Overview

Dataset statistics

Number of variables4
Number of observations111
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 KiB
Average record size in memory34.2 B

Variable types

Numeric1
Categorical2
Text1

Dataset

Description사용자는 해양산부에서 제공하는 전남제주 공동해역 데이터를 파일(csv)형식으로 사용 및 활용 할 수 있으며 공간정보를 포함한 정보를 간략하게 제공합니다.
URLhttps://www.data.go.kr/data/15112989/fileData.do

Alerts

레이어분류내용(lyr_cl_cn) has constant value ""Constant
레이어명(lyr_nm) is highly imbalanced (92.6%)Imbalance
일련번호(gid) has unique valuesUnique
공간정보(geom) has unique valuesUnique

Reproduction

Analysis started2023-12-12 23:43:49.175859
Analysis finished2023-12-12 23:43:49.467233
Duration0.29 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일련번호(gid)
Real number (ℝ)

UNIQUE 

Distinct111
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean56
Minimum1
Maximum111
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T08:43:49.531794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.5
Q128.5
median56
Q383.5
95-th percentile105.5
Maximum111
Range110
Interquartile range (IQR)55

Descriptive statistics

Standard deviation32.186954
Coefficient of variation (CV)0.57476703
Kurtosis-1.2
Mean56
Median Absolute Deviation (MAD)28
Skewness0
Sum6216
Variance1036
MonotonicityStrictly increasing
2023-12-13T08:43:49.649360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
2 1
 
0.9%
83 1
 
0.9%
82 1
 
0.9%
81 1
 
0.9%
80 1
 
0.9%
79 1
 
0.9%
78 1
 
0.9%
77 1
 
0.9%
76 1
 
0.9%
Other values (101) 101
91.0%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
111 1
0.9%
110 1
0.9%
109 1
0.9%
108 1
0.9%
107 1
0.9%
106 1
0.9%
105 1
0.9%
104 1
0.9%
103 1
0.9%
102 1
0.9%

레이어명(lyr_nm)
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1020.0 B
전남제주공동해역
110 
 
1

Length

Max length8
Median length8
Mean length7.9369369
Min length1

Unique

Unique1 ?
Unique (%)0.9%

Sample

1st row
2nd row전남제주공동해역
3rd row전남제주공동해역
4th row전남제주공동해역
5th row전남제주공동해역

Common Values

ValueCountFrequency (%)
전남제주공동해역 110
99.1%
1
 
0.9%

Length

2023-12-13T08:43:49.761025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:43:49.839665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전남제주공동해역 110
100.0%

레이어분류내용(lyr_cl_cn)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1020.0 B
해양공간계획이 수립된 해양공간의 범위
111 

Length

Max length20
Median length20
Mean length20
Min length20

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row해양공간계획이 수립된 해양공간의 범위
2nd row해양공간계획이 수립된 해양공간의 범위
3rd row해양공간계획이 수립된 해양공간의 범위
4th row해양공간계획이 수립된 해양공간의 범위
5th row해양공간계획이 수립된 해양공간의 범위

Common Values

ValueCountFrequency (%)
해양공간계획이 수립된 해양공간의 범위 111
100.0%

Length

2023-12-13T08:43:49.913721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:43:49.989469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해양공간계획이 111
25.0%
수립된 111
25.0%
해양공간의 111
25.0%
범위 111
25.0%

공간정보(geom)
Text

UNIQUE 

Distinct111
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1020.0 B
2023-12-13T08:43:50.154770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length37
Mean length37.045045
Min length35

Characters and Unicode

Total characters4112
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique111 ?
Unique (%)100.0%

Sample

1st row126.45000000021946 34.12500000052844
2nd row 126.45000000032489 34.100000000312626
3rd row 126.47500000014954 34.10000000074363
4th row 126.50000000042039 34.100000000406425
5th row 126.52500000042767 34.1000000003203
ValueCountFrequency (%)
126.45000000021946 2
 
0.9%
34.12500000052844 2
 
0.9%
33.75000000067663 1
 
0.5%
126.20000000069032 1
 
0.5%
34.00000000071694 1
 
0.5%
126.15000000029963 1
 
0.5%
33.649999999969204 1
 
0.5%
126.22500000075179 1
 
0.5%
33.97499999989672 1
 
0.5%
126.25000000013341 1
 
0.5%
Other values (210) 210
94.6%
2023-12-13T08:43:50.464156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1395
33.9%
9 421
 
10.2%
3 317
 
7.7%
2 278
 
6.8%
6 262
 
6.4%
5 246
 
6.0%
1 245
 
6.0%
. 222
 
5.4%
221
 
5.4%
4 203
 
4.9%
Other values (2) 302
 
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3669
89.2%
Other Punctuation 222
 
5.4%
Space Separator 221
 
5.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1395
38.0%
9 421
 
11.5%
3 317
 
8.6%
2 278
 
7.6%
6 262
 
7.1%
5 246
 
6.7%
1 245
 
6.7%
4 203
 
5.5%
7 169
 
4.6%
8 133
 
3.6%
Other Punctuation
ValueCountFrequency (%)
. 222
100.0%
Space Separator
ValueCountFrequency (%)
221
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4112
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1395
33.9%
9 421
 
10.2%
3 317
 
7.7%
2 278
 
6.8%
6 262
 
6.4%
5 246
 
6.0%
1 245
 
6.0%
. 222
 
5.4%
221
 
5.4%
4 203
 
4.9%
Other values (2) 302
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4112
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1395
33.9%
9 421
 
10.2%
3 317
 
7.7%
2 278
 
6.8%
6 262
 
6.4%
5 246
 
6.0%
1 245
 
6.0%
. 222
 
5.4%
221
 
5.4%
4 203
 
4.9%
Other values (2) 302
 
7.3%

Interactions

2023-12-13T08:43:49.253313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:43:50.551070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호(gid)레이어명(lyr_nm)
일련번호(gid)1.0000.054
레이어명(lyr_nm)0.0541.000
2023-12-13T08:43:50.617499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호(gid)레이어명(lyr_nm)
일련번호(gid)1.0000.000
레이어명(lyr_nm)0.0001.000

Missing values

2023-12-13T08:43:49.348708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:43:49.434618image/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

일련번호(gid)레이어명(lyr_nm)레이어분류내용(lyr_cl_cn)공간정보(geom)
01해양공간계획이 수립된 해양공간의 범위126.45000000021946 34.12500000052844
12전남제주공동해역해양공간계획이 수립된 해양공간의 범위126.45000000032489 34.100000000312626
23전남제주공동해역해양공간계획이 수립된 해양공간의 범위126.47500000014954 34.10000000074363
34전남제주공동해역해양공간계획이 수립된 해양공간의 범위126.50000000042039 34.100000000406425
45전남제주공동해역해양공간계획이 수립된 해양공간의 범위126.52500000042767 34.1000000003203
56전남제주공동해역해양공간계획이 수립된 해양공간의 범위126.55000000055682 34.10000000060859
67전남제주공동해역해양공간계획이 수립된 해양공간의 범위126.55000000080615 34.075000000608576
78전남제주공동해역해양공간계획이 수립된 해양공간의 범위126.57500000075413 34.07500000031253
89전남제주공동해역해양공간계획이 수립된 해양공간의 범위126.60000000067367 34.07500000060111
910전남제주공동해역해양공간계획이 수립된 해양공간의 범위126.62499999987169 34.07500000067877
일련번호(gid)레이어명(lyr_nm)레이어분류내용(lyr_cl_cn)공간정보(geom)
101102전남제주공동해역해양공간계획이 수립된 해양공간의 범위126.15000000077332 34.10000000040995
102103전남제주공동해역해양공간계획이 수립된 해양공간의 범위126.2000000005776 34.099999999984206
103104전남제주공동해역해양공간계획이 수립된 해양공간의 범위126.19999999994566 34.15000000065313
104105전남제주공동해역해양공간계획이 수립된 해양공간의 범위126.25000000036738 34.15000000013373
105106전남제주공동해역해양공간계획이 수립된 해양공간의 범위126.2999999998379 34.15000000075776
106107전남제주공동해역해양공간계획이 수립된 해양공간의 범위126.35000000047665 34.150000000131634
107108전남제주공동해역해양공간계획이 수립된 해양공간의 범위126.40000000000033 34.15000000027913
108109전남제주공동해역해양공간계획이 수립된 해양공간의 범위126.40000010454695 34.12500000069108
109110전남제주공동해역해양공간계획이 수립된 해양공간의 범위126.42500000060123 34.125000000196565
110111전남제주공동해역해양공간계획이 수립된 해양공간의 범위126.45000000021946 34.12500000052844