Overview

Dataset statistics

Number of variables8
Number of observations28
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 KiB
Average record size in memory70.7 B

Variable types

Text4
DateTime2
Numeric1
Categorical1

Dataset

Description제주특별자치도 서귀포시 관내 지역아동센터의 관한 데이터로 센터명, 전화번호, 팩스번호, 주소, 정원 등 정보를 제공합니다.
Author제주특별자치도 서귀포시
URLhttps://www.data.go.kr/data/15056056/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
정원 is highly overall correlated with 종사자수High correlation
종사자수 is highly overall correlated with 정원High correlation
센터명 has unique valuesUnique
주소 has unique valuesUnique
전화번호 has unique valuesUnique
팩스번호 has unique valuesUnique

Reproduction

Analysis started2024-04-06 09:02:48.543228
Analysis finished2024-04-06 09:02:50.093234
Duration1.55 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

센터명
Text

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
2024-04-06T18:02:50.326853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length2
Mean length2.9642857
Min length2

Characters and Unicode

Total characters83
Distinct characters62
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

Unique28 ?
Unique (%)100.0%

Sample

1st row가마
2nd row감산
3rd row다솜
4th row담쟁이
5th row대정골
ValueCountFrequency (%)
가마 1
 
3.2%
성읍 1
 
3.2%
성산 1
 
3.2%
혼디 1
 
3.2%
공립 1
 
3.2%
서귀포시 1
 
3.2%
중문 1
 
3.2%
중문제일 1
 
3.2%
위미 1
 
3.2%
온누리 1
 
3.2%
Other values (21) 21
67.7%
2024-04-06T18:02:50.975153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 3
 
3.6%
성 3
 
3.6%
포 3
 
3.6%
신 3
 
3.6%
3
 
3.6%
동 2
 
2.4%
정 2
 
2.4%
온 2
 
2.4%
디 2
 
2.4%
대 2
 
2.4%
Other values (52) 58
69.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 80
96.4%
Space Separator 3
 
3.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 3
 
3.8%
성 3
 
3.8%
포 3
 
3.8%
신 3
 
3.8%
동 2
 
2.5%
정 2
 
2.5%
온 2
 
2.5%
디 2
 
2.5%
대 2
 
2.5%
이 2
 
2.5%
Other values (51) 56
70.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 80
96.4%
Common 3
 
3.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 3
 
3.8%
성 3
 
3.8%
포 3
 
3.8%
신 3
 
3.8%
동 2
 
2.5%
정 2
 
2.5%
온 2
 
2.5%
디 2
 
2.5%
대 2
 
2.5%
이 2
 
2.5%
Other values (51) 56
70.0%
Common
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 80
96.4%
ASCII 3
 
3.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 3
 
3.8%
성 3
 
3.8%
포 3
 
3.8%
신 3
 
3.8%
동 2
 
2.5%
정 2
 
2.5%
온 2
 
2.5%
디 2
 
2.5%
대 2
 
2.5%
이 2
 
2.5%
Other values (51) 56
70.0%
ASCII
ValueCountFrequency (%)
3
100.0%

주소
Text

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
2024-04-06T18:02:51.355155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length27.5
Mean length24.964286
Min length20

Characters and Unicode

Total characters699
Distinct characters72
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

Unique28 ?
Unique (%)100.0%

Sample

1st row제주특별자치도 서귀포시 표선면 일주동로 6276
2nd row제주특별자치도 서귀포시 안덕면 감산중로 16-13
3rd row제주특별자치도 서귀포시 효돈로 214
4th row제주특별자치도 서귀포시 홍중로27번길 30
5th row제주특별자치도 서귀포시 대정읍 추사로55번길 7-4
ValueCountFrequency (%)
제주특별자치도 28
22.2%
서귀포시 28
22.2%
성산읍 4
 
3.2%
대정읍 3
 
2.4%
남원읍 3
 
2.4%
표선면 2
 
1.6%
동홍중앙로 2
 
1.6%
안덕면 2
 
1.6%
16 2
 
1.6%
신흥로 1
 
0.8%
Other values (51) 51
40.5%
2024-04-06T18:02:52.018359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
105
 
15.0%
서 31
 
4.4%
주 29
 
4.1%
로 28
 
4.0%
시 28
 
4.0%
포 28
 
4.0%
귀 28
 
4.0%
제 28
 
4.0%
도 28
 
4.0%
자 28
 
4.0%
Other values (62) 338
48.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 483
69.1%
Space Separator 105
 
15.0%
Decimal Number 104
 
14.9%
Dash Punctuation 7
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 31
 
6.4%
주 29
 
6.0%
로 28
 
5.8%
시 28
 
5.8%
포 28
 
5.8%
귀 28
 
5.8%
제 28
 
5.8%
도 28
 
5.8%
자 28
 
5.8%
별 28
 
5.8%
Other values (50) 199
41.2%
Decimal Number
ValueCountFrequency (%)
1 23
22.1%
5 14
13.5%
2 13
12.5%
0 10
9.6%
4 9
 
8.7%
6 8
 
7.7%
7 8
 
7.7%
3 7
 
6.7%
9 6
 
5.8%
8 6
 
5.8%
Space Separator
ValueCountFrequency (%)
105
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 483
69.1%
Common 216
30.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 31
 
6.4%
주 29
 
6.0%
로 28
 
5.8%
시 28
 
5.8%
포 28
 
5.8%
귀 28
 
5.8%
제 28
 
5.8%
도 28
 
5.8%
자 28
 
5.8%
별 28
 
5.8%
Other values (50) 199
41.2%
Common
ValueCountFrequency (%)
105
48.6%
1 23
 
10.6%
5 14
 
6.5%
2 13
 
6.0%
0 10
 
4.6%
4 9
 
4.2%
6 8
 
3.7%
7 8
 
3.7%
- 7
 
3.2%
3 7
 
3.2%
Other values (2) 12
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 483
69.1%
ASCII 216
30.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
105
48.6%
1 23
 
10.6%
5 14
 
6.5%
2 13
 
6.0%
0 10
 
4.6%
4 9
 
4.2%
6 8
 
3.7%
7 8
 
3.7%
- 7
 
3.2%
3 7
 
3.2%
Other values (2) 12
 
5.6%
Hangul
ValueCountFrequency (%)
서 31
 
6.4%
주 29
 
6.0%
로 28
 
5.8%
시 28
 
5.8%
포 28
 
5.8%
귀 28
 
5.8%
제 28
 
5.8%
도 28
 
5.8%
자 28
 
5.8%
별 28
 
5.8%
Other values (50) 199
41.2%

전화번호
Text

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
2024-04-06T18:02:52.334214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters336
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

Unique28 ?
Unique (%)100.0%

Sample

1st row064-787-3320
2nd row064-794-6497
3rd row064-767-3402
4th row064-732-3315
5th row064-792-3690
ValueCountFrequency (%)
064-787-3320 1
 
3.6%
064-794-6497 1
 
3.6%
064-764-4466 1
 
3.6%
064-738-5615 1
 
3.6%
064-738-0301 1
 
3.6%
064-764-8257 1
 
3.6%
064-767-0688 1
 
3.6%
064-792-8253 1
 
3.6%
064-767-3790 1
 
3.6%
064-764-4093 1
 
3.6%
Other values (18) 18
64.3%
2024-04-06T18:02:52.890657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 56
16.7%
0 49
14.6%
6 46
13.7%
4 41
12.2%
7 39
11.6%
3 32
9.5%
2 18
 
5.4%
9 17
 
5.1%
8 16
 
4.8%
1 11
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 280
83.3%
Dash Punctuation 56
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 49
17.5%
6 46
16.4%
4 41
14.6%
7 39
13.9%
3 32
11.4%
2 18
 
6.4%
9 17
 
6.1%
8 16
 
5.7%
1 11
 
3.9%
5 11
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 56
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 336
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 56
16.7%
0 49
14.6%
6 46
13.7%
4 41
12.2%
7 39
11.6%
3 32
9.5%
2 18
 
5.4%
9 17
 
5.1%
8 16
 
4.8%
1 11
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 336
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 56
16.7%
0 49
14.6%
6 46
13.7%
4 41
12.2%
7 39
11.6%
3 32
9.5%
2 18
 
5.4%
9 17
 
5.1%
8 16
 
4.8%
1 11
 
3.3%

팩스번호
Text

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
2024-04-06T18:02:53.233511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.107143
Min length12

Characters and Unicode

Total characters339
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

Unique28 ?
Unique (%)100.0%

Sample

1st row064-787-3323
2nd row064-794-6498
3rd row064-767-3403
4th row064-732-3314
5th row064-792-3691
ValueCountFrequency (%)
064-787-3323 1
 
3.6%
064-794-6498 1
 
3.6%
064-764-5566 1
 
3.6%
064-738-5616 1
 
3.6%
064-738-3350 1
 
3.6%
064-764-8250 1
 
3.6%
064-767-0684 1
 
3.6%
064-792-8252 1
 
3.6%
064-767-3791 1
 
3.6%
064-764-4091 1
 
3.6%
Other values (18) 18
64.3%
2024-04-06T18:02:53.851440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 56
16.5%
6 48
14.2%
4 43
12.7%
0 42
12.4%
7 36
10.6%
3 33
9.7%
2 26
7.7%
9 17
 
5.0%
8 15
 
4.4%
1 12
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 283
83.5%
Dash Punctuation 56
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 48
17.0%
4 43
15.2%
0 42
14.8%
7 36
12.7%
3 33
11.7%
2 26
9.2%
9 17
 
6.0%
8 15
 
5.3%
1 12
 
4.2%
5 11
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 56
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 339
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 56
16.5%
6 48
14.2%
4 43
12.7%
0 42
12.4%
7 36
10.6%
3 33
9.7%
2 26
7.7%
9 17
 
5.0%
8 15
 
4.4%
1 12
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 339
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 56
16.5%
6 48
14.2%
4 43
12.7%
0 42
12.4%
7 36
10.6%
3 33
9.7%
2 26
7.7%
9 17
 
5.0%
8 15
 
4.4%
1 12
 
3.5%

신고일
Date

Distinct23
Distinct (%)82.1%
Missing0
Missing (%)0.0%
Memory size356.0 B
Minimum2004-12-27 00:00:00
Maximum2021-09-01 00:00:00
2024-04-06T18:02:54.081445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:02:54.336313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)

정원
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)21.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.178571
Minimum19
Maximum39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2024-04-06T18:02:54.518598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19
5-th percentile19
Q129
median29
Q329
95-th percentile39
Maximum39
Range20
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5.4843452
Coefficient of variation (CV)0.18795798
Kurtosis0.43619025
Mean29.178571
Median Absolute Deviation (MAD)0
Skewness-0.19252092
Sum817
Variance30.078042
MonotonicityNot monotonic
2024-04-06T18:02:54.751470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
29 16
57.1%
19 4
 
14.3%
35 3
 
10.7%
39 3
 
10.7%
27 1
 
3.6%
28 1
 
3.6%
ValueCountFrequency (%)
19 4
 
14.3%
27 1
 
3.6%
28 1
 
3.6%
29 16
57.1%
35 3
 
10.7%
39 3
 
10.7%
ValueCountFrequency (%)
39 3
 
10.7%
35 3
 
10.7%
29 16
57.1%
28 1
 
3.6%
27 1
 
3.6%
19 4
 
14.3%

종사자수
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size356.0 B
2
21 
3
7 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 21
75.0%
3 7
 
25.0%

Length

2024-04-06T18:02:54.976311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:02:55.151621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 21
75.0%
3 7
 
25.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size356.0 B
Minimum2024-03-27 00:00:00
Maximum2024-03-27 00:00:00
2024-04-06T18:02:55.297740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:02:55.441746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-04-06T18:02:49.547116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T18:02:55.561548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
센터명주소전화번호팩스번호신고일정원종사자수
센터명1.0001.0001.0001.0001.0001.0001.000
주소1.0001.0001.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.000
팩스번호1.0001.0001.0001.0001.0001.0001.000
신고일1.0001.0001.0001.0001.0000.9360.610
정원1.0001.0001.0001.0000.9361.0000.755
종사자수1.0001.0001.0001.0000.6100.7551.000
2024-04-06T18:02:55.722097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정원종사자수
정원1.0000.836
종사자수0.8361.000

Missing values

2024-04-06T18:02:49.779507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T18:02:50.008895image/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

센터명주소전화번호팩스번호신고일정원종사자수데이터기준일자
0가마제주특별자치도 서귀포시 표선면 일주동로 6276064-787-3320064-787-33232007-03-022922024-03-27
1감산제주특별자치도 서귀포시 안덕면 감산중로 16-13064-794-6497064-794-64982006-06-261922024-03-27
2다솜제주특별자치도 서귀포시 효돈로 214064-767-3402064-767-34032021-05-182922024-03-27
3담쟁이제주특별자치도 서귀포시 홍중로27번길 30064-732-3315064-732-33142019-11-061922024-03-27
4대정골제주특별자치도 서귀포시 대정읍 추사로55번길 7-4064-792-3690064-792-36912011-10-281922024-03-27
5대정제주특별자치도 서귀포시 대정읍 동일하모로 200064-792-2273064-792-22622005-11-232922024-03-27
6동신파이디온제주특별자치도 서귀포시 동홍중앙로 13064-763-7879064-763-78772007-05-222922024-03-27
7동홍제주특별자치도 서귀포시 동홍중앙로 28064-763-0065064-732-06692010-07-122922024-03-27
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