Overview

Dataset statistics

Number of variables4
Number of observations136
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.4 KiB
Average record size in memory33.0 B

Variable types

Categorical1
Text3

Dataset

Description대구광역시_ 남구 생활체육 현황_20190630
Author대구광역시 남구
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=3072394&dataSetDetailId=30723941925f944a50b0&provdMethod=FILE

Reproduction

Analysis started2024-04-19 05:16:58.148171
Analysis finished2024-04-19 05:16:58.456758
Duration0.31 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설종류명
Categorical

Distinct15
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
당구장
51 
체육도장(태권도)
35 
근린공원
11 
골프장
10 
학교
8 
Other values (10)
21 

Length

Max length9
Median length8
Mean length4.9558824
Min length2

Unique

Unique3 ?
Unique (%)2.2%

Sample

1st row근린공원
2nd row근린공원
3rd row근린공원
4th row도시자연공원
5th row도시자연공원

Common Values

ValueCountFrequency (%)
당구장 51
37.5%
체육도장(태권도) 35
25.7%
근린공원 11
 
8.1%
골프장 10
 
7.4%
학교 8
 
5.9%
체육도장(복싱) 4
 
2.9%
도시자연공원 3
 
2.2%
둔치 3
 
2.2%
어린이공원 2
 
1.5%
공원 2
 
1.5%
Other values (5) 7
 
5.1%

Length

2024-04-19T14:16:58.520575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
당구장 51
37.5%
체육도장(태권도 35
25.7%
근린공원 11
 
8.1%
골프장 10
 
7.4%
학교 8
 
5.9%
체육도장(복싱 4
 
2.9%
도시자연공원 3
 
2.2%
둔치 3
 
2.2%
어린이공원 2
 
1.5%
공원 2
 
1.5%
Other values (5) 7
 
5.1%

체육시설명
Text

Distinct133
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-04-19T14:16:59.032797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length14
Mean length7.3161765
Min length2

Characters and Unicode

Total characters995
Distinct characters208
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

Unique131 ?
Unique (%)96.3%

Sample

1st row안지랑골(안일클럽)
2nd row안지랑골(대덕클럽)
3rd row앞산3지구(무당골)
4th row앞산공원 제1운동시설지구
5th row고산골 제1약수터
ValueCountFrequency (%)
태권도 12
 
6.8%
당구클럽 5
 
2.8%
tbc당구클럽 3
 
1.7%
계명대 3
 
1.7%
킹 2
 
1.1%
스포츠당구장 2
 
1.1%
당구장 2
 
1.1%
고산골 2
 
1.1%
i 2
 
1.1%
앞산공원 2
 
1.1%
Other values (141) 142
80.2%
2024-04-19T14:16:59.410411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 58
 
5.8%
당 52
 
5.2%
장 43
 
4.3%
41
 
4.1%
대 34
 
3.4%
도 33
 
3.3%
권 32
 
3.2%
태 32
 
3.2%
골 20
 
2.0%
클 19
 
1.9%
Other values (198) 631
63.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 869
87.3%
Uppercase Letter 42
 
4.2%
Space Separator 41
 
4.1%
Open Punctuation 13
 
1.3%
Close Punctuation 13
 
1.3%
Decimal Number 13
 
1.3%
Math Symbol 3
 
0.3%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 58
 
6.7%
당 52
 
6.0%
장 43
 
4.9%
대 34
 
3.9%
도 33
 
3.8%
권 32
 
3.7%
태 32
 
3.7%
골 20
 
2.3%
클 19
 
2.2%
럽 19
 
2.2%
Other values (170) 527
60.6%
Uppercase Letter
ValueCountFrequency (%)
I 5
11.9%
C 5
11.9%
P 4
9.5%
A 4
9.5%
T 4
9.5%
B 3
 
7.1%
R 3
 
7.1%
E 2
 
4.8%
S 2
 
4.8%
O 2
 
4.8%
Other values (8) 8
19.0%
Decimal Number
ValueCountFrequency (%)
2 4
30.8%
1 4
30.8%
5 2
15.4%
3 2
15.4%
4 1
 
7.7%
Space Separator
ValueCountFrequency (%)
41
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Math Symbol
ValueCountFrequency (%)
∼ 3
100.0%
Other Punctuation
ValueCountFrequency (%)
# 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 869
87.3%
Common 84
 
8.4%
Latin 42
 
4.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 58
 
6.7%
당 52
 
6.0%
장 43
 
4.9%
대 34
 
3.9%
도 33
 
3.8%
권 32
 
3.7%
태 32
 
3.7%
골 20
 
2.3%
클 19
 
2.2%
럽 19
 
2.2%
Other values (170) 527
60.6%
Latin
ValueCountFrequency (%)
I 5
11.9%
C 5
11.9%
P 4
9.5%
A 4
9.5%
T 4
9.5%
B 3
 
7.1%
R 3
 
7.1%
E 2
 
4.8%
S 2
 
4.8%
O 2
 
4.8%
Other values (8) 8
19.0%
Common
ValueCountFrequency (%)
41
48.8%
( 13
 
15.5%
) 13
 
15.5%
2 4
 
4.8%
1 4
 
4.8%
∼ 3
 
3.6%
5 2
 
2.4%
3 2
 
2.4%
4 1
 
1.2%
# 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 869
87.3%
ASCII 123
 
12.4%
Math Operators 3
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 58
 
6.7%
당 52
 
6.0%
장 43
 
4.9%
대 34
 
3.9%
도 33
 
3.8%
권 32
 
3.7%
태 32
 
3.7%
골 20
 
2.3%
클 19
 
2.2%
럽 19
 
2.2%
Other values (170) 527
60.6%
ASCII
ValueCountFrequency (%)
41
33.3%
( 13
 
10.6%
) 13
 
10.6%
I 5
 
4.1%
C 5
 
4.1%
P 4
 
3.3%
A 4
 
3.3%
T 4
 
3.3%
2 4
 
3.3%
1 4
 
3.3%
Other values (17) 26
21.1%
Math Operators
ValueCountFrequency (%)
∼ 3
100.0%

주소
Text

Distinct131
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-04-19T14:16:59.646896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length29.5
Mean length23.338235
Min length16

Characters and Unicode

Total characters3174
Distinct characters73
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

Unique127 ?
Unique (%)93.4%

Sample

1st row대구광역시 남구 대명동 산199
2nd row대구광역시 남구 대명동 1492-16
3rd row대구광역시 남구 대명동 산284-2
4th row대구광역시 남구 봉덕동 산127-2
5th row대구광역시 남구 봉덕동 산167
ValueCountFrequency (%)
대구광역시 136
20.8%
남구 136
20.8%
대명동 71
 
10.8%
봉덕동 25
 
3.8%
대명로 14
 
2.1%
현충로 14
 
2.1%
두류공원로 9
 
1.4%
이천동 8
 
1.2%
이천로 6
 
0.9%
효성로 5
 
0.8%
Other values (169) 231
35.3%
2024-04-19T14:17:00.014402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
604
19.0%
구 272
 
8.6%
대 262
 
8.3%
시 140
 
4.4%
광 136
 
4.3%
역 136
 
4.3%
남 136
 
4.3%
동 133
 
4.2%
) 119
 
3.7%
명 119
 
3.7%
Other values (63) 1117
35.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1832
57.7%
Space Separator 604
 
19.0%
Decimal Number 467
 
14.7%
Close Punctuation 119
 
3.7%
Open Punctuation 119
 
3.7%
Dash Punctuation 29
 
0.9%
Uppercase Letter 2
 
0.1%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 272
14.8%
대 262
14.3%
시 140
7.6%
광 136
 
7.4%
역 136
 
7.4%
남 136
 
7.4%
동 133
 
7.3%
명 119
 
6.5%
로 101
 
5.5%
덕 52
 
2.8%
Other values (47) 345
18.8%
Decimal Number
ValueCountFrequency (%)
1 113
24.2%
2 74
15.8%
6 51
10.9%
4 47
10.1%
3 39
 
8.4%
5 39
 
8.4%
8 29
 
6.2%
7 27
 
5.8%
9 25
 
5.4%
0 23
 
4.9%
Space Separator
ValueCountFrequency (%)
604
100.0%
Close Punctuation
ValueCountFrequency (%)
) 119
100.0%
Open Punctuation
ValueCountFrequency (%)
( 119
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1832
57.7%
Common 1340
42.2%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 272
14.8%
대 262
14.3%
시 140
7.6%
광 136
 
7.4%
역 136
 
7.4%
남 136
 
7.4%
동 133
 
7.3%
명 119
 
6.5%
로 101
 
5.5%
덕 52
 
2.8%
Other values (47) 345
18.8%
Common
ValueCountFrequency (%)
604
45.1%
) 119
 
8.9%
( 119
 
8.9%
1 113
 
8.4%
2 74
 
5.5%
6 51
 
3.8%
4 47
 
3.5%
3 39
 
2.9%
5 39
 
2.9%
- 29
 
2.2%
Other values (5) 106
 
7.9%
Latin
ValueCountFrequency (%)
B 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1832
57.7%
ASCII 1342
42.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
604
45.0%
) 119
 
8.9%
( 119
 
8.9%
1 113
 
8.4%
2 74
 
5.5%
6 51
 
3.8%
4 47
 
3.5%
3 39
 
2.9%
5 39
 
2.9%
- 29
 
2.2%
Other values (6) 108
 
8.0%
Hangul
ValueCountFrequency (%)
구 272
14.8%
대 262
14.3%
시 140
7.6%
광 136
 
7.4%
역 136
 
7.4%
남 136
 
7.4%
동 133
 
7.3%
명 119
 
6.5%
로 101
 
5.5%
덕 52
 
2.8%
Other values (47) 345
18.8%

전화번호
Text

Distinct81
Distinct (%)59.6%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-04-19T14:17:00.251157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.022059
Min length12

Characters and Unicode

Total characters1635
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

Unique80 ?
Unique (%)58.8%

Sample

1st row053-000-0000
2nd row053-000-0000
3rd row053-000-0000
4th row053-000-0000
5th row053-000-0000
ValueCountFrequency (%)
053-000-0000 56
41.2%
053-655-1872 1
 
0.7%
053-472-0019 1
 
0.7%
053-655-8785 1
 
0.7%
053-473-8253 1
 
0.7%
053-472-5246 1
 
0.7%
053-622-1805 1
 
0.7%
053-476-3396 1
 
0.7%
053-653-9647 1
 
0.7%
053-654-2216 1
 
0.7%
Other values (71) 71
52.2%
2024-04-19T14:17:00.610291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 585
35.8%
- 272
16.6%
5 185
 
11.3%
3 179
 
10.9%
6 84
 
5.1%
2 78
 
4.8%
7 73
 
4.5%
4 58
 
3.5%
1 43
 
2.6%
8 40
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1363
83.4%
Dash Punctuation 272
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 585
42.9%
5 185
 
13.6%
3 179
 
13.1%
6 84
 
6.2%
2 78
 
5.7%
7 73
 
5.4%
4 58
 
4.3%
1 43
 
3.2%
8 40
 
2.9%
9 38
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 272
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1635
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 585
35.8%
- 272
16.6%
5 185
 
11.3%
3 179
 
10.9%
6 84
 
5.1%
2 78
 
4.8%
7 73
 
4.5%
4 58
 
3.5%
1 43
 
2.6%
8 40
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1635
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 585
35.8%
- 272
16.6%
5 185
 
11.3%
3 179
 
10.9%
6 84
 
5.1%
2 78
 
4.8%
7 73
 
4.5%
4 58
 
3.5%
1 43
 
2.6%
8 40
 
2.4%

Correlations

2024-04-19T14:17:00.707028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설종류명전화번호
시설종류명1.0000.000
전화번호0.0001.000

Missing values

2024-04-19T14:16:58.355606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-19T14:16:58.426935image/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

시설종류명체육시설명주소전화번호
0근린공원안지랑골(안일클럽)대구광역시 남구 대명동 산199053-000-0000
1근린공원안지랑골(대덕클럽)대구광역시 남구 대명동 1492-16053-000-0000
2근린공원앞산3지구(무당골)대구광역시 남구 대명동 산284-2053-000-0000
3도시자연공원앞산공원 제1운동시설지구대구광역시 남구 봉덕동 산127-2053-000-0000
4도시자연공원고산골 제1약수터대구광역시 남구 봉덕동 산167053-000-0000
5근린공원앞산공원 제2운동시설지구(법장사 밑)대구광역시 남구 봉덕동 1238053-000-0000
6근린공원대덕쉼터대구광역시 남구 앞산순환로 54(대명동)053-000-0000
7근린공원강당골대구광역시 남구 봉덕동 산123-1053-000-0000
8근린공원큰골대구광역시 남구 현충로26길 67053-000-0000
9근린공원큰골케이블카앞대구광역시 남구 앞산순환로 456(대명동)053-000-0000
시설종류명체육시설명주소전화번호
126체육도장(태권도)해성 태권도 체육관대구광역시 남구 현충로26길 67 (대명동) 2층053-623-7890
127체육도장(복싱)대명복싱헬스체육관대구광역시 남구 대명10동 1642-41번지(3층)053-654-8382
128체육도장(복싱)복싱프라자대구광역시 남구 대명5동30-4(지하)053-621-0038
129체육도장(복싱)경상권투체육관대구광역시 남구 대명5동 1713-12 (3층)053-625-1277
130체육도장(복싱)신동기 복싱체육관대구광역시 남구 대명동 1161-1 (3층)053-652-1534
131체육도장(유도)용인대정진유도교실대구광역시 남구 봉덕3동 1292-5번지053-473-3292
132체육도장(유도)홍화유도관대구광역시 남구 대명동 1923-4 (3층)053-564-9043
133체육도장(검도)벽산체육연구관(검도)대구광역시 남구 봉덕1동605-4(3층)053-474-7989
134체육도장(검도)효승검도관대구광역시 남구 봉덕동1292-106(지하1)053-000-0000
135체육도장(유수)진식태극권수련원대구광역시 남구 대명9동908-2(지하)053-631-3651