Overview

Dataset statistics

Number of variables15
Number of observations7055
Missing cells751
Missing cells (%)0.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory895.8 KiB
Average record size in memory130.0 B

Variable types

Numeric7
Categorical5
Text3

Dataset

Description중장기개방계획에따른 경상남도 경남도립남해대학 데이터자료입니다.(과목학년, 과목코드, 수강반, 수강반, 요일, 시작교시, 종료교시, 이수구분, 교원구분)
Author경상남도
URLhttps://www.data.go.kr/data/15067565/fileData.do

Alerts

과목전공코드 has constant value ""Constant
년도 is highly overall correlated with 이수구분High correlation
시작교시 is highly overall correlated with 종료교시High correlation
종료교시 is highly overall correlated with 시작교시High correlation
이수구분 is highly overall correlated with 년도High correlation
강의실 has 699 (9.9%) missing valuesMissing

Reproduction

Analysis started2023-12-12 18:58:58.439056
Analysis finished2023-12-12 18:59:10.394367
Duration11.96 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년도
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2010.7453
Minimum2001
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size62.1 KiB
2023-12-13T03:59:10.498328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2001
5-th percentile2002
Q12005
median2012
Q32016
95-th percentile2019
Maximum2020
Range19
Interquartile range (IQR)11

Descriptive statistics

Standard deviation6.0061787
Coefficient of variation (CV)0.002987041
Kurtosis-1.5140509
Mean2010.7453
Median Absolute Deviation (MAD)6
Skewness-0.087780821
Sum14185808
Variance36.074182
MonotonicityNot monotonic
2023-12-13T03:59:10.693551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
2002 717
 
10.2%
2004 611
 
8.7%
2014 591
 
8.4%
2016 560
 
7.9%
2015 526
 
7.5%
2017 479
 
6.8%
2018 452
 
6.4%
2005 405
 
5.7%
2006 404
 
5.7%
2019 384
 
5.4%
Other values (10) 1926
27.3%
ValueCountFrequency (%)
2001 3
 
< 0.1%
2002 717
10.2%
2003 348
4.9%
2004 611
8.7%
2005 405
5.7%
2006 404
5.7%
2007 343
4.9%
2008 125
 
1.8%
2009 202
 
2.9%
2010 163
 
2.3%
ValueCountFrequency (%)
2020 237
3.4%
2019 384
5.4%
2018 452
6.4%
2017 479
6.8%
2016 560
7.9%
2015 526
7.5%
2014 591
8.4%
2013 291
4.1%
2012 9
 
0.1%
2011 205
 
2.9%

학기
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.2 KiB
1
4100 
2
2955 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 4100
58.1%
2 2955
41.9%

Length

2023-12-13T03:59:10.898835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:59:11.067968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 4100
58.1%
2 2955
41.9%

과목계열코드
Real number (ℝ)

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.0100638
Minimum1
Maximum98
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size62.1 KiB
2023-12-13T03:59:11.214845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median4
Q37
95-th percentile11
Maximum98
Range97
Interquartile range (IQR)4

Descriptive statistics

Standard deviation11.40981
Coefficient of variation (CV)1.8984507
Kurtosis56.346346
Mean6.0100638
Median Absolute Deviation (MAD)2
Skewness7.4175618
Sum42401
Variance130.18377
MonotonicityNot monotonic
2023-12-13T03:59:11.383164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
7 1101
15.6%
4 1076
15.3%
3 1073
15.2%
1 971
13.8%
6 815
11.6%
5 722
10.2%
2 579
8.2%
11 323
 
4.6%
97 94
 
1.3%
12 78
 
1.1%
Other values (6) 223
 
3.2%
ValueCountFrequency (%)
1 971
13.8%
2 579
8.2%
3 1073
15.2%
4 1076
15.3%
5 722
10.2%
6 815
11.6%
7 1101
15.6%
8 69
 
1.0%
9 71
 
1.0%
10 40
 
0.6%
ValueCountFrequency (%)
98 9
 
0.1%
97 94
 
1.3%
14 20
 
0.3%
13 14
 
0.2%
12 78
 
1.1%
11 323
 
4.6%
10 40
 
0.6%
9 71
 
1.0%
8 69
 
1.0%
7 1101
15.6%

과목전공코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.2 KiB
0
7055 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 7055
100.0%

Length

2023-12-13T03:59:11.589856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:59:11.741699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 7055
100.0%

과목학년
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.2 KiB
1
4082 
2
2902 
4
 
41
3
 
30

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 4082
57.9%
2 2902
41.1%
4 41
 
0.6%
3 30
 
0.4%

Length

2023-12-13T03:59:11.906017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:59:12.097154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 4082
57.9%
2 2902
41.1%
4 41
 
0.6%
3 30
 
0.4%
Distinct2450
Distinct (%)34.7%
Missing0
Missing (%)0.0%
Memory size55.2 KiB
2023-12-13T03:59:12.530707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.9995748
Min length5

Characters and Unicode

Total characters42327
Distinct characters15
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique890 ?
Unique (%)12.6%

Sample

1st row10622
2nd row10988
3rd rowB50005
4th row11239
5th rowC10001
ValueCountFrequency (%)
c30003 26
 
0.4%
c70024 24
 
0.3%
c30001 24
 
0.3%
c70037 23
 
0.3%
c70040 22
 
0.3%
c40017 21
 
0.3%
c70041 20
 
0.3%
d70001 18
 
0.3%
c10016 18
 
0.3%
c30027 18
 
0.3%
Other values (2440) 6841
97.0%
2023-12-13T03:59:13.241607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13522
31.9%
C 5278
 
12.5%
1 4933
 
11.7%
2 3292
 
7.8%
3 2666
 
6.3%
4 2472
 
5.8%
7 2228
 
5.3%
5 2049
 
4.8%
6 1851
 
4.4%
9 1189
 
2.8%
Other values (5) 2847
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 35275
83.3%
Uppercase Letter 7052
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13522
38.3%
1 4933
 
14.0%
2 3292
 
9.3%
3 2666
 
7.6%
4 2472
 
7.0%
7 2228
 
6.3%
5 2049
 
5.8%
6 1851
 
5.2%
9 1189
 
3.4%
8 1073
 
3.0%
Uppercase Letter
ValueCountFrequency (%)
C 5278
74.8%
A 902
 
12.8%
N 441
 
6.3%
B 356
 
5.0%
D 75
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
Common 35275
83.3%
Latin 7052
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13522
38.3%
1 4933
 
14.0%
2 3292
 
9.3%
3 2666
 
7.6%
4 2472
 
7.0%
7 2228
 
6.3%
5 2049
 
5.8%
6 1851
 
5.2%
9 1189
 
3.4%
8 1073
 
3.0%
Latin
ValueCountFrequency (%)
C 5278
74.8%
A 902
 
12.8%
N 441
 
6.3%
B 356
 
5.0%
D 75
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42327
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13522
31.9%
C 5278
 
12.5%
1 4933
 
11.7%
2 3292
 
7.8%
3 2666
 
6.3%
4 2472
 
5.8%
7 2228
 
5.3%
5 2049
 
4.8%
6 1851
 
4.4%
9 1189
 
2.8%
Other values (5) 2847
 
6.7%

수강반
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.2 KiB
A
4782 
B
2231 
C
 
42

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
A 4782
67.8%
B 2231
31.6%
C 42
 
0.6%

Length

2023-12-13T03:59:13.511632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:59:13.684700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
a 4782
67.8%
b 2231
31.6%
c 42
 
0.6%

요일
Real number (ℝ)

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.8223955
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size62.1 KiB
2023-12-13T03:59:13.924803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum6
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.3496086
Coefficient of variation (CV)0.47817842
Kurtosis-1.2081204
Mean2.8223955
Median Absolute Deviation (MAD)1
Skewness0.12381308
Sum19912
Variance1.8214434
MonotonicityNot monotonic
2023-12-13T03:59:14.132071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2 1629
23.1%
4 1548
21.9%
1 1529
21.7%
3 1407
19.9%
5 940
13.3%
6 2
 
< 0.1%
ValueCountFrequency (%)
1 1529
21.7%
2 1629
23.1%
3 1407
19.9%
4 1548
21.9%
5 940
13.3%
6 2
 
< 0.1%
ValueCountFrequency (%)
6 2
 
< 0.1%
5 940
13.3%
4 1548
21.9%
3 1407
19.9%
2 1629
23.1%
1 1529
21.7%

시작교시
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.3153792
Minimum1
Maximum15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size62.1 KiB
2023-12-13T03:59:14.322935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median5
Q36
95-th percentile8
Maximum15
Range14
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.6862512
Coefficient of variation (CV)0.62248325
Kurtosis-0.83041497
Mean4.3153792
Median Absolute Deviation (MAD)3
Skewness0.30151887
Sum30445
Variance7.2159458
MonotonicityNot monotonic
2023-12-13T03:59:14.509307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
1 1630
23.1%
6 1278
18.1%
5 863
12.2%
3 828
11.7%
2 812
11.5%
8 812
11.5%
7 421
 
6.0%
9 168
 
2.4%
4 131
 
1.9%
10 63
 
0.9%
Other values (5) 49
 
0.7%
ValueCountFrequency (%)
1 1630
23.1%
2 812
11.5%
3 828
11.7%
4 131
 
1.9%
5 863
12.2%
6 1278
18.1%
7 421
 
6.0%
8 812
11.5%
9 168
 
2.4%
10 63
 
0.9%
ValueCountFrequency (%)
15 1
 
< 0.1%
14 3
 
< 0.1%
13 31
 
0.4%
12 1
 
< 0.1%
11 13
 
0.2%
10 63
 
0.9%
9 168
 
2.4%
8 812
11.5%
7 421
 
6.0%
6 1278
18.1%

종료교시
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)0.2%
Missing44
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean5.4912281
Minimum1
Maximum15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size62.1 KiB
2023-12-13T03:59:14.721709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median6
Q38
95-th percentile9
Maximum15
Range14
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.6541548
Coefficient of variation (CV)0.48334449
Kurtosis-0.63472512
Mean5.4912281
Median Absolute Deviation (MAD)2
Skewness0.30096137
Sum38499
Variance7.0445379
MonotonicityNot monotonic
2023-12-13T03:59:14.924385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
3 1190
16.9%
4 1163
16.5%
7 1159
16.4%
9 986
14.0%
2 795
11.3%
8 643
9.1%
6 561
8.0%
5 159
 
2.3%
1 159
 
2.3%
10 106
 
1.5%
Other values (5) 90
 
1.3%
(Missing) 44
 
0.6%
ValueCountFrequency (%)
1 159
 
2.3%
2 795
11.3%
3 1190
16.9%
4 1163
16.5%
5 159
 
2.3%
6 561
8.0%
7 1159
16.4%
8 643
9.1%
9 986
14.0%
10 106
 
1.5%
ValueCountFrequency (%)
15 27
 
0.4%
14 7
 
0.1%
13 9
 
0.1%
12 39
 
0.6%
11 8
 
0.1%
10 106
 
1.5%
9 986
14.0%
8 643
9.1%
7 1159
16.4%
6 561
8.0%

이수구분
Real number (ℝ)

HIGH CORRELATION 

Distinct30
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.721049
Minimum1
Maximum60
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size62.1 KiB
2023-12-13T03:59:15.162196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q17
median7
Q322
95-th percentile60
Maximum60
Range59
Interquartile range (IQR)15

Descriptive statistics

Standard deviation18.675368
Coefficient of variation (CV)1.1879212
Kurtosis1.026647
Mean15.721049
Median Absolute Deviation (MAD)3
Skewness1.6027163
Sum110912
Variance348.76935
MonotonicityNot monotonic
2023-12-13T03:59:15.378545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
7 3194
45.3%
3 500
 
7.1%
1 439
 
6.2%
60 430
 
6.1%
23 391
 
5.5%
2 350
 
5.0%
4 300
 
4.3%
59 291
 
4.1%
22 210
 
3.0%
11 170
 
2.4%
Other values (20) 780
 
11.1%
ValueCountFrequency (%)
1 439
 
6.2%
2 350
 
5.0%
3 500
 
7.1%
4 300
 
4.3%
5 85
 
1.2%
7 3194
45.3%
9 6
 
0.1%
11 170
 
2.4%
12 4
 
0.1%
13 20
 
0.3%
ValueCountFrequency (%)
60 430
6.1%
59 291
4.1%
58 32
 
0.5%
57 50
 
0.7%
56 14
 
0.2%
54 7
 
0.1%
53 109
 
1.5%
52 68
 
1.0%
51 49
 
0.7%
29 47
 
0.7%

교원구분
Real number (ℝ)

Distinct7
Distinct (%)0.1%
Missing8
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean2.5986945
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size62.1 KiB
2023-12-13T03:59:15.609376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q33
95-th percentile7
Maximum8
Range7
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.6850812
Coefficient of variation (CV)0.64843376
Kurtosis1.4776508
Mean2.5986945
Median Absolute Deviation (MAD)1
Skewness1.2812213
Sum18313
Variance2.8394987
MonotonicityNot monotonic
2023-12-13T03:59:15.813291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
3 2900
41.1%
1 2578
36.5%
2 577
 
8.2%
7 453
 
6.4%
5 286
 
4.1%
4 186
 
2.6%
8 67
 
0.9%
(Missing) 8
 
0.1%
ValueCountFrequency (%)
1 2578
36.5%
2 577
 
8.2%
3 2900
41.1%
4 186
 
2.6%
5 286
 
4.1%
7 453
 
6.4%
8 67
 
0.9%
ValueCountFrequency (%)
8 67
 
0.9%
7 453
 
6.4%
5 286
 
4.1%
4 186
 
2.6%
3 2900
41.1%
2 577
 
8.2%
1 2578
36.5%

강의동
Categorical

Distinct20
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size55.2 KiB
02
2041 
03
1579 
04
1013 
01
875 
<NA>
780 
Other values (15)
767 

Length

Max length4
Median length2
Mean length2.146988
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row01
2nd row01
3rd row02
4th row03
5th row02

Common Values

ValueCountFrequency (%)
02 2041
28.9%
03 1579
22.4%
04 1013
14.4%
01 875
12.4%
<NA> 780
 
11.1%
3 581
 
8.2%
4 74
 
1.0%
1305 19
 
0.3%
1303 18
 
0.3%
1201 15
 
0.2%
Other values (10) 60
 
0.9%

Length

2023-12-13T03:59:16.544760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
02 2041
28.9%
03 1579
22.4%
04 1013
14.4%
01 875
12.4%
na 780
 
11.1%
3 581
 
8.2%
4 74
 
1.0%
1305 19
 
0.3%
1303 18
 
0.3%
1201 15
 
0.2%
Other values (9) 59
 
0.8%

강의실
Text

MISSING 

Distinct101
Distinct (%)1.6%
Missing699
Missing (%)9.9%
Memory size55.2 KiB
2023-12-13T03:59:16.982605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.8588735
Min length1

Characters and Unicode

Total characters24527
Distinct characters47
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)0.1%

Sample

1st row101
2nd row102
3rd row201
4th row301
5th row201
ValueCountFrequency (%)
2205 233
 
3.7%
1301 231
 
3.6%
4313 227
 
3.6%
2302 190
 
3.0%
1307 188
 
3.0%
4307 185
 
2.9%
2315 177
 
2.8%
2203 177
 
2.8%
4314 172
 
2.7%
pc실 170
 
2.7%
Other values (90) 4405
69.3%
2023-12-13T03:59:17.650907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 5405
22.0%
0 4259
17.4%
1 4059
16.5%
2 3673
15.0%
4 2644
10.8%
5 809
 
3.3%
7 756
 
3.1%
9 336
 
1.4%
P 192
 
0.8%
C 176
 
0.7%
Other values (37) 2218
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 22096
90.1%
Other Letter 1444
 
5.9%
Uppercase Letter 970
 
4.0%
Other Punctuation 16
 
0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
P 192
19.8%
C 176
18.1%
E 90
9.3%
M 66
 
6.8%
A 62
 
6.4%
O 57
 
5.9%
N 52
 
5.4%
W 41
 
4.2%
B 41
 
4.2%
K 33
 
3.4%
Other values (7) 160
16.5%
Other Letter
ValueCountFrequency (%)
170
11.8%
158
10.9%
158
10.9%
137
9.5%
137
9.5%
113
7.8%
113
7.8%
97
6.7%
97
6.7%
65
 
4.5%
Other values (7) 199
13.8%
Decimal Number
ValueCountFrequency (%)
3 5405
24.5%
0 4259
19.3%
1 4059
18.4%
2 3673
16.6%
4 2644
12.0%
5 809
 
3.7%
7 756
 
3.4%
9 336
 
1.5%
8 115
 
0.5%
6 40
 
0.2%
Other Punctuation
ValueCountFrequency (%)
& 14
87.5%
? 2
 
12.5%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22113
90.2%
Hangul 1444
 
5.9%
Latin 970
 
4.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
P 192
19.8%
C 176
18.1%
E 90
9.3%
M 66
 
6.8%
A 62
 
6.4%
O 57
 
5.9%
N 52
 
5.4%
W 41
 
4.2%
B 41
 
4.2%
K 33
 
3.4%
Other values (7) 160
16.5%
Hangul
ValueCountFrequency (%)
170
11.8%
158
10.9%
158
10.9%
137
9.5%
137
9.5%
113
7.8%
113
7.8%
97
6.7%
97
6.7%
65
 
4.5%
Other values (7) 199
13.8%
Common
ValueCountFrequency (%)
3 5405
24.4%
0 4259
19.3%
1 4059
18.4%
2 3673
16.6%
4 2644
12.0%
5 809
 
3.7%
7 756
 
3.4%
9 336
 
1.5%
8 115
 
0.5%
6 40
 
0.2%
Other values (3) 17
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23083
94.1%
Hangul 1444
 
5.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 5405
23.4%
0 4259
18.5%
1 4059
17.6%
2 3673
15.9%
4 2644
11.5%
5 809
 
3.5%
7 756
 
3.3%
9 336
 
1.5%
P 192
 
0.8%
C 176
 
0.8%
Other values (20) 774
 
3.4%
Hangul
ValueCountFrequency (%)
170
11.8%
158
10.9%
158
10.9%
137
9.5%
137
9.5%
113
7.8%
113
7.8%
97
6.7%
97
6.7%
65
 
4.5%
Other values (7) 199
13.8%
Distinct4425
Distinct (%)62.7%
Missing0
Missing (%)0.0%
Memory size55.2 KiB
2023-12-13T03:59:18.036276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length21.281786
Min length21

Characters and Unicode

Total characters150143
Distinct characters16
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4258 ?
Unique (%)60.4%

Sample

1st row2001-12-11 오후 1:55:40
2nd row2001-12-11 오후 1:55:51
3rd row2001-12-11 오후 1:56:12
4th row2001-12-11 오후 1:56:26
5th row2001-12-11 오후 1:56:12
ValueCountFrequency (%)
오후 4871
 
23.0%
오전 2184
 
10.3%
2003-03-05 144
 
0.7%
2002-08-30 143
 
0.7%
2002-05-22 128
 
0.6%
2007-08-22 127
 
0.6%
2002-05-23 96
 
0.5%
2005-08-25 95
 
0.4%
2004-03-06 94
 
0.4%
2002-03-15 93
 
0.4%
Other values (4432) 13190
62.3%
2023-12-13T03:59:18.619467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 24957
16.6%
2 17275
11.5%
- 14110
9.4%
14110
9.4%
: 14110
9.4%
1 14104
9.4%
3 9017
 
6.0%
7055
 
4.7%
4 6420
 
4.3%
5 6054
 
4.0%
Other values (6) 22931
15.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 93703
62.4%
Dash Punctuation 14110
 
9.4%
Space Separator 14110
 
9.4%
Other Punctuation 14110
 
9.4%
Other Letter 14110
 
9.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 24957
26.6%
2 17275
18.4%
1 14104
15.1%
3 9017
 
9.6%
4 6420
 
6.9%
5 6054
 
6.5%
8 5454
 
5.8%
6 3694
 
3.9%
9 3406
 
3.6%
7 3322
 
3.5%
Other Letter
ValueCountFrequency (%)
7055
50.0%
4871
34.5%
2184
 
15.5%
Dash Punctuation
ValueCountFrequency (%)
- 14110
100.0%
Space Separator
ValueCountFrequency (%)
14110
100.0%
Other Punctuation
ValueCountFrequency (%)
: 14110
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 136033
90.6%
Hangul 14110
 
9.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 24957
18.3%
2 17275
12.7%
- 14110
10.4%
14110
10.4%
: 14110
10.4%
1 14104
10.4%
3 9017
 
6.6%
4 6420
 
4.7%
5 6054
 
4.5%
8 5454
 
4.0%
Other values (3) 10422
7.7%
Hangul
ValueCountFrequency (%)
7055
50.0%
4871
34.5%
2184
 
15.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 136033
90.6%
Hangul 14110
 
9.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 24957
18.3%
2 17275
12.7%
- 14110
10.4%
14110
10.4%
: 14110
10.4%
1 14104
10.4%
3 9017
 
6.6%
4 6420
 
4.7%
5 6054
 
4.5%
8 5454
 
4.0%
Other values (3) 10422
7.7%
Hangul
ValueCountFrequency (%)
7055
50.0%
4871
34.5%
2184
 
15.5%

Interactions

2023-12-13T03:59:08.190779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:00.762225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:02.035760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:03.130680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:04.217469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:05.819630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:06.950560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:08.407640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:00.935106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:02.196671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:03.309709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:04.870770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:05.987309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:07.149659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:08.589437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:01.112003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:02.348441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:03.429798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:05.018903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:06.141475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:07.324216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:08.774667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:01.289987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:02.504780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:03.572248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:05.162984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:06.315659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:07.473187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:08.981878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:01.486237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:02.651013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:03.708834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:05.327559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:06.460312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:07.622724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:09.169773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:01.656694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:02.800445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:03.867913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:05.487879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:06.612493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:07.791783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:09.374714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:01.840837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:02.956165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:04.026528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:05.658224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:06.781752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:59:07.975224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:59:18.755383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도학기과목계열코드과목학년수강반요일시작교시종료교시이수구분교원구분강의동
년도1.0000.2400.3440.1690.1170.0790.2720.2740.7090.4120.623
학기0.2401.0000.0310.2620.0690.0220.0380.0680.1610.0480.206
과목계열코드0.3440.0311.0000.2930.3320.0320.3270.3620.2530.3130.514
과목학년0.1690.2620.2931.0000.1280.0390.4860.5070.1000.1330.209
수강반0.1170.0690.3320.1281.0000.0000.1060.0830.0880.0360.131
요일0.0790.0220.0320.0390.0001.0000.3310.2480.1440.1010.000
시작교시0.2720.0380.3270.4860.1060.3311.0000.9630.1660.1040.210
종료교시0.2740.0680.3620.5070.0830.2480.9631.0000.1810.0950.199
이수구분0.7090.1610.2530.1000.0880.1440.1660.1811.0000.6270.341
교원구분0.4120.0480.3130.1330.0360.1010.1040.0950.6271.0000.184
강의동0.6230.2060.5140.2090.1310.0000.2100.1990.3410.1841.000
2023-12-13T03:59:18.993185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
강의동학기과목학년수강반
강의동1.0000.1830.1150.069
학기0.1831.0000.1740.115
과목학년0.1150.1741.0000.120
수강반0.0690.1150.1201.000
2023-12-13T03:59:19.159094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도과목계열코드요일시작교시종료교시이수구분교원구분학기과목학년수강반강의동
년도1.0000.139-0.036-0.058-0.0210.6900.2000.1840.1020.0700.288
과목계열코드0.1391.0000.005-0.0350.0170.1330.1330.0520.2810.1140.319
요일-0.0360.0051.000-0.125-0.132-0.0440.0340.0160.0250.0000.000
시작교시-0.058-0.035-0.1251.0000.943-0.087-0.0290.0520.3110.0840.076
종료교시-0.0210.017-0.1320.9431.000-0.030-0.0140.0550.3270.0470.079
이수구분0.6900.133-0.044-0.087-0.0301.0000.0720.1720.0690.0590.158
교원구분0.2000.1330.034-0.029-0.0140.0721.0000.0520.0920.0240.082
학기0.1840.0520.0160.0520.0550.1720.0521.0000.1740.1150.183
과목학년0.1020.2810.0250.3110.3270.0690.0920.1741.0000.1200.115
수강반0.0700.1140.0000.0840.0470.0590.0240.1150.1201.0000.069
강의동0.2880.3190.0000.0760.0790.1580.0820.1830.1150.0691.000

Missing values

2023-12-13T03:59:09.694078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:59:10.045712image/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.
2023-12-13T03:59:10.282578image/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

년도학기과목계열코드과목전공코드과목학년과목코드수강반요일시작교시종료교시이수구분교원구분강의동강의실사용날짜,시간
02001190110622A1129<NA>011012001-12-11 오후 1:55:40
12001190110988A1349<NA>011022001-12-11 오후 1:55:51
220021901B50005A2139<NA>022012001-12-11 오후 1:56:12
32001190111239A2569<NA>033012001-12-11 오후 1:56:26
420021901C10001A3159<NA>022012001-12-11 오후 1:56:12
520021901A10001A2459<NA>043012001-12-11 오후 1:56:12
620021301C30027A12473333072002-03-07 오전 11:05:02
720021301C30003A16671333072002-03-07 오전 11:06:03
820021301C30001A17871333072002-03-07 오전 11:06:25
920021301C30015A224730333092002-03-07 오전 11:08:47
년도학기과목계열코드과목전공코드과목학년과목코드수강반요일시작교시종료교시이수구분교원구분강의동강의실사용날짜,시간
704520202201A20039A423533<NA><NA>2020-08-19 오전 10:05:31
704620202302C30338A5235830333072020-09-09 오전 11:10:12
704720202302C30338A5585830333072020-09-09 오전 11:10:12
704820202302C30351A1136020333042020-09-09 오전 11:10:12
704920202302C30351A1576020441012020-09-09 오전 11:10:12
705020202302N03039A25760305별동2020-09-09 오전 11:10:12
705120202302N03039A45760305별동2020-09-09 오전 11:10:12
705220202302N03040A3136010441012020-09-09 오전 11:10:12
705320202302N03040A4136010441012020-09-09 오전 11:10:12
705420202302N03041A2136010441012020-09-09 오전 11:10:12