Overview

Dataset statistics

Number of variables11
Number of observations26
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory102.9 B

Variable types

Text1
Numeric10

Dataset

Description전북특별자치도 군산 해역에서 어획된 품종별 개체수 및 현존량(구분, 개체수, 현종량 등)우리기관에서는 더 이상 생성 불가 데이터입니다.
Author전북특별자치도
URLhttps://www.data.go.kr/data/15055702/fileData.do

Alerts

3월 개체수(마리) is highly overall correlated with 3월 현존량(㎏)High correlation
3월 현존량(㎏) is highly overall correlated with 3월 개체수(마리)High correlation
5월 개체수(마리) is highly overall correlated with 5월 현존량(㎏)High correlation
5월 현존량(㎏) is highly overall correlated with 5월 개체수(마리)High correlation
7월개체수(마리) is highly overall correlated with 7월 현존량(㎏)High correlation
7월 현존량(㎏) is highly overall correlated with 7월개체수(마리)High correlation
9월 개체수(마리) is highly overall correlated with 9월 현존량(㎏)High correlation
9월 현존량(㎏) is highly overall correlated with 9월 개체수(마리)High correlation
11월 개체수(마리) is highly overall correlated with 11월 현존량(㎏)High correlation
11월 현존량(㎏) is highly overall correlated with 11월 개체수(마리)High correlation
구분 has unique valuesUnique
3월 개체수(마리) has 17 (65.4%) zerosZeros
3월 현존량(㎏) has 17 (65.4%) zerosZeros
5월 개체수(마리) has 15 (57.7%) zerosZeros
5월 현존량(㎏) has 15 (57.7%) zerosZeros
7월개체수(마리) has 21 (80.8%) zerosZeros
7월 현존량(㎏) has 21 (80.8%) zerosZeros
9월 개체수(마리) has 11 (42.3%) zerosZeros
9월 현존량(㎏) has 11 (42.3%) zerosZeros
11월 개체수(마리) has 12 (46.2%) zerosZeros
11월 현존량(㎏) has 12 (46.2%) zerosZeros

Reproduction

Analysis started2024-03-14 17:06:18.009241
Analysis finished2024-03-14 17:06:43.306765
Duration25.3 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size336.0 B
2024-03-15T02:06:44.002684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length27
Mean length23.730769
Min length19

Characters and Unicode

Total characters617
Distinct characters85
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

Unique26 ?
Unique (%)100.0%

Sample

1st row가숭어(Chelon haematocheiius)
2nd row갯가재(Oratosquilla oratoria)
3rd row꼼치(Liparis tanakae)
4th row꽃게(Portunus trituberculatus)
5th row넙치(Paralichthys olivadeus)
ValueCountFrequency (%)
japonicus 2
 
3.8%
가숭어(chelon 1
 
1.9%
haematocheiius 1
 
1.9%
villosus 1
 
1.9%
쑤기미(lmimicus 1
 
1.9%
양태(platycephalus 1
 
1.9%
indicus 1
 
1.9%
어름돔(plectorhinchus 1
 
1.9%
cinctus 1
 
1.9%
전어(konosirus 1
 
1.9%
Other values (42) 42
79.2%
2024-03-15T02:06:45.315091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 51
 
8.3%
s 46
 
7.5%
i 45
 
7.3%
u 32
 
5.2%
e 31
 
5.0%
o 30
 
4.9%
t 30
 
4.9%
27
 
4.4%
) 26
 
4.2%
( 26
 
4.2%
Other values (75) 273
44.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 436
70.7%
Other Letter 78
 
12.6%
Space Separator 27
 
4.4%
Close Punctuation 26
 
4.2%
Open Punctuation 26
 
4.2%
Uppercase Letter 24
 
3.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
어 6
 
7.7%
치 4
 
5.1%
미 4
 
5.1%
가 4
 
5.1%
기 3
 
3.8%
게 3
 
3.8%
볼 2
 
2.6%
삼 2
 
2.6%
조 2
 
2.6%
피 2
 
2.6%
Other values (39) 46
59.0%
Lowercase Letter
ValueCountFrequency (%)
a 51
11.7%
s 46
10.6%
i 45
10.3%
u 32
 
7.3%
e 31
 
7.1%
o 30
 
6.9%
t 30
 
6.9%
c 25
 
5.7%
r 21
 
4.8%
h 21
 
4.8%
Other values (13) 104
23.9%
Uppercase Letter
ValueCountFrequency (%)
S 6
25.0%
P 6
25.0%
H 2
 
8.3%
O 2
 
8.3%
C 2
 
8.3%
L 2
 
8.3%
R 1
 
4.2%
K 1
 
4.2%
M 1
 
4.2%
T 1
 
4.2%
Space Separator
ValueCountFrequency (%)
27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 26
100.0%
Open Punctuation
ValueCountFrequency (%)
( 26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 460
74.6%
Common 79
 
12.8%
Hangul 78
 
12.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
어 6
 
7.7%
치 4
 
5.1%
미 4
 
5.1%
가 4
 
5.1%
기 3
 
3.8%
게 3
 
3.8%
볼 2
 
2.6%
삼 2
 
2.6%
조 2
 
2.6%
피 2
 
2.6%
Other values (39) 46
59.0%
Latin
ValueCountFrequency (%)
a 51
 
11.1%
s 46
 
10.0%
i 45
 
9.8%
u 32
 
7.0%
e 31
 
6.7%
o 30
 
6.5%
t 30
 
6.5%
c 25
 
5.4%
r 21
 
4.6%
h 21
 
4.6%
Other values (23) 128
27.8%
Common
ValueCountFrequency (%)
27
34.2%
) 26
32.9%
( 26
32.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 539
87.4%
Hangul 78
 
12.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 51
 
9.5%
s 46
 
8.5%
i 45
 
8.3%
u 32
 
5.9%
e 31
 
5.8%
o 30
 
5.6%
t 30
 
5.6%
27
 
5.0%
) 26
 
4.8%
( 26
 
4.8%
Other values (26) 195
36.2%
Hangul
ValueCountFrequency (%)
어 6
 
7.7%
치 4
 
5.1%
미 4
 
5.1%
가 4
 
5.1%
기 3
 
3.8%
게 3
 
3.8%
볼 2
 
2.6%
삼 2
 
2.6%
조 2
 
2.6%
피 2
 
2.6%
Other values (39) 46
59.0%

3월 개체수(마리)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6
Distinct (%)23.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1153846
Minimum0
Maximum10
Zeros17
Zeros (%)65.4%
Negative0
Negative (%)0.0%
Memory size362.0 B
2024-03-15T02:06:45.697719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile6
Maximum10
Range10
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.3887557
Coefficient of variation (CV)2.1416431
Kurtosis8.2929672
Mean1.1153846
Median Absolute Deviation (MAD)0
Skewness2.8471557
Sum29
Variance5.7061538
MonotonicityNot monotonic
2024-03-15T02:06:46.052831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 17
65.4%
1 4
 
15.4%
3 2
 
7.7%
10 1
 
3.8%
7 1
 
3.8%
2 1
 
3.8%
ValueCountFrequency (%)
0 17
65.4%
1 4
 
15.4%
2 1
 
3.8%
3 2
 
7.7%
7 1
 
3.8%
10 1
 
3.8%
ValueCountFrequency (%)
10 1
 
3.8%
7 1
 
3.8%
3 2
 
7.7%
2 1
 
3.8%
1 4
 
15.4%
0 17
65.4%

3월 현존량(㎏)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct9
Distinct (%)34.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.28576923
Minimum0
Maximum2.3
Zeros17
Zeros (%)65.4%
Negative0
Negative (%)0.0%
Memory size362.0 B
2024-03-15T02:06:46.337469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.305
95-th percentile1.7825
Maximum2.3
Range2.3
Interquartile range (IQR)0.305

Descriptive statistics

Standard deviation0.61273925
Coefficient of variation (CV)2.144175
Kurtosis6.7890318
Mean0.28576923
Median Absolute Deviation (MAD)0
Skewness2.6769371
Sum7.43
Variance0.37544938
MonotonicityNot monotonic
2024-03-15T02:06:46.531592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0.0 17
65.4%
0.48 2
 
7.7%
2.3 1
 
3.8%
2.13 1
 
3.8%
0.32 1
 
3.8%
0.74 1
 
3.8%
0.71 1
 
3.8%
0.26 1
 
3.8%
0.01 1
 
3.8%
ValueCountFrequency (%)
0.0 17
65.4%
0.01 1
 
3.8%
0.26 1
 
3.8%
0.32 1
 
3.8%
0.48 2
 
7.7%
0.71 1
 
3.8%
0.74 1
 
3.8%
2.13 1
 
3.8%
2.3 1
 
3.8%
ValueCountFrequency (%)
2.3 1
 
3.8%
2.13 1
 
3.8%
0.74 1
 
3.8%
0.71 1
 
3.8%
0.48 2
 
7.7%
0.32 1
 
3.8%
0.26 1
 
3.8%
0.01 1
 
3.8%
0.0 17
65.4%

5월 개체수(마리)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct8
Distinct (%)30.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0384615
Minimum0
Maximum12
Zeros15
Zeros (%)57.7%
Negative0
Negative (%)0.0%
Memory size362.0 B
2024-03-15T02:06:46.715060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile10.25
Maximum12
Range12
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.5830799
Coefficient of variation (CV)1.7577373
Kurtosis2.4982971
Mean2.0384615
Median Absolute Deviation (MAD)0
Skewness1.893394
Sum53
Variance12.838462
MonotonicityNot monotonic
2024-03-15T02:06:47.009548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 15
57.7%
1 3
 
11.5%
8 2
 
7.7%
2 2
 
7.7%
4 1
 
3.8%
12 1
 
3.8%
3 1
 
3.8%
11 1
 
3.8%
ValueCountFrequency (%)
0 15
57.7%
1 3
 
11.5%
2 2
 
7.7%
3 1
 
3.8%
4 1
 
3.8%
8 2
 
7.7%
11 1
 
3.8%
12 1
 
3.8%
ValueCountFrequency (%)
12 1
 
3.8%
11 1
 
3.8%
8 2
 
7.7%
4 1
 
3.8%
3 1
 
3.8%
2 2
 
7.7%
1 3
 
11.5%
0 15
57.7%

5월 현존량(㎏)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct11
Distinct (%)42.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.39730769
Minimum0
Maximum4.72
Zeros15
Zeros (%)57.7%
Negative0
Negative (%)0.0%
Memory size362.0 B
2024-03-15T02:06:47.277618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.44
95-th percentile1.275
Maximum4.72
Range4.72
Interquartile range (IQR)0.44

Descriptive statistics

Standard deviation0.95002972
Coefficient of variation (CV)2.3911687
Kurtosis18.508629
Mean0.39730769
Median Absolute Deviation (MAD)0
Skewness4.0970167
Sum10.33
Variance0.90255646
MonotonicityNot monotonic
2024-03-15T02:06:47.480875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0.0 15
57.7%
0.65 2
 
7.7%
0.32 1
 
3.8%
0.48 1
 
3.8%
1.45 1
 
3.8%
0.25 1
 
3.8%
0.18 1
 
3.8%
0.75 1
 
3.8%
0.26 1
 
3.8%
4.72 1
 
3.8%
ValueCountFrequency (%)
0.0 15
57.7%
0.18 1
 
3.8%
0.25 1
 
3.8%
0.26 1
 
3.8%
0.32 1
 
3.8%
0.48 1
 
3.8%
0.62 1
 
3.8%
0.65 2
 
7.7%
0.75 1
 
3.8%
1.45 1
 
3.8%
ValueCountFrequency (%)
4.72 1
3.8%
1.45 1
3.8%
0.75 1
3.8%
0.65 2
7.7%
0.62 1
3.8%
0.48 1
3.8%
0.32 1
3.8%
0.26 1
3.8%
0.25 1
3.8%
0.18 1
3.8%

7월개체수(마리)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6
Distinct (%)23.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.8846154
Minimum0
Maximum195
Zeros21
Zeros (%)80.8%
Negative0
Negative (%)0.0%
Memory size362.0 B
2024-03-15T02:06:47.664356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3.75
Maximum195
Range195
Interquartile range (IQR)0

Descriptive statistics

Standard deviation38.177823
Coefficient of variation (CV)4.8420653
Kurtosis25.958231
Mean7.8846154
Median Absolute Deviation (MAD)0
Skewness5.0931608
Sum205
Variance1457.5462
MonotonicityNot monotonic
2024-03-15T02:06:48.036309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 21
80.8%
195 1
 
3.8%
4 1
 
3.8%
3 1
 
3.8%
2 1
 
3.8%
1 1
 
3.8%
ValueCountFrequency (%)
0 21
80.8%
1 1
 
3.8%
2 1
 
3.8%
3 1
 
3.8%
4 1
 
3.8%
195 1
 
3.8%
ValueCountFrequency (%)
195 1
 
3.8%
4 1
 
3.8%
3 1
 
3.8%
2 1
 
3.8%
1 1
 
3.8%
0 21
80.8%

7월 현존량(㎏)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6
Distinct (%)23.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.83807692
Minimum0
Maximum21.25
Zeros21
Zeros (%)80.8%
Negative0
Negative (%)0.0%
Memory size362.0 B
2024-03-15T02:06:48.397437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.215
Maximum21.25
Range21.25
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.1636129
Coefficient of variation (CV)4.9680557
Kurtosis25.989285
Mean0.83807692
Median Absolute Deviation (MAD)0
Skewness5.0975106
Sum21.79
Variance17.335672
MonotonicityNot monotonic
2024-03-15T02:06:48.687122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0.0 21
80.8%
21.25 1
 
3.8%
0.1 1
 
3.8%
0.11 1
 
3.8%
0.08 1
 
3.8%
0.25 1
 
3.8%
ValueCountFrequency (%)
0.0 21
80.8%
0.08 1
 
3.8%
0.1 1
 
3.8%
0.11 1
 
3.8%
0.25 1
 
3.8%
21.25 1
 
3.8%
ValueCountFrequency (%)
21.25 1
 
3.8%
0.25 1
 
3.8%
0.11 1
 
3.8%
0.1 1
 
3.8%
0.08 1
 
3.8%
0.0 21
80.8%

9월 개체수(마리)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6
Distinct (%)23.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.8846154
Minimum0
Maximum43
Zeros11
Zeros (%)42.3%
Negative0
Negative (%)0.0%
Memory size362.0 B
2024-03-15T02:06:48.862128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile6.5
Maximum43
Range43
Interquartile range (IQR)2

Descriptive statistics

Standard deviation8.3490211
Coefficient of variation (CV)2.8943273
Kurtosis23.726906
Mean2.8846154
Median Absolute Deviation (MAD)1
Skewness4.7905433
Sum75
Variance69.706154
MonotonicityNot monotonic
2024-03-15T02:06:49.037011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 11
42.3%
2 8
30.8%
1 4
 
15.4%
43 1
 
3.8%
5 1
 
3.8%
7 1
 
3.8%
ValueCountFrequency (%)
0 11
42.3%
1 4
 
15.4%
2 8
30.8%
5 1
 
3.8%
7 1
 
3.8%
43 1
 
3.8%
ValueCountFrequency (%)
43 1
 
3.8%
7 1
 
3.8%
5 1
 
3.8%
2 8
30.8%
1 4
 
15.4%
0 11
42.3%

9월 현존량(㎏)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct15
Distinct (%)57.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.67076923
Minimum0
Maximum7.8
Zeros11
Zeros (%)42.3%
Negative0
Negative (%)0.0%
Memory size362.0 B
2024-03-15T02:06:49.312742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.155
Q30.5175
95-th percentile2.245
Maximum7.8
Range7.8
Interquartile range (IQR)0.5175

Descriptive statistics

Standard deviation1.5714628
Coefficient of variation (CV)2.3427771
Kurtosis18.259928
Mean0.67076923
Median Absolute Deviation (MAD)0.155
Skewness4.0770173
Sum17.44
Variance2.4694954
MonotonicityNot monotonic
2024-03-15T02:06:49.668351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0.0 11
42.3%
0.16 2
 
7.7%
1.06 1
 
3.8%
7.8 1
 
3.8%
0.43 1
 
3.8%
0.45 1
 
3.8%
0.74 1
 
3.8%
0.54 1
 
3.8%
1.9 1
 
3.8%
0.85 1
 
3.8%
Other values (5) 5
19.2%
ValueCountFrequency (%)
0.0 11
42.3%
0.14 1
 
3.8%
0.15 1
 
3.8%
0.16 2
 
7.7%
0.3 1
 
3.8%
0.4 1
 
3.8%
0.43 1
 
3.8%
0.45 1
 
3.8%
0.54 1
 
3.8%
0.74 1
 
3.8%
ValueCountFrequency (%)
7.8 1
3.8%
2.36 1
3.8%
1.9 1
3.8%
1.06 1
3.8%
0.85 1
3.8%
0.74 1
3.8%
0.54 1
3.8%
0.45 1
3.8%
0.43 1
3.8%
0.4 1
3.8%

11월 개체수(마리)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct11
Distinct (%)42.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.9615385
Minimum0
Maximum26
Zeros12
Zeros (%)46.2%
Negative0
Negative (%)0.0%
Memory size362.0 B
2024-03-15T02:06:49.882985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q34
95-th percentile19.75
Maximum26
Range26
Interquartile range (IQR)4

Descriptive statistics

Standard deviation6.9941734
Coefficient of variation (CV)1.7655195
Kurtosis4.1941651
Mean3.9615385
Median Absolute Deviation (MAD)1
Skewness2.2199749
Sum103
Variance48.918462
MonotonicityNot monotonic
2024-03-15T02:06:50.084112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 12
46.2%
1 3
 
11.5%
2 2
 
7.7%
4 2
 
7.7%
6 1
 
3.8%
26 1
 
3.8%
19 1
 
3.8%
9 1
 
3.8%
20 1
 
3.8%
3 1
 
3.8%
ValueCountFrequency (%)
0 12
46.2%
1 3
 
11.5%
2 2
 
7.7%
3 1
 
3.8%
4 2
 
7.7%
5 1
 
3.8%
6 1
 
3.8%
9 1
 
3.8%
19 1
 
3.8%
20 1
 
3.8%
ValueCountFrequency (%)
26 1
 
3.8%
20 1
 
3.8%
19 1
 
3.8%
9 1
 
3.8%
6 1
 
3.8%
5 1
 
3.8%
4 2
7.7%
3 1
 
3.8%
2 2
7.7%
1 3
11.5%

11월 현존량(㎏)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct15
Distinct (%)57.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1738462
Minimum0
Maximum7.05
Zeros12
Zeros (%)46.2%
Negative0
Negative (%)0.0%
Memory size362.0 B
2024-03-15T02:06:50.276553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.105
Q30.8725
95-th percentile6.4825
Maximum7.05
Range7.05
Interquartile range (IQR)0.8725

Descriptive statistics

Standard deviation2.1971765
Coefficient of variation (CV)1.8717755
Kurtosis2.734904
Mean1.1738462
Median Absolute Deviation (MAD)0.105
Skewness2.0080476
Sum30.52
Variance4.8275846
MonotonicityNot monotonic
2024-03-15T02:06:50.579447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0.0 12
46.2%
6.31 1
 
3.8%
0.92 1
 
3.8%
0.25 1
 
3.8%
2.16 1
 
3.8%
7.05 1
 
3.8%
0.11 1
 
3.8%
1.29 1
 
3.8%
3.99 1
 
3.8%
6.54 1
 
3.8%
Other values (5) 5
19.2%
ValueCountFrequency (%)
0.0 12
46.2%
0.1 1
 
3.8%
0.11 1
 
3.8%
0.19 1
 
3.8%
0.23 1
 
3.8%
0.25 1
 
3.8%
0.65 1
 
3.8%
0.73 1
 
3.8%
0.92 1
 
3.8%
1.29 1
 
3.8%
ValueCountFrequency (%)
7.05 1
3.8%
6.54 1
3.8%
6.31 1
3.8%
3.99 1
3.8%
2.16 1
3.8%
1.29 1
3.8%
0.92 1
3.8%
0.73 1
3.8%
0.65 1
3.8%
0.25 1
3.8%

Interactions

2024-03-15T02:06:40.348486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:18.440233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:20.553184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:22.945148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:25.610881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:29.053372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:31.755875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:33.653455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:35.690545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:38.036935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:40.495299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:18.686948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:20.792171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:23.189687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:26.137525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:29.395116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:31.944688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:33.857305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:35.908980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:38.176199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:40.659650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:18.922856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:21.024998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:23.428004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:26.377108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:29.649285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:32.082896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:34.017438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:36.168797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:38.385331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:41.040771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:19.166642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:21.267090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:23.680625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:26.736377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:29.913767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:32.228459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:34.201677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:36.427685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:38.793606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:41.285408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:19.397962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:21.500439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:23.917315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:27.282357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:30.173713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:32.401766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:34.432816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:36.616301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:39.028819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:41.478045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:19.678906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:21.754823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:24.181643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:27.566754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:30.514803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:32.663174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:34.687563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:36.861190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:39.243557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:41.618051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:19.821780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:21.988589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:24.423788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:27.857945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:30.870382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:32.902025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:34.919122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:37.165833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:39.380180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:41.766678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:19.956342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:22.225845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:24.665459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:28.199195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:31.114696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:33.135422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:35.154155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:37.414966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:39.512168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:42.038845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:20.112661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:22.493187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:24.928358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:28.496596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:31.384001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:33.366030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:35.382262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:37.691990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:39.758260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:42.285593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:20.256560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:22.692460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:25.264699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:28.758953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:31.542488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:33.503097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:35.519075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:37.876606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:06:39.992904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T02:06:50.776706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분3월 개체수(마리)3월 현존량(㎏)5월 개체수(마리)5월 현존량(㎏)7월개체수(마리)7월 현존량(㎏)9월 개체수(마리)9월 현존량(㎏)11월 개체수(마리)11월 현존량(㎏)
구분1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
3월 개체수(마리)1.0001.0000.8740.7870.7060.0000.0000.7930.0000.5560.479
3월 현존량(㎏)1.0000.8741.0000.5050.2950.0000.0000.3800.4420.4380.616
5월 개체수(마리)1.0000.7870.5051.0000.7771.0001.0000.9950.7540.0000.000
5월 현존량(㎏)1.0000.7060.2950.7771.0000.3650.3650.5370.0000.4350.000
7월개체수(마리)1.0000.0000.0001.0000.3651.0000.6461.0001.0000.0000.000
7월 현존량(㎏)1.0000.0000.0001.0000.3650.6461.0001.0001.0000.0000.000
9월 개체수(마리)1.0000.7930.3800.9950.5371.0001.0001.0000.8090.9020.000
9월 현존량(㎏)1.0000.0000.4420.7540.0001.0001.0000.8091.0000.6190.617
11월 개체수(마리)1.0000.5560.4380.0000.4350.0000.0000.9020.6191.0000.969
11월 현존량(㎏)1.0000.4790.6160.0000.0000.0000.0000.0000.6170.9691.000
2024-03-15T02:06:51.160956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
3월 개체수(마리)3월 현존량(㎏)5월 개체수(마리)5월 현존량(㎏)7월개체수(마리)7월 현존량(㎏)9월 개체수(마리)9월 현존량(㎏)11월 개체수(마리)11월 현존량(㎏)
3월 개체수(마리)1.0000.9640.2510.269-0.080-0.1180.1840.2100.2770.296
3월 현존량(㎏)0.9641.0000.1530.174-0.162-0.1880.1080.2080.2680.324
5월 개체수(마리)0.2510.1531.0000.9700.2250.2150.1140.1090.1600.095
5월 현존량(㎏)0.2690.1740.9701.0000.2850.2950.2100.2150.2250.166
7월개체수(마리)-0.080-0.1620.2250.2851.0000.9900.2240.1910.1270.091
7월 현존량(㎏)-0.118-0.1880.2150.2950.9901.0000.2290.2110.1420.112
9월 개체수(마리)0.1840.1080.1140.2100.2240.2291.0000.8950.2890.262
9월 현존량(㎏)0.2100.2080.1090.2150.1910.2110.8951.0000.3280.337
11월 개체수(마리)0.2770.2680.1600.2250.1270.1420.2890.3281.0000.965
11월 현존량(㎏)0.2960.3240.0950.1660.0910.1120.2620.3370.9651.000

Missing values

2024-03-15T02:06:42.637825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T02:06:43.124487image/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

구분3월 개체수(마리)3월 현존량(㎏)5월 개체수(마리)5월 현존량(㎏)7월개체수(마리)7월 현존량(㎏)9월 개체수(마리)9월 현존량(㎏)11월 개체수(마리)11월 현존량(㎏)
0가숭어(Chelon haematocheiius)12.300.000.011.0666.31
1갯가재(Oratosquilla oratoria)00.080.3200.000.000.0
2꼼치(Liparis tanakae)10.4800.000.000.010.92
3꽃게(Portunus trituberculatus)00.040.6519521.25437.820.25
4넙치(Paralichthys olivadeus)00.000.000.020.4342.16
5돌가자미(kareius bicoloratus)00.000.000.000.0267.05
6말쥐치(Thamnaconus modestus )00.000.000.020.4510.11
7문치가자미(Pleuronectes yokohamae)102.1320.4800.020.7400.0
8민꽃게(Charybdis japonica)70.32121.4540.150.54191.29
9민어(Miichthys miiuy)00.000.000.021.900.0
구분3월 개체수(마리)3월 현존량(㎏)5월 개체수(마리)5월 현존량(㎏)7월개체수(마리)7월 현존량(㎏)9월 개체수(마리)9월 현존량(㎏)11월 개체수(마리)11월 현존량(㎏)
16어름돔(Plectorhinchus cinctus)00.000.000.010.400.0
17전어(Konosirus punctatus)00.000.000.020.1500.0
18조피볼락(Sebastes schlegelii)30.7130.7500.072.36206.54
19쥐노래미(Hexagrammos otakii)10.2620.2600.010.330.73
20참갑오징어(Sepia esculenta)00.0114.7200.000.000.0
21참조기(Larimichthys polyactis)00.000.000.020.1400.0
22풀망둑(Synechogobius hasta)00.000.000.000.020.1
23피뿔고둥(Rapana venosa)00.080.6200.000.050.65
24황해볼락(Sebastes koreanus)10.0100.000.020.1640.23
25해삼(Stichopus japonicus)20.4800.000.000.010.19