Overview

Dataset statistics

Number of variables11
Number of observations23
Missing cells66
Missing cells (%)26.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.3 KiB
Average record size in memory103.6 B

Variable types

Text1
Categorical4
Numeric6

Dataset

Description전북특별자치도 군산 해역에서 어획된 품종별 현황(개체수 및 현존량/1입방미터당) 데이터입니다. 품종, 개체수, 현존량 등의 정보를 포함하고 있습니다.
Author전북특별자치도
URLhttps://www.data.go.kr/data/15055703/fileData.do

Alerts

5월-개체수(마리) is highly overall correlated with 5월-현존량 and 2 other fieldsHigh correlation
11월-현존량 is highly overall correlated with 5월-현존량 and 7 other fieldsHigh correlation
3월-개체수(마리) is highly overall correlated with 9월-개체수(마리) and 3 other fieldsHigh correlation
11월-개체수(마리) is highly overall correlated with 5월-현존량 and 7 other fieldsHigh correlation
3월-현존량 is highly overall correlated with 5월-현존량 and 3 other fieldsHigh correlation
5월-현존량 is highly overall correlated with 3월-현존량 and 4 other fieldsHigh correlation
7월-개체수(마리) is highly overall correlated with 7월-현존량 and 4 other fieldsHigh correlation
7월-현존량 is highly overall correlated with 3월-현존량 and 5 other fieldsHigh correlation
9월-개체수(마리) is highly overall correlated with 3월-현존량 and 6 other fieldsHigh correlation
9월-현존량 is highly overall correlated with 3월-현존량 and 7 other fieldsHigh correlation
3월-현존량 has 12 (52.2%) missing valuesMissing
5월-현존량 has 10 (43.5%) missing valuesMissing
7월-개체수(마리) has 10 (43.5%) missing valuesMissing
7월-현존량 has 10 (43.5%) missing valuesMissing
9월-개체수(마리) has 12 (52.2%) missing valuesMissing
9월-현존량 has 12 (52.2%) missing valuesMissing
어획 품종 has unique valuesUnique

Reproduction

Analysis started2024-03-14 19:14:00.893480
Analysis finished2024-03-14 19:14:11.788643
Duration10.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

어획 품종
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size312.0 B
2024-03-15T04:14:12.638391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length27
Mean length24.173913
Min length19

Characters and Unicode

Total characters556
Distinct characters87
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

Unique23 ?
Unique (%)100.0%

Sample

1st row조피볼락(Sebastes schlegelii)
2nd row황해볼락(Sebastes koreanus)
3rd row쑤기미(Inimicus japonicus)
4th row삼세기(Hemitripterus villosus)
5th row노래미(Hexagrammos agrammus)
ValueCountFrequency (%)
japonicus 2
 
4.3%
조피볼락(sebastes 1
 
2.2%
trituberculatus 1
 
2.2%
gillii 1
 
2.2%
보구치(pennahia 1
 
2.2%
argentata 1
 
2.2%
붕장어(conger 1
 
2.2%
myriaster 1
 
2.2%
멸치(engraulis 1
 
2.2%
노랑가오리(dasyatis 1
 
2.2%
Other values (35) 35
76.1%
2024-03-15T04:14:14.302164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 48
 
8.6%
s 42
 
7.6%
e 35
 
6.3%
i 34
 
6.1%
u 28
 
5.0%
o 27
 
4.9%
t 24
 
4.3%
( 23
 
4.1%
r 23
 
4.1%
) 23
 
4.1%
Other values (77) 249
44.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 389
70.0%
Other Letter 75
 
13.5%
Open Punctuation 23
 
4.1%
Close Punctuation 23
 
4.1%
Space Separator 23
 
4.1%
Uppercase Letter 23
 
4.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
가 6
 
8.0%
치 5
 
6.7%
미 5
 
6.7%
어 3
 
4.0%
리 2
 
2.7%
게 2
 
2.7%
자 2
 
2.7%
기 2
 
2.7%
피 2
 
2.7%
꽃 2
 
2.7%
Other values (40) 44
58.7%
Lowercase Letter
ValueCountFrequency (%)
a 48
12.3%
s 42
10.8%
e 35
9.0%
i 34
 
8.7%
u 28
 
7.2%
o 27
 
6.9%
t 24
 
6.2%
r 23
 
5.9%
l 23
 
5.9%
n 19
 
4.9%
Other values (13) 86
22.1%
Uppercase Letter
ValueCountFrequency (%)
P 6
26.1%
C 4
17.4%
S 3
13.0%
O 2
 
8.7%
H 2
 
8.7%
D 1
 
4.3%
E 1
 
4.3%
Z 1
 
4.3%
I 1
 
4.3%
K 1
 
4.3%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Space Separator
ValueCountFrequency (%)
23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 412
74.1%
Hangul 75
 
13.5%
Common 69
 
12.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
가 6
 
8.0%
치 5
 
6.7%
미 5
 
6.7%
어 3
 
4.0%
리 2
 
2.7%
게 2
 
2.7%
자 2
 
2.7%
기 2
 
2.7%
피 2
 
2.7%
꽃 2
 
2.7%
Other values (40) 44
58.7%
Latin
ValueCountFrequency (%)
a 48
11.7%
s 42
 
10.2%
e 35
 
8.5%
i 34
 
8.3%
u 28
 
6.8%
o 27
 
6.6%
t 24
 
5.8%
r 23
 
5.6%
l 23
 
5.6%
n 19
 
4.6%
Other values (24) 109
26.5%
Common
ValueCountFrequency (%)
( 23
33.3%
) 23
33.3%
23
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 481
86.5%
Hangul 75
 
13.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 48
 
10.0%
s 42
 
8.7%
e 35
 
7.3%
i 34
 
7.1%
u 28
 
5.8%
o 27
 
5.6%
t 24
 
5.0%
( 23
 
4.8%
r 23
 
4.8%
) 23
 
4.8%
Other values (27) 174
36.2%
Hangul
ValueCountFrequency (%)
가 6
 
8.0%
치 5
 
6.7%
미 5
 
6.7%
어 3
 
4.0%
리 2
 
2.7%
게 2
 
2.7%
자 2
 
2.7%
기 2
 
2.7%
피 2
 
2.7%
꽃 2
 
2.7%
Other values (40) 44
58.7%

3월-개체수(마리)
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)21.7%
Missing0
Missing (%)0.0%
Memory size312.0 B
<NA>
12 
1
7 
5
2 
4
 
1
3
 
1

Length

Max length4
Median length4
Mean length2.5652174
Min length1

Unique

Unique2 ?
Unique (%)8.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 12
52.2%
1 7
30.4%
5 2
 
8.7%
4 1
 
4.3%
3 1
 
4.3%

Length

2024-03-15T04:14:14.555146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T04:14:14.794194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 12
52.2%
1 7
30.4%
5 2
 
8.7%
4 1
 
4.3%
3 1
 
4.3%

3월-현존량
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct7
Distinct (%)63.6%
Missing12
Missing (%)52.2%
Infinite0
Infinite (%)0.0%
Mean0.61818182
Minimum0.1
Maximum2.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size335.0 B
2024-03-15T04:14:15.149888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile0.15
Q10.2
median0.4
Q30.65
95-th percentile1.9
Maximum2.3
Range2.2
Interquartile range (IQR)0.45

Descriptive statistics

Standard deviation0.68675786
Coefficient of variation (CV)1.1109318
Kurtosis3.0906438
Mean0.61818182
Median Absolute Deviation (MAD)0.2
Skewness1.8847195
Sum6.8
Variance0.47163636
MonotonicityNot monotonic
2024-03-15T04:14:15.497192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0.2 4
 
17.4%
0.4 2
 
8.7%
2.3 1
 
4.3%
1.5 1
 
4.3%
0.5 1
 
4.3%
0.8 1
 
4.3%
0.1 1
 
4.3%
(Missing) 12
52.2%
ValueCountFrequency (%)
0.1 1
 
4.3%
0.2 4
17.4%
0.4 2
8.7%
0.5 1
 
4.3%
0.8 1
 
4.3%
1.5 1
 
4.3%
2.3 1
 
4.3%
ValueCountFrequency (%)
2.3 1
 
4.3%
1.5 1
 
4.3%
0.8 1
 
4.3%
0.5 1
 
4.3%
0.4 2
8.7%
0.2 4
17.4%
0.1 1
 
4.3%

5월-개체수(마리)
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)26.1%
Missing0
Missing (%)0.0%
Memory size312.0 B
<NA>
10 
1
7 
4
3 
6
 
1
18
 
1

Length

Max length4
Median length2
Mean length2.3913043
Min length1

Unique

Unique3 ?
Unique (%)13.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row1
5th row6

Common Values

ValueCountFrequency (%)
<NA> 10
43.5%
1 7
30.4%
4 3
 
13.0%
6 1
 
4.3%
18 1
 
4.3%
20 1
 
4.3%

Length

2024-03-15T04:14:15.892978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T04:14:16.191520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 10
43.5%
1 7
30.4%
4 3
 
13.0%
6 1
 
4.3%
18 1
 
4.3%
20 1
 
4.3%

5월-현존량
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct9
Distinct (%)69.2%
Missing10
Missing (%)43.5%
Infinite0
Infinite (%)0.0%
Mean1.2923077
Minimum0.1
Maximum6.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size335.0 B
2024-03-15T04:14:16.365746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile0.1
Q10.2
median0.4
Q32.1
95-th percentile4.64
Maximum6.8
Range6.7
Interquartile range (IQR)1.9

Descriptive statistics

Standard deviation1.9358295
Coefficient of variation (CV)1.4979633
Kurtosis5.3561205
Mean1.2923077
Median Absolute Deviation (MAD)0.2
Skewness2.2420403
Sum16.8
Variance3.7474359
MonotonicityNot monotonic
2024-03-15T04:14:16.670738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0.2 4
 
17.4%
0.1 2
 
8.7%
0.4 1
 
4.3%
0.5 1
 
4.3%
2.1 1
 
4.3%
2.2 1
 
4.3%
0.6 1
 
4.3%
6.8 1
 
4.3%
3.2 1
 
4.3%
(Missing) 10
43.5%
ValueCountFrequency (%)
0.1 2
8.7%
0.2 4
17.4%
0.4 1
 
4.3%
0.5 1
 
4.3%
0.6 1
 
4.3%
2.1 1
 
4.3%
2.2 1
 
4.3%
3.2 1
 
4.3%
6.8 1
 
4.3%
ValueCountFrequency (%)
6.8 1
 
4.3%
3.2 1
 
4.3%
2.2 1
 
4.3%
2.1 1
 
4.3%
0.6 1
 
4.3%
0.5 1
 
4.3%
0.4 1
 
4.3%
0.2 4
17.4%
0.1 2
8.7%

7월-개체수(마리)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct7
Distinct (%)53.8%
Missing10
Missing (%)43.5%
Infinite0
Infinite (%)0.0%
Mean4.2307692
Minimum1
Maximum11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size335.0 B
2024-03-15T04:14:17.021595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q35
95-th percentile10.4
Maximum11
Range10
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.1663293
Coefficient of variation (CV)0.7484051
Kurtosis0.86646465
Mean4.2307692
Median Absolute Deviation (MAD)2
Skewness1.2768036
Sum55
Variance10.025641
MonotonicityNot monotonic
2024-03-15T04:14:17.357886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
3 4
 
17.4%
2 2
 
8.7%
1 2
 
8.7%
5 2
 
8.7%
6 1
 
4.3%
11 1
 
4.3%
10 1
 
4.3%
(Missing) 10
43.5%
ValueCountFrequency (%)
1 2
8.7%
2 2
8.7%
3 4
17.4%
5 2
8.7%
6 1
 
4.3%
10 1
 
4.3%
11 1
 
4.3%
ValueCountFrequency (%)
11 1
 
4.3%
10 1
 
4.3%
6 1
 
4.3%
5 2
8.7%
3 4
17.4%
2 2
8.7%
1 2
8.7%

7월-현존량
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct8
Distinct (%)61.5%
Missing10
Missing (%)43.5%
Infinite0
Infinite (%)0.0%
Mean0.9
Minimum0.2
Maximum2.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size335.0 B
2024-03-15T04:14:17.683002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.2
5-th percentile0.2
Q10.3
median0.8
Q31.1
95-th percentile2.2
Maximum2.2
Range2
Interquartile range (IQR)0.8

Descriptive statistics

Standard deviation0.70237692
Coefficient of variation (CV)0.7804188
Kurtosis-0.11526164
Mean0.9
Median Absolute Deviation (MAD)0.5
Skewness0.93452417
Sum11.7
Variance0.49333333
MonotonicityNot monotonic
2024-03-15T04:14:18.059691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0.2 3
 
13.0%
1.1 2
 
8.7%
0.8 2
 
8.7%
2.2 2
 
8.7%
0.5 1
 
4.3%
1.5 1
 
4.3%
0.6 1
 
4.3%
0.3 1
 
4.3%
(Missing) 10
43.5%
ValueCountFrequency (%)
0.2 3
13.0%
0.3 1
 
4.3%
0.5 1
 
4.3%
0.6 1
 
4.3%
0.8 2
8.7%
1.1 2
8.7%
1.5 1
 
4.3%
2.2 2
8.7%
ValueCountFrequency (%)
2.2 2
8.7%
1.5 1
 
4.3%
1.1 2
8.7%
0.8 2
8.7%
0.6 1
 
4.3%
0.5 1
 
4.3%
0.3 1
 
4.3%
0.2 3
13.0%

9월-개체수(마리)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct7
Distinct (%)63.6%
Missing12
Missing (%)52.2%
Infinite0
Infinite (%)0.0%
Mean8
Minimum1
Maximum45
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size335.0 B
2024-03-15T04:14:18.380424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11.5
median2
Q38
95-th percentile29
Maximum45
Range44
Interquartile range (IQR)6.5

Descriptive statistics

Standard deviation12.907362
Coefficient of variation (CV)1.6134203
Kurtosis8.2908313
Mean8
Median Absolute Deviation (MAD)1
Skewness2.7892609
Sum88
Variance166.6
MonotonicityNot monotonic
2024-03-15T04:14:18.716931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 3
 
13.0%
2 3
 
13.0%
5 1
 
4.3%
6 1
 
4.3%
45 1
 
4.3%
13 1
 
4.3%
10 1
 
4.3%
(Missing) 12
52.2%
ValueCountFrequency (%)
1 3
13.0%
2 3
13.0%
5 1
 
4.3%
6 1
 
4.3%
10 1
 
4.3%
13 1
 
4.3%
45 1
 
4.3%
ValueCountFrequency (%)
45 1
 
4.3%
13 1
 
4.3%
10 1
 
4.3%
6 1
 
4.3%
5 1
 
4.3%
2 3
13.0%
1 3
13.0%

9월-현존량
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct9
Distinct (%)81.8%
Missing12
Missing (%)52.2%
Infinite0
Infinite (%)0.0%
Mean1.5636364
Minimum0.1
Maximum9.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size335.0 B
2024-03-15T04:14:19.054799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile0.1
Q10.15
median0.6
Q31.4
95-th percentile5.85
Maximum9.8
Range9.7
Interquartile range (IQR)1.25

Descriptive statistics

Standard deviation2.8058057
Coefficient of variation (CV)1.7944106
Kurtosis9.5053429
Mean1.5636364
Median Absolute Deviation (MAD)0.5
Skewness3.011699
Sum17.2
Variance7.8725455
MonotonicityNot monotonic
2024-03-15T04:14:19.427073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0.1 3
 
13.0%
0.2 1
 
4.3%
0.4 1
 
4.3%
1.5 1
 
4.3%
1.2 1
 
4.3%
0.6 1
 
4.3%
9.8 1
 
4.3%
1.3 1
 
4.3%
1.9 1
 
4.3%
(Missing) 12
52.2%
ValueCountFrequency (%)
0.1 3
13.0%
0.2 1
 
4.3%
0.4 1
 
4.3%
0.6 1
 
4.3%
1.2 1
 
4.3%
1.3 1
 
4.3%
1.5 1
 
4.3%
1.9 1
 
4.3%
9.8 1
 
4.3%
ValueCountFrequency (%)
9.8 1
 
4.3%
1.9 1
 
4.3%
1.5 1
 
4.3%
1.3 1
 
4.3%
1.2 1
 
4.3%
0.6 1
 
4.3%
0.4 1
 
4.3%
0.2 1
 
4.3%
0.1 3
13.0%

11월-개체수(마리)
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)21.7%
Missing0
Missing (%)0.0%
Memory size312.0 B
<NA>
17 
5
2 
1
2 
2
 
1
30
 
1

Length

Max length4
Median length4
Mean length3.2608696
Min length1

Unique

Unique2 ?
Unique (%)8.7%

Sample

1st row5
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 17
73.9%
5 2
 
8.7%
1 2
 
8.7%
2 1
 
4.3%
30 1
 
4.3%

Length

2024-03-15T04:14:19.850243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T04:14:20.191409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 17
73.9%
5 2
 
8.7%
1 2
 
8.7%
2 1
 
4.3%
30 1
 
4.3%

11월-현존량
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)26.1%
Missing0
Missing (%)0.0%
Memory size312.0 B
<NA>
17 
1.3
2 
0.2
 
1
1.2
 
1
0.1
 
1

Length

Max length4
Median length4
Mean length3.7391304
Min length3

Unique

Unique4 ?
Unique (%)17.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 17
73.9%
1.3 2
 
8.7%
0.2 1
 
4.3%
1.2 1
 
4.3%
0.1 1
 
4.3%
5.2 1
 
4.3%

Length

2024-03-15T04:14:20.577120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T04:14:20.923857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 17
73.9%
1.3 2
 
8.7%
0.2 1
 
4.3%
1.2 1
 
4.3%
0.1 1
 
4.3%
5.2 1
 
4.3%

Interactions

2024-03-15T04:14:08.982944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:14:01.558497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:14:03.173769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:14:05.163143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:14:06.635070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:14:07.950876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:14:09.123109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:14:01.796306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:14:03.512241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:14:05.502257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:14:06.787126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:14:08.090982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:14:09.275380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:14:02.028774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:14:03.810917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:14:05.761221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:14:06.970217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:14:08.238861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:14:09.499461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:14:02.271265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:14:04.178725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:14:06.013446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:14:07.219597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:14:08.414289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:14:09.764006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:14:02.586045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:14:04.512666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:14:06.288481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:14:07.476789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:14:08.652537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:14:09.993044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:14:02.848537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:14:04.794238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:14:06.500869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:14:07.730392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:14:08.841048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T04:14:21.161514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
어획 품종3월-개체수(마리)3월-현존량5월-개체수(마리)5월-현존량7월-개체수(마리)7월-현존량9월-개체수(마리)9월-현존량11월-개체수(마리)11월-현존량
어획 품종1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
3월-개체수(마리)1.0001.0000.6030.0000.0000.6720.7491.0001.0001.0001.000
3월-현존량1.0000.6031.0000.1651.0000.6620.767NaNNaN0.0000.000
5월-개체수(마리)1.0000.0000.1651.0000.9260.4860.8140.4240.6851.0001.000
5월-현존량1.0000.0001.0000.9261.0000.7060.0000.2870.0851.0001.000
7월-개체수(마리)1.0000.6720.6620.4860.7061.0000.0000.6660.0001.0001.000
7월-현존량1.0000.7490.7670.8140.0000.0001.0000.0000.5401.0001.000
9월-개체수(마리)1.0001.000NaN0.4240.2870.6660.0001.0000.7261.0001.000
9월-현존량1.0001.000NaN0.6850.0850.0000.5400.7261.0001.0001.000
11월-개체수(마리)1.0001.0000.0001.0001.0001.0001.0001.0001.0001.0001.000
11월-현존량1.0001.0000.0001.0001.0001.0001.0001.0001.0001.0001.000
2024-03-15T04:14:21.503155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
5월-개체수(마리)11월-현존량3월-개체수(마리)11월-개체수(마리)
5월-개체수(마리)1.0001.0000.0001.000
11월-현존량1.0001.0001.0000.866
3월-개체수(마리)0.0001.0001.0001.000
11월-개체수(마리)1.0000.8661.0001.000
2024-03-15T04:14:21.780089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
3월-현존량5월-현존량7월-개체수(마리)7월-현존량9월-개체수(마리)9월-현존량3월-개체수(마리)5월-개체수(마리)11월-개체수(마리)11월-현존량
3월-현존량1.0000.658-0.1920.6540.8660.8660.4520.0000.0000.000
5월-현존량0.6581.000-0.1840.3760.2990.7000.0000.6041.0001.000
7월-개체수(마리)-0.192-0.1841.0000.5040.7870.5770.3540.0001.0001.000
7월-현존량0.6540.3760.5041.0000.5150.6530.4680.0001.0001.000
9월-개체수(마리)0.8660.2990.7870.5151.0000.8601.0000.0001.0001.000
9월-현존량0.8660.7000.5770.6530.8601.0001.0000.2741.0001.000
3월-개체수(마리)0.4520.0000.3540.4681.0001.0001.0000.0001.0001.000
5월-개체수(마리)0.0000.6040.0000.0000.0000.2740.0001.0001.0001.000
11월-개체수(마리)0.0001.0001.0001.0001.0001.0001.0001.0001.0000.866
11월-현존량0.0001.0001.0001.0001.0001.0001.0001.0000.8661.000

Missing values

2024-03-15T04:14:10.527637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T04:14:11.156040image/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.
2024-03-15T04:14:11.459790image/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

어획 품종3월-개체수(마리)3월-현존량5월-개체수(마리)5월-현존량7월-개체수(마리)7월-현존량9월-개체수(마리)9월-현존량11월-개체수(마리)11월-현존량
0조피볼락(Sebastes schlegelii)10.4<NA><NA><NA><NA><NA><NA>51.3
1황해볼락(Sebastes koreanus)<NA><NA><NA><NA>20.210.1<NA><NA>
2쑤기미(Inimicus japonicus)<NA><NA><NA><NA>10.210.2<NA><NA>
3삼세기(Hemitripterus villosus)42.310.4<NA><NA><NA><NA><NA><NA>
4노래미(Hexagrammos agrammus)<NA><NA>60.530.520.4<NA><NA>
5넙치(Paralichthys olivadeus)<NA><NA>12.151.151.510.2
6문치가자미(Pleuronectes yokohamae)51.5<NA><NA>51.5<NA><NA><NA><NA>
7도다리(Pleuronichthys comutus)10.442.230.6<NA><NA><NA><NA>
8돌가자미(Kareius bicoloratus)10.5<NA><NA><NA><NA><NA><NA><NA><NA>
9박대(Cynoglossus semilaevis)10.210.260.8<NA><NA><NA><NA>
어획 품종3월-개체수(마리)3월-현존량5월-개체수(마리)5월-현존량7월-개체수(마리)7월-현존량9월-개체수(마리)9월-현존량11월-개체수(마리)11월-현존량
13보구치(Pennahia argentata)<NA><NA><NA><NA><NA><NA>60.6<NA><NA>
14붕장어(Conger myriaster)<NA><NA>10.2<NA><NA><NA><NA><NA><NA>
15멸치(Engraulis japonicus)<NA><NA>40.2<NA><NA><NA><NA><NA><NA>
16노랑가오리(Dasyatis akajei)10.8<NA><NA>10.8<NA><NA><NA><NA>
17꽃게(Portunus trituberculatus)10.2<NA><NA>30.3459.8<NA><NA>
18민꽃게(Charybdis japonica)30.210.1111.1131.351.3
19갯가재(Oratosquilla oratoria)50.140.230.220.120.1
20참갑오징어(Sepia esculenta)<NA><NA>186.8<NA><NA><NA><NA><NA><NA>
21주꾸미(Octopus ocellatus)<NA><NA>10.1<NA><NA>10.1<NA><NA>
22피뿔고둥(Rapana venosa)<NA><NA>203.2102.2101.9305.2