Overview

Dataset statistics

Number of variables13
Number of observations21
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.3 KiB
Average record size in memory112.3 B

Variable types

Numeric2
Categorical5
Text5
DateTime1

Alerts

공개여부 has constant value ""Constant
작성일 has constant value ""Constant
갱신주기 has constant value ""Constant
순번 is highly overall correlated with 수면적 and 2 other fieldsHigh correlation
수면적 is highly overall correlated with 순번High correlation
시군명 is highly overall correlated with 순번 and 2 other fieldsHigh correlation
비고 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
자료출처 is highly overall correlated with 시군명High correlation
자료출처 is highly imbalanced (54.6%)Imbalance
순번 has unique valuesUnique
낚시터명 has unique valuesUnique
소유자 has unique valuesUnique
도로명주소 has unique valuesUnique
지번주소 has unique valuesUnique

Reproduction

Analysis started2024-03-14 01:56:33.009730
Analysis finished2024-03-14 01:56:33.974622
Duration0.96 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11
Minimum1
Maximum21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-03-14T10:56:34.027131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q16
median11
Q316
95-th percentile20
Maximum21
Range20
Interquartile range (IQR)10

Descriptive statistics

Standard deviation6.2048368
Coefficient of variation (CV)0.56407607
Kurtosis-1.2
Mean11
Median Absolute Deviation (MAD)5
Skewness0
Sum231
Variance38.5
MonotonicityStrictly increasing
2024-03-14T10:56:34.136840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1 1
 
4.8%
2 1
 
4.8%
21 1
 
4.8%
20 1
 
4.8%
19 1
 
4.8%
18 1
 
4.8%
17 1
 
4.8%
16 1
 
4.8%
15 1
 
4.8%
14 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
1 1
4.8%
2 1
4.8%
3 1
4.8%
4 1
4.8%
5 1
4.8%
6 1
4.8%
7 1
4.8%
8 1
4.8%
9 1
4.8%
10 1
4.8%
ValueCountFrequency (%)
21 1
4.8%
20 1
4.8%
19 1
4.8%
18 1
4.8%
17 1
4.8%
16 1
4.8%
15 1
4.8%
14 1
4.8%
13 1
4.8%
12 1
4.8%

시군명
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)42.9%
Missing0
Missing (%)0.0%
Memory size300.0 B
익산시
6 
완주군
3 
정읍시
2 
남원시
2 
김제시
2 
Other values (4)
6 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique2 ?
Unique (%)9.5%

Sample

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

Common Values

ValueCountFrequency (%)
익산시 6
28.6%
완주군 3
14.3%
정읍시 2
 
9.5%
남원시 2
 
9.5%
김제시 2
 
9.5%
진안군 2
 
9.5%
임실군 2
 
9.5%
고창군 1
 
4.8%
부안군 1
 
4.8%

Length

2024-03-14T10:56:34.246074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:56:34.352752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
익산시 6
28.6%
완주군 3
14.3%
정읍시 2
 
9.5%
남원시 2
 
9.5%
김제시 2
 
9.5%
진안군 2
 
9.5%
임실군 2
 
9.5%
고창군 1
 
4.8%
부안군 1
 
4.8%

낚시터명
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2024-03-14T10:56:34.533534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length2
Mean length2.5238095
Min length2

Characters and Unicode

Total characters53
Distinct characters42
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row개울
2nd row왕궁
3rd row두모
4th row사결
5th row팔봉
ValueCountFrequency (%)
개울 1
 
4.3%
화정 1
 
4.3%
수동 1
 
4.3%
사람들 1
 
4.3%
닮은 1
 
4.3%
자연을 1
 
4.3%
호암 1
 
4.3%
백화리 1
 
4.3%
대성 1
 
4.3%
우리 1
 
4.3%
Other values (13) 13
56.5%
2024-03-14T10:56:34.814294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
성 3
 
5.7%
정 3
 
5.7%
우 2
 
3.8%
화 2
 
3.8%
백 2
 
3.8%
송 2
 
3.8%
2
 
3.8%
리 2
 
3.8%
사 2
 
3.8%
들 1
 
1.9%
Other values (32) 32
60.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 51
96.2%
Space Separator 2
 
3.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
성 3
 
5.9%
정 3
 
5.9%
우 2
 
3.9%
화 2
 
3.9%
백 2
 
3.9%
송 2
 
3.9%
리 2
 
3.9%
사 2
 
3.9%
들 1
 
2.0%
을 1
 
2.0%
Other values (31) 31
60.8%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 51
96.2%
Common 2
 
3.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
성 3
 
5.9%
정 3
 
5.9%
우 2
 
3.9%
화 2
 
3.9%
백 2
 
3.9%
송 2
 
3.9%
리 2
 
3.9%
사 2
 
3.9%
들 1
 
2.0%
을 1
 
2.0%
Other values (31) 31
60.8%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 51
96.2%
ASCII 2
 
3.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
성 3
 
5.9%
정 3
 
5.9%
우 2
 
3.9%
화 2
 
3.9%
백 2
 
3.9%
송 2
 
3.9%
리 2
 
3.9%
사 2
 
3.9%
들 1
 
2.0%
을 1
 
2.0%
Other values (31) 31
60.8%
ASCII
ValueCountFrequency (%)
2
100.0%

소유자
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2024-03-14T10:56:34.966931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length3
Mean length4
Min length2

Characters and Unicode

Total characters84
Distinct characters57
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

Unique21 ?
Unique (%)100.0%

Sample

1st row이정복
2nd row김영표
3rd row박근수
4th row박 수
5th row김중만
ValueCountFrequency (%)
이정복 1
 
4.5%
김영표 1
 
4.5%
한국농어촌공사(안인철 1
 
4.5%
한옥자 1
 
4.5%
진한 1
 
4.5%
진안군수(고애순 1
 
4.5%
김기택 1
 
4.5%
박은희 1
 
4.5%
송병전 1
 
4.5%
양화어업계농어촌공사 1
 
4.5%
Other values (12) 12
54.5%
2024-03-14T10:56:35.240085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 5
 
6.0%
영 3
 
3.6%
박 3
 
3.6%
어 3
 
3.6%
수 3
 
3.6%
한 3
 
3.6%
이 2
 
2.4%
촌 2
 
2.4%
공 2
 
2.4%
사 2
 
2.4%
Other values (47) 56
66.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 79
94.0%
Open Punctuation 2
 
2.4%
Close Punctuation 2
 
2.4%
Space Separator 1
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 5
 
6.3%
영 3
 
3.8%
박 3
 
3.8%
어 3
 
3.8%
수 3
 
3.8%
한 3
 
3.8%
이 2
 
2.5%
촌 2
 
2.5%
공 2
 
2.5%
사 2
 
2.5%
Other values (44) 51
64.6%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 79
94.0%
Common 5
 
6.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 5
 
6.3%
영 3
 
3.8%
박 3
 
3.8%
어 3
 
3.8%
수 3
 
3.8%
한 3
 
3.8%
이 2
 
2.5%
촌 2
 
2.5%
공 2
 
2.5%
사 2
 
2.5%
Other values (44) 51
64.6%
Common
ValueCountFrequency (%)
( 2
40.0%
) 2
40.0%
1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 79
94.0%
ASCII 5
 
6.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 5
 
6.3%
영 3
 
3.8%
박 3
 
3.8%
어 3
 
3.8%
수 3
 
3.8%
한 3
 
3.8%
이 2
 
2.5%
촌 2
 
2.5%
공 2
 
2.5%
사 2
 
2.5%
Other values (44) 51
64.6%
ASCII
ValueCountFrequency (%)
( 2
40.0%
) 2
40.0%
1
20.0%

도로명주소
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2024-03-14T10:56:35.473837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length25
Mean length21.571429
Min length15

Characters and Unicode

Total characters453
Distinct characters82
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

Unique21 ?
Unique (%)100.0%

Sample

1st row전라북도 익산시 왕궁면 화곡1길27-16
2nd row전라북도 익산시 왕궁면 호반로231-23
3rd row전라북도 익산시 망성면 두무길 90
4th row전라북도 익산시 용동면 대조리 178-46
5th row전라북도 익산시 춘포면 갈전길 67-26
ValueCountFrequency (%)
전라북도 20
 
19.8%
익산시 6
 
5.9%
진안군 3
 
3.0%
고산면 3
 
3.0%
완주군 3
 
3.0%
정읍시 2
 
2.0%
왕궁면 2
 
2.0%
김제시 2
 
2.0%
임실군 2
 
2.0%
남원시 2
 
2.0%
Other values (56) 56
55.4%
2024-03-14T10:56:35.798271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
80
 
17.7%
전 22
 
4.9%
북 22
 
4.9%
라 20
 
4.4%
도 20
 
4.4%
면 17
 
3.8%
1 15
 
3.3%
- 15
 
3.3%
산 12
 
2.6%
시 12
 
2.6%
Other values (72) 218
48.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 275
60.7%
Decimal Number 83
 
18.3%
Space Separator 80
 
17.7%
Dash Punctuation 15
 
3.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 22
 
8.0%
북 22
 
8.0%
라 20
 
7.3%
도 20
 
7.3%
면 17
 
6.2%
산 12
 
4.4%
시 12
 
4.4%
군 10
 
3.6%
길 10
 
3.6%
로 8
 
2.9%
Other values (60) 122
44.4%
Decimal Number
ValueCountFrequency (%)
1 15
18.1%
6 12
14.5%
2 10
12.0%
3 9
10.8%
7 8
9.6%
0 7
8.4%
4 6
 
7.2%
5 6
 
7.2%
8 5
 
6.0%
9 5
 
6.0%
Space Separator
ValueCountFrequency (%)
80
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 275
60.7%
Common 178
39.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 22
 
8.0%
북 22
 
8.0%
라 20
 
7.3%
도 20
 
7.3%
면 17
 
6.2%
산 12
 
4.4%
시 12
 
4.4%
군 10
 
3.6%
길 10
 
3.6%
로 8
 
2.9%
Other values (60) 122
44.4%
Common
ValueCountFrequency (%)
80
44.9%
1 15
 
8.4%
- 15
 
8.4%
6 12
 
6.7%
2 10
 
5.6%
3 9
 
5.1%
7 8
 
4.5%
0 7
 
3.9%
4 6
 
3.4%
5 6
 
3.4%
Other values (2) 10
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 275
60.7%
ASCII 178
39.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
80
44.9%
1 15
 
8.4%
- 15
 
8.4%
6 12
 
6.7%
2 10
 
5.6%
3 9
 
5.1%
7 8
 
4.5%
0 7
 
3.9%
4 6
 
3.4%
5 6
 
3.4%
Other values (2) 10
 
5.6%
Hangul
ValueCountFrequency (%)
전 22
 
8.0%
북 22
 
8.0%
라 20
 
7.3%
도 20
 
7.3%
면 17
 
6.2%
산 12
 
4.4%
시 12
 
4.4%
군 10
 
3.6%
길 10
 
3.6%
로 8
 
2.9%
Other values (60) 122
44.4%

지번주소
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2024-03-14T10:56:36.002628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length11.952381
Min length8

Characters and Unicode

Total characters251
Distinct characters59
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

Unique21 ?
Unique (%)100.0%

Sample

1st row왕궁면 용화리274-1
2nd row왕궁면 동봉리 592-8
3rd row망성면 화산리 381-5
4th row용동면 대조리 178-46
5th row춘포면 청평리 555
ValueCountFrequency (%)
고산면 3
 
5.1%
왕궁면 2
 
3.4%
용화리274-1 1
 
1.7%
봉의리 1
 
1.7%
3번지 1
 
1.7%
상동동 1
 
1.7%
87-3 1
 
1.7%
화정리 1
 
1.7%
405 1
 
1.7%
남봉리470-12 1
 
1.7%
Other values (46) 46
78.0%
2024-03-14T10:56:36.590775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
38
 
15.1%
리 19
 
7.6%
면 17
 
6.8%
1 16
 
6.4%
- 13
 
5.2%
7 10
 
4.0%
4 9
 
3.6%
5 9
 
3.6%
2 8
 
3.2%
동 7
 
2.8%
Other values (49) 105
41.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 124
49.4%
Decimal Number 76
30.3%
Space Separator 38
 
15.1%
Dash Punctuation 13
 
5.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 19
 
15.3%
면 17
 
13.7%
동 7
 
5.6%
산 7
 
5.6%
지 5
 
4.0%
성 4
 
3.2%
천 4
 
3.2%
번 4
 
3.2%
화 4
 
3.2%
용 4
 
3.2%
Other values (37) 49
39.5%
Decimal Number
ValueCountFrequency (%)
1 16
21.1%
7 10
13.2%
4 9
11.8%
5 9
11.8%
2 8
10.5%
6 6
 
7.9%
3 6
 
7.9%
8 6
 
7.9%
0 4
 
5.3%
9 2
 
2.6%
Space Separator
ValueCountFrequency (%)
38
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 127
50.6%
Hangul 124
49.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 19
 
15.3%
면 17
 
13.7%
동 7
 
5.6%
산 7
 
5.6%
지 5
 
4.0%
성 4
 
3.2%
천 4
 
3.2%
번 4
 
3.2%
화 4
 
3.2%
용 4
 
3.2%
Other values (37) 49
39.5%
Common
ValueCountFrequency (%)
38
29.9%
1 16
12.6%
- 13
 
10.2%
7 10
 
7.9%
4 9
 
7.1%
5 9
 
7.1%
2 8
 
6.3%
6 6
 
4.7%
3 6
 
4.7%
8 6
 
4.7%
Other values (2) 6
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 127
50.6%
Hangul 124
49.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
38
29.9%
1 16
12.6%
- 13
 
10.2%
7 10
 
7.9%
4 9
 
7.1%
5 9
 
7.1%
2 8
 
6.3%
6 6
 
4.7%
3 6
 
4.7%
8 6
 
4.7%
Other values (2) 6
 
4.7%
Hangul
ValueCountFrequency (%)
리 19
 
15.3%
면 17
 
13.7%
동 7
 
5.6%
산 7
 
5.6%
지 5
 
4.0%
성 4
 
3.2%
천 4
 
3.2%
번 4
 
3.2%
화 4
 
3.2%
용 4
 
3.2%
Other values (37) 49
39.5%

수면적
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2356.4087
Minimum0.0903
Maximum33901
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-03-14T10:56:36.699525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.0903
5-th percentile0.1
Q10.13
median0.3031
Q34.7
95-th percentile12550
Maximum33901
Range33900.91
Interquartile range (IQR)4.57

Descriptive statistics

Standard deviation7743.2835
Coefficient of variation (CV)3.2860528
Kurtosis15.307564
Mean2356.4087
Median Absolute Deviation (MAD)0.2031
Skewness3.8343861
Sum49484.582
Variance59958439
MonotonicityNot monotonic
2024-03-14T10:56:36.799441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0.2 2
 
9.5%
0.12 2
 
9.5%
0.1 2
 
9.5%
0.0903 1
 
4.8%
33901.0 1
 
4.8%
4.7 1
 
4.8%
17.2 1
 
4.8%
0.48 1
 
4.8%
1.0 1
 
4.8%
2999.0 1
 
4.8%
Other values (8) 8
38.1%
ValueCountFrequency (%)
0.0903 1
4.8%
0.1 2
9.5%
0.12 2
9.5%
0.13 1
4.8%
0.14 1
4.8%
0.2 2
9.5%
0.3 1
4.8%
0.3031 1
4.8%
0.399 1
4.8%
0.48 1
4.8%
ValueCountFrequency (%)
33901.0 1
4.8%
12550.0 1
4.8%
2999.0 1
4.8%
17.2 1
4.8%
7.0 1
4.8%
4.7 1
4.8%
2.0 1
4.8%
1.0 1
4.8%
0.48 1
4.8%
0.399 1
4.8%

유효기간
Text

Distinct20
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Memory size300.0 B
2024-03-14T10:56:36.946745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length19.952381
Min length18

Characters and Unicode

Total characters419
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)90.5%

Sample

1st row2013.06.19~2018.04.10
2nd row2013.06.19~2018.06.18
3rd row2015.03.11~2020.0310
4th row2013.02.05~2018.02.04
5th row2016.01.27~2026.02.26
ValueCountFrequency (%)
2015.1.11~2025.1.10 2
 
9.5%
2013.06.19~2018.04.10 1
 
4.8%
2015.5.8~2020.4.30 1
 
4.8%
2015.7.1~2016.9.30 1
 
4.8%
2015.03.16.~2025.03.15 1
 
4.8%
2014.11.18.~2021.11.17 1
 
4.8%
2013.2.18~2018.2.17 1
 
4.8%
2012.4.24.~2017.4.23 1
 
4.8%
2014.9.22~2024.9.21 1
 
4.8%
2015.9.10~2025.1.20 1
 
4.8%
Other values (10) 10
47.6%
2024-03-14T10:56:37.197517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 89
21.2%
1 74
17.7%
2 72
17.2%
0 70
16.7%
~ 21
 
5.0%
3 18
 
4.3%
5 17
 
4.1%
4 15
 
3.6%
6 13
 
3.1%
7 11
 
2.6%
Other values (3) 19
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 307
73.3%
Other Punctuation 89
 
21.2%
Math Symbol 21
 
5.0%
Space Separator 2
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 74
24.1%
2 72
23.5%
0 70
22.8%
3 18
 
5.9%
5 17
 
5.5%
4 15
 
4.9%
6 13
 
4.2%
7 11
 
3.6%
8 9
 
2.9%
9 8
 
2.6%
Other Punctuation
ValueCountFrequency (%)
. 89
100.0%
Math Symbol
ValueCountFrequency (%)
~ 21
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 419
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 89
21.2%
1 74
17.7%
2 72
17.2%
0 70
16.7%
~ 21
 
5.0%
3 18
 
4.3%
5 17
 
4.1%
4 15
 
3.6%
6 13
 
3.1%
7 11
 
2.6%
Other values (3) 19
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 419
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 89
21.2%
1 74
17.7%
2 72
17.2%
0 70
16.7%
~ 21
 
5.0%
3 18
 
4.3%
5 17
 
4.1%
4 15
 
3.6%
6 13
 
3.1%
7 11
 
2.6%
Other values (3) 19
 
4.5%

비고
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
등록
17 
허가
4 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
등록 17
81.0%
허가 4
 
19.0%

Length

2024-03-14T10:56:37.309994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:56:37.408854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
등록 17
81.0%
허가 4
 
19.0%

자료출처
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
해양수산과
19 
해양수산과
2 

Length

Max length6
Median length5
Mean length5.0952381
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
해양수산과 19
90.5%
해양수산과 2
 
9.5%

Length

2024-03-14T10:56:37.538754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:56:37.660250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해양수산과 21
100.0%

공개여부
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
공개
21 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공개 21
100.0%

Length

2024-03-14T10:56:37.742134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:56:37.817674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공개 21
100.0%

작성일
Date

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
Minimum2016-04-20 00:00:00
Maximum2016-04-20 00:00:00
2024-03-14T10:56:37.878508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:56:37.962245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

갱신주기
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
1년
21 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1년
2nd row1년
3rd row1년
4th row1년
5th row1년

Common Values

ValueCountFrequency (%)
1년 21
100.0%

Length

2024-03-14T10:56:38.062414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:56:38.144394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1년 21
100.0%

Interactions

2024-03-14T10:56:33.576125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:56:33.429888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:56:33.654542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:56:33.505730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T10:56:38.216367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시군명낚시터명소유자도로명주소지번주소수면적유효기간비고자료출처
순번1.0000.8801.0001.0001.0001.0000.5071.0000.4101.000
시군명0.8801.0001.0001.0001.0001.0000.0001.0000.6401.000
낚시터명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소유자1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
지번주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
수면적0.5070.0001.0001.0001.0001.0001.0001.0000.2270.000
유효기간1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
비고0.4100.6401.0001.0001.0001.0000.2271.0001.0000.000
자료출처1.0001.0001.0001.0001.0001.0000.0001.0000.0001.000
2024-03-14T10:56:38.331154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명비고자료출처
시군명1.0000.5020.795
비고0.5021.0000.000
자료출처0.7950.0001.000
2024-03-14T10:56:38.424799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번수면적시군명비고자료출처
순번1.0000.6180.5860.5040.000
수면적0.6181.0000.0000.3550.000
시군명0.5860.0001.0000.5020.795
비고0.5040.3550.5021.0000.000
자료출처0.0000.0000.7950.0001.000

Missing values

2024-03-14T10:56:33.780374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T10:56:33.920446image/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

순번시군명낚시터명소유자도로명주소지번주소수면적유효기간비고자료출처공개여부작성일갱신주기
01익산시개울이정복전라북도 익산시 왕궁면 화곡1길27-16왕궁면 용화리274-10.09032013.06.19~2018.04.10등록해양수산과공개2016.4.201년
12익산시왕궁김영표전라북도 익산시 왕궁면 호반로231-23왕궁면 동봉리 592-80.12013.06.19~2018.06.18등록해양수산과공개2016.4.201년
23익산시두모박근수전라북도 익산시 망성면 두무길 90망성면 화산리 381-50.132015.03.11~2020.0310등록해양수산과공개2016.4.201년
34익산시사결박 수전라북도 익산시 용동면 대조리 178-46용동면 대조리 178-460.22013.02.05~2018.02.04등록해양수산과공개2016.4.201년
45익산시팔봉김중만전라북도 익산시 춘포면 갈전길 67-26춘포면 청평리 5550.12016.01.27~2026.02.26등록해양수산과공개2016.4.201년
56익산시태성최암전라북도 익산시 여산면 태성길 460-50여산면 태성리 17번지0.32012.07.10~2017.07.09등록해양수산과공개2016.4.201년
67정읍시우정강영원전라북도 정읍시 소성면 소성상평로 238소성면 주천리 636번지0.30312011.6.15~2016.6.14등록해양수산과공개2016.4.201년
78정읍시국제하재완전라북도 정읍시 옹동면 오성리 정읍북로 1634-17옹동면 오성리 12730.3992012.4.23~2017.4.22등록해양수산과공개2016.4.201년
89남원시송치김형춘전라북도 남원시 주천면 웅치길 20주천면 송치리 2290.142015.1.11~2025.1.10등록해양수산과공개2016.4.201년
910남원시식정임건택전라북도 남원시 요천로 1975-9식정동 444-1번지 외 10.122015.1.11~2025.1.10등록해양수산과공개2016.4.201년
순번시군명낚시터명소유자도로명주소지번주소수면적유효기간비고자료출처공개여부작성일갱신주기
1112김제시신성김현순전라북도 김제시 모리생길 58-197상동동 87-37.02013.5.14~2017.5.4등록해양수산과공개2016.4.201년
1213완주군화정양화어업계농어촌공사전라북도 완주군 고산면 양화로 54-14고산면 화정리 40533901.02015.5.8~2020.4.30허가해양수산과공개2016.4.201년
1314완주군송현송병전전북 완주군 고산면 남봉로 5-106고산면 남봉리470-1212550.02015.9.10~2025.1.20등록해양수산과공개2016.4.201년
1415완주군우리박은희전라북도 완주군 고산면 양야신풍길 98고산면 양야리 5072999.02014.9.22~2024.9.21등록해양수산과공개2016.4.201년
1516진안군대성김기택전라북도 진안군 진안읍 오천리 산 48오천리111-10.22012.4.24.~2017.4.23.등록해양수산과공개2016.4.201년
1617진안군백화리진안군수(고애순)전라북도 진안군 진안군 안천면 진무로 3206안천면 백화리 342-81.02013.2.18~2018.2.17허가해양수산과공개2016.4.201년
1718임실군호암진한전라북도 임실군 신평면 호암3길 1-20신평면 호암리 174-10.122014.11.18.~2021.11.17.등록해양수산과공개2016.4.201년
1819임실군자연을 닮은 사람들한옥자전라북도 임실군 관촌면 용산리 176-6관촌면 용산리 176-60.482015.03.16.~2025.03.15.등록해양수산과공개2016.4.201년
1920고창군수동한국농어촌공사(안인철)전라북도 고창군 기동길2-7수동리 602-817.22015.7.1~2016.9.30허가해양수산과공개2016.4.201년
2021부안군곰소마린황이인주전라북도 부안군 보안면 신복길132-36보안면 신복리 산 75-514.72012.6.19~2017.6.18허가해양수산과공개2016.4.201년