Overview

Dataset statistics

Number of variables4
Number of observations36
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 KiB
Average record size in memory35.7 B

Variable types

Text3
Categorical1

Dataset

Description화성시 빗물이용시설에 관한 데이터로 빗물이용시설의 시설명, 주소, 저류조용량, 이용용도에 관한 데이터를 포함하고 있습니다.
URLhttps://www.data.go.kr/data/15114270/fileData.do

Alerts

이용용도 is highly imbalanced (81.7%)Imbalance
시설명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 21:16:26.238647
Analysis finished2023-12-12 21:16:26.671782
Duration0.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-13T06:16:26.829318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length16
Mean length13.333333
Min length6

Characters and Unicode

Total characters480
Distinct characters145
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)100.0%

Sample

1st row화성시근로자종합복지관
2nd row비봉면사무소
3rd row팔탄면사무소
4th row동탄배드민턴장(체육진흥과)
5th row동탄2 A41블럭(호반베르디움3차)
ValueCountFrequency (%)
동탄2 8
 
9.9%
반도유보라 5
 
6.2%
아이비파크 5
 
6.2%
동탄역 4
 
4.9%
c11bl(롯데캐슬 2
 
2.5%
금강펜테리움 2
 
2.5%
10차 2
 
2.5%
대방노블랜드 2
 
2.5%
송산 2
 
2.5%
아이파크캐슬 1
 
1.2%
Other values (48) 48
59.3%
2023-12-13T06:16:27.197537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
45
 
9.4%
동 20
 
4.2%
탄 18
 
3.8%
2 15
 
3.1%
이 14
 
2.9%
1 11
 
2.3%
차 11
 
2.3%
) 10
 
2.1%
( 10
 
2.1%
파 10
 
2.1%
Other values (135) 316
65.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 343
71.5%
Decimal Number 46
 
9.6%
Space Separator 45
 
9.4%
Uppercase Letter 21
 
4.4%
Close Punctuation 10
 
2.1%
Open Punctuation 10
 
2.1%
Dash Punctuation 4
 
0.8%
Lowercase Letter 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 20
 
5.8%
탄 18
 
5.2%
이 14
 
4.1%
차 11
 
3.2%
파 10
 
2.9%
스 10
 
2.9%
크 10
 
2.9%
라 9
 
2.6%
블 9
 
2.6%
역 8
 
2.3%
Other values (112) 224
65.3%
Decimal Number
ValueCountFrequency (%)
2 15
32.6%
1 11
23.9%
4 4
 
8.7%
6 3
 
6.5%
7 3
 
6.5%
3 3
 
6.5%
0 3
 
6.5%
9 2
 
4.3%
5 1
 
2.2%
8 1
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
L 5
23.8%
A 4
19.0%
B 4
19.0%
C 4
19.0%
S 1
 
4.8%
H 1
 
4.8%
I 1
 
4.8%
X 1
 
4.8%
Space Separator
ValueCountFrequency (%)
45
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 343
71.5%
Common 115
 
24.0%
Latin 22
 
4.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 20
 
5.8%
탄 18
 
5.2%
이 14
 
4.1%
차 11
 
3.2%
파 10
 
2.9%
스 10
 
2.9%
크 10
 
2.9%
라 9
 
2.6%
블 9
 
2.6%
역 8
 
2.3%
Other values (112) 224
65.3%
Common
ValueCountFrequency (%)
45
39.1%
2 15
 
13.0%
1 11
 
9.6%
) 10
 
8.7%
( 10
 
8.7%
4 4
 
3.5%
- 4
 
3.5%
6 3
 
2.6%
7 3
 
2.6%
3 3
 
2.6%
Other values (4) 7
 
6.1%
Latin
ValueCountFrequency (%)
L 5
22.7%
A 4
18.2%
B 4
18.2%
C 4
18.2%
S 1
 
4.5%
H 1
 
4.5%
I 1
 
4.5%
X 1
 
4.5%
e 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 343
71.5%
ASCII 137
 
28.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
45
32.8%
2 15
 
10.9%
1 11
 
8.0%
) 10
 
7.3%
( 10
 
7.3%
L 5
 
3.6%
4 4
 
2.9%
A 4
 
2.9%
B 4
 
2.9%
C 4
 
2.9%
Other values (13) 25
18.2%
Hangul
ValueCountFrequency (%)
동 20
 
5.8%
탄 18
 
5.2%
이 14
 
4.1%
차 11
 
3.2%
파 10
 
2.9%
스 10
 
2.9%
크 10
 
2.9%
라 9
 
2.6%
블 9
 
2.6%
역 8
 
2.3%
Other values (112) 224
65.3%

주소
Text

Distinct35
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-13T06:16:27.438747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20.5
Mean length16.722222
Min length13

Characters and Unicode

Total characters602
Distinct characters50
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

Unique34 ?
Unique (%)94.4%

Sample

1st row경기도 화성시 송산동 156
2nd row경기도 화성시 비봉면 양노리 253-1
3rd row경기도 화성시 팔탄면 구장리 563
4th row경기도 화성시 능동 1130
5th row경기도 화성시 목동 365
ValueCountFrequency (%)
경기도 36
23.2%
화성시 36
23.2%
오산동 8
 
5.2%
영천동 5
 
3.2%
목동 4
 
2.6%
산척동 4
 
2.6%
산 4
 
2.6%
신남리 3
 
1.9%
남양읍 3
 
1.9%
새솔동 2
 
1.3%
Other values (47) 50
32.3%
2023-12-13T06:16:27.811067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
119
19.8%
경 36
 
6.0%
도 36
 
6.0%
화 36
 
6.0%
성 36
 
6.0%
시 36
 
6.0%
기 36
 
6.0%
동 29
 
4.8%
산 20
 
3.3%
1 20
 
3.3%
Other values (40) 198
32.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 345
57.3%
Decimal Number 123
 
20.4%
Space Separator 119
 
19.8%
Dash Punctuation 15
 
2.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 36
10.4%
도 36
10.4%
화 36
10.4%
성 36
10.4%
시 36
10.4%
기 36
10.4%
동 29
8.4%
산 20
 
5.8%
오 8
 
2.3%
리 7
 
2.0%
Other values (28) 65
18.8%
Decimal Number
ValueCountFrequency (%)
1 20
16.3%
6 16
13.0%
3 15
12.2%
5 15
12.2%
7 11
8.9%
2 11
8.9%
9 11
8.9%
8 10
8.1%
0 9
7.3%
4 5
 
4.1%
Space Separator
ValueCountFrequency (%)
119
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 345
57.3%
Common 257
42.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 36
10.4%
도 36
10.4%
화 36
10.4%
성 36
10.4%
시 36
10.4%
기 36
10.4%
동 29
8.4%
산 20
 
5.8%
오 8
 
2.3%
리 7
 
2.0%
Other values (28) 65
18.8%
Common
ValueCountFrequency (%)
119
46.3%
1 20
 
7.8%
6 16
 
6.2%
- 15
 
5.8%
3 15
 
5.8%
5 15
 
5.8%
7 11
 
4.3%
2 11
 
4.3%
9 11
 
4.3%
8 10
 
3.9%
Other values (2) 14
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 345
57.3%
ASCII 257
42.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
119
46.3%
1 20
 
7.8%
6 16
 
6.2%
- 15
 
5.8%
3 15
 
5.8%
5 15
 
5.8%
7 11
 
4.3%
2 11
 
4.3%
9 11
 
4.3%
8 10
 
3.9%
Other values (2) 14
 
5.4%
Hangul
ValueCountFrequency (%)
경 36
10.4%
도 36
10.4%
화 36
10.4%
성 36
10.4%
시 36
10.4%
기 36
10.4%
동 29
8.4%
산 20
 
5.8%
오 8
 
2.3%
리 7
 
2.0%
Other values (28) 65
18.8%

저류조 용량
Text

Distinct35
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-13T06:16:28.077642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length3
Mean length4.3888889
Min length2

Characters and Unicode

Total characters158
Distinct characters15
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

Unique34 ?
Unique (%)94.4%

Sample

1st row226
2nd row128
3rd row80
4th row71
5th row695
ValueCountFrequency (%)
384 2
 
5.3%
245 1
 
2.6%
1555 1
 
2.6%
58 1
 
2.6%
707 1
 
2.6%
1225 1
 
2.6%
757 1
 
2.6%
312 1
 
2.6%
532 1
 
2.6%
308 1
 
2.6%
Other values (27) 27
71.1%
2023-12-13T06:16:28.816088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 21
13.3%
3 18
11.4%
0 18
11.4%
2 16
10.1%
5 16
10.1%
7 14
8.9%
8 9
 
5.7%
6 9
 
5.7%
4 8
 
5.1%
( 6
 
3.8%
Other values (5) 23
14.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 134
84.8%
Open Punctuation 6
 
3.8%
Other Letter 6
 
3.8%
Close Punctuation 6
 
3.8%
Other Punctuation 4
 
2.5%
Space Separator 2
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 21
15.7%
3 18
13.4%
0 18
13.4%
2 16
11.9%
5 16
11.9%
7 14
10.4%
8 9
6.7%
6 9
6.7%
4 8
 
6.0%
9 5
 
3.7%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Other Letter
ValueCountFrequency (%)
동 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 152
96.2%
Hangul 6
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 21
13.8%
3 18
11.8%
0 18
11.8%
2 16
10.5%
5 16
10.5%
7 14
9.2%
8 9
5.9%
6 9
5.9%
4 8
 
5.3%
( 6
 
3.9%
Other values (4) 17
11.2%
Hangul
ValueCountFrequency (%)
동 6
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 152
96.2%
Hangul 6
 
3.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 21
13.8%
3 18
11.8%
0 18
11.8%
2 16
10.5%
5 16
10.5%
7 14
9.2%
8 9
5.9%
6 9
5.9%
4 8
 
5.3%
( 6
 
3.9%
Other values (4) 17
11.2%
Hangul
ValueCountFrequency (%)
동 6
100.0%

이용용도
Categorical

IMBALANCE 

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
조경용수
35 
청소용수, 조경용수
 
1

Length

Max length10
Median length4
Mean length4.1666667
Min length4

Unique

Unique1 ?
Unique (%)2.8%

Sample

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

Common Values

ValueCountFrequency (%)
조경용수 35
97.2%
청소용수, 조경용수 1
 
2.8%

Length

2023-12-13T06:16:28.946076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:16:29.052199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
조경용수 36
97.3%
청소용수 1
 
2.7%

Correlations

2023-12-13T06:16:29.127326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설명주소저류조 용량이용용도
시설명1.0001.0001.0001.000
주소1.0001.0000.9931.000
저류조 용량1.0000.9931.0001.000
이용용도1.0001.0001.0001.000

Missing values

2023-12-13T06:16:26.548295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:16:26.639104image/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

시설명주소저류조 용량이용용도
0화성시근로자종합복지관경기도 화성시 송산동 156226조경용수
1비봉면사무소경기도 화성시 비봉면 양노리 253-1128조경용수
2팔탄면사무소경기도 화성시 팔탄면 구장리 56380조경용수
3동탄배드민턴장(체육진흥과)경기도 화성시 능동 113071조경용수
4동탄2 A41블럭(호반베르디움3차)경기도 화성시 목동 365695조경용수
5반도유보라 아이비파크 9차경기도 화성시 장지동 1009517조경용수
6금강펜테리움 센트럴파크 4차경기도 화성시 목동 산 33600조경용수
7e-편한세상경기도 화성시 목동 118-17960조경용수
8레이크자이 더 테라스경기도 화성시 송동 696350(12동), 350(27동), 300(29동)조경용수
9동탄파크자이경기도 화성시 영천동 651-1372627조경용수
시설명주소저류조 용량이용용도
26송산 대방노블랜드 5차경기도 화성시 새솔동 6384조경용수
27송산 대방노블랜드 6차경기도 화성시 새솔동 5308조경용수
28우남퍼스트빌 더테라스경기도 화성시 장지동 964630조경용수
29동탄역 예미지경기도 화성시 오산동 967-17375조경용수
30동탄2 LH4-2경기도 화성시 영천동 산17-23321(101동),342(105동),217(110동)조경용수
31봉담2지구 중흥S클래스경기도 화성시 봉담읍 상리 696396조경용수
32이마트 트레이더스 동탄점경기도 화성시 오산동 1022610조경용수
33화성시청역1블럭경기도 화성시 남양읍 신남리 산40-893조경용수
34화성시청역2블럭경기도 화성시 남양읍 신남리 산67-15101조경용수
35화성시청역3블럭경기도 화성시 남양읍 신남리 1560-377조경용수