Overview

Dataset statistics

Number of variables12
Number of observations50
Missing cells50
Missing cells (%)8.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.4 KiB
Average record size in memory109.6 B

Variable types

Categorical10
Numeric1
Unsupported1

Dataset

Description골프장, 스키장, 요트장, 조정장, 카누장, 빙상장, 자동차경주장 등 등록체육시설 년도별 통계
Author강원도
URLhttps://www.data.go.kr/data/15056036/fileData.do

Alerts

시군별 is highly overall correlated with 골프장 and 7 other fieldsHigh correlation
종합체육시설 is highly overall correlated with 골프장 and 5 other fieldsHigh correlation
요트장 is highly overall correlated with 골프장 and 8 other fieldsHigh correlation
승마장 is highly overall correlated with 골프장 and 7 other fieldsHigh correlation
카누장 is highly overall correlated with 골프장 and 8 other fieldsHigh correlation
연도별 is highly overall correlated with 요트장 and 5 other fieldsHigh correlation
스키장 is highly overall correlated with 골프장 and 5 other fieldsHigh correlation
조정장 is highly overall correlated with 골프장 and 8 other fieldsHigh correlation
빙상장 is highly overall correlated with 골프장 and 6 other fieldsHigh correlation
골프장 is highly overall correlated with 시군별 and 7 other fieldsHigh correlation
경륜장 has 50 (100.0%) missing valuesMissing
경륜장 is an unsupported type, check if it needs cleaning or further analysisUnsupported
골프장 has 8 (16.0%) zerosZeros

Reproduction

Analysis started2023-12-12 23:20:12.546374
Analysis finished2023-12-12 23:20:13.729176
Duration1.18 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군별
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)36.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
춘천시
 
3
홍천군
 
3
양양군
 
3
강릉시
 
3
태백시
 
3
Other values (13)
35 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row춘천시
2nd row원주시
3rd row강릉시
4th row동해시
5th row태백시

Common Values

ValueCountFrequency (%)
춘천시 3
 
6.0%
홍천군 3
 
6.0%
양양군 3
 
6.0%
강릉시 3
 
6.0%
태백시 3
 
6.0%
속초시 3
 
6.0%
횡성군 3
 
6.0%
삼척시 3
 
6.0%
영월군 3
 
6.0%
원주시 3
 
6.0%
Other values (8) 20
40.0%

Length

2023-12-13T08:20:13.800854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
춘천시 3
 
6.0%
영월군 3
 
6.0%
고성군 3
 
6.0%
철원군 3
 
6.0%
정선군 3
 
6.0%
평창군 3
 
6.0%
홍천군 3
 
6.0%
원주시 3
 
6.0%
삼척시 3
 
6.0%
횡성군 3
 
6.0%
Other values (8) 20
40.0%

연도별
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2010
18 
2011
18 
2012
14 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2010
2nd row2010
3rd row2010
4th row2010
5th row2010

Common Values

ValueCountFrequency (%)
2010 18
36.0%
2011 18
36.0%
2012 14
28.0%

Length

2023-12-13T08:20:13.892617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:20:13.987527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2010 18
36.0%
2011 18
36.0%
2012 14
28.0%

골프장
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct10
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.9
Minimum0
Maximum10
Zeros8
Zeros (%)16.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-13T08:20:14.080741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q34
95-th percentile9
Maximum10
Range10
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.7497681
Coefficient of variation (CV)0.94819589
Kurtosis0.26323718
Mean2.9
Median Absolute Deviation (MAD)1.5
Skewness1.096277
Sum145
Variance7.5612245
MonotonicityNot monotonic
2023-12-13T08:20:14.180332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
2 13
26.0%
1 11
22.0%
0 8
16.0%
4 6
12.0%
9 3
 
6.0%
7 3
 
6.0%
6 3
 
6.0%
3 1
 
2.0%
10 1
 
2.0%
5 1
 
2.0%
ValueCountFrequency (%)
0 8
16.0%
1 11
22.0%
2 13
26.0%
3 1
 
2.0%
4 6
12.0%
5 1
 
2.0%
6 3
 
6.0%
7 3
 
6.0%
9 3
 
6.0%
10 1
 
2.0%
ValueCountFrequency (%)
10 1
 
2.0%
9 3
 
6.0%
7 3
 
6.0%
6 3
 
6.0%
5 1
 
2.0%
4 6
12.0%
3 1
 
2.0%
2 13
26.0%
1 11
22.0%
0 8
16.0%

스키장
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
1
21 
0
20 
<NA>
6 
4
 
2
3
 
1

Length

Max length4
Median length1
Mean length1.36
Min length1

Unique

Unique1 ?
Unique (%)2.0%

Sample

1st row1
2nd row1
3rd row0
4th row0
5th row1

Common Values

ValueCountFrequency (%)
1 21
42.0%
0 20
40.0%
<NA> 6
 
12.0%
4 2
 
4.0%
3 1
 
2.0%

Length

2023-12-13T08:20:14.363402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:20:14.479563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 21
42.0%
0 20
40.0%
na 6
 
12.0%
4 2
 
4.0%
3 1
 
2.0%

요트장
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
<NA>
32 
0
18 

Length

Max length4
Median length4
Mean length2.92
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 32
64.0%
0 18
36.0%

Length

2023-12-13T08:20:14.626141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:20:14.764450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 32
64.0%
0 18
36.0%

조정장
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
<NA>
32 
0
18 

Length

Max length4
Median length4
Mean length2.92
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 32
64.0%
0 18
36.0%

Length

2023-12-13T08:20:14.879426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:20:14.995455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 32
64.0%
0 18
36.0%

카누장
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
<NA>
32 
0
18 

Length

Max length4
Median length4
Mean length2.92
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 32
64.0%
0 18
36.0%

Length

2023-12-13T08:20:15.096813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:20:15.194469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 32
64.0%
0 18
36.0%

빙상장
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
<NA>
32 
0
15 
1
 
3

Length

Max length4
Median length4
Mean length2.92
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row1
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 32
64.0%
0 15
30.0%
1 3
 
6.0%

Length

2023-12-13T08:20:15.326929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:20:15.431683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 32
64.0%
0 15
30.0%
1 3
 
6.0%

자동차 경주장
Categorical

Distinct3
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
<NA>
31 
0
17 
1
 
2

Length

Max length4
Median length4
Mean length2.86
Min length1

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> 31
62.0%
0 17
34.0%
1 2
 
4.0%

Length

2023-12-13T08:20:15.557490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:20:15.658450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 31
62.0%
0 17
34.0%
1 2
 
4.0%

경륜장
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing50
Missing (%)100.0%
Memory size582.0 B

승마장
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
<NA>
32 
0
16 
1
 
2

Length

Max length4
Median length4
Mean length2.92
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 32
64.0%
0 16
32.0%
1 2
 
4.0%

Length

2023-12-13T08:20:15.762833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:20:15.858904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 32
64.0%
0 16
32.0%
1 2
 
4.0%

종합체육시설
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
<NA>
32 
0
12 
1
6 

Length

Max length4
Median length4
Mean length2.92
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 32
64.0%
0 12
 
24.0%
1 6
 
12.0%

Length

2023-12-13T08:20:15.956686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:20:16.049249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 32
64.0%
0 12
 
24.0%
1 6
 
12.0%

Interactions

2023-12-13T08:20:13.392250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:20:16.122729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군별연도별골프장스키장빙상장자동차 경주장승마장종합체육시설
시군별1.0000.0000.8990.8641.0001.0001.0001.000
연도별0.0001.0000.0000.296NaN0.314NaNNaN
골프장0.8990.0001.0000.8290.6680.0001.0000.635
스키장0.8640.2960.8291.0000.2820.1520.4340.320
빙상장1.000NaN0.6680.2821.000NaN0.7240.000
자동차 경주장1.0000.3140.0000.152NaN1.000NaNNaN
승마장1.000NaN1.0000.4340.724NaN1.0000.326
종합체육시설1.000NaN0.6350.3200.000NaN0.3261.000
2023-12-13T08:20:16.256782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군별종합체육시설요트장자동차 경주장승마장카누장연도별스키장조정장빙상장
시군별1.0001.0001.0000.2431.0001.0000.0000.5401.0001.000
종합체육시설1.0001.0001.000NaN0.2031.0001.0000.4931.0000.000
요트장1.0001.0001.000NaN1.0001.0001.0001.0001.0001.000
자동차 경주장0.243NaNNaN1.000NaNNaN0.1960.232NaNNaN
승마장1.0000.2031.000NaN1.0001.0001.0000.6521.0000.513
카누장1.0001.0001.000NaN1.0001.0001.0001.0001.0001.000
연도별0.0001.0001.0000.1961.0001.0001.0000.2781.0001.000
스키장0.5400.4931.0000.2320.6521.0000.2781.0001.0000.437
조정장1.0001.0001.000NaN1.0001.0001.0001.0001.0001.000
빙상장1.0000.0001.000NaN0.5131.0001.0000.4371.0001.000
2023-12-13T08:20:16.398434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
골프장시군별연도별스키장요트장조정장카누장빙상장자동차 경주장승마장종합체육시설
골프장1.0000.5070.0000.6301.0001.0001.0000.6100.0000.8660.580
시군별0.5071.0000.0000.5401.0001.0001.0001.0000.2431.0001.000
연도별0.0000.0001.0000.2781.0001.0001.0001.0000.1961.0001.000
스키장0.6300.5400.2781.0001.0001.0001.0000.4370.2320.6520.493
요트장1.0001.0001.0001.0001.0001.0001.0001.0000.0001.0001.000
조정장1.0001.0001.0001.0001.0001.0001.0001.0000.0001.0001.000
카누장1.0001.0001.0001.0001.0001.0001.0001.0000.0001.0001.000
빙상장0.6101.0001.0000.4371.0001.0001.0001.0000.0000.5130.000
자동차 경주장0.0000.2430.1960.2320.0000.0000.0000.0001.0000.0000.000
승마장0.8661.0001.0000.6521.0001.0001.0000.5130.0001.0000.203
종합체육시설0.5801.0001.0000.4931.0001.0001.0000.0000.0000.2031.000

Missing values

2023-12-13T08:20:13.514816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:20:13.665039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

시군별연도별골프장스키장요트장조정장카누장빙상장자동차 경주장경륜장승마장종합체육시설
0춘천시2010410000<NA><NA>01
1원주시2010910001<NA><NA>11
2강릉시2010100001<NA><NA>00
3동해시2010000000<NA><NA>00
4태백시2010210000<NA><NA>00
5속초시2010200000<NA><NA>00
6삼척시2010200000<NA><NA>00
7홍천군2010310000<NA><NA>01
8횡성군2010410000<NA><NA>00
9영월군2010100000<NA><NA>00
시군별연도별골프장스키장요트장조정장카누장빙상장자동차 경주장경륜장승마장종합체육시설
40속초시20122<NA><NA><NA><NA><NA><NA><NA><NA><NA>
41삼척시20122<NA><NA><NA><NA><NA><NA><NA><NA><NA>
42홍천군201241<NA><NA><NA><NA><NA><NA><NA><NA>
43횡성군201261<NA><NA><NA><NA><NA><NA><NA><NA>
44영월군20121<NA><NA><NA><NA><NA><NA><NA><NA><NA>
45평창군201273<NA><NA><NA><NA><NA><NA><NA><NA>
46정선군201221<NA><NA><NA><NA><NA><NA><NA><NA>
47철원군20121<NA><NA><NA><NA><NA><NA><NA><NA><NA>
48고성군201251<NA><NA><NA><NA><NA><NA><NA><NA>
49양양군20121<NA><NA><NA><NA><NA><NA><NA><NA><NA>