Overview

Dataset statistics

Number of variables5
Number of observations135
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.5 KiB
Average record size in memory41.9 B

Variable types

Numeric1
Text3
Categorical1

Dataset

Description희귀.특산식물 목록 현황(국명, 과명, 학명 등)전북특별자치도지역의 희귀, 특산식물의 국제적으로 통용되는 학술적인 표준어 등우리기관에서는 더 이상 생성 불가 데이터입니다.
Author전북특별자치도
URLhttps://www.data.go.kr/data/15056485/fileData.do

Alerts

번호 is highly overall correlated with 비 고High correlation
비 고 is highly overall correlated with 번호High correlation
번호 has unique valuesUnique
국 명 has unique valuesUnique
학 명 has unique valuesUnique

Reproduction

Analysis started2024-03-14 21:05:26.490084
Analysis finished2024-03-14 21:05:27.725922
Duration1.24 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct135
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean68
Minimum1
Maximum135
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-15T06:05:28.093138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7.7
Q134.5
median68
Q3101.5
95-th percentile128.3
Maximum135
Range134
Interquartile range (IQR)67

Descriptive statistics

Standard deviation39.115214
Coefficient of variation (CV)0.57522374
Kurtosis-1.2
Mean68
Median Absolute Deviation (MAD)34
Skewness0
Sum9180
Variance1530
MonotonicityStrictly increasing
2024-03-15T06:05:28.375781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
94 1
 
0.7%
88 1
 
0.7%
89 1
 
0.7%
90 1
 
0.7%
91 1
 
0.7%
92 1
 
0.7%
93 1
 
0.7%
95 1
 
0.7%
2 1
 
0.7%
Other values (125) 125
92.6%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
135 1
0.7%
134 1
0.7%
133 1
0.7%
132 1
0.7%
131 1
0.7%
130 1
0.7%
129 1
0.7%
128 1
0.7%
127 1
0.7%
126 1
0.7%

국 명
Text

UNIQUE 

Distinct135
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-03-15T06:05:29.630530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4.1333333
Min length2

Characters and Unicode

Total characters558
Distinct characters204
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

Unique135 ?
Unique (%)100.0%

Sample

1st row벌레먹이말
2nd row청사조
3rd row벌깨풀
4th row광릉요강꽃
5th row백운난
ValueCountFrequency (%)
벌레먹이말 1
 
0.7%
이삭귀개 1
 
0.7%
만병초 1
 
0.7%
지치 1
 
0.7%
개지치 1
 
0.7%
쥐방울덩굴 1
 
0.7%
개족도리풀 1
 
0.7%
히어리 1
 
0.7%
태백제비꽃 1
 
0.7%
솜양지꽃 1
 
0.7%
Other values (125) 125
92.6%
2024-03-15T06:05:31.294234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
나 30
 
5.4%
꽃 24
 
4.3%
리 24
 
4.3%
무 20
 
3.6%
이 11
 
2.0%
초 10
 
1.8%
사 9
 
1.6%
풀 8
 
1.4%
미 8
 
1.4%
물 8
 
1.4%
Other values (194) 406
72.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 558
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
나 30
 
5.4%
꽃 24
 
4.3%
리 24
 
4.3%
무 20
 
3.6%
이 11
 
2.0%
초 10
 
1.8%
사 9
 
1.6%
풀 8
 
1.4%
미 8
 
1.4%
물 8
 
1.4%
Other values (194) 406
72.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 558
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
나 30
 
5.4%
꽃 24
 
4.3%
리 24
 
4.3%
무 20
 
3.6%
이 11
 
2.0%
초 10
 
1.8%
사 9
 
1.6%
풀 8
 
1.4%
미 8
 
1.4%
물 8
 
1.4%
Other values (194) 406
72.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 558
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
나 30
 
5.4%
꽃 24
 
4.3%
리 24
 
4.3%
무 20
 
3.6%
이 11
 
2.0%
초 10
 
1.8%
사 9
 
1.6%
풀 8
 
1.4%
미 8
 
1.4%
물 8
 
1.4%
Other values (194) 406
72.8%

과 명
Text

Distinct63
Distinct (%)46.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-03-15T06:05:32.303834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4.0074074
Min length2

Characters and Unicode

Total characters541
Distinct characters110
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

Unique36 ?
Unique (%)26.7%

Sample

1st row벌레잡이풀과
2nd row갈매나무과
3rd row꿀풀과
4th row난초과
5th row난초과
ValueCountFrequency (%)
국화과 12
 
8.9%
난초과 10
 
7.4%
미나리아재비과 10
 
7.4%
물푸레나무과 5
 
3.7%
붓꽃과 5
 
3.7%
산형과 5
 
3.7%
꿀풀과 4
 
3.0%
백합과 4
 
3.0%
수선화과 4
 
3.0%
콩과 3
 
2.2%
Other values (53) 73
54.1%
2024-03-15T06:05:33.659784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 135
25.0%
나 34
 
6.3%
무 22
 
4.1%
리 17
 
3.1%
화 16
 
3.0%
초 15
 
2.8%
비 13
 
2.4%
국 12
 
2.2%
미 12
 
2.2%
아 11
 
2.0%
Other values (100) 254
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 541
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 135
25.0%
나 34
 
6.3%
무 22
 
4.1%
리 17
 
3.1%
화 16
 
3.0%
초 15
 
2.8%
비 13
 
2.4%
국 12
 
2.2%
미 12
 
2.2%
아 11
 
2.0%
Other values (100) 254
47.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 541
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 135
25.0%
나 34
 
6.3%
무 22
 
4.1%
리 17
 
3.1%
화 16
 
3.0%
초 15
 
2.8%
비 13
 
2.4%
국 12
 
2.2%
미 12
 
2.2%
아 11
 
2.0%
Other values (100) 254
47.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 541
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 135
25.0%
나 34
 
6.3%
무 22
 
4.1%
리 17
 
3.1%
화 16
 
3.0%
초 15
 
2.8%
비 13
 
2.4%
국 12
 
2.2%
미 12
 
2.2%
아 11
 
2.0%
Other values (100) 254
47.0%

학 명
Text

UNIQUE 

Distinct135
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-03-15T06:05:35.222700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length78
Median length48
Mean length32.703704
Min length16

Characters and Unicode

Total characters4415
Distinct characters57
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique135 ?
Unique (%)100.0%

Sample

1st rowAldrovanda vesiculosa L.
2nd rowBerchemia racemosa Siebold & Zucc.
3rd rowDracocephalum rupestre Hance
4th rowCypripedium japonicum Thunb.
5th rowVexillabium yakushimensis (Yamam.) F.Maek.
ValueCountFrequency (%)
nakai 30
 
5.3%
20
 
3.5%
var 16
 
2.8%
l 14
 
2.5%
ex 11
 
1.9%
maxim 10
 
1.8%
makino 7
 
1.2%
koreana 7
 
1.2%
japonica 5
 
0.9%
siebold 5
 
0.9%
Other values (363) 443
78.0%
2024-03-15T06:05:37.238035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 453
 
10.3%
439
 
9.9%
i 371
 
8.4%
e 263
 
6.0%
o 240
 
5.4%
r 215
 
4.9%
n 213
 
4.8%
s 195
 
4.4%
. 176
 
4.0%
u 165
 
3.7%
Other values (47) 1685
38.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3269
74.0%
Space Separator 439
 
9.9%
Uppercase Letter 421
 
9.5%
Other Punctuation 200
 
4.5%
Close Punctuation 43
 
1.0%
Open Punctuation 42
 
1.0%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 453
13.9%
i 371
11.3%
e 263
 
8.0%
o 240
 
7.3%
r 215
 
6.6%
n 213
 
6.5%
s 195
 
6.0%
u 165
 
5.0%
l 165
 
5.0%
c 137
 
4.2%
Other values (16) 852
26.1%
Uppercase Letter
ValueCountFrequency (%)
S 44
 
10.5%
L 42
 
10.0%
C 37
 
8.8%
M 35
 
8.3%
N 33
 
7.8%
H 25
 
5.9%
K 24
 
5.7%
B 21
 
5.0%
P 19
 
4.5%
A 19
 
4.5%
Other values (14) 122
29.0%
Other Punctuation
ValueCountFrequency (%)
. 176
88.0%
& 20
 
10.0%
, 4
 
2.0%
Space Separator
ValueCountFrequency (%)
439
100.0%
Close Punctuation
ValueCountFrequency (%)
) 43
100.0%
Open Punctuation
ValueCountFrequency (%)
( 42
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3690
83.6%
Common 725
 
16.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 453
 
12.3%
i 371
 
10.1%
e 263
 
7.1%
o 240
 
6.5%
r 215
 
5.8%
n 213
 
5.8%
s 195
 
5.3%
u 165
 
4.5%
l 165
 
4.5%
c 137
 
3.7%
Other values (40) 1273
34.5%
Common
ValueCountFrequency (%)
439
60.6%
. 176
24.3%
) 43
 
5.9%
( 42
 
5.8%
& 20
 
2.8%
, 4
 
0.6%
- 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4415
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 453
 
10.3%
439
 
9.9%
i 371
 
8.4%
e 263
 
6.0%
o 240
 
5.4%
r 215
 
4.9%
n 213
 
4.8%
s 195
 
4.4%
. 176
 
4.0%
u 165
 
3.7%
Other values (47) 1685
38.2%

비 고
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
희귀식물(VU)
30 
희귀식물(NT)
29 
특산식물
21 
희귀식물(CR)
14 
희귀식물(EN)
14 
Other values (7)
27 

Length

Max length13
Median length8
Mean length7.9703704
Min length4

Unique

Unique2 ?
Unique (%)1.5%

Sample

1st row희귀식물(EW)
2nd row희귀식물(CR)
3rd row희귀식물(CR)
4th row희귀식물(CR)
5th row희귀식물(CR)

Common Values

ValueCountFrequency (%)
희귀식물(VU) 30
22.2%
희귀식물(NT) 29
21.5%
특산식물 21
15.6%
희귀식물(CR) 14
10.4%
희귀식물(EN) 14
10.4%
희귀식물(DD) 10
 
7.4%
희귀식물(NT),특산식물 5
 
3.7%
희귀식물(EN),특산식물 4
 
3.0%
희귀식물(CR),특산식물 3
 
2.2%
희귀식물(VU),특산식물 3
 
2.2%
Other values (2) 2
 
1.5%

Length

2024-03-15T06:05:37.700106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
희귀식물(vu 30
22.2%
희귀식물(nt 29
21.5%
특산식물 21
15.6%
희귀식물(cr 14
10.4%
희귀식물(en 14
10.4%
희귀식물(dd 10
 
7.4%
희귀식물(nt),특산식물 5
 
3.7%
희귀식물(en),특산식물 4
 
3.0%
희귀식물(cr),특산식물 3
 
2.2%
희귀식물(vu),특산식물 3
 
2.2%
Other values (2) 2
 
1.5%

Interactions

2024-03-15T06:05:26.922782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T06:05:37.984979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호과 명비 고
번호1.0000.7990.861
과 명0.7991.0000.646
비 고0.8610.6461.000
2024-03-15T06:05:38.225079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호비 고
번호1.0000.595
비 고0.5951.000

Missing values

2024-03-15T06:05:27.267724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T06:05:27.585531image/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

번호국 명과 명학 명비 고
01벌레먹이말벌레잡이풀과Aldrovanda vesiculosa L.희귀식물(EW)
12청사조갈매나무과Berchemia racemosa Siebold & Zucc.희귀식물(CR)
23벌깨풀꿀풀과Dracocephalum rupestre Hance희귀식물(CR)
34광릉요강꽃난초과Cypripedium japonicum Thunb.희귀식물(CR)
45백운난난초과Vexillabium yakushimensis (Yamam.) F.Maek.희귀식물(CR)
56복주머니란난초과Cypripedium macranthon Sw.희귀식물(CR)
67애기천마난초과Hetaeria sikokiana (Makino & F.Maek.) Tuyama희귀식물(CR)
78으름난초난초과Galeola septentrionalis Rchb.f.희귀식물(CR)
89미선나무물푸레나무과Abeliophyllum distichum Nakai희귀식물(CR),특산식물
910남방바람꽃미나리아재비과Anemone flaccida F.Schmidt희귀식물(CR)
번호국 명과 명학 명비 고
125126넓은잎각시붓꽃붓꽃과Iris rossii var. latifolia J.K.Sim & Y.S.Kim특산식물
126127붉노랑상사화수선화과Lycorsis flavenscens M.Y.Kim & S.T.Lee특산식물
127128매미꽃양귀비과Coreanomecon hylomeconoides Nakai특산식물
128129병꽃나무인동과Weigela subsessilis (Nakai) L.H.Bailey특산식물
129130긴서어나무자작나무과Carpinus laxiflora var. longispica Uyeki특산식물
130131노각나무차나무과Stewartia koreana Nakai ex Rehder특산식물
131132나래완두콩과Vicia hirticalycina Nakai특산식물
132133좀땅비싸리콩과Indigofera koreana Ohwi특산식물
133134오동나무현삼과Paulownia coreana Uyeki특산식물
134135회양목회양목과Buxus koreana (Nakai ex Rehder) T. H. Chung, P. S. toh, D. B. Lee, F. J. Lee.특산식물