Overview

Dataset statistics

Number of variables7
Number of observations226
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.7 KiB
Average record size in memory57.6 B

Variable types

Numeric1
Categorical3
Text3

Dataset

Description광주광역시 시청사 미술품 등록데이터로 청사에 전시된 보유 및 대여 미술품의 관리번호, 작품명, 작가 등의 항목을 제공합니다.
Author광주광역시
URLhttps://www.data.go.kr/data/15054778/fileData.do

Alerts

연번 is highly overall correlated with 소관High correlation
소관 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
부문별 is highly overall correlated with 소관High correlation
제작 연도 is highly overall correlated with 소관High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 23:15:17.918343
Analysis finished2023-12-12 23:15:19.070103
Duration1.15 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct226
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean113.5
Minimum1
Maximum226
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-13T08:15:19.165253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile12.25
Q157.25
median113.5
Q3169.75
95-th percentile214.75
Maximum226
Range225
Interquartile range (IQR)112.5

Descriptive statistics

Standard deviation65.384759
Coefficient of variation (CV)0.57607717
Kurtosis-1.2
Mean113.5
Median Absolute Deviation (MAD)56.5
Skewness0
Sum25651
Variance4275.1667
MonotonicityStrictly increasing
2023-12-13T08:15:19.327366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
171 1
 
0.4%
145 1
 
0.4%
146 1
 
0.4%
147 1
 
0.4%
148 1
 
0.4%
149 1
 
0.4%
150 1
 
0.4%
151 1
 
0.4%
152 1
 
0.4%
Other values (216) 216
95.6%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
226 1
0.4%
225 1
0.4%
224 1
0.4%
223 1
0.4%
222 1
0.4%
221 1
0.4%
220 1
0.4%
219 1
0.4%
218 1
0.4%
217 1
0.4%

소관
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
회계과
148 
미술관
78 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
회계과 148
65.5%
미술관 78
34.5%

Length

2023-12-13T08:15:19.489952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:15:19.579727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
회계과 148
65.5%
미술관 78
34.5%

작품명
Text

Distinct218
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-13T08:15:19.764747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length21
Mean length8.6283186
Min length1

Characters and Unicode

Total characters1950
Distinct characters290
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique213 ?
Unique (%)94.2%

Sample

1st row 形-Ⅲ
2nd row95-75
3rd rowAugust ①
4th rowCircle Ⅱ
5th rowGIFT BOX
ValueCountFrequency (%)
of 13
 
2.9%
no 8
 
1.8%
존재 8
 
1.8%
rule,s 8
 
1.8%
box 7
 
1.6%
sea 7
 
1.6%
점 7
 
1.6%
gift 7
 
1.6%
sound 7
 
1.6%
landscape 6
 
1.4%
Other values (309) 366
82.4%
2023-12-13T08:15:20.175453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
247
 
12.7%
0 58
 
3.0%
2 47
 
2.4%
1 46
 
2.4%
o 42
 
2.2%
의 37
 
1.9%
s 36
 
1.8%
- 34
 
1.7%
4 33
 
1.7%
e 32
 
1.6%
Other values (280) 1338
68.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 742
38.1%
Lowercase Letter 324
16.6%
Uppercase Letter 263
 
13.5%
Decimal Number 256
 
13.1%
Space Separator 247
 
12.7%
Dash Punctuation 34
 
1.7%
Other Punctuation 30
 
1.5%
Open Punctuation 20
 
1.0%
Close Punctuation 20
 
1.0%
Letter Number 10
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 37
 
5.0%
무 22
 
3.0%
등 17
 
2.3%
화 16
 
2.2%
산 16
 
2.2%
기 13
 
1.8%
미 11
 
1.5%
고 11
 
1.5%
리 11
 
1.5%
인 9
 
1.2%
Other values (211) 579
78.0%
Lowercase Letter
ValueCountFrequency (%)
o 42
13.0%
s 36
11.1%
e 32
9.9%
u 24
 
7.4%
r 23
 
7.1%
f 20
 
6.2%
a 19
 
5.9%
l 19
 
5.9%
n 18
 
5.6%
d 17
 
5.2%
Other values (12) 74
22.8%
Uppercase Letter
ValueCountFrequency (%)
O 29
11.0%
A 24
 
9.1%
N 23
 
8.7%
E 22
 
8.4%
R 20
 
7.6%
I 17
 
6.5%
P 16
 
6.1%
D 14
 
5.3%
C 13
 
4.9%
S 13
 
4.9%
Other values (11) 72
27.4%
Decimal Number
ValueCountFrequency (%)
0 58
22.7%
2 47
18.4%
1 46
18.0%
4 33
12.9%
9 19
 
7.4%
5 13
 
5.1%
8 13
 
5.1%
3 11
 
4.3%
7 10
 
3.9%
6 6
 
2.3%
Other Punctuation
ValueCountFrequency (%)
, 20
66.7%
/ 8
 
26.7%
. 1
 
3.3%
? 1
 
3.3%
Letter Number
ValueCountFrequency (%)
Ⅱ 4
40.0%
Ⅰ 3
30.0%
Ⅲ 2
20.0%
Ⅳ 1
 
10.0%
Other Number
ValueCountFrequency (%)
① 1
25.0%
④ 1
25.0%
③ 1
25.0%
② 1
25.0%
Space Separator
ValueCountFrequency (%)
247
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 733
37.6%
Common 611
31.3%
Latin 597
30.6%
Han 9
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 37
 
5.0%
무 22
 
3.0%
등 17
 
2.3%
화 16
 
2.2%
산 16
 
2.2%
기 13
 
1.8%
미 11
 
1.5%
고 11
 
1.5%
리 11
 
1.5%
인 9
 
1.2%
Other values (205) 570
77.8%
Latin
ValueCountFrequency (%)
o 42
 
7.0%
s 36
 
6.0%
e 32
 
5.4%
O 29
 
4.9%
u 24
 
4.0%
A 24
 
4.0%
r 23
 
3.9%
N 23
 
3.9%
E 22
 
3.7%
R 20
 
3.4%
Other values (37) 322
53.9%
Common
ValueCountFrequency (%)
247
40.4%
0 58
 
9.5%
2 47
 
7.7%
1 46
 
7.5%
- 34
 
5.6%
4 33
 
5.4%
( 20
 
3.3%
, 20
 
3.3%
) 20
 
3.3%
9 19
 
3.1%
Other values (12) 67
 
11.0%
Han
ValueCountFrequency (%)
形 4
44.4%
落 1
 
11.1%
花 1
 
11.1%
光 1
 
11.1%
景 1
 
11.1%
海 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1194
61.2%
Hangul 733
37.6%
Number Forms 10
 
0.5%
CJK 8
 
0.4%
Enclosed Alphanum 4
 
0.2%
CJK Compat Ideographs 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
247
20.7%
0 58
 
4.9%
2 47
 
3.9%
1 46
 
3.9%
o 42
 
3.5%
s 36
 
3.0%
- 34
 
2.8%
4 33
 
2.8%
e 32
 
2.7%
O 29
 
2.4%
Other values (51) 590
49.4%
Hangul
ValueCountFrequency (%)
의 37
 
5.0%
무 22
 
3.0%
등 17
 
2.3%
화 16
 
2.2%
산 16
 
2.2%
기 13
 
1.8%
미 11
 
1.5%
고 11
 
1.5%
리 11
 
1.5%
인 9
 
1.2%
Other values (205) 570
77.8%
Number Forms
ValueCountFrequency (%)
Ⅱ 4
40.0%
Ⅰ 3
30.0%
Ⅲ 2
20.0%
Ⅳ 1
 
10.0%
CJK
ValueCountFrequency (%)
形 4
50.0%
花 1
 
12.5%
光 1
 
12.5%
景 1
 
12.5%
海 1
 
12.5%
Enclosed Alphanum
ValueCountFrequency (%)
① 1
25.0%
④ 1
25.0%
③ 1
25.0%
② 1
25.0%
CJK Compat Ideographs
ValueCountFrequency (%)
落 1
100.0%

작가
Text

Distinct122
Distinct (%)54.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-13T08:15:20.460643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length3
Mean length3.159292
Min length2

Characters and Unicode

Total characters714
Distinct characters130
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

Unique95 ?
Unique (%)42.0%

Sample

1st row노정숙
2nd row강행복
3rd row김상연
4th row정재식
5th row김원
ValueCountFrequency (%)
김상연 8
 
3.5%
임병중 8
 
3.5%
서정봉 8
 
3.5%
박구환 8
 
3.5%
오이량 8
 
3.5%
김원 8
 
3.5%
정재형 8
 
3.5%
김영만 7
 
3.1%
노정숙 7
 
3.1%
김익모 7
 
3.1%
Other values (110) 150
66.1%
2023-12-13T08:15:20.857276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 59
 
8.3%
정 41
 
5.7%
29
 
4.1%
재 22
 
3.1%
영 22
 
3.1%
박 20
 
2.8%
이 19
 
2.7%
상 19
 
2.7%
숙 17
 
2.4%
강 15
 
2.1%
Other values (120) 451
63.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 678
95.0%
Space Separator 29
 
4.1%
Close Punctuation 5
 
0.7%
Other Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 59
 
8.7%
정 41
 
6.0%
재 22
 
3.2%
영 22
 
3.2%
박 20
 
2.9%
이 19
 
2.8%
상 19
 
2.8%
숙 17
 
2.5%
강 15
 
2.2%
임 14
 
2.1%
Other values (116) 430
63.4%
Space Separator
ValueCountFrequency (%)
29
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 678
95.0%
Common 36
 
5.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 59
 
8.7%
정 41
 
6.0%
재 22
 
3.2%
영 22
 
3.2%
박 20
 
2.9%
이 19
 
2.8%
상 19
 
2.8%
숙 17
 
2.5%
강 15
 
2.2%
임 14
 
2.1%
Other values (116) 430
63.4%
Common
ValueCountFrequency (%)
29
80.6%
) 5
 
13.9%
, 1
 
2.8%
( 1
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 678
95.0%
ASCII 36
 
5.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 59
 
8.7%
정 41
 
6.0%
재 22
 
3.2%
영 22
 
3.2%
박 20
 
2.9%
이 19
 
2.8%
상 19
 
2.8%
숙 17
 
2.5%
강 15
 
2.2%
임 14
 
2.1%
Other values (116) 430
63.4%
ASCII
ValueCountFrequency (%)
29
80.6%
) 5
 
13.9%
, 1
 
2.8%
( 1
 
2.8%

부문별
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
판화
100 
서양화
76 
한국화
17 
기타
 
8
회화
 
8
Other values (5)
17 

Length

Max length3
Median length2
Mean length2.4336283
Min length2

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
판화 100
44.2%
서양화 76
33.6%
한국화 17
 
7.5%
기타 8
 
3.5%
회화 8
 
3.5%
조각 7
 
3.1%
판화 4
 
1.8%
서예 3
 
1.3%
공예 2
 
0.9%
도자기 1
 
0.4%

Length

2023-12-13T08:15:20.977376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:15:21.077438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
판화 104
46.0%
서양화 76
33.6%
한국화 17
 
7.5%
기타 8
 
3.5%
회화 8
 
3.5%
조각 7
 
3.1%
서예 3
 
1.3%
공예 2
 
0.9%
도자기 1
 
0.4%

실제크기(가로세로)
Text

Distinct183
Distinct (%)81.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-13T08:15:21.330275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length9.8362832
Min length5

Characters and Unicode

Total characters2223
Distinct characters17
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

Unique159 ?
Unique (%)70.4%

Sample

1st row70×86,41×57
2nd row64×81,48×44
3rd row61×99,37×75
4th row92×75,67×51
5th row92×123,62×93
ValueCountFrequency (%)
86×67,62×43 7
 
3.0%
64×81,48×44 5
 
2.2%
61×99,37×75 4
 
1.7%
67×88,42×63 4
 
1.7%
64×77,41×54 4
 
1.7%
79×73,55×49 3
 
1.3%
× 3
 
1.3%
75×94,50×70 3
 
1.3%
130×162 3
 
1.3%
65×91 3
 
1.3%
Other values (176) 193
83.2%
2023-12-13T08:15:21.730169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
× 348
15.7%
1 335
15.1%
6 192
8.6%
0 160
7.2%
5 157
7.1%
7 154
6.9%
9 147
6.6%
4 142
6.4%
2 140
6.3%
3 138
 
6.2%
Other values (7) 310
13.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1698
76.4%
Math Symbol 348
 
15.7%
Other Punctuation 163
 
7.3%
Lowercase Letter 8
 
0.4%
Space Separator 6
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 335
19.7%
6 192
11.3%
0 160
9.4%
5 157
9.2%
7 154
9.1%
9 147
8.7%
4 142
8.4%
2 140
8.2%
3 138
8.1%
8 133
 
7.8%
Other Punctuation
ValueCountFrequency (%)
, 130
79.8%
. 23
 
14.1%
* 10
 
6.1%
Lowercase Letter
ValueCountFrequency (%)
x 7
87.5%
p 1
 
12.5%
Math Symbol
ValueCountFrequency (%)
× 348
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2215
99.6%
Latin 8
 
0.4%

Most frequent character per script

Common
ValueCountFrequency (%)
× 348
15.7%
1 335
15.1%
6 192
8.7%
0 160
7.2%
5 157
7.1%
7 154
7.0%
9 147
6.6%
4 142
6.4%
2 140
6.3%
3 138
 
6.2%
Other values (5) 302
13.6%
Latin
ValueCountFrequency (%)
x 7
87.5%
p 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1875
84.3%
None 348
 
15.7%

Most frequent character per block

None
ValueCountFrequency (%)
× 348
100.0%
ASCII
ValueCountFrequency (%)
1 335
17.9%
6 192
10.2%
0 160
8.5%
5 157
8.4%
7 154
8.2%
9 147
7.8%
4 142
7.6%
2 140
7.5%
3 138
7.4%
8 133
 
7.1%
Other values (6) 177
9.4%

제작 연도
Categorical

HIGH CORRELATION 

Distinct40
Distinct (%)17.7%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2004
49 
2003
29 
1995
13 
2001
 
11
2002
 
11
Other values (35)
113 

Length

Max length14
Median length4
Mean length4.1017699
Min length4

Unique

Unique12 ?
Unique (%)5.3%

Sample

1st row1993
2nd row1995
3rd row2003
4th row2004
5th row2001

Common Values

ValueCountFrequency (%)
2004 49
21.7%
2003 29
 
12.8%
1995 13
 
5.8%
2001 11
 
4.9%
2002 11
 
4.9%
1998 9
 
4.0%
2000 9
 
4.0%
2013 8
 
3.5%
2011 7
 
3.1%
1996 7
 
3.1%
Other values (30) 73
32.3%

Length

2023-12-13T08:15:21.861022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2004 49
21.7%
2003 29
 
12.8%
1995 13
 
5.8%
2001 11
 
4.9%
2002 11
 
4.9%
1998 9
 
4.0%
2000 9
 
4.0%
2013 8
 
3.5%
1992 7
 
3.1%
2011 7
 
3.1%
Other values (30) 73
32.3%

Interactions

2023-12-13T08:15:18.735517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:15:21.934942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번소관부문별제작 연도
연번1.0000.9960.6680.666
소관0.9961.0000.8700.856
부문별0.6680.8701.0000.850
제작 연도0.6660.8560.8501.000
2023-12-13T08:15:22.044158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
제작 연도부문별소관
제작 연도1.0000.4250.657
부문별0.4251.0000.691
소관0.6570.6911.000
2023-12-13T08:15:22.149763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번소관부문별제작 연도
연번1.0000.9260.2600.253
소관0.9261.0000.6910.657
부문별0.2600.6911.0000.425
제작 연도0.2530.6570.4251.000

Missing values

2023-12-13T08:15:18.860401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:15:19.016213image/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

연번소관작품명작가부문별실제크기(가로세로)제작 연도
01회계과形-Ⅲ노정숙판화70×86,41×571993
12회계과95-75강행복판화64×81,48×441995
23회계과August ①김상연판화61×99,37×752003
34회계과Circle Ⅱ정재식판화92×75,67×512004
45회계과GIFT BOX김원판화92×123,62×932001
56회계과GIFT BOX 0307김원판화92×123,62×932003
67회계과GIFT BOX 0308김원판화92×123,62×942003
78회계과GIFT BOX 0402김원판화67×88,42×632004
89회계과GIFT BOX 4022김원판화86×67,62×432004
910회계과GIFT BOX 4023김원판화67×88,42×632004
연번소관작품명작가부문별실제크기(가로세로)제작 연도
216217미술관춘색김준호서양화61×731995
217218미술관파꽃은 바람에 날리고최향기타73×912010
218219미술관푸른 달빛정상섭회화91*65.52016
219220미술관하얀장미한희원회화34*65.52017
220221미술관함께해요-더나은미래정윤태조각240×66×2202017
221222미술관해바라기주재현서양화130×1932013
222223미술관행복나무명현철회화72.7*116.82018
223224미술관행진이형모서양화72×912014
224225미술관홍도의 노을윤재우서양화112×145.51983
225226미술관홍매전지현한국화70×1102014