Overview

Dataset statistics

Number of variables10
Number of observations1067
Missing cells159
Missing cells (%)1.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory83.5 KiB
Average record size in memory80.1 B

Variable types

Text5
Categorical4
DateTime1

Dataset

Description담수생물자원은행 누리집에서 분양중인 천연추출물 목록 정보입니다. 테이블에는 은행자원번호, 식물명, 학명, 과명, 추출부위, 추출용매, 추출방법, 채집일, 채집장소가 포함되어 있습니다.
URLhttps://www.data.go.kr/data/15039059/fileData.do

Alerts

데이터 기준일 has constant value ""Constant
추출용매 is highly overall correlated with 추출방법High correlation
추출방법 is highly overall correlated with 추출용매High correlation
식물명 has 159 (14.9%) missing valuesMissing
은행자원번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 03:01:43.957482
Analysis finished2023-12-12 03:01:44.939183
Duration0.98 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

은행자원번호
Text

UNIQUE 

Distinct1067
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size8.5 KiB
2023-12-12T12:01:45.240289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length10.402062
Min length8

Characters and Unicode

Total characters11099
Distinct characters17
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

Unique1067 ?
Unique (%)100.0%

Sample

1st rowFBCC-EP29
2nd rowFBCC-EP34
3rd rowFBCC-EP38
4th rowFBCC-EP48
5th rowFBCC-EP85
ValueCountFrequency (%)
fbcc-ep29 1
 
0.1%
fbcc-ep1225 1
 
0.1%
fbcc-ep1238 1
 
0.1%
fbcc-ep1208 1
 
0.1%
fbcc-ep1237 1
 
0.1%
fbcc-ep1236 1
 
0.1%
fbcc-ep1235 1
 
0.1%
fbcc-ep1234 1
 
0.1%
fbcc-ep1233 1
 
0.1%
fbcc-ep1232 1
 
0.1%
Other values (1057) 1057
99.1%
2023-12-12T12:01:45.785564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 2134
19.2%
B 1082
9.7%
F 1067
9.6%
- 1067
9.6%
E 1067
9.6%
P 1042
9.4%
1 819
 
7.4%
4 382
 
3.4%
3 372
 
3.4%
2 366
 
3.3%
Other values (7) 1701
15.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 6402
57.7%
Decimal Number 3630
32.7%
Dash Punctuation 1067
 
9.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 819
22.6%
4 382
10.5%
3 372
10.2%
2 366
10.1%
5 298
 
8.2%
8 294
 
8.1%
6 291
 
8.0%
7 287
 
7.9%
0 278
 
7.7%
9 243
 
6.7%
Uppercase Letter
ValueCountFrequency (%)
C 2134
33.3%
B 1082
16.9%
F 1067
16.7%
E 1067
16.7%
P 1042
16.3%
A 10
 
0.2%
Dash Punctuation
ValueCountFrequency (%)
- 1067
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6402
57.7%
Common 4697
42.3%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1067
22.7%
1 819
17.4%
4 382
 
8.1%
3 372
 
7.9%
2 366
 
7.8%
5 298
 
6.3%
8 294
 
6.3%
6 291
 
6.2%
7 287
 
6.1%
0 278
 
5.9%
Latin
ValueCountFrequency (%)
C 2134
33.3%
B 1082
16.9%
F 1067
16.7%
E 1067
16.7%
P 1042
16.3%
A 10
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11099
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
C 2134
19.2%
B 1082
9.7%
F 1067
9.6%
- 1067
9.6%
E 1067
9.6%
P 1042
9.4%
1 819
 
7.4%
4 382
 
3.4%
3 372
 
3.4%
2 366
 
3.3%
Other values (7) 1701
15.3%

식물명
Text

MISSING 

Distinct222
Distinct (%)24.4%
Missing159
Missing (%)14.9%
Memory size8.5 KiB
2023-12-12T12:01:46.180329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.8557269
Min length1

Characters and Unicode

Total characters3501
Distinct characters267
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)1.5%

Sample

1st row벳지
2nd row참소리쟁이
3rd row벼룩이자리
4th row돌피
5th row한련초
ValueCountFrequency (%)
낙지다리 23
 
2.5%
물방동사니 18
 
2.0%
왕버들 18
 
2.0%
여뀌바늘 16
 
1.8%
갈풀 14
 
1.5%
갯버들 13
 
1.4%
연 12
 
1.3%
소리쟁이 10
 
1.1%
돌소리쟁이 10
 
1.1%
흑삼릉 10
 
1.1%
Other values (212) 764
84.1%
2023-12-12T12:01:46.812562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 166
 
4.7%
나 150
 
4.3%
이 122
 
3.5%
풀 104
 
3.0%
사 103
 
2.9%
무 98
 
2.8%
물 89
 
2.5%
개 87
 
2.5%
들 86
 
2.5%
버 60
 
1.7%
Other values (257) 2436
69.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3501
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 166
 
4.7%
나 150
 
4.3%
이 122
 
3.5%
풀 104
 
3.0%
사 103
 
2.9%
무 98
 
2.8%
물 89
 
2.5%
개 87
 
2.5%
들 86
 
2.5%
버 60
 
1.7%
Other values (257) 2436
69.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3501
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 166
 
4.7%
나 150
 
4.3%
이 122
 
3.5%
풀 104
 
3.0%
사 103
 
2.9%
무 98
 
2.8%
물 89
 
2.5%
개 87
 
2.5%
들 86
 
2.5%
버 60
 
1.7%
Other values (257) 2436
69.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3501
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 166
 
4.7%
나 150
 
4.3%
이 122
 
3.5%
풀 104
 
3.0%
사 103
 
2.9%
무 98
 
2.8%
물 89
 
2.5%
개 87
 
2.5%
들 86
 
2.5%
버 60
 
1.7%
Other values (257) 2436
69.6%

학명
Text

Distinct326
Distinct (%)30.6%
Missing0
Missing (%)0.0%
Memory size8.5 KiB
2023-12-12T12:01:47.297095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length80
Median length50
Mean length25.669166
Min length10

Characters and Unicode

Total characters27389
Distinct characters67
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

Unique41 ?
Unique (%)3.8%

Sample

1st rowVicia villosa Roth
2nd rowRumex japonicus Houtt.
3rd rowBoehmeria tricuspis var. paraspicata Nakai ex H. Gara
4th rowArenaria serpyllifolia L..
5th rowEchinochloa crusgalli (L.) P. Beauv.
ValueCountFrequency (%)
l 228
 
6.5%
salix 85
 
2.4%
var 62
 
1.8%
japonica 51
 
1.4%
ex 48
 
1.4%
thunb 41
 
1.2%
cyperus 38
 
1.1%
37
 
1.0%
polygonum 35
 
1.0%
steud 32
 
0.9%
Other values (568) 2876
81.4%
2023-12-12T12:01:48.047797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 2702
 
9.9%
2466
 
9.0%
i 2334
 
8.5%
e 1595
 
5.8%
s 1524
 
5.6%
r 1418
 
5.2%
u 1370
 
5.0%
n 1303
 
4.8%
o 1288
 
4.7%
l 1280
 
4.7%
Other values (57) 10109
36.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 21340
77.9%
Space Separator 2466
 
9.0%
Uppercase Letter 2234
 
8.2%
Other Punctuation 940
 
3.4%
Close Punctuation 176
 
0.6%
Open Punctuation 176
 
0.6%
Dash Punctuation 28
 
0.1%
Nonspacing Mark 13
 
< 0.1%
Math Symbol 8
 
< 0.1%
Decimal Number 8
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 2702
12.7%
i 2334
10.9%
e 1595
 
7.5%
s 1524
 
7.1%
r 1418
 
6.6%
u 1370
 
6.4%
n 1303
 
6.1%
o 1288
 
6.0%
l 1280
 
6.0%
c 961
 
4.5%
Other values (17) 5565
26.1%
Uppercase Letter
ValueCountFrequency (%)
L 337
15.1%
S 304
13.6%
P 197
 
8.8%
M 164
 
7.3%
A 151
 
6.8%
C 151
 
6.8%
T 134
 
6.0%
R 114
 
5.1%
H 90
 
4.0%
B 83
 
3.7%
Other values (15) 509
22.8%
Other Punctuation
ValueCountFrequency (%)
. 885
94.1%
& 44
 
4.7%
; 7
 
0.7%
, 4
 
0.4%
Nonspacing Mark
ValueCountFrequency (%)
́ 8
61.5%
̀ 4
30.8%
̈ 1
 
7.7%
Decimal Number
ValueCountFrequency (%)
0 4
50.0%
2 2
25.0%
5 2
25.0%
Space Separator
ValueCountFrequency (%)
2466
100.0%
Close Punctuation
ValueCountFrequency (%)
) 176
100.0%
Open Punctuation
ValueCountFrequency (%)
( 176
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%
Math Symbol
ValueCountFrequency (%)
× 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 23574
86.1%
Common 3802
 
13.9%
Inherited 13
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 2702
 
11.5%
i 2334
 
9.9%
e 1595
 
6.8%
s 1524
 
6.5%
r 1418
 
6.0%
u 1370
 
5.8%
n 1303
 
5.5%
o 1288
 
5.5%
l 1280
 
5.4%
c 961
 
4.1%
Other values (42) 7799
33.1%
Common
ValueCountFrequency (%)
2466
64.9%
. 885
 
23.3%
) 176
 
4.6%
( 176
 
4.6%
& 44
 
1.2%
- 28
 
0.7%
× 8
 
0.2%
; 7
 
0.2%
, 4
 
0.1%
0 4
 
0.1%
Other values (2) 4
 
0.1%
Inherited
ValueCountFrequency (%)
́ 8
61.5%
̀ 4
30.8%
̈ 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27366
99.9%
Diacriticals 13
 
< 0.1%
None 10
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 2702
 
9.9%
2466
 
9.0%
i 2334
 
8.5%
e 1595
 
5.8%
s 1524
 
5.6%
r 1418
 
5.2%
u 1370
 
5.0%
n 1303
 
4.8%
o 1288
 
4.7%
l 1280
 
4.7%
Other values (52) 10086
36.9%
None
ValueCountFrequency (%)
× 8
80.0%
ü 2
 
20.0%
Diacriticals
ValueCountFrequency (%)
́ 8
61.5%
̀ 4
30.8%
̈ 1
 
7.7%

과명
Text

Distinct81
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Memory size8.5 KiB
2023-12-12T12:01:48.788994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length10.568885
Min length7

Characters and Unicode

Total characters11277
Distinct characters42
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)1.1%

Sample

1st rowFabaceae
2nd rowPolygonaceae
3rd rowUrticaceae
4th rowCaryophyllaceae
5th rowPoaceae
ValueCountFrequency (%)
poaceae 117
 
11.0%
cyperaceae 114
 
10.7%
salicaceae 94
 
8.8%
polygonaceae 76
 
7.1%
asteraceae 68
 
6.4%
lamiaceae 35
 
3.3%
fabaceae 27
 
2.5%
brassicaceae 26
 
2.4%
betulaceae 25
 
2.3%
typhaceae 24
 
2.2%
Other values (71) 461
43.2%
2023-12-12T12:01:49.357038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 2631
23.3%
e 2483
22.0%
c 1307
11.6%
r 500
 
4.4%
o 489
 
4.3%
l 373
 
3.3%
i 373
 
3.3%
y 298
 
2.6%
n 291
 
2.6%
p 246
 
2.2%
Other values (32) 2286
20.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10210
90.5%
Uppercase Letter 1067
 
9.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 2631
25.8%
e 2483
24.3%
c 1307
12.8%
r 500
 
4.9%
o 489
 
4.8%
l 373
 
3.7%
i 373
 
3.7%
y 298
 
2.9%
n 291
 
2.9%
p 246
 
2.4%
Other values (12) 1219
11.9%
Uppercase Letter
ValueCountFrequency (%)
P 227
21.3%
C 190
17.8%
S 142
13.3%
A 106
9.9%
B 65
 
6.1%
L 55
 
5.2%
T 43
 
4.0%
F 33
 
3.1%
R 32
 
3.0%
H 29
 
2.7%
Other values (10) 145
13.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 11277
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 2631
23.3%
e 2483
22.0%
c 1307
11.6%
r 500
 
4.4%
o 489
 
4.3%
l 373
 
3.3%
i 373
 
3.3%
y 298
 
2.6%
n 291
 
2.6%
p 246
 
2.2%
Other values (32) 2286
20.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11277
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 2631
23.3%
e 2483
22.0%
c 1307
11.6%
r 500
 
4.4%
o 489
 
4.3%
l 373
 
3.3%
i 373
 
3.3%
y 298
 
2.6%
n 291
 
2.6%
p 246
 
2.2%
Other values (32) 2286
20.3%

추출부위
Categorical

Distinct11
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size8.5 KiB
전초
440 
지상부
164 
지하부
133 
잎
129 
가지
96 
Other values (6)
105 

Length

Max length4
Median length2
Mean length2.1799438
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전초
2nd row지하부
3rd row전초
4th row전초
5th row지상부

Common Values

ValueCountFrequency (%)
전초 440
41.2%
지상부 164
 
15.4%
지하부 133
 
12.5%
잎 129
 
12.1%
가지 96
 
9.0%
줄기 40
 
3.7%
꽃 30
 
2.8%
<NA> 27
 
2.5%
수피 4
 
0.4%
이삭 2
 
0.2%

Length

2023-12-12T12:01:49.584261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전초 440
41.2%
지상부 164
 
15.4%
지하부 133
 
12.5%
잎 129
 
12.1%
가지 96
 
9.0%
줄기 40
 
3.7%
꽃 30
 
2.8%
na 27
 
2.5%
수피 4
 
0.4%
이삭 2
 
0.2%

추출용매
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size8.5 KiB
증류수
534 
70%에탄올
508 
기타
 
15
메탄올
 
10

Length

Max length6
Median length3
Mean length4.4142455
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row70%에탄올
2nd row70%에탄올
3rd row70%에탄올
4th row70%에탄올
5th row70%에탄올

Common Values

ValueCountFrequency (%)
증류수 534
50.0%
70%에탄올 508
47.6%
기타 15
 
1.4%
메탄올 10
 
0.9%

Length

2023-12-12T12:01:49.771169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:01:49.936701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
증류수 534
50.0%
70%에탄올 508
47.6%
기타 15
 
1.4%
메탄올 10
 
0.9%

추출방법
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.5 KiB
열수추출
534 
용매추출
533 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
열수추출 534
50.0%
용매추출 533
50.0%

Length

2023-12-12T12:01:50.112768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:01:50.277571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
열수추출 534
50.0%
용매추출 533
50.0%

채집일
Date

Distinct152
Distinct (%)14.2%
Missing0
Missing (%)0.0%
Memory size8.5 KiB
Minimum2011-10-03 00:00:00
Maximum2022-07-25 00:00:00
2023-12-12T12:01:50.419789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:01:50.603761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

채집장소
Text

Distinct273
Distinct (%)25.6%
Missing0
Missing (%)0.0%
Memory size8.5 KiB
2023-12-12T12:01:51.025186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length26
Mean length19.538894
Min length9

Characters and Unicode

Total characters20848
Distinct characters247
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)1.3%

Sample

1st row경상북도 상주시 병성동 805-69
2nd row경상북도 상주시 병성동 689
3rd row경상북도 문경시 농암면 내서리 산 17-14
4th row경상북도 상주 도남동 703-4
5th row경상북도 안동 풍천면 광덕리 2-1
ValueCountFrequency (%)
경상북도 298
 
6.0%
경상남도 191
 
3.9%
강원도 114
 
2.3%
충청남도 105
 
2.1%
충청북도 94
 
1.9%
문경시 73
 
1.5%
창녕군 67
 
1.4%
경기도 65
 
1.3%
예천군 58
 
1.2%
인제군 53
 
1.1%
Other values (650) 3843
77.5%
2023-12-12T12:01:51.685147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4330
20.8%
도 1028
 
4.9%
리 912
 
4.4%
경 743
 
3.6%
면 630
 
3.0%
군 578
 
2.8%
상 576
 
2.8%
북 519
 
2.5%
시 490
 
2.4%
남 465
 
2.2%
Other values (237) 10577
50.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13446
64.5%
Space Separator 4330
 
20.8%
Decimal Number 2516
 
12.1%
Dash Punctuation 256
 
1.2%
Math Symbol 249
 
1.2%
Uppercase Letter 46
 
0.2%
Other Punctuation 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 1028
 
7.6%
리 912
 
6.8%
경 743
 
5.5%
면 630
 
4.7%
군 578
 
4.3%
상 576
 
4.3%
북 519
 
3.9%
시 490
 
3.6%
남 465
 
3.5%
읍 301
 
2.2%
Other values (200) 7204
53.6%
Decimal Number
ValueCountFrequency (%)
1 330
13.1%
２ 204
 
8.1%
2 179
 
7.1%
１ 178
 
7.1%
4 156
 
6.2%
６ 144
 
5.7%
３ 143
 
5.7%
５ 136
 
5.4%
3 135
 
5.4%
４ 124
 
4.9%
Other values (10) 787
31.3%
Uppercase Letter
ValueCountFrequency (%)
H 8
17.4%
P 6
13.0%
F 6
13.0%
R 4
8.7%
V 4
8.7%
G 4
8.7%
J 4
8.7%
X 2
 
4.3%
M 2
 
4.3%
Q 2
 
4.3%
Other values (2) 4
8.7%
Math Symbol
ValueCountFrequency (%)
− 239
96.0%
+ 10
 
4.0%
Space Separator
ValueCountFrequency (%)
4330
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 256
100.0%
Other Punctuation
ValueCountFrequency (%)
. 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13446
64.5%
Common 7356
35.3%
Latin 46
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 1028
 
7.6%
리 912
 
6.8%
경 743
 
5.5%
면 630
 
4.7%
군 578
 
4.3%
상 576
 
4.3%
북 519
 
3.9%
시 490
 
3.6%
남 465
 
3.5%
읍 301
 
2.2%
Other values (200) 7204
53.6%
Common
ValueCountFrequency (%)
4330
58.9%
1 330
 
4.5%
- 256
 
3.5%
− 239
 
3.2%
２ 204
 
2.8%
2 179
 
2.4%
１ 178
 
2.4%
4 156
 
2.1%
６ 144
 
2.0%
３ 143
 
1.9%
Other values (15) 1197
 
16.3%
Latin
ValueCountFrequency (%)
H 8
17.4%
P 6
13.0%
F 6
13.0%
R 4
8.7%
V 4
8.7%
G 4
8.7%
J 4
8.7%
X 2
 
4.3%
M 2
 
4.3%
Q 2
 
4.3%
Other values (2) 4
8.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13446
64.5%
ASCII 5891
28.3%
None 1272
 
6.1%
Math Operators 239
 
1.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4330
73.5%
1 330
 
5.6%
- 256
 
4.3%
2 179
 
3.0%
4 156
 
2.6%
3 135
 
2.3%
5 122
 
2.1%
8 109
 
1.9%
9 81
 
1.4%
7 72
 
1.2%
Other values (16) 121
 
2.1%
Hangul
ValueCountFrequency (%)
도 1028
 
7.6%
리 912
 
6.8%
경 743
 
5.5%
면 630
 
4.7%
군 578
 
4.3%
상 576
 
4.3%
북 519
 
3.9%
시 490
 
3.6%
남 465
 
3.5%
읍 301
 
2.2%
Other values (200) 7204
53.6%
Math Operators
ValueCountFrequency (%)
− 239
100.0%
None
ValueCountFrequency (%)
２ 204
16.0%
１ 178
14.0%
６ 144
11.3%
３ 143
11.2%
５ 136
10.7%
４ 124
9.7%
９ 117
9.2%
７ 83
6.5%
０ 83
6.5%
８ 60
 
4.7%

데이터 기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size8.5 KiB
2023-05-17
1067 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-05-17
2nd row2023-05-17
3rd row2023-05-17
4th row2023-05-17
5th row2023-05-17

Common Values

ValueCountFrequency (%)
2023-05-17 1067
100.0%

Length

2023-12-12T12:01:51.883057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:01:52.033810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-05-17 1067
100.0%

Correlations

2023-12-12T12:01:52.117326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과명추출부위추출용매추출방법
과명1.0000.6920.9560.000
추출부위0.6921.0000.0000.000
추출용매0.9560.0001.0001.000
추출방법0.0000.0001.0001.000
2023-12-12T12:01:52.228444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
추출부위추출용매추출방법
추출부위1.0000.0000.000
추출용매0.0001.0000.999
추출방법0.0000.9991.000
2023-12-12T12:01:52.362430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
추출부위추출용매추출방법
추출부위1.0000.0000.000
추출용매0.0001.0000.999
추출방법0.0000.9991.000

Missing values

2023-12-12T12:01:44.694779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:01:44.871078image/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.

Sample

은행자원번호식물명학명과명추출부위추출용매추출방법채집일채집장소데이터 기준일
0FBCC-EP29벳지Vicia villosa RothFabaceae전초70%에탄올용매추출2016-06-08경상북도 상주시 병성동 805-692023-05-17
1FBCC-EP34참소리쟁이Rumex japonicus Houtt.Polygonaceae지하부70%에탄올용매추출2016-06-08경상북도 상주시 병성동 6892023-05-17
2FBCC-EP38<NA>Boehmeria tricuspis var. paraspicata Nakai ex H. GaraUrticaceae전초70%에탄올용매추출2016-05-12경상북도 문경시 농암면 내서리 산 17-142023-05-17
3FBCC-EP48벼룩이자리Arenaria serpyllifolia L..Caryophyllaceae전초70%에탄올용매추출2016-04-22경상북도 상주 도남동 703-42023-05-17
4FBCC-EP85돌피Echinochloa crusgalli (L.) P. Beauv.Poaceae지상부70%에탄올용매추출2016-09-01경상북도 안동 풍천면 광덕리 2-12023-05-17
5FBCC-EP87한련초Eclipta prostrata (L.) L.Asteraceae전초70%에탄올용매추출2016-09-01경상북도 안동 풍천면 광덕리 2-12023-05-17
6FBCC-EP88<NA>Polygonum hydropiper L.Polygonaceae전초70%에탄올용매추출2016-09-01경상북도 안동 풍천면 광덕리 2-12023-05-17
7FBCC-EP89울산도깨비바늘Bidens pilosa L.Asteraceae전초70%에탄올용매추출2016-09-01경상북도 안동 풍천면 광덕리 32023-05-17
8FBCC-EP92가시도꼬마리Xanthium strumarium L.Asteraceae지상부70%에탄올용매추출2016-09-08경상북도 안동 도산면 동부리 새터교2023-05-17
9FBCC-EP93결명자Senna toraFabaceae지상부70%에탄올용매추출2016-09-08경상북도 안동 도산면 동부리 새터교2023-05-17
은행자원번호식물명학명과명추출부위추출용매추출방법채집일채집장소데이터 기준일
1057FBCC-EB15<NA>Sphingobium qiguoniiSphingomonadaceae<NA>기타용매추출2019-03-21전라남도 순천시 대대동 184-222023-05-17
1058FBCC-EB18<NA>Erythrobacter xanthusErythrobacteraceae<NA>기타용매추출2019-03-21전라남도 순천시 대대동 184-222023-05-17
1059FBCC-EB2<NA>Dickeya dadantii subsp. dadantiiPectobacteriaceae<NA>기타용매추출2019-03-21전라남도 순천시 대대동 184-222023-05-17
1060FBCC-EB20<NA>Altererythrobacter salegensErythrobacteraceae<NA>기타용매추출2019-03-21전라남도 순천시 대대동 184-222023-05-17
1061FBCC-EB4<NA>Erythrobacter xanthusErythrobacteraceae<NA>기타용매추출2019-03-21전라남도 순천시 대대동 184-222023-05-17
1062FBCC-EB5<NA>Shewanella fodinaeShewanellaceae<NA>기타용매추출2019-03-21전라남도 순천시 대대동 184-222023-05-17
1063FBCC-EB6<NA>Pedobacter lentusSphingobacteriaceae<NA>기타용매추출2019-03-21전라남도 순천시 대대동 184-222023-05-17
1064FBCC-EB7<NA>Sphingorhabdus flavimarisSphingomonadaceae<NA>기타용매추출2019-03-21전라남도 순천시 대대동 184-222023-05-17
1065FBCC-EB8<NA>Jiella aquimarisAurantimonadaceae<NA>기타용매추출2019-03-21전라남도 순천시 대대동 184-222023-05-17
1066FBCC-EB9<NA>Sphingorhabdus flavimarisSphingomonadaceae<NA>기타용매추출2019-03-21전라남도 순천시 대대동 184-222023-05-17