Overview

Dataset statistics

Number of variables27
Number of observations6954
Missing cells44852
Missing cells (%)23.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 MiB
Average record size in memory223.0 B

Variable types

Numeric5
Categorical8
Text14

Dataset

Description중장기개방계획에따른 경상남도 경남도립남해대학 데이터자료입니다.(전공이름, 과목이름, 과목코드등의 데이터를 포함하고있습니다.)
Author경상남도
URLhttps://www.data.go.kr/data/15067654/fileData.do

Alerts

학기구분 has constant value ""Constant
is highly imbalanced (65.7%)Imbalance
내용1 is highly imbalanced (54.2%)Imbalance
내용2 is highly imbalanced (55.9%)Imbalance
내용3 is highly imbalanced (51.5%)Imbalance
내용4 is highly imbalanced (55.0%)Imbalance
내용5 is highly imbalanced (98.6%)Imbalance
이론시수 has 1558 (22.4%) missing valuesMissing
실습시수 has 1558 (22.4%) missing valuesMissing
주교재 has 549 (7.9%) missing valuesMissing
참고문헌 has 2190 (31.5%) missing valuesMissing
강의목적및개요 has 2449 (35.2%) missing valuesMissing
항목1 has 307 (4.4%) missing valuesMissing
항목2 has 360 (5.2%) missing valuesMissing
항목3 has 448 (6.4%) missing valuesMissing
항목4 has 723 (10.4%) missing valuesMissing
항목5 has 6914 (99.4%) missing valuesMissing
항목6 has 6944 (99.9%) missing valuesMissing
항목7 has 6949 (99.9%) missing valuesMissing
내용6 has 6948 (99.9%) missing valuesMissing
내용7 has 6949 (99.9%) missing valuesMissing
이론시수 has 1102 (15.8%) zerosZeros
실습시수 has 2154 (31.0%) zerosZeros

Reproduction

Analysis started2023-12-12 14:41:52.105163
Analysis finished2023-12-12 14:41:55.017069
Duration2.91 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년도
Real number (ℝ)

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2012.9441
Minimum2002
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size61.2 KiB
2023-12-12T23:41:55.091467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2002
5-th percentile2006
Q12010
median2013
Q32017
95-th percentile2020
Maximum2020
Range18
Interquartile range (IQR)7

Descriptive statistics

Standard deviation4.3162958
Coefficient of variation (CV)0.0021442701
Kurtosis-1.0412676
Mean2012.9441
Median Absolute Deviation (MAD)4
Skewness0.067652001
Sum13998013
Variance18.63041
MonotonicityNot monotonic
2023-12-12T23:41:55.222829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
2015 603
 
8.7%
2012 599
 
8.6%
2011 587
 
8.4%
2020 581
 
8.4%
2013 577
 
8.3%
2014 564
 
8.1%
2010 503
 
7.2%
2019 487
 
7.0%
2006 443
 
6.4%
2018 438
 
6.3%
Other values (7) 1572
22.6%
ValueCountFrequency (%)
2002 1
 
< 0.1%
2005 92
 
1.3%
2006 443
6.4%
2007 375
5.4%
2008 372
5.3%
2009 377
5.4%
2010 503
7.2%
2011 587
8.4%
2012 599
8.6%
2013 577
8.3%
ValueCountFrequency (%)
2020 581
8.4%
2019 487
7.0%
2018 438
6.3%
2017 345
5.0%
2016 10
 
0.1%
2015 603
8.7%
2014 564
8.1%
2013 577
8.3%
2012 599
8.6%
2011 587
8.4%

학기
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.5 KiB
1
3835 
2
3119 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row2
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 3835
55.1%
2 3119
44.9%

Length

2023-12-12T23:41:55.372687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:41:55.513057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 3835
55.1%
2 3119
44.9%

학기구분
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.5 KiB
1
6954 

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 6954
100.0%

Length

2023-12-12T23:41:55.691668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:41:55.821830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 6954
100.0%

과목
Text

Distinct2759
Distinct (%)39.7%
Missing0
Missing (%)0.0%
Memory size54.5 KiB
2023-12-12T23:41:56.166731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters41724
Distinct characters17
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

Unique1121 ?
Unique (%)16.1%

Sample

1st rowB10002
2nd rowC10002
3rd rowC40028
4th rowA60001
5th rowA60001
ValueCountFrequency (%)
c50078 17
 
0.2%
c70041 17
 
0.2%
d70002 16
 
0.2%
c20150 15
 
0.2%
a50010 15
 
0.2%
c70040 14
 
0.2%
c60085 14
 
0.2%
a40015 14
 
0.2%
a70007 14
 
0.2%
c60095 14
 
0.2%
Other values (2749) 6804
97.8%
2023-12-12T23:41:56.691659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12058
28.9%
1 5824
14.0%
C 4907
11.8%
2 3342
 
8.0%
3 2487
 
6.0%
4 2399
 
5.7%
5 2305
 
5.5%
7 2144
 
5.1%
6 1980
 
4.7%
A 1207
 
2.9%
Other values (7) 3071
 
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 34770
83.3%
Uppercase Letter 6954
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12058
34.7%
1 5824
16.8%
2 3342
 
9.6%
3 2487
 
7.2%
4 2399
 
6.9%
5 2305
 
6.6%
7 2144
 
6.2%
6 1980
 
5.7%
9 1155
 
3.3%
8 1076
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
C 4907
70.6%
A 1207
 
17.4%
N 404
 
5.8%
B 364
 
5.2%
D 67
 
1.0%
E 4
 
0.1%
F 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 34770
83.3%
Latin 6954
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12058
34.7%
1 5824
16.8%
2 3342
 
9.6%
3 2487
 
7.2%
4 2399
 
6.9%
5 2305
 
6.6%
7 2144
 
6.2%
6 1980
 
5.7%
9 1155
 
3.3%
8 1076
 
3.1%
Latin
ValueCountFrequency (%)
C 4907
70.6%
A 1207
 
17.4%
N 404
 
5.8%
B 364
 
5.2%
D 67
 
1.0%
E 4
 
0.1%
F 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41724
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12058
28.9%
1 5824
14.0%
C 4907
11.8%
2 3342
 
8.0%
3 2487
 
6.0%
4 2399
 
5.7%
5 2305
 
5.5%
7 2144
 
5.1%
6 1980
 
4.7%
A 1207
 
2.9%
Other values (7) 3071
 
7.4%


Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.5 KiB
A
4917 
B
1954 
C
 
53
D
 
19
E
 
7
Other values (2)
 
4

Length

Max length4
Median length1
Mean length1.0012942
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
A 4917
70.7%
B 1954
 
28.1%
C 53
 
0.8%
D 19
 
0.3%
E 7
 
0.1%
<NA> 3
 
< 0.1%
2 1
 
< 0.1%

Length

2023-12-12T23:41:56.862422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:41:57.001817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
a 4917
70.7%
b 1954
 
28.1%
c 53
 
0.8%
d 19
 
0.3%
e 7
 
0.1%
na 3
 
< 0.1%
2 1
 
< 0.1%

이수구분
Real number (ℝ)

Distinct34
Distinct (%)0.5%
Missing3
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean17.568264
Minimum1
Maximum60
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size61.2 KiB
2023-12-12T23:41:57.117367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median7
Q323
95-th percentile60
Maximum60
Range59
Interquartile range (IQR)19

Descriptive statistics

Standard deviation21.348885
Coefficient of variation (CV)1.2151961
Kurtosis-0.22026938
Mean17.568264
Median Absolute Deviation (MAD)4
Skewness1.2579061
Sum122117
Variance455.77487
MonotonicityNot monotonic
2023-12-12T23:41:57.249907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
7 2722
39.1%
4 665
 
9.6%
60 540
 
7.8%
1 528
 
7.6%
2 444
 
6.4%
3 418
 
6.0%
59 416
 
6.0%
53 200
 
2.9%
23 173
 
2.5%
52 116
 
1.7%
Other values (24) 729
 
10.5%
ValueCountFrequency (%)
1 528
 
7.6%
2 444
 
6.4%
3 418
 
6.0%
4 665
 
9.6%
5 85
 
1.2%
6 2
 
< 0.1%
7 2722
39.1%
11 102
 
1.5%
12 3
 
< 0.1%
13 7
 
0.1%
ValueCountFrequency (%)
60 540
7.8%
59 416
6.0%
58 43
 
0.6%
57 58
 
0.8%
56 18
 
0.3%
54 13
 
0.2%
53 200
 
2.9%
52 116
 
1.7%
51 76
 
1.1%
41 1
 
< 0.1%

학점
Real number (ℝ)

Distinct15
Distinct (%)0.2%
Missing3
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean2.3013955
Minimum1
Maximum24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size61.2 KiB
2023-12-12T23:41:57.371006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q33
95-th percentile3
Maximum24
Range23
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.4915386
Coefficient of variation (CV)0.6481018
Kurtosis62.403411
Mean2.3013955
Median Absolute Deviation (MAD)0
Skewness7.0955211
Sum15997
Variance2.2246873
MonotonicityNot monotonic
2023-12-12T23:41:57.492058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
2 4472
64.3%
3 1585
 
22.8%
1 739
 
10.6%
8 52
 
0.7%
16 51
 
0.7%
4 30
 
0.4%
6 12
 
0.2%
15 3
 
< 0.1%
18 1
 
< 0.1%
24 1
 
< 0.1%
Other values (5) 5
 
0.1%
(Missing) 3
 
< 0.1%
ValueCountFrequency (%)
1 739
 
10.6%
2 4472
64.3%
3 1585
 
22.8%
4 30
 
0.4%
5 1
 
< 0.1%
6 12
 
0.2%
7 1
 
< 0.1%
8 52
 
0.7%
10 1
 
< 0.1%
12 1
 
< 0.1%
ValueCountFrequency (%)
24 1
 
< 0.1%
18 1
 
< 0.1%
16 51
0.7%
15 3
 
< 0.1%
14 1
 
< 0.1%
12 1
 
< 0.1%
10 1
 
< 0.1%
8 52
0.7%
7 1
 
< 0.1%
6 12
 
0.2%

이론시수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.1%
Missing1558
Missing (%)22.4%
Infinite0
Infinite (%)0.0%
Mean1.3061527
Minimum0
Maximum20
Zeros1102
Zeros (%)15.8%
Negative0
Negative (%)0.0%
Memory size61.2 KiB
2023-12-12T23:41:57.593041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile3
Maximum20
Range20
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.94464352
Coefficient of variation (CV)0.72322594
Kurtosis27.831119
Mean1.3061527
Median Absolute Deviation (MAD)1
Skewness1.6703475
Sum7048
Variance0.89235139
MonotonicityNot monotonic
2023-12-12T23:41:57.694177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 2083
30.0%
2 1709
24.6%
0 1102
15.8%
3 485
 
7.0%
4 12
 
0.2%
6 4
 
0.1%
20 1
 
< 0.1%
(Missing) 1558
22.4%
ValueCountFrequency (%)
0 1102
15.8%
1 2083
30.0%
2 1709
24.6%
3 485
 
7.0%
4 12
 
0.2%
6 4
 
0.1%
20 1
 
< 0.1%
ValueCountFrequency (%)
20 1
 
< 0.1%
6 4
 
0.1%
4 12
 
0.2%
3 485
 
7.0%
2 1709
24.6%
1 2083
30.0%
0 1102
15.8%

실습시수
Real number (ℝ)

MISSING  ZEROS 

Distinct19
Distinct (%)0.4%
Missing1558
Missing (%)22.4%
Infinite0
Infinite (%)0.0%
Mean1.5976649
Minimum0
Maximum40
Zeros2154
Zeros (%)31.0%
Negative0
Negative (%)0.0%
Memory size61.2 KiB
2023-12-12T23:41:57.804508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q32
95-th percentile3
Maximum40
Range40
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.8515164
Coefficient of variation (CV)1.7848025
Kurtosis78.884126
Mean1.5976649
Median Absolute Deviation (MAD)1
Skewness7.9281671
Sum8621
Variance8.1311456
MonotonicityNot monotonic
2023-12-12T23:41:57.912068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
2 2466
35.5%
0 2154
31.0%
3 459
 
6.6%
4 163
 
2.3%
1 81
 
1.2%
32 29
 
0.4%
16 23
 
0.3%
8 5
 
0.1%
12 4
 
0.1%
15 2
 
< 0.1%
Other values (9) 10
 
0.1%
(Missing) 1558
22.4%
ValueCountFrequency (%)
0 2154
31.0%
1 81
 
1.2%
2 2466
35.5%
3 459
 
6.6%
4 163
 
2.3%
5 1
 
< 0.1%
6 2
 
< 0.1%
7 1
 
< 0.1%
8 5
 
0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
40 1
 
< 0.1%
32 29
0.4%
30 1
 
< 0.1%
24 1
 
< 0.1%
20 1
 
< 0.1%
18 1
 
< 0.1%
16 23
0.3%
15 2
 
< 0.1%
12 4
 
0.1%
9 1
 
< 0.1%

주교재
Text

MISSING 

Distinct3223
Distinct (%)50.3%
Missing549
Missing (%)7.9%
Memory size54.5 KiB
2023-12-12T23:41:58.160000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length201
Median length135
Mean length31.299922
Min length1

Characters and Unicode

Total characters200476
Distinct characters824
Distinct categories16 ?
Distinct scripts7 ?
Distinct blocks14 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1788 ?
Unique (%)27.9%

Sample

1st row영어기초
2nd rowwrwrewe
3rd row김성혁, 관광마케팅의 이해, 백산출판사, 2003.
4th row2-------------
5th row2-------------
ValueCountFrequency (%)
1901
 
5.5%
493
 
1.4%
356
 
1.0%
322
 
0.9%
교재 297
 
0.9%
공저 262
 
0.8%
1 241
 
0.7%
출판사 181
 
0.5%
위한 148
 
0.4%
실무 147
 
0.4%
Other values (7073) 29916
87.3%
2023-12-12T23:41:58.608032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
29420
 
14.7%
, 5929
 
3.0%
0 3698
 
1.8%
2 3032
 
1.5%
2865
 
1.4%
2799
 
1.4%
) 2759
 
1.4%
( 2726
 
1.4%
1 2579
 
1.3%
. 2397
 
1.2%
Other values (814) 142272
71.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 105328
52.5%
Space Separator 29423
 
14.7%
Lowercase Letter 20500
 
10.2%
Other Punctuation 12778
 
6.4%
Decimal Number 12576
 
6.3%
Uppercase Letter 11842
 
5.9%
Close Punctuation 2847
 
1.4%
Open Punctuation 2816
 
1.4%
Dash Punctuation 1456
 
0.7%
Math Symbol 269
 
0.1%
Other values (6) 641
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2865
 
2.7%
2799
 
2.7%
1995
 
1.9%
1895
 
1.8%
1788
 
1.7%
1641
 
1.6%
1599
 
1.5%
1597
 
1.5%
1505
 
1.4%
1378
 
1.3%
Other values (702) 86266
81.9%
Lowercase Letter
ValueCountFrequency (%)
e 2139
 
10.4%
o 1840
 
9.0%
i 1758
 
8.6%
n 1689
 
8.2%
t 1605
 
7.8%
a 1581
 
7.7%
r 1503
 
7.3%
s 1231
 
6.0%
c 830
 
4.0%
d 830
 
4.0%
Other values (17) 5494
26.8%
Uppercase Letter
ValueCountFrequency (%)
C 1374
 
11.6%
A 1242
 
10.5%
S 994
 
8.4%
T 912
 
7.7%
E 831
 
7.0%
I 679
 
5.7%
P 658
 
5.6%
M 529
 
4.5%
R 520
 
4.4%
N 517
 
4.4%
Other values (16) 3586
30.3%
Other Punctuation
ValueCountFrequency (%)
, 5929
46.4%
. 2397
18.8%
/ 1650
 
12.9%
: 1607
 
12.6%
" 614
 
4.8%
* 235
 
1.8%
& 140
 
1.1%
' 80
 
0.6%
· 56
 
0.4%
; 24
 
0.2%
Other values (6) 46
 
0.4%
Decimal Number
ValueCountFrequency (%)
0 3698
29.4%
2 3032
24.1%
1 2579
20.5%
3 831
 
6.6%
5 553
 
4.4%
4 546
 
4.3%
8 411
 
3.3%
7 343
 
2.7%
6 316
 
2.5%
9 267
 
2.1%
Math Symbol
ValueCountFrequency (%)
+ 114
42.4%
| 71
26.4%
> 34
 
12.6%
< 31
 
11.5%
~ 16
 
5.9%
2
 
0.7%
= 1
 
0.4%
Close Punctuation
ValueCountFrequency (%)
) 2759
96.9%
] 74
 
2.6%
10
 
0.4%
} 3
 
0.1%
1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 2726
96.8%
[ 77
 
2.7%
10
 
0.4%
{ 2
 
0.1%
1
 
< 0.1%
Other Symbol
ValueCountFrequency (%)
15
50.0%
6
 
20.0%
4
 
13.3%
3
 
10.0%
2
 
6.7%
Space Separator
ValueCountFrequency (%)
29420
> 99.9%
  3
 
< 0.1%
Initial Punctuation
ValueCountFrequency (%)
205
98.1%
4
 
1.9%
Final Punctuation
ValueCountFrequency (%)
201
98.0%
4
 
2.0%
Letter Number
ValueCountFrequency (%)
5
55.6%
4
44.4%
Dash Punctuation
ValueCountFrequency (%)
- 1456
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 187
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 105212
52.5%
Common 62782
31.3%
Latin 32349
 
16.1%
Han 116
 
0.1%
Hiragana 12
 
< 0.1%
Katakana 3
 
< 0.1%
Greek 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2865
 
2.7%
2799
 
2.7%
1995
 
1.9%
1895
 
1.8%
1788
 
1.7%
1641
 
1.6%
1599
 
1.5%
1597
 
1.5%
1505
 
1.4%
1378
 
1.3%
Other values (649) 86150
81.9%
Common
ValueCountFrequency (%)
29420
46.9%
, 5929
 
9.4%
0 3698
 
5.9%
2 3032
 
4.8%
) 2759
 
4.4%
( 2726
 
4.3%
1 2579
 
4.1%
. 2397
 
3.8%
/ 1650
 
2.6%
: 1607
 
2.6%
Other values (46) 6985
 
11.1%
Latin
ValueCountFrequency (%)
e 2139
 
6.6%
o 1840
 
5.7%
i 1758
 
5.4%
n 1689
 
5.2%
t 1605
 
5.0%
a 1581
 
4.9%
r 1503
 
4.6%
C 1374
 
4.2%
A 1242
 
3.8%
s 1231
 
3.8%
Other values (44) 16387
50.7%
Han
ValueCountFrequency (%)
20
17.2%
12
 
10.3%
7
 
6.0%
7
 
6.0%
5
 
4.3%
5
 
4.3%
5
 
4.3%
5
 
4.3%
4
 
3.4%
3
 
2.6%
Other values (39) 43
37.1%
Katakana
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Hiragana
ValueCountFrequency (%)
6
50.0%
6
50.0%
Greek
ValueCountFrequency (%)
α 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 105178
52.5%
ASCII 94596
47.2%
Punctuation 416
 
0.2%
CJK 115
 
0.1%
None 110
 
0.1%
Compat Jamo 19
 
< 0.1%
Hiragana 12
 
< 0.1%
Number Forms 9
 
< 0.1%
Geometric Shapes 7
 
< 0.1%
Misc Symbols 6
 
< 0.1%
Other values (4) 8
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
29420
31.1%
, 5929
 
6.3%
0 3698
 
3.9%
2 3032
 
3.2%
) 2759
 
2.9%
( 2726
 
2.9%
1 2579
 
2.7%
. 2397
 
2.5%
e 2139
 
2.3%
o 1840
 
1.9%
Other values (79) 38077
40.3%
Hangul
ValueCountFrequency (%)
2865
 
2.7%
2799
 
2.7%
1995
 
1.9%
1895
 
1.8%
1788
 
1.7%
1641
 
1.6%
1599
 
1.5%
1597
 
1.5%
1505
 
1.4%
1378
 
1.3%
Other values (646) 86116
81.9%
Punctuation
ValueCountFrequency (%)
205
49.3%
201
48.3%
4
 
1.0%
4
 
1.0%
2
 
0.5%
None
ValueCountFrequency (%)
· 56
50.9%
15
 
13.6%
10
 
9.1%
10
 
9.1%
10
 
9.1%
  3
 
2.7%
α 2
 
1.8%
1
 
0.9%
1
 
0.9%
1
 
0.9%
CJK
ValueCountFrequency (%)
20
17.4%
12
 
10.4%
7
 
6.1%
7
 
6.1%
5
 
4.3%
5
 
4.3%
5
 
4.3%
5
 
4.3%
4
 
3.5%
3
 
2.6%
Other values (38) 42
36.5%
Compat Jamo
ValueCountFrequency (%)
15
78.9%
4
 
21.1%
Misc Symbols
ValueCountFrequency (%)
6
100.0%
Hiragana
ValueCountFrequency (%)
6
50.0%
6
50.0%
Number Forms
ValueCountFrequency (%)
5
55.6%
4
44.4%
Geometric Shapes
ValueCountFrequency (%)
4
57.1%
3
42.9%
Box Drawing
ValueCountFrequency (%)
2
100.0%
Math Operators
ValueCountFrequency (%)
2
100.0%
Katakana
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
CJK Compat Ideographs
ValueCountFrequency (%)
1
100.0%

참고문헌
Text

MISSING 

Distinct2254
Distinct (%)47.3%
Missing2190
Missing (%)31.5%
Memory size54.5 KiB
2023-12-12T23:41:59.050277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length191
Median length137
Mean length44.729849
Min length1

Characters and Unicode

Total characters213093
Distinct characters890
Distinct categories15 ?
Distinct scripts5 ?
Distinct blocks10 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1269 ?
Unique (%)26.6%

Sample

1st row영어기초문법
2nd rowrwerwerw
3rd row최태광, 관광마케팅, 백산출판사, 2002.
4th row3---
5th row3---
ValueCountFrequency (%)
2268
 
6.2%
컴퓨터 538
 
1.5%
487
 
1.3%
461
 
1.3%
391
 
1.1%
1 301
 
0.8%
221
 
0.6%
출판사 215
 
0.6%
2005 211
 
0.6%
빔프로젝트 199
 
0.5%
Other values (6807) 31007
85.4%
2023-12-12T23:41:59.706139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
33971
 
15.9%
, 10310
 
4.8%
0 4769
 
2.2%
. 3736
 
1.8%
2 3377
 
1.6%
3249
 
1.5%
2982
 
1.4%
) 2835
 
1.3%
( 2806
 
1.3%
2319
 
1.1%
Other values (880) 142739
67.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 115948
54.4%
Space Separator 33971
 
15.9%
Other Punctuation 18046
 
8.5%
Lowercase Letter 13890
 
6.5%
Decimal Number 13438
 
6.3%
Uppercase Letter 9271
 
4.4%
Close Punctuation 2871
 
1.3%
Open Punctuation 2845
 
1.3%
Dash Punctuation 1855
 
0.9%
Math Symbol 840
 
0.4%
Other values (5) 118
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3249
 
2.8%
2982
 
2.6%
2319
 
2.0%
1763
 
1.5%
1757
 
1.5%
1737
 
1.5%
1492
 
1.3%
1452
 
1.3%
1422
 
1.2%
1387
 
1.2%
Other values (774) 96388
83.1%
Lowercase Letter
ValueCountFrequency (%)
e 1489
 
10.7%
i 1351
 
9.7%
r 1175
 
8.5%
s 1111
 
8.0%
a 1109
 
8.0%
o 1014
 
7.3%
n 938
 
6.8%
t 848
 
6.1%
c 571
 
4.1%
u 477
 
3.4%
Other values (16) 3807
27.4%
Uppercase Letter
ValueCountFrequency (%)
C 1334
14.4%
A 885
 
9.5%
S 831
 
9.0%
E 690
 
7.4%
P 580
 
6.3%
T 509
 
5.5%
D 499
 
5.4%
I 443
 
4.8%
N 433
 
4.7%
R 422
 
4.6%
Other values (16) 2645
28.5%
Other Punctuation
ValueCountFrequency (%)
, 10310
57.1%
. 3736
 
20.7%
/ 1910
 
10.6%
: 1135
 
6.3%
" 341
 
1.9%
* 267
 
1.5%
· 143
 
0.8%
& 97
 
0.5%
' 50
 
0.3%
; 21
 
0.1%
Other values (6) 36
 
0.2%
Decimal Number
ValueCountFrequency (%)
0 4769
35.5%
2 3377
25.1%
1 1868
 
13.9%
3 837
 
6.2%
5 688
 
5.1%
9 467
 
3.5%
8 440
 
3.3%
4 431
 
3.2%
6 284
 
2.1%
7 277
 
2.1%
Math Symbol
ValueCountFrequency (%)
> 614
73.1%
+ 96
 
11.4%
| 76
 
9.0%
~ 21
 
2.5%
< 11
 
1.3%
= 10
 
1.2%
6
 
0.7%
5
 
0.6%
1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 2835
98.7%
] 13
 
0.5%
} 10
 
0.3%
10
 
0.3%
3
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 2806
98.6%
[ 15
 
0.5%
{ 11
 
0.4%
10
 
0.4%
3
 
0.1%
Other Symbol
ValueCountFrequency (%)
8
44.4%
5
27.8%
5
27.8%
Space Separator
ValueCountFrequency (%)
33971
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1855
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 94
100.0%
Final Punctuation
ValueCountFrequency (%)
2
100.0%
Initial Punctuation
ValueCountFrequency (%)
2
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 115766
54.3%
Common 73976
34.7%
Latin 23161
 
10.9%
Han 186
 
0.1%
Hiragana 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3249
 
2.8%
2982
 
2.6%
2319
 
2.0%
1763
 
1.5%
1757
 
1.5%
1737
 
1.5%
1492
 
1.3%
1452
 
1.3%
1422
 
1.2%
1387
 
1.2%
Other values (721) 96206
83.1%
Common
ValueCountFrequency (%)
33971
45.9%
, 10310
 
13.9%
0 4769
 
6.4%
. 3736
 
5.1%
2 3377
 
4.6%
) 2835
 
3.8%
( 2806
 
3.8%
/ 1910
 
2.6%
1 1868
 
2.5%
- 1855
 
2.5%
Other values (43) 6539
 
8.8%
Han
ValueCountFrequency (%)
9
 
4.8%
9
 
4.8%
8
 
4.3%
8
 
4.3%
7
 
3.8%
7
 
3.8%
7
 
3.8%
7
 
3.8%
6
 
3.2%
6
 
3.2%
Other values (43) 112
60.2%
Latin
ValueCountFrequency (%)
e 1489
 
6.4%
i 1351
 
5.8%
C 1334
 
5.8%
r 1175
 
5.1%
s 1111
 
4.8%
a 1109
 
4.8%
o 1014
 
4.4%
n 938
 
4.0%
A 885
 
3.8%
t 848
 
3.7%
Other values (42) 11907
51.4%
Hiragana
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 115753
54.3%
ASCII 96927
45.5%
None 187
 
0.1%
CJK 186
 
0.1%
Arrows 11
 
< 0.1%
Geometric Shapes 10
 
< 0.1%
Punctuation 9
 
< 0.1%
Compat Jamo 5
 
< 0.1%
Hiragana 4
 
< 0.1%
Math Operators 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
33971
35.0%
, 10310
 
10.6%
0 4769
 
4.9%
. 3736
 
3.9%
2 3377
 
3.5%
) 2835
 
2.9%
( 2806
 
2.9%
/ 1910
 
2.0%
1 1868
 
1.9%
- 1855
 
1.9%
Other values (81) 29490
30.4%
Hangul
ValueCountFrequency (%)
3249
 
2.8%
2982
 
2.6%
2319
 
2.0%
1763
 
1.5%
1757
 
1.5%
1737
 
1.5%
1492
 
1.3%
1452
 
1.3%
1422
 
1.2%
1387
 
1.2%
Other values (718) 96193
83.1%
None
ValueCountFrequency (%)
· 143
76.5%
10
 
5.3%
10
 
5.3%
10
 
5.3%
8
 
4.3%
3
 
1.6%
3
 
1.6%
CJK
ValueCountFrequency (%)
9
 
4.8%
9
 
4.8%
8
 
4.3%
8
 
4.3%
7
 
3.8%
7
 
3.8%
7
 
3.8%
7
 
3.8%
6
 
3.2%
6
 
3.2%
Other values (43) 112
60.2%
Arrows
ValueCountFrequency (%)
6
54.5%
5
45.5%
Geometric Shapes
ValueCountFrequency (%)
5
50.0%
5
50.0%
Punctuation
ValueCountFrequency (%)
5
55.6%
2
 
22.2%
2
 
22.2%
Hiragana
ValueCountFrequency (%)
4
100.0%
Compat Jamo
ValueCountFrequency (%)
3
60.0%
2
40.0%
Math Operators
ValueCountFrequency (%)
1
100.0%

강의목적및개요
Text

MISSING 

Distinct2120
Distinct (%)47.1%
Missing2449
Missing (%)35.2%
Memory size54.5 KiB
2023-12-12T23:42:00.131899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length237
Median length123
Mean length94.147392
Min length1

Characters and Unicode

Total characters424134
Distinct characters853
Distinct categories15 ?
Distinct scripts4 ?
Distinct blocks9 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1181 ?
Unique (%)26.2%

Sample

1st row영어기초문법
2nd rowrewrwre
3rd row숙박업, 항공업, 여행업, 주제공원, 리조트, 유람선, 외식업 등 서비스를 제공하는 관광기업의 기초적인 마케팅 지식을 함양하며, 특히 고객만족 경영, 내부마케팅 등 새로운 분야의 이론을 숙지하도록 한다
4th row1--------
5th row1--------
ValueCountFrequency (%)
1879
 
2.0%
1720
 
1.8%
한다 1054
 
1.1%
대한 923
 
1.0%
있는 885
 
0.9%
능력을 860
 
0.9%
있다 833
 
0.9%
있도록 744
 
0.8%
필요한 713
 
0.7%
통해 607
 
0.6%
Other values (11869) 85393
89.3%
2023-12-12T23:42:00.802176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
91975
 
21.7%
9613
 
2.3%
8310
 
2.0%
6822
 
1.6%
6767
 
1.6%
6726
 
1.6%
6424
 
1.5%
6285
 
1.5%
5452
 
1.3%
, 5173
 
1.2%
Other values (843) 270587
63.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 299593
70.6%
Space Separator 91975
 
21.7%
Lowercase Letter 14436
 
3.4%
Other Punctuation 10501
 
2.5%
Uppercase Letter 4566
 
1.1%
Decimal Number 1768
 
0.4%
Close Punctuation 476
 
0.1%
Open Punctuation 441
 
0.1%
Dash Punctuation 286
 
0.1%
Connector Punctuation 48
 
< 0.1%
Other values (5) 44
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
9613
 
3.2%
8310
 
2.8%
6822
 
2.3%
6767
 
2.3%
6726
 
2.2%
6424
 
2.1%
6285
 
2.1%
5452
 
1.8%
4934
 
1.6%
4832
 
1.6%
Other values (754) 233428
77.9%
Uppercase Letter
ValueCountFrequency (%)
C 775
17.0%
A 506
11.1%
D 408
8.9%
T 380
8.3%
P 367
8.0%
E 341
 
7.5%
S 320
 
7.0%
R 217
 
4.8%
I 210
 
4.6%
V 152
 
3.3%
Other values (16) 890
19.5%
Lowercase Letter
ValueCountFrequency (%)
e 1732
12.0%
s 1282
 
8.9%
o 1262
 
8.7%
t 1234
 
8.5%
i 1108
 
7.7%
n 1101
 
7.6%
r 956
 
6.6%
a 842
 
5.8%
l 660
 
4.6%
h 547
 
3.8%
Other values (15) 3712
25.7%
Other Punctuation
ValueCountFrequency (%)
, 5173
49.3%
. 4724
45.0%
/ 221
 
2.1%
: 107
 
1.0%
' 74
 
0.7%
· 71
 
0.7%
* 64
 
0.6%
& 49
 
0.5%
% 8
 
0.1%
; 7
 
0.1%
Decimal Number
ValueCountFrequency (%)
1 476
26.9%
2 426
24.1%
0 282
16.0%
3 265
15.0%
4 108
 
6.1%
8 64
 
3.6%
5 62
 
3.5%
9 52
 
2.9%
6 19
 
1.1%
7 14
 
0.8%
Close Punctuation
ValueCountFrequency (%)
) 452
95.0%
] 20
 
4.2%
4
 
0.8%
Open Punctuation
ValueCountFrequency (%)
( 417
94.6%
[ 20
 
4.5%
4
 
0.9%
Math Symbol
ValueCountFrequency (%)
+ 14
77.8%
> 2
 
11.1%
< 2
 
11.1%
Letter Number
ValueCountFrequency (%)
4
66.7%
2
33.3%
Space Separator
ValueCountFrequency (%)
91975
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 286
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 48
100.0%
Initial Punctuation
ValueCountFrequency (%)
9
100.0%
Final Punctuation
ValueCountFrequency (%)
9
100.0%
Other Symbol
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 299574
70.6%
Common 105533
 
24.9%
Latin 19008
 
4.5%
Han 19
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
9613
 
3.2%
8310
 
2.8%
6822
 
2.3%
6767
 
2.3%
6726
 
2.2%
6424
 
2.1%
6285
 
2.1%
5452
 
1.8%
4934
 
1.6%
4832
 
1.6%
Other values (746) 233409
77.9%
Latin
ValueCountFrequency (%)
e 1732
 
9.1%
s 1282
 
6.7%
o 1262
 
6.6%
t 1234
 
6.5%
i 1108
 
5.8%
n 1101
 
5.8%
r 956
 
5.0%
a 842
 
4.4%
C 775
 
4.1%
l 660
 
3.5%
Other values (43) 8056
42.4%
Common
ValueCountFrequency (%)
91975
87.2%
, 5173
 
4.9%
. 4724
 
4.5%
1 476
 
0.5%
) 452
 
0.4%
2 426
 
0.4%
( 417
 
0.4%
- 286
 
0.3%
0 282
 
0.3%
3 265
 
0.3%
Other values (26) 1057
 
1.0%
Han
ValueCountFrequency (%)
6
31.6%
3
15.8%
3
15.8%
3
15.8%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 299544
70.6%
ASCII 124436
29.3%
None 79
 
< 0.1%
Compat Jamo 30
 
< 0.1%
Punctuation 18
 
< 0.1%
CJK 18
 
< 0.1%
Number Forms 6
 
< 0.1%
Geometric Shapes 2
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
91975
73.9%
, 5173
 
4.2%
. 4724
 
3.8%
e 1732
 
1.4%
s 1282
 
1.0%
o 1262
 
1.0%
t 1234
 
1.0%
i 1108
 
0.9%
n 1101
 
0.9%
r 956
 
0.8%
Other values (71) 13889
 
11.2%
Hangul
ValueCountFrequency (%)
9613
 
3.2%
8310
 
2.8%
6822
 
2.3%
6767
 
2.3%
6726
 
2.2%
6424
 
2.1%
6285
 
2.1%
5452
 
1.8%
4934
 
1.6%
4832
 
1.6%
Other values (738) 233379
77.9%
None
ValueCountFrequency (%)
· 71
89.9%
4
 
5.1%
4
 
5.1%
Compat Jamo
ValueCountFrequency (%)
21
70.0%
2
 
6.7%
2
 
6.7%
1
 
3.3%
1
 
3.3%
1
 
3.3%
1
 
3.3%
1
 
3.3%
Punctuation
ValueCountFrequency (%)
9
50.0%
9
50.0%
CJK
ValueCountFrequency (%)
6
33.3%
3
16.7%
3
16.7%
3
16.7%
1
 
5.6%
1
 
5.6%
1
 
5.6%
Number Forms
ValueCountFrequency (%)
4
66.7%
2
33.3%
Geometric Shapes
ValueCountFrequency (%)
2
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
1
100.0%

항목1
Text

MISSING 

Distinct146
Distinct (%)2.2%
Missing307
Missing (%)4.4%
Memory size54.5 KiB
2023-12-12T23:42:01.090169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length4
Mean length3.6989619
Min length1

Characters and Unicode

Total characters24587
Distinct characters157
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)0.7%

Sample

1st row출석
2nd rowrwewer
3rd row4-
4th row4-
5th row중간조사
ValueCountFrequency (%)
중간시험 2749
39.9%
출석 1718
25.0%
중간고사 890
 
12.9%
출석평가 268
 
3.9%
직무능력평가1 163
 
2.4%
중간 132
 
1.9%
중간평가 107
 
1.6%
exam 68
 
1.0%
mid 49
 
0.7%
term 49
 
0.7%
Other values (140) 691
 
10.0%
2023-12-12T23:42:01.598867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3921
15.9%
3918
15.9%
2798
11.4%
2792
11.4%
2087
8.5%
2069
8.4%
916
 
3.7%
908
 
3.7%
661
 
2.7%
654
 
2.7%
Other values (147) 3863
15.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22808
92.8%
Lowercase Letter 1034
 
4.2%
Decimal Number 250
 
1.0%
Space Separator 244
 
1.0%
Uppercase Letter 175
 
0.7%
Dash Punctuation 22
 
0.1%
Close Punctuation 18
 
0.1%
Open Punctuation 18
 
0.1%
Other Punctuation 18
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3921
17.2%
3918
17.2%
2798
12.3%
2792
12.2%
2087
9.2%
2069
9.1%
916
 
4.0%
908
 
4.0%
661
 
2.9%
654
 
2.9%
Other values (118) 2084
9.1%
Lowercase Letter
ValueCountFrequency (%)
e 197
19.1%
m 135
13.1%
t 132
12.8%
a 114
11.0%
d 112
10.8%
n 91
8.8%
r 69
 
6.7%
i 68
 
6.6%
x 68
 
6.6%
c 45
 
4.4%
Other values (2) 3
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
M 67
38.3%
A 52
29.7%
E 30
17.1%
T 25
 
14.3%
F 1
 
0.6%
Decimal Number
ValueCountFrequency (%)
1 244
97.6%
4 3
 
1.2%
0 2
 
0.8%
3 1
 
0.4%
Other Punctuation
ValueCountFrequency (%)
/ 8
44.4%
, 5
27.8%
. 4
22.2%
% 1
 
5.6%
Space Separator
ValueCountFrequency (%)
244
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22808
92.8%
Latin 1209
 
4.9%
Common 570
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3921
17.2%
3918
17.2%
2798
12.3%
2792
12.2%
2087
9.2%
2069
9.1%
916
 
4.0%
908
 
4.0%
661
 
2.9%
654
 
2.9%
Other values (118) 2084
9.1%
Latin
ValueCountFrequency (%)
e 197
16.3%
m 135
11.2%
t 132
10.9%
a 114
9.4%
d 112
9.3%
n 91
7.5%
r 69
 
5.7%
i 68
 
5.6%
x 68
 
5.6%
M 67
 
5.5%
Other values (7) 156
12.9%
Common
ValueCountFrequency (%)
1 244
42.8%
244
42.8%
- 22
 
3.9%
) 18
 
3.2%
( 18
 
3.2%
/ 8
 
1.4%
, 5
 
0.9%
. 4
 
0.7%
4 3
 
0.5%
0 2
 
0.4%
Other values (2) 2
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22808
92.8%
ASCII 1779
 
7.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
3921
17.2%
3918
17.2%
2798
12.3%
2792
12.2%
2087
9.2%
2069
9.1%
916
 
4.0%
908
 
4.0%
661
 
2.9%
654
 
2.9%
Other values (118) 2084
9.1%
ASCII
ValueCountFrequency (%)
1 244
13.7%
244
13.7%
e 197
11.1%
m 135
 
7.6%
t 132
 
7.4%
a 114
 
6.4%
d 112
 
6.3%
n 91
 
5.1%
r 69
 
3.9%
i 68
 
3.8%
Other values (19) 373
21.0%

항목2
Text

MISSING 

Distinct215
Distinct (%)3.3%
Missing360
Missing (%)5.2%
Memory size54.5 KiB
2023-12-12T23:42:01.927079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length4
Mean length4.2682742
Min length1

Characters and Unicode

Total characters28145
Distinct characters204
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)0.9%

Sample

1st row과제
2nd rowrwerwer
3rd row기말고사
4th row기말고사
5th row기말고사
ValueCountFrequency (%)
기말시험 2741
39.7%
기말고사 902
 
13.1%
중간고사 416
 
6.0%
과제 310
 
4.5%
직무능력평가1 255
 
3.7%
직무능력평가2 165
 
2.4%
중간 158
 
2.3%
중간평가 140
 
2.0%
기말 127
 
1.8%
기말평가 104
 
1.5%
Other values (205) 1592
23.0%
2023-12-12T23:42:02.429108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3992
14.2%
3920
13.9%
2826
 
10.0%
2826
 
10.0%
1385
 
4.9%
1377
 
4.9%
1160
 
4.1%
1151
 
4.1%
811
 
2.9%
808
 
2.9%
Other values (194) 7889
28.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25785
91.6%
Lowercase Letter 907
 
3.2%
Decimal Number 821
 
2.9%
Space Separator 322
 
1.1%
Uppercase Letter 202
 
0.7%
Other Punctuation 54
 
0.2%
Close Punctuation 25
 
0.1%
Open Punctuation 25
 
0.1%
Dash Punctuation 2
 
< 0.1%
Other Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3992
15.5%
3920
15.2%
2826
11.0%
2826
11.0%
1385
 
5.4%
1377
 
5.3%
1160
 
4.5%
1151
 
4.5%
811
 
3.1%
808
 
3.1%
Other values (146) 5529
21.4%
Lowercase Letter
ValueCountFrequency (%)
a 139
15.3%
m 95
10.5%
i 91
10.0%
n 90
9.9%
e 82
9.0%
t 65
7.2%
x 59
6.5%
o 52
 
5.7%
l 52
 
5.7%
r 50
 
5.5%
Other values (10) 132
14.6%
Uppercase Letter
ValueCountFrequency (%)
E 57
28.2%
F 52
25.7%
H 20
 
9.9%
M 16
 
7.9%
A 16
 
7.9%
T 13
 
6.4%
B 7
 
3.5%
P 6
 
3.0%
R 5
 
2.5%
C 4
 
2.0%
Other values (4) 6
 
3.0%
Decimal Number
ValueCountFrequency (%)
1 558
68.0%
2 251
30.6%
3 5
 
0.6%
0 4
 
0.5%
4 3
 
0.4%
Other Punctuation
ValueCountFrequency (%)
/ 33
61.1%
, 16
29.6%
% 3
 
5.6%
. 2
 
3.7%
Space Separator
ValueCountFrequency (%)
322
100.0%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Symbol
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25785
91.6%
Common 1251
 
4.4%
Latin 1109
 
3.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3992
15.5%
3920
15.2%
2826
11.0%
2826
11.0%
1385
 
5.4%
1377
 
5.3%
1160
 
4.5%
1151
 
4.5%
811
 
3.1%
808
 
3.1%
Other values (146) 5529
21.4%
Latin
ValueCountFrequency (%)
a 139
12.5%
m 95
 
8.6%
i 91
 
8.2%
n 90
 
8.1%
e 82
 
7.4%
t 65
 
5.9%
x 59
 
5.3%
E 57
 
5.1%
o 52
 
4.7%
l 52
 
4.7%
Other values (24) 327
29.5%
Common
ValueCountFrequency (%)
1 558
44.6%
322
25.7%
2 251
20.1%
/ 33
 
2.6%
) 25
 
2.0%
( 25
 
2.0%
, 16
 
1.3%
3 5
 
0.4%
0 4
 
0.3%
4 3
 
0.2%
Other values (4) 9
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25785
91.6%
ASCII 2358
 
8.4%
Geometric Shapes 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
3992
15.5%
3920
15.2%
2826
11.0%
2826
11.0%
1385
 
5.4%
1377
 
5.3%
1160
 
4.5%
1151
 
4.5%
811
 
3.1%
808
 
3.1%
Other values (146) 5529
21.4%
ASCII
ValueCountFrequency (%)
1 558
23.7%
322
13.7%
2 251
10.6%
a 139
 
5.9%
m 95
 
4.0%
i 91
 
3.9%
n 90
 
3.8%
e 82
 
3.5%
t 65
 
2.8%
x 59
 
2.5%
Other values (37) 606
25.7%
Geometric Shapes
ValueCountFrequency (%)
2
100.0%

항목3
Text

MISSING 

Distinct231
Distinct (%)3.6%
Missing448
Missing (%)6.4%
Memory size54.5 KiB
2023-12-12T23:42:02.766982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length2
Mean length3.2075008
Min length1

Characters and Unicode

Total characters20868
Distinct characters193
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)1.0%

Sample

1st row중간
2nd rowwrewr
3rd row과제물
4th row과제물
5th row수시고사
ValueCountFrequency (%)
출석 3393
50.2%
중간고사 383
 
5.7%
기말고사 356
 
5.3%
과제 264
 
3.9%
직무능력평가2 235
 
3.5%
직무능력평가3 152
 
2.2%
기말평가 140
 
2.1%
중간 126
 
1.9%
기말 125
 
1.8%
과제물 92
 
1.4%
Other values (206) 1491
22.1%
2023-12-12T23:42:03.276883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3527
16.9%
3480
16.7%
1032
 
4.9%
1020
 
4.9%
854
 
4.1%
821
 
3.9%
761
 
3.6%
735
 
3.5%
676
 
3.2%
674
 
3.2%
Other values (183) 7288
34.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18622
89.2%
Lowercase Letter 881
 
4.2%
Decimal Number 793
 
3.8%
Space Separator 293
 
1.4%
Uppercase Letter 159
 
0.8%
Other Punctuation 91
 
0.4%
Open Punctuation 13
 
0.1%
Close Punctuation 12
 
0.1%
Dash Punctuation 2
 
< 0.1%
Other Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3527
18.9%
3480
18.7%
1032
 
5.5%
1020
 
5.5%
854
 
4.6%
821
 
4.4%
761
 
4.1%
735
 
3.9%
676
 
3.6%
674
 
3.6%
Other values (138) 5042
27.1%
Lowercase Letter
ValueCountFrequency (%)
e 144
16.3%
n 124
14.1%
t 122
13.8%
a 108
12.3%
d 70
7.9%
m 68
7.7%
c 51
 
5.8%
i 42
 
4.8%
x 37
 
4.2%
r 34
 
3.9%
Other values (10) 81
9.2%
Uppercase Letter
ValueCountFrequency (%)
A 51
32.1%
E 32
20.1%
F 25
15.7%
M 19
 
11.9%
H 12
 
7.5%
T 7
 
4.4%
C 6
 
3.8%
D 5
 
3.1%
L 1
 
0.6%
R 1
 
0.6%
Decimal Number
ValueCountFrequency (%)
2 536
67.6%
3 218
27.5%
1 27
 
3.4%
0 7
 
0.9%
4 5
 
0.6%
Other Punctuation
ValueCountFrequency (%)
/ 48
52.7%
, 32
35.2%
% 6
 
6.6%
. 4
 
4.4%
& 1
 
1.1%
Space Separator
ValueCountFrequency (%)
293
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Symbol
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18622
89.2%
Common 1206
 
5.8%
Latin 1040
 
5.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3527
18.9%
3480
18.7%
1032
 
5.5%
1020
 
5.5%
854
 
4.6%
821
 
4.4%
761
 
4.1%
735
 
3.9%
676
 
3.6%
674
 
3.6%
Other values (138) 5042
27.1%
Latin
ValueCountFrequency (%)
e 144
13.8%
n 124
11.9%
t 122
11.7%
a 108
10.4%
d 70
 
6.7%
m 68
 
6.5%
A 51
 
4.9%
c 51
 
4.9%
i 42
 
4.0%
x 37
 
3.6%
Other values (20) 223
21.4%
Common
ValueCountFrequency (%)
2 536
44.4%
293
24.3%
3 218
18.1%
/ 48
 
4.0%
, 32
 
2.7%
1 27
 
2.2%
( 13
 
1.1%
) 12
 
1.0%
0 7
 
0.6%
% 6
 
0.5%
Other values (5) 14
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18622
89.2%
ASCII 2244
 
10.8%
Geometric Shapes 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
3527
18.9%
3480
18.7%
1032
 
5.5%
1020
 
5.5%
854
 
4.6%
821
 
4.4%
761
 
4.1%
735
 
3.9%
676
 
3.6%
674
 
3.6%
Other values (138) 5042
27.1%
ASCII
ValueCountFrequency (%)
2 536
23.9%
293
13.1%
3 218
9.7%
e 144
 
6.4%
n 124
 
5.5%
t 122
 
5.4%
a 108
 
4.8%
d 70
 
3.1%
m 68
 
3.0%
A 51
 
2.3%
Other values (34) 510
22.7%
Geometric Shapes
ValueCountFrequency (%)
2
100.0%

항목4
Text

MISSING 

Distinct233
Distinct (%)3.7%
Missing723
Missing (%)10.4%
Memory size54.5 KiB
2023-12-12T23:42:03.605170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length2
Mean length2.980581
Min length1

Characters and Unicode

Total characters18572
Distinct characters178
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique68 ?
Unique (%)1.1%

Sample

1st row기말
2nd rowwerewrew
3rd row출결
4th row출결
5th row과제물
ValueCountFrequency (%)
과제 3339
50.9%
출석 574
 
8.8%
기말고사 417
 
6.4%
직무능력평가3 196
 
3.0%
기말 152
 
2.3%
과제물 133
 
2.0%
레포트 128
 
2.0%
기타 82
 
1.3%
72
 
1.1%
발표 59
 
0.9%
Other values (207) 1405
21.4%
2023-12-12T23:42:04.111602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3660
19.7%
3655
19.7%
730
 
3.9%
685
 
3.7%
631
 
3.4%
620
 
3.3%
602
 
3.2%
575
 
3.1%
512
 
2.8%
464
 
2.5%
Other values (168) 6438
34.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16636
89.6%
Lowercase Letter 805
 
4.3%
Decimal Number 466
 
2.5%
Space Separator 359
 
1.9%
Uppercase Letter 144
 
0.8%
Other Punctuation 117
 
0.6%
Open Punctuation 21
 
0.1%
Close Punctuation 19
 
0.1%
Dash Punctuation 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3660
22.0%
3655
22.0%
730
 
4.4%
685
 
4.1%
631
 
3.8%
620
 
3.7%
602
 
3.6%
575
 
3.5%
512
 
3.1%
464
 
2.8%
Other values (130) 4502
27.1%
Lowercase Letter
ValueCountFrequency (%)
t 175
21.7%
i 97
12.0%
e 84
10.4%
n 68
 
8.4%
a 65
 
8.1%
m 56
 
7.0%
d 50
 
6.2%
u 49
 
6.1%
s 40
 
5.0%
x 34
 
4.2%
Other values (8) 87
10.8%
Uppercase Letter
ValueCountFrequency (%)
A 68
47.2%
E 34
23.6%
F 30
20.8%
H 4
 
2.8%
T 4
 
2.8%
R 3
 
2.1%
D 1
 
0.7%
Decimal Number
ValueCountFrequency (%)
3 426
91.4%
2 24
 
5.2%
4 9
 
1.9%
1 4
 
0.9%
0 3
 
0.6%
Other Punctuation
ValueCountFrequency (%)
/ 57
48.7%
, 55
47.0%
% 3
 
2.6%
. 2
 
1.7%
Space Separator
ValueCountFrequency (%)
359
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16636
89.6%
Common 987
 
5.3%
Latin 949
 
5.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3660
22.0%
3655
22.0%
730
 
4.4%
685
 
4.1%
631
 
3.8%
620
 
3.7%
602
 
3.6%
575
 
3.5%
512
 
3.1%
464
 
2.8%
Other values (130) 4502
27.1%
Latin
ValueCountFrequency (%)
t 175
18.4%
i 97
10.2%
e 84
8.9%
n 68
 
7.2%
A 68
 
7.2%
a 65
 
6.8%
m 56
 
5.9%
d 50
 
5.3%
u 49
 
5.2%
s 40
 
4.2%
Other values (15) 197
20.8%
Common
ValueCountFrequency (%)
3 426
43.2%
359
36.4%
/ 57
 
5.8%
, 55
 
5.6%
2 24
 
2.4%
( 21
 
2.1%
) 19
 
1.9%
4 9
 
0.9%
- 5
 
0.5%
1 4
 
0.4%
Other values (3) 8
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16634
89.6%
ASCII 1936
 
10.4%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
3660
22.0%
3655
22.0%
730
 
4.4%
685
 
4.1%
631
 
3.8%
620
 
3.7%
602
 
3.6%
575
 
3.5%
512
 
3.1%
464
 
2.8%
Other values (129) 4500
27.1%
ASCII
ValueCountFrequency (%)
3 426
22.0%
359
18.5%
t 175
 
9.0%
i 97
 
5.0%
e 84
 
4.3%
n 68
 
3.5%
A 68
 
3.5%
a 65
 
3.4%
/ 57
 
2.9%
m 56
 
2.9%
Other values (28) 481
24.8%
Compat Jamo
ValueCountFrequency (%)
2
100.0%

항목5
Text

MISSING 

Distinct20
Distinct (%)50.0%
Missing6914
Missing (%)99.4%
Memory size54.5 KiB
2023-12-12T23:42:04.337695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length3.9
Min length2

Characters and Unicode

Total characters156
Distinct characters51
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)27.5%

Sample

1st rowrwer
2nd row기타
3rd row기타
4th row학습태도(발표)
5th row기말고사
ValueCountFrequency (%)
출석 10
23.8%
기말고사 7
16.7%
수업태도 3
 
7.1%
출석사항 2
 
4.8%
학습태도 2
 
4.8%
기타 2
 
4.8%
관련자격획득 2
 
4.8%
컴퓨터일반 2
 
4.8%
이론 2
 
4.8%
실기 1
 
2.4%
Other values (9) 9
21.4%
2023-12-12T23:42:05.039962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14
 
9.0%
13
 
8.3%
12
 
7.7%
11
 
7.1%
9
 
5.8%
8
 
5.1%
6
 
3.8%
6
 
3.8%
6
 
3.8%
3
 
1.9%
Other values (41) 68
43.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 136
87.2%
Lowercase Letter 7
 
4.5%
Space Separator 6
 
3.8%
Decimal Number 2
 
1.3%
Other Punctuation 2
 
1.3%
Close Punctuation 1
 
0.6%
Open Punctuation 1
 
0.6%
Uppercase Letter 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
14
 
10.3%
13
 
9.6%
12
 
8.8%
11
 
8.1%
9
 
6.6%
8
 
5.9%
6
 
4.4%
6
 
4.4%
3
 
2.2%
3
 
2.2%
Other values (27) 51
37.5%
Lowercase Letter
ValueCountFrequency (%)
r 2
28.6%
i 1
14.3%
z 1
14.3%
u 1
14.3%
e 1
14.3%
w 1
14.3%
Decimal Number
ValueCountFrequency (%)
0 1
50.0%
2 1
50.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
50.0%
% 1
50.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
Q 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 136
87.2%
Common 12
 
7.7%
Latin 8
 
5.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
14
 
10.3%
13
 
9.6%
12
 
8.8%
11
 
8.1%
9
 
6.6%
8
 
5.9%
6
 
4.4%
6
 
4.4%
3
 
2.2%
3
 
2.2%
Other values (27) 51
37.5%
Common
ValueCountFrequency (%)
6
50.0%
0 1
 
8.3%
2 1
 
8.3%
) 1
 
8.3%
( 1
 
8.3%
/ 1
 
8.3%
% 1
 
8.3%
Latin
ValueCountFrequency (%)
r 2
25.0%
i 1
12.5%
z 1
12.5%
u 1
12.5%
Q 1
12.5%
e 1
12.5%
w 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 136
87.2%
ASCII 20
 
12.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
14
 
10.3%
13
 
9.6%
12
 
8.8%
11
 
8.1%
9
 
6.6%
8
 
5.9%
6
 
4.4%
6
 
4.4%
3
 
2.2%
3
 
2.2%
Other values (27) 51
37.5%
ASCII
ValueCountFrequency (%)
6
30.0%
r 2
 
10.0%
0 1
 
5.0%
2 1
 
5.0%
) 1
 
5.0%
( 1
 
5.0%
i 1
 
5.0%
z 1
 
5.0%
u 1
 
5.0%
Q 1
 
5.0%
Other values (4) 4
20.0%

항목6
Text

MISSING 

Distinct6
Distinct (%)60.0%
Missing6944
Missing (%)99.9%
Memory size54.5 KiB
2023-12-12T23:42:05.204808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.8
Min length2

Characters and Unicode

Total characters38
Distinct characters21
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

Unique3 ?
Unique (%)30.0%

Sample

1st rowwer
2nd row출석
3rd row출석
4th row합계100%
5th row수업 태도
ValueCountFrequency (%)
출석 3
23.1%
평소태도 2
15.4%
엑셀 2
15.4%
이론 2
15.4%
wer 1
 
7.7%
합계100 1
 
7.7%
수업 1
 
7.7%
태도 1
 
7.7%
2023-12-12T23:42:05.571125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3
 
7.9%
3
 
7.9%
3
 
7.9%
3
 
7.9%
3
 
7.9%
0 2
 
5.3%
2
 
5.3%
2
 
5.3%
2
 
5.3%
2
 
5.3%
Other values (11) 13
34.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 28
73.7%
Space Separator 3
 
7.9%
Decimal Number 3
 
7.9%
Lowercase Letter 3
 
7.9%
Other Punctuation 1
 
2.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3
10.7%
3
10.7%
3
10.7%
3
10.7%
2
7.1%
2
7.1%
2
7.1%
2
7.1%
2
7.1%
2
7.1%
Other values (4) 4
14.3%
Lowercase Letter
ValueCountFrequency (%)
w 1
33.3%
e 1
33.3%
r 1
33.3%
Decimal Number
ValueCountFrequency (%)
0 2
66.7%
1 1
33.3%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
% 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 28
73.7%
Common 7
 
18.4%
Latin 3
 
7.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3
10.7%
3
10.7%
3
10.7%
3
10.7%
2
7.1%
2
7.1%
2
7.1%
2
7.1%
2
7.1%
2
7.1%
Other values (4) 4
14.3%
Common
ValueCountFrequency (%)
3
42.9%
0 2
28.6%
1 1
 
14.3%
% 1
 
14.3%
Latin
ValueCountFrequency (%)
w 1
33.3%
e 1
33.3%
r 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 28
73.7%
ASCII 10
 
26.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
3
10.7%
3
10.7%
3
10.7%
3
10.7%
2
7.1%
2
7.1%
2
7.1%
2
7.1%
2
7.1%
2
7.1%
Other values (4) 4
14.3%
ASCII
ValueCountFrequency (%)
3
30.0%
0 2
20.0%
w 1
 
10.0%
e 1
 
10.0%
r 1
 
10.0%
1 1
 
10.0%
% 1
 
10.0%

항목7
Text

MISSING 

Distinct3
Distinct (%)60.0%
Missing6949
Missing (%)99.9%
Memory size54.5 KiB
2023-12-12T23:42:05.721783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.2
Min length2

Characters and Unicode

Total characters11
Distinct characters7
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

Unique1 ?
Unique (%)20.0%

Sample

1st rowwer
2nd row합계
3rd row과제
4th row합계
5th row과제
ValueCountFrequency (%)
합계 2
40.0%
과제 2
40.0%
wer 1
20.0%
2023-12-12T23:42:06.003074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2
18.2%
2
18.2%
2
18.2%
2
18.2%
w 1
9.1%
e 1
9.1%
r 1
9.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8
72.7%
Lowercase Letter 3
 
27.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2
25.0%
2
25.0%
2
25.0%
2
25.0%
Lowercase Letter
ValueCountFrequency (%)
w 1
33.3%
e 1
33.3%
r 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8
72.7%
Latin 3
 
27.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2
25.0%
2
25.0%
2
25.0%
2
25.0%
Latin
ValueCountFrequency (%)
w 1
33.3%
e 1
33.3%
r 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8
72.7%
ASCII 3
 
27.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2
25.0%
2
25.0%
2
25.0%
2
25.0%
ASCII
ValueCountFrequency (%)
w 1
33.3%
e 1
33.3%
r 1
33.3%

내용1
Categorical

IMBALANCE 

Distinct33
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size54.5 KiB
30%
3335 
20%
1246 
20
1054 
30
579 
<NA>
387 
Other values (28)
353 

Length

Max length17
Median length3
Mean length2.8035663
Min length1

Unique

Unique4 ?
Unique (%)0.1%

Sample

1st row20
2nd rowwerwerwe
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
30% 3335
48.0%
20% 1246
 
17.9%
20 1054
 
15.2%
30 579
 
8.3%
<NA> 387
 
5.6%
50% 53
 
0.8%
40 52
 
0.7%
40% 47
 
0.7%
100 41
 
0.6%
25% 21
 
0.3%
Other values (23) 139
 
2.0%

Length

2023-12-12T23:42:06.166029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
30 3914
56.3%
20 2300
33.1%
na 387
 
5.6%
40 99
 
1.4%
50 63
 
0.9%
100 44
 
0.6%
25 40
 
0.6%
10 33
 
0.5%
0 22
 
0.3%
70 10
 
0.1%
Other values (17) 46
 
0.7%

내용2
Categorical

IMBALANCE 

Distinct34
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size54.5 KiB
30%
3985 
30
938 
20%
516 
20
501 
<NA>
425 
Other values (29)
589 

Length

Max length12
Median length3
Mean length2.8078804
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row10
2nd rowwrewerwerw
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
30% 3985
57.3%
30 938
 
13.5%
20% 516
 
7.4%
20 501
 
7.2%
<NA> 425
 
6.1%
40 164
 
2.4%
40% 122
 
1.8%
25% 59
 
0.8%
25 49
 
0.7%
50% 30
 
0.4%
Other values (24) 165
 
2.4%

Length

2023-12-12T23:42:06.306267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
30 4923
70.8%
20 1017
 
14.6%
na 425
 
6.1%
40 286
 
4.1%
25 108
 
1.6%
50 46
 
0.7%
10 33
 
0.5%
60 27
 
0.4%
80 25
 
0.4%
0 19
 
0.3%
Other values (14) 48
 
0.7%

내용3
Categorical

IMBALANCE 

Distinct28
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size54.5 KiB
20%
3517 
30%
1006 
30
765 
20
726 
<NA>
502 
Other values (23)
438 

Length

Max length13
Median length3
Mean length2.8277251
Min length1

Unique

Unique4 ?
Unique (%)0.1%

Sample

1st row30
2nd rowwrwr
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
20% 3517
50.6%
30% 1006
 
14.5%
30 765
 
11.0%
20 726
 
10.4%
<NA> 502
 
7.2%
40 118
 
1.7%
40% 74
 
1.1%
25% 44
 
0.6%
25 39
 
0.6%
10% 34
 
0.5%
Other values (18) 129
 
1.9%

Length

2023-12-12T23:42:06.417426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20 4243
61.0%
30 1771
25.5%
na 502
 
7.2%
40 192
 
2.8%
25 83
 
1.2%
10 54
 
0.8%
50 45
 
0.6%
15 20
 
0.3%
26 12
 
0.2%
80 10
 
0.1%
Other values (12) 26
 
0.4%

내용4
Categorical

IMBALANCE 

Distinct25
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size54.5 KiB
20%
3922 
20
960 
<NA>
780 
30%
499 
30
493 
Other values (20)
 
300

Length

Max length6
Median length3
Mean length2.8852459
Min length1

Unique

Unique6 ?
Unique (%)0.1%

Sample

1st row40
2nd rowwerwer
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
20% 3922
56.4%
20 960
 
13.8%
<NA> 780
 
11.2%
30% 499
 
7.2%
30 493
 
7.1%
10% 66
 
0.9%
10 56
 
0.8%
40% 56
 
0.8%
40 46
 
0.7%
15% 16
 
0.2%
Other values (15) 60
 
0.9%

Length

2023-12-12T23:42:06.536517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20 4882
70.2%
30 992
 
14.3%
na 780
 
11.2%
10 122
 
1.8%
40 102
 
1.5%
15 19
 
0.3%
50 18
 
0.3%
25 14
 
0.2%
24 12
 
0.2%
3
 
< 0.1%
Other values (7) 10
 
0.1%

내용5
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.5 KiB
<NA>
6928 
20%
 
11
10%
 
4
10
 
4
30%
 
2
Other values (4)
 
5

Length

Max length5
Median length4
Mean length3.9955421
Min length2

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd rowwrewr
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 6928
99.6%
20% 11
 
0.2%
10% 4
 
0.1%
10 4
 
0.1%
30% 2
 
< 0.1%
5% 2
 
< 0.1%
wrewr 1
 
< 0.1%
25% 1
 
< 0.1%
0% 1
 
< 0.1%

Length

2023-12-12T23:42:06.647859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:42:06.760912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6928
99.6%
20 11
 
0.2%
10 8
 
0.1%
30 2
 
< 0.1%
5 2
 
< 0.1%
wrewr 1
 
< 0.1%
25 1
 
< 0.1%
0 1
 
< 0.1%

내용6
Text

MISSING 

Distinct3
Distinct (%)50.0%
Missing6948
Missing (%)99.9%
Memory size54.5 KiB
2023-12-12T23:42:06.862918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3
Min length2

Characters and Unicode

Total characters18
Distinct characters7
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)16.7%

Sample

1st rowwrwer
2nd row20%
3rd row20%
4th row20%
5th row5%
ValueCountFrequency (%)
20 3
50.0%
5 2
33.3%
wrwer 1
 
16.7%
2023-12-12T23:42:07.132600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
% 5
27.8%
2 3
16.7%
0 3
16.7%
5 2
 
11.1%
w 2
 
11.1%
r 2
 
11.1%
e 1
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8
44.4%
Other Punctuation 5
27.8%
Lowercase Letter 5
27.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 3
37.5%
0 3
37.5%
5 2
25.0%
Lowercase Letter
ValueCountFrequency (%)
w 2
40.0%
r 2
40.0%
e 1
20.0%
Other Punctuation
ValueCountFrequency (%)
% 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13
72.2%
Latin 5
 
27.8%

Most frequent character per script

Common
ValueCountFrequency (%)
% 5
38.5%
2 3
23.1%
0 3
23.1%
5 2
 
15.4%
Latin
ValueCountFrequency (%)
w 2
40.0%
r 2
40.0%
e 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
% 5
27.8%
2 3
16.7%
0 3
16.7%
5 2
 
11.1%
w 2
 
11.1%
r 2
 
11.1%
e 1
 
5.6%

내용7
Text

MISSING 

Distinct3
Distinct (%)60.0%
Missing6949
Missing (%)99.9%
Memory size54.5 KiB
2023-12-12T23:42:07.257428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length4
Mean length4.4
Min length3

Characters and Unicode

Total characters22
Distinct characters6
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)20.0%

Sample

1st rowwerewrwe
2nd row100%
3rd row10%
4th row100%
5th row10%
ValueCountFrequency (%)
100 2
40.0%
10 2
40.0%
werewrwe 1
20.0%
2023-12-12T23:42:07.488077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6
27.3%
1 4
18.2%
% 4
18.2%
w 3
13.6%
e 3
13.6%
r 2
 
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10
45.5%
Lowercase Letter 8
36.4%
Other Punctuation 4
 
18.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 3
37.5%
e 3
37.5%
r 2
25.0%
Decimal Number
ValueCountFrequency (%)
0 6
60.0%
1 4
40.0%
Other Punctuation
ValueCountFrequency (%)
% 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14
63.6%
Latin 8
36.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6
42.9%
1 4
28.6%
% 4
28.6%
Latin
ValueCountFrequency (%)
w 3
37.5%
e 3
37.5%
r 2
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6
27.3%
1 4
18.2%
% 4
18.2%
w 3
13.6%
e 3
13.6%
r 2
 
9.1%
Distinct6933
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size54.5 KiB
2023-12-12T23:42:07.729201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length21.295945
Min length21

Characters and Unicode

Total characters148092
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

Unique6912 ?
Unique (%)99.4%

Sample

1st row2002-03-09 오전 9:17:21
2nd row2005-03-04 오후 3:35:49
3rd row2005-08-12 오후 6:22:23
4th row2005-03-16 오후 3:33:00
5th row2005-03-16 오후 3:33:00
ValueCountFrequency (%)
오후 4973
 
23.8%
오전 1981
 
9.5%
2020-08-18 94
 
0.5%
2012-02-24 91
 
0.4%
2012-08-17 88
 
0.4%
2006-02-24 86
 
0.4%
2013-02-28 84
 
0.4%
2006-02-23 82
 
0.4%
2009-02-27 74
 
0.4%
2011-08-26 73
 
0.3%
Other values (6981) 13236
63.4%
2023-12-12T23:42:08.117648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 23341
15.8%
2 18200
12.3%
1 15232
10.3%
- 13908
9.4%
13908
9.4%
: 13908
9.4%
3 7751
 
5.2%
6954
 
4.7%
8 6048
 
4.1%
4 5906
 
4.0%
Other values (6) 22936
15.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 92460
62.4%
Dash Punctuation 13908
 
9.4%
Space Separator 13908
 
9.4%
Other Punctuation 13908
 
9.4%
Other Letter 13908
 
9.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 23341
25.2%
2 18200
19.7%
1 15232
16.5%
3 7751
 
8.4%
8 6048
 
6.5%
4 5906
 
6.4%
5 5732
 
6.2%
9 3946
 
4.3%
7 3294
 
3.6%
6 3010
 
3.3%
Other Letter
ValueCountFrequency (%)
6954
50.0%
4973
35.8%
1981
 
14.2%
Dash Punctuation
ValueCountFrequency (%)
- 13908
100.0%
Space Separator
ValueCountFrequency (%)
13908
100.0%
Other Punctuation
ValueCountFrequency (%)
: 13908
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 134184
90.6%
Hangul 13908
 
9.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 23341
17.4%
2 18200
13.6%
1 15232
11.4%
- 13908
10.4%
13908
10.4%
: 13908
10.4%
3 7751
 
5.8%
8 6048
 
4.5%
4 5906
 
4.4%
5 5732
 
4.3%
Other values (3) 10250
7.6%
Hangul
ValueCountFrequency (%)
6954
50.0%
4973
35.8%
1981
 
14.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 134184
90.6%
Hangul 13908
 
9.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 23341
17.4%
2 18200
13.6%
1 15232
11.4%
- 13908
10.4%
13908
10.4%
: 13908
10.4%
3 7751
 
5.8%
8 6048
 
4.5%
4 5906
 
4.4%
5 5732
 
4.3%
Other values (3) 10250
7.6%
Hangul
ValueCountFrequency (%)
6954
50.0%
4973
35.8%
1981
 
14.2%

Sample

년도학기학기구분과목이수구분학점이론시수실습시수주교재참고문헌강의목적및개요항목1항목2항목3항목4항목5항목6항목7내용1내용2내용3내용4내용5내용6내용7사용날짜
0200211B10002A2222영어기초영어기초문법영어기초문법출석과제중간기말<NA><NA><NA>20103040<NA><NA><NA>2002-03-09 오전 9:17:21
1200511C10002A73<NA><NA>wrwrewerwerwerwrewrwrerwewerrwerwerwrewrwerewrewrwerwerwerwerwerwewrewerwerwwrwrwerwerwrewrwrwerwerewrwe2005-03-04 오후 3:35:49
2200521C40028A7212김성혁, 관광마케팅의 이해, 백산출판사, 2003.최태광, 관광마케팅, 백산출판사, 2002.숙박업, 항공업, 여행업, 주제공원, 리조트, 유람선, 외식업 등 서비스를 제공하는 관광기업의 기초적인 마케팅 지식을 함양하며, 특히 고객만족 경영, 내부마케팅 등 새로운 분야의 이론을 숙지하도록 한다<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2005-08-12 오후 6:22:23
3200511A60001A13222-------------3---1--------4-<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2005-03-16 오후 3:33:00
4200511A60001B13222-------------3---1--------4-<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2005-03-16 오후 3:33:00
5200511C50003A3212<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2005-06-16 오후 1:35:07
6200511C50003B3212<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2005-06-16 오후 1:35:07
7200521C70015A722012<NA>121212<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2005-08-12 오후 1:25:01
8200521C70015B722012<NA>12의목적테스트강의목적테스트강의목적테스트<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2005-08-12 오후 1:25:33
9200521C50002B7212<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2005-08-15 오후 11:20:31
년도학기학기구분과목이수구분학점이론시수실습시수주교재참고문헌강의목적및개요항목1항목2항목3항목4항목5항목6항목7내용1내용2내용3내용4내용5내용6내용7사용날짜
6944202021N07046A60330대한민국 조리기능장(양식), 권오천/송수익, 2016, 에듀팩토리<NA>서양핫푸드실무 과목은 체계적인 이론을 정립하고, 호텔과 레스토랑에서 사용 빈도가 높은 식재료를 가지고 현장과 같은 메뉴구성과 레시피를 기반으로, 산업체 현장에서 사용하는 프랑스식 더운요리의 코스메뉴를 직접 체험하여 전문적인 기능을 연마함에 목표를 둔다.출석평가직무능력평가1직무능력평가2직무능력평가3<NA><NA><NA>20%20%30%30%<NA><NA><NA>2020-09-03 오후 3:48:21
6945202021C07273A60330호텔연회조리(2018, 윤수선 외 2명 공저)메뉴이론과 실무(2005, 권오천외 1인 공저), 서울프라자호텔 메뉴집외식연회실무실습 과목은 조리관련 전문지식과 숙련된 기능을 바탕으로 국내,외 특급호텔에서 행해지는 각종 파티형태의 메뉴를 터득하여, 현장에서 직접 활용할 수 있도록 하며 실제의 연회행사와 동일한 실무학습을 체험토록 한다.중간시험기말시험출석과제<NA><NA><NA>30%30%20%20%<NA><NA><NA>2020-09-03 오후 3:49:00
6946202021C07251B59220빔, 칠판베이직 영양학NEW 영양학<NA>영양소가 무엇인지 알고, 체내에서 영양소의 대사와 기능에 의해 인체의 건강이 어떻게 유지, 변화되어 가는지를 이해하고 급원식품과 영양섭취기준을 안다출석중간고사기말고사과제물<NA><NA><NA>20%30%30%20%<NA><NA><NA>2020-09-03 오후 4:33:10
6947202021C07264A59220원격강의시스템(동영상), 빔, 칠판꼭 알아야 할 식품위생 및 HACCP실무<NA><NA>출석중간고사기말고사과제물<NA><NA><NA>20%30%30%20%<NA><NA><NA>2020-09-03 오후 5:56:55
6948202021C07264B59220원격강의시스템(동영상), 빔, 칠판꼭 알아야 할 식품위생 및 HACCP실무<NA><NA>출석중간고사기말고사과제물<NA><NA><NA>20%30%30%20%<NA><NA><NA>2020-09-03 오후 5:57:16
6949202021C07265A59220원격강의시스템(동영상), 빔, 칠판(과학으로 풀어쓴) 식품과 조리원리에센스 조리원리<NA>식품재료별로 각각의 특성과 조리 시 변화과정의 과학적인 원리를 이해하고, 올바른 조리방법을 결정할 수 있는 능력과 조리에 대한 과학적인 관념을 갖도록 한다출석중간고사기말고사과제물<NA><NA><NA>20%30%30%20%<NA><NA><NA>2020-09-03 오후 6:39:06
6950202021C07265B59220원격강의시스템(동영상), 빔, 칠판(과학으로 풀어쓴) 식품과 조리원리에센스 조리원리<NA>식품재료별로 각각의 특성과 조리 시 변화과정의 과학적인 원리를 이해하고, 올바른 조리방법을 결정할 수 있는 능력과 조리에 대한 과학적인 관념을 갖도록 한다출석중간고사기말고사과제물<NA><NA><NA>20%30%30%20%<NA><NA><NA>2020-09-03 오후 6:39:24
6951202021C60257A59303(NCS 학습모듈)임의편집자료- 컴퓨터 - 프린터 - 복사기 - 문서작성도구 - 사무용 데이터베이스 소프트웨어 - 전화기 - 다과류(차, 음료, 간식) - 다과용품(찻잔, 다기 등)- 비서이미지를 위한 페이스 기본 메이크업재료현대사회에서 비서가 갖춰야 할 실체와 본질을 이해하고, 전화와 방문객을 경영진의 상황에 따라 맞이하고 선별ㆍ대응하여 업무를 지원하는 능력을 배양하여 현장에 즉시 투입가능한 비서의 자질과 실무능력을 양성한다.출석중간기말과제<NA><NA><NA>20303020<NA><NA><NA>2020-09-15 오전 8:36:40
6952202021C60257B59303NCS 학습모듈임의편집자료- 컴퓨터 - 프린터 - 복사기 - 문서작성도구 - 사무용 데이터베이스 소프트웨어 - 전화기 - 다과류(차, 음료, 간식) - 다과용품(찻잔, 다기 등)- 비서이미지를 위한 페이스 기본 메이크업재료현대사회에서 비서가 갖춰야 할 실체와 본질을 이해하고, 전화와 방문객을 경영진의 상황에 따라 맞이하고 선별ㆍ대응하여 업무를 지원하는 능력을 배양하여 현장에 즉시 투입가능한 비서의 자질과 실무능력을 양성한다.출석중간기말과제<NA><NA><NA>20303020<NA><NA><NA>2020-09-15 오전 8:35:07
6953202021C60265A59303NCS 학습모듈임의편집자료-틴트컬러밤인텐스-CC쿠션-브로우 펜슬 셋트-워터프루프 마스카라-색조 아이필레트 - 거울이 포함된 작업대 - 메이크업 공용 의자 - 의자 (높이 조절이 가능한 의자)<NA>출석중간고사기말고사과제<NA><NA><NA>20303020<NA><NA><NA>2020-09-15 오전 8:50:02