Overview

Dataset statistics

Number of variables6
Number of observations246
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.9 KiB
Average record size in memory49.5 B

Variable types

Numeric1
Categorical2
Text3

Dataset

Description농촌지흥청 농사로 홈페이지에서는 곤충표본목록 정보를 제공합니다. 곤충 목에 따른 곤충 종류를 검색할 수 있습니다.
Author농촌진흥청
URLhttps://www.data.go.kr/data/15123579/fileData.do

Alerts

목명 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
목고유번호 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
순번 is highly overall correlated with 목고유번호 and 1 other fieldsHigh correlation
순번 has unique valuesUnique
과한글명 has unique valuesUnique
과영문명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 07:35:49.220487
Analysis finished2023-12-12 07:35:49.764810
Duration0.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct246
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean123.5
Minimum1
Maximum246
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2023-12-12T16:35:49.848026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13.25
Q162.25
median123.5
Q3184.75
95-th percentile233.75
Maximum246
Range245
Interquartile range (IQR)122.5

Descriptive statistics

Standard deviation71.158274
Coefficient of variation (CV)0.57618036
Kurtosis-1.2
Mean123.5
Median Absolute Deviation (MAD)61.5
Skewness0
Sum30381
Variance5063.5
MonotonicityStrictly increasing
2023-12-12T16:35:49.972211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
156 1
 
0.4%
158 1
 
0.4%
159 1
 
0.4%
160 1
 
0.4%
161 1
 
0.4%
162 1
 
0.4%
163 1
 
0.4%
164 1
 
0.4%
165 1
 
0.4%
Other values (236) 236
95.9%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
246 1
0.4%
245 1
0.4%
244 1
0.4%
243 1
0.4%
242 1
0.4%
241 1
0.4%
240 1
0.4%
239 1
0.4%
238 1
0.4%
237 1
0.4%

목고유번호
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
O1
56 
R1
53 
M1
38 
L1
24 
T1
14 
Other values (16)
61 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique6 ?
Unique (%)2.4%

Sample

1st rowV1
2nd rowV1
3rd rowV1
4th rowV1
5th rowV1

Common Values

ValueCountFrequency (%)
O1 56
22.8%
R1 53
21.5%
M1 38
15.4%
L1 24
9.8%
T1 14
 
5.7%
S1 12
 
4.9%
D1 9
 
3.7%
E1 9
 
3.7%
U1 7
 
2.8%
V1 6
 
2.4%
Other values (11) 18
 
7.3%

Length

2023-12-12T16:35:50.104473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
o1 56
22.8%
r1 53
21.5%
m1 38
15.4%
l1 24
9.8%
t1 14
 
5.7%
s1 12
 
4.9%
d1 9
 
3.7%
e1 9
 
3.7%
u1 7
 
2.8%
v1 6
 
2.4%
Other values (11) 18
 
7.3%

목명
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
딱정벌레목
56 
나비목
53 
매미목
38 
노린재목
24 
벌목
14 
Other values (16)
61 

Length

Max length5
Median length4
Mean length3.5650407
Min length2

Unique

Unique6 ?
Unique (%)2.4%

Sample

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

Common Values

ValueCountFrequency (%)
딱정벌레목 56
22.8%
나비목 53
21.5%
매미목 38
15.4%
노린재목 24
9.8%
벌목 14
 
5.7%
파리목 12
 
4.9%
잠자리목 9
 
3.7%
메뚜기목 9
 
3.7%
응애 7
 
2.8%
거미 6
 
2.4%
Other values (11) 18
 
7.3%

Length

2023-12-12T16:35:50.273740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
딱정벌레목 56
22.8%
나비목 53
21.5%
매미목 38
15.4%
노린재목 24
9.8%
벌목 14
 
5.7%
파리목 12
 
4.9%
잠자리목 9
 
3.7%
메뚜기목 9
 
3.7%
응애 7
 
2.8%
거미 6
 
2.4%
Other values (11) 18
 
7.3%

과고유번호
Text

Distinct133
Distinct (%)54.1%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2023-12-12T16:35:50.601382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters492
Distinct characters26
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

Unique71 ?
Unique (%)28.9%

Sample

1st rowDT
2nd rowDX
3rd rowDB
4th rowAQ
5th rowAI
ValueCountFrequency (%)
ah 6
 
2.4%
ab 5
 
2.0%
aa 5
 
2.0%
an 5
 
2.0%
bu 5
 
2.0%
ag 5
 
2.0%
aq 4
 
1.6%
ad 4
 
1.6%
bg 4
 
1.6%
ac 4
 
1.6%
Other values (123) 199
80.9%
2023-12-12T16:35:51.113076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 93
18.9%
B 63
12.8%
C 45
 
9.1%
D 41
 
8.3%
E 33
 
6.7%
G 23
 
4.7%
F 23
 
4.7%
K 15
 
3.0%
I 13
 
2.6%
T 13
 
2.6%
Other values (16) 130
26.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 492
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 93
18.9%
B 63
12.8%
C 45
 
9.1%
D 41
 
8.3%
E 33
 
6.7%
G 23
 
4.7%
F 23
 
4.7%
K 15
 
3.0%
I 13
 
2.6%
T 13
 
2.6%
Other values (16) 130
26.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 492
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 93
18.9%
B 63
12.8%
C 45
 
9.1%
D 41
 
8.3%
E 33
 
6.7%
G 23
 
4.7%
F 23
 
4.7%
K 15
 
3.0%
I 13
 
2.6%
T 13
 
2.6%
Other values (16) 130
26.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 492
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 93
18.9%
B 63
12.8%
C 45
 
9.1%
D 41
 
8.3%
E 33
 
6.7%
G 23
 
4.7%
F 23
 
4.7%
K 15
 
3.0%
I 13
 
2.6%
T 13
 
2.6%
Other values (16) 130
26.4%

과한글명
Text

UNIQUE 

Distinct246
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2023-12-12T16:35:51.478189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length5.203252
Min length3

Characters and Unicode

Total characters1280
Distinct characters236
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique246 ?
Unique (%)100.0%

Sample

1st row갈거미과
2nd row게거미과
3rd row닷거미과
4th row염낭거미과
5th row왕거미과
ValueCountFrequency (%)
갈거미과 1
 
0.4%
매미충과 1
 
0.4%
멸구과 1
 
0.4%
밀깍지벌레과 1
 
0.4%
방패멸구과 1
 
0.4%
뿌리혹벌레과 1
 
0.4%
뿔매미과 1
 
0.4%
상투벌레과 1
 
0.4%
선녀벌레과 1
 
0.4%
알락진딧물과 1
 
0.4%
Other values (236) 236
95.9%
2023-12-12T16:35:52.386950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 246
 
19.2%
벌 64
 
5.0%
나 61
 
4.8%
레 49
 
3.8%
방 49
 
3.8%
리 39
 
3.0%
이 37
 
2.9%
노 21
 
1.6%
재 21
 
1.6%
린 20
 
1.6%
Other values (226) 673
52.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1276
99.7%
Open Punctuation 2
 
0.2%
Close Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 246
 
19.3%
벌 64
 
5.0%
나 61
 
4.8%
레 49
 
3.8%
방 49
 
3.8%
리 39
 
3.1%
이 37
 
2.9%
노 21
 
1.6%
재 21
 
1.6%
린 20
 
1.6%
Other values (224) 669
52.4%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1276
99.7%
Common 4
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 246
 
19.3%
벌 64
 
5.0%
나 61
 
4.8%
레 49
 
3.8%
방 49
 
3.8%
리 39
 
3.1%
이 37
 
2.9%
노 21
 
1.6%
재 21
 
1.6%
린 20
 
1.6%
Other values (224) 669
52.4%
Common
ValueCountFrequency (%)
( 2
50.0%
) 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1276
99.7%
ASCII 4
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 246
 
19.3%
벌 64
 
5.0%
나 61
 
4.8%
레 49
 
3.8%
방 49
 
3.8%
리 39
 
3.1%
이 37
 
2.9%
노 21
 
1.6%
재 21
 
1.6%
린 20
 
1.6%
Other values (224) 669
52.4%
ASCII
ValueCountFrequency (%)
( 2
50.0%
) 2
50.0%

과영문명
Text

UNIQUE 

Distinct246
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2023-12-12T16:35:52.693539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length10.95935
Min length6

Characters and Unicode

Total characters2696
Distinct characters45
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

Unique246 ?
Unique (%)100.0%

Sample

1st rowTetragnathidae
2nd rowThomisidae
3rd rowPisauridae
4th rowClubionidae
5th rowAraneidae
ValueCountFrequency (%)
tetragnathidae 1
 
0.4%
cicadellidae 1
 
0.4%
delphacidae 1
 
0.4%
coccidae 1
 
0.4%
tropiduchidae 1
 
0.4%
phylloxeridae 1
 
0.4%
membracidae 1
 
0.4%
dictyopharidae 1
 
0.4%
flatidae 1
 
0.4%
drepanosiphidae 1
 
0.4%
Other values (236) 236
95.9%
2023-12-12T16:35:53.121088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 388
14.4%
e 379
14.1%
a 358
13.3%
d 292
10.8%
r 135
 
5.0%
o 130
 
4.8%
l 101
 
3.7%
t 96
 
3.6%
h 91
 
3.4%
n 85
 
3.2%
Other values (35) 641
23.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2450
90.9%
Uppercase Letter 246
 
9.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 35
14.2%
A 30
12.2%
P 27
11.0%
T 23
9.3%
L 19
7.7%
S 17
 
6.9%
M 13
 
5.3%
B 13
 
5.3%
D 12
 
4.9%
G 10
 
4.1%
Other values (13) 47
19.1%
Lowercase Letter
ValueCountFrequency (%)
i 388
15.8%
e 379
15.5%
a 358
14.6%
d 292
11.9%
r 135
 
5.5%
o 130
 
5.3%
l 101
 
4.1%
t 96
 
3.9%
h 91
 
3.7%
n 85
 
3.5%
Other values (12) 395
16.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 2696
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 388
14.4%
e 379
14.1%
a 358
13.3%
d 292
10.8%
r 135
 
5.0%
o 130
 
4.8%
l 101
 
3.7%
t 96
 
3.6%
h 91
 
3.4%
n 85
 
3.2%
Other values (35) 641
23.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2696
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 388
14.4%
e 379
14.1%
a 358
13.3%
d 292
10.8%
r 135
 
5.0%
o 130
 
4.8%
l 101
 
3.7%
t 96
 
3.6%
h 91
 
3.4%
n 85
 
3.2%
Other values (35) 641
23.8%

Interactions

2023-12-12T16:35:49.522885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:35:53.229290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번목고유번호목명
순번1.0000.9210.921
목고유번호0.9211.0001.000
목명0.9211.0001.000
2023-12-12T16:35:53.323121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
목명목고유번호
목명1.0001.000
목고유번호1.0001.000
2023-12-12T16:35:53.405821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번목고유번호목명
순번1.0000.6550.655
목고유번호0.6551.0001.000
목명0.6551.0001.000

Missing values

2023-12-12T16:35:49.621953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:35:49.725841image/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

순번목고유번호목명과고유번호과한글명과영문명
01V1거미DT갈거미과Tetragnathidae
12V1거미DX게거미과Thomisidae
23V1거미DB닷거미과Pisauridae
34V1거미AQ염낭거미과Clubionidae
45V1거미AI왕거미과Araneidae
56V1거미BX접시거미과Linyphiidae
67R1나비목CK가는나방과Gracillariidae
78R1나비목BG가는잎말이나방과Cochylidae
89R1나비목BU갈고리나방과Drepanidae
910R1나비목EW감꼭지나방과Stathmopodidae
순번목고유번호목명과고유번호과한글명과영문명
236237S1파리목BB노랑굴파리과Chloropidae
237238S1파리목EN등에과Tabanidae
238239S1파리목BU물가파리과Ephydridae
239240S1파리목BG벌붙이파리과Conopidae
240241S1파리목AM털파리과Bibionidae
241242S1파리목AH파리매과Asilidae
242243S1파리목AW혹파리과Cecidomyiidae
243244N1풀잠자리목AL명주잠자리과Myrmeleontidae
244245N1풀잠자리목AD풀잠자리과Chrysopidae
245246H1흰개미목AD흰개미과Rhinotermitidae