Overview

Dataset statistics

Number of variables5
Number of observations324
Missing cells95
Missing cells (%)5.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.8 KiB
Average record size in memory40.4 B

Variable types

Categorical2
Text3

Dataset

Description서울특별시 강동구 관내 종교시설현황(사찰, 교회, 성당 등)을 공공데이터로 제공합니다. 제공 항목: 구분(사찰, 교회, 성당 등), 명칭, 소재지, 행정동, 연락처 입니다. (연락처의 경우 미집계 또는 개인정보 공개 거부 등에 의하여 공란이 존재할 수 있습니다.)
Author서울특별시 강동구
URLhttps://www.data.go.kr/data/15011654/fileData.do

Alerts

구분 is highly imbalanced (66.0%)Imbalance
연락처 has 95 (29.3%) missing valuesMissing

Reproduction

Analysis started2023-12-11 23:54:38.343855
Analysis finished2023-12-11 23:54:38.703038
Duration0.36 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
교회
293 
사찰
 
22
성당
 
9

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
교회 293
90.4%
사찰 22
 
6.8%
성당 9
 
2.8%

Length

2023-12-12T08:54:38.757669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:54:38.859194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
교회 293
90.4%
사찰 22
 
6.8%
성당 9
 
2.8%

명칭
Text

Distinct291
Distinct (%)89.8%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2023-12-12T08:54:39.168465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length4.6697531
Min length2

Characters and Unicode

Total characters1513
Distinct characters199
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

Unique262 ?
Unique (%)80.9%

Sample

1st row가까운교회
2nd row강일교회
3rd row강일주사랑교회
4th row대명교회
5th row동광교회
ValueCountFrequency (%)
성당 9
 
2.6%
강동교회 5
 
1.5%
열린문교회 3
 
0.9%
소망교회 3
 
0.9%
아름다운교회 2
 
0.6%
벧엘교회 2
 
0.6%
삼일교회 2
 
0.6%
순복음 2
 
0.6%
우리교회 2
 
0.6%
아멘교회 2
 
0.6%
Other values (287) 310
90.6%
2023-12-12T08:54:39.653741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 280
 
18.5%
회 274
 
18.1%
성 52
 
3.4%
동 47
 
3.1%
사 29
 
1.9%
일 24
 
1.6%
광 21
 
1.4%
강 19
 
1.3%
19
 
1.3%
한 18
 
1.2%
Other values (189) 730
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1486
98.2%
Space Separator 19
 
1.3%
Open Punctuation 4
 
0.3%
Close Punctuation 4
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 280
 
18.8%
회 274
 
18.4%
성 52
 
3.5%
동 47
 
3.2%
사 29
 
2.0%
일 24
 
1.6%
광 21
 
1.4%
강 19
 
1.3%
한 18
 
1.2%
명 15
 
1.0%
Other values (186) 707
47.6%
Space Separator
ValueCountFrequency (%)
19
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1486
98.2%
Common 27
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 280
 
18.8%
회 274
 
18.4%
성 52
 
3.5%
동 47
 
3.2%
사 29
 
2.0%
일 24
 
1.6%
광 21
 
1.4%
강 19
 
1.3%
한 18
 
1.2%
명 15
 
1.0%
Other values (186) 707
47.6%
Common
ValueCountFrequency (%)
19
70.4%
( 4
 
14.8%
) 4
 
14.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1486
98.2%
ASCII 27
 
1.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 280
 
18.8%
회 274
 
18.4%
성 52
 
3.5%
동 47
 
3.2%
사 29
 
2.0%
일 24
 
1.6%
광 21
 
1.4%
강 19
 
1.3%
한 18
 
1.2%
명 15
 
1.0%
Other values (186) 707
47.6%
ASCII
ValueCountFrequency (%)
19
70.4%
( 4
 
14.8%
) 4
 
14.8%

소재지
Text

Distinct318
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2023-12-12T08:54:39.928044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length34
Mean length22.916667
Min length12

Characters and Unicode

Total characters7425
Distinct characters102
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique314 ?
Unique (%)96.9%

Sample

1st row서울시 강동구 아리수로98길 25 2층(강일동)
2nd row서울시 강동구 아리수로93길 91(강일동)
3rd row서울시 강동구 아리수로93길 38 (강일동)
4th row서울시 강동구 아리수로94길 91(강일동)
5th row서울시 강동구 고덕로 459(강일동)
ValueCountFrequency (%)
서울시 323
22.2%
강동구 316
21.7%
천호동 46
 
3.2%
암사동 42
 
2.9%
명일동 18
 
1.2%
성내동 18
 
1.2%
고덕동 17
 
1.2%
명일로 17
 
1.2%
구천면로 15
 
1.0%
천중로 10
 
0.7%
Other values (461) 635
43.6%
2023-12-12T08:54:40.392324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1142
 
15.4%
동 664
 
8.9%
구 349
 
4.7%
강 341
 
4.6%
시 326
 
4.4%
서 325
 
4.4%
울 325
 
4.4%
( 298
 
4.0%
) 297
 
4.0%
로 293
 
3.9%
Other values (92) 3065
41.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4224
56.9%
Decimal Number 1363
 
18.4%
Space Separator 1143
 
15.4%
Open Punctuation 298
 
4.0%
Close Punctuation 297
 
4.0%
Dash Punctuation 77
 
1.0%
Other Punctuation 22
 
0.3%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 664
15.7%
구 349
 
8.3%
강 341
 
8.1%
시 326
 
7.7%
서 325
 
7.7%
울 325
 
7.7%
로 293
 
6.9%
길 256
 
6.1%
천 139
 
3.3%
성 96
 
2.3%
Other values (74) 1110
26.3%
Decimal Number
ValueCountFrequency (%)
1 273
20.0%
2 176
12.9%
3 162
11.9%
4 129
9.5%
5 122
9.0%
6 120
8.8%
8 103
 
7.6%
7 99
 
7.3%
0 90
 
6.6%
9 89
 
6.5%
Space Separator
ValueCountFrequency (%)
1142
99.9%
　 1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
, 21
95.5%
@ 1
 
4.5%
Open Punctuation
ValueCountFrequency (%)
( 298
100.0%
Close Punctuation
ValueCountFrequency (%)
) 297
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 77
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4224
56.9%
Common 3200
43.1%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 664
15.7%
구 349
 
8.3%
강 341
 
8.1%
시 326
 
7.7%
서 325
 
7.7%
울 325
 
7.7%
로 293
 
6.9%
길 256
 
6.1%
천 139
 
3.3%
성 96
 
2.3%
Other values (74) 1110
26.3%
Common
ValueCountFrequency (%)
1142
35.7%
( 298
 
9.3%
) 297
 
9.3%
1 273
 
8.5%
2 176
 
5.5%
3 162
 
5.1%
4 129
 
4.0%
5 122
 
3.8%
6 120
 
3.8%
8 103
 
3.2%
Other values (7) 378
 
11.8%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4224
56.9%
ASCII 3200
43.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1142
35.7%
( 298
 
9.3%
) 297
 
9.3%
1 273
 
8.5%
2 176
 
5.5%
3 162
 
5.1%
4 129
 
4.0%
5 122
 
3.8%
6 120
 
3.8%
8 103
 
3.2%
Other values (7) 378
 
11.8%
Hangul
ValueCountFrequency (%)
동 664
15.7%
구 349
 
8.3%
강 341
 
8.1%
시 326
 
7.7%
서 325
 
7.7%
울 325
 
7.7%
로 293
 
6.9%
길 256
 
6.1%
천 139
 
3.3%
성 96
 
2.3%
Other values (74) 1110
26.3%
None
ValueCountFrequency (%)
　 1
100.0%

행정동
Categorical

Distinct11
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
성내동
64 
길동
54 
암사동
49 
천호동
49 
둔촌동
36 
Other values (6)
72 

Length

Max length3
Median length3
Mean length2.8271605
Min length1

Unique

Unique2 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
성내동 64
19.8%
길동 54
16.7%
암사동 49
15.1%
천호동 49
15.1%
둔촌동 36
11.1%
고덕동 22
 
6.8%
명일동 21
 
6.5%
강일동 17
 
5.2%
상일동 10
 
3.1%
1
 
0.3%

Length

2023-12-12T08:54:40.528322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
성내동 64
19.8%
길동 54
16.7%
암사동 49
15.2%
천호동 49
15.2%
둔촌동 36
11.1%
고덕동 22
 
6.8%
명일동 21
 
6.5%
강일동 17
 
5.3%
상일동 10
 
3.1%
풍납동 1
 
0.3%

연락처
Text

MISSING 

Distinct225
Distinct (%)98.3%
Missing95
Missing (%)29.3%
Memory size2.7 KiB
2023-12-12T08:54:40.788901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length11.104803
Min length11

Characters and Unicode

Total characters2543
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

Unique221 ?
Unique (%)96.5%

Sample

1st row02-470-8291
2nd row02-429-0898
3rd row02-478-9400
4th row02-481-2040
5th row02-428-6822
ValueCountFrequency (%)
02-483-0185 2
 
0.9%
02-3426-0691 2
 
0.9%
02-441-9002 2
 
0.9%
02-441-1236 2
 
0.9%
02-2296-1586 1
 
0.4%
02-426-1045 1
 
0.4%
02-470-8291 1
 
0.4%
02-481-2004 1
 
0.4%
02-481-1698 1
 
0.4%
02-442-3426 1
 
0.4%
Other values (215) 215
93.9%
2023-12-12T08:54:41.198693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 458
18.0%
2 405
15.9%
0 374
14.7%
4 334
13.1%
7 199
7.8%
8 174
 
6.8%
1 172
 
6.8%
9 121
 
4.8%
6 115
 
4.5%
3 109
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2085
82.0%
Dash Punctuation 458
 
18.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 405
19.4%
0 374
17.9%
4 334
16.0%
7 199
9.5%
8 174
8.3%
1 172
8.2%
9 121
 
5.8%
6 115
 
5.5%
3 109
 
5.2%
5 82
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 458
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2543
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 458
18.0%
2 405
15.9%
0 374
14.7%
4 334
13.1%
7 199
7.8%
8 174
 
6.8%
1 172
 
6.8%
9 121
 
4.8%
6 115
 
4.5%
3 109
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2543
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 458
18.0%
2 405
15.9%
0 374
14.7%
4 334
13.1%
7 199
7.8%
8 174
 
6.8%
1 172
 
6.8%
9 121
 
4.8%
6 115
 
4.5%
3 109
 
4.3%

Correlations

2023-12-12T08:54:41.287348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분행정동
구분1.0000.400
행정동0.4001.000
2023-12-12T08:54:41.602159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동구분
행정동1.0000.253
구분0.2531.000
2023-12-12T08:54:41.673168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분행정동
구분1.0000.253
행정동0.2531.000

Missing values

2023-12-12T08:54:38.585880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:54:38.671083image/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

구분명칭소재지행정동연락처
0교회가까운교회서울시 강동구 아리수로98길 25 2층(강일동)강일동02-470-8291
1교회강일교회서울시 강동구 아리수로93길 91(강일동)강일동02-429-0898
2교회강일주사랑교회서울시 강동구 아리수로93길 38 (강일동)강일동02-478-9400
3교회대명교회서울시 강동구 아리수로94길 91(강일동)강일동02-481-2040
4교회동광교회서울시 강동구 고덕로 459(강일동)강일동02-428-6822
5교회동부교회서울시 강동구 아리수로93가길 34(강일동)강일동02-441-3003
6교회보라성교회서울시 강동구 상일로12길 83 (강일동)강일동02-442-1677
7교회성민교회서울시 강동구 청뜰로 34(강일동)강일동02-3427-0694
8교회수림교회서울시 강동구 상일로 136(강일동)강일동02-441-3217
9교회아름다운강일교회서울시 강동구 아리수로94길 19(강일동)강일동02-442-0191
구분명칭소재지행정동연락처
314사찰천불사서울시 강동구 구천면로47가길 8-16(암사1동 485-25)암사동02-428-8194
315성당천호동 성당서울시 강동구 구천면로 236-1천호동02-470-5821
316성당명일동 성당서울시 강동구 양재대로 56길 28명일동02-481-0211
317성당고덕동 성당서울시 강동구 고덕로 83길 68고덕동02-429-3421
318성당길 동 성당서울시 강동구 명일로296길동02-488-3561
319성당둔촌동 성당서울시 강동구 풍성로 241둔촌동02-482-1841
320성당암사동 성당서울시 강동구 암사길 46암사동02-442-8511
321성당성내동 성당서울시 강동구 성내로 15길 58성내동02-478-4181
322성당강일동 성당서울시 강동구 구천면로 236-8강일동02-442-1244
323성당풍납동 성당서울시 강동구 토성로19길 21풍납동02-482-8151