Overview

Dataset statistics

Number of variables8
Number of observations45
Missing cells8
Missing cells (%)2.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 KiB
Average record size in memory68.9 B

Variable types

Categorical3
Text3
Numeric2

Dataset

Description수원도시공사에서 운영중인 문화스포츠 대관시설(장안구민회관 한누리아트홀, 가족여성회관, 종합운동장)사용내역정보
Author수원도시공사
URLhttps://www.data.go.kr/data/15123862/fileData.do

Alerts

대관시설명 is highly overall correlated with 대관코드 and 1 other fieldsHigh correlation
대관코드 is highly overall correlated with 거래번호 and 2 other fieldsHigh correlation
거래번호 is highly overall correlated with 대관코드High correlation
이용인원 is highly overall correlated with 대관코드High correlation
사용시작시간 is highly overall correlated with 대관시설명High correlation
거래번호 has 8 (17.8%) missing valuesMissing
대관순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 01:13:21.954143
Analysis finished2023-12-12 01:13:23.183916
Duration1.23 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대관코드
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size492.0 B
장안구민회관
37 
가족여성회관
8 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
장안구민회관 37
82.2%
가족여성회관 8
 
17.8%

Length

2023-12-12T10:13:23.263389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:13:23.387379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
장안구민회관 37
82.2%
가족여성회관 8
 
17.8%

대관시설명
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size492.0 B
한누리아트홀
29 
노송갤러리
7 
대회의실
6 
갤러리
 
2
참사랑방
 
1

Length

Max length6
Median length6
Mean length5.4
Min length3

Unique

Unique1 ?
Unique (%)2.2%

Sample

1st row대회의실
2nd row대회의실
3rd row대회의실
4th row대회의실
5th row갤러리

Common Values

ValueCountFrequency (%)
한누리아트홀 29
64.4%
노송갤러리 7
 
15.6%
대회의실 6
 
13.3%
갤러리 2
 
4.4%
참사랑방 1
 
2.2%

Length

2023-12-12T10:13:23.556064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:13:23.726064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한누리아트홀 29
64.4%
노송갤러리 7
 
15.6%
대회의실 6
 
13.3%
갤러리 2
 
4.4%
참사랑방 1
 
2.2%

대관순번
Text

UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size492.0 B
2023-12-12T10:13:24.036731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length6.3555556
Min length6

Characters and Unicode

Total characters286
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)100.0%

Sample

1st row2023-001
2nd row2023-002
3rd row2023-003
4th row2023-004
5th row2023-005
ValueCountFrequency (%)
2023-001 1
 
2.2%
202316 1
 
2.2%
202318 1
 
2.2%
202319 1
 
2.2%
202320 1
 
2.2%
202321 1
 
2.2%
202322 1
 
2.2%
202323 1
 
2.2%
202324 1
 
2.2%
202325 1
 
2.2%
Other values (35) 35
77.8%
2023-12-12T10:13:24.543694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 105
36.7%
0 73
25.5%
3 58
20.3%
1 15
 
5.2%
- 8
 
2.8%
4 5
 
1.7%
5 5
 
1.7%
6 5
 
1.7%
7 5
 
1.7%
8 4
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 278
97.2%
Dash Punctuation 8
 
2.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 105
37.8%
0 73
26.3%
3 58
20.9%
1 15
 
5.4%
4 5
 
1.8%
5 5
 
1.8%
6 5
 
1.8%
7 5
 
1.8%
8 4
 
1.4%
9 3
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 286
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 105
36.7%
0 73
25.5%
3 58
20.3%
1 15
 
5.2%
- 8
 
2.8%
4 5
 
1.7%
5 5
 
1.7%
6 5
 
1.7%
7 5
 
1.7%
8 4
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 286
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 105
36.7%
0 73
25.5%
3 58
20.3%
1 15
 
5.2%
- 8
 
2.8%
4 5
 
1.7%
5 5
 
1.7%
6 5
 
1.7%
7 5
 
1.7%
8 4
 
1.4%

거래번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct37
Distinct (%)100.0%
Missing8
Missing (%)17.8%
Infinite0
Infinite (%)0.0%
Mean20230113
Minimum20230080
Maximum20230146
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T10:13:24.729472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20230080
5-th percentile20230086
Q120230099
median20230118
Q320230128
95-th percentile20230138
Maximum20230146
Range66
Interquartile range (IQR)29

Descriptive statistics

Standard deviation17.67682
Coefficient of variation (CV)8.737875 × 10-7
Kurtosis-1.0711004
Mean20230113
Median Absolute Deviation (MAD)14
Skewness-0.14989406
Sum7.485142 × 108
Variance312.46997
MonotonicityNot monotonic
2023-12-12T10:13:24.969214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
20230132 1
 
2.2%
20230128 1
 
2.2%
20230133 1
 
2.2%
20230111 1
 
2.2%
20230083 1
 
2.2%
20230140 1
 
2.2%
20230131 1
 
2.2%
20230146 1
 
2.2%
20230087 1
 
2.2%
20230096 1
 
2.2%
Other values (27) 27
60.0%
(Missing) 8
 
17.8%
ValueCountFrequency (%)
20230080 1
2.2%
20230083 1
2.2%
20230087 1
2.2%
20230089 1
2.2%
20230090 1
2.2%
20230092 1
2.2%
20230096 1
2.2%
20230097 1
2.2%
20230098 1
2.2%
20230099 1
2.2%
ValueCountFrequency (%)
20230146 1
2.2%
20230140 1
2.2%
20230137 1
2.2%
20230134 1
2.2%
20230133 1
2.2%
20230132 1
2.2%
20230131 1
2.2%
20230130 1
2.2%
20230129 1
2.2%
20230128 1
2.2%

이용인원
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)46.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean214.24444
Minimum7
Maximum850
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T10:13:25.156235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile40
Q1100
median150
Q3300
95-th percentile540
Maximum850
Range843
Interquartile range (IQR)200

Descriptive statistics

Standard deviation174.00942
Coefficient of variation (CV)0.8122004
Kurtosis3.3426839
Mean214.24444
Median Absolute Deviation (MAD)72
Skewness1.6798171
Sum9641
Variance30279.28
MonotonicityNot monotonic
2023-12-12T10:13:25.322066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
100 9
20.0%
350 4
 
8.9%
200 4
 
8.9%
300 3
 
6.7%
150 3
 
6.7%
60 2
 
4.4%
120 2
 
4.4%
70 2
 
4.4%
210 2
 
4.4%
35 2
 
4.4%
Other values (11) 12
26.7%
ValueCountFrequency (%)
7 1
 
2.2%
35 2
 
4.4%
60 2
 
4.4%
70 2
 
4.4%
78 1
 
2.2%
100 9
20.0%
106 1
 
2.2%
120 2
 
4.4%
150 3
 
6.7%
170 1
 
2.2%
ValueCountFrequency (%)
850 1
 
2.2%
650 1
 
2.2%
550 1
 
2.2%
500 1
 
2.2%
400 2
4.4%
350 4
8.9%
300 3
6.7%
250 1
 
2.2%
240 1
 
2.2%
210 2
4.4%

대관사용일자
Text

Distinct44
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size492.0 B
2023-12-12T10:13:25.599173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length11
Mean length12.511111
Min length9

Characters and Unicode

Total characters563
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)95.6%

Sample

1st row2023.7.7.
2nd row2023.7.17.
3rd row2023.7.28.
4th row2023.8.19.
5th row2023.8.21.~2023.8.26.
ValueCountFrequency (%)
2023.08.25 2
 
4.4%
2023.7.17 1
 
2.2%
2023.09.18 1
 
2.2%
2023.08.29 1
 
2.2%
2023.08.30 1
 
2.2%
2023.08.31 1
 
2.2%
2023.09.01 1
 
2.2%
2023.09.02 1
 
2.2%
2023.09.06 1
 
2.2%
2023.09.09.~10 1
 
2.2%
Other values (34) 34
75.6%
2023-12-12T10:13:26.074131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 155
27.5%
2 122
21.7%
0 102
18.1%
3 57
 
10.1%
1 28
 
5.0%
8 23
 
4.1%
9 21
 
3.7%
7 20
 
3.6%
~ 15
 
2.7%
6 8
 
1.4%
Other values (2) 12
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 393
69.8%
Other Punctuation 155
 
27.5%
Math Symbol 15
 
2.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 122
31.0%
0 102
26.0%
3 57
14.5%
1 28
 
7.1%
8 23
 
5.9%
9 21
 
5.3%
7 20
 
5.1%
6 8
 
2.0%
5 6
 
1.5%
4 6
 
1.5%
Other Punctuation
ValueCountFrequency (%)
. 155
100.0%
Math Symbol
ValueCountFrequency (%)
~ 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 563
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 155
27.5%
2 122
21.7%
0 102
18.1%
3 57
 
10.1%
1 28
 
5.0%
8 23
 
4.1%
9 21
 
3.7%
7 20
 
3.6%
~ 15
 
2.7%
6 8
 
1.4%
Other values (2) 12
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 563
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 155
27.5%
2 122
21.7%
0 102
18.1%
3 57
 
10.1%
1 28
 
5.0%
8 23
 
4.1%
9 21
 
3.7%
7 20
 
3.6%
~ 15
 
2.7%
6 8
 
1.4%
Other values (2) 12
 
2.1%

시설금액(원)
Text

Distinct40
Distinct (%)88.9%
Missing0
Missing (%)0.0%
Memory size492.0 B
2023-12-12T10:13:26.308951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length7.2888889
Min length6

Characters and Unicode

Total characters328
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)80.0%

Sample

1st row80,000
2nd row60,000
3rd row60,000
4th row90,000
5th row248,000
ValueCountFrequency (%)
60,000 3
 
6.7%
261,800 2
 
4.4%
110,000 2
 
4.4%
80,000 2
 
4.4%
211,200 1
 
2.2%
1,864,900 1
 
2.2%
832,900 1
 
2.2%
313,800 1
 
2.2%
410,200 1
 
2.2%
2,225,500 1
 
2.2%
Other values (30) 30
66.7%
2023-12-12T10:13:26.687694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 117
35.7%
, 56
17.1%
1 27
 
8.2%
8 23
 
7.0%
2 21
 
6.4%
4 20
 
6.1%
6 16
 
4.9%
9 15
 
4.6%
3 14
 
4.3%
5 10
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 272
82.9%
Other Punctuation 56
 
17.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 117
43.0%
1 27
 
9.9%
8 23
 
8.5%
2 21
 
7.7%
4 20
 
7.4%
6 16
 
5.9%
9 15
 
5.5%
3 14
 
5.1%
5 10
 
3.7%
7 9
 
3.3%
Other Punctuation
ValueCountFrequency (%)
, 56
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 328
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 117
35.7%
, 56
17.1%
1 27
 
8.2%
8 23
 
7.0%
2 21
 
6.4%
4 20
 
6.1%
6 16
 
4.9%
9 15
 
4.6%
3 14
 
4.3%
5 10
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 328
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 117
35.7%
, 56
17.1%
1 27
 
8.2%
8 23
 
7.0%
2 21
 
6.4%
4 20
 
6.1%
6 16
 
4.9%
9 15
 
4.6%
3 14
 
4.3%
5 10
 
3.0%

사용시작시간
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)22.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
9:00
16 
10:00
9 
13:00
7 
8:00
5 
<NA>
2 
Other values (5)
6 

Length

Max length5
Median length4
Mean length4.4888889
Min length4

Unique

Unique4 ?
Unique (%)8.9%

Sample

1st row10:00
2nd row13:00
3rd row9:00
4th row12:00
5th row<NA>

Common Values

ValueCountFrequency (%)
9:00 16
35.6%
10:00 9
20.0%
13:00 7
15.6%
8:00 5
 
11.1%
<NA> 2
 
4.4%
14:00 2
 
4.4%
12:00 1
 
2.2%
18:00 1
 
2.2%
15:00 1
 
2.2%
19:00 1
 
2.2%

Length

2023-12-12T10:13:26.849722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:13:26.984924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
9:00 16
35.6%
10:00 9
20.0%
13:00 7
15.6%
8:00 5
 
11.1%
na 2
 
4.4%
14:00 2
 
4.4%
12:00 1
 
2.2%
18:00 1
 
2.2%
15:00 1
 
2.2%
19:00 1
 
2.2%

Interactions

2023-12-12T10:13:22.610247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:13:22.391955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:13:22.732618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:13:22.497531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T10:13:27.109645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대관코드대관시설명대관순번거래번호이용인원대관사용일자시설금액(원)사용시작시간
대관코드1.0001.0001.000NaN0.6261.0001.0000.410
대관시설명1.0001.0001.0000.4860.2361.0000.7720.880
대관순번1.0001.0001.0001.0001.0001.0001.0001.000
거래번호NaN0.4861.0001.0000.6210.8970.9810.452
이용인원0.6260.2361.0000.6211.0000.9600.9930.000
대관사용일자1.0001.0001.0000.8970.9601.0000.9820.979
시설금액(원)1.0000.7721.0000.9810.9930.9821.0000.000
사용시작시간0.4100.8801.0000.4520.0000.9790.0001.000
2023-12-12T10:13:27.264875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대관시설명대관코드사용시작시간
대관시설명1.0000.9640.735
대관코드0.9641.0000.368
사용시작시간0.7350.3681.000
2023-12-12T10:13:27.401724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
거래번호이용인원대관코드대관시설명사용시작시간
거래번호1.0000.0391.0000.3050.095
이용인원0.0391.0000.5760.1130.000
대관코드1.0000.5761.0000.9640.368
대관시설명0.3050.1130.9641.0000.735
사용시작시간0.0950.0000.3680.7351.000

Missing values

2023-12-12T10:13:22.918755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:13:23.119600image/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

대관코드대관시설명대관순번거래번호이용인원대관사용일자시설금액(원)사용시작시간
0가족여성회관대회의실2023-001<NA>602023.7.7.80,00010:00
1가족여성회관대회의실2023-002<NA>352023.7.17.60,00013:00
2가족여성회관대회의실2023-003<NA>352023.7.28.60,0009:00
3가족여성회관대회의실2023-004<NA>602023.8.19.90,00012:00
4가족여성회관갤러리2023-005<NA>1202023.8.21.~2023.8.26.248,000<NA>
5가족여성회관대회의실2023-006<NA>1002023.8.31.48,0009:00
6가족여성회관갤러리2023-007<NA>702023.9.2.~2023.9.6.80,000<NA>
7가족여성회관대회의실2023-008<NA>702023.9.15.60,00018:00
8장안구민회관한누리아트홀202301202301041062023.07.03.244,9009:00
9장안구민회관한누리아트홀202302202300963502023.07.04.908,50015:00
대관코드대관시설명대관순번거래번호이용인원대관사용일자시설금액(원)사용시작시간
35장안구민회관한누리아트홀202328202301464002023.09.22.1,178,2009:00
36장안구민회관한누리아트홀202329202301321002023.09.23.261,8009:00
37장안구민회관노송갤러리202330202300871502023.06.28.~07.02.118,80010:00
38장안구민회관노송갤러리20233120230102782023.07.17.~21.110,00010:00
39장안구민회관노송갤러리202332202300802402023.07.24.~08.06.325,60010:00
40장안구민회관노송갤러리202333202300901202023.08.14.~19.140,80010:00
41장안구민회관노송갤러리202334202300973002023.08.20.~31.250,80010:00
42장안구민회관노송갤러리202335202301371002023.09.11.~14.88,00010:00
43장안구민회관노송갤러리202336202301252002023.09.15.~23.211,20010:00
44장안구민회관참사랑방2023372023011972023.08.09.44,00019:00