Overview

Dataset statistics

Number of variables18
Number of observations146
Missing cells394
Missing cells (%)15.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory21.9 KiB
Average record size in memory153.9 B

Variable types

Categorical3
Text7
Numeric8

Dataset

Description공공체육시설(생활체육시설) 현황
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=C2V7PT97153860SH50324475843&infSeq=1

Alerts

집계년도 has constant value ""Constant
소유기관명 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 소유기관명High correlation
건축면적(㎡) is highly overall correlated with 연면적(㎡) and 2 other fieldsHigh correlation
연면적(㎡) is highly overall correlated with 건축면적(㎡) and 2 other fieldsHigh correlation
경기장합계면적(㎡) is highly overall correlated with 건축면적(㎡) and 4 other fieldsHigh correlation
체육관면적(㎡) is highly overall correlated with 경기장합계면적(㎡)High correlation
수영장면적(㎡) is highly overall correlated with 경기장합계면적(㎡)High correlation
건설사업비(백만원) is highly overall correlated with 건축면적(㎡) and 2 other fieldsHigh correlation
체육관가능종목내용 has 18 (12.3%) missing valuesMissing
기타시설명 has 21 (14.4%) missing valuesMissing
부지면적(㎡) has 2 (1.4%) missing valuesMissing
건축면적(㎡) has 3 (2.1%) missing valuesMissing
연면적(㎡) has 2 (1.4%) missing valuesMissing
경기장합계면적(㎡) has 23 (15.8%) missing valuesMissing
체육관면적(㎡) has 25 (17.1%) missing valuesMissing
체육관규격 has 47 (32.2%) missing valuesMissing
수영장면적(㎡) has 81 (55.5%) missing valuesMissing
수영장규격 has 74 (50.7%) missing valuesMissing
체력단련실비고사항 has 73 (50.0%) missing valuesMissing
건설사업비(백만원) has 24 (16.4%) missing valuesMissing

Reproduction

Analysis started2023-12-29 22:04:19.618195
Analysis finished2023-12-29 22:04:42.897887
Duration23.28 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

집계년도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2021
146 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021
2nd row2021
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2021 146
100.0%

Length

2023-12-29T22:04:43.102064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-29T22:04:43.407857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 146
100.0%

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)21.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
포천시
12 
이천시
12 
화성시
 
9
시흥시
 
9
수원시
 
9
Other values (26)
95 

Length

Max length4
Median length3
Mean length3.0753425
Min length3

Unique

Unique3 ?
Unique (%)2.1%

Sample

1st row가평군
2nd row가평군
3rd row가평군
4th row고양시
5th row고양시

Common Values

ValueCountFrequency (%)
포천시 12
 
8.2%
이천시 12
 
8.2%
화성시 9
 
6.2%
시흥시 9
 
6.2%
수원시 9
 
6.2%
성남시 9
 
6.2%
양주시 8
 
5.5%
안산시 7
 
4.8%
남양주시 6
 
4.1%
여주시 6
 
4.1%
Other values (21) 59
40.4%

Length

2023-12-29T22:04:43.769995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
포천시 12
 
8.2%
이천시 12
 
8.2%
화성시 9
 
6.2%
시흥시 9
 
6.2%
수원시 9
 
6.2%
성남시 9
 
6.2%
양주시 8
 
5.5%
안산시 7
 
4.8%
여주시 6
 
4.1%
남양주시 6
 
4.1%
Other values (21) 59
40.4%

시설명
Text

Distinct145
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-29T22:04:44.178519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length15
Mean length8.7945205
Min length5

Characters and Unicode

Total characters1284
Distinct characters196
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

Unique144 ?
Unique (%)98.6%

Sample

1st row조종국민체육센터
2nd row한석봉체육관
3rd row청평호반문화체육센터
4th row고양국민체육센터
5th row고양장미란체육관
ValueCountFrequency (%)
실내체육관 8
 
4.3%
체육관 5
 
2.7%
국민체육센터 3
 
1.6%
스포츠센터 3
 
1.6%
다목적체육관 3
 
1.6%
복합체육관 2
 
1.1%
동두천시 2
 
1.1%
체육공원 2
 
1.1%
농어민문화체육센터 2
 
1.1%
교육문화센터 2
 
1.1%
Other values (154) 154
82.8%
2023-12-29T22:04:45.133501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
육 115
 
9.0%
체 111
 
8.6%
터 89
 
6.9%
센 88
 
6.9%
관 68
 
5.3%
40
 
3.1%
화 37
 
2.9%
문 34
 
2.6%
민 34
 
2.6%
포 27
 
2.1%
Other values (186) 641
49.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1235
96.2%
Space Separator 40
 
3.1%
Uppercase Letter 4
 
0.3%
Open Punctuation 2
 
0.2%
Close Punctuation 2
 
0.2%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
육 115
 
9.3%
체 111
 
9.0%
터 89
 
7.2%
센 88
 
7.1%
관 68
 
5.5%
화 37
 
3.0%
문 34
 
2.8%
민 34
 
2.8%
포 27
 
2.2%
시 25
 
2.0%
Other values (178) 607
49.1%
Uppercase Letter
ValueCountFrequency (%)
Y 1
25.0%
A 1
25.0%
M 1
25.0%
C 1
25.0%
Space Separator
ValueCountFrequency (%)
40
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1235
96.2%
Common 45
 
3.5%
Latin 4
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
육 115
 
9.3%
체 111
 
9.0%
터 89
 
7.2%
센 88
 
7.1%
관 68
 
5.5%
화 37
 
3.0%
문 34
 
2.8%
민 34
 
2.8%
포 27
 
2.2%
시 25
 
2.0%
Other values (178) 607
49.1%
Common
ValueCountFrequency (%)
40
88.9%
( 2
 
4.4%
) 2
 
4.4%
2 1
 
2.2%
Latin
ValueCountFrequency (%)
Y 1
25.0%
A 1
25.0%
M 1
25.0%
C 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1235
96.2%
ASCII 49
 
3.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
육 115
 
9.3%
체 111
 
9.0%
터 89
 
7.2%
센 88
 
7.1%
관 68
 
5.5%
화 37
 
3.0%
문 34
 
2.8%
민 34
 
2.8%
포 27
 
2.2%
시 25
 
2.0%
Other values (178) 607
49.1%
ASCII
ValueCountFrequency (%)
40
81.6%
( 2
 
4.1%
) 2
 
4.1%
Y 1
 
2.0%
A 1
 
2.0%
M 1
 
2.0%
C 1
 
2.0%
2 1
 
2.0%

소유기관명
Categorical

HIGH CORRELATION 

Distinct33
Distinct (%)22.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
포천시
12 
이천시
11 
화성시
 
9
시흥시
 
9
수원시
 
9
Other values (28)
96 

Length

Max length8
Median length3
Mean length3.1780822
Min length3

Unique

Unique4 ?
Unique (%)2.7%

Sample

1st row가평군
2nd row가평군
3rd row가평군
4th row고양시
5th row고양시

Common Values

ValueCountFrequency (%)
포천시 12
 
8.2%
이천시 11
 
7.5%
화성시 9
 
6.2%
시흥시 9
 
6.2%
수원시 9
 
6.2%
성남시 8
 
5.5%
양주시 8
 
5.5%
안산시 7
 
4.8%
남양주시 6
 
4.1%
여주시 6
 
4.1%
Other values (23) 61
41.8%

Length

2023-12-29T22:04:45.555274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
포천시 12
 
8.2%
이천시 11
 
7.5%
화성시 9
 
6.2%
시흥시 9
 
6.2%
수원시 9
 
6.2%
성남시 8
 
5.5%
양주시 8
 
5.5%
안산시 7
 
4.8%
여주시 6
 
4.1%
남양주시 6
 
4.1%
Other values (23) 61
41.8%

관리주체명
Text

Distinct57
Distinct (%)39.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-29T22:04:46.025544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length7.1438356
Min length3

Characters and Unicode

Total characters1043
Distinct characters104
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)19.9%

Sample

1st row시설관리공단
2nd row시설관리공단
3rd row시설관리공단
4th row고양도시관리공사
5th row고양도시관리공사
ValueCountFrequency (%)
포천시 10
 
6.7%
이천시 10
 
6.7%
시흥도시공사 9
 
6.0%
시설관리공단 7
 
4.7%
위탁(수원시체육회 7
 
4.7%
위탁(남양주시도시공사 6
 
4.0%
화성도시공사 5
 
3.4%
위탁[코오롱글로벌㈜ 5
 
3.4%
양주도시공사 5
 
3.4%
위탁(김포도시관리공사 5
 
3.4%
Other values (48) 80
53.7%
2023-12-29T22:04:46.750057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 141
 
13.5%
공 74
 
7.1%
사 67
 
6.4%
도 66
 
6.3%
) 42
 
4.0%
위 42
 
4.0%
( 42
 
4.0%
탁 42
 
4.0%
천 31
 
3.0%
성 23
 
2.2%
Other values (94) 473
45.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 937
89.8%
Close Punctuation 47
 
4.5%
Open Punctuation 47
 
4.5%
Other Symbol 5
 
0.5%
Uppercase Letter 4
 
0.4%
Space Separator 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 141
 
15.0%
공 74
 
7.9%
사 67
 
7.2%
도 66
 
7.0%
위 42
 
4.5%
탁 42
 
4.5%
천 31
 
3.3%
성 23
 
2.5%
포 22
 
2.3%
리 22
 
2.3%
Other values (84) 407
43.4%
Uppercase Letter
ValueCountFrequency (%)
A 1
25.0%
C 1
25.0%
M 1
25.0%
Y 1
25.0%
Close Punctuation
ValueCountFrequency (%)
) 42
89.4%
] 5
 
10.6%
Open Punctuation
ValueCountFrequency (%)
( 42
89.4%
[ 5
 
10.6%
Other Symbol
ValueCountFrequency (%)
㈜ 5
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 942
90.3%
Common 97
 
9.3%
Latin 4
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 141
 
15.0%
공 74
 
7.9%
사 67
 
7.1%
도 66
 
7.0%
위 42
 
4.5%
탁 42
 
4.5%
천 31
 
3.3%
성 23
 
2.4%
포 22
 
2.3%
리 22
 
2.3%
Other values (85) 412
43.7%
Common
ValueCountFrequency (%)
) 42
43.3%
( 42
43.3%
[ 5
 
5.2%
] 5
 
5.2%
3
 
3.1%
Latin
ValueCountFrequency (%)
A 1
25.0%
C 1
25.0%
M 1
25.0%
Y 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 937
89.8%
ASCII 101
 
9.7%
None 5
 
0.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 141
 
15.0%
공 74
 
7.9%
사 67
 
7.2%
도 66
 
7.0%
위 42
 
4.5%
탁 42
 
4.5%
천 31
 
3.3%
성 23
 
2.5%
포 22
 
2.3%
리 22
 
2.3%
Other values (84) 407
43.4%
ASCII
ValueCountFrequency (%)
) 42
41.6%
( 42
41.6%
[ 5
 
5.0%
] 5
 
5.0%
3
 
3.0%
A 1
 
1.0%
C 1
 
1.0%
M 1
 
1.0%
Y 1
 
1.0%
None
ValueCountFrequency (%)
㈜ 5
100.0%

체육관가능종목내용
Text

MISSING 

Distinct77
Distinct (%)60.2%
Missing18
Missing (%)12.3%
Memory size1.3 KiB
2023-12-29T22:04:47.171415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length20.5
Mean length11.210938
Min length1

Characters and Unicode

Total characters1435
Distinct characters97
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

Unique57 ?
Unique (%)44.5%

Sample

1st row-
2nd row배드민턴, 배구클라이밍 등
3rd row배드민턴, 배구 등
4th row공연장, 농구장,배구장등
5th row역도연습
ValueCountFrequency (%)
배드민턴 31
 
13.2%
탁구 31
 
13.2%
농구 19
 
8.1%
등 13
 
5.5%
배드민턴,배구,농구 10
 
4.3%
배드민턴,배구,농구,탁구 7
 
3.0%
다목적 7
 
3.0%
체육 7
 
3.0%
농구,배구,배드민턴 6
 
2.6%
배드민턴,농구,배구 6
 
2.6%
Other values (70) 98
41.7%
2023-12-29T22:04:48.367367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 223
15.5%
구 211
14.7%
배 155
10.8%
109
 
7.6%
드 100
 
7.0%
민 94
 
6.6%
턴 94
 
6.6%
농 86
 
6.0%
탁 57
 
4.0%
등 19
 
1.3%
Other values (87) 287
20.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1062
74.0%
Other Punctuation 241
 
16.8%
Space Separator 109
 
7.6%
Decimal Number 10
 
0.7%
Uppercase Letter 8
 
0.6%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 211
19.9%
배 155
14.6%
드 100
9.4%
민 94
8.9%
턴 94
8.9%
농 86
 
8.1%
탁 57
 
5.4%
등 19
 
1.8%
장 14
 
1.3%
스 12
 
1.1%
Other values (74) 220
20.7%
Decimal Number
ValueCountFrequency (%)
3 4
40.0%
1 3
30.0%
2 2
20.0%
4 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
, 223
92.5%
. 12
 
5.0%
: 6
 
2.5%
Uppercase Letter
ValueCountFrequency (%)
X 4
50.0%
G 4
50.0%
Space Separator
ValueCountFrequency (%)
109
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1062
74.0%
Common 365
 
25.4%
Latin 8
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 211
19.9%
배 155
14.6%
드 100
9.4%
민 94
8.9%
턴 94
8.9%
농 86
 
8.1%
탁 57
 
5.4%
등 19
 
1.8%
장 14
 
1.3%
스 12
 
1.1%
Other values (74) 220
20.7%
Common
ValueCountFrequency (%)
, 223
61.1%
109
29.9%
. 12
 
3.3%
: 6
 
1.6%
3 4
 
1.1%
1 3
 
0.8%
2 2
 
0.5%
) 2
 
0.5%
( 2
 
0.5%
- 1
 
0.3%
Latin
ValueCountFrequency (%)
X 4
50.0%
G 4
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1062
74.0%
ASCII 373
 
26.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 223
59.8%
109
29.2%
. 12
 
3.2%
: 6
 
1.6%
3 4
 
1.1%
X 4
 
1.1%
G 4
 
1.1%
1 3
 
0.8%
2 2
 
0.5%
) 2
 
0.5%
Other values (3) 4
 
1.1%
Hangul
ValueCountFrequency (%)
구 211
19.9%
배 155
14.6%
드 100
9.4%
민 94
8.9%
턴 94
8.9%
농 86
 
8.1%
탁 57
 
5.4%
등 19
 
1.8%
장 14
 
1.3%
스 12
 
1.1%
Other values (74) 220
20.7%

기타시설명
Text

MISSING 

Distinct89
Distinct (%)71.2%
Missing21
Missing (%)14.4%
Memory size1.3 KiB
2023-12-29T22:04:49.144026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length26
Mean length13.664
Min length2

Characters and Unicode

Total characters1708
Distinct characters132
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique75 ?
Unique (%)60.0%

Sample

1st row체력단련실,헬스장, 다목적실
2nd row샤워실, 회의실, 사무실 등
3rd row헬스장
4th row사무실, 헬스장 등
5th row탁구장 등
ValueCountFrequency (%)
샤워실 38
 
13.0%
탈의실 30
 
10.2%
사무실 29
 
9.9%
등 21
 
7.2%
화장실 19
 
6.5%
헬스장 9
 
3.1%
다목적실 8
 
2.7%
에어로빅장 6
 
2.0%
탈의실,사무실 5
 
1.7%
샤워실,탈의실,사무실,다목적강당 4
 
1.4%
Other values (93) 124
42.3%
2023-12-29T22:04:50.241672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
실 242
 
14.2%
, 229
 
13.4%
174
 
10.2%
장 83
 
4.9%
무 60
 
3.5%
워 60
 
3.5%
샤 59
 
3.5%
의 58
 
3.4%
사 58
 
3.4%
탈 51
 
3.0%
Other values (122) 634
37.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1278
74.8%
Other Punctuation 232
 
13.6%
Space Separator 174
 
10.2%
Uppercase Letter 14
 
0.8%
Decimal Number 4
 
0.2%
Open Punctuation 3
 
0.2%
Close Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
실 242
18.9%
장 83
 
6.5%
무 60
 
4.7%
워 60
 
4.7%
샤 59
 
4.6%
의 58
 
4.5%
사 58
 
4.5%
탈 51
 
4.0%
스 38
 
3.0%
다 28
 
2.2%
Other values (112) 541
42.3%
Decimal Number
ValueCountFrequency (%)
4 2
50.0%
6 1
25.0%
2 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 229
98.7%
. 3
 
1.3%
Uppercase Letter
ValueCountFrequency (%)
X 7
50.0%
G 7
50.0%
Space Separator
ValueCountFrequency (%)
174
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1278
74.8%
Common 416
 
24.4%
Latin 14
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
실 242
18.9%
장 83
 
6.5%
무 60
 
4.7%
워 60
 
4.7%
샤 59
 
4.6%
의 58
 
4.5%
사 58
 
4.5%
탈 51
 
4.0%
스 38
 
3.0%
다 28
 
2.2%
Other values (112) 541
42.3%
Common
ValueCountFrequency (%)
, 229
55.0%
174
41.8%
. 3
 
0.7%
( 3
 
0.7%
) 3
 
0.7%
4 2
 
0.5%
6 1
 
0.2%
2 1
 
0.2%
Latin
ValueCountFrequency (%)
X 7
50.0%
G 7
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1278
74.8%
ASCII 430
 
25.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
실 242
18.9%
장 83
 
6.5%
무 60
 
4.7%
워 60
 
4.7%
샤 59
 
4.6%
의 58
 
4.5%
사 58
 
4.5%
탈 51
 
4.0%
스 38
 
3.0%
다 28
 
2.2%
Other values (112) 541
42.3%
ASCII
ValueCountFrequency (%)
, 229
53.3%
174
40.5%
X 7
 
1.6%
G 7
 
1.6%
. 3
 
0.7%
( 3
 
0.7%
) 3
 
0.7%
4 2
 
0.5%
6 1
 
0.2%
2 1
 
0.2%

준공연도
Real number (ℝ)

Distinct27
Distinct (%)18.6%
Missing1
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean2011.2345
Minimum1992
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-29T22:04:50.696791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1992
5-th percentile1998.2
Q12008
median2012
Q32017
95-th percentile2020
Maximum2021
Range29
Interquartile range (IQR)9

Descriptive statistics

Standard deviation6.6937095
Coefficient of variation (CV)0.0033281597
Kurtosis0.20334556
Mean2011.2345
Median Absolute Deviation (MAD)5
Skewness-0.77536399
Sum291629
Variance44.805747
MonotonicityNot monotonic
2023-12-29T22:04:51.149597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
2011 13
 
8.9%
2019 12
 
8.2%
2013 12
 
8.2%
2017 11
 
7.5%
2014 10
 
6.8%
2010 9
 
6.2%
2018 8
 
5.5%
2008 7
 
4.8%
2002 7
 
4.8%
2009 7
 
4.8%
Other values (17) 49
33.6%
ValueCountFrequency (%)
1992 2
 
1.4%
1994 2
 
1.4%
1995 1
 
0.7%
1996 1
 
0.7%
1998 2
 
1.4%
1999 1
 
0.7%
2001 2
 
1.4%
2002 7
4.8%
2003 3
2.1%
2004 3
2.1%
ValueCountFrequency (%)
2021 4
 
2.7%
2020 5
3.4%
2019 12
8.2%
2018 8
5.5%
2017 11
7.5%
2016 4
 
2.7%
2015 6
4.1%
2014 10
6.8%
2013 12
8.2%
2012 2
 
1.4%

부지면적(㎡)
Real number (ℝ)

MISSING 

Distinct143
Distinct (%)99.3%
Missing2
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean31212.077
Minimum330
Maximum305320
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-29T22:04:51.621782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum330
5-th percentile1629.75
Q14713.25
median10910
Q332860.5
95-th percentile123518.13
Maximum305320
Range304990
Interquartile range (IQR)28147.25

Descriptive statistics

Standard deviation48783.334
Coefficient of variation (CV)1.5629634
Kurtosis11.595554
Mean31212.077
Median Absolute Deviation (MAD)8220
Skewness3.0892297
Sum4494539.2
Variance2.3798136 × 109
MonotonicityNot monotonic
2023-12-29T22:04:52.065090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
104897.0 2
 
1.4%
33278.0 1
 
0.7%
15560.0 1
 
0.7%
12849.0 1
 
0.7%
7988.0 1
 
0.7%
81403.0 1
 
0.7%
22214.0 1
 
0.7%
2891.0 1
 
0.7%
6559.0 1
 
0.7%
25173.0 1
 
0.7%
Other values (133) 133
91.1%
(Missing) 2
 
1.4%
ValueCountFrequency (%)
330.0 1
0.7%
754.0 1
0.7%
836.0 1
0.7%
859.0 1
0.7%
1006.0 1
0.7%
1153.0 1
0.7%
1500.0 1
0.7%
1569.0 1
0.7%
1974.0 1
0.7%
2025.0 1
0.7%
ValueCountFrequency (%)
305320.0 1
0.7%
275280.0 1
0.7%
203778.0 1
0.7%
182829.0 1
0.7%
144936.0 1
0.7%
139821.0 1
0.7%
127588.0 1
0.7%
123747.0 1
0.7%
122221.2 1
0.7%
115066.0 1
0.7%

건축면적(㎡)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct143
Distinct (%)100.0%
Missing3
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean2853.9079
Minimum330
Maximum28156
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-29T22:04:52.456358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum330
5-th percentile544.73
Q11139.5
median1931
Q33202.28
95-th percentile7709.1
Maximum28156
Range27826
Interquartile range (IQR)2062.78

Descriptive statistics

Standard deviation3250.7805
Coefficient of variation (CV)1.1390629
Kurtosis27.354553
Mean2853.9079
Median Absolute Deviation (MAD)975
Skewness4.3400124
Sum408108.82
Variance10567574
MonotonicityNot monotonic
2023-12-29T22:04:52.876574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3042.33 1
 
0.7%
2557.0 1
 
0.7%
1133.09 1
 
0.7%
2568.0 1
 
0.7%
4438.0 1
 
0.7%
5225.0 1
 
0.7%
3373.0 1
 
0.7%
1793.0 1
 
0.7%
1236.0 1
 
0.7%
882.9 1
 
0.7%
Other values (133) 133
91.1%
(Missing) 3
 
2.1%
ValueCountFrequency (%)
330.0 1
0.7%
390.3 1
0.7%
442.53 1
0.7%
446.0 1
0.7%
478.0 1
0.7%
525.0 1
0.7%
534.89 1
0.7%
542.0 1
0.7%
569.3 1
0.7%
594.0 1
0.7%
ValueCountFrequency (%)
28156.0 1
0.7%
16405.82 1
0.7%
12352.0 1
0.7%
9721.0 1
0.7%
9560.0 1
0.7%
9556.78 1
0.7%
8173.0 1
0.7%
7726.0 1
0.7%
7557.0 1
0.7%
7329.0 1
0.7%

연면적(㎡)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct143
Distinct (%)99.3%
Missing2
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean6793.3001
Minimum330
Maximum41724
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-29T22:04:53.162747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum330
5-th percentile666.55
Q11667.25
median3880
Q38742
95-th percentile25733.95
Maximum41724
Range41394
Interquartile range (IQR)7074.75

Descriptive statistics

Standard deviation8168.8705
Coefficient of variation (CV)1.2024893
Kurtosis6.8987912
Mean6793.3001
Median Absolute Deviation (MAD)2894
Skewness2.5205946
Sum978235.22
Variance66730445
MonotonicityNot monotonic
2023-12-29T22:04:53.415187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9584.0 2
 
1.4%
7880.95 1
 
0.7%
26167.0 1
 
0.7%
1992.05 1
 
0.7%
6664.0 1
 
0.7%
13647.0 1
 
0.7%
8216.0 1
 
0.7%
4241.0 1
 
0.7%
8712.0 1
 
0.7%
3257.0 1
 
0.7%
Other values (133) 133
91.1%
(Missing) 2
 
1.4%
ValueCountFrequency (%)
330.0 1
0.7%
390.0 1
0.7%
439.29 1
0.7%
441.0 1
0.7%
525.0 1
0.7%
542.0 1
0.7%
594.0 1
0.7%
652.0 1
0.7%
749.0 1
0.7%
754.0 1
0.7%
ValueCountFrequency (%)
41724.0 1
0.7%
41056.0 1
0.7%
39370.75 1
0.7%
35849.0 1
0.7%
33471.92 1
0.7%
31097.0 1
0.7%
26925.87 1
0.7%
26167.0 1
0.7%
23280.0 1
0.7%
20332.72 1
0.7%

경기장합계면적(㎡)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct116
Distinct (%)94.3%
Missing23
Missing (%)15.8%
Infinite0
Infinite (%)0.0%
Mean1871.4826
Minimum25
Maximum12392
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-29T22:04:53.670033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum25
5-th percentile449.4
Q1828
median1548
Q32272
95-th percentile3814.9
Maximum12392
Range12367
Interquartile range (IQR)1444

Descriptive statistics

Standard deviation1702.8423
Coefficient of variation (CV)0.90988948
Kurtosis15.896208
Mean1871.4826
Median Absolute Deviation (MAD)720
Skewness3.4144608
Sum230192.36
Variance2899672
MonotonicityNot monotonic
2023-12-29T22:04:54.042662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
828.0 4
 
2.7%
2858.61 3
 
2.1%
2171.0 2
 
1.4%
807.0 2
 
1.4%
3431.0 1
 
0.7%
1064.0 1
 
0.7%
1320.0 1
 
0.7%
2087.0 1
 
0.7%
1370.0 1
 
0.7%
1697.0 1
 
0.7%
Other values (106) 106
72.6%
(Missing) 23
 
15.8%
ValueCountFrequency (%)
25.0 1
0.7%
229.0 1
0.7%
252.0 1
0.7%
308.0 1
0.7%
330.0 1
0.7%
398.52 1
0.7%
441.0 1
0.7%
525.0 1
0.7%
542.0 1
0.7%
594.0 1
0.7%
ValueCountFrequency (%)
12392.0 1
0.7%
9584.0 1
0.7%
8400.0 1
0.7%
7009.0 1
0.7%
4254.0 1
0.7%
3966.0 1
0.7%
3836.0 1
0.7%
3625.0 1
0.7%
3495.0 1
0.7%
3431.0 1
0.7%

체육관면적(㎡)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct116
Distinct (%)95.9%
Missing25
Missing (%)17.1%
Infinite0
Infinite (%)0.0%
Mean1159.1235
Minimum143.91
Maximum5708
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-29T22:04:54.487997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum143.91
5-th percentile340
Q1743.63
median907
Q31252.49
95-th percentile2775
Maximum5708
Range5564.09
Interquartile range (IQR)508.86

Descriptive statistics

Standard deviation921.65352
Coefficient of variation (CV)0.79512972
Kurtosis12.821805
Mean1159.1235
Median Absolute Deviation (MAD)225.41
Skewness3.2995537
Sum140253.94
Variance849445.22
MonotonicityNot monotonic
2023-12-29T22:04:54.884075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
807.0 2
 
1.4%
600.0 2
 
1.4%
2775.0 2
 
1.4%
907.0 2
 
1.4%
1200.0 2
 
1.4%
1417.0 1
 
0.7%
870.0 1
 
0.7%
904.0 1
 
0.7%
702.0 1
 
0.7%
1407.0 1
 
0.7%
Other values (106) 106
72.6%
(Missing) 25
 
17.1%
ValueCountFrequency (%)
143.91 1
0.7%
200.0 1
0.7%
252.0 1
0.7%
277.0 1
0.7%
308.0 1
0.7%
330.0 1
0.7%
340.0 1
0.7%
390.0 1
0.7%
398.52 1
0.7%
441.0 1
0.7%
ValueCountFrequency (%)
5708.0 1
0.7%
5562.83 1
0.7%
5473.0 1
0.7%
4502.0 1
0.7%
2846.0 1
0.7%
2775.0 2
1.4%
2392.0 1
0.7%
1969.0 1
0.7%
1960.0 1
0.7%
1953.35 1
0.7%

체육관규격
Text

MISSING 

Distinct95
Distinct (%)96.0%
Missing47
Missing (%)32.2%
Memory size1.3 KiB
2023-12-29T22:04:55.425316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length8.1616162
Min length1

Characters and Unicode

Total characters808
Distinct characters24
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique94 ?
Unique (%)94.9%

Sample

1st row-
2nd row56x35m
3rd row22.5×30m
4th row27×27m
5th row6997석
ValueCountFrequency (%)
x 20
 
13.9%
32x19m 5
 
3.5%
28×15 2
 
1.4%
12m 2
 
1.4%
19m 2
 
1.4%
36m 2
 
1.4%
25m 2
 
1.4%
54m 1
 
0.7%
21.8m 1
 
0.7%
32.2m 1
 
0.7%
Other values (106) 106
73.6%
2023-12-29T22:04:56.237240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
m 105
13.0%
2 101
12.5%
3 92
11.4%
× 69
8.5%
1 64
7.9%
. 55
 
6.8%
4 49
 
6.1%
45
 
5.6%
5 42
 
5.2%
0 39
 
4.8%
Other values (14) 147
18.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 481
59.5%
Lowercase Letter 135
 
16.7%
Math Symbol 69
 
8.5%
Other Punctuation 61
 
7.5%
Space Separator 45
 
5.6%
Uppercase Letter 9
 
1.1%
Other Letter 6
 
0.7%
Other Symbol 1
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 101
21.0%
3 92
19.1%
1 64
13.3%
4 49
10.2%
5 42
8.7%
0 39
 
8.1%
6 32
 
6.7%
8 25
 
5.2%
9 22
 
4.6%
7 15
 
3.1%
Other Letter
ValueCountFrequency (%)
면 3
50.0%
석 1
 
16.7%
구 1
 
16.7%
농 1
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 55
90.2%
* 5
 
8.2%
, 1
 
1.6%
Lowercase Letter
ValueCountFrequency (%)
m 105
77.8%
x 30
 
22.2%
Math Symbol
ValueCountFrequency (%)
× 69
100.0%
Space Separator
ValueCountFrequency (%)
45
100.0%
Uppercase Letter
ValueCountFrequency (%)
X 9
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 658
81.4%
Latin 144
 
17.8%
Hangul 6
 
0.7%

Most frequent character per script

Common
ValueCountFrequency (%)
2 101
15.3%
3 92
14.0%
× 69
10.5%
1 64
9.7%
. 55
8.4%
4 49
7.4%
45
6.8%
5 42
6.4%
0 39
 
5.9%
6 32
 
4.9%
Other values (7) 70
10.6%
Hangul
ValueCountFrequency (%)
면 3
50.0%
석 1
 
16.7%
구 1
 
16.7%
농 1
 
16.7%
Latin
ValueCountFrequency (%)
m 105
72.9%
x 30
 
20.8%
X 9
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 732
90.6%
None 69
 
8.5%
Hangul 6
 
0.7%
CJK Compat 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
m 105
14.3%
2 101
13.8%
3 92
12.6%
1 64
8.7%
. 55
7.5%
4 49
6.7%
45
6.1%
5 42
 
5.7%
0 39
 
5.3%
6 32
 
4.4%
Other values (8) 108
14.8%
None
ValueCountFrequency (%)
× 69
100.0%
Hangul
ValueCountFrequency (%)
면 3
50.0%
석 1
 
16.7%
구 1
 
16.7%
농 1
 
16.7%
CJK Compat
ValueCountFrequency (%)
㎡ 1
100.0%

수영장면적(㎡)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct61
Distinct (%)93.8%
Missing81
Missing (%)55.5%
Infinite0
Infinite (%)0.0%
Mean1303.872
Minimum300
Maximum6919
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-29T22:04:56.608192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum300
5-th percentile436
Q1819
median1058
Q31322
95-th percentile2528.11
Maximum6919
Range6619
Interquartile range (IQR)503

Descriptive statistics

Standard deviation1027.5078
Coefficient of variation (CV)0.78804344
Kurtosis15.287916
Mean1303.872
Median Absolute Deviation (MAD)264
Skewness3.4976216
Sum84751.68
Variance1055772.2
MonotonicityNot monotonic
2023-12-29T22:04:57.164056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1250.0 5
 
3.4%
793.0 1
 
0.7%
773.28 1
 
0.7%
415.65 1
 
0.7%
1239.0 1
 
0.7%
1526.02 1
 
0.7%
1799.58 1
 
0.7%
878.89 1
 
0.7%
1184.0 1
 
0.7%
820.0 1
 
0.7%
Other values (51) 51
34.9%
(Missing) 81
55.5%
ValueCountFrequency (%)
300.0 1
0.7%
360.0 1
0.7%
415.65 1
0.7%
420.0 1
0.7%
500.0 1
0.7%
600.0 1
0.7%
660.0 1
0.7%
666.01 1
0.7%
681.36 1
0.7%
687.0 1
0.7%
ValueCountFrequency (%)
6919.0 1
0.7%
4768.0 1
0.7%
3930.0 1
0.7%
2538.0 1
0.7%
2488.55 1
0.7%
2334.0 1
0.7%
2027.0 1
0.7%
1994.0 1
0.7%
1917.0 1
0.7%
1892.0 1
0.7%

수영장규격
Text

MISSING 

Distinct51
Distinct (%)70.8%
Missing74
Missing (%)50.7%
Memory size1.3 KiB
2023-12-29T22:04:57.537448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length8.5
Min length1

Characters and Unicode

Total characters612
Distinct characters24
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)56.9%

Sample

1st row6레인(25m)
2nd row6레인(25m)
3rd row6레인(25m)
4th row50m×26m
5th row25×15m
ValueCountFrequency (%)
6레인(25m 11
 
14.3%
25m 5
 
6.5%
25m×15m 4
 
5.2%
25(8레인 3
 
3.9%
50m(10레인 2
 
2.6%
50m×20m10레인 2
 
2.6%
25m×6레인 2
 
2.6%
25m×13m 2
 
2.6%
25m(6레인 2
 
2.6%
10레인(50m 2
 
2.6%
Other values (42) 42
54.5%
2023-12-29T22:04:58.312411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
m 101
16.5%
5 89
14.5%
2 69
11.3%
인 49
8.0%
레 49
8.0%
( 36
 
5.9%
× 36
 
5.9%
1 36
 
5.9%
) 35
 
5.7%
0 31
 
5.1%
Other values (14) 81
13.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 283
46.2%
Lowercase Letter 105
 
17.2%
Other Letter 101
 
16.5%
Open Punctuation 36
 
5.9%
Math Symbol 36
 
5.9%
Close Punctuation 35
 
5.7%
Other Punctuation 8
 
1.3%
Space Separator 5
 
0.8%
Uppercase Letter 2
 
0.3%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 89
31.4%
2 69
24.4%
1 36
12.7%
0 31
 
11.0%
6 25
 
8.8%
3 14
 
4.9%
8 10
 
3.5%
7 5
 
1.8%
4 4
 
1.4%
Other Letter
ValueCountFrequency (%)
인 49
48.5%
레 49
48.5%
유 1
 
1.0%
아 1
 
1.0%
풀 1
 
1.0%
Lowercase Letter
ValueCountFrequency (%)
m 101
96.2%
x 4
 
3.8%
Other Punctuation
ValueCountFrequency (%)
. 7
87.5%
, 1
 
12.5%
Open Punctuation
ValueCountFrequency (%)
( 36
100.0%
Math Symbol
ValueCountFrequency (%)
× 36
100.0%
Close Punctuation
ValueCountFrequency (%)
) 35
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Uppercase Letter
ValueCountFrequency (%)
X 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 404
66.0%
Latin 107
 
17.5%
Hangul 101
 
16.5%

Most frequent character per script

Common
ValueCountFrequency (%)
5 89
22.0%
2 69
17.1%
( 36
8.9%
× 36
8.9%
1 36
8.9%
) 35
 
8.7%
0 31
 
7.7%
6 25
 
6.2%
3 14
 
3.5%
8 10
 
2.5%
Other values (6) 23
 
5.7%
Hangul
ValueCountFrequency (%)
인 49
48.5%
레 49
48.5%
유 1
 
1.0%
아 1
 
1.0%
풀 1
 
1.0%
Latin
ValueCountFrequency (%)
m 101
94.4%
x 4
 
3.7%
X 2
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 475
77.6%
Hangul 101
 
16.5%
None 36
 
5.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
m 101
21.3%
5 89
18.7%
2 69
14.5%
( 36
 
7.6%
1 36
 
7.6%
) 35
 
7.4%
0 31
 
6.5%
6 25
 
5.3%
3 14
 
2.9%
8 10
 
2.1%
Other values (8) 29
 
6.1%
Hangul
ValueCountFrequency (%)
인 49
48.5%
레 49
48.5%
유 1
 
1.0%
아 1
 
1.0%
풀 1
 
1.0%
None
ValueCountFrequency (%)
× 36
100.0%

체력단련실비고사항
Text

MISSING 

Distinct67
Distinct (%)91.8%
Missing73
Missing (%)50.0%
Memory size1.3 KiB
2023-12-29T22:04:58.790117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.3013699
Min length1

Characters and Unicode

Total characters241
Distinct characters13
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

Unique63 ?
Unique (%)86.3%

Sample

1st row149
2nd row159
3rd row362
4th row유
5th row유
ValueCountFrequency (%)
277 3
 
4.1%
유 3
 
4.1%
200 2
 
2.7%
400 2
 
2.7%
490 1
 
1.4%
1350 1
 
1.4%
51 1
 
1.4%
294 1
 
1.4%
856 1
 
1.4%
626 1
 
1.4%
Other values (57) 57
78.1%
2023-12-29T22:04:59.679242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 31
12.9%
4 29
12.0%
2 28
11.6%
3 26
10.8%
0 21
8.7%
5 20
8.3%
7 19
7.9%
6 19
7.9%
9 17
7.1%
. 14
5.8%
Other values (3) 17
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 223
92.5%
Other Punctuation 14
 
5.8%
Other Letter 3
 
1.2%
Dash Punctuation 1
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 31
13.9%
4 29
13.0%
2 28
12.6%
3 26
11.7%
0 21
9.4%
5 20
9.0%
7 19
8.5%
6 19
8.5%
9 17
7.6%
8 13
5.8%
Other Punctuation
ValueCountFrequency (%)
. 14
100.0%
Other Letter
ValueCountFrequency (%)
유 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 238
98.8%
Hangul 3
 
1.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 31
13.0%
4 29
12.2%
2 28
11.8%
3 26
10.9%
0 21
8.8%
5 20
8.4%
7 19
8.0%
6 19
8.0%
9 17
7.1%
. 14
5.9%
Other values (2) 14
5.9%
Hangul
ValueCountFrequency (%)
유 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 238
98.8%
Hangul 3
 
1.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 31
13.0%
4 29
12.2%
2 28
11.8%
3 26
10.9%
0 21
8.8%
5 20
8.4%
7 19
8.0%
6 19
8.0%
9 17
7.1%
. 14
5.9%
Other values (2) 14
5.9%
Hangul
ValueCountFrequency (%)
유 3
100.0%

건설사업비(백만원)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct114
Distinct (%)93.4%
Missing24
Missing (%)16.4%
Infinite0
Infinite (%)0.0%
Mean14734.895
Minimum410
Maximum99128
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-29T22:05:00.100086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum410
5-th percentile977.2
Q13424.15
median9135.5
Q319468.25
95-th percentile49512.8
Maximum99128
Range98718
Interquartile range (IQR)16044.1

Descriptive statistics

Standard deviation17201.195
Coefficient of variation (CV)1.1673782
Kurtosis6.6987365
Mean14734.895
Median Absolute Deviation (MAD)6549.5
Skewness2.3425185
Sum1797657.2
Variance2.9588111 × 108
MonotonicityNot monotonic
2023-12-29T22:05:00.516581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10000.0 2
 
1.4%
900.0 2
 
1.4%
3790.0 2
 
1.4%
27500.0 2
 
1.4%
1150.0 2
 
1.4%
1200.0 2
 
1.4%
4950.0 2
 
1.4%
18600.0 2
 
1.4%
56432.0 1
 
0.7%
7359.0 1
 
0.7%
Other values (104) 104
71.2%
(Missing) 24
 
16.4%
ValueCountFrequency (%)
410.0 1
0.7%
630.0 1
0.7%
650.0 1
0.7%
900.0 2
1.4%
931.0 1
0.7%
976.0 1
0.7%
1000.0 1
0.7%
1010.0 1
0.7%
1150.0 2
1.4%
1200.0 2
1.4%
ValueCountFrequency (%)
99128.0 1
0.7%
79170.0 1
0.7%
74600.0 1
0.7%
62000.0 1
0.7%
61610.0 1
0.7%
56432.0 1
0.7%
49800.0 1
0.7%
44056.0 1
0.7%
38767.0 1
0.7%
38000.0 1
0.7%

Interactions

2023-12-29T22:04:39.379533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:26.423312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:28.553765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:30.356245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:32.169435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:34.112562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:35.890498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:37.405275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:39.528763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:26.661300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:28.839915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:30.595136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:32.411988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:34.355663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:36.082680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:37.657541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:39.694211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:26.925549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:29.085482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:30.848245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:32.654180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:34.601413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:36.242167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:37.910660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:39.936473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:27.164602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:29.329816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:31.083152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:32.889970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:34.811411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:36.387973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:38.151950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:40.195176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:27.398077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:29.567447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:31.316120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:33.114107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:34.955653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:36.524797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:38.411266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:40.439124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:27.791358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:29.817169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:31.558918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:33.362047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:35.109527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:36.685230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:38.722345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:40.675901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:27.936882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:29.967652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:31.788554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:33.603230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:35.297336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:36.972279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:38.987416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:40.852055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:28.200935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:30.128232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:31.944517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:33.864028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:35.634968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:37.178536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-29T22:04:39.242355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-29T22:05:00.815916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명소유기관명관리주체명체육관가능종목내용기타시설명준공연도부지면적(㎡)건축면적(㎡)연면적(㎡)경기장합계면적(㎡)체육관면적(㎡)체육관규격수영장면적(㎡)수영장규격체력단련실비고사항건설사업비(백만원)
시군명1.0001.0000.9980.9800.9950.5390.0000.4810.6510.7280.6981.0000.6130.9080.9760.676
소유기관명1.0001.0000.9990.9780.9900.6050.2310.8050.8510.7500.7051.0000.7580.9010.9810.698
관리주체명0.9980.9991.0000.9670.9930.6930.0000.7680.9070.8970.7151.0000.7210.9540.9840.803
체육관가능종목내용0.9800.9780.9671.0000.9720.6530.9440.8980.7280.9580.8310.9910.7620.6720.0000.881
기타시설명0.9950.9900.9930.9721.0000.6970.6290.0000.0000.0000.8220.9990.0000.8960.0000.943
준공연도0.5390.6050.6930.6530.6971.0000.0000.0000.7150.0000.4450.9660.4000.0000.9520.278
부지면적(㎡)0.0000.2310.0000.9440.6290.0001.0000.5510.3530.0000.4980.9880.5690.7680.0000.425
건축면적(㎡)0.4810.8050.7680.8980.0000.0000.5511.0000.8070.3410.4961.0000.6330.8600.0000.779
연면적(㎡)0.6510.8510.9070.7280.0000.7150.3530.8071.0000.5950.5231.0000.4090.7310.9380.746
경기장합계면적(㎡)0.7280.7500.8970.9580.0000.0000.0000.3410.5951.0000.6861.0000.9540.0000.0000.457
체육관면적(㎡)0.6980.7050.7150.8310.8220.4450.4980.4960.5230.6861.0001.0000.6280.0000.0000.775
체육관규격1.0001.0001.0000.9910.9990.9660.9881.0001.0001.0001.0001.0001.0001.0001.0001.000
수영장면적(㎡)0.6130.7580.7210.7620.0000.4000.5690.6330.4090.9540.6281.0001.0000.7140.0000.725
수영장규격0.9080.9010.9540.6720.8960.0000.7680.8600.7310.0000.0001.0000.7141.0000.8580.000
체력단련실비고사항0.9760.9810.9840.0000.0000.9520.0000.0000.9380.0000.0001.0000.0000.8581.0000.000
건설사업비(백만원)0.6760.6980.8030.8810.9430.2780.4250.7790.7460.4570.7751.0000.7250.0000.0001.000
2023-12-29T22:05:01.114289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소유기관명시군명
소유기관명1.0000.988
시군명0.9881.000
2023-12-29T22:05:01.370587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
준공연도부지면적(㎡)건축면적(㎡)연면적(㎡)경기장합계면적(㎡)체육관면적(㎡)수영장면적(㎡)건설사업비(백만원)시군명소유기관명
준공연도1.0000.007-0.108-0.166-0.117-0.075-0.1540.1330.2000.224
부지면적(㎡)0.0071.0000.4040.2330.2210.1920.1980.1270.0000.084
건축면적(㎡)-0.1080.4041.0000.8390.6040.4270.2730.6750.1910.440
연면적(㎡)-0.1660.2330.8391.0000.6530.4140.3170.8050.2690.462
경기장합계면적(㎡)-0.1170.2210.6040.6531.0000.5460.6180.6670.3480.363
체육관면적(㎡)-0.0750.1920.4270.4140.5461.0000.1940.4100.3360.343
수영장면적(㎡)-0.1540.1980.2730.3170.6180.1941.0000.3330.0000.334
건설사업비(백만원)0.1330.1270.6750.8050.6670.4100.3331.0000.2940.308
시군명0.2000.0000.1910.2690.3480.3360.0000.2941.0000.988
소유기관명0.2240.0840.4400.4620.3630.3430.3340.3080.9881.000

Missing values

2023-12-29T22:04:41.335551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-29T22:04:42.019838image/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.
2023-12-29T22:04:42.539551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

집계년도시군명시설명소유기관명관리주체명체육관가능종목내용기타시설명준공연도부지면적(㎡)건축면적(㎡)연면적(㎡)경기장합계면적(㎡)체육관면적(㎡)체육관규격수영장면적(㎡)수영장규격체력단련실비고사항건설사업비(백만원)
02021가평군조종국민체육센터가평군시설관리공단-체력단련실,헬스장, 다목적실20087500.01537.02997.01002.0<NA>-853.06레인(25m)1494950.0
12021가평군한석봉체육관가평군시설관리공단배드민턴, 배구클라이밍 등샤워실, 회의실, 사무실 등201662903.03042.337880.953221.01960.056x35m1102.06레인(25m)15917966.0
22021가평군청평호반문화체육센터가평군시설관리공단배드민턴, 배구 등헬스장20194582.02348.07318.02487.01173.0<NA>952.06레인(25m)36218600.0
32021고양시고양국민체육센터고양시고양도시관리공사공연장, 농구장,배구장등사무실, 헬스장 등2013182829.0985.192710.0675.0675.022.5×30m<NA><NA>유5277.0
42021고양시고양장미란체육관고양시고양도시관리공사역도연습탁구장 등20113180.7534.893444.92980.49980.027×27m<NA><NA>유11070.0
52021고양시고양체육관고양시고양도시관리공사농구에어로빅장,헬스장,스쿼시장2011305320.016405.8239370.75<NA>5708.06997석4768.050m×26m유99128.0
62021고양시일산 스포츠센터국민체육진흥공단한국체육산업개발<NA>에어로빅장,헬스장,스쿼시장19983717.02593.2535849.01835.61148.610×27.5m687.025×15m<NA>38000.0
72021고양시덕양 어울림누리몸과마음닦음터(체육관)고양시고양도시관리공사핸드볼,배구,농구에어로빅장,헬스장,스쿼시장200513400.07329.013400.012392.05473.0<NA>6919.050m×20m<NA><NA>
82021과천시과천시 청소년수련관체육관과천시과천도시공사배드민턴,농구,배구,풋살,탁구다목적실20078331.02489.03772.03373.01081.0<NA>1892.025mx5레인40014935.0
92021과천시과천 시민회관다목적체육관과천시과천도시공사배드민턴,농구,배구,풋살,탁구헬스,유도,에어로빅,태권도, 볼링 등199522237.07726.041056.025.04502.040×25m2538.025m×6레인61056432.0
집계년도시군명시설명소유기관명관리주체명체육관가능종목내용기타시설명준공연도부지면적(㎡)건축면적(㎡)연면적(㎡)경기장합계면적(㎡)체육관면적(㎡)체육관규격수영장면적(㎡)수영장규격체력단련실비고사항건설사업비(백만원)
1362021하남시하남국민체육센터하남시하남도시공사배드민턴,농구,배구,핸드볼샤워실,탈의실,사무실2007139821.03420.08832.0792.01417.040×20×16m872.06레인(25m)195<NA>
1372021화성시그린환경센터 주민편익시설화성시화성도시공사<NA>어린이놀이시설, 암벽, 스킨스쿠버장, 탁구장, 댄스실, 헬스장, 사무실2011<NA><NA><NA><NA><NA><NA><NA>25X13(5레인)<NA><NA>
1382021화성시동탄복합문화센터화성시화성시문화재단<NA>헬스장, 에어로빅장, 다목적실, 사무실2010<NA><NA><NA><NA><NA><NA><NA>25X20(8레인)<NA><NA>
1392021화성시화성남부국민체육센터화성시화성도시공사<NA>사무실, 다목적실201817875.51558.513830.67<NA>1238.7<NA><NA>25(6레인)<NA><NA>
1402021화성시동탄중앙어울림센터화성시화성도시공사<NA>체력단련실, 사무실201811128.03581.9811783.3<NA><NA><NA><NA>25(8레인)<NA>49800.0
1412021화성시반월체육센터화성시화성도시공사<NA>헬스장, 샤워실, 다목적실, 사무실201951409.03359.054960.23<NA><NA><NA><NA>25(8레인)<NA>44056.0
1422021화성시유앤아이센터화성시위탁(화성문화재단)농구,배구,탁구빙상장,수영장,골프연습장,에어로빅장200819325.03855.566120.03276.0932.022×35×91917.050×20(8레인)42774600.0
1432021화성시근로자종합복지관화성시한국노총화성지역지부<NA>다목적홀, 헬스장, 건강교육장, 사무실, 탁구교육장20141974.03047.1910460.77<NA><NA><NA><NA>25m(6레인)<NA><NA>
1442021화성시모두누림센터화성시화성시여성가족재단<NA>탈의실, 요가실, 스피닝실, 에어로빅실, 헬스장, 샤워실, 주차장 , 사무실201622500.03574.2220332.72<NA>5562.83<NA><NA>50m(8레인)<NA><NA>
1452021화성시화성국민체육센터화성시화성도시공사배드민턴,농구,배구체력단련실, 에어로빅실, 요가실, 탁구실201112249.01968.369984.762601.14938.9926.4×33.7×8.21230.6225(8레인)431.5330756.0