Overview

Dataset statistics

Number of variables10
Number of observations4420
Missing cells696
Missing cells (%)1.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory380.0 KiB
Average record size in memory88.0 B

Variable types

Numeric8
Categorical1
Text1

Dataset

Description보건의료인국가시험의 문항 분석자료(연도, 직종, 회차, 과목명, 평균점수(표준편차), 평균난이도(표준편차), 평균변별도(표준편차))를 제공합니다.
URLhttps://www.data.go.kr/data/15053154/fileData.do

Alerts

회차 is highly overall correlated with 직종High correlation
과목별평균점수 is highly overall correlated with 과목별평균표준편차High correlation
과목별평균표준편차 is highly overall correlated with 과목별평균점수High correlation
직종 is highly overall correlated with 회차High correlation
평균난이도 has 174 (3.9%) missing valuesMissing
난이도표준편차 has 174 (3.9%) missing valuesMissing
평균변별도 has 174 (3.9%) missing valuesMissing
변별도표준편차 has 174 (3.9%) missing valuesMissing

Reproduction

Analysis started2023-12-11 23:26:55.024048
Analysis finished2023-12-11 23:27:02.303620
Duration7.28 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

Distinct24
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2011.7846
Minimum2000
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size39.0 KiB
2023-12-12T08:27:02.359293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2000
5-th percentile2001
Q12006
median2012
Q32018
95-th percentile2022
Maximum2023
Range23
Interquartile range (IQR)12

Descriptive statistics

Standard deviation6.7850146
Coefficient of variation (CV)0.0033726347
Kurtosis-1.158309
Mean2011.7846
Median Absolute Deviation (MAD)6
Skewness-0.10124891
Sum8892088
Variance46.036423
MonotonicityIncreasing
2023-12-12T08:27:02.461866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
2018 222
 
5.0%
2019 218
 
4.9%
2012 216
 
4.9%
2013 212
 
4.8%
2020 205
 
4.6%
2010 203
 
4.6%
2021 201
 
4.5%
2011 200
 
4.5%
2022 199
 
4.5%
2015 198
 
4.5%
Other values (14) 2346
53.1%
ValueCountFrequency (%)
2000 169
3.8%
2001 187
4.2%
2002 175
4.0%
2003 170
3.8%
2004 153
3.5%
2005 163
3.7%
2006 162
3.7%
2007 162
3.7%
2008 162
3.7%
2009 184
4.2%
ValueCountFrequency (%)
2023 123
2.8%
2022 199
4.5%
2021 201
4.5%
2020 205
4.6%
2019 218
4.9%
2018 222
5.0%
2017 154
3.5%
2016 188
4.3%
2015 198
4.5%
2014 194
4.4%

직종
Categorical

HIGH CORRELATION 

Distinct46
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size34.7 KiB
치과의사
 
312
약사(4년제)
 
304
한의사
 
284
의사
 
204
간호사
 
192
Other values (41)
3124 

Length

Max length38
Median length36
Mean length32.855882
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
치과의사 312
 
7.1%
약사(4년제) 304
 
6.9%
한의사 284
 
6.4%
의사 204
 
4.6%
간호사 192
 
4.3%
치과기공사 192
 
4.3%
의지보조기기사 184
 
4.2%
영양사 181
 
4.1%
임상병리사 171
 
3.9%
방사선사 171
 
3.9%
Other values (36) 2225
50.3%

Length

2023-12-12T08:27:02.573933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
치과의사 312
 
6.4%
약사(4년제 304
 
6.2%
한의사 284
 
5.8%
보건교육사 207
 
4.2%
의사 204
 
4.2%
장애인재활상담사 196
 
4.0%
간호사 192
 
3.9%
치과기공사 192
 
3.9%
의지보조기기사 184
 
3.7%
2급 182
 
3.7%
Other values (31) 2655
54.1%

회차
Real number (ℝ)

HIGH CORRELATION 

Distinct87
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.532127
Minimum1
Maximum87
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size39.0 KiB
2023-12-12T08:27:02.688584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q116
median34
Q355
95-th percentile73
Maximum87
Range86
Interquartile range (IQR)39

Descriptive statistics

Standard deviation22.466532
Coefficient of variation (CV)0.63228785
Kurtosis-1.0236303
Mean35.532127
Median Absolute Deviation (MAD)19
Skewness0.22947986
Sum157052
Variance504.74506
MonotonicityNot monotonic
2023-12-12T08:27:02.801563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 102
 
2.3%
1 99
 
2.2%
3 92
 
2.1%
27 92
 
2.1%
28 92
 
2.1%
32 85
 
1.9%
30 82
 
1.9%
42 81
 
1.8%
29 80
 
1.8%
33 78
 
1.8%
Other values (77) 3537
80.0%
ValueCountFrequency (%)
1 99
2.2%
2 102
2.3%
3 92
2.1%
4 72
1.6%
5 72
1.6%
6 74
1.7%
7 76
1.7%
8 64
1.4%
9 65
1.5%
10 65
1.5%
ValueCountFrequency (%)
87 5
 
0.1%
86 6
 
0.1%
85 7
 
0.2%
84 7
 
0.2%
83 7
 
0.2%
82 7
 
0.2%
81 7
 
0.2%
80 8
 
0.2%
79 8
 
0.2%
78 20
0.5%

과목명
Text

Distinct252
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size34.7 KiB
2023-12-12T08:27:03.050827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length6.1830317
Min length2

Characters and Unicode

Total characters27329
Distinct characters170
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)0.2%

Sample

1st row구강내과학
2nd row소아치과학
3rd row치과교정학
4th row구강악안면방사선학
5th row구강보건학
ValueCountFrequency (%)
개론 225
 
3.8%
실기시험 221
 
3.8%
실기 213
 
3.6%
의료관계법규 193
 
3.3%
법규 153
 
2.6%
및 144
 
2.5%
개요 101
 
1.7%
공중보건학 99
 
1.7%
보건의약관계 95
 
1.6%
기초 90
 
1.5%
Other values (250) 4321
73.8%
2023-12-12T08:27:03.450476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 2666
 
9.8%
1435
 
5.3%
의 1017
 
3.7%
기 998
 
3.7%
보 787
 
2.9%
관 710
 
2.6%
론 706
 
2.6%
치 654
 
2.4%
생 608
 
2.2%
건 577
 
2.1%
Other values (160) 17171
62.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25028
91.6%
Space Separator 1435
 
5.3%
Decimal Number 298
 
1.1%
Uppercase Letter 159
 
0.6%
Other Punctuation 127
 
0.5%
Close Punctuation 126
 
0.5%
Open Punctuation 126
 
0.5%
Letter Number 30
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 2666
 
10.7%
의 1017
 
4.1%
기 998
 
4.0%
보 787
 
3.1%
관 710
 
2.8%
론 706
 
2.8%
치 654
 
2.6%
생 608
 
2.4%
건 577
 
2.3%
법 559
 
2.2%
Other values (143) 15746
62.9%
Decimal Number
ValueCountFrequency (%)
2 105
35.2%
1 93
31.2%
3 32
 
10.7%
4 23
 
7.7%
5 23
 
7.7%
6 9
 
3.0%
7 8
 
2.7%
0 5
 
1.7%
Uppercase Letter
ValueCountFrequency (%)
R 126
79.2%
I 33
 
20.8%
Other Punctuation
ValueCountFrequency (%)
· 113
89.0%
, 14
 
11.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 15
50.0%
Ⅱ 15
50.0%
Space Separator
ValueCountFrequency (%)
1435
100.0%
Close Punctuation
ValueCountFrequency (%)
) 126
100.0%
Open Punctuation
ValueCountFrequency (%)
( 126
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25028
91.6%
Common 2112
 
7.7%
Latin 189
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 2666
 
10.7%
의 1017
 
4.1%
기 998
 
4.0%
보 787
 
3.1%
관 710
 
2.8%
론 706
 
2.8%
치 654
 
2.6%
생 608
 
2.4%
건 577
 
2.3%
법 559
 
2.2%
Other values (143) 15746
62.9%
Common
ValueCountFrequency (%)
1435
67.9%
) 126
 
6.0%
( 126
 
6.0%
· 113
 
5.4%
2 105
 
5.0%
1 93
 
4.4%
3 32
 
1.5%
4 23
 
1.1%
5 23
 
1.1%
, 14
 
0.7%
Other values (3) 22
 
1.0%
Latin
ValueCountFrequency (%)
R 126
66.7%
I 33
 
17.5%
Ⅰ 15
 
7.9%
Ⅱ 15
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25028
91.6%
ASCII 2158
 
7.9%
None 113
 
0.4%
Number Forms 30
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 2666
 
10.7%
의 1017
 
4.1%
기 998
 
4.0%
보 787
 
3.1%
관 710
 
2.8%
론 706
 
2.8%
치 654
 
2.6%
생 608
 
2.4%
건 577
 
2.3%
법 559
 
2.2%
Other values (143) 15746
62.9%
ASCII
ValueCountFrequency (%)
1435
66.5%
) 126
 
5.8%
R 126
 
5.8%
( 126
 
5.8%
2 105
 
4.9%
1 93
 
4.3%
I 33
 
1.5%
3 32
 
1.5%
4 23
 
1.1%
5 23
 
1.1%
Other values (4) 36
 
1.7%
None
ValueCountFrequency (%)
· 113
100.0%
Number Forms
ValueCountFrequency (%)
Ⅰ 15
50.0%
Ⅱ 15
50.0%

과목별평균점수
Real number (ℝ)

HIGH CORRELATION 

Distinct2841
Distinct (%)64.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.241104
Minimum0.36
Maximum501
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size39.0 KiB
2023-12-12T08:27:03.587118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.36
5-th percentile8.4185
Q114.245
median20.765
Q333.4525
95-th percentile74.5865
Maximum501
Range500.64
Interquartile range (IQR)19.2075

Descriptive statistics

Standard deviation29.360381
Coefficient of variation (CV)1.0040791
Kurtosis57.558588
Mean29.241104
Median Absolute Deviation (MAD)8.225
Skewness5.7747446
Sum129245.68
Variance862.03197
MonotonicityNot monotonic
2023-12-12T08:27:03.716093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11.79 9
 
0.2%
17.72 7
 
0.2%
16.83 7
 
0.2%
15.7 7
 
0.2%
10.54 6
 
0.1%
12.26 6
 
0.1%
11.8 6
 
0.1%
15.69 6
 
0.1%
11.54 6
 
0.1%
15.68 6
 
0.1%
Other values (2831) 4354
98.5%
ValueCountFrequency (%)
0.36 1
< 0.1%
0.37 1
< 0.1%
0.46 1
< 0.1%
0.49 1
< 0.1%
0.57 1
< 0.1%
0.7 1
< 0.1%
0.78 2
< 0.1%
0.83 2
< 0.1%
0.84 1
< 0.1%
0.92 2
< 0.1%
ValueCountFrequency (%)
501.0 1
< 0.1%
432.0 1
< 0.1%
423.25 1
< 0.1%
409.0 1
< 0.1%
371.2 1
< 0.1%
338.28 1
< 0.1%
303.2 1
< 0.1%
269.95 1
< 0.1%
264.36 1
< 0.1%
263.6 1
< 0.1%

과목별평균표준편차
Real number (ℝ)

HIGH CORRELATION 

Distinct1246
Distinct (%)28.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.6088281
Minimum0
Maximum81.67
Zeros8
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size39.0 KiB
2023-12-12T08:27:03.846960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.6795
Q12.83
median4.06
Q36.41
95-th percentile13.7205
Maximum81.67
Range81.67
Interquartile range (IQR)3.58

Descriptive statistics

Standard deviation5.4544624
Coefficient of variation (CV)0.97247809
Kurtosis39.03628
Mean5.6088281
Median Absolute Deviation (MAD)1.56
Skewness4.9069584
Sum24791.02
Variance29.75116
MonotonicityNot monotonic
2023-12-12T08:27:03.984061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.71 19
 
0.4%
3.53 19
 
0.4%
3.25 18
 
0.4%
2.96 18
 
0.4%
2.81 17
 
0.4%
2.64 17
 
0.4%
3.04 16
 
0.4%
3.27 16
 
0.4%
2.67 16
 
0.4%
3.41 15
 
0.3%
Other values (1236) 4249
96.1%
ValueCountFrequency (%)
0.0 8
0.2%
0.18 1
 
< 0.1%
0.21 2
 
< 0.1%
0.23 1
 
< 0.1%
0.32 2
 
< 0.1%
0.35 2
 
< 0.1%
0.37 1
 
< 0.1%
0.39 2
 
< 0.1%
0.41 1
 
< 0.1%
0.44 1
 
< 0.1%
ValueCountFrequency (%)
81.67 1
< 0.1%
80.04 1
< 0.1%
66.75 1
< 0.1%
64.01 1
< 0.1%
61.32 1
< 0.1%
48.47 1
< 0.1%
46.95 1
< 0.1%
45.75 1
< 0.1%
45.68 1
< 0.1%
42.81 1
< 0.1%

평균난이도
Real number (ℝ)

MISSING 

Distinct2505
Distinct (%)59.0%
Missing174
Missing (%)3.9%
Infinite0
Infinite (%)0.0%
Mean68.959833
Minimum9.75
Maximum98.71
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size39.0 KiB
2023-12-12T08:27:04.114029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9.75
5-th percentile50.6925
Q163.0525
median70.02
Q376.035
95-th percentile82.89
Maximum98.71
Range88.96
Interquartile range (IQR)12.9825

Descriptive statistics

Standard deviation9.9519567
Coefficient of variation (CV)0.14431527
Kurtosis0.89558298
Mean68.959833
Median Absolute Deviation (MAD)6.41
Skewness-0.64067167
Sum292803.45
Variance99.041441
MonotonicityNot monotonic
2023-12-12T08:27:04.260212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
68.14 7
 
0.2%
72.99 7
 
0.2%
72.19 6
 
0.1%
72.95 6
 
0.1%
76.41 6
 
0.1%
70.44 6
 
0.1%
75.45 6
 
0.1%
68.0 6
 
0.1%
74.84 6
 
0.1%
73.48 6
 
0.1%
Other values (2495) 4184
94.7%
(Missing) 174
 
3.9%
ValueCountFrequency (%)
9.75 1
< 0.1%
18.55 1
< 0.1%
23.57 1
< 0.1%
24.55 1
< 0.1%
28.79 1
< 0.1%
32.84 1
< 0.1%
33.53 1
< 0.1%
34.22 1
< 0.1%
35.05 1
< 0.1%
35.19 1
< 0.1%
ValueCountFrequency (%)
98.71 1
< 0.1%
98.13 1
< 0.1%
97.87 1
< 0.1%
97.18 1
< 0.1%
96.67 1
< 0.1%
96.16 1
< 0.1%
95.66 1
< 0.1%
95.34 1
< 0.1%
95.29 1
< 0.1%
95.06 1
< 0.1%

난이도표준편차
Real number (ℝ)

MISSING 

Distinct1555
Distinct (%)36.6%
Missing174
Missing (%)3.9%
Infinite0
Infinite (%)0.0%
Mean19.111314
Minimum0
Maximum38.05
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size39.0 KiB
2023-12-12T08:27:04.422651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile12.215
Q116.5925
median19.29
Q321.8175
95-th percentile25.6
Maximum38.05
Range38.05
Interquartile range (IQR)5.225

Descriptive statistics

Standard deviation4.3955138
Coefficient of variation (CV)0.22999537
Kurtosis2.2146912
Mean19.111314
Median Absolute Deviation (MAD)2.61
Skewness-0.4458208
Sum81146.64
Variance19.320541
MonotonicityNot monotonic
2023-12-12T08:27:04.562083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19.01 11
 
0.2%
18.04 11
 
0.2%
18.26 10
 
0.2%
19.88 10
 
0.2%
21.79 10
 
0.2%
20.01 10
 
0.2%
20.89 10
 
0.2%
19.8 9
 
0.2%
21.66 9
 
0.2%
22.13 9
 
0.2%
Other values (1545) 4147
93.8%
(Missing) 174
 
3.9%
ValueCountFrequency (%)
0.0 2
< 0.1%
0.03 1
< 0.1%
0.08 1
< 0.1%
0.19 1
< 0.1%
0.44 1
< 0.1%
0.47 1
< 0.1%
0.54 1
< 0.1%
0.55 1
< 0.1%
0.62 1
< 0.1%
0.72 1
< 0.1%
ValueCountFrequency (%)
38.05 1
< 0.1%
38.0 1
< 0.1%
37.82 1
< 0.1%
36.94 1
< 0.1%
36.09 1
< 0.1%
35.71 1
< 0.1%
35.46 1
< 0.1%
35.22 1
< 0.1%
35.02 1
< 0.1%
34.47 1
< 0.1%

평균변별도
Real number (ℝ)

MISSING 

Distinct69
Distinct (%)1.6%
Missing174
Missing (%)3.9%
Infinite0
Infinite (%)0.0%
Mean0.26336552
Minimum-0.11
Maximum0.85
Zeros13
Zeros (%)0.3%
Negative1
Negative (%)< 0.1%
Memory size39.0 KiB
2023-12-12T08:27:04.722332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-0.11
5-th percentile0.14
Q10.2
median0.26
Q30.32
95-th percentile0.4
Maximum0.85
Range0.96
Interquartile range (IQR)0.12

Descriptive statistics

Standard deviation0.085210758
Coefficient of variation (CV)0.32354561
Kurtosis1.679357
Mean0.26336552
Median Absolute Deviation (MAD)0.06
Skewness0.55040793
Sum1118.25
Variance0.0072608732
MonotonicityNot monotonic
2023-12-12T08:27:04.844817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.27 205
 
4.6%
0.2 201
 
4.5%
0.24 201
 
4.5%
0.28 187
 
4.2%
0.26 187
 
4.2%
0.25 185
 
4.2%
0.19 185
 
4.2%
0.21 184
 
4.2%
0.23 180
 
4.1%
0.22 180
 
4.1%
Other values (59) 2351
53.2%
ValueCountFrequency (%)
-0.11 1
 
< 0.1%
0.0 13
0.3%
0.02 4
 
0.1%
0.03 2
 
< 0.1%
0.04 3
 
0.1%
0.05 2
 
< 0.1%
0.06 4
 
0.1%
0.07 2
 
< 0.1%
0.08 6
0.1%
0.09 9
0.2%
ValueCountFrequency (%)
0.85 1
< 0.1%
0.75 1
< 0.1%
0.73 1
< 0.1%
0.69 1
< 0.1%
0.67 1
< 0.1%
0.64 1
< 0.1%
0.63 1
< 0.1%
0.61 1
< 0.1%
0.6 2
< 0.1%
0.59 2
< 0.1%

변별도표준편차
Real number (ℝ)

MISSING 

Distinct58
Distinct (%)1.4%
Missing174
Missing (%)3.9%
Infinite0
Infinite (%)0.0%
Mean0.14151201
Minimum0
Maximum0.64
Zeros17
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size39.0 KiB
2023-12-12T08:27:04.980835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.09
Q10.11
median0.13
Q30.15
95-th percentile0.22
Maximum0.64
Range0.64
Interquartile range (IQR)0.04

Descriptive statistics

Standard deviation0.055785414
Coefficient of variation (CV)0.39420975
Kurtosis19.41647
Mean0.14151201
Median Absolute Deviation (MAD)0.02
Skewness3.2838411
Sum600.86
Variance0.0031120125
MonotonicityNot monotonic
2023-12-12T08:27:05.117523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.12 597
13.5%
0.13 559
12.6%
0.11 494
11.2%
0.14 482
10.9%
0.15 414
9.4%
0.1 332
7.5%
0.16 272
6.2%
0.17 179
 
4.0%
0.09 158
 
3.6%
0.18 134
 
3.0%
Other values (48) 625
14.1%
(Missing) 174
 
3.9%
ValueCountFrequency (%)
0.0 17
 
0.4%
0.01 10
 
0.2%
0.02 11
 
0.2%
0.03 8
 
0.2%
0.04 4
 
0.1%
0.05 8
 
0.2%
0.06 14
 
0.3%
0.07 28
 
0.6%
0.08 57
 
1.3%
0.09 158
3.6%
ValueCountFrequency (%)
0.64 1
< 0.1%
0.63 2
< 0.1%
0.61 2
< 0.1%
0.6 2
< 0.1%
0.59 1
< 0.1%
0.58 2
< 0.1%
0.57 2
< 0.1%
0.53 1
< 0.1%
0.5 1
< 0.1%
0.49 1
< 0.1%

Interactions

2023-12-12T08:27:01.210003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:56.283907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:57.033294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:57.730537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:58.442015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:59.142137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:59.741233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:27:00.379703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:27:01.296690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:56.379283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:57.132057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:57.811519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:58.525284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:59.212396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:59.820347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:27:00.447454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:27:01.376987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:56.480969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:57.214788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:57.888126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:58.605619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:59.277860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:59.889557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:27:00.720546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:27:01.470221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:56.569220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:57.305408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:57.993510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:58.690539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:59.363502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:59.967362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:27:00.807697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:27:01.563299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:56.677167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:57.396680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:58.090626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:58.781336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:59.458928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:27:00.061133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:27:00.882728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:27:01.678119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:56.761811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:57.467483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:58.178958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:58.879183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:59.520105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:27:00.136461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:27:00.949966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:27:01.788226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:56.855447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:57.551852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:58.271532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:58.971547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:59.594682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:27:00.218592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:27:01.026772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:27:01.879714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:56.938579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:57.629063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:58.347281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:59.053211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:59.665360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:27:00.294107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:27:01.103312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:27:05.436566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도직종회차과목별평균점수과목별평균표준편차평균난이도난이도표준편차평균변별도변별도표준편차
연도1.0000.5250.5800.0620.0360.1750.1910.1550.247
직종0.5251.0000.8810.8390.7410.6190.6210.6750.782
회차0.5800.8811.0000.2850.2320.4110.3530.4660.484
과목별평균점수0.0620.8390.2851.0000.7860.2800.1670.0000.368
과목별평균표준편차0.0360.7410.2320.7861.0000.2450.1710.2880.458
평균난이도0.1750.6190.4110.2800.2451.0000.6680.5380.533
난이도표준편차0.1910.6210.3530.1670.1710.6681.0000.6100.599
평균변별도0.1550.6750.4660.0000.2880.5380.6101.0000.633
변별도표준편차0.2470.7820.4840.3680.4580.5330.5990.6331.000
2023-12-12T08:27:05.535693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도회차과목별평균점수과목별평균표준편차평균난이도난이도표준편차평균변별도변별도표준편차직종
연도1.0000.0390.019-0.0400.101-0.0350.0000.0800.211
회차0.0391.0000.064-0.1080.335-0.072-0.260-0.4520.544
과목별평균점수0.0190.0641.0000.8310.219-0.012-0.0080.0480.473
과목별평균표준편차-0.040-0.1080.8311.000-0.140-0.0370.3690.2210.370
평균난이도0.1010.3350.219-0.1401.000-0.492-0.316-0.3990.263
난이도표준편차-0.035-0.072-0.012-0.037-0.4921.000-0.3230.1320.264
평균변별도0.000-0.260-0.0080.369-0.316-0.3231.0000.3860.300
변별도표준편차0.080-0.4520.0480.221-0.3990.1320.3861.0000.404
직종0.2110.5440.4730.3700.2630.2640.3000.4041.000

Missing values

2023-12-12T08:27:02.020618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:27:02.148213image/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.
2023-12-12T08:27:02.252741image/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

연도직종회차과목명과목별평균점수과목별평균표준편차평균난이도난이도표준편차평균변별도변별도표준편차
02000치과의사52구강내과학10.492.9569.8713.850.410.15
12000치과의사52소아치과학15.724.1360.3718.040.330.15
22000치과의사52치과교정학24.445.4674.0317.560.350.14
32000치과의사52구강악안면방사선학14.733.8856.5522.870.310.15
42000치과의사52구강보건학10.492.7652.3422.950.240.14
52000치과의사52보건의약관계 법규14.082.3870.2922.490.170.1
62000치과의사52치주과학16.964.6965.1414.740.390.12
72000치과의사52구강병리학8.252.454.9925.680.30.16
82000치과의사52치과보존학25.165.462.6620.60.290.15
92000치과의사52구강악안면외과학24.625.0561.4323.050.270.15
연도직종회차과목명과목별평균점수과목별평균표준편차평균난이도난이도표준편차평균변별도변별도표준편차
441020232급 장애인재활상담사7재활상담8.511.8274.6213.720.330.15
441120232급 장애인재활상담사7재활행정9.141.9674.5217.150.30.12
441220232급 장애인재활상담사7직업평가12.922.6874.4522.840.280.12
441320232급 장애인재활상담사7재활정책7.931.6677.616.560.280.14
441420232급 장애인재활상담사7직업재활개론21.253.9471.7520.230.310.14
44152023약사(6년제)74생명약학74.7110.4374.4322.530.210.12
44162023약사(6년제)74임상·실무약학244.486.4870.4721.510.20.12
44172023약사(6년제)74산업약학63.858.8370.8622.890.190.1
44182023약사(6년제)74보건·의약 관계 법규15.72.2978.5716.860.170.11
44192023약사(6년제)74임상·실무약학158.588.8376.0419.540.220.09