Overview

Dataset statistics

Number of variables4
Number of observations282
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.5 KiB
Average record size in memory34.5 B

Variable types

Numeric2
Categorical1
Text1

Dataset

Description연안침식 실태조사의 결과를 종합한 백서의 데이터로 연안침식백서 모니터링위치에 대하여 시도명과 모니터링지점명등의 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15114197/fileData.do

Alerts

공간정보일련번호(gid) is highly overall correlated with 시도명(sido_nm)High correlation
모니터링지점키(mnrg_spot_key) is highly overall correlated with 시도명(sido_nm)High correlation
시도명(sido_nm) is highly overall correlated with 공간정보일련번호(gid) and 1 other fieldsHigh correlation
공간정보일련번호(gid) has unique valuesUnique
모니터링지점명(mnrg_spot_nm) has unique valuesUnique
모니터링지점키(mnrg_spot_key) has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:50:58.593599
Analysis finished2023-12-12 15:50:59.615305
Duration1.02 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

공간정보일련번호(gid)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct282
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean141.5
Minimum1
Maximum282
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-13T00:50:59.717089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile15.05
Q171.25
median141.5
Q3211.75
95-th percentile267.95
Maximum282
Range281
Interquartile range (IQR)140.5

Descriptive statistics

Standard deviation81.550598
Coefficient of variation (CV)0.57632931
Kurtosis-1.2
Mean141.5
Median Absolute Deviation (MAD)70.5
Skewness0
Sum39903
Variance6650.5
MonotonicityNot monotonic
2023-12-13T00:50:59.941964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
186 1
 
0.4%
192 1
 
0.4%
191 1
 
0.4%
190 1
 
0.4%
189 1
 
0.4%
188 1
 
0.4%
187 1
 
0.4%
185 1
 
0.4%
194 1
 
0.4%
Other values (272) 272
96.5%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
282 1
0.4%
281 1
0.4%
280 1
0.4%
279 1
0.4%
278 1
0.4%
277 1
0.4%
276 1
0.4%
275 1
0.4%
274 1
0.4%
273 1
0.4%

시도명(sido_nm)
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
강원도
67 
전라남도
61 
경상북도
39 
경상남도
25 
인천광역시
23 
Other values (6)
67 

Length

Max length5
Median length4
Mean length3.8262411
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강원도 67
23.8%
전라남도 61
21.6%
경상북도 39
13.8%
경상남도 25
 
8.9%
인천광역시 23
 
8.2%
충청남도 23
 
8.2%
제주도 15
 
5.3%
부산광역시 10
 
3.5%
전라북도 9
 
3.2%
경기도 5
 
1.8%

Length

2023-12-13T00:51:00.148271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강원도 67
23.8%
전라남도 61
21.6%
경상북도 39
13.8%
경상남도 25
 
8.9%
인천광역시 23
 
8.2%
충청남도 23
 
8.2%
제주도 15
 
5.3%
부산광역시 10
 
3.5%
전라북도 9
 
3.2%
경기도 5
 
1.8%

모니터링지점명(mnrg_spot_nm)
Text

UNIQUE 

Distinct282
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2023-12-13T00:51:00.579951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length7.9042553
Min length3

Characters and Unicode

Total characters2229
Distinct characters229
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique282 ?
Unique (%)100.0%

Sample

1st row강문동 경포대해수욕장
2nd row초당동 강문해수욕장
3rd row강동면 정동진해수욕장
4th row연곡면 영진리
5th row안현동 사근진해수욕장
ValueCountFrequency (%)
해수욕장 102
 
19.0%
남면 5
 
0.9%
감포읍 5
 
0.9%
서도면 4
 
0.7%
북구 4
 
0.7%
기성면 4
 
0.7%
남정면 3
 
0.6%
남구 3
 
0.6%
근덕면 3
 
0.6%
화정면 3
 
0.6%
Other values (372) 402
74.7%
2023-12-13T00:51:01.246508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
256
 
11.5%
해 165
 
7.4%
장 162
 
7.3%
수 153
 
6.9%
욕 149
 
6.7%
면 104
 
4.7%
구 71
 
3.2%
지 61
 
2.7%
리 53
 
2.4%
G 37
 
1.7%
Other values (219) 1018
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1787
80.2%
Space Separator 256
 
11.5%
Decimal Number 89
 
4.0%
Uppercase Letter 74
 
3.3%
Math Symbol 10
 
0.4%
Close Punctuation 6
 
0.3%
Open Punctuation 6
 
0.3%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
해 165
 
9.2%
장 162
 
9.1%
수 153
 
8.6%
욕 149
 
8.3%
면 104
 
5.8%
구 71
 
4.0%
지 61
 
3.4%
리 53
 
3.0%
포 32
 
1.8%
남 30
 
1.7%
Other values (202) 807
45.2%
Decimal Number
ValueCountFrequency (%)
1 22
24.7%
2 18
20.2%
0 13
14.6%
3 13
14.6%
4 6
 
6.7%
6 4
 
4.5%
9 4
 
4.5%
5 3
 
3.4%
8 3
 
3.4%
7 3
 
3.4%
Uppercase Letter
ValueCountFrequency (%)
G 37
50.0%
W 37
50.0%
Space Separator
ValueCountFrequency (%)
256
100.0%
Math Symbol
ValueCountFrequency (%)
∼ 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Other Punctuation
ValueCountFrequency (%)
· 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1787
80.2%
Common 368
 
16.5%
Latin 74
 
3.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
해 165
 
9.2%
장 162
 
9.1%
수 153
 
8.6%
욕 149
 
8.3%
면 104
 
5.8%
구 71
 
4.0%
지 61
 
3.4%
리 53
 
3.0%
포 32
 
1.8%
남 30
 
1.7%
Other values (202) 807
45.2%
Common
ValueCountFrequency (%)
256
69.6%
1 22
 
6.0%
2 18
 
4.9%
0 13
 
3.5%
3 13
 
3.5%
∼ 10
 
2.7%
4 6
 
1.6%
) 6
 
1.6%
( 6
 
1.6%
6 4
 
1.1%
Other values (5) 14
 
3.8%
Latin
ValueCountFrequency (%)
G 37
50.0%
W 37
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1787
80.2%
ASCII 431
 
19.3%
Math Operators 10
 
0.4%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
256
59.4%
G 37
 
8.6%
W 37
 
8.6%
1 22
 
5.1%
2 18
 
4.2%
0 13
 
3.0%
3 13
 
3.0%
4 6
 
1.4%
) 6
 
1.4%
( 6
 
1.4%
Other values (5) 17
 
3.9%
Hangul
ValueCountFrequency (%)
해 165
 
9.2%
장 162
 
9.1%
수 153
 
8.6%
욕 149
 
8.3%
면 104
 
5.8%
구 71
 
4.0%
지 61
 
3.4%
리 53
 
3.0%
포 32
 
1.8%
남 30
 
1.7%
Other values (202) 807
45.2%
Math Operators
ValueCountFrequency (%)
∼ 10
100.0%
None
ValueCountFrequency (%)
· 1
100.0%

모니터링지점키(mnrg_spot_key)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct282
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43403154
Minimum26140001
Maximum50130009
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-13T00:51:01.505667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum26140001
5-th percentile28140005
Q142230002
median45800004
Q347125752
95-th percentile50046501
Maximum50130009
Range23990008
Interquartile range (IQR)4895749.5

Descriptive statistics

Standard deviation6393714
Coefficient of variation (CV)0.14730989
Kurtosis1.557462
Mean43403154
Median Absolute Deviation (MAD)2509999
Skewness-1.6370784
Sum1.2239689 × 1010
Variance4.0879579 × 1013
MonotonicityNot monotonic
2023-12-13T00:51:01.736976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42150001 1
 
0.4%
46900004 1
 
0.4%
46820002 1
 
0.4%
46820001 1
 
0.4%
46860001 1
 
0.4%
46900007 1
 
0.4%
46900006 1
 
0.4%
46900005 1
 
0.4%
46900003 1
 
0.4%
46820004 1
 
0.4%
Other values (272) 272
96.5%
ValueCountFrequency (%)
26140001 1
0.4%
26350001 1
0.4%
26350002 1
0.4%
26380001 1
0.4%
26440001 1
0.4%
26440002 1
0.4%
26440003 1
0.4%
26500001 1
0.4%
26710001 1
0.4%
26710002 1
0.4%
ValueCountFrequency (%)
50130009 1
0.4%
50130008 1
0.4%
50130007 1
0.4%
50130006 1
0.4%
50130005 1
0.4%
50130004 1
0.4%
50130003 1
0.4%
50130002 1
0.4%
50130001 1
0.4%
50110006 1
0.4%

Interactions

2023-12-13T00:50:59.129104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:50:58.852513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:50:59.265166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:50:58.984380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:51:01.872393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공간정보일련번호(gid)시도명(sido_nm)모니터링지점키(mnrg_spot_key)
공간정보일련번호(gid)1.0000.9320.867
시도명(sido_nm)0.9321.0000.972
모니터링지점키(mnrg_spot_key)0.8670.9721.000
2023-12-13T00:51:02.008685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공간정보일련번호(gid)모니터링지점키(mnrg_spot_key)시도명(sido_nm)
공간정보일련번호(gid)1.000-0.0720.753
모니터링지점키(mnrg_spot_key)-0.0721.0000.922
시도명(sido_nm)0.7530.9221.000

Missing values

2023-12-13T00:50:59.443806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:50:59.559700image/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

공간정보일련번호(gid)시도명(sido_nm)모니터링지점명(mnrg_spot_nm)모니터링지점키(mnrg_spot_key)
01강원도강문동 경포대해수욕장42150001
12강원도초당동 강문해수욕장42150002
23강원도강동면 정동진해수욕장42150003
34강원도연곡면 영진리42150004
45강원도안현동 사근진해수욕장42150005
56강원도사천면 사천진리(1)(2)42150006
67강원도성덕동 남항진해수욕장42150007
78강원도연곡면 동덕리42150008
89강원도주문진읍 주문진 해수욕장42150009
910강원도토성면 천진해수욕장42820001
공간정보일련번호(gid)시도명(sido_nm)모니터링지점명(mnrg_spot_nm)모니터링지점키(mnrg_spot_key)
272272강원도GW1142820016
273273강원도GW1242820017
274274강원도GW1342820018
275275강원도GW1642830010
276276강원도GW1742830011
277277강원도GW1842830012
278278강원도GW1942830013
279279강원도GW2042830014
280281강원도GW2242830016
281282강원도GW2342830017