Overview

Dataset statistics

Number of variables4
Number of observations24
Missing cells10
Missing cells (%)10.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory972.0 B
Average record size in memory40.5 B

Variable types

Numeric3
Text1

Dataset

Description충청남도 공공체육시설 세부현황 자료입니다. 자료기준 : 2021년 12월 31일 공공체육시설 총 1,829개소 총 면적 10,047,870m2
URLhttps://www.data.go.kr/data/15019908/fileData.do

Alerts

개소 is highly overall correlated with 연면적High correlation
연면적 is highly overall correlated with 개소High correlation
개소 has 5 (20.8%) missing valuesMissing
연면적 has 5 (20.8%) missing valuesMissing
번호 has unique valuesUnique
종목 has unique valuesUnique

Reproduction

Analysis started2023-12-12 19:03:36.759581
Analysis finished2023-12-12 19:03:38.036044
Duration1.28 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.166667
Minimum1
Maximum25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T04:03:38.094594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.15
Q16.75
median13.5
Q319.25
95-th percentile23.85
Maximum25
Range24
Interquartile range (IQR)12.5

Descriptive statistics

Standard deviation7.4697457
Coefficient of variation (CV)0.56732246
Kurtosis-1.234444
Mean13.166667
Median Absolute Deviation (MAD)6.5
Skewness-0.065751263
Sum316
Variance55.797101
MonotonicityStrictly increasing
2023-12-13T04:03:38.221002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 1
 
4.2%
15 1
 
4.2%
25 1
 
4.2%
24 1
 
4.2%
23 1
 
4.2%
22 1
 
4.2%
21 1
 
4.2%
20 1
 
4.2%
19 1
 
4.2%
18 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
1 1
4.2%
2 1
4.2%
3 1
4.2%
4 1
4.2%
5 1
4.2%
6 1
4.2%
7 1
4.2%
8 1
4.2%
10 1
4.2%
11 1
4.2%
ValueCountFrequency (%)
25 1
4.2%
24 1
4.2%
23 1
4.2%
22 1
4.2%
21 1
4.2%
20 1
4.2%
19 1
4.2%
18 1
4.2%
17 1
4.2%
16 1
4.2%

종목
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-13T04:03:38.413022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.25
Min length3

Characters and Unicode

Total characters102
Distinct characters57
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st row육상경기장
2nd row축구장
3rd row하키장
4th row야구장
5th row싸이클경기장
ValueCountFrequency (%)
육상경기장 1
 
4.2%
축구장 1
 
4.2%
설상경기장 1
 
4.2%
빙상장 1
 
4.2%
요트장 1
 
4.2%
조정카누장 1
 
4.2%
골프연습장 1
 
4.2%
승마장 1
 
4.2%
양궁장 1
 
4.2%
국궁장 1
 
4.2%
Other values (14) 14
58.3%
2023-12-13T04:03:38.754953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 20
 
19.6%
기 6
 
5.9%
육 4
 
3.9%
이 4
 
3.9%
트 3
 
2.9%
관 3
 
2.9%
상 3
 
2.9%
구 3
 
2.9%
경 3
 
2.9%
체 3
 
2.9%
Other values (47) 50
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 102
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 20
 
19.6%
기 6
 
5.9%
육 4
 
3.9%
이 4
 
3.9%
트 3
 
2.9%
관 3
 
2.9%
상 3
 
2.9%
구 3
 
2.9%
경 3
 
2.9%
체 3
 
2.9%
Other values (47) 50
49.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 102
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 20
 
19.6%
기 6
 
5.9%
육 4
 
3.9%
이 4
 
3.9%
트 3
 
2.9%
관 3
 
2.9%
상 3
 
2.9%
구 3
 
2.9%
경 3
 
2.9%
체 3
 
2.9%
Other values (47) 50
49.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 102
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 20
 
19.6%
기 6
 
5.9%
육 4
 
3.9%
이 4
 
3.9%
트 3
 
2.9%
관 3
 
2.9%
상 3
 
2.9%
구 3
 
2.9%
경 3
 
2.9%
체 3
 
2.9%
Other values (47) 50
49.0%

개소
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct14
Distinct (%)73.7%
Missing5
Missing (%)20.8%
Infinite0
Infinite (%)0.0%
Mean96.263158
Minimum1
Maximum1342
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T04:03:38.886287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median17
Q331.5
95-th percentile346.6
Maximum1342
Range1341
Interquartile range (IQR)29.5

Descriptive statistics

Standard deviation306.18202
Coefficient of variation (CV)3.180677
Kurtosis17.705628
Mean96.263158
Median Absolute Deviation (MAD)15
Skewness4.1662525
Sum1829
Variance93747.427
MonotonicityNot monotonic
2023-12-13T04:03:39.025265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
2 4
16.7%
1 3
12.5%
17 1
 
4.2%
30 1
 
4.2%
23 1
 
4.2%
34 1
 
4.2%
1342 1
 
4.2%
40 1
 
4.2%
33 1
 
4.2%
236 1
 
4.2%
Other values (4) 4
16.7%
(Missing) 5
20.8%
ValueCountFrequency (%)
1 3
12.5%
2 4
16.7%
6 1
 
4.2%
9 1
 
4.2%
17 1
 
4.2%
22 1
 
4.2%
23 1
 
4.2%
26 1
 
4.2%
30 1
 
4.2%
33 1
 
4.2%
ValueCountFrequency (%)
1342 1
4.2%
236 1
4.2%
40 1
4.2%
34 1
4.2%
33 1
4.2%
30 1
4.2%
26 1
4.2%
23 1
4.2%
22 1
4.2%
17 1
4.2%

연면적
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct19
Distinct (%)100.0%
Missing5
Missing (%)20.8%
Infinite0
Infinite (%)0.0%
Mean528835.24
Minimum3388
Maximum2108110
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T04:03:39.138981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3388
5-th percentile8025.7
Q130260
median181581
Q3931433.05
95-th percentile1899431.5
Maximum2108110
Range2104722
Interquartile range (IQR)901173.05

Descriptive statistics

Standard deviation638208.2
Coefficient of variation (CV)1.2068186
Kurtosis1.1966934
Mean528835.24
Median Absolute Deviation (MAD)178193
Skewness1.3428046
Sum10047870
Variance4.073097 × 1011
MonotonicityNot monotonic
2023-12-13T04:03:39.245386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
985639.0 1
 
4.2%
524214.0 1
 
4.2%
30892.0 1
 
4.2%
8541.0 1
 
4.2%
25843.0 1
 
4.2%
159252.0 1
 
4.2%
12930.0 1
 
4.2%
29628.0 1
 
4.2%
181581.0 1
 
4.2%
2108110.0 1
 
4.2%
Other values (9) 9
37.5%
(Missing) 5
20.8%
ValueCountFrequency (%)
3388.0 1
4.2%
8541.0 1
4.2%
12930.0 1
4.2%
25843.0 1
4.2%
29628.0 1
4.2%
30892.0 1
4.2%
33008.0 1
4.2%
98286.9 1
4.2%
159252.0 1
4.2%
181581.0 1
4.2%
ValueCountFrequency (%)
2108110.0 1
4.2%
1876245.0 1
4.2%
995513.63 1
4.2%
985639.0 1
4.2%
932570.1 1
4.2%
930296.0 1
4.2%
651671.0 1
4.2%
524214.0 1
4.2%
460261.0 1
4.2%
181581.0 1
4.2%

Interactions

2023-12-13T04:03:37.548709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:03:36.921175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:03:37.271068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:03:37.630984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:03:37.039036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:03:37.365471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:03:37.716260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:03:37.155242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:03:37.466702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T04:03:39.327139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호종목개소연면적
번호1.0001.0000.0000.000
종목1.0001.0001.0001.000
개소0.0001.0001.0000.925
연면적0.0001.0000.9251.000
2023-12-13T04:03:39.427036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호개소연면적
번호1.000-0.336-0.474
개소-0.3361.0000.820
연면적-0.4740.8201.000

Missing values

2023-12-13T04:03:37.819639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:03:37.901446image/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.
2023-12-13T04:03:37.990896image/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

번호종목개소연면적
01육상경기장172108110.0
12축구장30985639.0
23하키장233008.0
34야구장23460261.0
45싸이클경기장<NA><NA>
56테니스장34651671.0
67씨름장23388.0
78간이운동장13421876245.0
810구기체육관40930296.0
911투기체육관198286.9
번호종목개소연면적
1416사격장212930.0
1517국궁장22159252.0
1618양궁장<NA><NA>
1719승마장225843.0
1820골프연습장<NA><NA>
1921조정카누장<NA><NA>
2022요트장18541.0
2123빙상장130892.0
2224설상경기장<NA><NA>
2325기타시설26524214.0