Overview

Dataset statistics

Number of variables6
Number of observations798
Missing cells768
Missing cells (%)16.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory39.9 KiB
Average record size in memory51.2 B

Variable types

Numeric3
Text3

Dataset

Description국립중앙박물관 도서관 소장자료로 박물관에서 발간한 자료 목록입니다. "서명, 저작자, 발행자, 발행년" 정보를 포함하고 있습니다.
Author문화체육관광부 국립중앙박물관
URLhttps://www.data.go.kr/data/3070614/fileData.do

Alerts

순번 is highly overall correlated with 발행시작일 and 1 other fieldsHigh correlation
발행시작일 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
발행종료일 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
발행종료일 has 766 (96.0%) missing valuesMissing
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 03:48:19.943969
Analysis finished2023-12-12 03:48:22.372815
Duration2.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct798
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean399.5
Minimum1
Maximum798
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.1 KiB
2023-12-12T12:48:22.806287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile40.85
Q1200.25
median399.5
Q3598.75
95-th percentile758.15
Maximum798
Range797
Interquartile range (IQR)398.5

Descriptive statistics

Standard deviation230.50705
Coefficient of variation (CV)0.57698886
Kurtosis-1.2
Mean399.5
Median Absolute Deviation (MAD)199.5
Skewness0
Sum318801
Variance53133.5
MonotonicityStrictly increasing
2023-12-12T12:48:23.002056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
526 1
 
0.1%
528 1
 
0.1%
529 1
 
0.1%
530 1
 
0.1%
531 1
 
0.1%
532 1
 
0.1%
533 1
 
0.1%
534 1
 
0.1%
535 1
 
0.1%
Other values (788) 788
98.7%
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 (%)
798 1
0.1%
797 1
0.1%
796 1
0.1%
795 1
0.1%
794 1
0.1%
793 1
0.1%
792 1
0.1%
791 1
0.1%
790 1
0.1%
789 1
0.1%

서명
Text

Distinct793
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
2023-12-12T12:48:23.312758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length237
Median length119.5
Mean length40.745614
Min length2

Characters and Unicode

Total characters32515
Distinct characters1113
Distinct categories11 ?
Distinct scripts6 ?
Distinct blocks10 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique788 ?
Unique (%)98.7%

Sample

1st row韓國支石墓硏究 = Studies of dolmens in Korea
2nd row矢島貝塚
3rd row(百濟)武寧王陵遺物特別展
4th row國立博物館所藏品目錄 : 舊德壽宮美術館
5th row湖巖蒐集 韓國美術特別展
ValueCountFrequency (%)
621
 
10.1%
of 221
 
3.6%
the 188
 
3.1%
국립중앙박물관 79
 
1.3%
in 66
 
1.1%
museum 61
 
1.0%
and 59
 
1.0%
korea 55
 
0.9%
박물관 52
 
0.8%
national 45
 
0.7%
Other values (2796) 4680
76.4%
2023-12-12T12:48:23.877277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5334
 
16.4%
e 1512
 
4.7%
o 1136
 
3.5%
a 1096
 
3.4%
n 1082
 
3.3%
t 1038
 
3.2%
i 1003
 
3.1%
r 810
 
2.5%
s 787
 
2.4%
l 534
 
1.6%
Other values (1103) 18183
55.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 12660
38.9%
Other Letter 10804
33.2%
Space Separator 5334
16.4%
Decimal Number 1013
 
3.1%
Uppercase Letter 885
 
2.7%
Other Punctuation 787
 
2.4%
Close Punctuation 322
 
1.0%
Open Punctuation 321
 
1.0%
Math Symbol 272
 
0.8%
Dash Punctuation 115
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 309
 
2.9%
물 278
 
2.6%
의 273
 
2.5%
박 239
 
2.2%
국 239
 
2.2%
전 170
 
1.6%
사 153
 
1.4%
화 150
 
1.4%
고 144
 
1.3%
시 141
 
1.3%
Other values (1012) 8708
80.6%
Lowercase Letter
ValueCountFrequency (%)
e 1512
11.9%
o 1136
 
9.0%
a 1096
 
8.7%
n 1082
 
8.5%
t 1038
 
8.2%
i 1003
 
7.9%
r 810
 
6.4%
s 787
 
6.2%
l 534
 
4.2%
u 498
 
3.9%
Other values (16) 3164
25.0%
Uppercase Letter
ValueCountFrequency (%)
K 108
 
12.2%
S 94
 
10.6%
M 65
 
7.3%
A 64
 
7.2%
C 59
 
6.7%
T 52
 
5.9%
N 47
 
5.3%
B 43
 
4.9%
I 42
 
4.7%
G 41
 
4.6%
Other values (15) 270
30.5%
Decimal Number
ValueCountFrequency (%)
0 279
27.5%
1 241
23.8%
2 199
19.6%
9 69
 
6.8%
5 47
 
4.6%
8 41
 
4.0%
7 38
 
3.8%
3 37
 
3.7%
6 36
 
3.6%
4 26
 
2.6%
Other Punctuation
ValueCountFrequency (%)
: 354
45.0%
, 182
23.1%
. 132
 
16.8%
· 69
 
8.8%
' 24
 
3.0%
& 16
 
2.0%
" 6
 
0.8%
! 2
 
0.3%
? 2
 
0.3%
Math Symbol
ValueCountFrequency (%)
= 252
92.6%
~ 11
 
4.0%
+ 3
 
1.1%
< 2
 
0.7%
> 2
 
0.7%
∞ 1
 
0.4%
∼ 1
 
0.4%
Close Punctuation
ValueCountFrequency (%)
) 262
81.4%
] 55
 
17.1%
」 2
 
0.6%
〉 2
 
0.6%
』 1
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 262
81.6%
[ 54
 
16.8%
「 2
 
0.6%
〈 2
 
0.6%
『 1
 
0.3%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
50.0%
Ⅲ 1
50.0%
Space Separator
ValueCountFrequency (%)
5334
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 115
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 13547
41.7%
Hangul 9122
28.1%
Common 8164
25.1%
Han 1656
 
5.1%
Hiragana 14
 
< 0.1%
Katakana 12
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 309
 
3.4%
물 278
 
3.0%
의 273
 
3.0%
박 239
 
2.6%
국 239
 
2.6%
전 170
 
1.9%
사 153
 
1.7%
화 150
 
1.6%
고 144
 
1.6%
시 141
 
1.5%
Other values (523) 7026
77.0%
Han
ValueCountFrequency (%)
國 69
 
4.2%
物 50
 
3.0%
館 41
 
2.5%
博 40
 
2.4%
中 39
 
2.4%
立 33
 
2.0%
術 32
 
1.9%
韓 31
 
1.9%
美 30
 
1.8%
央 28
 
1.7%
Other values (462) 1263
76.3%
Latin
ValueCountFrequency (%)
e 1512
 
11.2%
o 1136
 
8.4%
a 1096
 
8.1%
n 1082
 
8.0%
t 1038
 
7.7%
i 1003
 
7.4%
r 810
 
6.0%
s 787
 
5.8%
l 534
 
3.9%
u 498
 
3.7%
Other values (43) 4051
29.9%
Common
ValueCountFrequency (%)
5334
65.3%
: 354
 
4.3%
0 279
 
3.4%
) 262
 
3.2%
( 262
 
3.2%
= 252
 
3.1%
1 241
 
3.0%
2 199
 
2.4%
, 182
 
2.2%
. 132
 
1.6%
Other values (28) 667
 
8.2%
Katakana
ValueCountFrequency (%)
ア 4
33.3%
ン 1
 
8.3%
ク 1
 
8.3%
ハ 1
 
8.3%
ブ 1
 
8.3%
ッ 1
 
8.3%
ド 1
 
8.3%
ジ 1
 
8.3%
ヅ 1
 
8.3%
Hiragana
ValueCountFrequency (%)
の 6
42.9%
に 2
 
14.3%
く 1
 
7.1%
づ 1
 
7.1%
て 1
 
7.1%
わ 1
 
7.1%
い 1
 
7.1%
し 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21628
66.5%
Hangul 9121
28.1%
CJK 1627
 
5.0%
None 79
 
0.2%
CJK Compat Ideographs 29
 
0.1%
Hiragana 14
 
< 0.1%
Katakana 12
 
< 0.1%
Math Operators 2
 
< 0.1%
Number Forms 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5334
24.7%
e 1512
 
7.0%
o 1136
 
5.3%
a 1096
 
5.1%
n 1082
 
5.0%
t 1038
 
4.8%
i 1003
 
4.6%
r 810
 
3.7%
s 787
 
3.6%
l 534
 
2.5%
Other values (70) 7296
33.7%
Hangul
ValueCountFrequency (%)
관 309
 
3.4%
물 278
 
3.0%
의 273
 
3.0%
박 239
 
2.6%
국 239
 
2.6%
전 170
 
1.9%
사 153
 
1.7%
화 150
 
1.6%
고 144
 
1.6%
시 141
 
1.5%
Other values (522) 7025
77.0%
CJK
ValueCountFrequency (%)
國 69
 
4.2%
物 50
 
3.1%
館 41
 
2.5%
博 40
 
2.5%
中 39
 
2.4%
立 33
 
2.0%
術 32
 
2.0%
韓 31
 
1.9%
美 30
 
1.8%
央 28
 
1.7%
Other values (446) 1234
75.8%
None
ValueCountFrequency (%)
· 69
87.3%
」 2
 
2.5%
「 2
 
2.5%
〈 2
 
2.5%
〉 2
 
2.5%
』 1
 
1.3%
『 1
 
1.3%
CJK Compat Ideographs
ValueCountFrequency (%)
金 7
24.1%
李 3
10.3%
樂 3
10.3%
龍 2
 
6.9%
論 2
 
6.9%
樂 2
 
6.9%
來 1
 
3.4%
陵 1
 
3.4%
樓 1
 
3.4%
略 1
 
3.4%
Other values (6) 6
20.7%
Hiragana
ValueCountFrequency (%)
の 6
42.9%
に 2
 
14.3%
く 1
 
7.1%
づ 1
 
7.1%
て 1
 
7.1%
わ 1
 
7.1%
い 1
 
7.1%
し 1
 
7.1%
Katakana
ValueCountFrequency (%)
ア 4
33.3%
ン 1
 
8.3%
ク 1
 
8.3%
ハ 1
 
8.3%
ブ 1
 
8.3%
ッ 1
 
8.3%
ド 1
 
8.3%
ジ 1
 
8.3%
ヅ 1
 
8.3%
Math Operators
ValueCountFrequency (%)
∞ 1
50.0%
∼ 1
50.0%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
50.0%
Ⅲ 1
50.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

저작자
Text

Distinct210
Distinct (%)26.3%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
2023-12-12T12:48:24.182673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length192
Median length54
Mean length11.857143
Min length3

Characters and Unicode

Total characters9462
Distinct characters288
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique163 ?
Unique (%)20.4%

Sample

1st row國立博物館
2nd row國立博物館
3rd row國立博物館
4th row國立博物館
5th row國立博物館
ValueCountFrequency (%)
국립중앙박물관 535
36.7%
편 204
 
14.0%
國立中央博物館 94
 
6.4%
museum 38
 
2.6%
of 37
 
2.5%
編 37
 
2.5%
미술부 33
 
2.3%
korea 32
 
2.2%
national 30
 
2.1%
역사부 22
 
1.5%
Other values (220) 396
27.2%
2023-12-12T12:48:24.677657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 710
 
7.5%
관 699
 
7.4%
물 672
 
7.1%
박 671
 
7.1%
660
 
7.0%
립 649
 
6.9%
중 622
 
6.6%
앙 620
 
6.6%
편 214
 
2.3%
a 136
 
1.4%
Other values (278) 3809
40.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7310
77.3%
Lowercase Letter 943
 
10.0%
Space Separator 660
 
7.0%
Open Punctuation 137
 
1.4%
Close Punctuation 137
 
1.4%
Uppercase Letter 134
 
1.4%
Other Punctuation 133
 
1.4%
Decimal Number 6
 
0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 710
 
9.7%
관 699
 
9.6%
물 672
 
9.2%
박 671
 
9.2%
립 649
 
8.9%
중 622
 
8.5%
앙 620
 
8.5%
편 214
 
2.9%
國 109
 
1.5%
館 108
 
1.5%
Other values (225) 2236
30.6%
Lowercase Letter
ValueCountFrequency (%)
a 136
14.4%
o 125
13.3%
e 104
11.0%
u 97
10.3%
m 77
8.2%
i 61
6.5%
n 60
6.4%
s 53
 
5.6%
t 53
 
5.6%
r 51
 
5.4%
Other values (12) 126
13.4%
Uppercase Letter
ValueCountFrequency (%)
N 37
27.6%
K 36
26.9%
M 14
 
10.4%
S 7
 
5.2%
C 6
 
4.5%
I 5
 
3.7%
H 4
 
3.0%
B 4
 
3.0%
O 4
 
3.0%
A 4
 
3.0%
Other values (8) 13
 
9.7%
Other Punctuation
ValueCountFrequency (%)
; 111
83.5%
, 19
 
14.3%
· 2
 
1.5%
: 1
 
0.8%
Decimal Number
ValueCountFrequency (%)
0 3
50.0%
2 2
33.3%
5 1
 
16.7%
Open Punctuation
ValueCountFrequency (%)
[ 135
98.5%
( 2
 
1.5%
Close Punctuation
ValueCountFrequency (%)
] 135
98.5%
) 2
 
1.5%
Space Separator
ValueCountFrequency (%)
660
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6460
68.3%
Latin 1077
 
11.4%
Common 1075
 
11.4%
Han 850
 
9.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 710
11.0%
관 699
10.8%
물 672
10.4%
박 671
10.4%
립 649
10.0%
중 622
9.6%
앙 620
9.6%
편 214
 
3.3%
부 98
 
1.5%
회 71
 
1.1%
Other values (181) 1434
22.2%
Han
ValueCountFrequency (%)
國 109
12.8%
館 108
12.7%
立 107
12.6%
物 107
12.6%
博 106
12.5%
央 101
11.9%
中 101
11.9%
編 38
 
4.5%
術 7
 
0.8%
美 6
 
0.7%
Other values (34) 60
7.1%
Latin
ValueCountFrequency (%)
a 136
12.6%
o 125
11.6%
e 104
 
9.7%
u 97
 
9.0%
m 77
 
7.1%
i 61
 
5.7%
n 60
 
5.6%
s 53
 
4.9%
t 53
 
4.9%
r 51
 
4.7%
Other values (30) 260
24.1%
Common
ValueCountFrequency (%)
660
61.4%
[ 135
 
12.6%
] 135
 
12.6%
; 111
 
10.3%
, 19
 
1.8%
0 3
 
0.3%
· 2
 
0.2%
2 2
 
0.2%
- 2
 
0.2%
) 2
 
0.2%
Other values (3) 4
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6460
68.3%
ASCII 2150
 
22.7%
CJK 850
 
9.0%
None 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 710
11.0%
관 699
10.8%
물 672
10.4%
박 671
10.4%
립 649
10.0%
중 622
9.6%
앙 620
9.6%
편 214
 
3.3%
부 98
 
1.5%
회 71
 
1.1%
Other values (181) 1434
22.2%
ASCII
ValueCountFrequency (%)
660
30.7%
a 136
 
6.3%
[ 135
 
6.3%
] 135
 
6.3%
o 125
 
5.8%
; 111
 
5.2%
e 104
 
4.8%
u 97
 
4.5%
m 77
 
3.6%
i 61
 
2.8%
Other values (42) 509
23.7%
CJK
ValueCountFrequency (%)
國 109
12.8%
館 108
12.7%
立 107
12.6%
物 107
12.6%
博 106
12.5%
央 101
11.9%
中 101
11.9%
編 38
 
4.5%
術 7
 
0.8%
美 6
 
0.7%
Other values (34) 60
7.1%
None
ValueCountFrequency (%)
· 2
100.0%

발행자
Text

Distinct138
Distinct (%)17.3%
Missing1
Missing (%)0.1%
Memory size6.4 KiB
2023-12-12T12:48:24.935305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length7
Mean length8.7465496
Min length1

Characters and Unicode

Total characters6971
Distinct characters255
Distinct categories7 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique92 ?
Unique (%)11.5%

Sample

1st row國立博物館
2nd row國立博物館
3rd row國立博物館
4th row國立博物館
5th row國立博物館
ValueCountFrequency (%)
국립중앙박물관 448
47.0%
國立中央博物館 74
 
7.8%
museum 33
 
3.5%
of 31
 
3.3%
korea 31
 
3.3%
통천문화사 27
 
2.8%
national 27
 
2.8%
한국박물관협회:국립중앙박물관 19
 
2.0%
한국박물관협회 11
 
1.2%
건립추진기획단 7
 
0.7%
Other values (154) 245
25.7%
2023-12-12T12:48:25.475930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 603
 
8.7%
관 584
 
8.4%
박 579
 
8.3%
물 579
 
8.3%
립 545
 
7.8%
중 528
 
7.6%
앙 527
 
7.6%
156
 
2.2%
a 106
 
1.5%
o 103
 
1.5%
Other values (245) 2661
38.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5868
84.2%
Lowercase Letter 716
 
10.3%
Space Separator 156
 
2.2%
Uppercase Letter 129
 
1.9%
Other Punctuation 80
 
1.1%
Close Punctuation 11
 
0.2%
Open Punctuation 11
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 603
 
10.3%
관 584
 
10.0%
박 579
 
9.9%
물 579
 
9.9%
립 545
 
9.3%
중 528
 
9.0%
앙 527
 
9.0%
國 93
 
1.6%
物 90
 
1.5%
館 90
 
1.5%
Other values (198) 1650
28.1%
Lowercase Letter
ValueCountFrequency (%)
a 106
14.8%
o 103
14.4%
u 74
10.3%
e 74
10.3%
m 62
8.7%
r 44
6.1%
n 40
 
5.6%
i 39
 
5.4%
s 39
 
5.4%
t 39
 
5.4%
Other values (11) 96
13.4%
Uppercase Letter
ValueCountFrequency (%)
N 40
31.0%
K 30
23.3%
A 14
 
10.9%
M 10
 
7.8%
G 8
 
6.2%
S 6
 
4.7%
O 3
 
2.3%
F 3
 
2.3%
U 3
 
2.3%
H 2
 
1.6%
Other values (9) 10
 
7.8%
Other Punctuation
ValueCountFrequency (%)
: 74
92.5%
, 3
 
3.8%
· 2
 
2.5%
. 1
 
1.2%
Space Separator
ValueCountFrequency (%)
156
100.0%
Close Punctuation
ValueCountFrequency (%)
] 11
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5110
73.3%
Latin 845
 
12.1%
Han 758
 
10.9%
Common 258
 
3.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 603
11.8%
관 584
11.4%
박 579
11.3%
물 579
11.3%
립 545
10.7%
중 528
10.3%
앙 527
10.3%
사 75
 
1.5%
회 68
 
1.3%
한 68
 
1.3%
Other values (134) 954
18.7%
Han
ValueCountFrequency (%)
國 93
12.3%
物 90
11.9%
館 90
11.9%
博 89
11.7%
立 88
11.6%
央 81
10.7%
中 80
10.6%
社 15
 
2.0%
版 10
 
1.3%
出 10
 
1.3%
Other values (54) 112
14.8%
Latin
ValueCountFrequency (%)
a 106
12.5%
o 103
12.2%
u 74
 
8.8%
e 74
 
8.8%
m 62
 
7.3%
r 44
 
5.2%
N 40
 
4.7%
n 40
 
4.7%
i 39
 
4.6%
s 39
 
4.6%
Other values (30) 224
26.5%
Common
ValueCountFrequency (%)
156
60.5%
: 74
28.7%
] 11
 
4.3%
[ 11
 
4.3%
, 3
 
1.2%
· 2
 
0.8%
. 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5110
73.3%
ASCII 1098
 
15.8%
CJK 758
 
10.9%
None 5
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 603
11.8%
관 584
11.4%
박 579
11.3%
물 579
11.3%
립 545
10.7%
중 528
10.3%
앙 527
10.3%
사 75
 
1.5%
회 68
 
1.3%
한 68
 
1.3%
Other values (134) 954
18.7%
ASCII
ValueCountFrequency (%)
156
14.2%
a 106
 
9.7%
o 103
 
9.4%
u 74
 
6.7%
: 74
 
6.7%
e 74
 
6.7%
m 62
 
5.6%
r 44
 
4.0%
N 40
 
3.6%
n 40
 
3.6%
Other values (35) 325
29.6%
CJK
ValueCountFrequency (%)
國 93
12.3%
物 90
11.9%
館 90
11.9%
博 89
11.7%
立 88
11.6%
央 81
10.7%
中 80
10.6%
社 15
 
2.0%
版 10
 
1.3%
出 10
 
1.3%
Other values (54) 112
14.8%
None
ValueCountFrequency (%)
ı 3
60.0%
· 2
40.0%

발행시작일
Real number (ℝ)

HIGH CORRELATION 

Distinct55
Distinct (%)6.9%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean2006.5483
Minimum1967
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.1 KiB
2023-12-12T12:48:25.666419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1967
5-th percentile1982
Q12002
median2009
Q32014
95-th percentile2020
Maximum2022
Range55
Interquartile range (IQR)12

Descriptive statistics

Standard deviation10.947533
Coefficient of variation (CV)0.0054559031
Kurtosis1.4201739
Mean2006.5483
Median Absolute Deviation (MAD)6
Skewness-1.2354129
Sum1599219
Variance119.84848
MonotonicityNot monotonic
2023-12-12T12:48:25.851374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2007 52
 
6.5%
2011 49
 
6.1%
2006 45
 
5.6%
2010 41
 
5.1%
2012 37
 
4.6%
2014 36
 
4.5%
2008 34
 
4.3%
2015 34
 
4.3%
2009 29
 
3.6%
2016 28
 
3.5%
Other values (45) 412
51.6%
ValueCountFrequency (%)
1967 1
 
0.1%
1968 1
 
0.1%
1970 1
 
0.1%
1971 3
0.4%
1972 3
0.4%
1973 3
0.4%
1974 2
 
0.3%
1975 5
0.6%
1976 3
0.4%
1977 4
0.5%
ValueCountFrequency (%)
2022 7
 
0.9%
2021 23
2.9%
2020 20
2.5%
2019 27
3.4%
2018 25
3.1%
2017 23
2.9%
2016 28
3.5%
2015 34
4.3%
2014 36
4.5%
2013 25
3.1%

발행종료일
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct19
Distinct (%)59.4%
Missing766
Missing (%)96.0%
Infinite0
Infinite (%)0.0%
Mean2008.4062
Minimum1978
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.1 KiB
2023-12-12T12:48:26.020263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1978
5-th percentile1980
Q12008
median2011.5
Q32017
95-th percentile2020
Maximum2021
Range43
Interquartile range (IQR)9

Descriptive statistics

Standard deviation12.628333
Coefficient of variation (CV)0.0062877384
Kurtosis0.96722822
Mean2008.4062
Median Absolute Deviation (MAD)5
Skewness-1.4328676
Sum64269
Variance159.4748
MonotonicityNot monotonic
2023-12-12T12:48:26.176573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
2009 4
 
0.5%
2008 3
 
0.4%
2017 3
 
0.4%
2019 3
 
0.4%
2014 2
 
0.3%
2020 2
 
0.3%
2015 2
 
0.3%
1980 2
 
0.3%
1997 1
 
0.1%
2016 1
 
0.1%
Other values (9) 9
 
1.1%
(Missing) 766
96.0%
ValueCountFrequency (%)
1978 1
 
0.1%
1980 2
0.3%
1985 1
 
0.1%
1988 1
 
0.1%
1997 1
 
0.1%
2007 1
 
0.1%
2008 3
0.4%
2009 4
0.5%
2010 1
 
0.1%
2011 1
 
0.1%
ValueCountFrequency (%)
2021 1
 
0.1%
2020 2
0.3%
2019 3
0.4%
2018 1
 
0.1%
2017 3
0.4%
2016 1
 
0.1%
2015 2
0.3%
2014 2
0.3%
2012 1
 
0.1%
2011 1
 
0.1%

Interactions

2023-12-12T12:48:21.706800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:20.926669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:21.339845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:21.807940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:21.080346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:21.489722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:21.891571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:21.206325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:21.602568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:48:26.303939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번발행시작일발행종료일
순번1.0000.963NaN
발행시작일0.9631.0000.817
발행종료일NaN0.8171.000
2023-12-12T12:48:26.420857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번발행시작일발행종료일
순번1.0000.8740.651
발행시작일0.8741.0000.616
발행종료일0.6510.6161.000

Missing values

2023-12-12T12:48:22.040364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:48:22.204666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-12T12:48:22.306407image/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

순번서명저작자발행자발행시작일발행종료일
01韓國支石墓硏究 = Studies of dolmens in Korea國立博物館國立博物館1967<NA>
12矢島貝塚國立博物館國立博物館1970<NA>
23(百濟)武寧王陵遺物特別展國立博物館國立博物館1971<NA>
34國立博物館所藏品目錄 : 舊德壽宮美術館國立博物館國立博物館1971<NA>
45湖巖蒐集 韓國美術特別展國立博物館國立博物館1971<NA>
56陳列品圖錄國立中央博物館 編國立中央博物館1972<NA>
67韓國繪畵. 1972,1977國立中央博物館 編國立中央博物館1972<NA>
78韓國美術二千年國立中央博物館 [編]光明出版社1973<NA>
89韓國美術二千年國立中央博物館 [編]光明出版社1973<NA>
910韓國先史時代靑銅器國立中央博物館 編國立中央博物館1973<NA>
순번서명저작자발행자발행시작일발행종료일
788789국립중앙박물관 교육프로그램 자료집 = National Museum of Korea education programs. 2009, 2015-2020국립중앙박물관 교육과국립중앙박물관20102021
789790박물관 교육 국외 전문가 초청 워크숍. [2011-2012]국립중앙박물관 교육과;국립중앙박물관 국제교류홍보과 [편]국립중앙박물관20112012
790791(국립중앙박물관 소장)조선 묘지명. 1-3국립중앙박물관 고고역사부국립중앙박물관20112014
791792몽골 도르릭 나르스 흉노무덤. 1-2국립중앙박물관 고고역사부;몽골 국립박물관;몽골과학아카데미 고고학연구소국립중앙박물관20112014
792793Museum network fellowship : colloquium research papers. 2012~2019National museum of KoreaNational museum of Korea20122019
793794(국립중앙박물관 소장) 동원컬렉션 목록집 = Catalogue of the Dongwon colletion in the National museum of Korea국립중앙박물관국립중앙박물관:한국고고미술연구소20142015
794795(국립중앙박물관 소장)불교조각 조사보고 = Buddhist sculpture in the national museum of Korea. 1-3국립중앙박물관국립중앙박물관20142018
795796慶州 瑞鳳塚 = Gyeongju Seobongchong. 1,2국립중앙박물관국립중앙박물관20142020
796797국립중앙박물관 업무편람. 2016-2017국립중앙박물관 기획운영단 기획총괄과국립중앙박물관 기획운영단 기획총괄과20162017
797798우리가족 박물관 탐방 : 후기·사진 모음집. 2016,2017국립중앙박물관국립중앙박물관20162017