Overview

Dataset statistics

Number of variables13
Number of observations25
Missing cells126
Missing cells (%)38.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.7 KiB
Average record size in memory109.3 B

Variable types

Text13

Alerts

Unnamed: 1 has 17 (68.0%) missing valuesMissing
Unnamed: 2 has 18 (72.0%) missing valuesMissing
Unnamed: 3 has 13 (52.0%) missing valuesMissing
Unnamed: 4 has 14 (56.0%) missing valuesMissing
Unnamed: 5 has 13 (52.0%) missing valuesMissing
Unnamed: 6 has 14 (56.0%) missing valuesMissing
Unnamed: 7 has 7 (28.0%) missing valuesMissing
Unnamed: 8 has 8 (32.0%) missing valuesMissing
Unnamed: 9 has 10 (40.0%) missing valuesMissing
Unnamed: 10 has 11 (44.0%) missing valuesMissing
Unnamed: 12 has 1 (4.0%) missing valuesMissing
군산해역에서 어획된 품종별 개체수 및 현존량(2014년) has unique valuesUnique

Reproduction

Analysis started2024-03-14 02:49:44.295754
Analysis finished2024-03-14 02:49:45.448428
Duration1.15 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

군산해역에서 어획된 품종별 개체수 및 현존량(2014년)
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2024-03-14T11:49:45.617030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length28
Mean length22.08
Min length2

Characters and Unicode

Total characters552
Distinct characters86
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

Unique25 ?
Unique (%)100.0%

Sample

1st row일자
2nd row구분
3rd row조피볼락(Sebastes schlegelii)
4th row황해볼락(Sebastes koreanus)
5th row삼세기(Hemitripterus villosus)
ValueCountFrequency (%)
일자 1
 
2.1%
japonicus 1
 
2.1%
보구치(pennahia 1
 
2.1%
argentata 1
 
2.1%
삼치(scomberomorus 1
 
2.1%
niphomius 1
 
2.1%
참돔(pagrus 1
 
2.1%
major 1
 
2.1%
꼼치(liparis 1
 
2.1%
tanakae 1
 
2.1%
Other values (37) 37
78.7%
2024-03-14T11:49:45.936701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 49
 
8.9%
s 43
 
7.8%
e 35
 
6.3%
o 29
 
5.3%
u 29
 
5.3%
i 29
 
5.3%
r 24
 
4.3%
22
 
4.0%
( 22
 
4.0%
) 22
 
4.0%
Other values (76) 248
44.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 390
70.7%
Other Letter 74
 
13.4%
Space Separator 22
 
4.0%
Open Punctuation 22
 
4.0%
Close Punctuation 22
 
4.0%
Uppercase Letter 22
 
4.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
치 8
 
10.8%
넙 3
 
4.1%
가 3
 
4.1%
삼 2
 
2.7%
구 2
 
2.7%
게 2
 
2.7%
자 2
 
2.7%
어 2
 
2.7%
피 2
 
2.7%
볼 2
 
2.7%
Other values (40) 46
62.2%
Lowercase Letter
ValueCountFrequency (%)
a 49
12.6%
s 43
11.0%
e 35
 
9.0%
o 29
 
7.4%
u 29
 
7.4%
i 29
 
7.4%
r 24
 
6.2%
n 21
 
5.4%
t 21
 
5.4%
l 18
 
4.6%
Other values (14) 92
23.6%
Uppercase Letter
ValueCountFrequency (%)
P 8
36.4%
S 4
18.2%
C 3
 
13.6%
H 2
 
9.1%
E 1
 
4.5%
L 1
 
4.5%
O 1
 
4.5%
R 1
 
4.5%
Z 1
 
4.5%
Space Separator
ValueCountFrequency (%)
22
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 412
74.6%
Hangul 74
 
13.4%
Common 66
 
12.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
치 8
 
10.8%
넙 3
 
4.1%
가 3
 
4.1%
삼 2
 
2.7%
구 2
 
2.7%
게 2
 
2.7%
자 2
 
2.7%
어 2
 
2.7%
피 2
 
2.7%
볼 2
 
2.7%
Other values (40) 46
62.2%
Latin
ValueCountFrequency (%)
a 49
11.9%
s 43
 
10.4%
e 35
 
8.5%
o 29
 
7.0%
u 29
 
7.0%
i 29
 
7.0%
r 24
 
5.8%
n 21
 
5.1%
t 21
 
5.1%
l 18
 
4.4%
Other values (23) 114
27.7%
Common
ValueCountFrequency (%)
22
33.3%
( 22
33.3%
) 22
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 478
86.6%
Hangul 74
 
13.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 49
 
10.3%
s 43
 
9.0%
e 35
 
7.3%
o 29
 
6.1%
u 29
 
6.1%
i 29
 
6.1%
r 24
 
5.0%
22
 
4.6%
( 22
 
4.6%
) 22
 
4.6%
Other values (26) 174
36.4%
Hangul
ValueCountFrequency (%)
치 8
 
10.8%
넙 3
 
4.1%
가 3
 
4.1%
삼 2
 
2.7%
구 2
 
2.7%
게 2
 
2.7%
자 2
 
2.7%
어 2
 
2.7%
피 2
 
2.7%
볼 2
 
2.7%
Other values (40) 46
62.2%

Unnamed: 1
Text

MISSING 

Distinct5
Distinct (%)62.5%
Missing17
Missing (%)68.0%
Memory size332.0 B
2024-03-14T11:49:46.030495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length1
Mean length2
Min length1

Characters and Unicode

Total characters16
Distinct characters11
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

Unique3 ?
Unique (%)37.5%

Sample

1st row3월
2nd row개체수(마리)
3rd row4
4th row1
5th row4
ValueCountFrequency (%)
1 3
37.5%
4 2
25.0%
3월 1
 
12.5%
개체수(마리 1
 
12.5%
11 1
 
12.5%
2024-03-14T11:49:46.222466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 5
31.2%
4 2
 
12.5%
3 1
 
6.2%
월 1
 
6.2%
개 1
 
6.2%
체 1
 
6.2%
수 1
 
6.2%
( 1
 
6.2%
마 1
 
6.2%
리 1
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8
50.0%
Other Letter 6
37.5%
Open Punctuation 1
 
6.2%
Close Punctuation 1
 
6.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
월 1
16.7%
개 1
16.7%
체 1
16.7%
수 1
16.7%
마 1
16.7%
리 1
16.7%
Decimal Number
ValueCountFrequency (%)
1 5
62.5%
4 2
 
25.0%
3 1
 
12.5%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10
62.5%
Hangul 6
37.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
월 1
16.7%
개 1
16.7%
체 1
16.7%
수 1
16.7%
마 1
16.7%
리 1
16.7%
Common
ValueCountFrequency (%)
1 5
50.0%
4 2
 
20.0%
3 1
 
10.0%
( 1
 
10.0%
) 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10
62.5%
Hangul 6
37.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 5
50.0%
4 2
 
20.0%
3 1
 
10.0%
( 1
 
10.0%
) 1
 
10.0%
Hangul
ValueCountFrequency (%)
월 1
16.7%
개 1
16.7%
체 1
16.7%
수 1
16.7%
마 1
16.7%
리 1
16.7%

Unnamed: 2
Text

MISSING 

Distinct7
Distinct (%)100.0%
Missing18
Missing (%)72.0%
Memory size332.0 B
2024-03-14T11:49:46.350213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.1428571
Min length3

Characters and Unicode

Total characters29
Distinct characters14
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)100.0%

Sample

1st row현존량(㎏)
2nd row1.32
3rd row0.14
4th row0.95
5th row0.04
ValueCountFrequency (%)
현존량(㎏ 1
14.3%
1.32 1
14.3%
0.14 1
14.3%
0.95 1
14.3%
0.04 1
14.3%
0.1 1
14.3%
2.55 1
14.3%
2024-03-14T11:49:46.595447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 6
20.7%
0 5
17.2%
1 3
10.3%
5 3
10.3%
2 2
 
6.9%
4 2
 
6.9%
현 1
 
3.4%
존 1
 
3.4%
량 1
 
3.4%
( 1
 
3.4%
Other values (4) 4
13.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17
58.6%
Other Punctuation 6
 
20.7%
Other Letter 3
 
10.3%
Open Punctuation 1
 
3.4%
Other Symbol 1
 
3.4%
Close Punctuation 1
 
3.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5
29.4%
1 3
17.6%
5 3
17.6%
2 2
 
11.8%
4 2
 
11.8%
3 1
 
5.9%
9 1
 
5.9%
Other Letter
ValueCountFrequency (%)
현 1
33.3%
존 1
33.3%
량 1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Other Symbol
ValueCountFrequency (%)
㎏ 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 26
89.7%
Hangul 3
 
10.3%

Most frequent character per script

Common
ValueCountFrequency (%)
. 6
23.1%
0 5
19.2%
1 3
11.5%
5 3
11.5%
2 2
 
7.7%
4 2
 
7.7%
( 1
 
3.8%
㎏ 1
 
3.8%
) 1
 
3.8%
3 1
 
3.8%
Hangul
ValueCountFrequency (%)
현 1
33.3%
존 1
33.3%
량 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25
86.2%
Hangul 3
 
10.3%
CJK Compat 1
 
3.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 6
24.0%
0 5
20.0%
1 3
12.0%
5 3
12.0%
2 2
 
8.0%
4 2
 
8.0%
( 1
 
4.0%
) 1
 
4.0%
3 1
 
4.0%
9 1
 
4.0%
Hangul
ValueCountFrequency (%)
현 1
33.3%
존 1
33.3%
량 1
33.3%
CJK Compat
ValueCountFrequency (%)
㎏ 1
100.0%

Unnamed: 3
Text

MISSING 

Distinct6
Distinct (%)50.0%
Missing13
Missing (%)52.0%
Memory size332.0 B
2024-03-14T11:49:46.682300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.6666667
Min length1

Characters and Unicode

Total characters20
Distinct characters12
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

Unique5 ?
Unique (%)41.7%

Sample

1st row5월
2nd row개체수(마리)
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 7
58.3%
5월 1
 
8.3%
개체수(마리 1
 
8.3%
4 1
 
8.3%
5 1
 
8.3%
16 1
 
8.3%
2024-03-14T11:49:46.922817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 8
40.0%
5 2
 
10.0%
월 1
 
5.0%
개 1
 
5.0%
체 1
 
5.0%
수 1
 
5.0%
( 1
 
5.0%
마 1
 
5.0%
리 1
 
5.0%
) 1
 
5.0%
Other values (2) 2
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12
60.0%
Other Letter 6
30.0%
Open Punctuation 1
 
5.0%
Close Punctuation 1
 
5.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
월 1
16.7%
개 1
16.7%
체 1
16.7%
수 1
16.7%
마 1
16.7%
리 1
16.7%
Decimal Number
ValueCountFrequency (%)
1 8
66.7%
5 2
 
16.7%
4 1
 
8.3%
6 1
 
8.3%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14
70.0%
Hangul 6
30.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 8
57.1%
5 2
 
14.3%
( 1
 
7.1%
) 1
 
7.1%
4 1
 
7.1%
6 1
 
7.1%
Hangul
ValueCountFrequency (%)
월 1
16.7%
개 1
16.7%
체 1
16.7%
수 1
16.7%
마 1
16.7%
리 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14
70.0%
Hangul 6
30.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 8
57.1%
5 2
 
14.3%
( 1
 
7.1%
) 1
 
7.1%
4 1
 
7.1%
6 1
 
7.1%
Hangul
ValueCountFrequency (%)
월 1
16.7%
개 1
16.7%
체 1
16.7%
수 1
16.7%
마 1
16.7%
리 1
16.7%

Unnamed: 4
Text

MISSING 

Distinct7
Distinct (%)63.6%
Missing14
Missing (%)56.0%
Memory size332.0 B
2024-03-14T11:49:47.123164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.0909091
Min length3

Characters and Unicode

Total characters45
Distinct characters15
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)45.5%

Sample

1st row현존량(㎏)
2nd row0.01
3rd row0.02
4th row0.02
5th row0.02
ValueCountFrequency (%)
0.01 3
27.3%
0.02 3
27.3%
현존량(㎏ 1
 
9.1%
0.1 1
 
9.1%
1.46 1
 
9.1%
0.74 1
 
9.1%
2.39 1
 
9.1%
2024-03-14T11:49:47.344692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
31.1%
. 10
22.2%
1 5
 
11.1%
2 4
 
8.9%
4 2
 
4.4%
현 1
 
2.2%
존 1
 
2.2%
량 1
 
2.2%
( 1
 
2.2%
㎏ 1
 
2.2%
Other values (5) 5
 
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 29
64.4%
Other Punctuation 10
 
22.2%
Other Letter 3
 
6.7%
Open Punctuation 1
 
2.2%
Other Symbol 1
 
2.2%
Close Punctuation 1
 
2.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14
48.3%
1 5
 
17.2%
2 4
 
13.8%
4 2
 
6.9%
6 1
 
3.4%
7 1
 
3.4%
3 1
 
3.4%
9 1
 
3.4%
Other Letter
ValueCountFrequency (%)
현 1
33.3%
존 1
33.3%
량 1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Other Symbol
ValueCountFrequency (%)
㎏ 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 42
93.3%
Hangul 3
 
6.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
33.3%
. 10
23.8%
1 5
 
11.9%
2 4
 
9.5%
4 2
 
4.8%
( 1
 
2.4%
㎏ 1
 
2.4%
) 1
 
2.4%
6 1
 
2.4%
7 1
 
2.4%
Other values (2) 2
 
4.8%
Hangul
ValueCountFrequency (%)
현 1
33.3%
존 1
33.3%
량 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41
91.1%
Hangul 3
 
6.7%
CJK Compat 1
 
2.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14
34.1%
. 10
24.4%
1 5
 
12.2%
2 4
 
9.8%
4 2
 
4.9%
( 1
 
2.4%
) 1
 
2.4%
6 1
 
2.4%
7 1
 
2.4%
3 1
 
2.4%
Hangul
ValueCountFrequency (%)
현 1
33.3%
존 1
33.3%
량 1
33.3%
CJK Compat
ValueCountFrequency (%)
㎏ 1
100.0%

Unnamed: 5
Text

MISSING 

Distinct9
Distinct (%)75.0%
Missing13
Missing (%)52.0%
Memory size332.0 B
2024-03-14T11:49:47.457007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length2
Mean length2.0833333
Min length1

Characters and Unicode

Total characters25
Distinct characters14
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

Unique7 ?
Unique (%)58.3%

Sample

1st row7월
2nd row개체수(마리)
3rd row1
4th row2
5th row1
ValueCountFrequency (%)
13 3
25.0%
1 2
16.7%
7월 1
 
8.3%
개체수(마리 1
 
8.3%
2 1
 
8.3%
3 1
 
8.3%
34 1
 
8.3%
11 1
 
8.3%
92 1
 
8.3%
2024-03-14T11:49:47.701376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 7
28.0%
3 5
20.0%
2 2
 
8.0%
7 1
 
4.0%
월 1
 
4.0%
개 1
 
4.0%
체 1
 
4.0%
수 1
 
4.0%
( 1
 
4.0%
마 1
 
4.0%
Other values (4) 4
16.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17
68.0%
Other Letter 6
 
24.0%
Open Punctuation 1
 
4.0%
Close Punctuation 1
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7
41.2%
3 5
29.4%
2 2
 
11.8%
7 1
 
5.9%
4 1
 
5.9%
9 1
 
5.9%
Other Letter
ValueCountFrequency (%)
월 1
16.7%
개 1
16.7%
체 1
16.7%
수 1
16.7%
마 1
16.7%
리 1
16.7%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19
76.0%
Hangul 6
 
24.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 7
36.8%
3 5
26.3%
2 2
 
10.5%
7 1
 
5.3%
( 1
 
5.3%
) 1
 
5.3%
4 1
 
5.3%
9 1
 
5.3%
Hangul
ValueCountFrequency (%)
월 1
16.7%
개 1
16.7%
체 1
16.7%
수 1
16.7%
마 1
16.7%
리 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19
76.0%
Hangul 6
 
24.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 7
36.8%
3 5
26.3%
2 2
 
10.5%
7 1
 
5.3%
( 1
 
5.3%
) 1
 
5.3%
4 1
 
5.3%
9 1
 
5.3%
Hangul
ValueCountFrequency (%)
월 1
16.7%
개 1
16.7%
체 1
16.7%
수 1
16.7%
마 1
16.7%
리 1
16.7%

Unnamed: 6
Text

MISSING 

Distinct11
Distinct (%)100.0%
Missing14
Missing (%)56.0%
Memory size332.0 B
2024-03-14T11:49:47.860339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.5454545
Min length3

Characters and Unicode

Total characters39
Distinct characters16
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)100.0%

Sample

1st row현존량(㎏)
2nd row0.05
3rd row1.2
4th row0.3
5th row0.2
ValueCountFrequency (%)
현존량(㎏ 1
9.1%
0.05 1
9.1%
1.2 1
9.1%
0.3 1
9.1%
0.2 1
9.1%
7.9 1
9.1%
0.8 1
9.1%
0.45 1
9.1%
4.4 1
9.1%
2.2 1
9.1%
2024-03-14T11:49:48.116673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 10
25.6%
0 6
15.4%
2 4
 
10.3%
4 3
 
7.7%
5 2
 
5.1%
1 2
 
5.1%
7 2
 
5.1%
8 2
 
5.1%
현 1
 
2.6%
존 1
 
2.6%
Other values (6) 6
15.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 23
59.0%
Other Punctuation 10
25.6%
Other Letter 3
 
7.7%
Open Punctuation 1
 
2.6%
Other Symbol 1
 
2.6%
Close Punctuation 1
 
2.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6
26.1%
2 4
17.4%
4 3
13.0%
5 2
 
8.7%
1 2
 
8.7%
7 2
 
8.7%
8 2
 
8.7%
3 1
 
4.3%
9 1
 
4.3%
Other Letter
ValueCountFrequency (%)
현 1
33.3%
존 1
33.3%
량 1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Other Symbol
ValueCountFrequency (%)
㎏ 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 36
92.3%
Hangul 3
 
7.7%

Most frequent character per script

Common
ValueCountFrequency (%)
. 10
27.8%
0 6
16.7%
2 4
 
11.1%
4 3
 
8.3%
5 2
 
5.6%
1 2
 
5.6%
7 2
 
5.6%
8 2
 
5.6%
( 1
 
2.8%
㎏ 1
 
2.8%
Other values (3) 3
 
8.3%
Hangul
ValueCountFrequency (%)
현 1
33.3%
존 1
33.3%
량 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 35
89.7%
Hangul 3
 
7.7%
CJK Compat 1
 
2.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 10
28.6%
0 6
17.1%
2 4
 
11.4%
4 3
 
8.6%
5 2
 
5.7%
1 2
 
5.7%
7 2
 
5.7%
8 2
 
5.7%
( 1
 
2.9%
) 1
 
2.9%
Other values (2) 2
 
5.7%
Hangul
ValueCountFrequency (%)
현 1
33.3%
존 1
33.3%
량 1
33.3%
CJK Compat
ValueCountFrequency (%)
㎏ 1
100.0%

Unnamed: 7
Text

MISSING 

Distinct11
Distinct (%)61.1%
Missing7
Missing (%)28.0%
Memory size332.0 B
2024-03-14T11:49:48.209593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.6666667
Min length1

Characters and Unicode

Total characters30
Distinct characters15
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

Unique7 ?
Unique (%)38.9%

Sample

1st row9월
2nd row개체수(마리)
3rd row8
4th row1
5th row1
ValueCountFrequency (%)
1 5
27.8%
2 2
 
11.1%
9 2
 
11.1%
4 2
 
11.1%
9월 1
 
5.6%
개체수(마리 1
 
5.6%
8 1
 
5.6%
24 1
 
5.6%
30 1
 
5.6%
14 1
 
5.6%
2024-03-14T11:49:48.402403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 9
30.0%
4 4
13.3%
2 3
 
10.0%
9 3
 
10.0%
월 1
 
3.3%
개 1
 
3.3%
체 1
 
3.3%
수 1
 
3.3%
( 1
 
3.3%
마 1
 
3.3%
Other values (5) 5
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 22
73.3%
Other Letter 6
 
20.0%
Open Punctuation 1
 
3.3%
Close Punctuation 1
 
3.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 9
40.9%
4 4
18.2%
2 3
 
13.6%
9 3
 
13.6%
8 1
 
4.5%
3 1
 
4.5%
0 1
 
4.5%
Other Letter
ValueCountFrequency (%)
월 1
16.7%
개 1
16.7%
체 1
16.7%
수 1
16.7%
마 1
16.7%
리 1
16.7%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24
80.0%
Hangul 6
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 9
37.5%
4 4
16.7%
2 3
 
12.5%
9 3
 
12.5%
( 1
 
4.2%
) 1
 
4.2%
8 1
 
4.2%
3 1
 
4.2%
0 1
 
4.2%
Hangul
ValueCountFrequency (%)
월 1
16.7%
개 1
16.7%
체 1
16.7%
수 1
16.7%
마 1
16.7%
리 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24
80.0%
Hangul 6
 
20.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 9
37.5%
4 4
16.7%
2 3
 
12.5%
9 3
 
12.5%
( 1
 
4.2%
) 1
 
4.2%
8 1
 
4.2%
3 1
 
4.2%
0 1
 
4.2%
Hangul
ValueCountFrequency (%)
월 1
16.7%
개 1
16.7%
체 1
16.7%
수 1
16.7%
마 1
16.7%
리 1
16.7%

Unnamed: 8
Text

MISSING 

Distinct17
Distinct (%)100.0%
Missing8
Missing (%)32.0%
Memory size332.0 B
2024-03-14T11:49:48.540688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length3.8823529
Min length3

Characters and Unicode

Total characters66
Distinct characters15
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)100.0%

Sample

1st row현존량(㎏)
2nd row1.02
3rd row0.45
4th row0.18
5th row0.24
ValueCountFrequency (%)
현존량(㎏ 1
 
5.9%
0.2 1
 
5.9%
0.78 1
 
5.9%
0.05 1
 
5.9%
1.11 1
 
5.9%
1.9 1
 
5.9%
0.02 1
 
5.9%
0.17 1
 
5.9%
2.25 1
 
5.9%
1.02 1
 
5.9%
Other values (7) 7
41.2%
2024-03-14T11:49:48.779744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 16
24.2%
0 13
19.7%
1 11
16.7%
2 6
 
9.1%
5 4
 
6.1%
8 4
 
6.1%
4 2
 
3.0%
7 2
 
3.0%
9 2
 
3.0%
현 1
 
1.5%
Other values (5) 5
 
7.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 44
66.7%
Other Punctuation 16
 
24.2%
Other Letter 3
 
4.5%
Open Punctuation 1
 
1.5%
Other Symbol 1
 
1.5%
Close Punctuation 1
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
29.5%
1 11
25.0%
2 6
13.6%
5 4
 
9.1%
8 4
 
9.1%
4 2
 
4.5%
7 2
 
4.5%
9 2
 
4.5%
Other Letter
ValueCountFrequency (%)
현 1
33.3%
존 1
33.3%
량 1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Other Symbol
ValueCountFrequency (%)
㎏ 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 63
95.5%
Hangul 3
 
4.5%

Most frequent character per script

Common
ValueCountFrequency (%)
. 16
25.4%
0 13
20.6%
1 11
17.5%
2 6
 
9.5%
5 4
 
6.3%
8 4
 
6.3%
4 2
 
3.2%
7 2
 
3.2%
9 2
 
3.2%
( 1
 
1.6%
Other values (2) 2
 
3.2%
Hangul
ValueCountFrequency (%)
현 1
33.3%
존 1
33.3%
량 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 62
93.9%
Hangul 3
 
4.5%
CJK Compat 1
 
1.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 16
25.8%
0 13
21.0%
1 11
17.7%
2 6
 
9.7%
5 4
 
6.5%
8 4
 
6.5%
4 2
 
3.2%
7 2
 
3.2%
9 2
 
3.2%
( 1
 
1.6%
Hangul
ValueCountFrequency (%)
현 1
33.3%
존 1
33.3%
량 1
33.3%
CJK Compat
ValueCountFrequency (%)
㎏ 1
100.0%

Unnamed: 9
Text

MISSING 

Distinct10
Distinct (%)66.7%
Missing10
Missing (%)40.0%
Memory size332.0 B
2024-03-14T11:49:48.894593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.7333333
Min length1

Characters and Unicode

Total characters26
Distinct characters16
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

Unique7 ?
Unique (%)46.7%

Sample

1st row11월
2nd row개체수(마리)
3rd row16
4th row3
5th row2
ValueCountFrequency (%)
3 3
20.0%
1 3
20.0%
2 2
13.3%
11월 1
 
6.7%
개체수(마리 1
 
6.7%
16 1
 
6.7%
28 1
 
6.7%
4 1
 
6.7%
5 1
 
6.7%
69 1
 
6.7%
2024-03-14T11:49:49.119680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 6
23.1%
3 3
11.5%
2 3
11.5%
6 2
 
7.7%
월 1
 
3.8%
개 1
 
3.8%
체 1
 
3.8%
수 1
 
3.8%
( 1
 
3.8%
마 1
 
3.8%
Other values (6) 6
23.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18
69.2%
Other Letter 6
 
23.1%
Open Punctuation 1
 
3.8%
Close Punctuation 1
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6
33.3%
3 3
16.7%
2 3
16.7%
6 2
 
11.1%
8 1
 
5.6%
4 1
 
5.6%
5 1
 
5.6%
9 1
 
5.6%
Other Letter
ValueCountFrequency (%)
월 1
16.7%
개 1
16.7%
체 1
16.7%
수 1
16.7%
마 1
16.7%
리 1
16.7%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 20
76.9%
Hangul 6
 
23.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 6
30.0%
3 3
15.0%
2 3
15.0%
6 2
 
10.0%
( 1
 
5.0%
) 1
 
5.0%
8 1
 
5.0%
4 1
 
5.0%
5 1
 
5.0%
9 1
 
5.0%
Hangul
ValueCountFrequency (%)
월 1
16.7%
개 1
16.7%
체 1
16.7%
수 1
16.7%
마 1
16.7%
리 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20
76.9%
Hangul 6
 
23.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 6
30.0%
3 3
15.0%
2 3
15.0%
6 2
 
10.0%
( 1
 
5.0%
) 1
 
5.0%
8 1
 
5.0%
4 1
 
5.0%
5 1
 
5.0%
9 1
 
5.0%
Hangul
ValueCountFrequency (%)
월 1
16.7%
개 1
16.7%
체 1
16.7%
수 1
16.7%
마 1
16.7%
리 1
16.7%

Unnamed: 10
Text

MISSING 

Distinct11
Distinct (%)78.6%
Missing11
Missing (%)44.0%
Memory size332.0 B
2024-03-14T11:49:49.344786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.3571429
Min length3

Characters and Unicode

Total characters47
Distinct characters15
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)57.1%

Sample

1st row현존량(㎏)
2nd row4.5
3rd row0.1
4th row0.3
5th row1.8
ValueCountFrequency (%)
0.1 2
14.3%
0.3 2
14.3%
0.8 2
14.3%
현존량(㎏ 1
7.1%
4.5 1
7.1%
1.8 1
7.1%
36.5 1
7.1%
1.4 1
7.1%
1.3 1
7.1%
0.2 1
7.1%
2024-03-14T11:49:49.604737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 13
27.7%
0 7
14.9%
1 6
12.8%
3 4
 
8.5%
8 4
 
8.5%
4 3
 
6.4%
5 2
 
4.3%
현 1
 
2.1%
존 1
 
2.1%
량 1
 
2.1%
Other values (5) 5
 
10.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 28
59.6%
Other Punctuation 13
27.7%
Other Letter 3
 
6.4%
Open Punctuation 1
 
2.1%
Other Symbol 1
 
2.1%
Close Punctuation 1
 
2.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7
25.0%
1 6
21.4%
3 4
14.3%
8 4
14.3%
4 3
10.7%
5 2
 
7.1%
6 1
 
3.6%
2 1
 
3.6%
Other Letter
ValueCountFrequency (%)
현 1
33.3%
존 1
33.3%
량 1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Other Symbol
ValueCountFrequency (%)
㎏ 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 44
93.6%
Hangul 3
 
6.4%

Most frequent character per script

Common
ValueCountFrequency (%)
. 13
29.5%
0 7
15.9%
1 6
13.6%
3 4
 
9.1%
8 4
 
9.1%
4 3
 
6.8%
5 2
 
4.5%
( 1
 
2.3%
㎏ 1
 
2.3%
) 1
 
2.3%
Other values (2) 2
 
4.5%
Hangul
ValueCountFrequency (%)
현 1
33.3%
존 1
33.3%
량 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 43
91.5%
Hangul 3
 
6.4%
CJK Compat 1
 
2.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 13
30.2%
0 7
16.3%
1 6
14.0%
3 4
 
9.3%
8 4
 
9.3%
4 3
 
7.0%
5 2
 
4.7%
( 1
 
2.3%
) 1
 
2.3%
6 1
 
2.3%
Hangul
ValueCountFrequency (%)
현 1
33.3%
존 1
33.3%
량 1
33.3%
CJK Compat
ValueCountFrequency (%)
㎏ 1
100.0%

Unnamed: 11
Text

Distinct16
Distinct (%)64.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2024-03-14T11:49:49.736338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length1.8
Min length1

Characters and Unicode

Total characters45
Distinct characters18
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

Unique11 ?
Unique (%)44.0%

Sample

1st row합계
2nd row개체수(마리)
3rd row24
4th row4
5th row4
ValueCountFrequency (%)
4 4
16.0%
1 4
16.0%
2 2
 
8.0%
28 2
 
8.0%
17 2
 
8.0%
합계 1
 
4.0%
개체수(마리 1
 
4.0%
24 1
 
4.0%
5 1
 
4.0%
10 1
 
4.0%
Other values (6) 6
24.0%
2024-03-14T11:49:49.951952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 9
20.0%
2 7
15.6%
4 6
13.3%
3 5
11.1%
8 3
 
6.7%
7 2
 
4.4%
5 2
 
4.4%
마 1
 
2.2%
0 1
 
2.2%
) 1
 
2.2%
Other values (8) 8
17.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 36
80.0%
Other Letter 7
 
15.6%
Close Punctuation 1
 
2.2%
Open Punctuation 1
 
2.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 9
25.0%
2 7
19.4%
4 6
16.7%
3 5
13.9%
8 3
 
8.3%
7 2
 
5.6%
5 2
 
5.6%
0 1
 
2.8%
9 1
 
2.8%
Other Letter
ValueCountFrequency (%)
마 1
14.3%
리 1
14.3%
수 1
14.3%
체 1
14.3%
개 1
14.3%
계 1
14.3%
합 1
14.3%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 38
84.4%
Hangul 7
 
15.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 9
23.7%
2 7
18.4%
4 6
15.8%
3 5
13.2%
8 3
 
7.9%
7 2
 
5.3%
5 2
 
5.3%
0 1
 
2.6%
) 1
 
2.6%
( 1
 
2.6%
Hangul
ValueCountFrequency (%)
마 1
14.3%
리 1
14.3%
수 1
14.3%
체 1
14.3%
개 1
14.3%
계 1
14.3%
합 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38
84.4%
Hangul 7
 
15.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 9
23.7%
2 7
18.4%
4 6
15.8%
3 5
13.2%
8 3
 
7.9%
7 2
 
5.3%
5 2
 
5.3%
0 1
 
2.6%
) 1
 
2.6%
( 1
 
2.6%
Hangul
ValueCountFrequency (%)
마 1
14.3%
리 1
14.3%
수 1
14.3%
체 1
14.3%
개 1
14.3%
계 1
14.3%
합 1
14.3%

Unnamed: 12
Text

MISSING 

Distinct24
Distinct (%)100.0%
Missing1
Missing (%)4.0%
Memory size332.0 B
2024-03-14T11:49:50.108455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.0416667
Min length3

Characters and Unicode

Total characters97
Distinct characters16
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st row현존량(㎏)
2nd row5.52
3rd row0.11
4th row1.32
5th row0.51
ValueCountFrequency (%)
현존량(㎏ 1
 
4.2%
5.52 1
 
4.2%
4.02 1
 
4.2%
5.86 1
 
4.2%
0.61 1
 
4.2%
2.81 1
 
4.2%
10.14 1
 
4.2%
0.03 1
 
4.2%
1.3 1
 
4.2%
0.17 1
 
4.2%
Other values (14) 14
58.3%
2024-03-14T11:49:50.372973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 23
23.7%
0 15
15.5%
1 13
13.4%
2 11
11.3%
5 7
 
7.2%
3 6
 
6.2%
4 5
 
5.2%
8 5
 
5.2%
6 4
 
4.1%
7 2
 
2.1%
Other values (6) 6
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68
70.1%
Other Punctuation 23
 
23.7%
Other Letter 3
 
3.1%
Open Punctuation 1
 
1.0%
Other Symbol 1
 
1.0%
Close Punctuation 1
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15
22.1%
1 13
19.1%
2 11
16.2%
5 7
10.3%
3 6
 
8.8%
4 5
 
7.4%
8 5
 
7.4%
6 4
 
5.9%
7 2
 
2.9%
Other Letter
ValueCountFrequency (%)
현 1
33.3%
존 1
33.3%
량 1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Other Symbol
ValueCountFrequency (%)
㎏ 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 94
96.9%
Hangul 3
 
3.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 23
24.5%
0 15
16.0%
1 13
13.8%
2 11
11.7%
5 7
 
7.4%
3 6
 
6.4%
4 5
 
5.3%
8 5
 
5.3%
6 4
 
4.3%
7 2
 
2.1%
Other values (3) 3
 
3.2%
Hangul
ValueCountFrequency (%)
현 1
33.3%
존 1
33.3%
량 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 93
95.9%
Hangul 3
 
3.1%
CJK Compat 1
 
1.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 23
24.7%
0 15
16.1%
1 13
14.0%
2 11
11.8%
5 7
 
7.5%
3 6
 
6.5%
4 5
 
5.4%
8 5
 
5.4%
6 4
 
4.3%
7 2
 
2.2%
Other values (2) 2
 
2.2%
Hangul
ValueCountFrequency (%)
현 1
33.3%
존 1
33.3%
량 1
33.3%
CJK Compat
ValueCountFrequency (%)
㎏ 1
100.0%

Correlations

2024-03-14T11:49:50.455306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
군산해역에서 어획된 품종별 개체수 및 현존량(2014년)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12
군산해역에서 어획된 품종별 개체수 및 현존량(2014년)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 11.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 21.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 31.0001.0001.0001.0001.0000.8491.0001.0001.0000.7511.0000.7891.000
Unnamed: 41.0001.0001.0001.0001.0000.6381.0001.0001.0000.8971.0000.8321.000
Unnamed: 51.0001.0001.0000.8490.6381.0001.0000.9431.0000.7700.8791.0001.000
Unnamed: 61.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 71.0001.0001.0001.0001.0000.9431.0001.0001.0000.9110.8770.9831.000
Unnamed: 81.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 91.0001.0001.0000.7510.8970.7701.0000.9111.0001.0000.8550.9031.000
Unnamed: 101.0001.0001.0001.0001.0000.8791.0000.8771.0000.8551.0000.9131.000
Unnamed: 111.0001.0001.0000.7890.8321.0001.0000.9831.0000.9030.9131.0001.000
Unnamed: 121.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000

Missing values

2024-03-14T11:49:45.035901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:49:45.178786image/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.
2024-03-14T11:49:45.335749image/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

군산해역에서 어획된 품종별 개체수 및 현존량(2014년)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12
0일자3월<NA>5월<NA>7월<NA>9월<NA>11월<NA>합계<NA>
1구분개체수(마리)현존량(㎏)개체수(마리)현존량(㎏)개체수(마리)현존량(㎏)개체수(마리)현존량(㎏)개체수(마리)현존량(㎏)개체수(마리)현존량(㎏)
2조피볼락(Sebastes schlegelii)<NA><NA><NA><NA><NA><NA>81.02164.5245.52
3황해볼락(Sebastes koreanus)<NA><NA>10.01<NA><NA><NA><NA>30.140.11
4삼세기(Hemitripterus villosus)41.32<NA><NA><NA><NA><NA><NA><NA><NA>41.32
5노래미(Hexagrammos agrammus)10.1410.0210.05<NA><NA>20.350.51
6넙치(Paralichthys olivadeus)<NA><NA><NA><NA><NA><NA>10.4511.822.25
7문치가자미(Pleuronectes yokohamae)40.95<NA><NA>21.210.1830.8103.13
8별넙치(Pseudorhombus cinnamoneus)<NA><NA><NA><NA><NA><NA>20.24<NA><NA>20.24
9점넙치(Pseudorhombus pentophthalmus)<NA><NA><NA><NA><NA><NA>10.1<NA><NA>10.1
군산해역에서 어획된 품종별 개체수 및 현존량(2014년)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12
15삼치(Scomberomorus niphomius)<NA><NA><NA><NA><NA><NA>10.2<NA><NA>10.2
16참돔(Pagrus major)<NA><NA><NA><NA><NA><NA>40.17<NA><NA>40.17
17꼼치(Liparis tanakae)<NA><NA><NA><NA><NA><NA><NA><NA>41.341.3
18멸치(Engraulis japonicus)<NA><NA>10.01<NA><NA>300.02<NA><NA>310.03
19꽃게(Portunus trituberculatus)10.04<NA><NA>347.991.910.34510.14
20민꽃게(Charybdis japonica)<NA><NA>10.1130.8141.1150.8332.81
21갯가재(Oratosquilla oratoria)<NA><NA>10.01130.4520.0510.1170.61
22참갑오징어(Sepia esculenta)<NA><NA>41.46134.4<NA><NA><NA><NA>175.86
23피뿔고둥(Rapana venosa)10.150.74112.240.7820.2234.02
24합계112.55162.399217.81119.86948.129880.64