Overview

Dataset statistics

Number of variables6
Number of observations27
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 KiB
Average record size in memory53.9 B

Variable types

Numeric1
Text4
Categorical1

Dataset

Description노원구에 위치한 아이휴센터 현황에 대한 데이터로 시설명, 행정동명, 연락처, 주소, 기준일자등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15068437/fileData.do

Alerts

기준일자 has constant value ""Constant
연번 has unique valuesUnique
시설명 has unique valuesUnique
연락처 has unique valuesUnique
주소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 20:55:14.484621
Analysis finished2023-12-12 20:55:15.014050
Duration0.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14
Minimum1
Maximum27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-13T05:55:15.085191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.3
Q17.5
median14
Q320.5
95-th percentile25.7
Maximum27
Range26
Interquartile range (IQR)13

Descriptive statistics

Standard deviation7.9372539
Coefficient of variation (CV)0.56694671
Kurtosis-1.2
Mean14
Median Absolute Deviation (MAD)7
Skewness0
Sum378
Variance63
MonotonicityStrictly increasing
2023-12-13T05:55:15.220994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
1 1
 
3.7%
2 1
 
3.7%
27 1
 
3.7%
26 1
 
3.7%
25 1
 
3.7%
24 1
 
3.7%
23 1
 
3.7%
22 1
 
3.7%
21 1
 
3.7%
20 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
1 1
3.7%
2 1
3.7%
3 1
3.7%
4 1
3.7%
5 1
3.7%
6 1
3.7%
7 1
3.7%
8 1
3.7%
9 1
3.7%
10 1
3.7%
ValueCountFrequency (%)
27 1
3.7%
26 1
3.7%
25 1
3.7%
24 1
3.7%
23 1
3.7%
22 1
3.7%
21 1
3.7%
20 1
3.7%
19 1
3.7%
18 1
3.7%

시설명
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-13T05:55:15.450576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.1111111
Min length3

Characters and Unicode

Total characters138
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

Unique27 ?
Unique (%)100.0%

Sample

1st row월계문화
2nd row상계10단지
3rd row상계5간촌
4th row달빛마실
5th row상계3단지
ValueCountFrequency (%)
월계문화 1
 
3.7%
상계동아불암 1
 
3.7%
중계온마을 1
 
3.7%
하계어울림융합형 1
 
3.7%
공릉비선 1
 
3.7%
노원융합형 1
 
3.7%
상계보람2단지 1
 
3.7%
상계12단지 1
 
3.7%
상계두산융합형 1
 
3.7%
중계무지개 1
 
3.7%
Other values (17) 17
63.0%
2023-12-13T05:55:15.824373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
계 20
 
14.5%
상 12
 
8.7%
지 10
 
7.2%
단 9
 
6.5%
1 5
 
3.6%
융 3
 
2.2%
마 3
 
2.2%
동 3
 
2.2%
중 3
 
2.2%
월 3
 
2.2%
Other values (52) 67
48.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 124
89.9%
Decimal Number 14
 
10.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
계 20
 
16.1%
상 12
 
9.7%
지 10
 
8.1%
단 9
 
7.3%
융 3
 
2.4%
마 3
 
2.4%
동 3
 
2.4%
중 3
 
2.4%
월 3
 
2.4%
공 3
 
2.4%
Other values (45) 55
44.4%
Decimal Number
ValueCountFrequency (%)
1 5
35.7%
2 3
21.4%
5 2
 
14.3%
3 1
 
7.1%
0 1
 
7.1%
7 1
 
7.1%
6 1
 
7.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 124
89.9%
Common 14
 
10.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
계 20
 
16.1%
상 12
 
9.7%
지 10
 
8.1%
단 9
 
7.3%
융 3
 
2.4%
마 3
 
2.4%
동 3
 
2.4%
중 3
 
2.4%
월 3
 
2.4%
공 3
 
2.4%
Other values (45) 55
44.4%
Common
ValueCountFrequency (%)
1 5
35.7%
2 3
21.4%
5 2
 
14.3%
3 1
 
7.1%
0 1
 
7.1%
7 1
 
7.1%
6 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 124
89.9%
ASCII 14
 
10.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
계 20
 
16.1%
상 12
 
9.7%
지 10
 
8.1%
단 9
 
7.3%
융 3
 
2.4%
마 3
 
2.4%
동 3
 
2.4%
중 3
 
2.4%
월 3
 
2.4%
공 3
 
2.4%
Other values (45) 55
44.4%
ASCII
ValueCountFrequency (%)
1 5
35.7%
2 3
21.4%
5 2
 
14.3%
3 1
 
7.1%
0 1
 
7.1%
7 1
 
7.1%
6 1
 
7.1%

동명
Text

Distinct18
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-13T05:55:16.027602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.4814815
Min length4

Characters and Unicode

Total characters121
Distinct characters20
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

Unique11 ?
Unique (%)40.7%

Sample

1st row월계1동
2nd row상계8동
3rd row상계5동
4th row월계1동
5th row상계6.7동
ValueCountFrequency (%)
상계6.7동 4
14.8%
공릉2동 2
 
7.4%
상계9동 2
 
7.4%
상계8동 2
 
7.4%
상계1동 2
 
7.4%
월계1동 2
 
7.4%
상계5동 2
 
7.4%
하계1동 1
 
3.7%
상계3.4동 1
 
3.7%
중계4동 1
 
3.7%
Other values (8) 8
29.6%
2023-12-13T05:55:16.357003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 27
22.3%
계 24
19.8%
상 14
11.6%
1 8
 
6.6%
. 6
 
5.0%
2 5
 
4.1%
6 4
 
3.3%
7 4
 
3.3%
중 4
 
3.3%
월 4
 
3.3%
Other values (10) 21
17.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 82
67.8%
Decimal Number 33
27.3%
Other Punctuation 6
 
5.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 8
24.2%
2 5
15.2%
6 4
12.1%
7 4
12.1%
3 3
 
9.1%
9 2
 
6.1%
8 2
 
6.1%
5 2
 
6.1%
4 2
 
6.1%
0 1
 
3.0%
Other Letter
ValueCountFrequency (%)
동 27
32.9%
계 24
29.3%
상 14
17.1%
중 4
 
4.9%
월 4
 
4.9%
공 3
 
3.7%
릉 3
 
3.7%
하 2
 
2.4%
본 1
 
1.2%
Other Punctuation
ValueCountFrequency (%)
. 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 82
67.8%
Common 39
32.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 8
20.5%
. 6
15.4%
2 5
12.8%
6 4
10.3%
7 4
10.3%
3 3
 
7.7%
9 2
 
5.1%
8 2
 
5.1%
5 2
 
5.1%
4 2
 
5.1%
Hangul
ValueCountFrequency (%)
동 27
32.9%
계 24
29.3%
상 14
17.1%
중 4
 
4.9%
월 4
 
4.9%
공 3
 
3.7%
릉 3
 
3.7%
하 2
 
2.4%
본 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 82
67.8%
ASCII 39
32.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 27
32.9%
계 24
29.3%
상 14
17.1%
중 4
 
4.9%
월 4
 
4.9%
공 3
 
3.7%
릉 3
 
3.7%
하 2
 
2.4%
본 1
 
1.2%
ASCII
ValueCountFrequency (%)
1 8
20.5%
. 6
15.4%
2 5
12.8%
6 4
10.3%
7 4
10.3%
3 3
 
7.7%
9 2
 
5.1%
8 2
 
5.1%
5 2
 
5.1%
4 2
 
5.1%

연락처
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-13T05:55:16.558390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length11.296296
Min length11

Characters and Unicode

Total characters305
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

Unique27 ?
Unique (%)100.0%

Sample

1st row02-909-3273
2nd row070-4245-1172
3rd row02-931-8437
4th row02-943-0045
5th row02-930-8669
ValueCountFrequency (%)
02-909-3273 1
 
3.7%
02-951-1102 1
 
3.7%
02-933-0128 1
 
3.7%
02-979-7714 1
 
3.7%
02-973-7373 1
 
3.7%
02-939-1128 1
 
3.7%
02-934-0208 1
 
3.7%
02-3392-0010 1
 
3.7%
02-6956-9480 1
 
3.7%
02-3296-5265 1
 
3.7%
Other values (17) 17
63.0%
2023-12-13T05:55:16.930972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 54
17.7%
0 51
16.7%
2 45
14.8%
9 35
11.5%
1 31
10.2%
3 25
8.2%
7 16
 
5.2%
4 13
 
4.3%
5 13
 
4.3%
8 11
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 251
82.3%
Dash Punctuation 54
 
17.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 51
20.3%
2 45
17.9%
9 35
13.9%
1 31
12.4%
3 25
10.0%
7 16
 
6.4%
4 13
 
5.2%
5 13
 
5.2%
8 11
 
4.4%
6 11
 
4.4%
Dash Punctuation
ValueCountFrequency (%)
- 54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 305
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 54
17.7%
0 51
16.7%
2 45
14.8%
9 35
11.5%
1 31
10.2%
3 25
8.2%
7 16
 
5.2%
4 13
 
4.3%
5 13
 
4.3%
8 11
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 305
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 54
17.7%
0 51
16.7%
2 45
14.8%
9 35
11.5%
1 31
10.2%
3 25
8.2%
7 16
 
5.2%
4 13
 
4.3%
5 13
 
4.3%
8 11
 
3.6%

주소
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-13T05:55:17.185848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length37
Mean length34.407407
Min length21

Characters and Unicode

Total characters929
Distinct characters94
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)100.0%

Sample

1st row서울시 노원구 월계로42길 9, 2층(월계동, 월계문화복지센터)
2nd row서울시 노원구 노원로 564, 1021동 104호(상계주공10단지)
3rd row서울시 노원구 한글비석로49길 36, 1층(상계동)
4th row서울시 노원구 광운로13길 9(월계동)
5th row서울시 노원구 동일로215길 48, 326동 112호(상계주공3단지)
ValueCountFrequency (%)
서울시 27
 
17.4%
노원구 26
 
16.8%
한글비석로 3
 
1.9%
관리동 2
 
1.3%
102동 2
 
1.3%
섬밭로 2
 
1.3%
53 1
 
0.6%
동일로241길 1
 
0.6%
104호(중계무지개아파트 1
 
0.6%
201동 1
 
0.6%
Other values (89) 89
57.4%
2023-12-13T05:55:17.563789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
128
 
13.8%
1 67
 
7.2%
2 38
 
4.1%
0 37
 
4.0%
동 35
 
3.8%
노 28
 
3.0%
울 28
 
3.0%
계 28
 
3.0%
, 28
 
3.0%
서 27
 
2.9%
Other values (84) 485
52.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 489
52.6%
Decimal Number 231
24.9%
Space Separator 128
 
13.8%
Other Punctuation 28
 
3.0%
Open Punctuation 26
 
2.8%
Close Punctuation 26
 
2.8%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 35
 
7.2%
노 28
 
5.7%
울 28
 
5.7%
계 28
 
5.7%
서 27
 
5.5%
시 27
 
5.5%
원 27
 
5.5%
구 27
 
5.5%
로 27
 
5.5%
호 17
 
3.5%
Other values (69) 218
44.6%
Decimal Number
ValueCountFrequency (%)
1 67
29.0%
2 38
16.5%
0 37
16.0%
3 19
 
8.2%
4 16
 
6.9%
6 15
 
6.5%
5 13
 
5.6%
8 10
 
4.3%
7 9
 
3.9%
9 7
 
3.0%
Space Separator
ValueCountFrequency (%)
128
100.0%
Other Punctuation
ValueCountFrequency (%)
, 28
100.0%
Open Punctuation
ValueCountFrequency (%)
( 26
100.0%
Close Punctuation
ValueCountFrequency (%)
) 26
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 489
52.6%
Common 440
47.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 35
 
7.2%
노 28
 
5.7%
울 28
 
5.7%
계 28
 
5.7%
서 27
 
5.5%
시 27
 
5.5%
원 27
 
5.5%
구 27
 
5.5%
로 27
 
5.5%
호 17
 
3.5%
Other values (69) 218
44.6%
Common
ValueCountFrequency (%)
128
29.1%
1 67
15.2%
2 38
 
8.6%
0 37
 
8.4%
, 28
 
6.4%
( 26
 
5.9%
) 26
 
5.9%
3 19
 
4.3%
4 16
 
3.6%
6 15
 
3.4%
Other values (5) 40
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 489
52.6%
ASCII 440
47.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
128
29.1%
1 67
15.2%
2 38
 
8.6%
0 37
 
8.4%
, 28
 
6.4%
( 26
 
5.9%
) 26
 
5.9%
3 19
 
4.3%
4 16
 
3.6%
6 15
 
3.4%
Other values (5) 40
 
9.1%
Hangul
ValueCountFrequency (%)
동 35
 
7.2%
노 28
 
5.7%
울 28
 
5.7%
계 28
 
5.7%
서 27
 
5.5%
시 27
 
5.5%
원 27
 
5.5%
구 27
 
5.5%
로 27
 
5.5%
호 17
 
3.5%
Other values (69) 218
44.6%

기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-07-25
27 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-07-25
2nd row2023-07-25
3rd row2023-07-25
4th row2023-07-25
5th row2023-07-25

Common Values

ValueCountFrequency (%)
2023-07-25 27
100.0%

Length

2023-12-13T05:55:17.682267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:55:17.766335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-07-25 27
100.0%

Interactions

2023-12-13T05:55:14.741788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:55:17.823314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시설명동명연락처주소
연번1.0001.0000.5941.0001.000
시설명1.0001.0001.0001.0001.000
동명0.5941.0001.0001.0001.000
연락처1.0001.0001.0001.0001.000
주소1.0001.0001.0001.0001.000

Missing values

2023-12-13T05:55:14.861765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:55:14.968907image/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

연번시설명동명연락처주소기준일자
01월계문화월계1동02-909-3273서울시 노원구 월계로42길 9, 2층(월계동, 월계문화복지센터)2023-07-25
12상계10단지상계8동070-4245-1172서울시 노원구 노원로 564, 1021동 104호(상계주공10단지)2023-07-25
23상계5간촌상계5동02-931-8437서울시 노원구 한글비석로49길 36, 1층(상계동)2023-07-25
34달빛마실월계1동02-943-0045서울시 노원구 광운로13길 9(월계동)2023-07-25
45상계3단지상계6.7동02-930-8669서울시 노원구 동일로215길 48, 326동 112호(상계주공3단지)2023-07-25
56공릉태강공릉2동02-948-9084서울시 노원구 공릉로34길 62, 1002동 101호(공릉태강아파트)2023-07-25
67하계극동하계2동02-3296-6412서울시 노원구 섬밭로 229, 3동 111호(하계극동아파트)2023-07-25
78월계그랑빌월계3동02-972-1252서울시 노원구 마들로 31, 115동104호(월계그랑빌아파트)2023-07-25
89상계7단지상계10동02-6227-0101서울시 노원구 상계로1길 92, 718동 1층 106호(상계주공7단지)2023-07-25
910공릉라이프공릉1동02-971-5650서울시 노원구 섬밭로 123, 관리동 2층(공릉라이프아파트)2023-07-25
연번시설명동명연락처주소기준일자
1718상계1단지상계6.7동02-936-1101서울시 노원구 동일로213길 21, 111동 101호(상계주공1단지)2023-07-25
1819중계무지개중계2.3동02-3296-5265서울시 노원구 동일로208길 19, 201동 104호(중계무지개아파트)2023-07-25
1920상계두산융합형상계1동02-6956-9480서울시 노원구 동일로241길 53, 관리동 2층(상계두산아파트)2023-07-25
2021상계12단지상계9동02-3392-0010서울시 노원구 한글비석로 530, 1207동 106호(상계주공12단지)2023-07-25
2122상계보람2단지상계9동02-934-0208서울시 노원구 한글비석로 480, 208동 102호(상계보람2단지)2023-07-25
2223노원융합형상계6.7동02-939-1128서울시 덕릉로70길 100, 아이돌봄센터 2층(상계동)2023-07-25
2324공릉비선공릉2동02-973-7373서울시 노원구 화랑로51길 78, 504동 105호2023-07-25
2425하계어울림융합형하계1동02-979-7714서울시 노원구 공릉로62길 18, 3층(하계어울림센터)2023-07-25
2526중계온마을중계4동02-933-0128서울시 노원구 한글비석로 371, 가동 1층(중계온마을센터)2023-07-25
2627중계청구2차중계1동02-930-0110서울시 노원구 중계로 233, 101동 104호(중계청구3차)2023-07-25