Overview

Dataset statistics

Number of variables5
Number of observations10000
Missing cells2
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory488.3 KiB
Average record size in memory50.0 B

Variable types

Numeric2
Text3

Dataset

Description2024년 3월까지 한국수자원공사 보유 도서(39608권) 목록을 제공합니다.- 갱신주기 : 1년- 보관장소 : 본사(대전 대덕구 연축동)
Author한국수자원공사
URLhttps://www.data.go.kr/data/3072561/fileData.do

Alerts

순번 is highly overall correlated with 출판년도High correlation
출판년도 is highly overall correlated with 순번High correlation
순번 has unique valuesUnique

Reproduction

Analysis started2024-04-21 02:47:41.202776
Analysis finished2024-04-21 02:47:44.287251
Duration3.08 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19784.878
Minimum8
Maximum39604
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T11:47:44.365788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile1986.9
Q19938.75
median19719.5
Q329768.5
95-th percentile37482.2
Maximum39604
Range39596
Interquartile range (IQR)19829.75

Descriptive statistics

Standard deviation11408.891
Coefficient of variation (CV)0.57664702
Kurtosis-1.2104049
Mean19784.878
Median Absolute Deviation (MAD)9911
Skewness0.0029217637
Sum1.9784878 × 108
Variance1.3016279 × 108
MonotonicityNot monotonic
2024-04-21T11:47:44.493803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
28289 1
 
< 0.1%
35059 1
 
< 0.1%
18390 1
 
< 0.1%
7774 1
 
< 0.1%
21570 1
 
< 0.1%
6674 1
 
< 0.1%
27005 1
 
< 0.1%
14002 1
 
< 0.1%
12534 1
 
< 0.1%
23118 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
8 1
< 0.1%
12 1
< 0.1%
14 1
< 0.1%
20 1
< 0.1%
25 1
< 0.1%
27 1
< 0.1%
35 1
< 0.1%
36 1
< 0.1%
39 1
< 0.1%
44 1
< 0.1%
ValueCountFrequency (%)
39604 1
< 0.1%
39601 1
< 0.1%
39596 1
< 0.1%
39594 1
< 0.1%
39591 1
< 0.1%
39587 1
< 0.1%
39583 1
< 0.1%
39573 1
< 0.1%
39564 1
< 0.1%
39553 1
< 0.1%

서명
Text

Distinct9924
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-21T11:47:44.709909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length318
Median length124
Mean length28.7627
Min length1

Characters and Unicode

Total characters287627
Distinct characters1739
Distinct categories15 ?
Distinct scripts7 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9857 ?
Unique (%)98.6%

Sample

1st row영산강(하류) 하천기본계획 보고서
2nd row척산천 하천기본계획 보고서
3rd row추계학적 기법을 적용한 홍수예측체계 개선
4th row도시계획현황:2007
5th row강희대제(12)-제왕삼부곡 제1작
ValueCountFrequency (%)
2748
 
5.2%
of 789
 
1.5%
및 734
 
1.4%
연구 615
 
1.2%
and 609
 
1.2%
water 467
 
0.9%
위한 424
 
0.8%
the 389
 
0.7%
관한 312
 
0.6%
in 282
 
0.5%
Other values (22993) 45521
86.1%
2024-04-21T11:47:45.100659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
43403
 
15.1%
e 6336
 
2.2%
n 5307
 
1.8%
a 4963
 
1.7%
o 4876
 
1.7%
i 4632
 
1.6%
r 4452
 
1.5%
t 4429
 
1.5%
E 3799
 
1.3%
s 3331
 
1.2%
Other values (1729) 202099
70.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 126631
44.0%
Lowercase Letter 56783
19.7%
Space Separator 43403
 
15.1%
Uppercase Letter 37409
 
13.0%
Decimal Number 10660
 
3.7%
Other Punctuation 5745
 
2.0%
Close Punctuation 2900
 
1.0%
Open Punctuation 2895
 
1.0%
Dash Punctuation 905
 
0.3%
Math Symbol 169
 
0.1%
Other values (5) 127
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 2897
 
2.3%
기 2701
 
2.1%
수 2385
 
1.9%
지 2244
 
1.8%
한 2220
 
1.8%
사 2167
 
1.7%
서 1728
 
1.4%
보 1723
 
1.4%
구 1701
 
1.3%
계 1686
 
1.3%
Other values (1628) 105179
83.1%
Lowercase Letter
ValueCountFrequency (%)
e 6336
11.2%
n 5307
 
9.3%
a 4963
 
8.7%
o 4876
 
8.6%
i 4632
 
8.2%
r 4452
 
7.8%
t 4429
 
7.8%
s 3331
 
5.9%
l 2559
 
4.5%
c 2191
 
3.9%
Other values (17) 13707
24.1%
Uppercase Letter
ValueCountFrequency (%)
E 3799
 
10.2%
A 3205
 
8.6%
N 3051
 
8.2%
I 2806
 
7.5%
O 2756
 
7.4%
T 2712
 
7.2%
R 2705
 
7.2%
S 2515
 
6.7%
C 1915
 
5.1%
L 1489
 
4.0%
Other values (16) 10456
28.0%
Other Punctuation
ValueCountFrequency (%)
; 2331
40.6%
: 1410
24.5%
, 878
 
15.3%
. 694
 
12.1%
· 104
 
1.8%
& 89
 
1.5%
/ 87
 
1.5%
? 54
 
0.9%
! 46
 
0.8%
' 39
 
0.7%
Other values (4) 13
 
0.2%
Decimal Number
ValueCountFrequency (%)
1 2452
23.0%
2 1795
16.8%
0 1784
16.7%
9 1347
12.6%
3 776
 
7.3%
5 599
 
5.6%
8 566
 
5.3%
4 509
 
4.8%
6 424
 
4.0%
7 408
 
3.8%
Letter Number
ValueCountFrequency (%)
Ⅱ 47
40.9%
Ⅰ 44
38.3%
Ⅲ 12
 
10.4%
Ⅳ 8
 
7.0%
Ⅴ 3
 
2.6%
Ⅵ 1
 
0.9%
Math Symbol
ValueCountFrequency (%)
~ 158
93.5%
+ 6
 
3.6%
= 3
 
1.8%
< 1
 
0.6%
> 1
 
0.6%
Close Punctuation
ValueCountFrequency (%)
) 2864
98.8%
] 36
 
1.2%
Open Punctuation
ValueCountFrequency (%)
( 2862
98.9%
[ 33
 
1.1%
Initial Punctuation
ValueCountFrequency (%)
‘ 2
66.7%
“ 1
33.3%
Other Number
ValueCountFrequency (%)
₂ 2
66.7%
⑥ 1
33.3%
Other Symbol
ValueCountFrequency (%)
° 1
50.0%
® 1
50.0%
Space Separator
ValueCountFrequency (%)
43403
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 905
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 123748
43.0%
Latin 94306
32.8%
Common 66689
23.2%
Han 2081
 
0.7%
Katakana 404
 
0.1%
Hiragana 398
 
0.1%
Greek 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 2897
 
2.3%
기 2701
 
2.2%
수 2385
 
1.9%
지 2244
 
1.8%
한 2220
 
1.8%
사 2167
 
1.8%
서 1728
 
1.4%
보 1723
 
1.4%
구 1701
 
1.4%
계 1686
 
1.4%
Other values (1045) 102296
82.7%
Han
ValueCountFrequency (%)
水 100
 
4.8%
設 36
 
1.7%
計 32
 
1.5%
技 32
 
1.5%
工 29
 
1.4%
術 29
 
1.4%
管 27
 
1.3%
第 25
 
1.2%
川 25
 
1.2%
河 24
 
1.2%
Other values (465) 1722
82.7%
Latin
ValueCountFrequency (%)
e 6336
 
6.7%
n 5307
 
5.6%
a 4963
 
5.3%
o 4876
 
5.2%
i 4632
 
4.9%
r 4452
 
4.7%
t 4429
 
4.7%
E 3799
 
4.0%
s 3331
 
3.5%
A 3205
 
3.4%
Other values (48) 48976
51.9%
Katakana
ValueCountFrequency (%)
ム 31
 
7.7%
リ 28
 
6.9%
ン 27
 
6.7%
ダ 27
 
6.7%
ト 23
 
5.7%
ス 22
 
5.4%
ク 18
 
4.5%
ル 14
 
3.5%
ツ 14
 
3.5%
ズ 12
 
3.0%
Other values (48) 188
46.5%
Hiragana
ValueCountFrequency (%)
の 126
31.7%
と 42
 
10.6%
る 24
 
6.0%
に 23
 
5.8%
す 15
 
3.8%
た 9
 
2.3%
で 9
 
2.3%
し 9
 
2.3%
え 9
 
2.3%
を 9
 
2.3%
Other values (40) 123
30.9%
Common
ValueCountFrequency (%)
43403
65.1%
) 2864
 
4.3%
( 2862
 
4.3%
1 2452
 
3.7%
; 2331
 
3.5%
2 1795
 
2.7%
0 1784
 
2.7%
: 1410
 
2.1%
9 1347
 
2.0%
- 905
 
1.4%
Other values (32) 5536
 
8.3%
Greek
ValueCountFrequency (%)
φ 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 160765
55.9%
Hangul 123291
42.9%
CJK 2050
 
0.7%
Compat Jamo 457
 
0.2%
Katakana 404
 
0.1%
Hiragana 398
 
0.1%
Number Forms 115
 
< 0.1%
None 112
 
< 0.1%
CJK Compat Ideographs 31
 
< 0.1%
Punctuation 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
43403
27.0%
e 6336
 
3.9%
n 5307
 
3.3%
a 4963
 
3.1%
o 4876
 
3.0%
i 4632
 
2.9%
r 4452
 
2.8%
t 4429
 
2.8%
E 3799
 
2.4%
s 3331
 
2.1%
Other values (75) 75237
46.8%
Hangul
ValueCountFrequency (%)
의 2897
 
2.3%
기 2701
 
2.2%
수 2385
 
1.9%
지 2244
 
1.8%
한 2220
 
1.8%
사 2167
 
1.8%
서 1728
 
1.4%
보 1723
 
1.4%
구 1701
 
1.4%
계 1686
 
1.4%
Other values (1042) 101839
82.6%
Compat Jamo
ValueCountFrequency (%)
ㆍ 446
97.6%
ㅡ 10
 
2.2%
ㅂ 1
 
0.2%
Hiragana
ValueCountFrequency (%)
の 126
31.7%
と 42
 
10.6%
る 24
 
6.0%
に 23
 
5.8%
す 15
 
3.8%
た 9
 
2.3%
で 9
 
2.3%
し 9
 
2.3%
え 9
 
2.3%
を 9
 
2.3%
Other values (40) 123
30.9%
None
ValueCountFrequency (%)
· 104
92.9%
： 2
 
1.8%
₂ 2
 
1.8%
° 1
 
0.9%
® 1
 
0.9%
． 1
 
0.9%
φ 1
 
0.9%
CJK
ValueCountFrequency (%)
水 100
 
4.9%
設 36
 
1.8%
計 32
 
1.6%
技 32
 
1.6%
工 29
 
1.4%
術 29
 
1.4%
管 27
 
1.3%
第 25
 
1.2%
川 25
 
1.2%
河 24
 
1.2%
Other values (450) 1691
82.5%
Number Forms
ValueCountFrequency (%)
Ⅱ 47
40.9%
Ⅰ 44
38.3%
Ⅲ 12
 
10.4%
Ⅳ 8
 
7.0%
Ⅴ 3
 
2.6%
Ⅵ 1
 
0.9%
Katakana
ValueCountFrequency (%)
ム 31
 
7.7%
リ 28
 
6.9%
ン 27
 
6.7%
ダ 27
 
6.7%
ト 23
 
5.7%
ス 22
 
5.4%
ク 18
 
4.5%
ル 14
 
3.5%
ツ 14
 
3.5%
ズ 12
 
3.0%
Other values (48) 188
46.5%
CJK Compat Ideographs
ValueCountFrequency (%)
利 5
16.1%
力 4
12.9%
流 3
9.7%
論 3
9.7%
金 3
9.7%
劣 2
 
6.5%
陸 2
 
6.5%
例 2
 
6.5%
理 1
 
3.2%
洛 1
 
3.2%
Other values (5) 5
16.1%
Punctuation
ValueCountFrequency (%)
‘ 2
66.7%
“ 1
33.3%
Enclosed Alphanum
ValueCountFrequency (%)
⑥ 1
100.0%

저자
Text

Distinct6368
Distinct (%)63.7%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2024-04-21T11:47:45.335173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length103
Median length73
Mean length11.869787
Min length1

Characters and Unicode

Total characters118686
Distinct characters965
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

Unique5487 ?
Unique (%)54.9%

Sample

1st row국토해양부 익산지방국토관리청 편;현대엔지니어링 편;삼안 편
2nd row경상북도 편
3rd row국토해양부 한강홍수통제소 편
4th row국토해양부 편;한국토지공사 편
5th row얼웨허 저;홍순도 역
ValueCountFrequency (%)
편 5020
 
18.3%
저 3935
 
14.3%
역 919
 
3.3%
건설교통부 267
 
1.0%
of 216
 
0.8%
건설부 215
 
0.8%
국토해양부 187
 
0.7%
한국수자원공사 115
 
0.4%
수자원연구소 109
 
0.4%
한국건설기술연구원 103
 
0.4%
Other values (9076) 16410
59.7%
2024-04-21T11:47:45.727114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17627
 
14.9%
편 6275
 
5.3%
저 6079
 
5.1%
; 3432
 
2.9%
국 1763
 
1.5%
원 1594
 
1.3%
e 1591
 
1.3%
A 1502
 
1.3%
, 1460
 
1.2%
부 1448
 
1.2%
Other values (955) 75915
64.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67214
56.6%
Space Separator 17627
 
14.9%
Uppercase Letter 14220
 
12.0%
Lowercase Letter 13275
 
11.2%
Other Punctuation 6117
 
5.2%
Dash Punctuation 130
 
0.1%
Decimal Number 66
 
0.1%
Open Punctuation 18
 
< 0.1%
Close Punctuation 18
 
< 0.1%
Modifier Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
편 6275
 
9.3%
저 6079
 
9.0%
국 1763
 
2.6%
원 1594
 
2.4%
부 1448
 
2.2%
한 1318
 
2.0%
수 1119
 
1.7%
이 1103
 
1.6%
연 1100
 
1.6%
건 1065
 
1.6%
Other values (882) 44350
66.0%
Lowercase Letter
ValueCountFrequency (%)
e 1591
12.0%
a 1298
9.8%
r 1254
 
9.4%
n 1193
 
9.0%
o 1170
 
8.8%
i 1010
 
7.6%
t 810
 
6.1%
s 728
 
5.5%
l 671
 
5.1%
h 410
 
3.1%
Other values (16) 3140
23.7%
Uppercase Letter
ValueCountFrequency (%)
A 1502
 
10.6%
E 1270
 
8.9%
R 961
 
6.8%
C 939
 
6.6%
S 927
 
6.5%
I 878
 
6.2%
N 849
 
6.0%
O 833
 
5.9%
T 626
 
4.4%
L 567
 
4.0%
Other values (16) 4868
34.2%
Decimal Number
ValueCountFrequency (%)
0 20
30.3%
2 15
22.7%
1 10
15.2%
5 5
 
7.6%
9 4
 
6.1%
6 3
 
4.5%
3 3
 
4.5%
7 3
 
4.5%
4 2
 
3.0%
8 1
 
1.5%
Other Punctuation
ValueCountFrequency (%)
; 3432
56.1%
, 1460
23.9%
. 1191
 
19.5%
& 21
 
0.3%
/ 9
 
0.1%
· 4
 
0.1%
Space Separator
ValueCountFrequency (%)
17627
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 130
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 66727
56.2%
Latin 27495
23.2%
Common 23977
 
20.2%
Han 468
 
0.4%
Katakana 19
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
편 6275
 
9.4%
저 6079
 
9.1%
국 1763
 
2.6%
원 1594
 
2.4%
부 1448
 
2.2%
한 1318
 
2.0%
수 1119
 
1.7%
이 1103
 
1.7%
연 1100
 
1.6%
건 1065
 
1.6%
Other values (675) 43863
65.7%
Han
ValueCountFrequency (%)
會 23
 
4.9%
協 15
 
3.2%
水 13
 
2.8%
門 9
 
1.9%
鐵 9
 
1.9%
野 9
 
1.9%
管 9
 
1.9%
土 8
 
1.7%
幸 8
 
1.7%
設 8
 
1.7%
Other values (188) 357
76.3%
Latin
ValueCountFrequency (%)
e 1591
 
5.8%
A 1502
 
5.5%
a 1298
 
4.7%
E 1270
 
4.6%
r 1254
 
4.6%
n 1193
 
4.3%
o 1170
 
4.3%
i 1010
 
3.7%
R 961
 
3.5%
C 939
 
3.4%
Other values (42) 15307
55.7%
Common
ValueCountFrequency (%)
17627
73.5%
; 3432
 
14.3%
, 1460
 
6.1%
. 1191
 
5.0%
- 130
 
0.5%
& 21
 
0.1%
0 20
 
0.1%
( 18
 
0.1%
) 18
 
0.1%
2 15
 
0.1%
Other values (11) 45
 
0.2%
Katakana
ValueCountFrequency (%)
ダ 3
15.8%
ム 3
15.8%
ン 3
15.8%
ト 2
10.5%
リ 2
10.5%
ク 2
10.5%
コ 2
10.5%
セ 1
 
5.3%
タ 1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 66718
56.2%
ASCII 51468
43.4%
CJK 466
 
0.4%
Katakana 19
 
< 0.1%
Compat Jamo 9
 
< 0.1%
None 4
 
< 0.1%
CJK Compat Ideographs 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17627
34.2%
; 3432
 
6.7%
e 1591
 
3.1%
A 1502
 
2.9%
, 1460
 
2.8%
a 1298
 
2.5%
E 1270
 
2.5%
r 1254
 
2.4%
n 1193
 
2.3%
. 1191
 
2.3%
Other values (62) 19650
38.2%
Hangul
ValueCountFrequency (%)
편 6275
 
9.4%
저 6079
 
9.1%
국 1763
 
2.6%
원 1594
 
2.4%
부 1448
 
2.2%
한 1318
 
2.0%
수 1119
 
1.7%
이 1103
 
1.7%
연 1100
 
1.6%
건 1065
 
1.6%
Other values (674) 43854
65.7%
CJK
ValueCountFrequency (%)
會 23
 
4.9%
協 15
 
3.2%
水 13
 
2.8%
門 9
 
1.9%
鐵 9
 
1.9%
野 9
 
1.9%
管 9
 
1.9%
土 8
 
1.7%
幸 8
 
1.7%
設 8
 
1.7%
Other values (186) 355
76.2%
Compat Jamo
ValueCountFrequency (%)
ㆍ 9
100.0%
None
ValueCountFrequency (%)
· 4
100.0%
Katakana
ValueCountFrequency (%)
ダ 3
15.8%
ム 3
15.8%
ン 3
15.8%
ト 2
10.5%
リ 2
10.5%
ク 2
10.5%
コ 2
10.5%
セ 1
 
5.3%
タ 1
 
5.3%
CJK Compat Ideographs
ValueCountFrequency (%)
旅 1
50.0%
林 1
50.0%

출판사
Text

Distinct3064
Distinct (%)30.6%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2024-04-21T11:47:45.979949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length47
Mean length6.8048805
Min length1

Characters and Unicode

Total characters68042
Distinct characters748
Distinct categories12 ?
Distinct scripts6 ?
Distinct blocks9 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2035 ?
Unique (%)20.4%

Sample

1st row국토해양부
2nd row경상북도
3rd row국토해양부
4th row국토해양부
5th row더봄
ValueCountFrequency (%)
한국수자원공사 607
 
5.0%
건설교통부 267
 
2.2%
of 212
 
1.7%
국토해양부 184
 
1.5%
국토연구원 174
 
1.4%
건설부 174
 
1.4%
환경부 170
 
1.4%
산업기지개발공사 137
 
1.1%
충북대학교 132
 
1.1%
university 115
 
0.9%
Other values (3154) 10020
82.2%
2024-04-21T11:47:46.373675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2204
 
3.2%
국 2027
 
3.0%
원 1867
 
2.7%
사 1754
 
2.6%
한 1523
 
2.2%
공 1250
 
1.8%
부 1218
 
1.8%
A 1215
 
1.8%
e 1198
 
1.8%
E 1170
 
1.7%
Other values (738) 52616
77.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 42704
62.8%
Uppercase Letter 11995
 
17.6%
Lowercase Letter 10416
 
15.3%
Space Separator 2204
 
3.2%
Other Punctuation 482
 
0.7%
Dash Punctuation 106
 
0.2%
Decimal Number 100
 
0.1%
Close Punctuation 15
 
< 0.1%
Open Punctuation 15
 
< 0.1%
Other Symbol 3
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 2027
 
4.7%
원 1867
 
4.4%
사 1754
 
4.1%
한 1523
 
3.6%
공 1250
 
2.9%
부 1218
 
2.9%
학 1167
 
2.7%
대 1066
 
2.5%
교 1007
 
2.4%
수 976
 
2.3%
Other values (663) 28849
67.6%
Uppercase Letter
ValueCountFrequency (%)
A 1215
 
10.1%
E 1170
 
9.8%
S 1013
 
8.4%
I 908
 
7.6%
C 823
 
6.9%
R 773
 
6.4%
N 729
 
6.1%
O 684
 
5.7%
U 525
 
4.4%
T 502
 
4.2%
Other values (16) 3653
30.5%
Lowercase Letter
ValueCountFrequency (%)
e 1198
11.5%
i 965
9.3%
r 938
 
9.0%
n 927
 
8.9%
o 885
 
8.5%
s 833
 
8.0%
a 747
 
7.2%
t 599
 
5.8%
l 581
 
5.6%
c 358
 
3.4%
Other values (15) 2385
22.9%
Decimal Number
ValueCountFrequency (%)
2 49
49.0%
1 38
38.0%
0 6
 
6.0%
3 2
 
2.0%
6 1
 
1.0%
8 1
 
1.0%
7 1
 
1.0%
5 1
 
1.0%
4 1
 
1.0%
Other Punctuation
ValueCountFrequency (%)
. 311
64.5%
& 91
 
18.9%
, 41
 
8.5%
· 34
 
7.1%
/ 5
 
1.0%
Close Punctuation
ValueCountFrequency (%)
) 14
93.3%
] 1
 
6.7%
Open Punctuation
ValueCountFrequency (%)
( 14
93.3%
[ 1
 
6.7%
Other Symbol
ValueCountFrequency (%)
♥ 2
66.7%
㈜ 1
33.3%
Space Separator
ValueCountFrequency (%)
2204
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 106
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Math Symbol
ValueCountFrequency (%)
| 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 42421
62.3%
Latin 22411
32.9%
Common 2926
 
4.3%
Han 250
 
0.4%
Katakana 23
 
< 0.1%
Hiragana 11
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 2027
 
4.8%
원 1867
 
4.4%
사 1754
 
4.1%
한 1523
 
3.6%
공 1250
 
2.9%
부 1218
 
2.9%
학 1167
 
2.8%
대 1066
 
2.5%
교 1007
 
2.4%
수 976
 
2.3%
Other values (550) 28566
67.3%
Han
ValueCountFrequency (%)
會 22
 
8.8%
協 15
 
6.0%
水 12
 
4.8%
學 10
 
4.0%
鐵 9
 
3.6%
門 9
 
3.6%
管 9
 
3.6%
工 8
 
3.2%
設 7
 
2.8%
版 5
 
2.0%
Other values (85) 144
57.6%
Latin
ValueCountFrequency (%)
A 1215
 
5.4%
e 1198
 
5.3%
E 1170
 
5.2%
S 1013
 
4.5%
i 965
 
4.3%
r 938
 
4.2%
n 927
 
4.1%
I 908
 
4.1%
o 885
 
3.9%
s 833
 
3.7%
Other values (41) 12359
55.1%
Common
ValueCountFrequency (%)
2204
75.3%
. 311
 
10.6%
- 106
 
3.6%
& 91
 
3.1%
2 49
 
1.7%
, 41
 
1.4%
1 38
 
1.3%
· 34
 
1.2%
) 14
 
0.5%
( 14
 
0.5%
Other values (13) 24
 
0.8%
Katakana
ValueCountFrequency (%)
ム 4
17.4%
ダ 3
13.0%
コ 2
8.7%
ク 2
8.7%
リ 2
8.7%
ト 2
8.7%
ン 2
8.7%
ヴ 1
 
4.3%
ル 1
 
4.3%
ネ 1
 
4.3%
Other values (3) 3
13.0%
Hiragana
ValueCountFrequency (%)
ぎ 2
18.2%
い 2
18.2%
よ 2
18.2%
う 2
18.2%
せ 2
18.2%
ち 1
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 42411
62.3%
ASCII 25301
37.2%
CJK 246
 
0.4%
None 35
 
0.1%
Katakana 23
 
< 0.1%
Hiragana 11
 
< 0.1%
Compat Jamo 9
 
< 0.1%
CJK Compat Ideographs 4
 
< 0.1%
Misc Symbols 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2204
 
8.7%
A 1215
 
4.8%
e 1198
 
4.7%
E 1170
 
4.6%
S 1013
 
4.0%
i 965
 
3.8%
r 938
 
3.7%
n 927
 
3.7%
I 908
 
3.6%
o 885
 
3.5%
Other values (62) 13878
54.9%
Hangul
ValueCountFrequency (%)
국 2027
 
4.8%
원 1867
 
4.4%
사 1754
 
4.1%
한 1523
 
3.6%
공 1250
 
2.9%
부 1218
 
2.9%
학 1167
 
2.8%
대 1066
 
2.5%
교 1007
 
2.4%
수 976
 
2.3%
Other values (547) 28556
67.3%
None
ValueCountFrequency (%)
· 34
97.1%
㈜ 1
 
2.9%
CJK
ValueCountFrequency (%)
會 22
 
8.9%
協 15
 
6.1%
水 12
 
4.9%
學 10
 
4.1%
鐵 9
 
3.7%
門 9
 
3.7%
管 9
 
3.7%
工 8
 
3.3%
設 7
 
2.8%
版 5
 
2.0%
Other values (81) 140
56.9%
Compat Jamo
ValueCountFrequency (%)
ㆍ 8
88.9%
ㅣ 1
 
11.1%
Katakana
ValueCountFrequency (%)
ム 4
17.4%
ダ 3
13.0%
コ 2
8.7%
ク 2
8.7%
リ 2
8.7%
ト 2
8.7%
ン 2
8.7%
ヴ 1
 
4.3%
ル 1
 
4.3%
ネ 1
 
4.3%
Other values (3) 3
13.0%
Misc Symbols
ValueCountFrequency (%)
♥ 2
100.0%
Hiragana
ValueCountFrequency (%)
ぎ 2
18.2%
い 2
18.2%
よ 2
18.2%
う 2
18.2%
せ 2
18.2%
ち 1
9.1%
CJK Compat Ideographs
ValueCountFrequency (%)
理 1
25.0%
鹿 1
25.0%
旅 1
25.0%
漏 1
25.0%

출판년도
Real number (ℝ)

HIGH CORRELATION 

Distinct95
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2000.819
Minimum1923
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T11:47:46.511072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1923
5-th percentile1972
Q11992
median2003
Q32013
95-th percentile2020
Maximum2023
Range100
Interquartile range (IQR)21

Descriptive statistics

Standard deviation14.995097
Coefficient of variation (CV)0.0074944793
Kurtosis0.61243218
Mean2000.819
Median Absolute Deviation (MAD)10
Skewness-0.83042746
Sum20008190
Variance224.85292
MonotonicityNot monotonic
2024-04-21T11:47:46.825592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2009 327
 
3.3%
2010 319
 
3.2%
2008 315
 
3.1%
2013 315
 
3.1%
2007 309
 
3.1%
1994 299
 
3.0%
2020 296
 
3.0%
2012 296
 
3.0%
2016 287
 
2.9%
2006 285
 
2.9%
Other values (85) 6952
69.5%
ValueCountFrequency (%)
1923 1
 
< 0.1%
1926 1
 
< 0.1%
1927 1
 
< 0.1%
1929 1
 
< 0.1%
1930 1
 
< 0.1%
1932 1
 
< 0.1%
1934 2
< 0.1%
1935 1
 
< 0.1%
1936 3
< 0.1%
1937 3
< 0.1%
ValueCountFrequency (%)
2023 77
 
0.8%
2022 196
2.0%
2021 220
2.2%
2020 296
3.0%
2019 212
2.1%
2018 221
2.2%
2017 218
2.2%
2016 287
2.9%
2015 237
2.4%
2014 222
2.2%

Interactions

2024-04-21T11:47:43.869971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:47:43.628826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:47:43.957549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:47:43.780819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T11:47:46.907383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번출판년도
순번1.0000.950
출판년도0.9501.000
2024-04-21T11:47:46.989451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번출판년도
순번1.0001.000
출판년도1.0001.000

Missing values

2024-04-21T11:47:44.070107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T11:47:44.156269image/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.
2024-04-21T11:47:44.242697image/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

순번서명저자출판사출판년도
2828828289영산강(하류) 하천기본계획 보고서국토해양부 익산지방국토관리청 편;현대엔지니어링 편;삼안 편국토해양부2011
2746727468척산천 하천기본계획 보고서경상북도 편경상북도2010
2959629597추계학적 기법을 적용한 홍수예측체계 개선국토해양부 한강홍수통제소 편국토해양부2012
2431224313도시계획현황:2007국토해양부 편;한국토지공사 편국토해양부2008
3280432805강희대제(12)-제왕삼부곡 제1작얼웨허 저;홍순도 역더봄2016
60366037Stochastic Analysis of Drought PhenomenaUS Army Corps of Engineers 편US Army Corps of Engineers1985
2553925540뇌를 움직이는 메모사카토 켄지 저;김하경 역비즈니스세상2009
3890838909소리튠 영어혁명 ; 30년 영알못도 귀가 뚫리고 입이 트이는이정은 저미다스북스2022
94559456레이다를 이용한 단시간 강우예측 결과의 정성 및 정량적인평가(2) ; 모델 데스트 및 현업화기상연구소 편기상연구소1991
37933794Water quality evaluation of proposed twin valley lake wild rice river, minnesotaFord, Dennis E. 저;Thornton, Kent W. 저;Ford, W.Bryan 저U.S.Army Engineer Waterways Experiment Station1979
순번서명저자출판사출판년도
42484249기술지도서(40) ; 도로의선형설계건설부 편정우사1980
1572415725New 오성식 생활영어 SOS guide book두산출판 BG 편두산출판 BG1999
1701617017제8회 세계 물의 날 기념 물 심포지엄 2000 ; 21세기의 물홍보실 편;한국물학술단체연합회 편한국수자원공사2000
3073530736지역활성화를 위한 지방하천 정비사업 개선방향 연구차주영 저;이상민 저건축도시공간연구소2013
1260812609고도FCS-BIOFILM시스템에 의한 하수처리에 관한 연구김정현 저동아대학교대학원1995
2249822499한국수자원학회지:2006(V.39 No.1-6)한국수자원학회 편한국수자원학회2006
1339013391경영실적보고서(관리제도):1995경영관리실 편한국수자원공사1996
1514215143댐 일본(ダム 日本):1998년 9월호일본댐협회 편일본댐협회1998
82238224상수도시설개량 및 보완사업 수리용량 및 구조계산서(1)충주시 편충주시1989
1946119462에코 에너지호프만, 피터 저;강호산 역생각의 나무2003