Overview

Dataset statistics

Number of variables8
Number of observations107
Missing cells105
Missing cells (%)12.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.0 KiB
Average record size in memory67.2 B

Variable types

Numeric2
Categorical4
Text2

Dataset

Description광주광역시 문화예술회관 공연시설에 관한 데이터로 대극장, 소극장의 무대시설물, 무대기계시설물, 무대음향장비 등의 보유 항목을 제공합니다.
Author광주광역시
URLhttps://www.data.go.kr/data/3036282/fileData.do

Alerts

비고 has constant value ""Constant
데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 장소 and 2 other fieldsHigh correlation
장소 is highly overall correlated with 연번High correlation
구분 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
수량단위 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
비고 has 105 (98.1%) missing valuesMissing
연번 has unique valuesUnique
수량 has 14 (13.1%) zerosZeros

Reproduction

Analysis started2023-12-12 12:00:52.032562
Analysis finished2023-12-12 12:00:53.191910
Duration1.16 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct107
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54
Minimum1
Maximum107
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T21:00:53.279409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.3
Q127.5
median54
Q380.5
95-th percentile101.7
Maximum107
Range106
Interquartile range (IQR)53

Descriptive statistics

Standard deviation31.032241
Coefficient of variation (CV)0.57467114
Kurtosis-1.2
Mean54
Median Absolute Deviation (MAD)27
Skewness0
Sum5778
Variance963
MonotonicityStrictly increasing
2023-12-12T21:00:53.423545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
69 1
 
0.9%
80 1
 
0.9%
79 1
 
0.9%
78 1
 
0.9%
77 1
 
0.9%
76 1
 
0.9%
75 1
 
0.9%
74 1
 
0.9%
73 1
 
0.9%
Other values (97) 97
90.7%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
107 1
0.9%
106 1
0.9%
105 1
0.9%
104 1
0.9%
103 1
0.9%
102 1
0.9%
101 1
0.9%
100 1
0.9%
99 1
0.9%
98 1
0.9%

장소
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size988.0 B
대극장
58 
소극장
49 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대극장 58
54.2%
소극장 49
45.8%

Length

2023-12-12T21:00:53.557323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:00:53.661181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대극장 58
54.2%
소극장 49
45.8%

구분
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size988.0 B
상부 무대기계시설물
44 
음향조정실
37 
무대 시설물
16 
하부 무대기계시설물
10 

Length

Max length10
Median length10
Mean length7.6728972
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row무대 시설물
2nd row무대 시설물
3rd row무대 시설물
4th row무대 시설물
5th row무대 시설물

Common Values

ValueCountFrequency (%)
상부 무대기계시설물 44
41.1%
음향조정실 37
34.6%
무대 시설물 16
 
15.0%
하부 무대기계시설물 10
 
9.3%

Length

2023-12-12T21:00:53.771571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:00:53.874129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
무대기계시설물 54
30.5%
상부 44
24.9%
음향조정실 37
20.9%
무대 16
 
9.0%
시설물 16
 
9.0%
하부 10
 
5.6%

품목
Text

Distinct63
Distinct (%)58.9%
Missing0
Missing (%)0.0%
Memory size988.0 B
2023-12-12T21:00:54.103483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length28
Mean length8.2336449
Min length2

Characters and Unicode

Total characters881
Distinct characters156
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)17.8%

Sample

1st row피아노(스타인웨이)
2nd row피아노(야마하)
3rd row전자오르간(ALLEN)
4th row보면대
5th row고무매트
ValueCountFrequency (%)
무대 6
 
3.8%
d 4
 
2.5%
sound 4
 
2.5%
mic 4
 
2.5%
침하 2
 
1.3%
승강 2
 
1.3%
q 2
 
1.3%
e 2
 
1.3%
국부조명바톤 2
 
1.3%
조명푸리세늄 2
 
1.3%
Other values (78) 129
81.1%
2023-12-12T21:00:54.527892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
53
 
6.0%
M 29
 
3.3%
E 27
 
3.1%
O 25
 
2.8%
D 24
 
2.7%
S 24
 
2.7%
A 21
 
2.4%
( 21
 
2.4%
) 21
 
2.4%
N 20
 
2.3%
Other values (146) 616
69.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 410
46.5%
Uppercase Letter 291
33.0%
Space Separator 53
 
6.0%
Lowercase Letter 34
 
3.9%
Decimal Number 31
 
3.5%
Open Punctuation 21
 
2.4%
Close Punctuation 21
 
2.4%
Other Punctuation 19
 
2.2%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
트 15
 
3.7%
조 14
 
3.4%
전 13
 
3.2%
톤 12
 
2.9%
대 12
 
2.9%
명 12
 
2.9%
바 12
 
2.9%
무 12
 
2.9%
이 11
 
2.7%
리 10
 
2.4%
Other values (93) 287
70.0%
Uppercase Letter
ValueCountFrequency (%)
M 29
10.0%
E 27
9.3%
O 25
 
8.6%
D 24
 
8.2%
S 24
 
8.2%
A 21
 
7.2%
N 20
 
6.9%
I 20
 
6.9%
C 19
 
6.5%
R 17
 
5.8%
Other values (12) 65
22.3%
Lowercase Letter
ValueCountFrequency (%)
e 7
20.6%
o 5
14.7%
n 4
11.8%
r 3
8.8%
i 2
 
5.9%
s 2
 
5.9%
u 2
 
5.9%
b 1
 
2.9%
m 1
 
2.9%
p 1
 
2.9%
Other values (6) 6
17.6%
Decimal Number
ValueCountFrequency (%)
0 12
38.7%
1 6
19.4%
5 4
 
12.9%
4 4
 
12.9%
2 2
 
6.5%
3 2
 
6.5%
8 1
 
3.2%
Other Punctuation
ValueCountFrequency (%)
* 7
36.8%
. 6
31.6%
, 5
26.3%
/ 1
 
5.3%
Space Separator
ValueCountFrequency (%)
53
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 410
46.5%
Latin 325
36.9%
Common 146
 
16.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
트 15
 
3.7%
조 14
 
3.4%
전 13
 
3.2%
톤 12
 
2.9%
대 12
 
2.9%
명 12
 
2.9%
바 12
 
2.9%
무 12
 
2.9%
이 11
 
2.7%
리 10
 
2.4%
Other values (93) 287
70.0%
Latin
ValueCountFrequency (%)
M 29
 
8.9%
E 27
 
8.3%
O 25
 
7.7%
D 24
 
7.4%
S 24
 
7.4%
A 21
 
6.5%
N 20
 
6.2%
I 20
 
6.2%
C 19
 
5.8%
R 17
 
5.2%
Other values (28) 99
30.5%
Common
ValueCountFrequency (%)
53
36.3%
( 21
 
14.4%
) 21
 
14.4%
0 12
 
8.2%
* 7
 
4.8%
. 6
 
4.1%
1 6
 
4.1%
, 5
 
3.4%
5 4
 
2.7%
4 4
 
2.7%
Other values (5) 7
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 471
53.5%
Hangul 410
46.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
53
 
11.3%
M 29
 
6.2%
E 27
 
5.7%
O 25
 
5.3%
D 24
 
5.1%
S 24
 
5.1%
A 21
 
4.5%
( 21
 
4.5%
) 21
 
4.5%
N 20
 
4.2%
Other values (43) 206
43.7%
Hangul
ValueCountFrequency (%)
트 15
 
3.7%
조 14
 
3.4%
전 13
 
3.2%
톤 12
 
2.9%
대 12
 
2.9%
명 12
 
2.9%
바 12
 
2.9%
무 12
 
2.9%
이 11
 
2.7%
리 10
 
2.4%
Other values (93) 287
70.0%

수량
Real number (ℝ)

ZEROS 

Distinct23
Distinct (%)21.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.897196
Minimum0
Maximum360
Zeros14
Zeros (%)13.1%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T21:00:54.652935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q34
95-th percentile67
Maximum360
Range360
Interquartile range (IQR)3

Descriptive statistics

Standard deviation45.638434
Coefficient of variation (CV)3.284003
Kurtosis37.52845
Mean13.897196
Median Absolute Deviation (MAD)1
Skewness5.7463306
Sum1487
Variance2082.8667
MonotonicityNot monotonic
2023-12-12T21:00:54.798860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
1 37
34.6%
2 19
17.8%
0 14
 
13.1%
3 6
 
5.6%
4 6
 
5.6%
8 3
 
2.8%
6 3
 
2.8%
10 2
 
1.9%
60 2
 
1.9%
5 2
 
1.9%
Other values (13) 13
 
12.1%
ValueCountFrequency (%)
0 14
 
13.1%
1 37
34.6%
2 19
17.8%
3 6
 
5.6%
4 6
 
5.6%
5 2
 
1.9%
6 3
 
2.8%
8 3
 
2.8%
10 2
 
1.9%
12 1
 
0.9%
ValueCountFrequency (%)
360 1
0.9%
250 1
0.9%
111 1
0.9%
100 1
0.9%
85 1
0.9%
70 1
0.9%
60 2
1.9%
52 1
0.9%
40 1
0.9%
29 1
0.9%

수량단위
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size988.0 B
set
54 
대
35 
개
13 
식
 
5

Length

Max length3
Median length3
Mean length2.0093458
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
set 54
50.5%
대 35
32.7%
개 13
 
12.1%
식 5
 
4.7%

Length

2023-12-12T21:00:54.934719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:00:55.057934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
set 54
50.5%
대 35
32.7%
개 13
 
12.1%
식 5
 
4.7%

비고
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)50.0%
Missing105
Missing (%)98.1%
Memory size988.0 B
2023-12-12T21:00:55.197114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters10
Distinct characters5
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

Unique0 ?
Unique (%)0.0%

Sample

1st row대극장공유
2nd row대극장공유
ValueCountFrequency (%)
대극장공유 2
100.0%
2023-12-12T21:00:55.535637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 2
20.0%
극 2
20.0%
장 2
20.0%
공 2
20.0%
유 2
20.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 2
20.0%
극 2
20.0%
장 2
20.0%
공 2
20.0%
유 2
20.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 2
20.0%
극 2
20.0%
장 2
20.0%
공 2
20.0%
유 2
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 2
20.0%
극 2
20.0%
장 2
20.0%
공 2
20.0%
유 2
20.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size988.0 B
2022-12-05
107 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-12-05
2nd row2022-12-05
3rd row2022-12-05
4th row2022-12-05
5th row2022-12-05

Common Values

ValueCountFrequency (%)
2022-12-05 107
100.0%

Length

2023-12-12T21:00:55.680990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:00:55.780495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-12-05 107
100.0%

Interactions

2023-12-12T21:00:52.689007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:00:52.439800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:00:52.806166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:00:52.561505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:00:55.839945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번장소구분품목수량수량단위
연번1.0000.9970.8600.0000.4520.790
장소0.9971.0000.0000.0000.0000.000
구분0.8600.0001.0001.0000.4340.968
품목0.0000.0001.0001.0000.0000.991
수량0.4520.0000.4340.0001.0000.509
수량단위0.7900.0000.9680.9910.5091.000
2023-12-12T21:00:55.966652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분수량단위장소
구분1.0000.7570.000
수량단위0.7571.0000.000
장소0.0000.0001.000
2023-12-12T21:00:56.097814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번수량장소구분수량단위
연번1.000-0.2370.9120.6910.591
수량-0.2371.0000.0000.2900.348
장소0.9120.0001.0000.0000.000
구분0.6910.2900.0001.0000.757
수량단위0.5910.3480.0000.7571.000

Missing values

2023-12-12T21:00:52.976947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:00:53.139433image/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

연번장소구분품목수량수량단위비고데이터기준일자
01대극장무대 시설물피아노(스타인웨이)1개<NA>2022-12-05
12대극장무대 시설물피아노(야마하)1개<NA>2022-12-05
23대극장무대 시설물전자오르간(ALLEN)1개<NA>2022-12-05
34대극장무대 시설물보면대85개<NA>2022-12-05
45대극장무대 시설물고무매트29개<NA>2022-12-05
56대극장무대 시설물의자100개<NA>2022-12-05
67대극장무대 시설물덧마루(사각)360개<NA>2022-12-05
78대극장무대 시설물받침대(150*300*450)250개<NA>2022-12-05
89대극장상부 무대기계시설물방화막1set<NA>2022-12-05
910대극장상부 무대기계시설물현수막1set<NA>2022-12-05
연번장소구분품목수량수량단위비고데이터기준일자
9798소극장음향조정실무선마이크(젠하이저, 슈어)20대<NA>2022-12-05
9899소극장음향조정실카세트 TASCAM1대<NA>2022-12-05
99100소극장음향조정실DI BOX2대<NA>2022-12-05
100101소극장음향조정실PROSCENIUM(MEYER SOUND)4대<NA>2022-12-05
101102소극장음향조정실SIDE MEYER SOUND4대<NA>2022-12-05
102103소극장음향조정실STAGE MONITOR4대<NA>2022-12-05
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