Overview

Dataset statistics

Number of variables7
Number of observations74
Missing cells74
Missing cells (%)14.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.4 KiB
Average record size in memory60.8 B

Variable types

Numeric3
Text2
Categorical1
DateTime1

Dataset

Description광주광역시 동구 기계설비성능점검대상건축물 현황 데이터 입니다.데이터는 건물명, 주소, 연면적, 세대수 등으로 구성되어있습니다.건물이 공동주택일 경우 세대수로, 공동주택이 아닌경우 연면적 데이터를 제공하고 있습니다.
Author광주광역시 동구
URLhttps://www.data.go.kr/data/15125535/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
순번 is highly overall correlated with 연면적_제곱미터 and 2 other fieldsHigh correlation
연면적_제곱미터 is highly overall correlated with 순번High correlation
세대수 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
비고 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
연면적_제곱미터 has 19 (25.7%) missing valuesMissing
세대수 has 55 (74.3%) missing valuesMissing
순번 has unique valuesUnique
건물명 has unique valuesUnique

Reproduction

Analysis started2023-12-16 16:02:14.232740
Analysis finished2023-12-16 16:02:19.638993
Duration5.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct74
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.5
Minimum1
Maximum74
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size798.0 B
2023-12-16T16:02:19.838640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.65
Q119.25
median37.5
Q355.75
95-th percentile70.35
Maximum74
Range73
Interquartile range (IQR)36.5

Descriptive statistics

Standard deviation21.505813
Coefficient of variation (CV)0.57348835
Kurtosis-1.2
Mean37.5
Median Absolute Deviation (MAD)18.5
Skewness0
Sum2775
Variance462.5
MonotonicityStrictly increasing
2023-12-16T16:02:20.635870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.4%
57 1
 
1.4%
55 1
 
1.4%
54 1
 
1.4%
53 1
 
1.4%
52 1
 
1.4%
51 1
 
1.4%
50 1
 
1.4%
49 1
 
1.4%
48 1
 
1.4%
Other values (64) 64
86.5%
ValueCountFrequency (%)
1 1
1.4%
2 1
1.4%
3 1
1.4%
4 1
1.4%
5 1
1.4%
6 1
1.4%
7 1
1.4%
8 1
1.4%
9 1
1.4%
10 1
1.4%
ValueCountFrequency (%)
74 1
1.4%
73 1
1.4%
72 1
1.4%
71 1
1.4%
70 1
1.4%
69 1
1.4%
68 1
1.4%
67 1
1.4%
66 1
1.4%
65 1
1.4%

건물명
Text

UNIQUE 

Distinct74
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size724.0 B
2023-12-16T16:02:21.533518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length13
Mean length7.6891892
Min length3

Characters and Unicode

Total characters569
Distinct characters189
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)100.0%

Sample

1st row조선대학교
2nd row국립아시아문화전당
3rd row전남대학교병원
4th row롯데백화점
5th row조선대학교병원
ValueCountFrequency (%)
롯데백화점 2
 
2.0%
무등산 2
 
2.0%
금남로 2
 
2.0%
조선대학교 1
 
1.0%
광주 1
 
1.0%
갤러리존 1
 
1.0%
사옥 1
 
1.0%
광주지역사업부 1
 
1.0%
주)아모레퍼시픽 1
 
1.0%
하나은행 1
 
1.0%
Other values (89) 89
87.3%
2023-12-16T16:02:23.170059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
28
 
4.9%
주 19
 
3.3%
광 13
 
2.3%
아 12
 
2.1%
크 11
 
1.9%
파 11
 
1.9%
남 11
 
1.9%
산 11
 
1.9%
등 10
 
1.8%
교 10
 
1.8%
Other values (179) 433
76.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 501
88.0%
Space Separator 28
 
4.9%
Uppercase Letter 20
 
3.5%
Decimal Number 12
 
2.1%
Open Punctuation 2
 
0.4%
Close Punctuation 2
 
0.4%
Other Punctuation 2
 
0.4%
Dash Punctuation 1
 
0.2%
Other Symbol 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 19
 
3.8%
광 13
 
2.6%
아 12
 
2.4%
크 11
 
2.2%
파 11
 
2.2%
남 11
 
2.2%
산 11
 
2.2%
등 10
 
2.0%
교 10
 
2.0%
학 9
 
1.8%
Other values (156) 384
76.6%
Uppercase Letter
ValueCountFrequency (%)
S 5
25.0%
C 4
20.0%
K 2
 
10.0%
I 2
 
10.0%
T 1
 
5.0%
X 1
 
5.0%
E 1
 
5.0%
P 1
 
5.0%
L 1
 
5.0%
A 1
 
5.0%
Decimal Number
ValueCountFrequency (%)
1 4
33.3%
2 4
33.3%
4 2
16.7%
7 1
 
8.3%
5 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
· 1
50.0%
Space Separator
ValueCountFrequency (%)
28
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 502
88.2%
Common 47
 
8.3%
Latin 20
 
3.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 19
 
3.8%
광 13
 
2.6%
아 12
 
2.4%
크 11
 
2.2%
파 11
 
2.2%
남 11
 
2.2%
산 11
 
2.2%
등 10
 
2.0%
교 10
 
2.0%
학 9
 
1.8%
Other values (157) 385
76.7%
Common
ValueCountFrequency (%)
28
59.6%
1 4
 
8.5%
2 4
 
8.5%
4 2
 
4.3%
( 2
 
4.3%
) 2
 
4.3%
7 1
 
2.1%
- 1
 
2.1%
, 1
 
2.1%
5 1
 
2.1%
Latin
ValueCountFrequency (%)
S 5
25.0%
C 4
20.0%
K 2
 
10.0%
I 2
 
10.0%
T 1
 
5.0%
X 1
 
5.0%
E 1
 
5.0%
P 1
 
5.0%
L 1
 
5.0%
A 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 501
88.0%
ASCII 66
 
11.6%
None 2
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
28
42.4%
S 5
 
7.6%
C 4
 
6.1%
1 4
 
6.1%
2 4
 
6.1%
4 2
 
3.0%
K 2
 
3.0%
I 2
 
3.0%
( 2
 
3.0%
) 2
 
3.0%
Other values (11) 11
 
16.7%
Hangul
ValueCountFrequency (%)
주 19
 
3.8%
광 13
 
2.6%
아 12
 
2.4%
크 11
 
2.2%
파 11
 
2.2%
남 11
 
2.2%
산 11
 
2.2%
등 10
 
2.0%
교 10
 
2.0%
학 9
 
1.8%
Other values (156) 384
76.6%
None
ValueCountFrequency (%)
㈜ 1
50.0%
· 1
50.0%

주소
Text

Distinct73
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size724.0 B
2023-12-16T16:02:23.877233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length7.7972973
Min length4

Characters and Unicode

Total characters577
Distinct characters41
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

Unique72 ?
Unique (%)97.3%

Sample

1st row서석동 375
2nd row광산동 113
3rd row학동 8
4th row대인동 7-1
5th row학동 539
ValueCountFrequency (%)
계림동 10
 
6.8%
학동 5
 
3.4%
금남로5가 5
 
3.4%
동명동 5
 
3.4%
대인동 5
 
3.4%
용산동 5
 
3.4%
서석동 5
 
3.4%
소태동 4
 
2.7%
수기동 3
 
2.0%
지산동 3
 
2.0%
Other values (88) 98
66.2%
2023-12-16T16:02:25.102656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
74
 
12.8%
동 64
 
11.1%
1 54
 
9.4%
2 39
 
6.8%
- 34
 
5.9%
3 29
 
5.0%
5 25
 
4.3%
0 21
 
3.6%
9 18
 
3.1%
남 17
 
2.9%
Other values (31) 202
35.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242
41.9%
Other Letter 227
39.3%
Space Separator 74
 
12.8%
Dash Punctuation 34
 
5.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 64
28.2%
남 17
 
7.5%
로 16
 
7.0%
가 14
 
6.2%
금 13
 
5.7%
산 11
 
4.8%
림 11
 
4.8%
계 10
 
4.4%
석 5
 
2.2%
서 5
 
2.2%
Other values (19) 61
26.9%
Decimal Number
ValueCountFrequency (%)
1 54
22.3%
2 39
16.1%
3 29
12.0%
5 25
10.3%
0 21
 
8.7%
9 18
 
7.4%
6 17
 
7.0%
4 15
 
6.2%
8 14
 
5.8%
7 10
 
4.1%
Space Separator
ValueCountFrequency (%)
74
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 350
60.7%
Hangul 227
39.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 64
28.2%
남 17
 
7.5%
로 16
 
7.0%
가 14
 
6.2%
금 13
 
5.7%
산 11
 
4.8%
림 11
 
4.8%
계 10
 
4.4%
석 5
 
2.2%
서 5
 
2.2%
Other values (19) 61
26.9%
Common
ValueCountFrequency (%)
74
21.1%
1 54
15.4%
2 39
11.1%
- 34
9.7%
3 29
 
8.3%
5 25
 
7.1%
0 21
 
6.0%
9 18
 
5.1%
6 17
 
4.9%
4 15
 
4.3%
Other values (2) 24
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 350
60.7%
Hangul 227
39.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
74
21.1%
1 54
15.4%
2 39
11.1%
- 34
9.7%
3 29
 
8.3%
5 25
 
7.1%
0 21
 
6.0%
9 18
 
5.1%
6 17
 
4.9%
4 15
 
4.3%
Other values (2) 24
 
6.9%
Hangul
ValueCountFrequency (%)
동 64
28.2%
남 17
 
7.5%
로 16
 
7.0%
가 14
 
6.2%
금 13
 
5.7%
산 11
 
4.8%
림 11
 
4.8%
계 10
 
4.4%
석 5
 
2.2%
서 5
 
2.2%
Other values (19) 61
26.9%

연면적_제곱미터
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct55
Distinct (%)100.0%
Missing19
Missing (%)25.7%
Infinite0
Infinite (%)0.0%
Mean222258.77
Minimum10200
Maximum10148363
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size798.0 B
2023-12-16T16:02:25.877920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10200
5-th percentile10578.72
Q112603.925
median18756.623
Q330338.198
95-th percentile118614.71
Maximum10148363
Range10138163
Interquartile range (IQR)17734.273

Descriptive statistics

Standard deviation1365994.4
Coefficient of variation (CV)6.145964
Kurtosis54.529383
Mean222258.77
Median Absolute Deviation (MAD)7765.5825
Skewness7.371137
Sum12224233
Variance1.8659408 × 1012
MonotonicityNot monotonic
2023-12-16T16:02:26.862910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
131868.27 1
 
1.4%
17381.7 1
 
1.4%
17239.605 1
 
1.4%
16879.0 1
 
1.4%
16575.15 1
 
1.4%
16931.9 1
 
1.4%
14957.46 1
 
1.4%
14937.03 1
 
1.4%
13309.01 1
 
1.4%
13251.36 1
 
1.4%
Other values (45) 45
60.8%
(Missing) 19
25.7%
ValueCountFrequency (%)
10200.0 1
1.4%
10378.15 1
1.4%
10506.83 1
1.4%
10609.53 1
1.4%
10651.17 1
1.4%
10797.02 1
1.4%
10797.47 1
1.4%
10891.76 1
1.4%
10991.04 1
1.4%
11249.92 1
1.4%
ValueCountFrequency (%)
10148363.0 1
1.4%
647593.25 1
1.4%
131868.27 1
1.4%
112934.62 1
1.4%
85264.46 1
1.4%
60559.82 1
1.4%
49632.54 1
1.4%
49209.36 1
1.4%
46990.35 1
1.4%
45603.702 1
1.4%

세대수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct19
Distinct (%)100.0%
Missing55
Missing (%)74.3%
Infinite0
Infinite (%)0.0%
Mean915.52632
Minimum528
Maximum2336
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size798.0 B
2023-12-16T16:02:27.426142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum528
5-th percentile542.4
Q1651
median784
Q3955
95-th percentile1777.1
Maximum2336
Range1808
Interquartile range (IQR)304

Descriptive statistics

Standard deviation457.57991
Coefficient of variation (CV)0.49979984
Kurtosis4.6174275
Mean915.52632
Median Absolute Deviation (MAD)168
Skewness2.0998979
Sum17395
Variance209379.37
MonotonicityStrictly decreasing
2023-12-16T16:02:27.997502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
1715 1
 
1.4%
528 1
 
1.4%
544 1
 
1.4%
570 1
 
1.4%
580 1
 
1.4%
648 1
 
1.4%
654 1
 
1.4%
658 1
 
1.4%
690 1
 
1.4%
2336 1
 
1.4%
Other values (9) 9
 
12.2%
(Missing) 55
74.3%
ValueCountFrequency (%)
528 1
1.4%
544 1
1.4%
570 1
1.4%
580 1
1.4%
648 1
1.4%
654 1
1.4%
658 1
1.4%
690 1
1.4%
772 1
1.4%
784 1
1.4%
ValueCountFrequency (%)
2336 1
1.4%
1715 1
1.4%
1410 1
1.4%
1074 1
1.4%
958 1
1.4%
952 1
1.4%
908 1
1.4%
820 1
1.4%
794 1
1.4%
784 1
1.4%

비고
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size724.0 B
<NA>
55 
공동주택
19 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 55
74.3%
공동주택 19
 
25.7%

Length

2023-12-16T16:02:28.647969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T16:02:29.318019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 55
74.3%
공동주택 19
 
25.7%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size724.0 B
Minimum2023-12-11 00:00:00
Maximum2023-12-11 00:00:00
2023-12-16T16:02:29.815670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T16:02:30.333043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-16T16:02:17.604696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T16:02:15.351451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T16:02:16.466733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T16:02:17.954666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T16:02:15.678141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T16:02:16.879527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T16:02:18.230345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T16:02:15.960759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T16:02:17.327823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-16T16:02:30.774990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번건물명주소연면적_제곱미터세대수
순번1.0001.0000.9290.2081.000
건물명1.0001.0001.0001.0001.000
주소0.9291.0001.0001.0001.000
연면적_제곱미터0.2081.0001.0001.000NaN
세대수1.0001.0001.000NaN1.000
2023-12-16T16:02:31.313958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번연면적_제곱미터세대수비고
순번1.000-0.893-1.0001.000
연면적_제곱미터-0.8931.000NaN0.000
세대수-1.000NaN1.0001.000
비고1.0000.0001.0001.000

Missing values

2023-12-16T16:02:18.734532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-16T16:02:19.226217image/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.
2023-12-16T16:02:19.501287image/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

순번건물명주소연면적_제곱미터세대수비고데이터기준일자
01조선대학교서석동 375647593.25<NA><NA>2023-12-11
12국립아시아문화전당광산동 113131868.27<NA><NA>2023-12-11
23전남대학교병원학동 8112934.62<NA><NA>2023-12-11
34롯데백화점대인동 7-185264.46<NA><NA>2023-12-11
45조선대학교병원학동 53960559.82<NA><NA>2023-12-11
56조선이공대학교서석동 29049632.54<NA><NA>2023-12-11
67(주)케이티건물 주1동서석동 31-949209.36<NA><NA>2023-12-11
78광주은행 본점대인동 7-1246990.35<NA><NA>2023-12-11
89유탑유블레스 원시티수기동 68-145603.702<NA><NA>2023-12-11
910용산차량기지용산동 1-141158.27<NA><NA>2023-12-11
순번건물명주소연면적_제곱미터세대수비고데이터기준일자
6465월남호반베르디움 2차월남동 638<NA>784공동주택2023-12-11
6566무등산골드클래스2차용산동 284<NA>772공동주택2023-12-11
6667무등산골드클래스소태동 1103<NA>690공동주택2023-12-11
6768계림두산위브계림동 52<NA>658공동주택2023-12-11
6869월남호반베르디움1차월남동 620<NA>654공동주택2023-12-11
6970푸른길 두산위브계림동 1815<NA>648공동주택2023-12-11
7071모아미래도아파트소태동 501<NA>580공동주택2023-12-11
7172용산지구 모아엘가 에듀파크용산동 663<NA>570공동주택2023-12-11
7273내남지구2차진아리채내남동 904<NA>544공동주택2023-12-11
7374광주용산엘에이치1단지용산동 669<NA>528공동주택2023-12-11