Overview

Dataset statistics

Number of variables11
Number of observations31
Missing cells152
Missing cells (%)44.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.1 KiB
Average record size in memory102.1 B

Variable types

Text1
Numeric9
Categorical1

Dataset

Description전북특별자치도 부안 해역에서 어획된 품종별 현황(개체수 및 현존량) 데이터입니다. 품종 구분, 개체수, 현존량 등을 포함하고 있습니다.
Author전북특별자치도
URLhttps://www.data.go.kr/data/15055704/fileData.do

Alerts

3월-개체수(마리) is highly overall correlated with 3월-현존량 and 4 other fieldsHigh correlation
3월-현존량 is highly overall correlated with 3월-개체수(마리) and 3 other fieldsHigh correlation
5월-개체수(마리) is highly overall correlated with 5월-현존량 and 1 other fieldsHigh correlation
5월-현존량 is highly overall correlated with 3월-개체수(마리) and 2 other fieldsHigh correlation
7월-개체수(마리) is highly overall correlated with 7월-현존량 and 1 other fieldsHigh correlation
7월-현존량 is highly overall correlated with 7월-개체수(마리) and 2 other fieldsHigh correlation
9월-개체수(마리) is highly overall correlated with 3월-개체수(마리) and 5 other fieldsHigh correlation
9월-현존량 is highly overall correlated with 7월-현존량 and 2 other fieldsHigh correlation
11월-현존량 is highly overall correlated with 3월-개체수(마리) and 4 other fieldsHigh correlation
11월-개체수(마리) is highly overall correlated with 3월-개체수(마리) and 4 other fieldsHigh correlation
3월-개체수(마리) has 21 (67.7%) missing valuesMissing
3월-현존량 has 21 (67.7%) missing valuesMissing
5월-개체수(마리) has 16 (51.6%) missing valuesMissing
5월-현존량 has 16 (51.6%) missing valuesMissing
7월-개체수(마리) has 11 (35.5%) missing valuesMissing
7월-현존량 has 11 (35.5%) missing valuesMissing
9월-개체수(마리) has 17 (54.8%) missing valuesMissing
9월-현존량 has 17 (54.8%) missing valuesMissing
11월-현존량 has 22 (71.0%) missing valuesMissing
품종 구분 has unique valuesUnique

Reproduction

Analysis started2024-03-15 01:38:27.494934
Analysis finished2024-03-15 01:38:49.259006
Duration21.76 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

품종 구분
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size376.0 B
2024-03-15T10:38:50.291500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length27
Mean length24.129032
Min length15

Characters and Unicode

Total characters748
Distinct characters101
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)100.0%

Sample

1st row조피볼락(Sebastes schlegelii)
2nd row황해볼락(Sebastes koreanus)
3rd row개볼락(Sebastes pachycephalus)
4th row쑤기미(Inimicus japonicus)
5th row삼세기(Hemitripterus villosus)
ValueCountFrequency (%)
조피볼락(sebastes 1
 
1.6%
웅어(coili 1
 
1.6%
obtusata 1
 
1.6%
보리멸(sillago 1
 
1.6%
sihama 1
 
1.6%
동갈돗돔(hapalogenys 1
 
1.6%
nitens 1
 
1.6%
어름돔(plectorhinchus 1
 
1.6%
cinctus 1
 
1.6%
수조기(nivea 1
 
1.6%
Other values (52) 52
83.9%
2024-03-15T10:38:51.882863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 64
 
8.6%
s 57
 
7.6%
e 47
 
6.3%
i 44
 
5.9%
o 39
 
5.2%
u 38
 
5.1%
n 34
 
4.5%
( 31
 
4.1%
31
 
4.1%
) 31
 
4.1%
Other values (91) 332
44.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 527
70.5%
Other Letter 97
 
13.0%
Open Punctuation 31
 
4.1%
Space Separator 31
 
4.1%
Close Punctuation 31
 
4.1%
Uppercase Letter 31
 
4.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
치 8
 
8.2%
가 5
 
5.2%
미 4
 
4.1%
어 4
 
4.1%
기 3
 
3.1%
락 3
 
3.1%
볼 3
 
3.1%
꽃 2
 
2.1%
대 2
 
2.1%
게 2
 
2.1%
Other values (53) 61
62.9%
Lowercase Letter
ValueCountFrequency (%)
a 64
12.1%
s 57
10.8%
e 47
 
8.9%
i 44
 
8.3%
o 39
 
7.4%
u 38
 
7.2%
n 34
 
6.5%
l 29
 
5.5%
t 28
 
5.3%
r 26
 
4.9%
Other values (14) 121
23.0%
Uppercase Letter
ValueCountFrequency (%)
P 9
29.0%
S 8
25.8%
C 4
12.9%
H 3
 
9.7%
N 1
 
3.2%
T 1
 
3.2%
O 1
 
3.2%
I 1
 
3.2%
K 1
 
3.2%
Z 1
 
3.2%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Space Separator
ValueCountFrequency (%)
31
100.0%
Close Punctuation
ValueCountFrequency (%)
) 31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 558
74.6%
Hangul 97
 
13.0%
Common 93
 
12.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
치 8
 
8.2%
가 5
 
5.2%
미 4
 
4.1%
어 4
 
4.1%
기 3
 
3.1%
락 3
 
3.1%
볼 3
 
3.1%
꽃 2
 
2.1%
대 2
 
2.1%
게 2
 
2.1%
Other values (53) 61
62.9%
Latin
ValueCountFrequency (%)
a 64
11.5%
s 57
 
10.2%
e 47
 
8.4%
i 44
 
7.9%
o 39
 
7.0%
u 38
 
6.8%
n 34
 
6.1%
l 29
 
5.2%
t 28
 
5.0%
r 26
 
4.7%
Other values (25) 152
27.2%
Common
ValueCountFrequency (%)
( 31
33.3%
31
33.3%
) 31
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 651
87.0%
Hangul 97
 
13.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 64
 
9.8%
s 57
 
8.8%
e 47
 
7.2%
i 44
 
6.8%
o 39
 
6.0%
u 38
 
5.8%
n 34
 
5.2%
( 31
 
4.8%
31
 
4.8%
) 31
 
4.8%
Other values (28) 235
36.1%
Hangul
ValueCountFrequency (%)
치 8
 
8.2%
가 5
 
5.2%
미 4
 
4.1%
어 4
 
4.1%
기 3
 
3.1%
락 3
 
3.1%
볼 3
 
3.1%
꽃 2
 
2.1%
대 2
 
2.1%
게 2
 
2.1%
Other values (53) 61
62.9%

3월-개체수(마리)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct6
Distinct (%)60.0%
Missing21
Missing (%)67.7%
Infinite0
Infinite (%)0.0%
Mean9.5
Minimum1
Maximum55
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size407.0 B
2024-03-15T10:38:52.261936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11.25
median3
Q36
95-th percentile38.8
Maximum55
Range54
Interquartile range (IQR)4.75

Descriptive statistics

Standard deviation16.886879
Coefficient of variation (CV)1.7775662
Kurtosis7.2505506
Mean9.5
Median Absolute Deviation (MAD)2
Skewness2.6519852
Sum95
Variance285.16667
MonotonicityNot monotonic
2024-03-15T10:38:52.645833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3 3
 
9.7%
1 3
 
9.7%
2 1
 
3.2%
19 1
 
3.2%
7 1
 
3.2%
55 1
 
3.2%
(Missing) 21
67.7%
ValueCountFrequency (%)
1 3
9.7%
2 1
 
3.2%
3 3
9.7%
7 1
 
3.2%
19 1
 
3.2%
55 1
 
3.2%
ValueCountFrequency (%)
55 1
 
3.2%
19 1
 
3.2%
7 1
 
3.2%
3 3
9.7%
2 1
 
3.2%
1 3
9.7%

3월-현존량
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct8
Distinct (%)80.0%
Missing21
Missing (%)67.7%
Infinite0
Infinite (%)0.0%
Mean2.97
Minimum0.1
Maximum15.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size407.0 B
2024-03-15T10:38:53.110467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile0.145
Q10.2
median0.5
Q31.125
95-th percentile13.175
Maximum15.2
Range15.1
Interquartile range (IQR)0.925

Descriptive statistics

Standard deviation5.3777422
Coefficient of variation (CV)1.8106876
Kurtosis2.5218141
Mean2.97
Median Absolute Deviation (MAD)0.35
Skewness1.9277179
Sum29.7
Variance28.920111
MonotonicityNot monotonic
2024-03-15T10:38:53.329720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0.2 3
 
9.7%
0.7 1
 
3.2%
10.7 1
 
3.2%
0.9 1
 
3.2%
0.3 1
 
3.2%
15.2 1
 
3.2%
0.1 1
 
3.2%
1.2 1
 
3.2%
(Missing) 21
67.7%
ValueCountFrequency (%)
0.1 1
 
3.2%
0.2 3
9.7%
0.3 1
 
3.2%
0.7 1
 
3.2%
0.9 1
 
3.2%
1.2 1
 
3.2%
10.7 1
 
3.2%
15.2 1
 
3.2%
ValueCountFrequency (%)
15.2 1
 
3.2%
10.7 1
 
3.2%
1.2 1
 
3.2%
0.9 1
 
3.2%
0.7 1
 
3.2%
0.3 1
 
3.2%
0.2 3
9.7%
0.1 1
 
3.2%

5월-개체수(마리)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct6
Distinct (%)40.0%
Missing16
Missing (%)51.6%
Infinite0
Infinite (%)0.0%
Mean2.6
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size407.0 B
2024-03-15T10:38:53.585737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q32.5
95-th percentile7.3
Maximum8
Range7
Interquartile range (IQR)1.5

Descriptive statistics

Standard deviation2.3844736
Coefficient of variation (CV)0.91710523
Kurtosis1.0073464
Mean2.6
Median Absolute Deviation (MAD)1
Skewness1.5348619
Sum39
Variance5.6857143
MonotonicityNot monotonic
2024-03-15T10:38:53.903999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 7
22.6%
2 4
 
12.9%
7 1
 
3.2%
3 1
 
3.2%
8 1
 
3.2%
6 1
 
3.2%
(Missing) 16
51.6%
ValueCountFrequency (%)
1 7
22.6%
2 4
12.9%
3 1
 
3.2%
6 1
 
3.2%
7 1
 
3.2%
8 1
 
3.2%
ValueCountFrequency (%)
8 1
 
3.2%
7 1
 
3.2%
6 1
 
3.2%
3 1
 
3.2%
2 4
12.9%
1 7
22.6%

5월-현존량
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct8
Distinct (%)53.3%
Missing16
Missing (%)51.6%
Infinite0
Infinite (%)0.0%
Mean0.61333333
Minimum0.1
Maximum3.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size407.0 B
2024-03-15T10:38:54.112900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile0.1
Q10.2
median0.3
Q30.5
95-th percentile1.97
Maximum3.3
Range3.2
Interquartile range (IQR)0.3

Descriptive statistics

Standard deviation0.83654619
Coefficient of variation (CV)1.363934
Kurtosis8.1037706
Mean0.61333333
Median Absolute Deviation (MAD)0.1
Skewness2.7300732
Sum9.2
Variance0.69980952
MonotonicityNot monotonic
2024-03-15T10:38:54.367983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0.3 4
 
12.9%
0.1 3
 
9.7%
0.4 2
 
6.5%
0.2 2
 
6.5%
0.6 1
 
3.2%
1.2 1
 
3.2%
3.3 1
 
3.2%
1.4 1
 
3.2%
(Missing) 16
51.6%
ValueCountFrequency (%)
0.1 3
9.7%
0.2 2
6.5%
0.3 4
12.9%
0.4 2
6.5%
0.6 1
 
3.2%
1.2 1
 
3.2%
1.4 1
 
3.2%
3.3 1
 
3.2%
ValueCountFrequency (%)
3.3 1
 
3.2%
1.4 1
 
3.2%
1.2 1
 
3.2%
0.6 1
 
3.2%
0.4 2
6.5%
0.3 4
12.9%
0.2 2
6.5%
0.1 3
9.7%

7월-개체수(마리)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct10
Distinct (%)50.0%
Missing11
Missing (%)35.5%
Infinite0
Infinite (%)0.0%
Mean8.75
Minimum1
Maximum57
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size407.0 B
2024-03-15T10:38:54.554708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q35.75
95-th percentile42.75
Maximum57
Range56
Interquartile range (IQR)3.75

Descriptive statistics

Standard deviation15.060842
Coefficient of variation (CV)1.721239
Kurtosis5.8893493
Mean8.75
Median Absolute Deviation (MAD)1
Skewness2.5242664
Sum175
Variance226.82895
MonotonicityNot monotonic
2024-03-15T10:38:54.870121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
2 7
22.6%
1 4
 
12.9%
3 2
 
6.5%
5 1
 
3.2%
12 1
 
3.2%
4 1
 
3.2%
42 1
 
3.2%
57 1
 
3.2%
8 1
 
3.2%
23 1
 
3.2%
(Missing) 11
35.5%
ValueCountFrequency (%)
1 4
12.9%
2 7
22.6%
3 2
 
6.5%
4 1
 
3.2%
5 1
 
3.2%
8 1
 
3.2%
12 1
 
3.2%
23 1
 
3.2%
42 1
 
3.2%
57 1
 
3.2%
ValueCountFrequency (%)
57 1
 
3.2%
42 1
 
3.2%
23 1
 
3.2%
12 1
 
3.2%
8 1
 
3.2%
5 1
 
3.2%
4 1
 
3.2%
3 2
 
6.5%
2 7
22.6%
1 4
12.9%

7월-현존량
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct14
Distinct (%)70.0%
Missing11
Missing (%)35.5%
Infinite0
Infinite (%)0.0%
Mean1.07
Minimum0.1
Maximum4.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size407.0 B
2024-03-15T10:38:55.240614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile0.195
Q10.3
median0.55
Q31.025
95-th percentile3.82
Maximum4.2
Range4.1
Interquartile range (IQR)0.725

Descriptive statistics

Standard deviation1.2431285
Coefficient of variation (CV)1.1618023
Kurtosis2.210547
Mean1.07
Median Absolute Deviation (MAD)0.3
Skewness1.8497379
Sum21.4
Variance1.5453684
MonotonicityNot monotonic
2024-03-15T10:38:55.532678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0.5 3
 
9.7%
0.3 3
 
9.7%
1.0 2
 
6.5%
0.2 2
 
6.5%
1.1 1
 
3.2%
0.6 1
 
3.2%
0.4 1
 
3.2%
0.7 1
 
3.2%
1.4 1
 
3.2%
0.1 1
 
3.2%
Other values (4) 4
 
12.9%
(Missing) 11
35.5%
ValueCountFrequency (%)
0.1 1
 
3.2%
0.2 2
6.5%
0.3 3
9.7%
0.4 1
 
3.2%
0.5 3
9.7%
0.6 1
 
3.2%
0.7 1
 
3.2%
0.8 1
 
3.2%
1.0 2
6.5%
1.1 1
 
3.2%
ValueCountFrequency (%)
4.2 1
 
3.2%
3.8 1
 
3.2%
3.5 1
 
3.2%
1.4 1
 
3.2%
1.1 1
 
3.2%
1.0 2
6.5%
0.8 1
 
3.2%
0.7 1
 
3.2%
0.6 1
 
3.2%
0.5 3
9.7%

9월-개체수(마리)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct8
Distinct (%)57.1%
Missing17
Missing (%)54.8%
Infinite0
Infinite (%)0.0%
Mean6.4285714
Minimum1
Maximum38
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size407.0 B
2024-03-15T10:38:55.813545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q36
95-th percentile19.8
Maximum38
Range37
Interquartile range (IQR)4

Descriptive statistics

Standard deviation9.508816
Coefficient of variation (CV)1.4791492
Kurtosis11.092214
Mean6.4285714
Median Absolute Deviation (MAD)2
Skewness3.2078181
Sum90
Variance90.417582
MonotonicityNot monotonic
2024-03-15T10:38:56.375911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 3
 
9.7%
2 3
 
9.7%
6 2
 
6.5%
5 2
 
6.5%
3 1
 
3.2%
8 1
 
3.2%
38 1
 
3.2%
10 1
 
3.2%
(Missing) 17
54.8%
ValueCountFrequency (%)
1 3
9.7%
2 3
9.7%
3 1
 
3.2%
5 2
6.5%
6 2
6.5%
8 1
 
3.2%
10 1
 
3.2%
38 1
 
3.2%
ValueCountFrequency (%)
38 1
 
3.2%
10 1
 
3.2%
8 1
 
3.2%
6 2
6.5%
5 2
6.5%
3 1
 
3.2%
2 3
9.7%
1 3
9.7%

9월-현존량
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct11
Distinct (%)78.6%
Missing17
Missing (%)54.8%
Infinite0
Infinite (%)0.0%
Mean1.2214286
Minimum0.05
Maximum5.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size407.0 B
2024-03-15T10:38:56.738524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.05
5-th percentile0.05
Q10.3
median1
Q31.275
95-th percentile3.515
Maximum5.4
Range5.35
Interquartile range (IQR)0.975

Descriptive statistics

Standard deviation1.4309376
Coefficient of variation (CV)1.1715279
Kurtosis5.3817859
Mean1.2214286
Median Absolute Deviation (MAD)0.7
Skewness2.1349726
Sum17.1
Variance2.0475824
MonotonicityNot monotonic
2024-03-15T10:38:57.122129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0.3 2
 
6.5%
0.05 2
 
6.5%
1.1 2
 
6.5%
1.2 1
 
3.2%
1.3 1
 
3.2%
2.5 1
 
3.2%
2.3 1
 
3.2%
0.5 1
 
3.2%
5.4 1
 
3.2%
0.9 1
 
3.2%
(Missing) 17
54.8%
ValueCountFrequency (%)
0.05 2
6.5%
0.1 1
3.2%
0.3 2
6.5%
0.5 1
3.2%
0.9 1
3.2%
1.1 2
6.5%
1.2 1
3.2%
1.3 1
3.2%
2.3 1
3.2%
2.5 1
3.2%
ValueCountFrequency (%)
5.4 1
3.2%
2.5 1
3.2%
2.3 1
3.2%
1.3 1
3.2%
1.2 1
3.2%
1.1 2
6.5%
0.9 1
3.2%
0.5 1
3.2%
0.3 2
6.5%
0.1 1
3.2%

11월-개체수(마리)
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)19.4%
Missing0
Missing (%)0.0%
Memory size376.0 B
<NA>
22 
1
4 
5
 
2
8
 
1
4
 
1

Length

Max length4
Median length4
Mean length3.1290323
Min length1

Unique

Unique3 ?
Unique (%)9.7%

Sample

1st row8
2nd row<NA>
3rd row1
4th row<NA>
5th row4

Common Values

ValueCountFrequency (%)
<NA> 22
71.0%
1 4
 
12.9%
5 2
 
6.5%
8 1
 
3.2%
4 1
 
3.2%
9 1
 
3.2%

Length

2024-03-15T10:38:57.537209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T10:38:57.892587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 22
71.0%
1 4
 
12.9%
5 2
 
6.5%
8 1
 
3.2%
4 1
 
3.2%
9 1
 
3.2%

11월-현존량
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct7
Distinct (%)77.8%
Missing22
Missing (%)71.0%
Infinite0
Infinite (%)0.0%
Mean0.94444444
Minimum0.1
Maximum2.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size407.0 B
2024-03-15T10:38:58.116619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile0.1
Q10.2
median0.9
Q31.4
95-th percentile2.06
Maximum2.3
Range2.2
Interquartile range (IQR)1.2

Descriptive statistics

Standard deviation0.7986099
Coefficient of variation (CV)0.84558696
Kurtosis-1.14681
Mean0.94444444
Median Absolute Deviation (MAD)0.7
Skewness0.42058366
Sum8.5
Variance0.63777778
MonotonicityNot monotonic
2024-03-15T10:38:58.297348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0.1 2
 
6.5%
1.4 2
 
6.5%
1.7 1
 
3.2%
2.3 1
 
3.2%
0.4 1
 
3.2%
0.2 1
 
3.2%
0.9 1
 
3.2%
(Missing) 22
71.0%
ValueCountFrequency (%)
0.1 2
6.5%
0.2 1
3.2%
0.4 1
3.2%
0.9 1
3.2%
1.4 2
6.5%
1.7 1
3.2%
2.3 1
3.2%
ValueCountFrequency (%)
2.3 1
3.2%
1.7 1
3.2%
1.4 2
6.5%
0.9 1
3.2%
0.4 1
3.2%
0.2 1
3.2%
0.1 2
6.5%

Interactions

2024-03-15T10:38:46.012551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:28.025369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:29.928136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:32.412512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:34.912631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:37.174583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:39.470724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:41.620328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:43.970015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:46.168612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:28.180524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:30.174343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:32.781273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:35.156012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:37.416089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:39.729763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:41.874273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:44.210583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:46.357368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:28.346440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:30.401462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:33.071644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:35.409770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:37.668292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:39.987979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:42.145284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:44.458685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:46.608161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:28.497873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:30.718867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:33.348964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:35.670009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:37.923297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:40.164020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:42.613892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:44.703631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:46.803020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:28.644553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:30.987460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:33.626673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:35.917025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:38.172029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:40.321752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:42.890672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:44.950102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:47.052960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:28.782548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:31.260531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:33.875798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:36.162876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:38.413092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:40.563980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:43.039973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:45.190417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:47.224820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:28.935159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:31.553672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:34.129381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:36.417451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:38.657034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:40.795017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:43.184472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:45.422471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:47.453973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:29.182299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:31.864383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:34.403922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:36.682714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:38.913016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:41.051178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:43.454858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:45.670907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:47.700541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:29.675457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:32.139209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:34.654887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:36.926935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:39.154576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:41.285350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:43.708973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:38:45.856446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T10:38:58.449902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
품종 구분3월-개체수(마리)3월-현존량5월-개체수(마리)5월-현존량7월-개체수(마리)7월-현존량9월-개체수(마리)9월-현존량11월-개체수(마리)11월-현존량
품종 구분1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
3월-개체수(마리)1.0001.0001.0000.4160.0000.8580.4160.0000.8271.0001.000
3월-현존량1.0001.0001.0001.0000.0000.0001.0000.0001.0001.0001.000
5월-개체수(마리)1.0000.4161.0001.0000.8780.8830.6810.5580.7791.0001.000
5월-현존량1.0000.0000.0000.8781.0000.2470.0000.0000.6621.0001.000
7월-개체수(마리)1.0000.8580.0000.8830.2471.0000.7380.8090.8720.6880.647
7월-현존량1.0000.4161.0000.6810.0000.7381.0000.3300.7300.8950.573
9월-개체수(마리)1.0000.0000.0000.5580.0000.8090.3301.0000.6750.6881.000
9월-현존량1.0000.8271.0000.7790.6620.8720.7300.6751.0000.5730.942
11월-개체수(마리)1.0001.0001.0001.0001.0000.6880.8950.6880.5731.0000.850
11월-현존량1.0001.0001.0001.0001.0000.6470.5731.0000.9420.8501.000
2024-03-15T10:38:58.754368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
3월-개체수(마리)3월-현존량5월-개체수(마리)5월-현존량7월-개체수(마리)7월-현존량9월-개체수(마리)9월-현존량11월-현존량11월-개체수(마리)
3월-개체수(마리)1.0000.736-0.355-0.5630.2350.232-0.738-0.2000.5001.000
3월-현존량0.7361.000-0.4620.090-0.377-0.143-0.9490.2001.0001.000
5월-개체수(마리)-0.355-0.4621.0000.534-0.044-0.0660.476-0.4490.1051.000
5월-현존량-0.5630.0900.5341.000-0.2040.0280.3610.2910.3161.000
7월-개체수(마리)0.235-0.377-0.044-0.2041.0000.6810.5620.019-0.2790.000
7월-현존량0.232-0.143-0.0660.0280.6811.0000.6370.560-0.3970.408
9월-개체수(마리)-0.738-0.9490.4760.3610.5620.6371.0000.674-0.9280.000
9월-현존량-0.2000.200-0.4490.2910.0190.5600.6741.000-0.8120.000
11월-현존량0.5001.0000.1050.316-0.279-0.397-0.928-0.8121.0000.632
11월-개체수(마리)1.0001.0001.0001.0000.0000.4080.0000.0000.6321.000

Missing values

2024-03-15T10:38:48.051062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T10:38:48.614247image/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.
2024-03-15T10:38:48.956650image/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

품종 구분3월-개체수(마리)3월-현존량5월-개체수(마리)5월-현존량7월-개체수(마리)7월-현존량9월-개체수(마리)9월-현존량11월-개체수(마리)11월-현존량
0조피볼락(Sebastes schlegelii)20.720.431.030.381.7
1황해볼락(Sebastes koreanus)30.220.1<NA><NA><NA><NA><NA><NA>
2개볼락(Sebastes pachycephalus)<NA><NA><NA><NA><NA><NA><NA><NA>10.1
3쑤기미(Inimicus japonicus)<NA><NA>10.651.161.2<NA><NA>
4삼세기(Hemitripterus villosus)1910.7<NA><NA><NA><NA><NA><NA>42.3
5노래미(Hexagrammos agrammus)30.971.210.2<NA><NA><NA><NA>
6넙치(Paralichthys olivadeus)<NA><NA><NA><NA>20.551.351.4
7별넙치(Pseudorhombus cinnamoneus)<NA><NA><NA><NA>120.6<NA><NA><NA><NA>
8문치가자미(Pleuronectes yokohamae)10.3<NA><NA>20.3<NA><NA><NA><NA>
9도다리(Pleuronichthys comutus)<NA><NA>10.330.4<NA><NA><NA><NA>
품종 구분3월-개체수(마리)3월-현존량5월-개체수(마리)5월-현존량7월-개체수(마리)7월-현존량9월-개체수(마리)9월-현존량11월-개체수(마리)11월-현존량
21보구치(Pennahia argentata)<NA><NA><NA><NA>20.350.5<NA><NA>
22말쥐치(Thamnaconus modestus)<NA><NA>10.210.2<NA><NA><NA><NA>
23웅어(Coili nasus)10.1<NA><NA><NA><NA><NA><NA><NA><NA>
24날매퉁이(Saurida elongata)<NA><NA><NA><NA>21.0<NA><NA><NA><NA>
25꽃게(Portunus trituberculatus)<NA><NA><NA><NA>424.2385.410.1
26민꽃게(Charybdis japonica)30.230.3573.8100.950.9
27갯가재(Oratosquilla oratoria)551.220.180.520.1<NA><NA>
28대하(Penaeus chinensis)<NA><NA>10.1<NA><NA><NA><NA><NA><NA>
29참갑오징어(Sepia esculenta)<NA><NA>83.310.3<NA><NA><NA><NA>
30피뿔고둥(Rapana venosa)<NA><NA>61.4233.561.191.4