630.8710.4770.1341.000
2023-12-12T09:43:20.830070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
응시지역성별합격여부학교소재지졸업여부연령대
응시지역1.0000.2360.0750.6500.3260.171
성별0.2361.0000.1020.3110.0000.292
합격여부0.0750.1021.0000.0690.1770.102
학교소재지0.6500.3110.0691.0000.3570.408
졸업여부0.3260.0000.1770.3571.0000.000
연령대0.1710.2920.1020.4080.0001.000
2023-12-12T09:43:20.948787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도회차일련번호성별연령대응시지역졸업여부합격여부학교소재지
연도1.0000.9990.9930.0660.1320.1670.6070.1960.241
회차0.9991.0000.9940.0000.1390.1480.7020.1850.208
일련번호0.9930.9941.0000.0000.1440.2800.7040.1630.297
성별0.0660.0000.0001.0000.2920.2360.0000.1020.311
연령대0.1320.1390.1440.2921.0000.1710.0000.1020.408
응시지역0.1670.1480.2800.2360.1711.0000.3260.0750.650
졸업여부0.6070.7020.7040.0000.0000.3261.0000.1770.357
합격여부0.1960.1850.1630.1020.1020.0750.1771.0000.069
학교소재지0.2410.2080.2970.3110.4080.6500.3570.0691.000

Missing values

2023-12-12T09:43:18.206708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:43:18.349455image/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

연도직종회차일련번호성별연령대응시지역졸업여부합격여부학교소재지
02011보건교육사 1급2130서울특별시졸업불합격기타
12011보건교육사 1급2240서울특별시졸업불합격기타
22011보건교육사 1급2340서울특별시졸업합격기타
32011보건교육사 1급2430서울특별시졸업예정불합격기타
42011보건교육사 1급2540부산광역시졸업예정결시기타
52011보건교육사 1급2640부산광역시졸업예정불합격기타
62011보건교육사 1급2740부산광역시졸업예정불합격기타
72011보건교육사 1급2830부산광역시졸업예정불합격기타
82011보건교육사 1급2930부산광역시졸업예정불합격기타
92011보건교육사 1급21030부산광역시졸업예정불합격기타
연도직종회차일련번호성별연령대응시지역졸업여부합격여부학교소재지
1352023보건교육사 1급1413640서울특별시졸업결시서울특별시
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