Overview

Dataset statistics

Number of variables6
Number of observations177
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.9 KiB
Average record size in memory51.7 B

Variable types

Categorical2
Text1
Numeric3

Dataset

Description한국사능력검정시험 연도별, 회차별, 급수별 등의 기준에 따라 응시자 수, 합격자 수, 합격률 등의 정보를 제공합니다.
Author교육부 국사편찬위원회
URLhttps://www.data.go.kr/data/3059204/fileData.do

Alerts

응시자수(명) is highly overall correlated with 합격자수(명)High correlation
합격자수(명) is highly overall correlated with 응시자수(명)High correlation
응시자수(명) has unique valuesUnique
합격자수(명) has unique valuesUnique

Reproduction

Analysis started2023-12-12 03:01:10.914683
Analysis finished2023-12-12 03:01:13.150671
Duration2.24 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Categorical

Distinct17
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2014년
12 
2016년
12 
2019년
12 
2010년
12 
2017년
12 
Other values (12)
117 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2006년
2nd row2006년
3rd row2006년
4th row2006년
5th row2007년

Common Values

ValueCountFrequency (%)
2014년 12
 
6.8%
2016년 12
 
6.8%
2019년 12
 
6.8%
2010년 12
 
6.8%
2017년 12
 
6.8%
2018년 12
 
6.8%
2015년 12
 
6.8%
2007년 12
 
6.8%
2013년 12
 
6.8%
2012년 12
 
6.8%
Other values (7) 57
32.2%

Length

2023-12-12T12:01:13.236748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2014년 12
 
6.8%
2015년 12
 
6.8%
2012년 12
 
6.8%
2016년 12
 
6.8%
2007년 12
 
6.8%
2013년 12
 
6.8%
2018년 12
 
6.8%
2017년 12
 
6.8%
2010년 12
 
6.8%
2019년 12
 
6.8%
Other values (7) 57
32.2%

회차
Text

Distinct60
Distinct (%)33.9%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-12T12:01:13.553425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length13.937853
Min length12

Characters and Unicode

Total characters2467
Distinct characters15
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)1.7%

Sample

1st row1회(2006-11-25)
2nd row1회(2006-11-25)
3rd row1회(2006-11-25)
4th row1회(2006-11-25)
5th row2회(2007-5-27)
ValueCountFrequency (%)
3회(2007-10-27 6
 
3.4%
2회(2007-5-27 6
 
3.4%
8회(2010-5-8 4
 
2.3%
1회(2006-11-25 4
 
2.3%
10회(2010-10-23 4
 
2.3%
7회(2009-10-24 4
 
2.3%
5회(2008-10-25 4
 
2.3%
6회(2009-5-23 4
 
2.3%
4회(2008-6-14 4
 
2.3%
9회(2010-8-14 4
 
2.3%
Other values (50) 133
75.1%
2023-12-12T12:01:14.113816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 397
16.1%
- 354
14.3%
1 328
13.3%
0 307
12.4%
회 177
7.2%
( 177
7.2%
) 177
7.2%
5 106
 
4.3%
8 95
 
3.9%
4 90
 
3.6%
Other values (5) 259
10.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1581
64.1%
Dash Punctuation 354
 
14.3%
Other Letter 177
 
7.2%
Open Punctuation 177
 
7.2%
Close Punctuation 177
 
7.2%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 397
25.1%
1 328
20.7%
0 307
19.4%
5 106
 
6.7%
8 95
 
6.0%
4 90
 
5.7%
3 85
 
5.4%
7 66
 
4.2%
6 62
 
3.9%
9 45
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 354
100.0%
Other Letter
ValueCountFrequency (%)
회 177
100.0%
Open Punctuation
ValueCountFrequency (%)
( 177
100.0%
Close Punctuation
ValueCountFrequency (%)
) 177
100.0%
Other Punctuation
ValueCountFrequency (%)
' 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2290
92.8%
Hangul 177
 
7.2%

Most frequent character per script

Common
ValueCountFrequency (%)
2 397
17.3%
- 354
15.5%
1 328
14.3%
0 307
13.4%
( 177
7.7%
) 177
7.7%
5 106
 
4.6%
8 95
 
4.1%
4 90
 
3.9%
3 85
 
3.7%
Other values (4) 174
7.6%
Hangul
ValueCountFrequency (%)
회 177
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2290
92.8%
Hangul 177
 
7.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 397
17.3%
- 354
15.5%
1 328
14.3%
0 307
13.4%
( 177
7.7%
) 177
7.7%
5 106
 
4.6%
8 95
 
4.1%
4 90
 
3.9%
3 85
 
3.7%
Other values (4) 174
7.6%
Hangul
ValueCountFrequency (%)
회 177
100.0%

급수
Categorical

Distinct14
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
고급
38 
초급
38 
중급
31 
심화
14 
기본
11 
Other values (9)
45 

Length

Max length3
Median length2
Mean length2.0847458
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3급
2nd row4급
3rd row5급
4th row6급
5th row1급

Common Values

ValueCountFrequency (%)
고급 38
21.5%
초급 38
21.5%
중급 31
17.5%
심화 14
 
7.9%
기본 11
 
6.2%
3급 10
 
5.6%
4급 10
 
5.6%
고 급 5
 
2.8%
중 급 5
 
2.8%
초 급 5
 
2.8%
Other values (4) 10
 
5.6%

Length

2023-12-12T12:01:14.307103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
고급 38
19.8%
초급 38
19.8%
중급 31
16.1%
급 15
 
7.8%
심화 14
 
7.3%
기본 11
 
5.7%
3급 10
 
5.2%
4급 10
 
5.2%
고 5
 
2.6%
중 5
 
2.6%
Other values (5) 15
 
7.8%

응시자수(명)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct177
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24687.588
Minimum1350
Maximum103213
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-12T12:01:14.481132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1350
5-th percentile3406
Q15816
median12150
Q338625
95-th percentile73822
Maximum103213
Range101863
Interquartile range (IQR)32809

Descriptive statistics

Standard deviation24513.139
Coefficient of variation (CV)0.99293376
Kurtosis0.278829
Mean24687.588
Median Absolute Deviation (MAD)8347
Skewness1.1454053
Sum4369703
Variance6.0089399 × 108
MonotonicityNot monotonic
2023-12-12T12:01:14.690563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8539 1
 
0.6%
6228 1
 
0.6%
66431 1
 
0.6%
36623 1
 
0.6%
9266 1
 
0.6%
49166 1
 
0.6%
21805 1
 
0.6%
4583 1
 
0.6%
67977 1
 
0.6%
33933 1
 
0.6%
Other values (167) 167
94.4%
ValueCountFrequency (%)
1350 1
0.6%
1408 1
0.6%
1477 1
0.6%
1955 1
0.6%
2108 1
0.6%
2304 1
0.6%
2609 1
0.6%
3116 1
0.6%
3118 1
0.6%
3478 1
0.6%
ValueCountFrequency (%)
103213 1
0.6%
97339 1
0.6%
92249 1
0.6%
82898 1
0.6%
76428 1
0.6%
75934 1
0.6%
75429 1
0.6%
74977 1
0.6%
74162 1
0.6%
73737 1
0.6%

합격자수(명)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct177
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14241.169
Minimum336
Maximum76806
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-12T12:01:14.926267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum336
5-th percentile1356.8
Q13284
median5749
Q322553
95-th percentile43740.2
Maximum76806
Range76470
Interquartile range (IQR)19269

Descriptive statistics

Standard deviation14892.161
Coefficient of variation (CV)1.0457119
Kurtosis1.4310326
Mean14241.169
Median Absolute Deviation (MAD)4232
Skewness1.3497489
Sum2520687
Variance2.2177645 × 108
MonotonicityNot monotonic
2023-12-12T12:01:15.153947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3903 1
 
0.6%
4934 1
 
0.6%
46062 1
 
0.6%
23775 1
 
0.6%
7038 1
 
0.6%
27873 1
 
0.6%
12726 1
 
0.6%
3090 1
 
0.6%
49019 1
 
0.6%
19298 1
 
0.6%
Other values (167) 167
94.4%
ValueCountFrequency (%)
336 1
0.6%
375 1
0.6%
667 1
0.6%
862 1
0.6%
935 1
0.6%
1027 1
0.6%
1256 1
0.6%
1260 1
0.6%
1276 1
0.6%
1377 1
0.6%
ValueCountFrequency (%)
76806 1
0.6%
63146 1
0.6%
49019 1
0.6%
47841 1
0.6%
46716 1
0.6%
46689 1
0.6%
46438 1
0.6%
46062 1
0.6%
45417 1
0.6%
43321 1
0.6%

합격률(퍼센트)
Real number (ℝ)

Distinct175
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57.466045
Minimum4.49
Maximum87.25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-12T12:01:15.358542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.49
5-th percentile29.022
Q147.93
median58.27
Q368.76
95-th percentile79.9
Maximum87.25
Range82.76
Interquartile range (IQR)20.83

Descriptive statistics

Standard deviation15.995909
Coefficient of variation (CV)0.2783541
Kurtosis0.65183019
Mean57.466045
Median Absolute Deviation (MAD)10.48
Skewness-0.74263493
Sum10171.49
Variance255.86912
MonotonicityNot monotonic
2023-12-12T12:01:15.557575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
74.84 2
 
1.1%
63.85 2
 
1.1%
45.71 1
 
0.6%
54.34 1
 
0.6%
75.96 1
 
0.6%
56.69 1
 
0.6%
58.36 1
 
0.6%
67.42 1
 
0.6%
72.11 1
 
0.6%
56.87 1
 
0.6%
Other values (165) 165
93.2%
ValueCountFrequency (%)
4.49 1
0.6%
5.21 1
0.6%
17.19 1
0.6%
17.45 1
0.6%
18.55 1
0.6%
19.44 1
0.6%
19.99 1
0.6%
23.81 1
0.6%
27.63 1
0.6%
29.37 1
0.6%
ValueCountFrequency (%)
87.25 1
0.6%
86.98 1
0.6%
85.05 1
0.6%
85.04 1
0.6%
83.26 1
0.6%
82.88 1
0.6%
81.58 1
0.6%
81.01 1
0.6%
80.62 1
0.6%
79.72 1
0.6%

Interactions

2023-12-12T12:01:12.122149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:01:11.333686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:01:11.710063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:01:12.258758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:01:11.447459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:01:11.849207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:01:12.409148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:01:11.583457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:01:11.995097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:01:15.676562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도회차급수응시자수(명)합격자수(명)합격률(퍼센트)
연도1.0001.0000.7620.5210.4860.383
회차1.0001.0000.0000.7310.6790.000
급수0.7620.0001.0000.6570.6200.621
응시자수(명)0.5210.7310.6571.0000.8810.114
합격자수(명)0.4860.6790.6200.8811.0000.093
합격률(퍼센트)0.3830.0000.6210.1140.0931.000
2023-12-12T12:01:15.812935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도급수
연도1.0000.376
급수0.3761.000
2023-12-12T12:01:15.931008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
응시자수(명)합격자수(명)합격률(퍼센트)연도급수
응시자수(명)1.0000.932-0.1270.2280.332
합격자수(명)0.9321.0000.1830.2130.315
합격률(퍼센트)-0.1270.1831.0000.1540.303
연도0.2280.2130.1541.0000.376
급수0.3320.3150.3030.3761.000

Missing values

2023-12-12T12:01:12.558975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:01:13.086656image/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

연도회차급수응시자수(명)합격자수(명)합격률(퍼센트)
02006년1회(2006-11-25)3급8539390345.71
12006년1회(2006-11-25)4급3971126031.73
22006년1회(2006-11-25)5급1477125685.04
32006년1회(2006-11-25)6급1408102772.94
42007년2회(2007-5-27)1급195533617.19
52007년2회(2007-5-27)2급535793517.45
62007년2회(2007-5-27)3급6922264938.27
72007년2회(2007-5-27)4급4568155934.13
82007년2회(2007-5-27)5급3118265285.05
92007년2회(2007-5-27)6급2304200486.98
연도회차급수응시자수(명)합격자수(명)합격률(퍼센트)
1672021년55회(2021-9-11)심화681953850756.47
1682021년55회(2021-9-11)기본6109349557.21
1692021년56회('21-10-23)심화754294668961.9
1702022년57회(2022-2-12)심화973396314664.87
1712022년57회(2022-2-12)기본12751574945.09
1722022년58회(2022-4-10)심화698873456649.46
1732022년58회(2022-4-10)기본7624425155.76
1742022년59회(2022-6-11)심화692563199246.19
1752022년60회(2022-8-6)심화759344185555.12
1762022년60회(2022-8-6)기본7659340844.5