Overview

Dataset statistics

Number of variables7
Number of observations291
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.0 KiB
Average record size in memory56.4 B

Variable types

Categorical4
Text3

Dataset

Description동대문구의 종교시설 관련 된 자료입니다. 관내 종교시설(기독교, 불교, 천주교, 기타종교시설)의 시설명, 주소, 전화번호 등의 정보를 담고 있습니다.
Author공공데이터포털
URLhttps://www.data.go.kr/data/15117584/fileData.do

Alerts

관리기관명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
종교구분 is highly imbalanced (65.0%)Imbalance

Reproduction

Analysis started2024-04-20 15:59:29.231148
Analysis finished2024-04-20 15:59:30.264274
Duration1.03 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

행정동
Categorical

Distinct14
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
제기동
31 
답십리2동
28 
청량리동
25 
용신동
24 
전농1동
24 
Other values (9)
159 

Length

Max length5
Median length4
Mean length3.9347079
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row답십리1동
2nd row답십리1동
3rd row답십리1동
4th row답십리1동
5th row답십리1동

Common Values

ValueCountFrequency (%)
제기동 31
10.7%
답십리2동 28
9.6%
청량리동 25
8.6%
용신동 24
8.2%
전농1동 24
8.2%
장안2동 23
7.9%
장안1동 22
7.6%
이문1동 21
7.2%
전농2동 21
7.2%
답십리1동 20
 
6.9%
Other values (4) 52
17.9%

Length

2024-04-21T00:59:30.514350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
제기동 31
10.7%
답십리2동 28
9.6%
청량리동 25
8.6%
용신동 24
8.2%
전농1동 24
8.2%
장안2동 23
7.9%
장안1동 22
7.6%
이문1동 21
7.2%
전농2동 21
7.2%
답십리1동 20
 
6.9%
Other values (4) 52
17.9%

종교구분
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
기독교
256 
불교
 
20
기타종교시설
 
8
천주교
 
7

Length

Max length6
Median length3
Mean length3.0137457
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기독교 256
88.0%
불교 20
 
6.9%
기타종교시설 8
 
2.7%
천주교 7
 
2.4%

Length

2024-04-21T00:59:30.952431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:59:31.297698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기독교 256
88.0%
불교 20
 
6.9%
기타종교시설 8
 
2.7%
천주교 7
 
2.4%

시설명
Text

Distinct260
Distinct (%)89.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2024-04-21T00:59:32.215865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length15
Mean length5.4329897
Min length3

Characters and Unicode

Total characters1581
Distinct characters223
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique235 ?
Unique (%)80.8%

Sample

1st row반석침례교회
2nd row경신교회
3rd row답십리교회
4th row경안교회
5th row희망샘교회
ValueCountFrequency (%)
교회 9
 
2.9%
청량사 4
 
1.3%
하나님의 4
 
1.3%
반석교회 3
 
1.0%
벧엘교회 3
 
1.0%
참사랑교회 3
 
1.0%
동대문교회 3
 
1.0%
임마누엘교회 2
 
0.6%
정금교회 2
 
0.6%
새생명교회 2
 
0.6%
Other values (262) 279
88.9%
2024-04-21T00:59:33.314232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 275
 
17.4%
회 262
 
16.6%
동 45
 
2.8%
성 38
 
2.4%
리 36
 
2.3%
23
 
1.5%
사 23
 
1.5%
문 18
 
1.1%
예 17
 
1.1%
안 17
 
1.1%
Other values (213) 827
52.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1541
97.5%
Space Separator 23
 
1.5%
Uppercase Letter 13
 
0.8%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 275
 
17.8%
회 262
 
17.0%
동 45
 
2.9%
성 38
 
2.5%
리 36
 
2.3%
사 23
 
1.5%
문 18
 
1.2%
예 17
 
1.1%
안 17
 
1.1%
일 16
 
1.0%
Other values (201) 794
51.5%
Uppercase Letter
ValueCountFrequency (%)
F 3
23.1%
U 2
15.4%
B 2
15.4%
C 1
 
7.7%
A 1
 
7.7%
I 1
 
7.7%
N 1
 
7.7%
S 1
 
7.7%
G 1
 
7.7%
Space Separator
ValueCountFrequency (%)
23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1541
97.5%
Common 27
 
1.7%
Latin 13
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 275
 
17.8%
회 262
 
17.0%
동 45
 
2.9%
성 38
 
2.5%
리 36
 
2.3%
사 23
 
1.5%
문 18
 
1.2%
예 17
 
1.1%
안 17
 
1.1%
일 16
 
1.0%
Other values (201) 794
51.5%
Latin
ValueCountFrequency (%)
F 3
23.1%
U 2
15.4%
B 2
15.4%
C 1
 
7.7%
A 1
 
7.7%
I 1
 
7.7%
N 1
 
7.7%
S 1
 
7.7%
G 1
 
7.7%
Common
ValueCountFrequency (%)
23
85.2%
( 2
 
7.4%
) 2
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1541
97.5%
ASCII 40
 
2.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 275
 
17.8%
회 262
 
17.0%
동 45
 
2.9%
성 38
 
2.5%
리 36
 
2.3%
사 23
 
1.5%
문 18
 
1.2%
예 17
 
1.1%
안 17
 
1.1%
일 16
 
1.0%
Other values (201) 794
51.5%
ASCII
ValueCountFrequency (%)
23
57.5%
F 3
 
7.5%
( 2
 
5.0%
) 2
 
5.0%
U 2
 
5.0%
B 2
 
5.0%
C 1
 
2.5%
A 1
 
2.5%
I 1
 
2.5%
N 1
 
2.5%
Other values (2) 2
 
5.0%

주소
Text

Distinct287
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2024-04-21T00:59:34.503038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length18
Mean length12.986254
Min length5

Characters and Unicode

Total characters3779
Distinct characters84
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique285 ?
Unique (%)97.9%

Sample

1st row천호대로71길 35 (답십리동)
2nd row답십리로 86 (답십리동)
3rd row사가정로2길 59 (답십리동)
4th row천호대로69가길 21 (답십리동)
5th row전농로5길 5 (답십리동)
ValueCountFrequency (%)
장안동 35
 
4.7%
답십리동 34
 
4.5%
전농동 27
 
3.6%
제기동 22
 
2.9%
이문동 19
 
2.5%
한천로 17
 
2.3%
답십리로 13
 
1.7%
청량리동 13
 
1.7%
휘경동 12
 
1.6%
용두동 10
 
1.3%
Other values (361) 546
73.0%
2024-04-21T00:59:35.945902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
458
 
12.1%
로 291
 
7.7%
1 221
 
5.8%
동 209
 
5.5%
) 202
 
5.3%
( 202
 
5.3%
길 168
 
4.4%
2 146
 
3.9%
3 124
 
3.3%
4 106
 
2.8%
Other values (74) 1652
43.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1878
49.7%
Decimal Number 992
26.3%
Space Separator 458
 
12.1%
Close Punctuation 202
 
5.3%
Open Punctuation 202
 
5.3%
Dash Punctuation 47
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 291
 
15.5%
동 209
 
11.1%
길 168
 
8.9%
리 86
 
4.6%
답 72
 
3.8%
십 72
 
3.8%
기 62
 
3.3%
천 59
 
3.1%
장 56
 
3.0%
한 55
 
2.9%
Other values (60) 748
39.8%
Decimal Number
ValueCountFrequency (%)
1 221
22.3%
2 146
14.7%
3 124
12.5%
4 106
10.7%
5 77
 
7.8%
7 69
 
7.0%
6 68
 
6.9%
8 64
 
6.5%
0 60
 
6.0%
9 57
 
5.7%
Space Separator
ValueCountFrequency (%)
458
100.0%
Close Punctuation
ValueCountFrequency (%)
) 202
100.0%
Open Punctuation
ValueCountFrequency (%)
( 202
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 47
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1901
50.3%
Hangul 1878
49.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 291
 
15.5%
동 209
 
11.1%
길 168
 
8.9%
리 86
 
4.6%
답 72
 
3.8%
십 72
 
3.8%
기 62
 
3.3%
천 59
 
3.1%
장 56
 
3.0%
한 55
 
2.9%
Other values (60) 748
39.8%
Common
ValueCountFrequency (%)
458
24.1%
1 221
11.6%
) 202
10.6%
( 202
10.6%
2 146
 
7.7%
3 124
 
6.5%
4 106
 
5.6%
5 77
 
4.1%
7 69
 
3.6%
6 68
 
3.6%
Other values (4) 228
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1901
50.3%
Hangul 1878
49.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
458
24.1%
1 221
11.6%
) 202
10.6%
( 202
10.6%
2 146
 
7.7%
3 124
 
6.5%
4 106
 
5.6%
5 77
 
4.1%
7 69
 
3.6%
6 68
 
3.6%
Other values (4) 228
12.0%
Hangul
ValueCountFrequency (%)
로 291
 
15.5%
동 209
 
11.1%
길 168
 
8.9%
리 86
 
4.6%
답 72
 
3.8%
십 72
 
3.8%
기 62
 
3.3%
천 59
 
3.1%
장 56
 
3.0%
한 55
 
2.9%
Other values (60) 748
39.8%

전화번호
Text

Distinct247
Distinct (%)84.9%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2024-04-21T00:59:36.857208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length11.714777
Min length11

Characters and Unicode

Total characters3409
Distinct characters14
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique245 ?
Unique (%)84.2%

Sample

1st row02-2245-8604
2nd row02-2212-9776
3rd row02-2246-4949
4th row02-2245-0054
5th row02-2244-2567
ValueCountFrequency (%)
02-0000-0000 44
 
15.1%
02-966-1505 2
 
0.7%
02-2249-4785 1
 
0.3%
02-967-0806 1
 
0.3%
02-2215-3691 1
 
0.3%
02-3295-0691 1
 
0.3%
02-2245-8604 1
 
0.3%
02-923-2745 1
 
0.3%
02-927-3831 1
 
0.3%
02-926-1406 1
 
0.3%
Other values (237) 237
81.4%
2024-04-21T00:59:38.019796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 800
23.5%
2 671
19.7%
- 582
17.1%
9 227
 
6.7%
4 200
 
5.9%
6 190
 
5.6%
1 190
 
5.6%
5 145
 
4.3%
3 143
 
4.2%
7 131
 
3.8%
Other values (4) 130
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2823
82.8%
Dash Punctuation 582
 
17.1%
Math Symbol 2
 
0.1%
Other Punctuation 1
 
< 0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 800
28.3%
2 671
23.8%
9 227
 
8.0%
4 200
 
7.1%
6 190
 
6.7%
1 190
 
6.7%
5 145
 
5.1%
3 143
 
5.1%
7 131
 
4.6%
8 126
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 582
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Other Punctuation
ValueCountFrequency (%)
? 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3409
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 800
23.5%
2 671
19.7%
- 582
17.1%
9 227
 
6.7%
4 200
 
5.9%
6 190
 
5.6%
1 190
 
5.6%
5 145
 
4.3%
3 143
 
4.2%
7 131
 
3.8%
Other values (4) 130
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3409
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 800
23.5%
2 671
19.7%
- 582
17.1%
9 227
 
6.7%
4 200
 
5.9%
6 190
 
5.6%
1 190
 
5.6%
5 145
 
4.3%
3 143
 
4.2%
7 131
 
3.8%
Other values (4) 130
 
3.8%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
서울특별시 동대문구청
291 

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울특별시 동대문구청
2nd row서울특별시 동대문구청
3rd row서울특별시 동대문구청
4th row서울특별시 동대문구청
5th row서울특별시 동대문구청

Common Values

ValueCountFrequency (%)
서울특별시 동대문구청 291
100.0%

Length

2024-04-21T00:59:38.251911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:59:38.411606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 291
50.0%
동대문구청 291
50.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2023-08-01
291 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-01
2nd row2023-08-01
3rd row2023-08-01
4th row2023-08-01
5th row2023-08-01

Common Values

ValueCountFrequency (%)
2023-08-01 291
100.0%

Length

2024-04-21T00:59:38.575351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T00:59:38.736428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-01 291
100.0%

Correlations

2024-04-21T00:59:38.828810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동종교구분
행정동1.0000.225
종교구분0.2251.000
2024-04-21T00:59:38.967461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동종교구분
행정동1.0000.126
종교구분0.1261.000
2024-04-21T00:59:39.099878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동종교구분
행정동1.0000.126
종교구분0.1261.000

Missing values

2024-04-21T00:59:29.743025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T00:59:30.119742image/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

행정동종교구분시설명주소전화번호관리기관명데이터기준일자
0답십리1동기독교반석침례교회천호대로71길 35 (답십리동)02-2245-8604서울특별시 동대문구청2023-08-01
1답십리1동기독교경신교회답십리로 86 (답십리동)02-2212-9776서울특별시 동대문구청2023-08-01
2답십리1동기독교답십리교회사가정로2길 59 (답십리동)02-2246-4949서울특별시 동대문구청2023-08-01
3답십리1동기독교경안교회천호대로69가길 21 (답십리동)02-2245-0054서울특별시 동대문구청2023-08-01
4답십리1동기독교희망샘교회전농로5길 5 (답십리동)02-2244-2567서울특별시 동대문구청2023-08-01
5답십리1동기독교동명교회답십리로 136(답십리동)02-2241-7191서울특별시 동대문구청2023-08-01
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