Overview

Dataset statistics

Number of variables5
Number of observations225
Missing cells3
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.6 KiB
Average record size in memory43.6 B

Variable types

Numeric3
Categorical1
Text1

Dataset

Description연도별로 시행된 대학수학능력시험(본수능) 등급구분과 표준점수에 대한 통계 정보를 제공합니다. (이전 데이터는 하단의 주기성 과거 데이터를 확인하시기 바랍니다.)
Author한국교육과정평가원
URLhttps://www.data.go.kr/data/15080193/fileData.do

Reproduction

Analysis started2023-12-12 03:28:13.610097
Analysis finished2023-12-12 03:28:15.518787
Duration1.91 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

등급
Real number (ℝ)

Distinct9
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-12T12:28:15.604475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5
Q37
95-th percentile9
Maximum9
Range8
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.5877458
Coefficient of variation (CV)0.51754917
Kurtosis-1.230629
Mean5
Median Absolute Deviation (MAD)2
Skewness0
Sum1125
Variance6.6964286
MonotonicityNot monotonic
2023-12-12T12:28:15.796807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 25
11.1%
2 25
11.1%
3 25
11.1%
4 25
11.1%
5 25
11.1%
6 25
11.1%
7 25
11.1%
8 25
11.1%
9 25
11.1%
ValueCountFrequency (%)
1 25
11.1%
2 25
11.1%
3 25
11.1%
4 25
11.1%
5 25
11.1%
6 25
11.1%
7 25
11.1%
8 25
11.1%
9 25
11.1%
ValueCountFrequency (%)
9 25
11.1%
8 25
11.1%
7 25
11.1%
6 25
11.1%
5 25
11.1%
4 25
11.1%
3 25
11.1%
2 25
11.1%
1 25
11.1%

과목
Categorical

Distinct25
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
국어
 
9
수학
 
9
생활과 윤리
 
9
윤리와 사상
 
9
한국지리
 
9
Other values (20)
180 

Length

Max length11
Median length9
Mean length5.12
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
국어 9
 
4.0%
수학 9
 
4.0%
생활과 윤리 9
 
4.0%
윤리와 사상 9
 
4.0%
한국지리 9
 
4.0%
세계지리 9
 
4.0%
동아시아사 9
 
4.0%
세계사 9
 
4.0%
경제 9
 
4.0%
정치와 법 9
 
4.0%
Other values (15) 135
60.0%

Length

2023-12-12T12:28:16.019544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
ⅰ 36
 
9.3%
ⅱ 36
 
9.3%
생명과학 18
 
4.7%
지구과학 18
 
4.7%
물리학 18
 
4.7%
경제 18
 
4.7%
기초 18
 
4.7%
화학 18
 
4.7%
기술 9
 
2.3%
공업 9
 
2.3%
Other values (21) 189
48.8%

구분 점수
Text

Distinct57
Distinct (%)25.4%
Missing1
Missing (%)0.4%
Memory size1.9 KiB
2023-12-12T12:28:16.343860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.2589286
Min length2

Characters and Unicode

Total characters506
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)9.8%

Sample

1st row126
2nd row122
3rd row117
4th row110
5th row99
ValueCountFrequency (%)
37 11
 
4.9%
59 11
 
4.9%
63 11
 
4.9%
41 10
 
4.5%
53 10
 
4.5%
46 9
 
4.0%
64 8
 
3.6%
34미만 7
 
3.1%
34 7
 
3.1%
47 7
 
3.1%
Other values (47) 133
59.4%
2023-12-12T12:28:16.878917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 99
19.6%
6 79
15.6%
4 77
15.2%
5 69
13.6%
7 33
 
6.5%
1 27
 
5.3%
미 25
 
4.9%
만 25
 
4.9%
8 21
 
4.2%
9 18
 
3.6%
Other values (2) 33
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 456
90.1%
Other Letter 50
 
9.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 99
21.7%
6 79
17.3%
4 77
16.9%
5 69
15.1%
7 33
 
7.2%
1 27
 
5.9%
8 21
 
4.6%
9 18
 
3.9%
0 17
 
3.7%
2 16
 
3.5%
Other Letter
ValueCountFrequency (%)
미 25
50.0%
만 25
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 456
90.1%
Hangul 50
 
9.9%

Most frequent character per script

Common
ValueCountFrequency (%)
3 99
21.7%
6 79
17.3%
4 77
16.9%
5 69
15.1%
7 33
 
7.2%
1 27
 
5.9%
8 21
 
4.6%
9 18
 
3.9%
0 17
 
3.7%
2 16
 
3.5%
Hangul
ValueCountFrequency (%)
미 25
50.0%
만 25
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 456
90.1%
Hangul 50
 
9.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 99
21.7%
6 79
17.3%
4 77
16.9%
5 69
15.1%
7 33
 
7.2%
1 27
 
5.9%
8 21
 
4.6%
9 18
 
3.9%
0 17
 
3.7%
2 16
 
3.5%
Hangul
ValueCountFrequency (%)
미 25
50.0%
만 25
50.0%

인원(명)
Real number (ℝ)

Distinct209
Distinct (%)93.3%
Missing1
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean7805.9732
Minimum1
Maximum92636
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-12T12:28:17.078446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile15.95
Q1237.75
median1497
Q37329
95-th percentile31317.25
Maximum92636
Range92635
Interquartile range (IQR)7091.25

Descriptive statistics

Standard deviation15408.016
Coefficient of variation (CV)1.9738751
Kurtosis12.498162
Mean7805.9732
Median Absolute Deviation (MAD)1460.5
Skewness3.3516429
Sum1748538
Variance2.3740697 × 108
MonotonicityNot monotonic
2023-12-12T12:28:17.284076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
247 3
 
1.3%
2 3
 
1.3%
190 2
 
0.9%
117 2
 
0.9%
10 2
 
0.9%
48 2
 
0.9%
200 2
 
0.9%
6 2
 
0.9%
800 2
 
0.9%
71 2
 
0.9%
Other values (199) 202
89.8%
ValueCountFrequency (%)
1 1
 
0.4%
2 3
1.3%
3 2
0.9%
4 1
 
0.4%
6 2
0.9%
10 2
0.9%
14 1
 
0.4%
27 1
 
0.4%
29 1
 
0.4%
31 1
 
0.4%
ValueCountFrequency (%)
92636 1
0.4%
89600 1
0.4%
76497 1
0.4%
73879 1
0.4%
73072 1
0.4%
72544 1
0.4%
53106 1
0.4%
52708 1
0.4%
51869 1
0.4%
43429 1
0.4%

비율(퍼센트)
Real number (ℝ)

Distinct203
Distinct (%)90.6%
Missing1
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean11.16067
Minimum1.76
Maximum26.09
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-12T12:28:17.471928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.76
5-th percentile2.9345
Q16.1375
median10.91
Q316.5525
95-th percentile20.743
Maximum26.09
Range24.33
Interquartile range (IQR)10.415

Descriptive statistics

Standard deviation5.893098
Coefficient of variation (CV)0.5280237
Kurtosis-1.1357221
Mean11.16067
Median Absolute Deviation (MAD)5.04
Skewness0.2437813
Sum2499.99
Variance34.728604
MonotonicityNot monotonic
2023-12-12T12:28:18.069729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.7 4
 
1.8%
11.7 2
 
0.9%
18.0 2
 
0.9%
5.88 2
 
0.9%
18.06 2
 
0.9%
6.73 2
 
0.9%
4.78 2
 
0.9%
3.61 2
 
0.9%
12.98 2
 
0.9%
16.73 2
 
0.9%
Other values (193) 202
89.8%
ValueCountFrequency (%)
1.76 1
0.4%
1.84 1
0.4%
2.01 1
0.4%
2.44 1
0.4%
2.6 1
0.4%
2.64 1
0.4%
2.7 1
0.4%
2.77 1
0.4%
2.83 1
0.4%
2.87 1
0.4%
ValueCountFrequency (%)
26.09 1
0.4%
23.49 1
0.4%
22.97 1
0.4%
21.83 1
0.4%
21.77 1
0.4%
21.46 1
0.4%
21.39 1
0.4%
21.34 1
0.4%
20.89 1
0.4%
20.84 1
0.4%

Interactions

2023-12-12T12:28:14.664373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:28:13.876263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:28:14.271866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:28:14.816681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:28:14.012157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:28:14.424890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:28:14.936852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:28:14.140122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:28:14.554591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:28:18.206732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등급과목구분 점수인원(명)비율(퍼센트)
등급1.0000.0000.9950.3260.851
과목0.0001.0000.0000.6220.000
구분 점수0.9950.0001.0000.9690.930
인원(명)0.3260.6220.9691.0000.386
비율(퍼센트)0.8510.0000.9300.3861.000
2023-12-12T12:28:18.325518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등급인원(명)비율(퍼센트)과목
등급1.000-0.035-0.1090.000
인원(명)-0.0351.0000.2620.281
비율(퍼센트)-0.1090.2621.0000.000
과목0.0000.2810.0001.000

Missing values

2023-12-12T12:28:15.124342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:28:15.285709image/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.
2023-12-12T12:28:15.433940image/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

등급과목구분 점수인원(명)비율(퍼센트)
01국어126198584.45
12국어122311606.99
23국어1175186911.63
34국어1107649717.15
45국어999263620.77
56국어857387916.56
67국어705310611.91
78국어58311236.98
89국어58미만159153.57
91수학133225715.26
등급과목구분 점수인원(명)비율(퍼센트)
2159수산·해운 산업 기초<NA><NA><NA>
2161인간발달68514.72
2172인간발달65898.24
2183인간발달6011010.19
2194인간발달5120018.52
2205인간발달4621519.91
2216인간발달4216715.46
2227인간발달3814213.15
2238인간발달36676.2
2249인간발달36미만393.61