Overview

Dataset statistics

Number of variables7
Number of observations29
Missing cells24
Missing cells (%)11.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 KiB
Average record size in memory60.6 B

Variable types

Categorical1
Text6

Dataset

Description경남도내 연도별 해수욕장 방문 현황입니다.
Author경상남도
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=3034255

Alerts

비고 has 24 (82.8%) missing valuesMissing
해수욕장명 has unique valuesUnique
‘18년(방문객, 명) has unique valuesUnique

Reproduction

Analysis started2023-12-10 23:46:17.631053
Analysis finished2023-12-10 23:46:18.298833
Duration0.67 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시/군
Categorical

Distinct5
Distinct (%)17.2%
Missing0
Missing (%)0.0%
Memory size364.0 B
거 제
17 
통영
5 
남 해
5 
창원
 
1
사 천
 
1

Length

Max length3
Median length3
Mean length2.7931034
Min length2

Unique

Unique2 ?
Unique (%)6.9%

Sample

1st row창원
2nd row통영
3rd row통영
4th row통영
5th row통영

Common Values

ValueCountFrequency (%)
거 제 17
58.6%
통영 5
 
17.2%
남 해 5
 
17.2%
창원 1
 
3.4%
사 천 1
 
3.4%

Length

2023-12-11T08:46:18.358239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:46:18.451779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
거 17
32.7%
제 17
32.7%
통영 5
 
9.6%
남 5
 
9.6%
해 5
 
9.6%
창원 1
 
1.9%
사 1
 
1.9%
천 1
 
1.9%

해수욕장명
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-11T08:46:18.638288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length2
Mean length3.7241379
Min length2

Characters and Unicode

Total characters108
Distinct characters73
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)100.0%

Sample

1st row광암
2nd row통영공설
3rd row비진도 산호빛해변
4th row사량 대항
5th row덕동
ValueCountFrequency (%)
광암 1
 
2.8%
통영공설 1
 
2.8%
옆개(물안 1
 
2.8%
덕원 1
 
2.8%
여차 1
 
2.8%
함목 1
 
2.8%
죽림 1
 
2.8%
옥계 1
 
2.8%
사곡 1
 
2.8%
구영 1
 
2.8%
Other values (26) 26
72.2%
2023-12-11T08:46:19.013910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7
 
6.5%
사 4
 
3.7%
변 4
 
3.7%
해 4
 
3.7%
덕 3
 
2.8%
포 3
 
2.8%
동 2
 
1.9%
몽 2
 
1.9%
남 2
 
1.9%
래 2
 
1.9%
Other values (63) 75
69.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 98
90.7%
Space Separator 7
 
6.5%
Close Punctuation 1
 
0.9%
Other Punctuation 1
 
0.9%
Open Punctuation 1
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 4
 
4.1%
변 4
 
4.1%
해 4
 
4.1%
덕 3
 
3.1%
포 3
 
3.1%
동 2
 
2.0%
몽 2
 
2.0%
남 2
 
2.0%
래 2
 
2.0%
대 2
 
2.0%
Other values (59) 70
71.4%
Space Separator
ValueCountFrequency (%)
7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 98
90.7%
Common 10
 
9.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 4
 
4.1%
변 4
 
4.1%
해 4
 
4.1%
덕 3
 
3.1%
포 3
 
3.1%
동 2
 
2.0%
몽 2
 
2.0%
남 2
 
2.0%
래 2
 
2.0%
대 2
 
2.0%
Other values (59) 70
71.4%
Common
ValueCountFrequency (%)
7
70.0%
) 1
 
10.0%
, 1
 
10.0%
( 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 98
90.7%
ASCII 10
 
9.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7
70.0%
) 1
 
10.0%
, 1
 
10.0%
( 1
 
10.0%
Hangul
ValueCountFrequency (%)
사 4
 
4.1%
변 4
 
4.1%
해 4
 
4.1%
덕 3
 
3.1%
포 3
 
3.1%
동 2
 
2.0%
몽 2
 
2.0%
남 2
 
2.0%
래 2
 
2.0%
대 2
 
2.0%
Other values (59) 70
71.4%

규모(㎡)
Text

Distinct27
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-11T08:46:19.178626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.7586207
Min length5

Characters and Unicode

Total characters167
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)89.7%

Sample

1st row25,653
2nd row7,500
3rd row22,000
4th row6,000
5th row3,300
ValueCountFrequency (%)
6,000 3
 
10.3%
25,653 1
 
3.4%
6,600 1
 
3.4%
27,000 1
 
3.4%
13,000 1
 
3.4%
104,749 1
 
3.4%
546,392 1
 
3.4%
4,000 1
 
3.4%
5,000 1
 
3.4%
1,100 1
 
3.4%
Other values (17) 17
58.6%
2023-12-11T08:46:19.505013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 70
41.9%
, 29
17.4%
1 12
 
7.2%
6 10
 
6.0%
5 10
 
6.0%
3 9
 
5.4%
2 8
 
4.8%
4 6
 
3.6%
9 6
 
3.6%
7 4
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 138
82.6%
Other Punctuation 29
 
17.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 70
50.7%
1 12
 
8.7%
6 10
 
7.2%
5 10
 
7.2%
3 9
 
6.5%
2 8
 
5.8%
4 6
 
4.3%
9 6
 
4.3%
7 4
 
2.9%
8 3
 
2.2%
Other Punctuation
ValueCountFrequency (%)
, 29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 167
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 70
41.9%
, 29
17.4%
1 12
 
7.2%
6 10
 
6.0%
5 10
 
6.0%
3 9
 
5.4%
2 8
 
4.8%
4 6
 
3.6%
9 6
 
3.6%
7 4
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 167
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 70
41.9%
, 29
17.4%
1 12
 
7.2%
6 10
 
6.0%
5 10
 
6.0%
3 9
 
5.4%
2 8
 
4.8%
4 6
 
3.6%
9 6
 
3.6%
7 4
 
2.4%

‘16년(방문객, 명)
Text

Distinct28
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-11T08:46:19.696783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.2758621
Min length1

Characters and Unicode

Total characters153
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

Unique27 ?
Unique (%)93.1%

Sample

1st row-
2nd row12,457
3rd row16,085
4th row2,739
5th row3,942
ValueCountFrequency (%)
2
 
6.9%
12,457 1
 
3.4%
16,980 1
 
3.4%
12,504 1
 
3.4%
109,492 1
 
3.4%
193,816 1
 
3.4%
9,045 1
 
3.4%
2,377 1
 
3.4%
4,918 1
 
3.4%
3,809 1
 
3.4%
Other values (18) 18
62.1%
2023-12-11T08:46:20.021047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 27
17.6%
9 17
11.1%
3 16
10.5%
0 15
9.8%
4 14
9.2%
6 13
8.5%
1 12
7.8%
7 11
7.2%
8 10
 
6.5%
2 8
 
5.2%
Other values (2) 10
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 124
81.0%
Other Punctuation 27
 
17.6%
Dash Punctuation 2
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 17
13.7%
3 16
12.9%
0 15
12.1%
4 14
11.3%
6 13
10.5%
1 12
9.7%
7 11
8.9%
8 10
8.1%
2 8
6.5%
5 8
6.5%
Other Punctuation
ValueCountFrequency (%)
, 27
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 153
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
, 27
17.6%
9 17
11.1%
3 16
10.5%
0 15
9.8%
4 14
9.2%
6 13
8.5%
1 12
7.8%
7 11
7.2%
8 10
 
6.5%
2 8
 
5.2%
Other values (2) 10
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 153
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 27
17.6%
9 17
11.1%
3 16
10.5%
0 15
9.8%
4 14
9.2%
6 13
8.5%
1 12
7.8%
7 11
7.2%
8 10
 
6.5%
2 8
 
5.2%
Other values (2) 10
 
6.5%

‘17년(방문객, 명)
Text

Distinct28
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-11T08:46:20.202201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.3448276
Min length1

Characters and Unicode

Total characters155
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

Unique27 ?
Unique (%)93.1%

Sample

1st row-
2nd row15,520
3rd row13,422
4th row2,927
5th row2,570
ValueCountFrequency (%)
2
 
6.9%
15,520 1
 
3.4%
7,382 1
 
3.4%
6,316 1
 
3.4%
103,851 1
 
3.4%
167,407 1
 
3.4%
17,616 1
 
3.4%
4,002 1
 
3.4%
4,195 1
 
3.4%
3,257 1
 
3.4%
Other values (18) 18
62.1%
2023-12-11T08:46:20.536175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 27
17.4%
5 19
12.3%
1 16
10.3%
2 15
9.7%
0 13
8.4%
7 13
8.4%
3 12
7.7%
6 12
7.7%
4 10
 
6.5%
8 9
 
5.8%
Other values (2) 9
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 126
81.3%
Other Punctuation 27
 
17.4%
Dash Punctuation 2
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 19
15.1%
1 16
12.7%
2 15
11.9%
0 13
10.3%
7 13
10.3%
3 12
9.5%
6 12
9.5%
4 10
7.9%
8 9
7.1%
9 7
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 27
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 155
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
, 27
17.4%
5 19
12.3%
1 16
10.3%
2 15
9.7%
0 13
8.4%
7 13
8.4%
3 12
7.7%
6 12
7.7%
4 10
 
6.5%
8 9
 
5.8%
Other values (2) 9
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 155
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 27
17.4%
5 19
12.3%
1 16
10.3%
2 15
9.7%
0 13
8.4%
7 13
8.4%
3 12
7.7%
6 12
7.7%
4 10
 
6.5%
8 9
 
5.8%
Other values (2) 9
 
5.8%

‘18년(방문객, 명)
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-11T08:46:20.764603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.4482759
Min length1

Characters and Unicode

Total characters158
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)100.0%

Sample

1st row29,350
2nd row12,953
3rd row12,540
4th row4,307
5th row2,248
ValueCountFrequency (%)
29,350 1
 
3.4%
11,562 1
 
3.4%
6,436 1
 
3.4%
4,830 1
 
3.4%
69,897 1
 
3.4%
115,272 1
 
3.4%
11,590 1
 
3.4%
2,051 1
 
3.4%
8,130 1
 
3.4%
3,544 1
 
3.4%
Other values (19) 19
65.5%
2023-12-11T08:46:21.145378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 28
17.7%
2 20
12.7%
5 20
12.7%
0 19
12.0%
1 15
9.5%
3 13
8.2%
9 10
 
6.3%
4 10
 
6.3%
7 9
 
5.7%
8 8
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 130
82.3%
Other Punctuation 28
 
17.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 20
15.4%
5 20
15.4%
0 19
14.6%
1 15
11.5%
3 13
10.0%
9 10
7.7%
4 10
7.7%
7 9
6.9%
8 8
 
6.2%
6 6
 
4.6%
Other Punctuation
ValueCountFrequency (%)
, 28
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 158
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
, 28
17.7%
2 20
12.7%
5 20
12.7%
0 19
12.0%
1 15
9.5%
3 13
8.2%
9 10
 
6.3%
4 10
 
6.3%
7 9
 
5.7%
8 8
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 158
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 28
17.7%
2 20
12.7%
5 20
12.7%
0 19
12.0%
1 15
9.5%
3 13
8.2%
9 10
 
6.3%
4 10
 
6.3%
7 9
 
5.7%
8 8
 
5.1%

비고
Text

MISSING 

Distinct4
Distinct (%)80.0%
Missing24
Missing (%)82.8%
Memory size364.0 B
2023-12-11T08:46:21.300169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.8
Min length2

Characters and Unicode

Total characters14
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)60.0%

Sample

1st row비지정
2nd row비지정
3rd row비개장
4th row최고
5th row방문객
ValueCountFrequency (%)
비지정 2
40.0%
비개장 1
20.0%
최고 1
20.0%
방문객 1
20.0%
2023-12-11T08:46:21.620523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
비 3
21.4%
지 2
14.3%
정 2
14.3%
개 1
 
7.1%
장 1
 
7.1%
최 1
 
7.1%
고 1
 
7.1%
방 1
 
7.1%
문 1
 
7.1%
객 1
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 3
21.4%
지 2
14.3%
정 2
14.3%
개 1
 
7.1%
장 1
 
7.1%
최 1
 
7.1%
고 1
 
7.1%
방 1
 
7.1%
문 1
 
7.1%
객 1
 
7.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 3
21.4%
지 2
14.3%
정 2
14.3%
개 1
 
7.1%
장 1
 
7.1%
최 1
 
7.1%
고 1
 
7.1%
방 1
 
7.1%
문 1
 
7.1%
객 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
비 3
21.4%
지 2
14.3%
정 2
14.3%
개 1
 
7.1%
장 1
 
7.1%
최 1
 
7.1%
고 1
 
7.1%
방 1
 
7.1%
문 1
 
7.1%
객 1
 
7.1%

Correlations

2023-12-11T08:46:21.708514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시/군해수욕장명규모(㎡)‘16년(방문객, 명)‘17년(방문객, 명)‘18년(방문객, 명)비고
시/군1.0001.0000.9280.0000.0001.0001.000
해수욕장명1.0001.0001.0001.0001.0001.0001.000
규모(㎡)0.9281.0001.0000.9690.9691.0001.000
‘16년(방문객, 명)0.0001.0000.9691.0001.0001.0001.000
‘17년(방문객, 명)0.0001.0000.9691.0001.0001.0001.000
‘18년(방문객, 명)1.0001.0001.0001.0001.0001.0001.000
비고1.0001.0001.0001.0001.0001.0001.000

Missing values

2023-12-11T08:46:18.160479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:46:18.259739image/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

시/군해수욕장명규모(㎡)‘16년(방문객, 명)‘17년(방문객, 명)‘18년(방문객, 명)비고
0창원광암25,653--29,350<NA>
1통영통영공설7,50012,45715,52012,953<NA>
2통영비진도 산호빛해변22,00016,08513,42212,540<NA>
3통영사량 대항6,0002,7392,9274,307<NA>
4통영덕동3,3003,9422,5702,248비지정
5통영봉암 몽돌24,0007,9589,6745,278비지정
6사 천남일대66,00043,89335,30528,100<NA>
7거 제명사31,50013,63520,97220,827<NA>
8거 제학동 흑진주몽돌해변148,00096,41064,96555,902<NA>
9거 제구조라92,70077,46055,50055,737<NA>
시/군해수욕장명규모(㎡)‘16년(방문객, 명)‘17년(방문객, 명)‘18년(방문객, 명)비고
19거 제죽림15,900--0비개장
20거 제옥계1,1003,8093,2573,544<NA>
21거 제사곡5,0004,9184,1958,130<NA>
22거 제구영4,0002,3774,0022,051<NA>
23거 제망치6,0009,04517,61611,590<NA>
24남 해상주 은모래비치546,392193,816167,407115,272최고
25남 해송정 솔바람해변104,749109,492103,85169,897방문객
26남 해사촌13,00012,5046,3164,830<NA>
27남 해두곡,월포27,00016,9807,3826,436<NA>
28남 해설리19,20043,36451,2829,068<NA>