Overview

Dataset statistics

Number of variables10
Number of observations33
Missing cells13
Missing cells (%)3.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 KiB
Average record size in memory88.0 B

Variable types

Text5
Categorical1
Numeric4

Dataset

Description충청북도의 테니스장 현황을 시설명, 소재지, 소재지도로명주소, 소재지지번주소, 면적(제곱미터), 코트수(면), 수용인원, 준공년도, 관리기관, 전화번호 등 정보로 제공합니다.
Author충청북도
URLhttps://www.data.go.kr/data/15071052/fileData.do

Alerts

면적(제곱미터) is highly overall correlated with 코트수(면)High correlation
코트수(면) is highly overall correlated with 면적(제곱미터) and 1 other fieldsHigh correlation
수용인원 is highly overall correlated with 코트수(면)High correlation
소재지도로명주소 has 2 (6.1%) missing valuesMissing
코트수(면) has 1 (3.0%) missing valuesMissing
수용인원 has 10 (30.3%) missing valuesMissing
시설명 has unique valuesUnique
면적(제곱미터) has unique valuesUnique

Reproduction

Analysis started2023-12-12 01:29:24.102625
Analysis finished2023-12-12 01:29:27.154704
Duration3.05 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
2023-12-12T10:29:27.294791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length9.030303
Min length5

Characters and Unicode

Total characters298
Distinct characters82
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)100.0%

Sample

1st row청주정구장
2nd row국제테니스장
3rd row공설테니스장
4th row강내생활체육공원테니스장
5th row탄금테니스장
ValueCountFrequency (%)
테니스장 6
 
14.3%
청주정구장 1
 
2.4%
광혜원 1
 
2.4%
소프트테니스장 1
 
2.4%
영동실외테니스장 1
 
2.4%
영동실내테니스장 1
 
2.4%
영동군민소프트테니스장 1
 
2.4%
증평테니스장 1
 
2.4%
반탄테니스장 1
 
2.4%
진전종합스포츠타운 1
 
2.4%
Other values (27) 27
64.3%
2023-12-12T10:29:27.632045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
33
 
11.1%
31
 
10.4%
30
 
10.1%
30
 
10.1%
14
 
4.7%
12
 
4.0%
10
 
3.4%
10
 
3.4%
9
 
3.0%
6
 
2.0%
Other values (72) 113
37.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 289
97.0%
Space Separator 9
 
3.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
33
 
11.4%
31
 
10.7%
30
 
10.4%
30
 
10.4%
14
 
4.8%
12
 
4.2%
10
 
3.5%
10
 
3.5%
6
 
2.1%
6
 
2.1%
Other values (71) 107
37.0%
Space Separator
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 289
97.0%
Common 9
 
3.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
33
 
11.4%
31
 
10.7%
30
 
10.4%
30
 
10.4%
14
 
4.8%
12
 
4.2%
10
 
3.5%
10
 
3.5%
6
 
2.1%
6
 
2.1%
Other values (71) 107
37.0%
Common
ValueCountFrequency (%)
9
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 289
97.0%
ASCII 9
 
3.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
33
 
11.4%
31
 
10.7%
30
 
10.4%
30
 
10.4%
14
 
4.8%
12
 
4.2%
10
 
3.5%
10
 
3.5%
6
 
2.1%
6
 
2.1%
Other values (71) 107
37.0%
ASCII
ValueCountFrequency (%)
9
100.0%

소재지
Categorical

Distinct10
Distinct (%)30.3%
Missing0
Missing (%)0.0%
Memory size396.0 B
음성군
충주시
제천시
청주시
옥천군
Other values (5)
10 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)3.0%

Sample

1st row청주시
2nd row청주시
3rd row청주시
4th row청주시
5th row충주시

Common Values

ValueCountFrequency (%)
음성군 6
18.2%
충주시 5
15.2%
제천시 5
15.2%
청주시 4
12.1%
옥천군 3
9.1%
영동군 3
9.1%
증평군 2
 
6.1%
진천군 2
 
6.1%
단양군 2
 
6.1%
보은군 1
 
3.0%

Length

2023-12-12T10:29:27.779495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:29:27.921022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
음성군 6
18.2%
충주시 5
15.2%
제천시 5
15.2%
청주시 4
12.1%
옥천군 3
9.1%
영동군 3
9.1%
증평군 2
 
6.1%
진천군 2
 
6.1%
단양군 2
 
6.1%
보은군 1
 
3.0%
Distinct27
Distinct (%)87.1%
Missing2
Missing (%)6.1%
Memory size396.0 B
2023-12-12T10:29:28.173153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length22
Mean length17.741935
Min length1

Characters and Unicode

Total characters550
Distinct characters80
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

Unique24 ?
Unique (%)77.4%

Sample

1st row충청북도 청주시 흥덕구 대신로 157
2nd row충청북도 청주시 상당구 호미로 242
3rd row충청북도 청주시 청원구 오창읍 오창대로 197
4th row충청북도 청주시 흥덕구 강내면 석화사인길 13-51
5th row충청북도 충주시 낙수당2길 8
ValueCountFrequency (%)
충청북도 28
 
20.7%
음성군 5
 
3.7%
제천시 5
 
3.7%
충주시 4
 
3.0%
청주시 4
 
3.0%
옥천군 3
 
2.2%
3
 
2.2%
옥천읍 3
 
2.2%
영동군 3
 
2.2%
영동읍 3
 
2.2%
Other values (66) 74
54.8%
2023-12-12T10:29:28.583508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
104
18.9%
34
 
6.2%
32
 
5.8%
30
 
5.5%
29
 
5.3%
22
 
4.0%
1 17
 
3.1%
16
 
2.9%
15
 
2.7%
15
 
2.7%
Other values (70) 236
42.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 363
66.0%
Space Separator 104
 
18.9%
Decimal Number 78
 
14.2%
Dash Punctuation 5
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
34
 
9.4%
32
 
8.8%
30
 
8.3%
29
 
8.0%
22
 
6.1%
16
 
4.4%
15
 
4.1%
15
 
4.1%
14
 
3.9%
13
 
3.6%
Other values (58) 143
39.4%
Decimal Number
ValueCountFrequency (%)
1 17
21.8%
3 12
15.4%
4 9
11.5%
7 7
9.0%
5 7
9.0%
2 7
9.0%
0 7
9.0%
6 4
 
5.1%
8 4
 
5.1%
9 4
 
5.1%
Space Separator
ValueCountFrequency (%)
104
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 363
66.0%
Common 187
34.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
34
 
9.4%
32
 
8.8%
30
 
8.3%
29
 
8.0%
22
 
6.1%
16
 
4.4%
15
 
4.1%
15
 
4.1%
14
 
3.9%
13
 
3.6%
Other values (58) 143
39.4%
Common
ValueCountFrequency (%)
104
55.6%
1 17
 
9.1%
3 12
 
6.4%
4 9
 
4.8%
7 7
 
3.7%
5 7
 
3.7%
2 7
 
3.7%
0 7
 
3.7%
- 5
 
2.7%
6 4
 
2.1%
Other values (2) 8
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 363
66.0%
ASCII 187
34.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
104
55.6%
1 17
 
9.1%
3 12
 
6.4%
4 9
 
4.8%
7 7
 
3.7%
5 7
 
3.7%
2 7
 
3.7%
0 7
 
3.7%
- 5
 
2.7%
6 4
 
2.1%
Other values (2) 8
 
4.3%
Hangul
ValueCountFrequency (%)
34
 
9.4%
32
 
8.8%
30
 
8.3%
29
 
8.0%
22
 
6.1%
16
 
4.4%
15
 
4.1%
15
 
4.1%
14
 
3.9%
13
 
3.6%
Other values (58) 143
39.4%
Distinct31
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Memory size396.0 B
2023-12-12T10:29:28.863018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length23
Mean length20.757576
Min length15

Characters and Unicode

Total characters685
Distinct characters86
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

Unique29 ?
Unique (%)87.9%

Sample

1st row충청북도 청주시 흥덕구 송정동 산140-61
2nd row충청북도 청주시 상당구 금천동 327
3rd row충청북도 청주시 청원구 오창읍 구룡리 375
4th row충청북도 청주시 흥덕구 강내면 탑연리 259-1
5th row충청북도 충주시 칠금동 509-79
ValueCountFrequency (%)
충청북도 32
 
19.6%
음성군 6
 
3.7%
제천시 5
 
3.1%
충주시 5
 
3.1%
청주시 4
 
2.5%
옥천읍 3
 
1.8%
옥천군 3
 
1.8%
영동군 3
 
1.8%
영동읍 3
 
1.8%
단양읍 2
 
1.2%
Other values (84) 97
59.5%
2023-12-12T10:29:29.303538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/