Overview

Dataset statistics

Number of variables15
Number of observations159
Missing cells55
Missing cells (%)2.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory19.4 KiB
Average record size in memory124.8 B

Variable types

Text7
Categorical3
Numeric4
DateTime1

Dataset

Description산청군 약초 정보(약초명, 지역, 효능, 사용부위, 생약명, 학명, 과명, 생육상명, 결실시기, 용도 등 )에 대한 공공데이터 자료입니다.
URLhttps://www.data.go.kr/data/15041774/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
개화시기 시작(월) is highly overall correlated with 개화시기 종료(월) and 2 other fieldsHigh correlation
개화시기 종료(월) is highly overall correlated with 개화시기 시작(월) and 1 other fieldsHigh correlation
결실시기 시작(월) is highly overall correlated with 개화시기 시작(월) and 1 other fieldsHigh correlation
결실시기 종료(월) is highly overall correlated with 개화시기 시작(월) and 2 other fieldsHigh correlation
이명 has 17 (10.7%) missing valuesMissing
개화시기 시작(월) has 6 (3.8%) missing valuesMissing
개화시기 종료(월) has 6 (3.8%) missing valuesMissing
결실시기 시작(월) has 12 (7.5%) missing valuesMissing
결실시기 종료(월) has 12 (7.5%) missing valuesMissing
약초명 has unique valuesUnique
학명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 16:41:16.589173
Analysis finished2023-12-12 16:41:20.005548
Duration3.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

약초명
Text

UNIQUE 

Distinct159
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-13T01:41:20.419715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length3.3081761
Min length1

Characters and Unicode

Total characters526
Distinct characters212
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique159 ?
Unique (%)100.0%

Sample

1st row가새뽕나무
2nd row가시오갈피
3rd row감국(甘菊)
4th row황벽나무
5th row황금
ValueCountFrequency (%)
가새뽕나무 1
 
0.6%
잇꽃 1
 
0.6%
인삼 1
 
0.6%
인동초 1
 
0.6%
도꼬마리 1
 
0.6%
산마늘 1
 
0.6%
도라지 1
 
0.6%
독활 1
 
0.6%
두릅나무 1
 
0.6%
사철쑥(더위지기 1
 
0.6%
Other values (149) 149
93.7%
2023-12-13T01:41:21.032594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
나 25
 
4.8%
무 24
 
4.6%
리 15
 
2.9%
초 13
 
2.5%
오 11
 
2.1%
풀 10
 
1.9%
마 9
 
1.7%
지 9
 
1.7%
이 9
 
1.7%
) 8
 
1.5%
Other values (202) 393
74.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 510
97.0%
Close Punctuation 8
 
1.5%
Open Punctuation 8
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
나 25
 
4.9%
무 24
 
4.7%
리 15
 
2.9%
초 13
 
2.5%
오 11
 
2.2%
풀 10
 
2.0%
마 9
 
1.8%
지 9
 
1.8%
이 9
 
1.8%
고 8
 
1.6%
Other values (200) 377
73.9%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 507
96.4%
Common 16
 
3.0%
Han 3
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
나 25
 
4.9%
무 24
 
4.7%
리 15
 
3.0%
초 13
 
2.6%
오 11
 
2.2%
풀 10
 
2.0%
마 9
 
1.8%
지 9
 
1.8%
이 9
 
1.8%
고 8
 
1.6%
Other values (197) 374
73.8%
Han
ValueCountFrequency (%)
甘 1
33.3%
菊 1
33.3%
葛 1
33.3%
Common
ValueCountFrequency (%)
) 8
50.0%
( 8
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 507
96.4%
ASCII 16
 
3.0%
CJK 3
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
나 25
 
4.9%
무 24
 
4.7%
리 15
 
3.0%
초 13
 
2.6%
오 11
 
2.2%
풀 10
 
2.0%
마 9
 
1.8%
지 9
 
1.8%
이 9
 
1.8%
고 8
 
1.6%
Other values (197) 374
73.8%
ASCII
ValueCountFrequency (%)
) 8
50.0%
( 8
50.0%
CJK
ValueCountFrequency (%)
甘 1
33.3%
菊 1
33.3%
葛 1
33.3%

권역별 구분
Categorical

Distinct22
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
88 
지리산권
15 
집현산권
9 
웅석산권
 
7
황매산권
 
6
Other values (17)
34 

Length

Max length23
Median length4
Mean length5.4779874
Min length3

Unique

Unique8 ?
Unique (%)5.0%

Sample

1st row<NA>
2nd row지리산권
3rd row왕산권
4th row지리산권
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 88
55.3%
지리산권 15
 
9.4%
집현산권 9
 
5.7%
웅석산권 7
 
4.4%
황매산권 6
 
3.8%
왕산권+웅석산권 5
 
3.1%
지리산권+왕산권+집현산권 4
 
2.5%
왕산권 3
 
1.9%
지리산권+집현산권 3
 
1.9%
지리산권+황매산권+왕산권+집현산권+웅석산권 3
 
1.9%
Other values (12) 16
 
10.1%

Length

2023-12-13T01:41:21.222732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 88
55.3%
지리산권 15
 
9.4%
집현산권 9
 
5.7%
웅석산권 7
 
4.4%
황매산권 6
 
3.8%
왕산권+웅석산권 5
 
3.1%
지리산권+왕산권+집현산권 4
 
2.5%
왕산권 3
 
1.9%
지리산권+집현산권 3
 
1.9%
지리산권+황매산권+왕산권+집현산권+웅석산권 3
 
1.9%
Other values (12) 16
 
10.1%

효능별 구분
Text

Distinct115
Distinct (%)72.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-13T01:41:21.458244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length88
Median length39
Mean length16.610063
Min length2

Characters and Unicode

Total characters2641
Distinct characters59
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique97 ?
Unique (%)61.0%

Sample

1st row기침가래
2nd row자양강장
3rd row고혈압+기침가래
4th row위장질환+당뇨병
5th row해열+진통+치통+비뇨+생식기+성병+부종+이뇨+간장질환
ValueCountFrequency (%)
기침가래 10
 
6.3%
비뇨+생식기+성병+부종+이뇨 6
 
3.8%
신경통+관절염 5
 
3.1%
해열+진통+치통+독사+독충 4
 
2.5%
해열+진통+치통 4
 
2.5%
자양강장+보신 4
 
2.5%
정신+신경+불면증 4
 
2.5%
위장질환 3
 
1.9%
부인병 3
 
1.9%
자양강장 3
 
1.9%
Other values (105) 113
71.1%
2023-12-13T01:41:21.886309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
+ 629
23.8%
통 134
 
5.1%
신 105
 
4.0%
뇨 89
 
3.4%
장 83
 
3.1%
병 81
 
3.1%
기 76
 
2.9%
부 68
 
2.6%
경 58
 
2.2%
환 53
 
2.0%
Other values (49) 1265
47.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2012
76.2%
Math Symbol 629
 
23.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
통 134
 
6.7%
신 105
 
5.2%
뇨 89
 
4.4%
장 83
 
4.1%
병 81
 
4.0%
기 76
 
3.8%
부 68
 
3.4%
경 58
 
2.9%
환 53
 
2.6%
질 53
 
2.6%
Other values (48) 1212
60.2%
Math Symbol
ValueCountFrequency (%)
+ 629
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2012
76.2%
Common 629
 
23.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
통 134
 
6.7%
신 105
 
5.2%
뇨 89
 
4.4%
장 83
 
4.1%
병 81
 
4.0%
기 76
 
3.8%
부 68
 
3.4%
경 58
 
2.9%
환 53
 
2.6%
질 53
 
2.6%
Other values (48) 1212
60.2%
Common
ValueCountFrequency (%)
+ 629
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2012
76.2%
ASCII 629
 
23.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
+ 629
100.0%
Hangul
ValueCountFrequency (%)
통 134
 
6.7%
신 105
 
5.2%
뇨 89
 
4.4%
장 83
 
4.1%
병 81
 
4.0%
기 76
 
3.8%
부 68
 
3.4%
경 58
 
2.9%
환 53
 
2.6%
질 53
 
2.6%
Other values (48) 1212
60.2%

사용부위별 구분
Categorical

Distinct20
Distinct (%)12.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
42 
줄기+잎
31 
전초
28 
줄기+잎+과실
16 
과실
10 
Other values (15)
32 

Length

Max length20
Median length13
Mean length4.3081761
Min length2

Unique

Unique7 ?
Unique (%)4.4%

Sample

1st row줄기+잎+과실
2nd row줄기+잎
3rd row꽃류
4th row줄기+잎
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 42
26.4%
줄기+잎 31
19.5%
전초 28
17.6%
줄기+잎+과실 16
 
10.1%
과실 10
 
6.3%
꽃류 5
 
3.1%
줄기+잎+종자 5
 
3.1%
과실+전초 4
 
2.5%
줄기+잎+꽃류 3
 
1.9%
종자+전초 2
 
1.3%
Other values (10) 13
 
8.2%

Length

2023-12-13T01:41:22.039326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 42
26.4%
줄기+잎 31
19.5%
전초 28
17.6%
줄기+잎+과실 16
 
10.1%
과실 10
 
6.3%
꽃류 5
 
3.1%
줄기+잎+종자 5
 
3.1%
과실+전초 4
 
2.5%
줄기+잎+꽃류 3
 
1.9%
꽃류+전초 2
 
1.3%
Other values (10) 13
 
8.2%

생약명
Text

Distinct156
Distinct (%)98.7%
Missing1
Missing (%)0.6%
Memory size1.4 KiB
2023-12-13T01:41:22.357247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length6.5506329
Min length2

Characters and Unicode

Total characters1035
Distinct characters376
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique154 ?
Unique (%)97.5%

Sample

1st row상기(桑起),상근(桑根),상실(桑實)
2nd row자오가근(刺五加根)
3rd row야국(野菊)
4th row황백(黃栢)
5th row황금(黃芩)
ValueCountFrequency (%)
산약(山藥 2
 
1.3%
미후리 2
 
1.3%
지유 1
 
0.6%
산수유(山茱萸 1
 
0.6%
인진고(茵陳蒿 1
 
0.6%
초작약(焦芍藥 1
 
0.6%
상기(桑起),상근(桑根),상실(桑實 1
 
0.6%
총목피(曾木皮 1
 
0.6%
신초(神草),황삼(黃蔘 1
 
0.6%
인동(忍冬 1
 
0.6%
Other values (146) 146
92.4%
2023-12-13T01:41:22.821530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 137
 
13.2%
) 137
 
13.2%
초 23
 
2.2%
자 16
 
1.5%
草 15
 
1.4%
산 10
 
1.0%
, 10
 
1.0%
백 9
 
0.9%
오 9
 
0.9%
子 9
 
0.9%
Other values (366) 660
63.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 751
72.6%
Open Punctuation 137
 
13.2%
Close Punctuation 137
 
13.2%
Other Punctuation 10
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
초 23
 
3.1%
자 16
 
2.1%
草 15
 
2.0%
산 10
 
1.3%
백 9
 
1.2%
오 9
 
1.2%
子 9
 
1.2%
수 9
 
1.2%
山 8
 
1.1%
천 8
 
1.1%
Other values (363) 635
84.6%
Open Punctuation
ValueCountFrequency (%)
( 137
100.0%
Close Punctuation
ValueCountFrequency (%)
) 137
100.0%
Other Punctuation
ValueCountFrequency (%)
, 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 412
39.8%
Han 339
32.8%
Common 284
27.4%

Most frequent character per script

Han
ValueCountFrequency (%)
草 15
 
4.4%
子 9
 
2.7%
山 8
 
2.4%
黃 7
 
2.1%
皮 7
 
2.1%
白 6
 
1.8%
蔘 6
 
1.8%
根 5
 
1.5%
烏 4
 
1.2%
藥 4
 
1.2%
Other values (205) 268
79.1%
Hangul
ValueCountFrequency (%)
초 23
 
5.6%
자 16
 
3.9%
산 10
 
2.4%
백 9
 
2.2%
오 9
 
2.2%
수 9
 
2.2%
천 8
 
1.9%
근 7
 
1.7%
유 7
 
1.7%
삼 7
 
1.7%
Other values (148) 307
74.5%
Common
ValueCountFrequency (%)
( 137
48.2%
) 137
48.2%
, 10
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 412
39.8%
CJK 330
31.9%
ASCII 284
27.4%
CJK Compat Ideographs 9
 
0.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 137
48.2%
) 137
48.2%
, 10
 
3.5%
Hangul
ValueCountFrequency (%)
초 23
 
5.6%
자 16
 
3.9%
산 10
 
2.4%
백 9
 
2.2%
오 9
 
2.2%
수 9
 
2.2%
천 8
 
1.9%
근 7
 
1.7%
유 7
 
1.7%
삼 7
 
1.7%
Other values (148) 307
74.5%
CJK
ValueCountFrequency (%)
草 15
 
4.5%
子 9
 
2.7%
山 8
 
2.4%
黃 7
 
2.1%
皮 7
 
2.1%
白 6
 
1.8%
蔘 6
 
1.8%
根 5
 
1.5%
烏 4
 
1.2%
藥 4
 
1.2%
Other values (196) 259
78.5%
CJK Compat Ideographs
ValueCountFrequency (%)
旅 1
11.1%
龍 1
11.1%
鈴 1
11.1%
連 1
11.1%
雷 1
11.1%
參 1
11.1%
狼 1
11.1%
律 1
11.1%
金 1
11.1%

학명
Text

UNIQUE 

Distinct159
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-13T01:41:23.100529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length40
Mean length27.150943
Min length12

Characters and Unicode

Total characters4317
Distinct characters55
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique159 ?
Unique (%)100.0%

Sample

1st rowMorusbombycisL.for.dissectaNAKAI
2nd rowAcanthopanaxSenticosusHARMS.
3rd rowChrysanthemumindicumL.
4th rowPhellodendronamurense
5th rowScutellariabaicalensisGeorgi
ValueCountFrequency (%)
morusbombycisl.for.dissectanakai 1
 
0.6%
carthamustinctoriusl 1
 
0.6%
panaxginsengc.ameyer 1
 
0.6%
lonicerajaponica 1
 
0.6%
xanthiumstrumariuml 1
 
0.6%
alliumvictorialisl.var.platyphyllummakino 1
 
0.6%
platycodongrandiflorum(jacq.)a.dc 1
 
0.6%
araliacontinentalisthunb 1
 
0.6%
araliaelata(miq.)seem 1
 
0.6%
artemisiacapillaristhunb 1
 
0.6%
Other values (149) 149
93.7%
2023-12-13T01:41:23.548441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 413
 
9.6%
i 352
 
8.2%
s 223
 
5.2%
e 217
 
5.0%
n 215
 
5.0%
. 209
 
4.8%
r 208
 
4.8%
o 194
 
4.5%
u 190
 
4.4%
l 162
 
3.8%
Other values (45) 1934
44.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3091
71.6%
Uppercase Letter 936
 
21.7%
Other Punctuation 209
 
4.8%
Close Punctuation 40
 
0.9%
Open Punctuation 40
 
0.9%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 413
13.4%
i 352
11.4%
s 223
 
7.2%
e 217
 
7.0%
n 215
 
7.0%
r 208
 
6.7%
o 194
 
6.3%
u 190
 
6.1%
l 162
 
5.2%
t 149
 
4.8%
Other values (16) 768
24.8%
Uppercase Letter
ValueCountFrequency (%)
A 121
 
12.9%
L 64
 
6.8%
M 61
 
6.5%
I 60
 
6.4%
N 57
 
6.1%
C 56
 
6.0%
E 54
 
5.8%
R 45
 
4.8%
H 44
 
4.7%
T 41
 
4.4%
Other values (15) 333
35.6%
Other Punctuation
ValueCountFrequency (%)
. 209
100.0%
Close Punctuation
ValueCountFrequency (%)
) 40
100.0%
Open Punctuation
ValueCountFrequency (%)
( 40
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4027
93.3%
Common 290
 
6.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 413
 
10.3%
i 352
 
8.7%
s 223
 
5.5%
e 217
 
5.4%
n 215
 
5.3%
r 208
 
5.2%
o 194
 
4.8%
u 190
 
4.7%
l 162
 
4.0%
t 149
 
3.7%
Other values (41) 1704
42.3%
Common
ValueCountFrequency (%)
. 209
72.1%
) 40
 
13.8%
( 40
 
13.8%
- 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4317
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 413
 
9.6%
i 352
 
8.2%
s 223
 
5.2%
e 217
 
5.0%
n 215
 
5.0%
. 209
 
4.8%
r 208
 
4.8%
o 194
 
4.5%
u 190
 
4.4%
l 162
 
3.8%
Other values (45) 1934
44.8%

이명
Text

MISSING 

Distinct142
Distinct (%)100.0%
Missing17
Missing (%)10.7%
Memory size1.4 KiB
2023-12-13T01:41:23.813722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length21
Mean length9.5211268
Min length2

Characters and Unicode

Total characters1352
Distinct characters426
Distinct categories7 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique142 ?
Unique (%)100.0%

Sample

1st row가새뽕
2nd row자오가(刺五加)
3rd row고의(苦薏)+야산국
4th row벽목(蘗木)+황경나무+황경피나무+단항(檀杭)
5th row속썩은풀
ValueCountFrequency (%)
까치수영 1
 
0.7%
땃두릅 1
 
0.7%
산화칠(山花七)+낙신부(落新婦 1
 
0.7%
애탕쑥 1
 
0.7%
신초+황삼+혈삼 1
 
0.7%
연동고장+연동줄+인동꽃+인동넝쿨+능박나무+겨우살이덩굴 1
 
0.7%
저이(猪耳 1
 
0.7%
산총 1
 
0.7%
민산작약+산함박꽃+적작약 1
 
0.7%
엄나무 1
 
0.7%
Other values (132) 132
93.0%
2023-12-13T01:41:24.326016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
+ 159
 
11.8%
( 64
 
4.7%
) 64
 
4.7%
나 33
 
2.4%
무 32
 
2.4%
초 27
 
2.0%
산 20
 
1.5%
자 17
 
1.3%
지 13
 
1.0%
수 13
 
1.0%
Other values (416) 910
67.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1045
77.3%
Math Symbol 159
 
11.8%
Open Punctuation 64
 
4.7%
Close Punctuation 64
 
4.7%
Lowercase Letter 18
 
1.3%
Other Punctuation 1
 
0.1%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
나 33
 
3.2%
무 32
 
3.1%
초 27
 
2.6%
산 20
 
1.9%
자 17
 
1.6%
지 13
 
1.2%
수 13
 
1.2%
화 13
 
1.2%
삼 13
 
1.2%
기 12
 
1.1%
Other values (399) 852
81.5%
Lowercase Letter
ValueCountFrequency (%)
r 3
16.7%
w 2
11.1%
i 2
11.1%
e 2
11.1%
h 2
11.1%
u 1
 
5.6%
t 1
 
5.6%
f 1
 
5.6%
m 1
 
5.6%
o 1
 
5.6%
Other values (2) 2
11.1%
Math Symbol
ValueCountFrequency (%)
+ 159
100.0%
Open Punctuation
ValueCountFrequency (%)
( 64
100.0%
Close Punctuation
ValueCountFrequency (%)
) 64
100.0%
Other Punctuation
ValueCountFrequency (%)
· 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
P 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 888
65.7%
Common 288
 
21.3%
Han 157
 
11.6%
Latin 19
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
나 33
 
3.7%
무 32
 
3.6%
초 27
 
3.0%
산 20
 
2.3%
자 17
 
1.9%
지 13
 
1.5%
수 13
 
1.5%
화 13
 
1.5%
삼 13
 
1.5%
기 12
 
1.4%
Other values (283) 695
78.3%
Han
ValueCountFrequency (%)
蔘 5
 
3.2%
草 5
 
3.2%
花 5
 
3.2%
蓮 3
 
1.9%
子 3
 
1.9%
萎 3
 
1.9%
黃 3
 
1.9%
香 3
 
1.9%
母 2
 
1.3%
土 2
 
1.3%
Other values (106) 123
78.3%
Latin
ValueCountFrequency (%)
r 3
15.8%
w 2
10.5%
i 2
10.5%
e 2
10.5%
h 2
10.5%
u 1
 
5.3%
t 1
 
5.3%
f 1
 
5.3%
m 1
 
5.3%
o 1
 
5.3%
Other values (3) 3
15.8%
Common
ValueCountFrequency (%)
+ 159
55.2%
( 64
22.2%
) 64
22.2%
· 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 888
65.7%
ASCII 306
 
22.6%
CJK 154
 
11.4%
CJK Compat Ideographs 3
 
0.2%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
+ 159
52.0%
( 64
20.9%
) 64
20.9%
r 3
 
1.0%
w 2
 
0.7%
i 2
 
0.7%
e 2
 
0.7%
h 2
 
0.7%
u 1
 
0.3%
t 1
 
0.3%
Other values (6) 6
 
2.0%
Hangul
ValueCountFrequency (%)
나 33
 
3.7%
무 32
 
3.6%
초 27
 
3.0%
산 20
 
2.3%
자 17
 
1.9%
지 13
 
1.5%
수 13
 
1.5%
화 13
 
1.5%
삼 13
 
1.5%
기 12
 
1.4%
Other values (283) 695
78.3%
CJK
ValueCountFrequency (%)
蔘 5
 
3.2%
草 5
 
3.2%
花 5
 
3.2%
蓮 3
 
1.9%
子 3
 
1.9%
萎 3
 
1.9%
黃 3
 
1.9%
香 3
 
1.9%
母 2
 
1.3%
土 2
 
1.3%
Other values (103) 120
77.9%
None
ValueCountFrequency (%)
· 1
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
女 1
33.3%
利 1
33.3%
落 1
33.3%

과명
Text

Distinct75
Distinct (%)47.5%
Missing1
Missing (%)0.6%
Memory size1.4 KiB
2023-12-13T01:41:24.613257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length8
Mean length3.8291139
Min length2

Characters and Unicode

Total characters605
Distinct characters133
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)29.7%

Sample

1st row뽕나무과
2nd row오갈피과
3rd row국화과
4th row운향과
5th row꿀풀과
ValueCountFrequency (%)
국화과 14
 
8.9%
백합과 12
 
7.6%
꿀풀과 10
 
6.3%
장미과 6
 
3.8%
초롱꽃과 5
 
3.2%
미나리과 5
 
3.2%
마디풀과 5
 
3.2%
미나리아재비과 5
 
3.2%
콩과 4
 
2.5%
가지과 4
 
2.5%
Other values (65) 88
55.7%
2023-12-13T01:41:25.075826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 159
26.3%
나 38
 
6.3%
무 24
 
4.0%
리 19
 
3.1%
미 18
 
3.0%
풀 16
 
2.6%
화 15
 
2.5%
국 14
 
2.3%
백 13
 
2.1%
합 12
 
2.0%
Other values (123) 277
45.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 591
97.7%
Lowercase Letter 11
 
1.8%
Uppercase Letter 1
 
0.2%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 159
26.9%
나 38
 
6.4%
무 24
 
4.1%
리 19
 
3.2%
미 18
 
3.0%
풀 16
 
2.7%
화 15
 
2.5%
국 14
 
2.4%
백 13
 
2.2%
합 12
 
2.0%
Other values (112) 263
44.5%
Lowercase Letter
ValueCountFrequency (%)
e 3
27.3%
l 2
18.2%
m 1
 
9.1%
n 1
 
9.1%
a 1
 
9.1%
r 1
 
9.1%
f 1
 
9.1%
i 1
 
9.1%
Uppercase Letter
ValueCountFrequency (%)
U 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 591
97.7%
Latin 12
 
2.0%
Common 2
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 159
26.9%
나 38
 
6.4%
무 24
 
4.1%
리 19
 
3.2%
미 18
 
3.0%
풀 16
 
2.7%
화 15
 
2.5%
국 14
 
2.4%
백 13
 
2.2%
합 12
 
2.0%
Other values (112) 263
44.5%
Latin
ValueCountFrequency (%)
e 3
25.0%
l 2
16.7%
U 1
 
8.3%
m 1
 
8.3%
n 1
 
8.3%
a 1
 
8.3%
r 1
 
8.3%
f 1
 
8.3%
i 1
 
8.3%
Common
ValueCountFrequency (%)
( 1
50.0%
) 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 591
97.7%
ASCII 14
 
2.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 159
26.9%
나 38
 
6.4%
무 24
 
4.1%
리 19
 
3.2%
미 18
 
3.0%
풀 16
 
2.7%
화 15
 
2.5%
국 14
 
2.4%
백 13
 
2.2%
합 12
 
2.0%
Other values (112) 263
44.5%
ASCII
ValueCountFrequency (%)
e 3
21.4%
l 2
14.3%
U 1
 
7.1%
( 1
 
7.1%
m 1
 
7.1%
n 1
 
7.1%
) 1
 
7.1%
a 1
 
7.1%
r 1
 
7.1%
f 1
 
7.1%

생육상명
Categorical

Distinct38
Distinct (%)23.9%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
다년생초본
70 
목본식물
22 
여러해살이풀
14 
한해살이풀
 
4
다년생덩굴초본
 
4
Other values (33)
45 

Length

Max length10
Median length5
Mean length5.2578616
Min length4

Unique

Unique25 ?
Unique (%)15.7%

Sample

1st row목본식물
2nd row목본식물
3rd row다년생초본
4th row낙엽교목
5th row여러해살이풀

Common Values

ValueCountFrequency (%)
다년생초본 70
44.0%
목본식물 22
 
13.8%
여러해살이풀 14
 
8.8%
한해살이풀 4
 
2.5%
다년생덩굴초본 4
 
2.5%
낙엽교목 3
 
1.9%
여러해살이덩굴풀 3
 
1.9%
<NA> 3
 
1.9%
두해살이풀 3
 
1.9%
상록목본식물 2
 
1.3%
Other values (28) 31
19.5%

Length

2023-12-13T01:41:25.245981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
다년생초본 70
44.0%
목본식물 22
 
13.8%
여러해살이풀 14
 
8.8%
한해살이풀 4
 
2.5%
다년생덩굴초본 4
 
2.5%
낙엽교목 3
 
1.9%
여러해살이덩굴풀 3
 
1.9%
na 3
 
1.9%
두해살이풀 3
 
1.9%
다년생상록초본 2
 
1.3%
Other values (28) 31
19.5%

개화시기 시작(월)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct9
Distinct (%)5.9%
Missing6
Missing (%)3.8%
Infinite0
Infinite (%)0.0%
Mean6.1568627
Minimum2
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-13T01:41:25.353691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile4
Q15
median6
Q37
95-th percentile8
Maximum10
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.5136121
Coefficient of variation (CV)0.24584146
Kurtosis-0.24198039
Mean6.1568627
Median Absolute Deviation (MAD)1
Skewness-0.039342281
Sum942
Variance2.2910217
MonotonicityNot monotonic
2023-12-13T01:41:25.487177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
6 38
23.9%
7 34
21.4%
5 29
18.2%
8 23
14.5%
4 17
10.7%
9 5
 
3.1%
3 4
 
2.5%
10 2
 
1.3%
2 1
 
0.6%
(Missing) 6
 
3.8%
ValueCountFrequency (%)
2 1
 
0.6%
3 4
 
2.5%
4 17
10.7%
5 29
18.2%
6 38
23.9%
7 34
21.4%
8 23
14.5%
9 5
 
3.1%
10 2
 
1.3%
ValueCountFrequency (%)
10 2
 
1.3%
9 5
 
3.1%
8 23
14.5%
7 34
21.4%
6 38
23.9%
5 29
18.2%
4 17
10.7%
3 4
 
2.5%
2 1
 
0.6%

개화시기 종료(월)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct8
Distinct (%)5.2%
Missing6
Missing (%)3.8%
Infinite0
Infinite (%)0.0%
Mean7.2745098
Minimum3
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-13T01:41:25.640631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile4.6
Q16
median7
Q39
95-th percentile10
Maximum10
Range7
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.6512965
Coefficient of variation (CV)0.22699763
Kurtosis-0.73561537
Mean7.2745098
Median Absolute Deviation (MAD)1
Skewness-0.35011861
Sum1113
Variance2.7267802
MonotonicityNot monotonic
2023-12-13T01:41:26.091866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
8 34
21.4%
9 33
20.8%
7 29
18.2%
6 20
12.6%
5 20
12.6%
10 9
 
5.7%
4 7
 
4.4%
3 1
 
0.6%
(Missing) 6
 
3.8%
ValueCountFrequency (%)
3 1
 
0.6%
4 7
 
4.4%
5 20
12.6%
6 20
12.6%
7 29
18.2%
8 34
21.4%
9 33
20.8%
10 9
 
5.7%
ValueCountFrequency (%)
10 9
 
5.7%
9 33
20.8%
8 34
21.4%
7 29
18.2%
6 20
12.6%
5 20
12.6%
4 7
 
4.4%
3 1
 
0.6%

결실시기 시작(월)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct7
Distinct (%)4.8%
Missing12
Missing (%)7.5%
Infinite0
Infinite (%)0.0%
Mean8.9659864
Minimum5
Maximum11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-13T01:41:26.188527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile6
Q19
median9
Q310
95-th percentile10
Maximum11
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.2789924
Coefficient of variation (CV)0.14264938
Kurtosis0.75405503
Mean8.9659864
Median Absolute Deviation (MAD)1
Skewness-1.0309257
Sum1318
Variance1.6358215
MonotonicityNot monotonic
2023-12-13T01:41:26.279935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
9 57
35.8%
10 49
30.8%
7 14
 
8.8%
8 11
 
6.9%
11 7
 
4.4%
6 7
 
4.4%
5 2
 
1.3%
(Missing) 12
 
7.5%
ValueCountFrequency (%)
5 2
 
1.3%
6 7
 
4.4%
7 14
 
8.8%
8 11
 
6.9%
9 57
35.8%
10 49
30.8%
11 7
 
4.4%
ValueCountFrequency (%)
11 7
 
4.4%
10 49
30.8%
9 57
35.8%
8 11
 
6.9%
7 14
 
8.8%
6 7
 
4.4%
5 2
 
1.3%

결실시기 종료(월)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct7
Distinct (%)4.8%
Missing12
Missing (%)7.5%
Infinite0
Infinite (%)0.0%
Mean9.5170068
Minimum6
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-13T01:41:26.374621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile7
Q19
median10
Q310
95-th percentile11
Maximum12
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.2183176
Coefficient of variation (CV)0.12801479
Kurtosis1.3645478
Mean9.5170068
Median Absolute Deviation (MAD)0
Skewness-1.1228975
Sum1399
Variance1.4842978
MonotonicityNot monotonic
2023-12-13T01:41:26.477703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
10 74
46.5%
9 27
 
17.0%
11 19
 
11.9%
8 14
 
8.8%
6 6
 
3.8%
7 5
 
3.1%
12 2
 
1.3%
(Missing) 12
 
7.5%
ValueCountFrequency (%)
6 6
 
3.8%
7 5
 
3.1%
8 14
 
8.8%
9 27
 
17.0%
10 74
46.5%
11 19
 
11.9%
12 2
 
1.3%
ValueCountFrequency (%)
12 2
 
1.3%
11 19
 
11.9%
10 74
46.5%
9 27
 
17.0%
8 14
 
8.8%
7 5
 
3.1%
6 6
 
3.8%

용도
Text

Distinct60
Distinct (%)37.7%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-13T01:41:26.663608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length17
Mean length6.7358491
Min length2

Characters and Unicode

Total characters1071
Distinct characters67
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)27.7%

Sample

1st row식용+약용
2nd row식용+약용
3rd row약용+식용(어린순)+관상용
4th row목재+조경+염료+약재
5th row약용+식용+공업용+밀원용
ValueCountFrequency (%)
약용 29
18.2%
식용+약용 23
14.5%
관상용+약용 10
 
6.3%
약용+식용 10
 
6.3%
식용+약용+관상용 8
 
5.0%
식용+관상용+약용 7
 
4.4%
약용+관상용 6
 
3.8%
식용 5
 
3.1%
관상용+식용+약용 4
 
2.5%
약용+식용+관상용 3
 
1.9%
Other values (48) 54
34.0%
2023-12-13T01:41:26.987830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
용 313
29.2%
+ 203
19.0%
약 148
13.8%
식 97
 
9.1%
관 64
 
6.0%
상 63
 
5.9%
재 15
 
1.4%
( 12
 
1.1%
) 12
 
1.1%
료 12
 
1.1%
Other values (57) 132
12.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 844
78.8%
Math Symbol 203
 
19.0%
Open Punctuation 12
 
1.1%
Close Punctuation 12
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
용 313
37.1%
약 148
17.5%
식 97
 
11.5%
관 64
 
7.6%
상 63
 
7.5%
재 15
 
1.8%
료 12
 
1.4%
원 12
 
1.4%
밀 9
 
1.1%
수 8
 
0.9%
Other values (54) 103
 
12.2%
Math Symbol
ValueCountFrequency (%)
+ 203
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 844
78.8%
Common 227
 
21.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
용 313
37.1%
약 148
17.5%
식 97
 
11.5%
관 64
 
7.6%
상 63
 
7.5%
재 15
 
1.8%
료 12
 
1.4%
원 12
 
1.4%
밀 9
 
1.1%
수 8
 
0.9%
Other values (54) 103
 
12.2%
Common
ValueCountFrequency (%)
+ 203
89.4%
( 12
 
5.3%
) 12
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 844
78.8%
ASCII 227
 
21.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
용 313
37.1%
약 148
17.5%
식 97
 
11.5%
관 64
 
7.6%
상 63
 
7.5%
재 15
 
1.8%
료 12
 
1.4%
원 12
 
1.4%
밀 9
 
1.1%
수 8
 
0.9%
Other values (54) 103
 
12.2%
ASCII
ValueCountFrequency (%)
+ 203
89.4%
( 12
 
5.3%
) 12
 
5.3%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Minimum2023-07-17 00:00:00
Maximum2023-07-17 00:00:00
2023-12-13T01:41:27.106565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:41:27.194891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T01:41:18.943176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:41:17.699189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:41:18.166915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:41:18.591730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:41:19.040053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:41:17.859586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:41:18.248573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:41:18.680039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:41:19.162935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:41:17.976924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:41:18.373159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:41:18.764707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:41:19.253825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:41:18.064749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:41:18.480862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:41:18.851609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:41:27.270346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
권역별 구분사용부위별 구분과명생육상명개화시기 시작(월)개화시기 종료(월)결실시기 시작(월)결실시기 종료(월)용도
권역별 구분1.0000.5230.7900.4710.0000.0000.0000.0000.627
사용부위별 구분0.5231.0000.8140.6820.6770.6850.0000.0000.000
과명0.7900.8141.0000.8490.8310.8680.0000.0000.657
생육상명0.4710.6820.8491.0000.0000.0000.0000.0000.807
개화시기 시작(월)0.0000.6770.8310.0001.0000.8860.4990.5350.394
개화시기 종료(월)0.0000.6850.8680.0000.8861.0000.4980.5370.000
결실시기 시작(월)0.0000.0000.0000.0000.4990.4981.0000.9020.550
결실시기 종료(월)0.0000.0000.0000.0000.5350.5370.9021.0000.000
용도0.6270.0000.6570.8070.3940.0000.5500.0001.000
2023-12-13T01:41:27.391119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사용부위별 구분생육상명권역별 구분
사용부위별 구분1.0000.2200.189
생육상명0.2201.0000.123
권역별 구분0.1890.1231.000
2023-12-13T01:41:27.472651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
개화시기 시작(월)개화시기 종료(월)결실시기 시작(월)결실시기 종료(월)권역별 구분사용부위별 구분생육상명
개화시기 시작(월)1.0000.8940.5280.5230.0000.3230.000
개화시기 종료(월)0.8941.0000.4970.5320.0000.3490.000
결실시기 시작(월)0.5280.4971.0000.7770.0000.0000.000
결실시기 종료(월)0.5230.5320.7771.0000.0000.0000.000
권역별 구분0.0000.0000.0000.0001.0000.1890.123
사용부위별 구분0.3230.3490.0000.0000.1891.0000.220
생육상명0.0000.0000.0000.0000.1230.2201.000

Missing values

2023-12-13T01:41:19.423343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:41:19.673725image/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.
2023-12-13T01:41:19.882251image/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

약초명권역별 구분효능별 구분사용부위별 구분생약명학명이명과명생육상명개화시기 시작(월)개화시기 종료(월)결실시기 시작(월)결실시기 종료(월)용도데이터기준일자
0가새뽕나무<NA>기침가래줄기+잎+과실상기(桑起),상근(桑根),상실(桑實)MorusbombycisL.for.dissectaNAKAI가새뽕뽕나무과목본식물6678식용+약용2023-07-17
1가시오갈피지리산권자양강장줄기+잎자오가근(刺五加根)AcanthopanaxSenticosusHARMS.자오가(刺五加)오갈피과목본식물671010식용+약용2023-07-17
2감국(甘菊)왕산권고혈압+기침가래꽃류야국(野菊)ChrysanthemumindicumL.고의(苦薏)+야산국국화과다년생초본9101111약용+식용(어린순)+관상용2023-07-17
3황벽나무지리산권위장질환+당뇨병줄기+잎황백(黃栢)Phellodendronamurense벽목(蘗木)+황경나무+황경피나무+단항(檀杭)운향과낙엽교목66710목재+조경+염료+약재2023-07-17
4황금<NA>해열+진통+치통+비뇨+생식기+성병+부종+이뇨+간장질환<NA>황금(黃芩)ScutellariabaicalensisGeorgi속썩은풀꿀풀과여러해살이풀7899약용+식용+공업용+밀원용2023-07-17
5환삼덩굴<NA>비뇨+생식기+성병+부종+이뇨과실+전초율초(律草)HumulusjaponicusSieboldetZuccarini좀환삼덩굴+범상덩굴삼과한해살이풀79910식용+약재+섬유2023-07-17
6화살나무지리산권항암제+당뇨병+부인병+정신+신경+불면증줄기+잎+과실귀전우(鬼箭羽)EuonymusalatusSieb홑잎나무+참빗나무노박덩굴과낙엽교목551010관상+약용2023-07-17
7호장근<NA>신경통+관절염+비뇨+생식기+성병+부종+이뇨<NA>호장근(虎杖根)ReynoutriajaponicaHoutt.까치수영여뀌과여러해살이풀681010약용+식용2023-07-17
8호두나무<NA>기침가래+비뇨+생식기+성병종자호두(胡桃)JuglanssinensisDode호핵(胡核)+핵도인(核桃仁)가래나무과낙엽교목4599식용+약재+목재2023-07-17
9형개<NA>중풍+정신+신경+불면증전초형개(荊芥)Schizonepetatenuifolia(Benth.)Briq.가소+은치채꿀풀과한해살이초본89910약용2023-07-17
약초명권역별 구분효능별 구분사용부위별 구분생약명학명이명과명생육상명개화시기 시작(월)개화시기 종료(월)결실시기 시작(월)결실시기 종료(월)용도데이터기준일자
149수리취지리산권+황매산권+왕산권+집현산권+웅석산권해열+진통+치통+신경통+관절염+비뇨+생식기+성병+정신+신경+불면증+부종+이뇨전초산우방(山牛蒡)SynuruspalmatopinnatifidusKITAMURA.var.indivisusKITAMURA.개취+떡취국화과다년생초본910911식용+약용2023-07-17
150승마(끼멸가리)지리산권+집현산권해열+진통+치통+독사+독충<NA>승마(升麻)CimicifugaheracleifoliaKOM.끼멸가리미나리과아재비과다년생초본891010약용2023-07-17
151신선초<NA>고혈압+간장질환전초신선초Angelicakeiskei명일엽(明日葉)·신립초산형과여러해살이풀6879식용2023-07-17
152쑥황매산권해열+진통+치통+위장질환+고혈압+비뇨+생식기+성병+지혈제+기생충+구제+부인병+정신+신경+불면증+부종+이뇨+간장질환줄기+잎+종자애(艾)Artemisiaprincepsvar.orientalis(PAMPAN.)HARA.<NA>국화과다년생초본791011약용+식용2023-07-17
153애기똥풀<NA>해열+진통+치통+위장질환+항암제+간장질환전초백굴채(白屈菜)ChelidoniummajusL.씨아똥+까치다리+젖풀+아기똥풀양귀비과다년생초본5879약용2023-07-17
154약모밀<NA>기침가래전초어성초(漁腥草)HouttuyniacordataTHUNB.집약초+즙채+십자풀삼백초과다년생초본6789약용(땅속줄기+잎)+식용2023-07-17
155억새<NA>기침가래줄기+잎망경(芒莖)Miscanthussinensisvar.purpurascensRENDLE.<NA>벼과다년생초본<NA><NA><NA><NA>관상용+식용+약용2023-07-17
156엉겅퀴집현산권지혈제+부종+이뇨전초대계Cirsiumjaponicumvar.ussuriense(REGEL)KITAMURA.향가새+가시나물국화과다년생초본10899식용(과실주+양주+탄산음료)+약용2023-07-17
157여뀌<NA>비뇨+생식기+성병+부종+이뇨줄기+잎+과실수료PolygonumhydropiperL.버들어뀌마디풀과일년새초본691010식용+약용+밀원용2023-07-17
158여로왕산권+웅석산권해열+진통+치통+고혈압+중풍+기생충+구제<NA>여로(旅路)veratrumkaackiivar.japonicumT.SHMIZU<NA>백합과다년생초본781010관상용+약용2023-07-17