Overview

Dataset statistics

Number of variables6
Number of observations137
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.6 KiB
Average record size in memory49.0 B

Variable types

Categorical4
Text2

Dataset

Description경기도 시흥시의 체육시설 현황 정보에 대한 데이터로 권역, 동, 시설명, 종목, 주소, 데이터 기준일자 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15113975/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
권역 is highly overall correlated with High correlation
is highly overall correlated with 권역High correlation

Reproduction

Analysis started2023-12-12 08:52:13.298493
Analysis finished2023-12-12 08:52:14.029369
Duration0.73 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

권역
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
중부
53 
남부
44 
북부
40 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
중부 53
38.7%
남부 44
32.1%
북부 40
29.2%

Length

2023-12-12T17:52:14.124339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:52:14.239331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중부 53
38.7%
남부 44
32.1%
북부 40
29.2%


Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)13.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
월곶동
14 
정왕2동
13 
목감동
13 
대야동
13 
신현동
11 
Other values (13)
73 

Length

Max length4
Median length3
Mean length3.2919708
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
월곶동 14
10.2%
정왕2동 13
9.5%
목감동 13
9.5%
대야동 13
9.5%
신현동 11
 
8.0%
군자동 10
 
7.3%
정왕1동 10
 
7.3%
정왕3동 8
 
5.8%
능곡동 7
 
5.1%
매화동 6
 
4.4%
Other values (8) 32
23.4%

Length

2023-12-12T17:52:14.375990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
월곶동 14
10.2%
목감동 13
9.5%
대야동 13
9.5%
정왕2동 13
9.5%
신현동 11
 
8.0%
군자동 10
 
7.3%
정왕1동 10
 
7.3%
정왕3동 8
 
5.8%
능곡동 7
 
5.1%
정왕본동 6
 
4.4%
Other values (8) 32
23.4%
Distinct69
Distinct (%)50.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T17:52:14.712680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length8.8321168
Min length4

Characters and Unicode

Total characters1210
Distinct characters133
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

Unique39 ?
Unique (%)28.5%

Sample

1st row시흥시 체육관
2nd row대야동 체육시설
3rd row대야동 체육시설
4th row대야동 체육시설
5th row대야배수지 체육시설
ValueCountFrequency (%)
체육시설 55
 
20.4%
하부 11
 
4.1%
포동 9
 
3.3%
정왕동 7
 
2.6%
국민체육센터 7
 
2.6%
옥구공원 6
 
2.2%
생활체육공원 6
 
2.2%
체육공원 6
 
2.2%
월곶에코피아 6
 
2.2%
시화mtv 6
 
2.2%
Other values (73) 150
55.8%
2023-12-12T17:52:15.210824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
132
 
10.9%
97
 
8.0%
96
 
7.9%
78
 
6.4%
65
 
5.4%
55
 
4.5%
40
 
3.3%
40
 
3.3%
26
 
2.1%
15
 
1.2%
Other values (123) 566
46.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1016
84.0%
Space Separator 132
 
10.9%
Decimal Number 20
 
1.7%
Uppercase Letter 18
 
1.5%
Close Punctuation 12
 
1.0%
Open Punctuation 12
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
97
 
9.5%
96
 
9.4%
78
 
7.7%
65
 
6.4%
55
 
5.4%
40
 
3.9%
40
 
3.9%
26
 
2.6%
15
 
1.5%
14
 
1.4%
Other values (109) 490
48.2%
Decimal Number
ValueCountFrequency (%)
3 6
30.0%
4 5
25.0%
1 2
 
10.0%
2 2
 
10.0%
8 2
 
10.0%
6 1
 
5.0%
7 1
 
5.0%
5 1
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
M 6
33.3%
T 6
33.3%
V 6
33.3%
Space Separator
ValueCountFrequency (%)
132
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1016
84.0%
Common 176
 
14.5%
Latin 18
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
97
 
9.5%
96
 
9.4%
78
 
7.7%
65
 
6.4%
55
 
5.4%
40
 
3.9%
40
 
3.9%
26
 
2.6%
15
 
1.5%
14
 
1.4%
Other values (109) 490
48.2%
Common
ValueCountFrequency (%)
132
75.0%
) 12
 
6.8%
( 12
 
6.8%
3 6
 
3.4%
4 5
 
2.8%
1 2
 
1.1%
2 2
 
1.1%
8 2
 
1.1%
6 1
 
0.6%
7 1
 
0.6%
Latin
ValueCountFrequency (%)
M 6
33.3%
T 6
33.3%
V 6
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1016
84.0%
ASCII 194
 
16.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
132
68.0%
) 12
 
6.2%
( 12
 
6.2%
M 6
 
3.1%
T 6
 
3.1%
V 6
 
3.1%
3 6
 
3.1%
4 5
 
2.6%
1 2
 
1.0%
2 2
 
1.0%
Other values (4) 5
 
2.6%
Hangul
ValueCountFrequency (%)
97
 
9.5%
96
 
9.4%
78
 
7.7%
65
 
6.4%
55
 
5.4%
40
 
3.9%
40
 
3.9%
26
 
2.6%
15
 
1.5%
14
 
1.4%
Other values (109) 490
48.2%

종 목
Categorical

Distinct32
Distinct (%)23.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
풋살
17 
족구
16 
배드민턴
14 
다목적체육관
11 
게이트볼
11 
Other values (27)
68 

Length

Max length20
Median length8
Mean length3.4452555
Min length2

Unique

Unique17 ?
Unique (%)12.4%

Sample

1st row다목적체육관
2nd row테니스
3rd row족구
4th row배드민턴
5th row풋살

Common Values

ValueCountFrequency (%)
풋살 17
12.4%
족구 16
11.7%
배드민턴 14
10.2%
다목적체육관 11
 
8.0%
게이트볼 11
 
8.0%
테니스 11
 
8.0%
농구 9
 
6.6%
축구 8
 
5.8%
다목적운동장 5
 
3.6%
수영 4
 
2.9%
Other values (22) 31
22.6%

Length

2023-12-12T17:52:15.382050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
풋살 17
11.8%
족구 17
11.8%
배드민턴 14
9.7%
게이트볼 12
 
8.3%
다목적체육관 11
 
7.6%
테니스 11
 
7.6%
농구 11
 
7.6%
축구 8
 
5.6%
다목적운동장 5
 
3.5%
수영 4
 
2.8%
Other values (24) 34
23.6%

주소
Text

Distinct75
Distinct (%)54.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T17:52:15.737285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length31
Mean length20.379562
Min length15

Characters and Unicode

Total characters2792
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

Unique47 ?
Unique (%)34.3%

Sample

1st row경기도 시흥시 대야동 377-79번지
2nd row경기도 시흥시 대야동 565번지
3rd row경기도 시흥시 대야동 63-3번지
4th row경기도 시흥시 대야동 68-2번지
5th row경기도 시흥시 대야동 산170-21번지
ValueCountFrequency (%)
경기도 137
23.1%
시흥시 137
23.1%
정왕동 40
 
6.8%
조남동 13
 
2.2%
12
 
2.0%
포동 10
 
1.7%
월곶동 8
 
1.4%
대야동 8
 
1.4%
2138번지 7
 
1.2%
능곡동 7
 
1.2%
Other values (104) 213
36.0%
2023-12-12T17:52:16.322623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
460
16.5%
274
 
9.8%
137
 
4.9%
137
 
4.9%
137
 
4.9%
137
 
4.9%
129
 
4.6%
119
 
4.3%
118
 
4.2%
1 107
 
3.8%
Other values (84) 1037
37.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1618
58.0%
Decimal Number 582
 
20.8%
Space Separator 460
 
16.5%
Dash Punctuation 80
 
2.9%
Other Punctuation 22
 
0.8%
Open Punctuation 15
 
0.5%
Close Punctuation 15
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
274
16.9%
137
 
8.5%
137
 
8.5%
137
 
8.5%
137
 
8.5%
129
 
8.0%
119
 
7.4%
118
 
7.3%
41
 
2.5%
41
 
2.5%
Other values (67) 348
21.5%
Decimal Number
ValueCountFrequency (%)
1 107
18.4%
2 74
12.7%
8 65
11.2%
5 61
10.5%
7 57
9.8%
0 57
9.8%
6 54
9.3%
3 47
8.1%
9 35
 
6.0%
4 25
 
4.3%
Other Punctuation
ValueCountFrequency (%)
: 12
54.5%
/ 6
27.3%
. 4
 
18.2%
Space Separator
ValueCountFrequency (%)
460
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 80
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1618
58.0%
Common 1174
42.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
274
16.9%
137
 
8.5%
137
 
8.5%
137
 
8.5%
137
 
8.5%
129
 
8.0%
119
 
7.4%
118
 
7.3%
41
 
2.5%
41
 
2.5%
Other values (67) 348
21.5%
Common
ValueCountFrequency (%)
460
39.2%
1 107
 
9.1%
- 80
 
6.8%
2 74
 
6.3%
8 65
 
5.5%
5 61
 
5.2%
7 57
 
4.9%
0 57
 
4.9%
6 54
 
4.6%
3 47
 
4.0%
Other values (7) 112
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1618
58.0%
ASCII 1174
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
460
39.2%
1 107
 
9.1%
- 80
 
6.8%
2 74
 
6.3%
8 65
 
5.5%
5 61
 
5.2%
7 57
 
4.9%
0 57
 
4.9%
6 54
 
4.6%
3 47
 
4.0%
Other values (7) 112
 
9.5%
Hangul
ValueCountFrequency (%)
274
16.9%
137
 
8.5%
137
 
8.5%
137
 
8.5%
137
 
8.5%
129
 
8.0%
119
 
7.4%
118
 
7.3%
41
 
2.5%
41
 
2.5%
Other values (67) 348
21.5%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-05-24
137 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-05-24
2nd row2023-05-24
3rd row2023-05-24
4th row2023-05-24
5th row2023-05-24

Common Values

ValueCountFrequency (%)
2023-05-24 137
100.0%

Length

2023-12-12T17:52:16.511525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:52:16.642811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-05-24 137
100.0%

Correlations

2023-12-12T17:52:16.741657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
권역시설명종 목주소
권역1.0001.0001.0000.1551.000
1.0001.0000.9990.0001.000
시설명1.0000.9991.0000.0000.999
종 목0.1550.0000.0001.0000.000
주소1.0001.0000.9990.0001.000
2023-12-12T17:52:16.889105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
권역종 목
권역1.0000.9420.055
0.9421.0000.000
종 목0.0550.0001.000
2023-12-12T17:52:17.008379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
권역종 목
권역1.0000.9420.055
0.9421.0000.000
종 목0.0550.0001.000

Missing values

2023-12-12T17:52:13.864748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:52:13.985535image/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

권역시설명종 목주소데이터기준일자
0북부대야동시흥시 체육관다목적체육관경기도 시흥시 대야동 377-79번지2023-05-24
1북부대야동대야동 체육시설테니스경기도 시흥시 대야동 565번지2023-05-24
2북부대야동대야동 체육시설족구경기도 시흥시 대야동 63-3번지2023-05-24
3북부대야동대야동 체육시설배드민턴경기도 시흥시 대야동 68-2번지2023-05-24
4북부대야동대야배수지 체육시설풋살경기도 시흥시 대야동 산170-21번지2023-05-24
5북부대야동대야배수지 체육시설테니스경기도 시흥시 대야동 산170-21번지2023-05-24
6북부대야동대야배수지 체육시설족구경기도 시흥시 대야동 산170-21번지2023-05-24
7북부대야동대야동 인공암벽장암벽경기도 시흥시 대야동 332-1번지2023-05-24
8북부대야동계수동 체육시설게이트볼경기도 시흥시 계수동 475-5번지2023-05-24
9북부대야동계수동 체육시설씨름경기도 시흥시 계수동 475-5번지2023-05-24
권역시설명종 목주소데이터기준일자
127남부정왕3동옥구공원축구경기도 시흥시 정왕동 2138번지2023-05-24
128남부정왕3동옥구공원걷기 트랙경기도 시흥시 정왕동 2138번지2023-05-24
129남부정왕3동정왕3동 게이트볼장게이트볼경기도 시흥시 정왕3동 2140번지2023-05-24
130남부정왕4동함송 생활체육관다목적체육관경기도 시흥시 정왕동 1886-1번지2023-05-24
131남부정왕4동함송 실외체육시설풋살경기도 시흥시 정왕동 1878-1번지2023-05-24
132남부정왕4동함송 실외체육시설족구경기도 시흥시 정왕동 1878-1번지2023-05-24
133남부배곧동배곧 테니스장테니스경기도 시흥시 정왕동 1772-21번지2023-05-24
134남부배곧동배곧 농구장농구경기도 시흥시 정왕동 1771-1번지 일원(근린5호공원)2023-05-24
135남부배곧동배곧 풋살장풋살경기도 시흥시 정왕동 1772-21번지2023-05-24
136남부배곧동배곧 체육시설다목적운동장경기도 시흥시 정왕동 2488번지2023-05-24