Overview

Dataset statistics

Number of variables7
Number of observations41
Missing cells29
Missing cells (%)10.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory62.2 B

Variable types

Categorical2
Text2
Numeric3

Dataset

Description공공체육시설현황자료 데이타를 제공합니다 경기장명, 부지면적, 연면적, 수용인원, 설립연도 입니다 자료에 대하여 제공합니다
URLhttps://www.data.go.kr/data/15081316/fileData.do

Alerts

부지면적 is highly overall correlated with 경기장 면적High correlation
경기장 면적 is highly overall correlated with 부지면적High correlation
부지면적 has 13 (31.7%) missing valuesMissing
건물 연면적 has 10 (24.4%) missing valuesMissing
경기장 면적 has 6 (14.6%) missing valuesMissing

Reproduction

Analysis started2023-12-12 02:04:01.952205
Analysis finished2023-12-12 02:04:03.674781
Duration1.72 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

수탁기관
Categorical

Distinct4
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Memory size460.0 B
시설관리공단
32 
(재)하나금융축구단
5 
대전시체육회
 
3
(주)한화이글스
 
1

Length

Max length10
Median length6
Mean length6.5365854
Min length6

Unique

Unique1 ?
Unique (%)2.4%

Sample

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

Common Values

ValueCountFrequency (%)
시설관리공단 32
78.0%
(재)하나금융축구단 5
 
12.2%
대전시체육회 3
 
7.3%
(주)한화이글스 1
 
2.4%

Length

2023-12-12T11:04:03.778019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:04:04.300369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
시설관리공단 32
78.0%
재)하나금융축구단 5
 
12.2%
대전시체육회 3
 
7.3%
주)한화이글스 1
 
2.4%

시설명
Categorical

Distinct6
Distinct (%)14.6%
Missing0
Missing (%)0.0%
Memory size460.0 B
기타체육시설
23 
한밭 종합 운동장
10 
월드컵 경기장
4 
월평경기장
 
2
국민 생활관
 
1

Length

Max length10
Median length6
Mean length7.0731707
Min length5

Unique

Unique2 ?
Unique (%)4.9%

Sample

1st row한밭 종합 운동장
2nd row한밭 종합 운동장
3rd row한밭 종합 운동장
4th row한밭 종합 운동장
5th row한밭 종합 운동장

Common Values

ValueCountFrequency (%)
기타체육시설 23
56.1%
한밭 종합 운동장 10
24.4%
월드컵 경기장 4
 
9.8%
월평경기장 2
 
4.9%
국민 생활관 1
 
2.4%
용운국제 수영장 1
 
2.4%

Length

2023-12-12T11:04:04.464459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:04:04.627488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타체육시설 23
34.3%
한밭 10
14.9%
종합 10
14.9%
운동장 10
14.9%
월드컵 4
 
6.0%
경기장 4
 
6.0%
월평경기장 2
 
3.0%
국민 1
 
1.5%
생활관 1
 
1.5%
용운국제 1
 
1.5%

세부시설명
Text

Distinct39
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-12T11:04:04.947692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length11
Mean length7.7317073
Min length2

Characters and Unicode

Total characters317
Distinct characters113
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

Unique37 ?
Unique (%)90.2%

Sample

1st row종합운동장
2nd row보조경기장
3rd row충무체육관
4th row한밭수영장
5th row한밭체육관
ValueCountFrequency (%)
수영장등 2
 
4.3%
사회인야구장 2
 
4.3%
갑천파크골프장 2
 
4.3%
2구장 1
 
2.1%
종합운동장 1
 
2.1%
직장운동경기부선수숙소 1
 
2.1%
송강실내테니스장 1
 
2.1%
지수체육공원 1
 
2.1%
론볼장,풋살장,궁도장 1
 
2.1%
한마음생활체육관 1
 
2.1%
Other values (34) 34
72.3%
2023-12-12T11:04:05.482419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 41
 
12.9%
구 14
 
4.4%
체 8
 
2.5%
육 8
 
2.5%
기 8
 
2.5%
인 8
 
2.5%
한 8
 
2.5%
밭 7
 
2.2%
수 6
 
1.9%
6
 
1.9%
Other values (103) 203
64.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 297
93.7%
Space Separator 6
 
1.9%
Other Punctuation 4
 
1.3%
Open Punctuation 4
 
1.3%
Close Punctuation 4
 
1.3%
Decimal Number 2
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 41
 
13.8%
구 14
 
4.7%
체 8
 
2.7%
육 8
 
2.7%
기 8
 
2.7%
인 8
 
2.7%
한 8
 
2.7%
밭 7
 
2.4%
수 6
 
2.0%
축 5
 
1.7%
Other values (97) 184
62.0%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 297
93.7%
Common 20
 
6.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 41
 
13.8%
구 14
 
4.7%
체 8
 
2.7%
육 8
 
2.7%
기 8
 
2.7%
인 8
 
2.7%
한 8
 
2.7%
밭 7
 
2.4%
수 6
 
2.0%
축 5
 
1.7%
Other values (97) 184
62.0%
Common
ValueCountFrequency (%)
6
30.0%
, 4
20.0%
( 4
20.0%
) 4
20.0%
1 1
 
5.0%
2 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 297
93.7%
ASCII 20
 
6.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 41
 
13.8%
구 14
 
4.7%
체 8
 
2.7%
육 8
 
2.7%
기 8
 
2.7%
인 8
 
2.7%
한 8
 
2.7%
밭 7
 
2.4%
수 6
 
2.0%
축 5
 
1.7%
Other values (97) 184
62.0%
ASCII
ValueCountFrequency (%)
6
30.0%
, 4
20.0%
( 4
20.0%
) 4
20.0%
1 1
 
5.0%
2 1
 
5.0%

위치
Text

Distinct25
Distinct (%)61.0%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-12T11:04:05.829180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length20
Mean length16.731707
Min length11

Characters and Unicode

Total characters686
Distinct characters77
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

Unique19 ?
Unique (%)46.3%

Sample

1st row중구 대종로 373 (부사동)
2nd row중구 대종로 373 (부사동)
3rd row중구 대종로 373 (부사동)
4th row중구 대종로 373 (부사동)
5th row중구 대종로 373 (부사동)
ValueCountFrequency (%)
중구 16
 
11.1%
유성구 14
 
9.7%
대종로 12
 
8.3%
부사동 10
 
6.9%
373 10
 
6.9%
서구 6
 
4.2%
55-3 4
 
2.8%
신갈마로 4
 
2.8%
내동 4
 
2.8%
노은동 4
 
2.8%
Other values (46) 60
41.7%
2023-12-12T11:04:06.337429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
103
 
15.0%
동 44
 
6.4%
구 40
 
5.8%
3 37
 
5.4%
( 32
 
4.7%
) 32
 
4.7%
로 32
 
4.7%
대 24
 
3.5%
중 17
 
2.5%
7 16
 
2.3%
Other values (67) 309
45.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 374
54.5%
Decimal Number 134
 
19.5%
Space Separator 103
 
15.0%
Open Punctuation 32
 
4.7%
Close Punctuation 32
 
4.7%
Dash Punctuation 7
 
1.0%
Lowercase Letter 2
 
0.3%
Other Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 44
 
11.8%
구 40
 
10.7%
로 32
 
8.6%
대 24
 
6.4%
중 17
 
4.5%
유 15
 
4.0%
성 14
 
3.7%
번 14
 
3.7%
사 14
 
3.7%
부 13
 
3.5%
Other values (51) 147
39.3%
Decimal Number
ValueCountFrequency (%)
3 37
27.6%
7 16
11.9%
1 16
11.9%
5 14
 
10.4%
6 12
 
9.0%
2 10
 
7.5%
4 9
 
6.7%
0 9
 
6.7%
9 8
 
6.0%
8 3
 
2.2%
Space Separator
ValueCountFrequency (%)
103
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 374
54.5%
Common 310
45.2%
Latin 2
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 44
 
11.8%
구 40
 
10.7%
로 32
 
8.6%
대 24
 
6.4%
중 17
 
4.5%
유 15
 
4.0%
성 14
 
3.7%
번 14
 
3.7%
사 14
 
3.7%
부 13
 
3.5%
Other values (51) 147
39.3%
Common
ValueCountFrequency (%)
103
33.2%
3 37
 
11.9%
( 32
 
10.3%
) 32
 
10.3%
7 16
 
5.2%
1 16
 
5.2%
5 14
 
4.5%
6 12
 
3.9%
2 10
 
3.2%
4 9
 
2.9%
Other values (5) 29
 
9.4%
Latin
ValueCountFrequency (%)
m 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 374
54.5%
ASCII 312
45.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
103
33.0%
3 37
 
11.9%
( 32
 
10.3%
) 32
 
10.3%
7 16
 
5.1%
1 16
 
5.1%
5 14
 
4.5%
6 12
 
3.8%
2 10
 
3.2%
4 9
 
2.9%
Other values (6) 31
 
9.9%
Hangul
ValueCountFrequency (%)
동 44
 
11.8%
구 40
 
10.7%
로 32
 
8.6%
대 24
 
6.4%
중 17
 
4.5%
유 15
 
4.0%
성 14
 
3.7%
번 14
 
3.7%
사 14
 
3.7%
부 13
 
3.5%
Other values (51) 147
39.3%

부지면적
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct28
Distinct (%)100.0%
Missing13
Missing (%)31.7%
Infinite0
Infinite (%)0.0%
Mean36242.821
Minimum540
Maximum172378
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T11:04:06.477527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum540
5-th percentile2145.75
Q17700.75
median17732.5
Q343447.5
95-th percentile133672.5
Maximum172378
Range171838
Interquartile range (IQR)35746.75

Descriptive statistics

Standard deviation44051.285
Coefficient of variation (CV)1.2154486
Kurtosis3.8268934
Mean36242.821
Median Absolute Deviation (MAD)14043.5
Skewness1.9885447
Sum1014799
Variance1.9405158 × 109
MonotonicityNot monotonic
2023-12-12T11:04:06.633217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
8077 1
 
2.4%
3397 1
 
2.4%
15630 1
 
2.4%
38097 1
 
2.4%
33912 1
 
2.4%
6572 1
 
2.4%
13457 1
 
2.4%
13600 1
 
2.4%
32162 1
 
2.4%
4116 1
 
2.4%
Other values (18) 18
43.9%
(Missing) 13
31.7%
ValueCountFrequency (%)
540 1
2.4%
1472 1
2.4%
3397 1
2.4%
3981 1
2.4%
4116 1
2.4%
5250 1
2.4%
6572 1
2.4%
8077 1
2.4%
9360 1
2.4%
13457 1
2.4%
ValueCountFrequency (%)
172378 1
2.4%
157777 1
2.4%
88907 1
2.4%
78555 1
2.4%
67576 1
2.4%
67105 1
2.4%
59499 1
2.4%
38097 1
2.4%
36532 1
2.4%
33912 1
2.4%

건물 연면적
Real number (ℝ)

MISSING 

Distinct31
Distinct (%)100.0%
Missing10
Missing (%)24.4%
Infinite0
Infinite (%)0.0%
Mean7489.4194
Minimum44
Maximum100473
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T11:04:06.786802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum44
5-th percentile171
Q1536
median2673
Q36310.5
95-th percentile19468
Maximum100473
Range100429
Interquartile range (IQR)5774.5

Descriptive statistics

Standard deviation18036.821
Coefficient of variation (CV)2.408307
Kurtosis25.468547
Mean7489.4194
Median Absolute Deviation (MAD)2240
Skewness4.87537
Sum232172
Variance3.2532692 × 108
MonotonicityNot monotonic
2023-12-12T11:04:06.970277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
13384 1
 
2.4%
8168 1
 
2.4%
433 1
 
2.4%
311 1
 
2.4%
2673 1
 
2.4%
563 1
 
2.4%
4463 1
 
2.4%
2830 1
 
2.4%
2111 1
 
2.4%
776 1
 
2.4%
Other values (21) 21
51.2%
(Missing) 10
24.4%
ValueCountFrequency (%)
44 1
2.4%
119 1
2.4%
223 1
2.4%
311 1
2.4%
354 1
2.4%
433 1
2.4%
484 1
2.4%
509 1
2.4%
563 1
2.4%
776 1
2.4%
ValueCountFrequency (%)
100473 1
2.4%
21394 1
2.4%
17542 1
2.4%
13384 1
2.4%
10578 1
2.4%
8203 1
2.4%
8168 1
2.4%
6390 1
2.4%
6231 1
2.4%
5971 1
2.4%

경기장 면적
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct35
Distinct (%)100.0%
Missing6
Missing (%)14.6%
Infinite0
Infinite (%)0.0%
Mean9477.7429
Minimum113
Maximum45707
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T11:04:07.107867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum113
5-th percentile798.6
Q12085
median4350
Q313515
95-th percentile35167.5
Maximum45707
Range45594
Interquartile range (IQR)11430

Descriptive statistics

Standard deviation11058.981
Coefficient of variation (CV)1.166837
Kurtosis3.4284965
Mean9477.7429
Median Absolute Deviation (MAD)3350
Skewness1.9004743
Sum331721
Variance1.2230106 × 108
MonotonicityNot monotonic
2023-12-12T11:04:07.265779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
13573 1
 
2.4%
2450 1
 
2.4%
13693 1
 
2.4%
1949 1
 
2.4%
1555 1
 
2.4%
45707 1
 
2.4%
4350 1
 
2.4%
3600 1
 
2.4%
11385 1
 
2.4%
13600 1
 
2.4%
Other values (25) 25
61.0%
(Missing) 6
 
14.6%
ValueCountFrequency (%)
113 1
2.4%
527 1
2.4%
915 1
2.4%
1250 1
2.4%
1555 1
2.4%
1716 1
2.4%
1863 1
2.4%
1949 1
2.4%
2070 1
2.4%
2100 1
2.4%
ValueCountFrequency (%)
45707 1
2.4%
38097 1
2.4%
33912 1
2.4%
23414 1
2.4%
20010 1
2.4%
15630 1
2.4%
13693 1
2.4%
13600 1
2.4%
13573 1
2.4%
13457 1
2.4%

Interactions

2023-12-12T11:04:02.934911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:04:02.327348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:04:02.619961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:04:03.047470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:04:02.436282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:04:02.724266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:04:03.147814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:04:02.531672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:04:02.831439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T11:04:07.417060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수탁기관시설명세부시설명위치부지면적건물 연면적경기장 면적
수탁기관1.0000.6021.0000.9210.4910.0000.000
시설명0.6021.0000.0001.0000.5180.5070.000
세부시설명1.0000.0001.0000.0000.9610.3691.000
위치0.9211.0000.0001.0000.8350.0000.830
부지면적0.4910.5180.9610.8351.0000.5480.817
건물 연면적0.0000.5070.3690.0000.5481.0000.668
경기장 면적0.0000.0001.0000.8300.8170.6681.000
2023-12-12T11:04:07.552336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설명수탁기관
시설명1.0000.418
수탁기관0.4181.000
2023-12-12T11:04:07.663743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부지면적건물 연면적경기장 면적수탁기관시설명
부지면적1.0000.4090.5720.3330.333
건물 연면적0.4091.0000.1590.0000.330
경기장 면적0.5720.1591.0000.0000.000
수탁기관0.3330.0000.0001.0000.418
시설명0.3330.3300.0000.4181.000

Missing values

2023-12-12T11:04:03.262895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:04:03.415318image/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.
2023-12-12T11:04:03.581552image/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

수탁기관시설명세부시설명위치부지면적건물 연면적경기장 면적
0시설관리공단한밭 종합 운동장종합운동장중구 대종로 373 (부사동)1577772139420010
1시설관리공단한밭 종합 운동장보조경기장중구 대종로 373 (부사동)<NA>1338413573
2시설관리공단한밭 종합 운동장충무체육관중구 대종로 373 (부사동)<NA>105781716
3시설관리공단한밭 종합 운동장한밭수영장중구 대종로 373 (부사동)<NA>59711250
4시설관리공단한밭 종합 운동장한밭체육관중구 대종로 373 (부사동)<NA>82032100
5시설관리공단한밭 종합 운동장한밭정구장중구 대종로 373 (부사동)<NA>1193735
6시설관리공단한밭 종합 운동장한밭육상실내연습장중구 대종로 373 (부사동)<NA>21951863
7시설관리공단한밭 종합 운동장한밭씨름장중구 대종로 373 (부사동)<NA>354113
8시설관리공단한밭 종합 운동장한밭게이트볼장중구 대종로 373 (부사동)<NA>509915
9시설관리공단한밭 종합 운동장기타중구 대종로 373 (부사동)<NA>44<NA>
수탁기관시설명세부시설명위치부지면적건물 연면적경기장 면적
31대전시체육회기타체육시설월평궁도장서구 신갈마로 55-3 (내동) 월평경기장52503114350
32대전시체육회기타체육시설월평양궁장서구 신갈마로 55-3 (내동) 월평경기장41164333600
33(주)한화이글스기타체육시설한밭야구장중구 대종로 373(부사동)32162816811385
34시설관리공단기타체육시설사회인야구장유성구 문지동 66번지13600<NA>13600
35시설관리공단기타체육시설사회인야구장유성구 탑립동 7번지13457<NA>13457
36시설관리공단기타체육시설중촌근린공원 리틀야구장중구 중촌동 260번지6572<NA>6572
37시설관리공단기타체육시설갑천파크골프장 1구장유성구 탑립동 184-4번지33912<NA>33912
38시설관리공단기타체육시설갑천파크골프장 2구장유성구 탑립동 184-4번지38097<NA>38097
39시설관리공단기타체육시설유등천파크골프장서구 둔상동 466번지15630<NA>15630
40시설관리공단기타체육시설그라운드골프장유성구 봉명동 496-25번지3397<NA>3397