Overview

Dataset statistics

Number of variables6
Number of observations25
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 KiB
Average record size in memory54.3 B

Variable types

Categorical1
Numeric1
Text1
Boolean3

Dataset

Description대구시설공단 체육시설 시설관련정보입니다.
Author대구시설공단
URLhttps://www.data.go.kr/data/15088098/fileData.do

Alerts

업장사용여부 has constant value ""Constant

Reproduction

Analysis started2023-12-12 06:01:22.492348
Analysis finished2023-12-12 06:01:23.027088
Duration0.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

센터명
Categorical

Distinct3
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
서재문화체육센터
12 
올림픽기념국민생활관
7 
대구실내빙상장
6 

Length

Max length10
Median length8
Mean length8.32
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서재문화체육센터 12
48.0%
올림픽기념국민생활관 7
28.0%
대구실내빙상장 6
24.0%

Length

2023-12-12T15:01:23.120305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:01:23.246736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서재문화체육센터 12
48.0%
올림픽기념국민생활관 7
28.0%
대구실내빙상장 6
24.0%

업장코드
Real number (ℝ)

Distinct12
Distinct (%)48.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.24
Minimum1
Maximum13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T15:01:23.355057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5
Q37
95-th percentile11.8
Maximum13
Range12
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.4312291
Coefficient of variation (CV)0.65481472
Kurtosis-0.020948798
Mean5.24
Median Absolute Deviation (MAD)2
Skewness0.82762271
Sum131
Variance11.773333
MonotonicityNot monotonic
2023-12-12T15:01:23.500794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2 3
12.0%
3 3
12.0%
4 3
12.0%
5 3
12.0%
6 3
12.0%
1 3
12.0%
7 2
8.0%
8 1
 
4.0%
10 1
 
4.0%
11 1
 
4.0%
Other values (2) 2
8.0%
ValueCountFrequency (%)
1 3
12.0%
2 3
12.0%
3 3
12.0%
4 3
12.0%
5 3
12.0%
6 3
12.0%
7 2
8.0%
8 1
 
4.0%
10 1
 
4.0%
11 1
 
4.0%
ValueCountFrequency (%)
13 1
 
4.0%
12 1
 
4.0%
11 1
 
4.0%
10 1
 
4.0%
8 1
 
4.0%
7 2
8.0%
6 3
12.0%
5 3
12.0%
4 3
12.0%
3 3
12.0%

업장명
Text

Distinct22
Distinct (%)88.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-12T15:01:23.725295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length6.32
Min length2

Characters and Unicode

Total characters158
Distinct characters65
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

Unique20 ?
Unique (%)80.0%

Sample

1st row수 영 장
2nd row체력단련실
3rd row탁 구 장
4th row요 가
5th row다목적체육관
ValueCountFrequency (%)
장 9
 
16.4%
기 3
 
5.5%
타 3
 
5.5%
스 3
 
5.5%
업 3
 
5.5%
수 2
 
3.6%
댄 2
 
3.6%
구 2
 
3.6%
영 2
 
3.6%
체력증진교실 1
 
1.8%
Other values (25) 25
45.5%
2023-12-12T15:01:24.145395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
50
31.6%
장 10
 
6.3%
스 6
 
3.8%
실 4
 
2.5%
체 4
 
2.5%
관 4
 
2.5%
트 3
 
1.9%
로 3
 
1.9%
아 3
 
1.9%
기 3
 
1.9%
Other values (55) 68
43.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 106
67.1%
Space Separator 50
31.6%
Open Punctuation 1
 
0.6%
Close Punctuation 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 10
 
9.4%
스 6
 
5.7%
실 4
 
3.8%
체 4
 
3.8%
관 4
 
3.8%
트 3
 
2.8%
로 3
 
2.8%
아 3
 
2.8%
기 3
 
2.8%
업 3
 
2.8%
Other values (52) 63
59.4%
Space Separator
ValueCountFrequency (%)
50
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 106
67.1%
Common 52
32.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 10
 
9.4%
스 6
 
5.7%
실 4
 
3.8%
체 4
 
3.8%
관 4
 
3.8%
트 3
 
2.8%
로 3
 
2.8%
아 3
 
2.8%
기 3
 
2.8%
업 3
 
2.8%
Other values (52) 63
59.4%
Common
ValueCountFrequency (%)
50
96.2%
( 1
 
1.9%
) 1
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 106
67.1%
ASCII 52
32.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
50
96.2%
( 1
 
1.9%
) 1
 
1.9%
Hangul
ValueCountFrequency (%)
장 10
 
9.4%
스 6
 
5.7%
실 4
 
3.8%
체 4
 
3.8%
관 4
 
3.8%
트 3
 
2.8%
로 3
 
2.8%
아 3
 
2.8%
기 3
 
2.8%
업 3
 
2.8%
Other values (52) 63
59.4%

업장사용여부
Boolean

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size157.0 B
True
25 
ValueCountFrequency (%)
True 25
100.0%
2023-12-12T15:01:24.260695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

대관유무
Boolean

Distinct2
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size157.0 B
False
20 
True
5 
ValueCountFrequency (%)
False 20
80.0%
True 5
 
20.0%
2023-12-12T15:01:24.348851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

전자키사용유무
Boolean

Distinct2
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size157.0 B
False
22 
True
3 
ValueCountFrequency (%)
False 22
88.0%
True 3
 
12.0%
2023-12-12T15:01:24.452187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Interactions

2023-12-12T15:01:22.735104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:01:24.538595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
센터명업장코드업장명대관유무전자키사용유무
센터명1.0000.0000.0000.1340.165
업장코드0.0001.0001.0000.5130.506
업장명0.0001.0001.0001.0000.000
대관유무0.1340.5131.0001.0000.000
전자키사용유무0.1650.5060.0000.0001.000
2023-12-12T15:01:24.668588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
센터명대관유무전자키사용유무
센터명1.0000.2090.259
대관유무0.2091.0000.000
전자키사용유무0.2590.0001.000
2023-12-12T15:01:24.763274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업장코드센터명대관유무전자키사용유무
업장코드1.0000.0000.4570.411
센터명0.0001.0000.2090.259
대관유무0.4570.2091.0000.000
전자키사용유무0.4110.2590.0001.000

Missing values

2023-12-12T15:01:22.863366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:01:22.983143image/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

센터명업장코드업장명업장사용여부대관유무전자키사용유무
0서재문화체육센터2수 영 장YNY
1서재문화체육센터3체력단련실YNN
2서재문화체육센터4탁 구 장YYN
3서재문화체육센터5요 가YNN
4서재문화체육센터6다목적체육관YYN
5서재문화체육센터7풋 살 장YYN
6서재문화체육센터8족 구 장YYN
7대구실내빙상장6시 설 대 관YYN
8서재문화체육센터1기 타 업 장YNN
9서재문화체육센터10아쿠아로빅장YNY
센터명업장코드업장명업장사용여부대관유무전자키사용유무
15올림픽기념국민생활관4실내체육관YNN
16올림픽기념국민생활관5댄 스 실YNN
17올림픽기념국민생활관6복합프로그램YNN
18올림픽기념국민생활관7체력증진교실YNN
19대구실내빙상장1기 타 업 장YNN
20대구실내빙상장2쇼트트랙(스피드)YNN
21대구실내빙상장3피겨YNN
22대구실내빙상장4아이스하키YNN
23대구실내빙상장5자유 스케이트YNN
24서재문화체육센터13코로나 강습관련YNY