Overview

Dataset statistics

Number of variables5
Number of observations1479
Missing cells1338
Missing cells (%)18.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory60.8 KiB
Average record size in memory42.1 B

Variable types

Numeric2
Text3

Dataset

Description현대한국구술자료관 구술자료와 관련된 각주 정보
Author한국학중앙연구원
URLhttps://www.data.go.kr/data/15049071/fileData.do

Alerts

번호 is highly overall correlated with 각주번호High correlation
각주번호 is highly overall correlated with 번호High correlation
각주명 has 670 (45.3%) missing valuesMissing
각주내용 has 668 (45.2%) missing valuesMissing
번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 07:56:19.701316
Analysis finished2023-12-12 07:56:21.614884
Duration1.91 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1479
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean740
Minimum1
Maximum1479
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.1 KiB
2023-12-12T16:56:21.681684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile74.9
Q1370.5
median740
Q31109.5
95-th percentile1405.1
Maximum1479
Range1478
Interquartile range (IQR)739

Descriptive statistics

Standard deviation427.09484
Coefficient of variation (CV)0.57715519
Kurtosis-1.2
Mean740
Median Absolute Deviation (MAD)370
Skewness0
Sum1094460
Variance182410
MonotonicityStrictly increasing
2023-12-12T16:56:21.863730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
984 1
 
0.1%
993 1
 
0.1%
992 1
 
0.1%
991 1
 
0.1%
990 1
 
0.1%
989 1
 
0.1%
988 1
 
0.1%
987 1
 
0.1%
986 1
 
0.1%
Other values (1469) 1469
99.3%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1479 1
0.1%
1478 1
0.1%
1477 1
0.1%
1476 1
0.1%
1475 1
0.1%
1474 1
0.1%
1473 1
0.1%
1472 1
0.1%
1471 1
0.1%
1470 1
0.1%

각주번호
Real number (ℝ)

HIGH CORRELATION 

Distinct37
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.617309
Minimum1
Maximum37
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.1 KiB
2023-12-12T16:56:22.081781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q16
median12
Q317
95-th percentile33
Maximum37
Range36
Interquartile range (IQR)11

Descriptive statistics

Standard deviation9.0409307
Coefficient of variation (CV)0.71654984
Kurtosis0.34551211
Mean12.617309
Median Absolute Deviation (MAD)6
Skewness0.9072443
Sum18661
Variance81.738428
MonotonicityIncreasing
2023-12-12T16:56:22.210913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
12 109
 
7.4%
2 99
 
6.7%
1 97
 
6.6%
9 85
 
5.7%
10 79
 
5.3%
17 74
 
5.0%
3 73
 
4.9%
6 67
 
4.5%
15 62
 
4.2%
4 61
 
4.1%
Other values (27) 673
45.5%
ValueCountFrequency (%)
1 97
6.6%
2 99
6.7%
3 73
4.9%
4 61
4.1%
5 27
 
1.8%
6 67
4.5%
7 37
 
2.5%
8 61
4.1%
9 85
5.7%
10 79
5.3%
ValueCountFrequency (%)
37 14
0.9%
36 29
2.0%
35 9
 
0.6%
34 10
 
0.7%
33 21
1.4%
32 10
 
0.7%
31 12
0.8%
30 10
 
0.7%
29 12
0.8%
28 10
 
0.7%

캡션번호
Text

Distinct109
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size11.7 KiB
2023-12-12T16:56:22.541132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.7937796
Min length5

Characters and Unicode

Total characters8569
Distinct characters14
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

Unique10 ?
Unique (%)0.7%

Sample

1st rowcap_1
2nd rowcap_2
3rd rowcap_3
4th rowcap_4
5th rowcap_5
ValueCountFrequency (%)
cap_1 37
 
2.5%
cap_2 37
 
2.5%
cap_3 37
 
2.5%
cap_4 37
 
2.5%
cap_5 35
 
2.4%
cap_6 33
 
2.2%
cap_7 33
 
2.2%
cap_8 33
 
2.2%
cap_9 33
 
2.2%
cap_10 32
 
2.2%
Other values (99) 1132
76.5%
2023-12-12T16:56:23.084857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
c 1479
17.3%
a 1479
17.3%
p 1479
17.3%
_ 1479
17.3%
1 433
 
5.1%
2 379
 
4.4%
3 341
 
4.0%
4 311
 
3.6%
5 276
 
3.2%
6 229
 
2.7%
Other values (4) 684
8.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4437
51.8%
Decimal Number 2653
31.0%
Connector Punctuation 1479
 
17.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 433
16.3%
2 379
14.3%
3 341
12.9%
4 311
11.7%
5 276
10.4%
6 229
8.6%
7 202
7.6%
8 174
6.6%
9 166
 
6.3%
0 142
 
5.4%
Lowercase Letter
ValueCountFrequency (%)
c 1479
33.3%
a 1479
33.3%
p 1479
33.3%
Connector Punctuation
ValueCountFrequency (%)
_ 1479
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4437
51.8%
Common 4132
48.2%

Most frequent character per script

Common
ValueCountFrequency (%)
_ 1479
35.8%
1 433
 
10.5%
2 379
 
9.2%
3 341
 
8.3%
4 311
 
7.5%
5 276
 
6.7%
6 229
 
5.5%
7 202
 
4.9%
8 174
 
4.2%
9 166
 
4.0%
Latin
ValueCountFrequency (%)
c 1479
33.3%
a 1479
33.3%
p 1479
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8569
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
c 1479
17.3%
a 1479
17.3%
p 1479
17.3%
_ 1479
17.3%
1 433
 
5.1%
2 379
 
4.4%
3 341
 
4.0%
4 311
 
3.6%
5 276
 
3.2%
6 229
 
2.7%
Other values (4) 684
8.0%

각주명
Text

MISSING 

Distinct554
Distinct (%)68.5%
Missing670
Missing (%)45.3%
Memory size11.7 KiB
2023-12-12T16:56:23.465314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length111
Median length3
Mean length6.2855377
Min length1

Characters and Unicode

Total characters5085
Distinct characters555
Distinct categories10 ?
Distinct scripts5 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique456 ?
Unique (%)56.4%

Sample

1st row노태우
2nd row김대중
3rd row한일협정
4th row윤보선
5th row와이에스(YS)
ValueCountFrequency (%)
김대중 19
 
1.7%
구술자 18
 
1.6%
추가사항 18
 
1.6%
사건 18
 
1.6%
요청 18
 
1.6%
김영삼 16
 
1.4%
박정희 13
 
1.2%
윤보선 11
 
1.0%
김종필 10
 
0.9%
전두환 9
 
0.8%
Other values (753) 965
86.5%
2023-12-12T16:56:24.001376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
308
 
6.1%
( 182
 
3.6%
) 181
 
3.6%
이 158
 
3.1%
김 141
 
2.8%
사 106
 
2.1%
정 62
 
1.2%
박 52
 
1.0%
에 51
 
1.0%
일 51
 
1.0%
Other values (545) 3793
74.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3494
68.7%
Lowercase Letter 410
 
8.1%
Space Separator 308
 
6.1%
Uppercase Letter 255
 
5.0%
Open Punctuation 183
 
3.6%
Close Punctuation 182
 
3.6%
Decimal Number 169
 
3.3%
Other Punctuation 81
 
1.6%
Math Symbol 2
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 158
 
4.5%
김 141
 
4.0%
사 106
 
3.0%
정 62
 
1.8%
박 52
 
1.5%
에 51
 
1.5%
일 51
 
1.5%
구 46
 
1.3%
영 44
 
1.3%
대 43
 
1.2%
Other values (474) 2740
78.4%
Lowercase Letter
ValueCountFrequency (%)
e 45
11.0%
a 42
10.2%
r 40
9.8%
n 39
9.5%
o 34
 
8.3%
i 34
 
8.3%
t 28
 
6.8%
l 23
 
5.6%
u 18
 
4.4%
d 18
 
4.4%
Other values (14) 89
21.7%
Uppercase Letter
ValueCountFrequency (%)
A 29
 
11.4%
D 25
 
9.8%
I 24
 
9.4%
P 18
 
7.1%
C 16
 
6.3%
O 14
 
5.5%
S 14
 
5.5%
M 13
 
5.1%
K 11
 
4.3%
U 11
 
4.3%
Other values (13) 80
31.4%
Decimal Number
ValueCountFrequency (%)
1 37
21.9%
6 19
11.2%
8 18
10.7%
0 18
10.7%
2 17
10.1%
5 17
10.1%
4 16
9.5%
9 11
 
6.5%
3 9
 
5.3%
7 7
 
4.1%
Other Punctuation
ValueCountFrequency (%)
. 38
46.9%
, 21
25.9%
' 12
 
14.8%
· 7
 
8.6%
… 2
 
2.5%
: 1
 
1.2%
Open Punctuation
ValueCountFrequency (%)
( 182
99.5%
[ 1
 
0.5%
Close Punctuation
ValueCountFrequency (%)
) 181
99.5%
] 1
 
0.5%
Math Symbol
ValueCountFrequency (%)
× 1
50.0%
＝ 1
50.0%
Space Separator
ValueCountFrequency (%)
308
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3402
66.9%
Common 926
 
18.2%
Latin 665
 
13.1%
Han 80
 
1.6%
Hiragana 12
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 158
 
4.6%
김 141
 
4.1%
사 106
 
3.1%
정 62
 
1.8%
박 52
 
1.5%
에 51
 
1.5%
일 51
 
1.5%
구 46
 
1.4%
영 44
 
1.3%
대 43
 
1.3%
Other values (386) 2648
77.8%
Han
ValueCountFrequency (%)
金 3
 
3.8%
會 2
 
2.5%
料 1
 
1.2%
肥 1
 
1.2%
卞 1
 
1.2%
榮 1
 
1.2%
湖 1
 
1.2%
泰 1
 
1.2%
權 1
 
1.2%
承 1
 
1.2%
Other values (67) 67
83.8%
Latin
ValueCountFrequency (%)
e 45
 
6.8%
a 42
 
6.3%
r 40
 
6.0%
n 39
 
5.9%
o 34
 
5.1%
i 34
 
5.1%
A 29
 
4.4%
t 28
 
4.2%
D 25
 
3.8%
I 24
 
3.6%
Other values (37) 325
48.9%
Common
ValueCountFrequency (%)
308
33.3%
( 182
19.7%
) 181
19.5%
. 38
 
4.1%
1 37
 
4.0%
, 21
 
2.3%
6 19
 
2.1%
8 18
 
1.9%
0 18
 
1.9%
2 17
 
1.8%
Other values (14) 87
 
9.4%
Hiragana
ValueCountFrequency (%)
は 2
16.7%
き 1
8.3%
し 1
8.3%
の 1
8.3%
ぶ 1
8.3%
す 1
8.3%
け 1
8.3%
お 1
8.3%
ま 1
8.3%
か 1
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3402
66.9%
ASCII 1580
31.1%
CJK 73
 
1.4%
Hiragana 12
 
0.2%
None 9
 
0.2%
CJK Compat Ideographs 7
 
0.1%
Punctuation 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
308
19.5%
( 182
 
11.5%
) 181
 
11.5%
e 45
 
2.8%
a 42
 
2.7%
r 40
 
2.5%
n 39
 
2.5%
. 38
 
2.4%
1 37
 
2.3%
o 34
 
2.2%
Other values (57) 634
40.1%
Hangul
ValueCountFrequency (%)
이 158
 
4.6%
김 141
 
4.1%
사 106
 
3.1%
정 62
 
1.8%
박 52
 
1.5%
에 51
 
1.5%
일 51
 
1.5%
구 46
 
1.4%
영 44
 
1.3%
대 43
 
1.3%
Other values (386) 2648
77.8%
None
ValueCountFrequency (%)
· 7
77.8%
× 1
 
11.1%
＝ 1
 
11.1%
CJK Compat Ideographs
ValueCountFrequency (%)
金 3
42.9%
烈 1
 
14.3%
率 1
 
14.3%
不 1
 
14.3%
連 1
 
14.3%
CJK
ValueCountFrequency (%)
會 2
 
2.7%
料 1
 
1.4%
肥 1
 
1.4%
卞 1
 
1.4%
榮 1
 
1.4%
湖 1
 
1.4%
泰 1
 
1.4%
權 1
 
1.4%
承 1
 
1.4%
烈 1
 
1.4%
Other values (62) 62
84.9%
Punctuation
ValueCountFrequency (%)
… 2
100.0%
Hiragana
ValueCountFrequency (%)
は 2
16.7%
き 1
8.3%
し 1
8.3%
の 1
8.3%
ぶ 1
8.3%
す 1
8.3%
け 1
8.3%
お 1
8.3%
ま 1
8.3%
か 1
8.3%

각주내용
Text

MISSING 

Distinct666
Distinct (%)82.1%
Missing668
Missing (%)45.2%
Memory size11.7 KiB
2023-12-12T16:56:24.392958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length599
Median length244
Mean length114.07645
Min length2

Characters and Unicode

Total characters92516
Distinct characters1355
Distinct categories14 ?
Distinct scripts5 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique583 ?
Unique (%)71.9%

Sample

1st row제13대 대통령.
2nd row제15대 대통령.
3rd row한국과 일본이 1965년 6월 22일 도쿄에서 '한-일 양국의 국교관계에 관한 조약(기본조약)'을 조인함으로써 수교
4th row제4대 대통령.
5th row김영삼을 지칭함.
ValueCountFrequency (%)
대통령 120
 
0.7%
지냈다 103
 
0.6%
등을 98
 
0.6%
89
 
0.5%
후 84
 
0.5%
대한민국의 73
 
0.4%
한국의 68
 
0.4%
정치가 67
 
0.4%
국회의원 64
 
0.4%
국회의원을 55
 
0.3%
Other values (8288) 16679
95.3%
2023-12-12T16:56:24.970675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16780
 
18.1%
. 2580
 
2.8%
1 2512
 
2.7%
9 1679
 
1.8%
, 1539
 
1.7%
대 1532
 
1.7%
의 1480
 
1.6%
이 1213
 
1.3%
국 1195
 
1.3%
다 1146
 
1.2%
Other values (1345) 60860
65.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 57153
61.8%
Space Separator 16780
 
18.1%
Decimal Number 9264
 
10.0%
Other Punctuation 4885
 
5.3%
Lowercase Letter 1993
 
2.2%
Open Punctuation 720
 
0.8%
Close Punctuation 716
 
0.8%
Uppercase Letter 569
 
0.6%
Dash Punctuation 317
 
0.3%
Math Symbol 78
 
0.1%
Other values (4) 41
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 1532
 
2.7%
의 1480
 
2.6%
이 1213
 
2.1%
국 1195
 
2.1%
다 1146
 
2.0%
에 1120
 
2.0%
하 1068
 
1.9%
을 1054
 
1.8%
정 1003
 
1.8%
제 895
 
1.6%
Other values (1246) 45447
79.5%
Lowercase Letter
ValueCountFrequency (%)
n 236
11.8%
e 233
11.7%
t 190
9.5%
o 189
9.5%
a 183
9.2%
i 156
 
7.8%
r 148
 
7.4%
l 84
 
4.2%
s 77
 
3.9%
c 69
 
3.5%
Other values (15) 428
21.5%
Uppercase Letter
ValueCountFrequency (%)
A 70
12.3%
I 56
 
9.8%
D 47
 
8.3%
C 37
 
6.5%
U 35
 
6.2%
E 35
 
6.2%
S 32
 
5.6%
P 32
 
5.6%
O 26
 
4.6%
M 26
 
4.6%
Other values (13) 173
30.4%
Other Punctuation
ValueCountFrequency (%)
. 2580
52.8%
, 1539
31.5%
· 563
 
11.5%
' 118
 
2.4%
: 62
 
1.3%
" 10
 
0.2%
/ 7
 
0.1%
; 3
 
0.1%
， 2
 
< 0.1%
% 1
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 2512
27.1%
9 1679
18.1%
2 844
 
9.1%
0 759
 
8.2%
6 722
 
7.8%
5 667
 
7.2%
8 643
 
6.9%
4 493
 
5.3%
3 474
 
5.1%
7 471
 
5.1%
Math Symbol
ValueCountFrequency (%)
∼ 55
70.5%
< 8
 
10.3%
> 8
 
10.3%
≒ 2
 
2.6%
＝ 2
 
2.6%
× 2
 
2.6%
= 1
 
1.3%
Open Punctuation
ValueCountFrequency (%)
( 649
90.1%
[ 33
 
4.6%
《 22
 
3.1%
『 8
 
1.1%
「 6
 
0.8%
〈 2
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 646
90.2%
] 33
 
4.6%
》 22
 
3.1%
』 7
 
1.0%
」 6
 
0.8%
〉 2
 
0.3%
Other Number
ValueCountFrequency (%)
⑤ 1
20.0%
④ 1
20.0%
③ 1
20.0%
② 1
20.0%
① 1
20.0%
Final Punctuation
ValueCountFrequency (%)
’ 13
72.2%
” 5
 
27.8%
Initial Punctuation
ValueCountFrequency (%)
‘ 12
70.6%
“ 5
29.4%
Space Separator
ValueCountFrequency (%)
16780
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 317
100.0%
Other Symbol
ValueCountFrequency (%)
㎞ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 55553
60.0%
Common 32801
35.5%
Latin 2562
 
2.8%
Han 1592
 
1.7%
Hiragana 8
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 1532
 
2.8%
의 1480
 
2.7%
이 1213
 
2.2%
국 1195
 
2.2%
다 1146
 
2.1%
에 1120
 
2.0%
하 1068
 
1.9%
을 1054
 
1.9%
정 1003
 
1.8%
제 895
 
1.6%
Other values (736) 43847
78.9%
Han
ValueCountFrequency (%)
金 87
 
5.5%
朴 38
 
2.4%
李 27
 
1.7%
民 23
 
1.4%
尹 18
 
1.1%
黨 16
 
1.0%
國 16
 
1.0%
在 15
 
0.9%
李 14
 
0.9%
圭 14
 
0.9%
Other values (492) 1324
83.2%
Common
ValueCountFrequency (%)
16780
51.2%
. 2580
 
7.9%
1 2512
 
7.7%
9 1679
 
5.1%
, 1539
 
4.7%
2 844
 
2.6%
0 759
 
2.3%
6 722
 
2.2%
5 667
 
2.0%
( 649
 
2.0%
Other values (41) 4070
 
12.4%
Latin
ValueCountFrequency (%)
n 236
 
9.2%
e 233
 
9.1%
t 190
 
7.4%
o 189
 
7.4%
a 183
 
7.1%
i 156
 
6.1%
r 148
 
5.8%
l 84
 
3.3%
s 77
 
3.0%
A 70
 
2.7%
Other values (38) 996
38.9%
Hiragana
ValueCountFrequency (%)
ん 1
12.5%
だ 1
12.5%
い 1
12.5%
わ 1
12.5%
り 1
12.5%
そ 1
12.5%
み 1
12.5%
か 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 55552
60.0%
ASCII 34621
37.4%
CJK 1546
 
1.7%
None 644
 
0.7%
Math Operators 57
 
0.1%
CJK Compat Ideographs 46
 
< 0.1%
Punctuation 35
 
< 0.1%
Hiragana 8
 
< 0.1%
Enclosed Alphanum 5
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16780
48.5%
. 2580
 
7.5%
1 2512
 
7.3%
9 1679
 
4.8%
, 1539
 
4.4%
2 844
 
2.4%
0 759
 
2.2%
6 722
 
2.1%
5 667
 
1.9%
( 649
 
1.9%
Other values (65) 5890
 
17.0%
Hangul
ValueCountFrequency (%)
대 1532
 
2.8%
의 1480
 
2.7%
이 1213
 
2.2%
국 1195
 
2.2%
다 1146
 
2.1%
에 1120
 
2.0%
하 1068
 
1.9%
을 1054
 
1.9%
정 1003
 
1.8%
제 895
 
1.6%
Other values (735) 43846
78.9%
None
ValueCountFrequency (%)
· 563
87.4%
》 22
 
3.4%
《 22
 
3.4%
『 8
 
1.2%
』 7
 
1.1%
」 6
 
0.9%
「 6
 
0.9%
〈 2
 
0.3%
〉 2
 
0.3%
， 2
 
0.3%
Other values (2) 4
 
0.6%
CJK
ValueCountFrequency (%)
金 87
 
5.6%
朴 38
 
2.5%
李 27
 
1.7%
民 23
 
1.5%
尹 18
 
1.2%
黨 16
 
1.0%
國 16
 
1.0%
在 15
 
1.0%
圭 14
 
0.9%
大 14
 
0.9%
Other values (477) 1278
82.7%
Math Operators
ValueCountFrequency (%)
∼ 55
96.5%
≒ 2
 
3.5%
CJK Compat Ideographs
ValueCountFrequency (%)
李 14
30.4%
金 13
28.3%
盧 5
 
10.9%
率 2
 
4.3%
祿 2
 
4.3%
魯 1
 
2.2%
說 1
 
2.2%
梁 1
 
2.2%
利 1
 
2.2%
林 1
 
2.2%
Other values (5) 5
 
10.9%
Punctuation
ValueCountFrequency (%)
’ 13
37.1%
‘ 12
34.3%
” 5
 
14.3%
“ 5
 
14.3%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
⑤ 1
20.0%
④ 1
20.0%
③ 1
20.0%
② 1
20.0%
① 1
20.0%
Hiragana
ValueCountFrequency (%)
ん 1
12.5%
だ 1
12.5%
い 1
12.5%
わ 1
12.5%
り 1
12.5%
そ 1
12.5%
み 1
12.5%
か 1
12.5%
CJK Compat
ValueCountFrequency (%)
㎞ 1
100.0%

Interactions

2023-12-12T16:56:21.157503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:20.709712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:21.270107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:56:20.818155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:56:25.107259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호각주번호
번호1.0000.979
각주번호0.9791.000
2023-12-12T16:56:25.209708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호각주번호
번호1.0000.999
각주번호0.9991.000

Missing values

2023-12-12T16:56:21.401900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:56:21.485682image/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.
2023-12-12T16:56:21.570523image/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

번호각주번호캡션번호각주명각주내용
011cap_1<NA><NA>
121cap_2<NA><NA>
231cap_3노태우제13대 대통령.
341cap_4<NA><NA>
451cap_5김대중제15대 대통령.
561cap_6한일협정한국과 일본이 1965년 6월 22일 도쿄에서 '한-일 양국의 국교관계에 관한 조약(기본조약)'을 조인함으로써 수교
671cap_7<NA><NA>
781cap_8윤보선제4대 대통령.
891cap_9<NA><NA>
9101cap_10<NA><NA>
번호각주번호캡션번호각주명각주내용
1469147037cap_5중위에요.구술자가 언급한 인물은 김지회 중위이다.
1470147137cap_6저 그쪽에서 서울까지 내… 데려온 사실은, 이렇게 동여매고 이게 아니고, 고저 같이 갑시다 해서, 그래서 헌병대에 넘겨준 기억이 나요.구술자가 언급한 인물의 이름은 조경순이다.
1471147237cap_7최남근은…. 중국군 출신일 거예요.최남근은 중국군 출신이 아니라 만주군 출신이다.
1472147337cap_8그러니까 도착하자마자 정일권 장군이, 육해공 총참모장, 아 총사령관, 육군참모총장 겸 육해공 총대장.정일권은 곧바로 귀국해 6월 28일경 육군참모총장 겸 삼군 총사령관에 임명된다.
1473147437cap_9아그레망(Agrement)아그레망(agrement)은 한 국가가 다른 나라로 외교관을 파견할 때 이 인물에 대해 상대국이 동의를 해 주는 국제적인 관례를 의미한다.
1474147537cap_10사(4)선 개헌사(4)선 개헌이란 존재하지 않는다. 이승만의 삼(3)선을 위한 1954년 사사오입 개헌 당시, '초대 대통령(이승만)'은 연임 제한을 받지 않는다는 조항이 들어갔으므로 이승만에게 별도의 사(4)선 개헌이 필요하지 않았기 때문이다.
1475147637cap_11김창룡 장군 암살사건김창룡 암살사건은 1956년 1월 30일 발생하였다. 당시 김창룡 특무부대(CIC)장을 저격 살해한 사람은 신초식, 송용고 두 사람이었는데, 이들은 허태영 육군대령의 지시에 따라 움직였다. 또한 조사 과정에서 허태영 배후에 강문봉 중장이 있다는 사실이 밝혀졌다. 결국 허태영, 신초식, 송용고는 사형을 당했고, 강문봉은 사형 선고로 무기로 감행되었다가 4.19 이후 석방, 복권되었다.
1476147737cap_12사상논쟁사상논쟁은 1963년 10월 제5대 대통령 선거 과정에서 벌어졌다. 당시 윤보선을 비롯한 야당 후보들은 박정희의 남로당 전력을 문제 삼아 박정희를 중립주의자, 공산주의자로 공격했고, 이에 맞서 박정희는 민족주의를 표방하면서 윤보선 등을 봉건주의자, 사대주의자로 몰아갔다.
1477147837cap_13그 사람은 간사만 아마 한 십(10) 몇 년간 했지.이 부분에서 면담자는 계속 해방 직후 활동한 '학병단'에 대해 질문하고 있으나, 반면 구술자는 1960년대 이후 만들어진 '1.20동지회'에 대해서 설명하고 있다. 구술자가 면담자의 질문을 잘못 이해한 듯하다.
1478147937cap_14폴 새뮤엘슨(Paul Samuelson)폴 새뮤엘슨은 1915년 출생한 미국의 경제학자로서 MIT 교수로 재직하면서 1970년 노벨경제학상을 수상하였고 2009년 12월 사망하였다.