Overview

Dataset statistics

Number of variables6
Number of observations172
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.4 KiB
Average record size in memory49.8 B

Variable types

Categorical2
Text4

Dataset

Description- 제주도 읍면동별 리·통사무소 정보를 제공합니다. - 데이터 제공처: 제주특별자치도
Author제주특별자치도 미래성장과
URLhttps://www.jejudatahub.net/data/view/data/938

Alerts

데이터 기준일 has constant value ""Constant
마을명 has unique valuesUnique
주소 has unique valuesUnique
전화번호 has unique valuesUnique
팩스번호 has unique valuesUnique

Reproduction

Analysis started2023-12-11 19:58:31.141276
Analysis finished2023-12-11 19:58:32.355109
Duration1.21 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

읍면동
Categorical

Distinct12
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
애월읍
26 
대정읍
23 
한림읍
21 
남원읍
17 
한경면
15 
Other values (7)
70 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
애월읍 26
15.1%
대정읍 23
13.4%
한림읍 21
12.2%
남원읍 17
9.9%
한경면 15
8.7%
성산읍 14
8.1%
구좌읍 12
7.0%
조천읍 12
7.0%
안덕면 12
7.0%
표선면 10
 
5.8%
Other values (2) 10
 
5.8%

Length

2023-12-12T04:58:32.451408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
애월읍 26
15.1%
대정읍 23
13.4%
한림읍 21
12.2%
남원읍 17
9.9%
한경면 15
8.7%
성산읍 14
8.1%
구좌읍 12
7.0%
조천읍 12
7.0%
안덕면 12
7.0%
표선면 10
 
5.8%
Other values (2) 10
 
5.8%

마을명
Text

UNIQUE 

Distinct172
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-12T04:58:32.905097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.4011628
Min length3

Characters and Unicode

Total characters585
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

Unique172 ?
Unique (%)100.0%

Sample

1st row귀덕1리
2nd row귀덕2리
3rd row귀덕3리
4th row수원리
5th row한수리
ValueCountFrequency (%)
귀덕1리 1
 
0.6%
신도2리 1
 
0.6%
하례1리 1
 
0.6%
구억리 1
 
0.6%
가파리 1
 
0.6%
마라리 1
 
0.6%
영락리 1
 
0.6%
무릉1리 1
 
0.6%
무릉2리 1
 
0.6%
신도1리 1
 
0.6%
Other values (163) 163
94.2%
2023-12-12T04:58:33.585940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 172
29.4%
2 28
 
4.8%
1 28
 
4.8%
신 18
 
3.1%
산 13
 
2.2%
수 12
 
2.1%
성 11
 
1.9%
하 10
 
1.7%
상 10
 
1.7%
흥 9
 
1.5%
Other values (112) 274
46.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 518
88.5%
Decimal Number 65
 
11.1%
Space Separator 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 172
33.2%
신 18
 
3.5%
산 13
 
2.5%
수 12
 
2.3%
성 11
 
2.1%
하 10
 
1.9%
상 10
 
1.9%
흥 9
 
1.7%
광 8
 
1.5%
천 8
 
1.5%
Other values (108) 247
47.7%
Decimal Number
ValueCountFrequency (%)
2 28
43.1%
1 28
43.1%
3 9
 
13.8%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 518
88.5%
Common 67
 
11.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 172
33.2%
신 18
 
3.5%
산 13
 
2.5%
수 12
 
2.3%
성 11
 
2.1%
하 10
 
1.9%
상 10
 
1.9%
흥 9
 
1.7%
광 8
 
1.5%
천 8
 
1.5%
Other values (108) 247
47.7%
Common
ValueCountFrequency (%)
2 28
41.8%
1 28
41.8%
3 9
 
13.4%
2
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 518
88.5%
ASCII 67
 
11.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 172
33.2%
신 18
 
3.5%
산 13
 
2.5%
수 12
 
2.3%
성 11
 
2.1%
하 10
 
1.9%
상 10
 
1.9%
흥 9
 
1.7%
광 8
 
1.5%
천 8
 
1.5%
Other values (108) 247
47.7%
ASCII
ValueCountFrequency (%)
2 28
41.8%
1 28
41.8%
3 9
 
13.4%
2
 
3.0%

주소
Text

UNIQUE 

Distinct172
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-12T04:58:33.957734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length14.116279
Min length9

Characters and Unicode

Total characters2428
Distinct characters143
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

Unique172 ?
Unique (%)100.0%

Sample

1st row제주시 한림읍 귀덕로 97-2
2nd row제주시 한림읍 귀덕3길 44
3rd row제주시 한림읍 한수풀로 337
4th row제주시 한림읍 수원9길 2
5th row제주시 한림읍 한림로 739
ValueCountFrequency (%)
제주시 93
 
15.2%
애월읍 26
 
4.3%
대정읍 23
 
3.8%
한림읍 21
 
3.4%
남원읍 17
 
2.8%
한경면 15
 
2.5%
성산읍 14
 
2.3%
안덕면 12
 
2.0%
조천읍 12
 
2.0%
구좌읍 12
 
2.0%
Other values (287) 366
59.9%
2023-12-12T04:58:34.487740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
439
 
18.1%
로 137
 
5.6%
읍 127
 
5.2%
주 102
 
4.2%
1 95
 
3.9%
시 94
 
3.9%
제 93
 
3.8%
2 59
 
2.4%
길 55
 
2.3%
4 55
 
2.3%
Other values (133) 1172
48.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1467
60.4%
Decimal Number 496
 
20.4%
Space Separator 439
 
18.1%
Dash Punctuation 26
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 137
 
9.3%
읍 127
 
8.7%
주 102
 
7.0%
시 94
 
6.4%
제 93
 
6.3%
길 55
 
3.7%
한 49
 
3.3%
면 47
 
3.2%
산 34
 
2.3%
월 31
 
2.1%
Other values (121) 698
47.6%
Decimal Number
ValueCountFrequency (%)
1 95
19.2%
2 59
11.9%
4 55
11.1%
3 50
10.1%
5 47
9.5%
7 43
8.7%
0 42
8.5%
6 39
7.9%
9 34
 
6.9%
8 32
 
6.5%
Space Separator
ValueCountFrequency (%)
439
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1467
60.4%
Common 961
39.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 137
 
9.3%
읍 127
 
8.7%
주 102
 
7.0%
시 94
 
6.4%
제 93
 
6.3%
길 55
 
3.7%
한 49
 
3.3%
면 47
 
3.2%
산 34
 
2.3%
월 31
 
2.1%
Other values (121) 698
47.6%
Common
ValueCountFrequency (%)
439
45.7%
1 95
 
9.9%
2 59
 
6.1%
4 55
 
5.7%
3 50
 
5.2%
5 47
 
4.9%
7 43
 
4.5%
0 42
 
4.4%
6 39
 
4.1%
9 34
 
3.5%
Other values (2) 58
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1467
60.4%
ASCII 961
39.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
439
45.7%
1 95
 
9.9%
2 59
 
6.1%
4 55
 
5.7%
3 50
 
5.2%
5 47
 
4.9%
7 43
 
4.5%
0 42
 
4.4%
6 39
 
4.1%
9 34
 
3.5%
Other values (2) 58
 
6.0%
Hangul
ValueCountFrequency (%)
로 137
 
9.3%
읍 127
 
8.7%
주 102
 
7.0%
시 94
 
6.4%
제 93
 
6.3%
길 55
 
3.7%
한 49
 
3.3%
면 47
 
3.2%
산 34
 
2.3%
월 31
 
2.1%
Other values (121) 698
47.6%

전화번호
Text

UNIQUE 

Distinct172
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-12T04:58:34.944648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters1376
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

Unique172 ?
Unique (%)100.0%

Sample

1st row796-3438
2nd row796-3187
3rd row796-3606
4th row796-2269
5th row796-2584
ValueCountFrequency (%)
796-3438 1
 
0.6%
773-1731 1
 
0.6%
767-0144 1
 
0.6%
794-8186 1
 
0.6%
794-7130 1
 
0.6%
792-4663 1
 
0.6%
792-2106 1
 
0.6%
792-2058 1
 
0.6%
792-1732 1
 
0.6%
792-2224 1
 
0.6%
Other values (162) 162
94.2%
2023-12-12T04:58:35.570776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 259
18.8%
- 172
12.5%
9 146
10.6%
3 135
9.8%
8 121
8.8%
4 112
8.1%
2 106
7.7%
1 103
 
7.5%
0 93
 
6.8%
6 85
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1204
87.5%
Dash Punctuation 172
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 259
21.5%
9 146
12.1%
3 135
11.2%
8 121
10.0%
4 112
9.3%
2 106
8.8%
1 103
 
8.6%
0 93
 
7.7%
6 85
 
7.1%
5 44
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 172
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1376
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 259
18.8%
- 172
12.5%
9 146
10.6%
3 135
9.8%
8 121
8.8%
4 112
8.1%
2 106
7.7%
1 103
 
7.5%
0 93
 
6.8%
6 85
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1376
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 259
18.8%
- 172
12.5%
9 146
10.6%
3 135
9.8%
8 121
8.8%
4 112
8.1%
2 106
7.7%
1 103
 
7.5%
0 93
 
6.8%
6 85
 
6.2%

팩스번호
Text

UNIQUE 

Distinct172
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-12T04:58:35.957963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters1376
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

Unique172 ?
Unique (%)100.0%

Sample

1st row796-1630
2nd row796-1631
3rd row796-1632
4th row796-1633
5th row796-1634
ValueCountFrequency (%)
796-1630 1
 
0.6%
772-4805 1
 
0.6%
767-3344 1
 
0.6%
794-6035 1
 
0.6%
794-6036 1
 
0.6%
792-0086 1
 
0.6%
792-4801 1
 
0.6%
792-4802 1
 
0.6%
792-4803 1
 
0.6%
792-4804 1
 
0.6%
Other values (162) 162
94.2%
2023-12-12T04:58:36.545775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 274
19.9%
- 172
12.5%
4 152
11.0%
8 120
8.7%
9 118
8.6%
6 117
8.5%
2 108
 
7.8%
1 85
 
6.2%
0 83
 
6.0%
3 82
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1204
87.5%
Dash Punctuation 172
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 274
22.8%
4 152
12.6%
8 120
10.0%
9 118
9.8%
6 117
9.7%
2 108
 
9.0%
1 85
 
7.1%
0 83
 
6.9%
3 82
 
6.8%
5 65
 
5.4%
Dash Punctuation
ValueCountFrequency (%)
- 172
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1376
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 274
19.9%
- 172
12.5%
4 152
11.0%
8 120
8.7%
9 118
8.6%
6 117
8.5%
2 108
 
7.8%
1 85
 
6.2%
0 83
 
6.0%
3 82
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1376
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 274
19.9%
- 172
12.5%
4 152
11.0%
8 120
8.7%
9 118
8.6%
6 117
8.5%
2 108
 
7.8%
1 85
 
6.2%
0 83
 
6.0%
3 82
 
6.0%

데이터 기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
20210817
172 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20210817
2nd row20210817
3rd row20210817
4th row20210817
5th row20210817

Common Values

ValueCountFrequency (%)
20210817 172
100.0%

Length

2023-12-12T04:58:36.720674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T04:58:36.842792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20210817 172
100.0%

Missing values

2023-12-12T04:58:31.910211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T04:58:32.287842image/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

읍면동마을명주소전화번호팩스번호데이터 기준일
0한림읍귀덕1리제주시 한림읍 귀덕로 97-2796-3438796-163020210817
1한림읍귀덕2리제주시 한림읍 귀덕3길 44796-3187796-163120210817
2한림읍귀덕3리제주시 한림읍 한수풀로 337796-3606796-163220210817
3한림읍수원리제주시 한림읍 수원9길 2796-2269796-163320210817
4한림읍한수리제주시 한림읍 한림로 739796-2584796-163420210817
5한림읍대림리제주시 한림읍 한수풀로 180796-2588796-163520210817
6한림읍한림1리제주시 한림읍 한림해안로 154796-2076796-163620210817
7한림읍한림2리제주시 한림읍 한림남길 6796-2819796-163720210817
8한림읍한림3리제주시 한림읍 장원길 87796-1257796-163920210817
9한림읍강구리제주시 한림읍 강구로 92796-2347796-163820210817
읍면동마을명주소전화번호팩스번호데이터 기준일
162표선면표선리표선면 표선동서로 234787-0024787-401120210817
163표선면하천리표선면 하천로 59787-0404787-401220210817
164표선면성읍1리표선면 중산간동로 4658787-1306787-401320210817
165표선면성읍2리표선면 성읍이리로58번길 8787-1367787-401420210817
166표선면가시리표선면 가시로 565번길 20787-1305787-401520210817
167표선면세화1리표선면 세성로 302787-3309787-401620210817
168표선면세화2리표선면 일주동로 6276787-3310787-401720210817
169표선면세화3리표선면 세화로 168787-1504787-401820210817
170표선면토산1리표선면 중산간동로5570번길 2787-3307787-401920210817
171표선면토산2리표선면 토산중앙로 16번길 1787-3308787-402020210817