Overview

Dataset statistics

Number of variables23
Number of observations54
Missing cells308
Missing cells (%)24.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.6 KiB
Average record size in memory201.4 B

Variable types

Categorical10
Text2
Numeric10
Unsupported1

Dataset

Description공공체육시설 현황(롤러스케이트)
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=927BASCC737748GXS8J74502219&infSeq=1

Alerts

집계년도 has constant value ""Constant
실내외구분명 is highly imbalanced (77.1%)Imbalance
관람석좌석수 is highly imbalanced (73.2%)Imbalance
수용인원수(명) is highly imbalanced (77.2%)Imbalance
좌석형태명 is highly imbalanced (55.5%)Imbalance
준공연도 has 4 (7.4%) missing valuesMissing
부지면적(㎡) has 7 (13.0%) missing valuesMissing
건축면적(㎡) has 45 (83.3%) missing valuesMissing
연면적(㎡) has 48 (88.9%) missing valuesMissing
트랙주로연장(m) has 20 (37.0%) missing valuesMissing
트랙주로폭(m) has 20 (37.0%) missing valuesMissing
필드폭(m) has 30 (55.6%) missing valuesMissing
필드길이(m) has 30 (55.6%) missing valuesMissing
면적(㎡) has 14 (25.9%) missing valuesMissing
건설사업비(백만원) has 36 (66.7%) missing valuesMissing
비고사항 has 54 (100.0%) missing valuesMissing
비고사항 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건축면적(㎡) has 1 (1.9%) zerosZeros
연면적(㎡) has 1 (1.9%) zerosZeros
건설사업비(백만원) has 2 (3.7%) zerosZeros

Reproduction

Analysis started2023-12-22 21:40:55.230315
Analysis finished2023-12-22 21:40:56.578242
Duration1.35 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

집계년도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size564.0 B
2021
54 

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 54
100.0%

Length

2023-12-22T21:40:56.969529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-22T21:40:57.655835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 54
100.0%

시군명
Categorical

Distinct23
Distinct (%)42.6%
Missing0
Missing (%)0.0%
Memory size564.0 B
화성시
14 
시흥시
4 
용인시
4 
광주시
3 
의정부시
3 
Other values (18)
26 

Length

Max length4
Median length3
Mean length3.0740741
Min length3

Unique

Unique11 ?
Unique (%)20.4%

Sample

1st row고양시
2nd row광명시
3rd row광명시
4th row광주시
5th row광주시

Common Values

ValueCountFrequency (%)
화성시 14
25.9%
시흥시 4
 
7.4%
용인시 4
 
7.4%
광주시 3
 
5.6%
의정부시 3
 
5.6%
성남시 3
 
5.6%
양주시 2
 
3.7%
안양시 2
 
3.7%
안산시 2
 
3.7%
양평군 2
 
3.7%
Other values (13) 15
27.8%

Length

2023-12-22T21:40:58.220448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
화성시 14
25.9%
용인시 4
 
7.4%
시흥시 4
 
7.4%
광주시 3
 
5.6%
의정부시 3
 
5.6%
성남시 3
 
5.6%
양평군 2
 
3.7%
평택시 2
 
3.7%
광명시 2
 
3.7%
안산시 2
 
3.7%
Other values (13) 15
27.8%

시설명
Text

Distinct52
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Memory size564.0 B
2023-12-22T21:40:59.148853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length17
Mean length12.833333
Min length6

Characters and Unicode

Total characters693
Distinct characters115
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)94.4%

Sample

1st row서정공원 간이 인라인스케이트장
2nd row소하 인라인장
3rd row광명역세권 인라인장
4th row광주시민체육관인라인스케이트장
5th row청석공원인라인스케이트장
ValueCountFrequency (%)
인라인스케이트장 17
 
17.9%
인라인장 12
 
12.6%
롤러스케이트장 3
 
3.2%
체육시설 3
 
3.2%
금오동 1
 
1.1%
체육공원롤러스케이트장 1
 
1.1%
포천 1
 
1.1%
이충레포츠타운인라인스케이트장 1
 
1.1%
소사벌레포츠타운인라인스케이트장 1
 
1.1%
이천 1
 
1.1%
Other values (54) 54
56.8%
2023-12-22T21:41:00.973737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
인 95
 
13.7%
장 56
 
8.1%
라 47
 
6.8%
41
 
5.9%
이 40
 
5.8%
트 37
 
5.3%
스 36
 
5.2%
케 36
 
5.2%
원 26
 
3.8%
공 25
 
3.6%
Other values (105) 254
36.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 644
92.9%
Space Separator 41
 
5.9%
Decimal Number 4
 
0.6%
Close Punctuation 2
 
0.3%
Open Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 95
14.8%
장 56
 
8.7%
라 47
 
7.3%
이 40
 
6.2%
트 37
 
5.7%
스 36
 
5.6%
케 36
 
5.6%
원 26
 
4.0%
공 25
 
3.9%
육 17
 
2.6%
Other values (99) 229
35.6%
Decimal Number
ValueCountFrequency (%)
2 2
50.0%
1 1
25.0%
4 1
25.0%
Space Separator
ValueCountFrequency (%)
41
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 644
92.9%
Common 49
 
7.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 95
14.8%
장 56
 
8.7%
라 47
 
7.3%
이 40
 
6.2%
트 37
 
5.7%
스 36
 
5.6%
케 36
 
5.6%
원 26
 
4.0%
공 25
 
3.9%
육 17
 
2.6%
Other values (99) 229
35.6%
Common
ValueCountFrequency (%)
41
83.7%
2 2
 
4.1%
) 2
 
4.1%
( 2
 
4.1%
1 1
 
2.0%
4 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 644
92.9%
ASCII 49
 
7.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
인 95
14.8%
장 56
 
8.7%
라 47
 
7.3%
이 40
 
6.2%
트 37
 
5.7%
스 36
 
5.6%
케 36
 
5.6%
원 26
 
4.0%
공 25
 
3.9%
육 17
 
2.6%
Other values (99) 229
35.6%
ASCII
ValueCountFrequency (%)
41
83.7%
2 2
 
4.1%
) 2
 
4.1%
( 2
 
4.1%
1 1
 
2.0%
4 1
 
2.0%

소유기관명
Categorical

Distinct23
Distinct (%)42.6%
Missing0
Missing (%)0.0%
Memory size564.0 B
화성시
14 
시흥시
4 
용인시
4 
광주시
3 
의정부시
3 
Other values (18)
26 

Length

Max length4
Median length3
Mean length3.1111111
Min length3

Unique

Unique11 ?
Unique (%)20.4%

Sample

1st row고양시
2nd row광명시
3rd row광명시
4th row광주시
5th row광주시

Common Values

ValueCountFrequency (%)
화성시 14
25.9%
시흥시 4
 
7.4%
용인시 4
 
7.4%
광주시 3
 
5.6%
의정부시 3
 
5.6%
성남시 3
 
5.6%
양주시 2
 
3.7%
안양시 2
 
3.7%
<NA> 2
 
3.7%
양평군 2
 
3.7%
Other values (13) 15
27.8%

Length

2023-12-22T21:41:01.958209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
화성시 14
25.9%
용인시 4
 
7.4%
시흥시 4
 
7.4%
광주시 3
 
5.6%
의정부시 3
 
5.6%
성남시 3
 
5.6%
양평군 2
 
3.7%
평택시 2
 
3.7%
광명시 2
 
3.7%
na 2
 
3.7%
Other values (13) 15
27.8%

관리주체명
Text

Distinct33
Distinct (%)61.1%
Missing0
Missing (%)0.0%
Memory size564.0 B
2023-12-22T21:41:02.821507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length5.7592593
Min length3

Characters and Unicode

Total characters311
Distinct characters60
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 (%)44.4%

Sample

1st row공원관리과
2nd row광명시
3rd row광명시
4th row위탁(광주도시관리공사)
5th row광주시(공원정책과)
ValueCountFrequency (%)
화성도시공사 12
21.8%
용인시 3
 
5.5%
체육진흥과 3
 
5.5%
화성시 2
 
3.6%
광명시 2
 
3.6%
안양도시공사 2
 
3.6%
안산도시공사 2
 
3.6%
의정부시 2
 
3.6%
성남도시개발공사 2
 
3.6%
평택시(체육진흥과 1
 
1.8%
Other values (24) 24
43.6%
2023-12-22T21:41:05.591477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 49
15.8%
공 30
 
9.6%
사 26
 
8.4%
도 25
 
8.0%
성 17
 
5.5%
화 15
 
4.8%
과 8
 
2.6%
( 7
 
2.3%
) 7
 
2.3%
체 6
 
1.9%
Other values (50) 121
38.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 296
95.2%
Open Punctuation 7
 
2.3%
Close Punctuation 7
 
2.3%
Space Separator 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 49
16.6%
공 30
 
10.1%
사 26
 
8.8%
도 25
 
8.4%
성 17
 
5.7%
화 15
 
5.1%
과 8
 
2.7%
체 6
 
2.0%
육 6
 
2.0%
흥 5
 
1.7%
Other values (47) 109
36.8%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 296
95.2%
Common 15
 
4.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 49
16.6%
공 30
 
10.1%
사 26
 
8.8%
도 25
 
8.4%
성 17
 
5.7%
화 15
 
5.1%
과 8
 
2.7%
체 6
 
2.0%
육 6
 
2.0%
흥 5
 
1.7%
Other values (47) 109
36.8%
Common
ValueCountFrequency (%)
( 7
46.7%
) 7
46.7%
1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 296
95.2%
ASCII 15
 
4.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 49
16.6%
공 30
 
10.1%
사 26
 
8.8%
도 25
 
8.4%
성 17
 
5.7%
화 15
 
5.1%
과 8
 
2.7%
체 6
 
2.0%
육 6
 
2.0%
흥 5
 
1.7%
Other values (47) 109
36.8%
ASCII
ValueCountFrequency (%)
( 7
46.7%
) 7
46.7%
1
 
6.7%

준공연도
Real number (ℝ)

MISSING 

Distinct16
Distinct (%)32.0%
Missing4
Missing (%)7.4%
Infinite0
Infinite (%)0.0%
Mean2009.76
Minimum2000
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-22T21:41:07.012584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2000
5-th percentile2005
Q12006
median2008
Q32012
95-th percentile2018
Maximum2021
Range21
Interquartile range (IQR)6

Descriptive statistics

Standard deviation4.6139098
Coefficient of variation (CV)0.0022957516
Kurtosis-0.21020221
Mean2009.76
Median Absolute Deviation (MAD)2
Skewness0.69772628
Sum100488
Variance21.288163
MonotonicityNot monotonic
2023-12-22T21:41:07.862141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
2006 9
16.7%
2008 8
14.8%
2009 5
9.3%
2017 5
9.3%
2007 4
7.4%
2018 3
 
5.6%
2005 3
 
5.6%
2010 3
 
5.6%
2012 2
 
3.7%
2011 2
 
3.7%
Other values (6) 6
11.1%
(Missing) 4
7.4%
ValueCountFrequency (%)
2000 1
 
1.9%
2004 1
 
1.9%
2005 3
 
5.6%
2006 9
16.7%
2007 4
7.4%
2008 8
14.8%
2009 5
9.3%
2010 3
 
5.6%
2011 2
 
3.7%
2012 2
 
3.7%
ValueCountFrequency (%)
2021 1
 
1.9%
2018 3
5.6%
2017 5
9.3%
2015 1
 
1.9%
2014 1
 
1.9%
2013 1
 
1.9%
2012 2
 
3.7%
2011 2
 
3.7%
2010 3
5.6%
2009 5
9.3%

실내외구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size564.0 B
실외
52 
<NA>
 
2

Length

Max length4
Median length2
Mean length2.0740741
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
실외 52
96.3%
<NA> 2
 
3.7%

Length

2023-12-22T21:41:08.629105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-22T21:41:09.269275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
실외 52
96.3%
na 2
 
3.7%

트랙바닥재료명
Categorical

Distinct9
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size564.0 B
우레탄
17 
<NA>
14 
아크릴
9 
에폭시
5 
아스콘
3 
Other values (4)
6 

Length

Max length10
Median length3
Mean length3.5740741
Min length3

Unique

Unique3 ?
Unique (%)5.6%

Sample

1st row우레탄
2nd row아크릴
3rd row우레탄
4th row아크릴
5th row우레탄

Common Values

ValueCountFrequency (%)
우레탄 17
31.5%
<NA> 14
25.9%
아크릴 9
16.7%
에폭시 5
 
9.3%
아스콘 3
 
5.6%
콘크리트 3
 
5.6%
렌진몰탈 1
 
1.9%
콘크리트코로실 코팅 1
 
1.9%
콘크리트코로실코팅 1
 
1.9%

Length

2023-12-22T21:41:10.087729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-22T21:41:10.512696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
우레탄 17
30.9%
na 14
25.5%
아크릴 9
16.4%
에폭시 5
 
9.1%
아스콘 3
 
5.5%
콘크리트 3
 
5.5%
렌진몰탈 1
 
1.8%
콘크리트코로실 1
 
1.8%
코팅 1
 
1.8%
콘크리트코로실코팅 1
 
1.8%

필드바닥재료명
Categorical

Distinct8
Distinct (%)14.8%
Missing0
Missing (%)0.0%
Memory size564.0 B
<NA>
27 
우레탄
12 
아크릴
8 
아스콘
3 
에폭시
 
1
Other values (3)
3 

Length

Max length4
Median length4
Mean length3.5185185
Min length2

Unique

Unique4 ?
Unique (%)7.4%

Sample

1st row<NA>
2nd row아크릴
3rd row우레탄
4th row아크릴
5th row우레탄

Common Values

ValueCountFrequency (%)
<NA> 27
50.0%
우레탄 12
22.2%
아크릴 8
 
14.8%
아스콘 3
 
5.6%
에폭시 1
 
1.9%
판석 1
 
1.9%
아스팔트 1
 
1.9%
콘크리트 1
 
1.9%

Length

2023-12-22T21:41:11.141078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-22T21:41:12.043703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 27
50.0%
우레탄 12
22.2%
아크릴 8
 
14.8%
아스콘 3
 
5.6%
에폭시 1
 
1.9%
판석 1
 
1.9%
아스팔트 1
 
1.9%
콘크리트 1
 
1.9%

부지면적(㎡)
Real number (ℝ)

MISSING 

Distinct46
Distinct (%)97.9%
Missing7
Missing (%)13.0%
Infinite0
Infinite (%)0.0%
Mean10700.032
Minimum292
Maximum193530
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-22T21:41:12.974520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum292
5-th percentile364
Q1897
median2971
Q35583
95-th percentile38049
Maximum193530
Range193238
Interquartile range (IQR)4686

Descriptive statistics

Standard deviation29447.226
Coefficient of variation (CV)2.752069
Kurtosis33.748123
Mean10700.032
Median Absolute Deviation (MAD)2193
Skewness5.5193244
Sum502901.5
Variance8.6713911 × 108
MonotonicityNot monotonic
2023-12-22T21:41:14.052141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
2840.0 2
 
3.7%
1425.0 1
 
1.9%
3757.0 1
 
1.9%
3462.5 1
 
1.9%
778.0 1
 
1.9%
25456.0 1
 
1.9%
5881.0 1
 
1.9%
4000.0 1
 
1.9%
5053.0 1
 
1.9%
21182.0 1
 
1.9%
Other values (36) 36
66.7%
(Missing) 7
 
13.0%
ValueCountFrequency (%)
292.0 1
1.9%
300.0 1
1.9%
352.0 1
1.9%
392.0 1
1.9%
400.0 1
1.9%
532.0 1
1.9%
550.0 1
1.9%
560.0 1
1.9%
695.0 1
1.9%
770.0 1
1.9%
ValueCountFrequency (%)
193530.0 1
1.9%
52474.0 1
1.9%
38064.0 1
1.9%
38014.0 1
1.9%
25456.0 1
1.9%
23450.0 1
1.9%
21182.0 1
1.9%
10609.0 1
1.9%
7149.0 1
1.9%
6675.0 1
1.9%

건축면적(㎡)
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)100.0%
Missing45
Missing (%)83.3%
Infinite0
Infinite (%)0.0%
Mean1032.62
Minimum0
Maximum5151
Zeros1
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-22T21:41:14.693332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile16
Q140.58
median352
Q31377
95-th percentile3706.6
Maximum5151
Range5151
Interquartile range (IQR)1336.42

Descriptive statistics

Standard deviation1646.2871
Coefficient of variation (CV)1.5942816
Kurtosis6.0569927
Mean1032.62
Median Absolute Deviation (MAD)312
Skewness2.3797342
Sum9293.58
Variance2710261.1
MonotonicityNot monotonic
2023-12-22T21:41:15.162027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
40.0 1
 
1.9%
352.0 1
 
1.9%
532.0 1
 
1.9%
1377.0 1
 
1.9%
1540.0 1
 
1.9%
261.0 1
 
1.9%
5151.0 1
 
1.9%
40.58 1
 
1.9%
0.0 1
 
1.9%
(Missing) 45
83.3%
ValueCountFrequency (%)
0.0 1
1.9%
40.0 1
1.9%
40.58 1
1.9%
261.0 1
1.9%
352.0 1
1.9%
532.0 1
1.9%
1377.0 1
1.9%
1540.0 1
1.9%
5151.0 1
1.9%
ValueCountFrequency (%)
5151.0 1
1.9%
1540.0 1
1.9%
1377.0 1
1.9%
532.0 1
1.9%
352.0 1
1.9%
261.0 1
1.9%
40.58 1
1.9%
40.0 1
1.9%
0.0 1
1.9%

연면적(㎡)
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)100.0%
Missing48
Missing (%)88.9%
Infinite0
Infinite (%)0.0%
Mean1147.0967
Minimum0
Maximum5250
Zeros1
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-22T21:41:15.721455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10
Q140.145
median150.79
Q31033.5
95-th percentile4260.25
Maximum5250
Range5250
Interquartile range (IQR)993.355

Descriptive statistics

Standard deviation2069.085
Coefficient of variation (CV)1.8037582
Kurtosis4.777375
Mean1147.0967
Median Absolute Deviation (MAD)130.79
Skewness2.1727395
Sum6882.58
Variance4281112.8
MonotonicityNot monotonic
2023-12-22T21:41:16.222150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
40.0 1
 
1.9%
261.0 1
 
1.9%
5250.0 1
 
1.9%
1291.0 1
 
1.9%
40.58 1
 
1.9%
0.0 1
 
1.9%
(Missing) 48
88.9%
ValueCountFrequency (%)
0.0 1
1.9%
40.0 1
1.9%
40.58 1
1.9%
261.0 1
1.9%
1291.0 1
1.9%
5250.0 1
1.9%
ValueCountFrequency (%)
5250.0 1
1.9%
1291.0 1
1.9%
261.0 1
1.9%
40.58 1
1.9%
40.0 1
1.9%
0.0 1
1.9%

트랙주로연장(m)
Real number (ℝ)

MISSING 

Distinct18
Distinct (%)52.9%
Missing20
Missing (%)37.0%
Infinite0
Infinite (%)0.0%
Mean162.35294
Minimum70
Maximum250
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-22T21:41:16.931445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum70
5-th percentile98.6
Q1121.25
median175
Q3200
95-th percentile200
Maximum250
Range180
Interquartile range (IQR)78.75

Descriptive statistics

Standard deviation42.894432
Coefficient of variation (CV)0.26420483
Kurtosis-0.84556539
Mean162.35294
Median Absolute Deviation (MAD)25
Skewness-0.30796395
Sum5520
Variance1839.9323
MonotonicityNot monotonic
2023-12-22T21:41:17.566661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
200 11
20.4%
120 4
 
7.4%
125 2
 
3.7%
170 2
 
3.7%
100 2
 
3.7%
115 1
 
1.9%
190 1
 
1.9%
70 1
 
1.9%
145 1
 
1.9%
147 1
 
1.9%
Other values (8) 8
 
14.8%
(Missing) 20
37.0%
ValueCountFrequency (%)
70 1
 
1.9%
96 1
 
1.9%
100 2
3.7%
115 1
 
1.9%
120 4
7.4%
125 2
3.7%
140 1
 
1.9%
145 1
 
1.9%
147 1
 
1.9%
150 1
 
1.9%
ValueCountFrequency (%)
250 1
 
1.9%
200 11
20.4%
192 1
 
1.9%
190 1
 
1.9%
189 1
 
1.9%
186 1
 
1.9%
180 1
 
1.9%
170 2
 
3.7%
150 1
 
1.9%
147 1
 
1.9%

트랙주로폭(m)
Real number (ℝ)

MISSING 

Distinct9
Distinct (%)26.5%
Missing20
Missing (%)37.0%
Infinite0
Infinite (%)0.0%
Mean4.7147059
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-22T21:41:18.365173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median5.5
Q36
95-th percentile6.545
Maximum8
Range7
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.7574314
Coefficient of variation (CV)0.37275525
Kurtosis-0.85357796
Mean4.7147059
Median Absolute Deviation (MAD)0.65
Skewness-0.45543484
Sum160.3
Variance3.0885651
MonotonicityNot monotonic
2023-12-22T21:41:19.134389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
6.0 14
25.9%
3.0 5
 
9.3%
2.0 4
 
7.4%
4.0 4
 
7.4%
5.0 3
 
5.6%
7.0 1
 
1.9%
8.0 1
 
1.9%
6.3 1
 
1.9%
1.0 1
 
1.9%
(Missing) 20
37.0%
ValueCountFrequency (%)
1.0 1
 
1.9%
2.0 4
 
7.4%
3.0 5
 
9.3%
4.0 4
 
7.4%
5.0 3
 
5.6%
6.0 14
25.9%
6.3 1
 
1.9%
7.0 1
 
1.9%
8.0 1
 
1.9%
ValueCountFrequency (%)
8.0 1
 
1.9%
7.0 1
 
1.9%
6.3 1
 
1.9%
6.0 14
25.9%
5.0 3
 
5.6%
4.0 4
 
7.4%
3.0 5
 
9.3%
2.0 4
 
7.4%
1.0 1
 
1.9%

트랙주로수
Categorical

Distinct4
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size564.0 B
1
26 
<NA>
20 
2
7 
3
 
1

Length

Max length4
Median length1
Mean length2.1111111
Min length1

Unique

Unique1 ?
Unique (%)1.9%

Sample

1st row2
2nd row1
3rd row1
4th row1
5th row2

Common Values

ValueCountFrequency (%)
1 26
48.1%
<NA> 20
37.0%
2 7
 
13.0%
3 1
 
1.9%

Length

2023-12-22T21:41:19.744324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-22T21:41:20.713191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 26
48.1%
na 20
37.0%
2 7
 
13.0%
3 1
 
1.9%

필드폭(m)
Real number (ℝ)

MISSING 

Distinct17
Distinct (%)70.8%
Missing30
Missing (%)55.6%
Infinite0
Infinite (%)0.0%
Mean26.041667
Minimum8
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-22T21:41:21.199358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile10.75
Q120
median24
Q330
95-th percentile47.1
Maximum50
Range42
Interquartile range (IQR)10

Descriptive statistics

Standard deviation10.650492
Coefficient of variation (CV)0.40897888
Kurtosis0.36654571
Mean26.041667
Median Absolute Deviation (MAD)6
Skewness0.72100757
Sum625
Variance113.43297
MonotonicityNot monotonic
2023-12-22T21:41:21.727054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
30 4
 
7.4%
20 3
 
5.6%
21 2
 
3.7%
24 2
 
3.7%
8 1
 
1.9%
10 1
 
1.9%
15 1
 
1.9%
19 1
 
1.9%
32 1
 
1.9%
25 1
 
1.9%
Other values (7) 7
 
13.0%
(Missing) 30
55.6%
ValueCountFrequency (%)
8 1
 
1.9%
10 1
 
1.9%
15 1
 
1.9%
18 1
 
1.9%
19 1
 
1.9%
20 3
5.6%
21 2
3.7%
22 1
 
1.9%
24 2
3.7%
25 1
 
1.9%
ValueCountFrequency (%)
50 1
 
1.9%
48 1
 
1.9%
42 1
 
1.9%
40 1
 
1.9%
32 1
 
1.9%
30 4
7.4%
26 1
 
1.9%
25 1
 
1.9%
24 2
3.7%
22 1
 
1.9%

필드길이(m)
Real number (ℝ)

MISSING 

Distinct14
Distinct (%)58.3%
Missing30
Missing (%)55.6%
Infinite0
Infinite (%)0.0%
Mean78.6875
Minimum25
Maximum400
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-22T21:41:22.400978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum25
5-th percentile38.3
Q150
median63.5
Q385
95-th percentile100
Maximum400
Range375
Interquartile range (IQR)35

Descriptive statistics

Standard deviation71.61458
Coefficient of variation (CV)0.91011381
Kurtosis19.49058
Mean78.6875
Median Absolute Deviation (MAD)18.75
Skewness4.2244394
Sum1888.5
Variance5128.6481
MonotonicityNot monotonic
2023-12-22T21:41:22.894037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
85.0 3
 
5.6%
50.0 3
 
5.6%
100.0 3
 
5.6%
60.0 2
 
3.7%
80.0 2
 
3.7%
64.0 2
 
3.7%
40.0 2
 
3.7%
38.0 1
 
1.9%
42.5 1
 
1.9%
70.0 1
 
1.9%
Other values (4) 4
 
7.4%
(Missing) 30
55.6%
ValueCountFrequency (%)
25.0 1
 
1.9%
38.0 1
 
1.9%
40.0 2
3.7%
42.5 1
 
1.9%
50.0 3
5.6%
57.0 1
 
1.9%
60.0 2
3.7%
63.0 1
 
1.9%
64.0 2
3.7%
70.0 1
 
1.9%
ValueCountFrequency (%)
400.0 1
 
1.9%
100.0 3
5.6%
85.0 3
5.6%
80.0 2
3.7%
70.0 1
 
1.9%
64.0 2
3.7%
63.0 1
 
1.9%
60.0 2
3.7%
57.0 1
 
1.9%
50.0 3
5.6%

면적(㎡)
Real number (ℝ)

MISSING 

Distinct37
Distinct (%)92.5%
Missing14
Missing (%)25.9%
Infinite0
Infinite (%)0.0%
Mean2048.4625
Minimum250
Maximum5881
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-22T21:41:23.705571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum250
5-th percentile387
Q1834
median1616
Q32995.625
95-th percentile4652.75
Maximum5881
Range5631
Interquartile range (IQR)2161.625

Descriptive statistics

Standard deviation1451.972
Coefficient of variation (CV)0.70881064
Kurtosis-0.16776437
Mean2048.4625
Median Absolute Deviation (MAD)851
Skewness0.86498797
Sum81938.5
Variance2108222.7
MonotonicityNot monotonic
2023-12-22T21:41:24.610105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
1054.0 2
 
3.7%
2840.0 2
 
3.7%
834.0 2
 
3.7%
2400.0 1
 
1.9%
3825.0 1
 
1.9%
4000.0 1
 
1.9%
4800.0 1
 
1.9%
1410.0 1
 
1.9%
1858.0 1
 
1.9%
1425.0 1
 
1.9%
Other values (27) 27
50.0%
(Missing) 14
25.9%
ValueCountFrequency (%)
250.0 1
1.9%
292.0 1
1.9%
392.0 1
1.9%
550.0 1
1.9%
560.0 1
1.9%
695.0 1
1.9%
760.0 1
1.9%
770.0 1
1.9%
807.0 1
1.9%
834.0 2
3.7%
ValueCountFrequency (%)
5881.0 1
1.9%
4800.0 1
1.9%
4645.0 1
1.9%
4400.0 1
1.9%
4000.0 1
1.9%
3825.0 1
1.9%
3757.0 1
1.9%
3686.0 1
1.9%
3599.0 1
1.9%
3462.5 1
1.9%

관람석좌석수
Categorical

IMBALANCE 

Distinct5
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Memory size564.0 B
<NA>
49 
500
 
2
20
 
1
100
 
1
233
 
1

Length

Max length4
Median length4
Mean length3.8888889
Min length2

Unique

Unique3 ?
Unique (%)5.6%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 49
90.7%
500 2
 
3.7%
20 1
 
1.9%
100 1
 
1.9%
233 1
 
1.9%

Length

2023-12-22T21:41:25.514653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-22T21:41:26.391937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 49
90.7%
500 2
 
3.7%
20 1
 
1.9%
100 1
 
1.9%
233 1
 
1.9%

수용인원수(명)
Categorical

IMBALANCE 

Distinct5
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Memory size564.0 B
<NA>
50 
500
 
1
1000
 
1
100
 
1
233
 
1

Length

Max length4
Median length4
Mean length3.9444444
Min length3

Unique

Unique4 ?
Unique (%)7.4%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 50
92.6%
500 1
 
1.9%
1000 1
 
1.9%
100 1
 
1.9%
233 1
 
1.9%

Length

2023-12-22T21:41:27.202192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-22T21:41:27.799184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 50
92.6%
500 1
 
1.9%
1000 1
 
1.9%
100 1
 
1.9%
233 1
 
1.9%

좌석형태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size564.0 B
<NA>
49 
의자식
5 

Length

Max length4
Median length4
Mean length3.9074074
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 49
90.7%
의자식 5
 
9.3%

Length

2023-12-22T21:41:28.628685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-22T21:41:29.467501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 49
90.7%
의자식 5
 
9.3%

건설사업비(백만원)
Real number (ℝ)

MISSING  ZEROS 

Distinct17
Distinct (%)94.4%
Missing36
Missing (%)66.7%
Infinite0
Infinite (%)0.0%
Mean2312.2222
Minimum0
Maximum16213
Zeros2
Zeros (%)3.7%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-22T21:41:30.083838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1325
median625
Q32363.25
95-th percentile10081.95
Maximum16213
Range16213
Interquartile range (IQR)2038.25

Descriptive statistics

Standard deviation4100.3487
Coefficient of variation (CV)1.7733368
Kurtosis8.1095041
Mean2312.2222
Median Absolute Deviation (MAD)600
Skewness2.7859557
Sum41620
Variance16812859
MonotonicityNot monotonic
2023-12-22T21:41:30.699238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 2
 
3.7%
900 1
 
1.9%
4052 1
 
1.9%
9000 1
 
1.9%
1500 1
 
1.9%
500 1
 
1.9%
1380 1
 
1.9%
418 1
 
1.9%
400 1
 
1.9%
124 1
 
1.9%
Other values (7) 7
 
13.0%
(Missing) 36
66.7%
ValueCountFrequency (%)
0 2
3.7%
50 1
1.9%
124 1
1.9%
300 1
1.9%
400 1
1.9%
418 1
1.9%
500 1
1.9%
600 1
1.9%
650 1
1.9%
900 1
1.9%
ValueCountFrequency (%)
16213 1
1.9%
9000 1
1.9%
4052 1
1.9%
2882 1
1.9%
2651 1
1.9%
1500 1
1.9%
1380 1
1.9%
900 1
1.9%
650 1
1.9%
600 1
1.9%

비고사항
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing54
Missing (%)100.0%
Memory size618.0 B

Sample

집계년도시군명시설명소유기관명관리주체명준공연도실내외구분명트랙바닥재료명필드바닥재료명부지면적(㎡)건축면적(㎡)연면적(㎡)트랙주로연장(m)트랙주로폭(m)트랙주로수필드폭(m)필드길이(m)면적(㎡)관람석좌석수수용인원수(명)좌석형태명건설사업비(백만원)비고사항
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62021구리시인창동 철도부지공원 체육시설 인라인스케이트장구리시구리시<NA>실외<NA>우레탄7149.0<NA><NA><NA><NA><NA>1942.5807.0<NA><NA><NA><NA><NA>
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집계년도시군명시설명소유기관명관리주체명준공연도실내외구분명트랙바닥재료명필드바닥재료명부지면적(㎡)건축면적(㎡)연면적(㎡)트랙주로연장(m)트랙주로폭(m)트랙주로수필드폭(m)필드길이(m)면적(㎡)관람석좌석수수용인원수(명)좌석형태명건설사업비(백만원)비고사항
442021화성시향남2 화합공원인라인스케이트장화성시화성도시공사2017실외<NA><NA>1244.0<NA><NA>1205.01<NA><NA><NA><NA><NA><NA><NA><NA>
452021화성시하나어린이공원 인라인스케이트장화성시화성시2008실외에폭시<NA>550.0<NA><NA><NA><NA><NA><NA><NA>550.0<NA><NA><NA><NA><NA>
462021화성시비봉 인라인스케이트장화성시화성시2006실외콘크리트<NA>2840.0<NA><NA><NA><NA><NA><NA><NA>2840.0<NA><NA><NA><NA><NA>
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482021화성시하늘빛공원 인라인스케이트장화성시화성도시공사2008실외에폭시<NA>560.0<NA><NA><NA><NA><NA><NA><NA>560.0<NA><NA><NA><NA><NA>
492021화성시슬기샘공원(동탄4호) 인라인스케이트장화성시화성도시공사2008실외에폭시<NA>695.0<NA><NA><NA><NA><NA><NA><NA>695.0<NA><NA><NA><NA><NA>
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512021화성시비봉고가하부체육시설화성시화성도시공사2006실외콘크리트<NA>2840.0<NA><NA><NA><NA><NA><NA><NA>2840.0<NA><NA><NA><NA><NA>
522021화성시썬큰인라인장화성시화성도시공사2008실외우레탄<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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