Overview

Dataset statistics

Number of variables6
Number of observations424
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory20.4 KiB
Average record size in memory49.3 B

Variable types

Numeric1
Categorical3
Text2

Dataset

Description서울특별시 구로구 관내에 소재하고 있는 종교시설 현황에 관한 데이터입니다. 항목은 연번, 종교구분, 시설명, 주소, 행정동, 데이터기준일자로 되어있습니다.
Author공공데이터포털
URLhttps://www.data.go.kr/data/15117705/fileData.do

Alerts

데이터기준일 has constant value ""Constant
연번 is highly overall correlated with 종교구분 and 1 other fieldsHigh correlation
종교구분 is highly overall correlated with 연번High correlation
행정동 is highly overall correlated with 연번High correlation
종교구분 is highly imbalanced (73.0%)Imbalance
연번 has unique valuesUnique

Reproduction

Analysis started2024-04-17 08:58:41.256191
Analysis finished2024-04-17 08:58:41.737134
Duration0.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct424
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean212.5
Minimum1
Maximum424
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-04-17T17:58:41.796679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile22.15
Q1106.75
median212.5
Q3318.25
95-th percentile402.85
Maximum424
Range423
Interquartile range (IQR)211.5

Descriptive statistics

Standard deviation122.54251
Coefficient of variation (CV)0.57667063
Kurtosis-1.2
Mean212.5
Median Absolute Deviation (MAD)106
Skewness0
Sum90100
Variance15016.667
MonotonicityStrictly increasing
2024-04-17T17:58:42.160299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
293 1
 
0.2%
291 1
 
0.2%
290 1
 
0.2%
289 1
 
0.2%
288 1
 
0.2%
287 1
 
0.2%
286 1
 
0.2%
285 1
 
0.2%
284 1
 
0.2%
Other values (414) 414
97.6%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
424 1
0.2%
423 1
0.2%
422 1
0.2%
421 1
0.2%
420 1
0.2%
419 1
0.2%
418 1
0.2%
417 1
0.2%
416 1
0.2%
415 1
0.2%

종교구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
교회
387 
사찰
 
23
성당
 
10
기타
 
4

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 387
91.3%
사찰 23
 
5.4%
성당 10
 
2.4%
기타 4
 
0.9%

Length

2024-04-17T17:58:42.262305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T17:58:42.353520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
교회 387
91.3%
사찰 23
 
5.4%
성당 10
 
2.4%
기타 4
 
0.9%

시설명
Text

Distinct372
Distinct (%)87.7%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2024-04-17T17:58:42.523636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length18
Mean length5.7830189
Min length3

Characters and Unicode

Total characters2452
Distinct characters273
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique333 ?
Unique (%)78.5%

Sample

1st row사랑침례교회
2nd row새소망교회
3rd row신도림제일교회
4th row신도림중앙교회
5th row예수촌교회
ValueCountFrequency (%)
참빛교회 5
 
1.1%
교회 5
 
1.1%
새소망교회 4
 
0.9%
반석교회 4
 
0.9%
벧엘교회 3
 
0.7%
한사랑교회 3
 
0.7%
사랑의교회 3
 
0.7%
평안교회 3
 
0.7%
임마누엘교회 3
 
0.7%
예향교회 3
 
0.7%
Other values (373) 413
92.0%
2024-04-17T17:58:42.835507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 405
 
16.5%
회 398
 
16.2%
사 56
 
2.3%
로 44
 
1.8%
성 44
 
1.8%
구 37
 
1.5%
복 35
 
1.4%
의 31
 
1.3%
랑 31
 
1.3%
동 30
 
1.2%
Other values (263) 1341
54.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2384
97.2%
Space Separator 30
 
1.2%
Open Punctuation 13
 
0.5%
Close Punctuation 13
 
0.5%
Decimal Number 9
 
0.4%
Uppercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 405
 
17.0%
회 398
 
16.7%
사 56
 
2.3%
로 44
 
1.8%
성 44
 
1.8%
구 37
 
1.6%
복 35
 
1.5%
의 31
 
1.3%
랑 31
 
1.3%
동 30
 
1.3%
Other values (251) 1273
53.4%
Decimal Number
ValueCountFrequency (%)
2 2
22.2%
1 2
22.2%
3 2
22.2%
5 1
11.1%
6 1
11.1%
4 1
11.1%
Uppercase Letter
ValueCountFrequency (%)
S 1
33.3%
G 1
33.3%
I 1
33.3%
Space Separator
ValueCountFrequency (%)
30
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2384
97.2%
Common 65
 
2.7%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 405
 
17.0%
회 398
 
16.7%
사 56
 
2.3%
로 44
 
1.8%
성 44
 
1.8%
구 37
 
1.6%
복 35
 
1.5%
의 31
 
1.3%
랑 31
 
1.3%
동 30
 
1.3%
Other values (251) 1273
53.4%
Common
ValueCountFrequency (%)
30
46.2%
( 13
20.0%
) 13
20.0%
2 2
 
3.1%
1 2
 
3.1%
3 2
 
3.1%
5 1
 
1.5%
6 1
 
1.5%
4 1
 
1.5%
Latin
ValueCountFrequency (%)
S 1
33.3%
G 1
33.3%
I 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2384
97.2%
ASCII 68
 
2.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 405
 
17.0%
회 398
 
16.7%
사 56
 
2.3%
로 44
 
1.8%
성 44
 
1.8%
구 37
 
1.6%
복 35
 
1.5%
의 31
 
1.3%
랑 31
 
1.3%
동 30
 
1.3%
Other values (251) 1273
53.4%
ASCII
ValueCountFrequency (%)
30
44.1%
( 13
19.1%
) 13
19.1%
2 2
 
2.9%
1 2
 
2.9%
3 2
 
2.9%
5 1
 
1.5%
6 1
 
1.5%
S 1
 
1.5%
G 1
 
1.5%
Other values (2) 2
 
2.9%

주소
Text

Distinct422
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2024-04-17T17:58:43.096423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length29
Mean length18.04717
Min length5

Characters and Unicode

Total characters7652
Distinct characters130
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique420 ?
Unique (%)99.1%

Sample

1st row서울시 구로구 구로중앙로40길 46
2nd row서울시 구로구 신도림로 2 엘림빌딩
3rd row서울시 구로구 신도림로13길 18
4th row서울시 구로구 신도림로 78
5th row서울시 구로구 신도림로11나길 13
ValueCountFrequency (%)
구로구 384
22.7%
서울시 366
21.6%
고척로 20
 
1.2%
2층 18
 
1.1%
3층 18
 
1.1%
지하 14
 
0.8%
경인로 12
 
0.7%
개봉로 12
 
0.7%
서울 10
 
0.6%
4층 8
 
0.5%
Other values (516) 833
49.1%
2024-04-17T17:58:43.475533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1304
17.0%
로 855
 
11.2%
구 827
 
10.8%
서 392
 
5.1%
1 380
 
5.0%
울 376
 
4.9%
시 367
 
4.8%
길 301
 
3.9%
2 256
 
3.3%
3 217
 
2.8%
Other values (120) 2377
31.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4430
57.9%
Decimal Number 1699
 
22.2%
Space Separator 1304
 
17.0%
Dash Punctuation 93
 
1.2%
Other Punctuation 60
 
0.8%
Close Punctuation 31
 
0.4%
Open Punctuation 31
 
0.4%
Lowercase Letter 3
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 855
19.3%
구 827
18.7%
서 392
 
8.8%
울 376
 
8.5%
시 367
 
8.3%
길 301
 
6.8%
개 86
 
1.9%
봉 86
 
1.9%
층 65
 
1.5%
동 63
 
1.4%
Other values (101) 1012
22.8%
Decimal Number
ValueCountFrequency (%)
1 380
22.4%
2 256
15.1%
3 217
12.8%
5 151
 
8.9%
8 135
 
7.9%
4 128
 
7.5%
7 117
 
6.9%
0 113
 
6.7%
6 110
 
6.5%
9 92
 
5.4%
Lowercase Letter
ValueCountFrequency (%)
b 1
33.3%
i 1
33.3%
k 1
33.3%
Space Separator
ValueCountFrequency (%)
1304
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 93
100.0%
Other Punctuation
ValueCountFrequency (%)
, 60
100.0%
Close Punctuation
ValueCountFrequency (%)
) 31
100.0%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4430
57.9%
Common 3218
42.1%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 855
19.3%
구 827
18.7%
서 392
 
8.8%
울 376
 
8.5%
시 367
 
8.3%
길 301
 
6.8%
개 86
 
1.9%
봉 86
 
1.9%
층 65
 
1.5%
동 63
 
1.4%
Other values (101) 1012
22.8%
Common
ValueCountFrequency (%)
1304
40.5%
1 380
 
11.8%
2 256
 
8.0%
3 217
 
6.7%
5 151
 
4.7%
8 135
 
4.2%
4 128
 
4.0%
7 117
 
3.6%
0 113
 
3.5%
6 110
 
3.4%
Other values (5) 307
 
9.5%
Latin
ValueCountFrequency (%)
b 1
25.0%
i 1
25.0%
A 1
25.0%
k 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4430
57.9%
ASCII 3222
42.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1304
40.5%
1 380
 
11.8%
2 256
 
7.9%
3 217
 
6.7%
5 151
 
4.7%
8 135
 
4.2%
4 128
 
4.0%
7 117
 
3.6%
0 113
 
3.5%
6 110
 
3.4%
Other values (9) 311
 
9.7%
Hangul
ValueCountFrequency (%)
로 855
19.3%
구 827
18.7%
서 392
 
8.8%
울 376
 
8.5%
시 367
 
8.3%
길 301
 
6.8%
개 86
 
1.9%
봉 86
 
1.9%
층 65
 
1.5%
동 63
 
1.4%
Other values (101) 1012
22.8%

행정동
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
개봉1동
45 
고척2동
42 
오류2동
42 
수궁동
41 
개봉2동
39 
Other values (11)
215 

Length

Max length4
Median length4
Mean length3.884434
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개봉1동 45
10.6%
고척2동 42
9.9%
오류2동 42
9.9%
수궁동 41
9.7%
개봉2동 39
9.2%
개봉3동 38
9.0%
구로5동 27
 
6.4%
구로2동 26
 
6.1%
고척1동 26
 
6.1%
신도림동 21
 
5.0%
Other values (6) 77
18.2%

Length

2024-04-17T17:58:43.601676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
개봉1동 45
10.6%
고척2동 42
9.9%
오류2동 42
9.9%
수궁동 41
9.7%
개봉2동 39
9.2%
개봉3동 38
9.0%
구로5동 27
 
6.4%
구로2동 26
 
6.1%
고척1동 26
 
6.1%
신도림동 21
 
5.0%
Other values (6) 77
18.2%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2023-08-02
424 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-02
2nd row2023-08-02
3rd row2023-08-02
4th row2023-08-02
5th row2023-08-02

Common Values

ValueCountFrequency (%)
2023-08-02 424
100.0%

Length

2024-04-17T17:58:43.699878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T17:58:43.773888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-02 424
100.0%

Interactions

2024-04-17T17:58:41.523591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T17:58:43.821860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번종교구분행정동
연번1.0000.7130.942
종교구분0.7131.0000.000
행정동0.9420.0001.000
2024-04-17T17:58:43.891532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종교구분행정동
종교구분1.0000.000
행정동0.0001.000
2024-04-17T17:58:43.964529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번종교구분행정동
연번1.0000.5130.755
종교구분0.5131.0000.000
행정동0.7550.0001.000

Missing values

2024-04-17T17:58:41.612732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T17:58:41.702502image/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

연번종교구분시설명주소행정동데이터기준일
01교회사랑침례교회서울시 구로구 구로중앙로40길 46신도림동2023-08-02
12교회새소망교회서울시 구로구 신도림로 2 엘림빌딩신도림동2023-08-02
23교회신도림제일교회서울시 구로구 신도림로13길 18신도림동2023-08-02
34교회신도림중앙교회서울시 구로구 신도림로 78신도림동2023-08-02
45교회예수촌교회서울시 구로구 신도림로11나길 13신도림동2023-08-02
56교회푸른초장교회서울시 구로구 신도림로19길 7신도림동2023-08-02
67교회성락침례교회서울시 구로구 신도림로 56-24신도림동2023-08-02
78교회예수비전교회서울시 구로구 신도림로15길 22신도림동2023-08-02
89교회뉴크리에이션 교회서울시 구로구 신도림로 105신도림동2023-08-02
910교회대림장로교회서울시 구로구 신도림로 16, 403호신도림동2023-08-02
연번종교구분시설명주소행정동데이터기준일
414415사찰청암사부일로1다길 16-15수궁동2023-08-02
415416사찰관음사오리로22길 77수궁동2023-08-02
416417사찰원각사오리로21가길 146수궁동2023-08-02
417418사찰다보사부일로13길 81수궁동2023-08-02
418419사찰보현정사오리로 1307-1수궁동2023-08-02
419420사찰광덕사오리로22가길 84수궁동2023-08-02
420421기타원불교구로교당가마산로20길50구로2동2023-08-02
421422기타한국SGI구로구 공원로 54구로5동2023-08-02
422423기타원불교개봉교당개봉로16길 15개봉2동2023-08-02
423424기타대순진리회구로회관개봉로12길 9-33개봉3동2023-08-02