Overview

Dataset statistics

Number of variables6
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 KiB
Average record size in memory54.5 B

Variable types

Numeric1
Text5

Dataset

Description경상남도내 정보화마을의 조성 현황에 대한 데이터로, 마을명, 전화번호, 홈페이지, 특산물 쇼핑, 주변 관광지 정보를 제공합니다.
Author경상남도
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15056300

Alerts

연번 has unique valuesUnique
마을명 has unique valuesUnique
전화번호 has unique valuesUnique
홈페이지 has unique valuesUnique
특산물 쇼핑 has unique valuesUnique

Reproduction

Analysis started2023-12-10 23:38:02.333472
Analysis finished2023-12-10 23:38:03.054332
Duration0.72 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.5
Minimum1
Maximum24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-11T08:38:03.149856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.15
Q16.75
median12.5
Q318.25
95-th percentile22.85
Maximum24
Range23
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation7.0710678
Coefficient of variation (CV)0.56568542
Kurtosis-1.2
Mean12.5
Median Absolute Deviation (MAD)6
Skewness0
Sum300
Variance50
MonotonicityStrictly increasing
2023-12-11T08:38:03.328695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 1
 
4.2%
14 1
 
4.2%
24 1
 
4.2%
23 1
 
4.2%
22 1
 
4.2%
21 1
 
4.2%
20 1
 
4.2%
19 1
 
4.2%
18 1
 
4.2%
17 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
1 1
4.2%
2 1
4.2%
3 1
4.2%
4 1
4.2%
5 1
4.2%
6 1
4.2%
7 1
4.2%
8 1
4.2%
9 1
4.2%
10 1
4.2%
ValueCountFrequency (%)
24 1
4.2%
23 1
4.2%
22 1
4.2%
21 1
4.2%
20 1
4.2%
19 1
4.2%
18 1
4.2%
17 1
4.2%
16 1
4.2%
15 1
4.2%

마을명
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-11T08:38:03.645188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.2916667
Min length7

Characters and Unicode

Total characters223
Distinct characters96
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

Unique24 ?
Unique (%)100.0%

Sample

1st row거제 구조라관광어촌마을
2nd row거제 어구낚시마을
3rd row거창 가남마을
4th row거창 서변마을
5th row고성 송천참다래마을
ValueCountFrequency (%)
거제 2
 
4.2%
함안 2
 
4.2%
창녕 2
 
4.2%
의령 2
 
4.2%
하동 2
 
4.2%
김해 2
 
4.2%
밀양 2
 
4.2%
거창 2
 
4.2%
옥종딸기마을 1
 
2.1%
월촌마을 1
 
2.1%
Other values (30) 30
62.5%
2023-12-11T08:38:04.020822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
마 24
 
10.8%
24
 
10.8%
을 24
 
10.8%
양 6
 
2.7%
산 6
 
2.7%
대 6
 
2.7%
창 5
 
2.2%
거 4
 
1.8%
과 4
 
1.8%
천 4
 
1.8%
Other values (86) 116
52.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 199
89.2%
Space Separator 24
 
10.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 24
 
12.1%
을 24
 
12.1%
양 6
 
3.0%
산 6
 
3.0%
대 6
 
3.0%
창 5
 
2.5%
거 4
 
2.0%
과 4
 
2.0%
천 4
 
2.0%
감 3
 
1.5%
Other values (85) 113
56.8%
Space Separator
ValueCountFrequency (%)
24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 199
89.2%
Common 24
 
10.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 24
 
12.1%
을 24
 
12.1%
양 6
 
3.0%
산 6
 
3.0%
대 6
 
3.0%
창 5
 
2.5%
거 4
 
2.0%
과 4
 
2.0%
천 4
 
2.0%
감 3
 
1.5%
Other values (85) 113
56.8%
Common
ValueCountFrequency (%)
24
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 199
89.2%
ASCII 24
 
10.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
마 24
 
12.1%
을 24
 
12.1%
양 6
 
3.0%
산 6
 
3.0%
대 6
 
3.0%
창 5
 
2.5%
거 4
 
2.0%
과 4
 
2.0%
천 4
 
2.0%
감 3
 
1.5%
Other values (85) 113
56.8%
ASCII
ValueCountFrequency (%)
24
100.0%

전화번호
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-11T08:38:04.269376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.041667
Min length12

Characters and Unicode

Total characters289
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

Unique24 ?
Unique (%)100.0%

Sample

1st row055-681-2749
2nd row055-634-0440
3rd row055-940-3950
4th row055-940-3841
5th row070-7767-8622
ValueCountFrequency (%)
055-681-2749 1
 
4.2%
055-634-0440 1
 
4.2%
055-587-6262 1
 
4.2%
055-582-9977 1
 
4.2%
055-880-6409 1
 
4.2%
055-880-6109 1
 
4.2%
055-642-1917 1
 
4.2%
055-272-0011 1
 
4.2%
055-532-0334 1
 
4.2%
055-533-1600 1
 
4.2%
Other values (14) 14
58.3%
2023-12-11T08:38:04.613389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 59
20.4%
0 49
17.0%
- 48
16.6%
2 22
 
7.6%
7 19
 
6.6%
3 19
 
6.6%
6 18
 
6.2%
4 17
 
5.9%
8 15
 
5.2%
9 12
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 241
83.4%
Dash Punctuation 48
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 59
24.5%
0 49
20.3%
2 22
 
9.1%
7 19
 
7.9%
3 19
 
7.9%
6 18
 
7.5%
4 17
 
7.1%
8 15
 
6.2%
9 12
 
5.0%
1 11
 
4.6%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 289
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 59
20.4%
0 49
17.0%
- 48
16.6%
2 22
 
7.6%
7 19
 
6.6%
3 19
 
6.6%
6 18
 
6.2%
4 17
 
5.9%
8 15
 
5.2%
9 12
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 289
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 59
20.4%
0 49
17.0%
- 48
16.6%
2 22
 
7.6%
7 19
 
6.6%
3 19
 
6.6%
6 18
 
6.2%
4 17
 
5.9%
8 15
 
5.2%
9 12
 
4.2%

홈페이지
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-11T08:38:04.856432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18.5
Mean length16.458333
Min length13

Characters and Unicode

Total characters395
Distinct characters23
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
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 rowgujora.invil.org
2nd roweogu.invil.org
3rd rowganam.invil.org
4th rowseobyeon.invil.org
5th rowchamdarae.invil.org
ValueCountFrequency (%)
gujora.invil.org 1
 
4.2%
eogu.invil.org 1
 
4.2%
chilbuk.invil.org 1
 
4.2%
wolchon.invil.org 1
 
4.2%
okjong.invil.org 1
 
4.2%
daebonggam.invil.org 1
 
4.2%
haklim.invil.org 1
 
4.2%
gohyeon.invil.org 1
 
4.2%
sgo.invil.org 1
 
4.2%
mosan.invil.org 1
 
4.2%
Other values (14) 14
58.3%
2023-12-11T08:38:05.277393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 52
13.2%
. 48
12.2%
o 43
10.9%
n 37
9.4%
g 34
8.6%
l 31
7.8%
r 26
6.6%
v 25
6.3%
a 22
 
5.6%
e 17
 
4.3%
Other values (13) 60
15.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 346
87.6%
Other Punctuation 48
 
12.2%
Decimal Number 1
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 52
15.0%
o 43
12.4%
n 37
10.7%
g 34
9.8%
l 31
9.0%
r 26
7.5%
v 25
7.2%
a 22
6.4%
e 17
 
4.9%
h 8
 
2.3%
Other values (11) 51
14.7%
Other Punctuation
ValueCountFrequency (%)
. 48
100.0%
Decimal Number
ValueCountFrequency (%)
7 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 346
87.6%
Common 49
 
12.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 52
15.0%
o 43
12.4%
n 37
10.7%
g 34
9.8%
l 31
9.0%
r 26
7.5%
v 25
7.2%
a 22
6.4%
e 17
 
4.9%
h 8
 
2.3%
Other values (11) 51
14.7%
Common
ValueCountFrequency (%)
. 48
98.0%
7 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 395
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 52
13.2%
. 48
12.2%
o 43
10.9%
n 37
9.4%
g 34
8.6%
l 31
7.8%
r 26
6.6%
v 25
6.3%
a 22
 
5.6%
e 17
 
4.3%
Other values (13) 60
15.2%

특산물 쇼핑
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-11T08:38:05.528256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length12
Mean length10.875
Min length6

Characters and Unicode

Total characters261
Distinct characters99
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
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 row멸치, 조청, 한과
2nd row액젓, 젓갈류, 굴
3rd row쌀, 딸기, 오미자
4th row사과, 딸기, 블루베리
5th row참다래, 취나물
ValueCountFrequency (%)
사과 4
 
5.8%
딸기 4
 
5.8%
곶감 3
 
4.3%
블루베리 2
 
2.9%
단감 2
 
2.9%
대봉감 2
 
2.9%
감식초 2
 
2.9%
우리밀 2
 
2.9%
양파즙 2
 
2.9%
수박 2
 
2.9%
Other values (42) 44
63.8%
2023-12-11T08:38:06.003168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
45
 
17.2%
, 42
 
16.1%
감 9
 
3.4%
사 6
 
2.3%
과 6
 
2.3%
기 6
 
2.3%
리 6
 
2.3%
딸 4
 
1.5%
토 4
 
1.5%
마 3
 
1.1%
Other values (89) 130
49.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 174
66.7%
Space Separator 45
 
17.2%
Other Punctuation 42
 
16.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
감 9
 
5.2%
사 6
 
3.4%
과 6
 
3.4%
기 6
 
3.4%
리 6
 
3.4%
딸 4
 
2.3%
토 4
 
2.3%
마 3
 
1.7%
젓 3
 
1.7%
단 3
 
1.7%
Other values (87) 124
71.3%
Space Separator
ValueCountFrequency (%)
45
100.0%
Other Punctuation
ValueCountFrequency (%)
, 42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 174
66.7%
Common 87
33.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
감 9
 
5.2%
사 6
 
3.4%
과 6
 
3.4%
기 6
 
3.4%
리 6
 
3.4%
딸 4
 
2.3%
토 4
 
2.3%
마 3
 
1.7%
젓 3
 
1.7%
단 3
 
1.7%
Other values (87) 124
71.3%
Common
ValueCountFrequency (%)
45
51.7%
, 42
48.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 174
66.7%
ASCII 87
33.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
45
51.7%
, 42
48.3%
Hangul
ValueCountFrequency (%)
감 9
 
5.2%
사 6
 
3.4%
과 6
 
3.4%
기 6
 
3.4%
리 6
 
3.4%
딸 4
 
2.3%
토 4
 
2.3%
마 3
 
1.7%
젓 3
 
1.7%
단 3
 
1.7%
Other values (87) 124
71.3%

주변 관광지
Text

Distinct23
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-11T08:38:06.274463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length12.125
Min length8

Characters and Unicode

Total characters291
Distinct characters122
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)91.7%

Sample

1st row구조라해수욕장, 해금강
2nd row한산도, 청마생가
3rd row장군봉, 미녀봉, 가조온천
4th row금원산자연휴양림, 수승대
5th row고성공룡박물관, 상족암
ValueCountFrequency (%)
화왕산 2
 
3.5%
케이블카 2
 
3.5%
우포늪 2
 
3.5%
충익사 2
 
3.5%
부곡온천 2
 
3.5%
벽화산성 1
 
1.8%
광심정 1
 
1.8%
구조라해수욕장 1
 
1.8%
해금강 1
 
1.8%
배내골계곡 1
 
1.8%
Other values (42) 42
73.7%
2023-12-11T08:38:06.684888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 33
 
11.3%
33
 
11.3%
산 10
 
3.4%
사 9
 
3.1%
천 6
 
2.1%
해 5
 
1.7%
원 5
 
1.7%
화 4
 
1.4%
마 4
 
1.4%
대 4
 
1.4%
Other values (112) 178
61.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 225
77.3%
Other Punctuation 33
 
11.3%
Space Separator 33
 
11.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 10
 
4.4%
사 9
 
4.0%
천 6
 
2.7%
해 5
 
2.2%
원 5
 
2.2%
화 4
 
1.8%
마 4
 
1.8%
대 4
 
1.8%
성 4
 
1.8%
가 4
 
1.8%
Other values (110) 170
75.6%
Other Punctuation
ValueCountFrequency (%)
, 33
100.0%
Space Separator
ValueCountFrequency (%)
33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 225
77.3%
Common 66
 
22.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 10
 
4.4%
사 9
 
4.0%
천 6
 
2.7%
해 5
 
2.2%
원 5
 
2.2%
화 4
 
1.8%
마 4
 
1.8%
대 4
 
1.8%
성 4
 
1.8%
가 4
 
1.8%
Other values (110) 170
75.6%
Common
ValueCountFrequency (%)
, 33
50.0%
33
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 225
77.3%
ASCII 66
 
22.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 33
50.0%
33
50.0%
Hangul
ValueCountFrequency (%)
산 10
 
4.4%
사 9
 
4.0%
천 6
 
2.7%
해 5
 
2.2%
원 5
 
2.2%
화 4
 
1.8%
마 4
 
1.8%
대 4
 
1.8%
성 4
 
1.8%
가 4
 
1.8%
Other values (110) 170
75.6%

Interactions

2023-12-11T08:38:02.708456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:38:06.785425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번마을명전화번호홈페이지특산물 쇼핑주변 관광지
연번1.0001.0001.0001.0001.0001.000
마을명1.0001.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.000
홈페이지1.0001.0001.0001.0001.0001.000
특산물 쇼핑1.0001.0001.0001.0001.0001.000
주변 관광지1.0001.0001.0001.0001.0001.000

Missing values

2023-12-11T08:38:02.840196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:38:03.003557image/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

연번마을명전화번호홈페이지특산물 쇼핑주변 관광지
01거제 구조라관광어촌마을055-681-2749gujora.invil.org멸치, 조청, 한과구조라해수욕장, 해금강
12거제 어구낚시마을055-634-0440eogu.invil.org액젓, 젓갈류, 굴한산도, 청마생가
23거창 가남마을055-940-3950ganam.invil.org쌀, 딸기, 오미자장군봉, 미녀봉, 가조온천
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