Overview

Dataset statistics

Number of variables5
Number of observations71
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 KiB
Average record size in memory43.9 B

Variable types

Numeric2
Text2
Categorical1

Dataset

Description부산광역시_수영구_다중이용시설실내공기질관리대상현황_20230320
Author부산광역시 수영구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15026343

Alerts

번호 is highly overall correlated with 시설군 High correlation
시설군 is highly overall correlated with 번호High correlation
번호 has unique valuesUnique
업소명(건물명) has unique valuesUnique
연면적 has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:36:47.706297
Analysis finished2023-12-10 16:36:48.986754
Duration1.28 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct71
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36
Minimum1
Maximum71
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size771.0 B
2023-12-11T01:36:49.123672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.5
Q118.5
median36
Q353.5
95-th percentile67.5
Maximum71
Range70
Interquartile range (IQR)35

Descriptive statistics

Standard deviation20.639767
Coefficient of variation (CV)0.57332687
Kurtosis-1.2
Mean36
Median Absolute Deviation (MAD)18
Skewness0
Sum2556
Variance426
MonotonicityStrictly increasing
2023-12-11T01:36:49.259435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.4%
2 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%
47 1
 
1.4%
46 1
 
1.4%
Other values (61) 61
85.9%
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 (%)
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%
64 1
1.4%
63 1
1.4%
62 1
1.4%

업소명(건물명)
Text

UNIQUE 

Distinct71
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size700.0 B
2023-12-11T01:36:49.552170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length8.2816901
Min length3

Characters and Unicode

Total characters588
Distinct characters166
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique71 ?
Unique (%)100.0%

Sample

1st row남천역
2nd row금련산역
3rd row광안역
4th row수영역(2호선)
5th row민락역
ValueCountFrequency (%)
pc 3
 
3.1%
좋은강안병원 3
 
3.1%
메가마트 2
 
2.1%
코스트코부산점 2
 
2.1%
광안자모병원 2
 
2.1%
의료법인 2
 
2.1%
실내주차장 2
 
2.1%
랑체pc방 1
 
1.0%
온아이어린이집 1
 
1.0%
도산어린이집 1
 
1.0%
Other values (78) 78
80.4%
2023-12-11T01:36:50.010177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
26
 
4.4%
원 23
 
3.9%
이 20
 
3.4%
병 20
 
3.4%
어 15
 
2.6%
집 15
 
2.6%
린 14
 
2.4%
안 14
 
2.4%
영 14
 
2.4%
의 13
 
2.2%
Other values (156) 414
70.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 527
89.6%
Space Separator 26
 
4.4%
Uppercase Letter 26
 
4.4%
Open Punctuation 3
 
0.5%
Close Punctuation 3
 
0.5%
Decimal Number 2
 
0.3%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 23
 
4.4%
이 20
 
3.8%
병 20
 
3.8%
어 15
 
2.8%
집 15
 
2.8%
린 14
 
2.7%
안 14
 
2.7%
영 14
 
2.7%
의 13
 
2.5%
수 13
 
2.5%
Other values (138) 366
69.4%
Uppercase Letter
ValueCountFrequency (%)
C 7
26.9%
P 7
26.9%
E 2
 
7.7%
S 2
 
7.7%
O 1
 
3.8%
X 1
 
3.8%
L 1
 
3.8%
V 1
 
3.8%
R 1
 
3.8%
B 1
 
3.8%
Other values (2) 2
 
7.7%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
3 1
50.0%
Space Separator
ValueCountFrequency (%)
26
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 527
89.6%
Common 35
 
6.0%
Latin 26
 
4.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 23
 
4.4%
이 20
 
3.8%
병 20
 
3.8%
어 15
 
2.8%
집 15
 
2.8%
린 14
 
2.7%
안 14
 
2.7%
영 14
 
2.7%
의 13
 
2.5%
수 13
 
2.5%
Other values (138) 366
69.4%
Latin
ValueCountFrequency (%)
C 7
26.9%
P 7
26.9%
E 2
 
7.7%
S 2
 
7.7%
O 1
 
3.8%
X 1
 
3.8%
L 1
 
3.8%
V 1
 
3.8%
R 1
 
3.8%
B 1
 
3.8%
Other values (2) 2
 
7.7%
Common
ValueCountFrequency (%)
26
74.3%
( 3
 
8.6%
) 3
 
8.6%
2 1
 
2.9%
3 1
 
2.9%
& 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 527
89.6%
ASCII 61
 
10.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
26
42.6%
C 7
 
11.5%
P 7
 
11.5%
( 3
 
4.9%
) 3
 
4.9%
E 2
 
3.3%
S 2
 
3.3%
O 1
 
1.6%
2 1
 
1.6%
X 1
 
1.6%
Other values (8) 8
 
13.1%
Hangul
ValueCountFrequency (%)
원 23
 
4.4%
이 20
 
3.8%
병 20
 
3.8%
어 15
 
2.8%
집 15
 
2.8%
린 14
 
2.7%
안 14
 
2.7%
영 14
 
2.7%
의 13
 
2.5%
수 13
 
2.5%
Other values (138) 366
69.4%

주소
Text

Distinct64
Distinct (%)90.1%
Missing0
Missing (%)0.0%
Memory size700.0 B
2023-12-11T01:36:50.322524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length36
Mean length27.394366
Min length20

Characters and Unicode

Total characters1945
Distinct characters95
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

Unique59 ?
Unique (%)83.1%

Sample

1st row부산광역시 수영구 수영로 지하 410 (남천동)
2nd row부산광역시 수영구 수영로 지하 482( 남천동)
3rd row부산광역시 수영구 수영로 지하 576 (광안동)
4th row부산광역시 수영구 수영로 지하 677 (광안동)
5th row부산광역시 수영구 수영로 지하 769 (민락동)
ValueCountFrequency (%)
부산광역시 71
18.3%
수영구 71
18.3%
광안동 30
 
7.8%
수영로 21
 
5.4%
남천동 17
 
4.4%
망미동 10
 
2.6%
지하 8
 
2.1%
민락동 8
 
2.1%
광안해변로 5
 
1.3%
677 4
 
1.0%
Other values (117) 142
36.7%
2023-12-11T01:36:50.792173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
320
 
16.5%
광 116
 
6.0%
수 109
 
5.6%
영 102
 
5.2%
산 78
 
4.0%
동 74
 
3.8%
구 73
 
3.8%
부 72
 
3.7%
( 71
 
3.7%
역 71
 
3.7%
Other values (85) 859
44.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1189
61.1%
Space Separator 320
 
16.5%
Decimal Number 273
 
14.0%
Open Punctuation 71
 
3.7%
Close Punctuation 71
 
3.7%
Math Symbol 9
 
0.5%
Other Punctuation 6
 
0.3%
Dash Punctuation 4
 
0.2%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 116
 
9.8%
수 109
 
9.2%
영 102
 
8.6%
산 78
 
6.6%
동 74
 
6.2%
구 73
 
6.1%
부 72
 
6.1%
역 71
 
6.0%
시 71
 
6.0%
로 70
 
5.9%
Other values (67) 353
29.7%
Decimal Number
ValueCountFrequency (%)
1 41
15.0%
5 34
12.5%
7 33
12.1%
2 32
11.7%
3 32
11.7%
6 30
11.0%
4 27
9.9%
0 16
 
5.9%
9 14
 
5.1%
8 14
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
S 1
50.0%
K 1
50.0%
Space Separator
ValueCountFrequency (%)
320
100.0%
Open Punctuation
ValueCountFrequency (%)
( 71
100.0%
Close Punctuation
ValueCountFrequency (%)
) 71
100.0%
Math Symbol
ValueCountFrequency (%)
~ 9
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1189
61.1%
Common 754
38.8%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 116
 
9.8%
수 109
 
9.2%
영 102
 
8.6%
산 78
 
6.6%
동 74
 
6.2%
구 73
 
6.1%
부 72
 
6.1%
역 71
 
6.0%
시 71
 
6.0%
로 70
 
5.9%
Other values (67) 353
29.7%
Common
ValueCountFrequency (%)
320
42.4%
( 71
 
9.4%
) 71
 
9.4%
1 41
 
5.4%
5 34
 
4.5%
7 33
 
4.4%
2 32
 
4.2%
3 32
 
4.2%
6 30
 
4.0%
4 27
 
3.6%
Other values (6) 63
 
8.4%
Latin
ValueCountFrequency (%)
S 1
50.0%
K 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1189
61.1%
ASCII 756
38.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
320
42.3%
( 71
 
9.4%
) 71
 
9.4%
1 41
 
5.4%
5 34
 
4.5%
7 33
 
4.4%
2 32
 
4.2%
3 32
 
4.2%
6 30
 
4.0%
4 27
 
3.6%
Other values (8) 65
 
8.6%
Hangul
ValueCountFrequency (%)
광 116
 
9.8%
수 109
 
9.2%
영 102
 
8.6%
산 78
 
6.6%
동 74
 
6.2%
구 73
 
6.1%
부 72
 
6.1%
역 71
 
6.0%
시 71
 
6.0%
로 70
 
5.9%
Other values (67) 353
29.7%

시설군
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)16.9%
Missing0
Missing (%)0.0%
Memory size700.0 B
의료기관
18 
어린이집
14 
실내주차장
11 
인터넷컴퓨터게임시설제공업
8 
지하역사
7 
Other values (7)
13 

Length

Max length13
Median length4
Mean length5.3098592
Min length3

Unique

Unique4 ?
Unique (%)5.6%

Sample

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

Common Values

ValueCountFrequency (%)
의료기관 18
25.4%
어린이집 14
19.7%
실내주차장 11
15.5%
인터넷컴퓨터게임시설제공업 8
11.3%
지하역사 7
 
9.9%
노인요양시설 4
 
5.6%
목욕장업 3
 
4.2%
대규모점포 2
 
2.8%
지하상가 1
 
1.4%
장례식장 1
 
1.4%
Other values (2) 2
 
2.8%

Length

2023-12-11T01:36:50.929470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
의료기관 18
25.4%
어린이집 14
19.7%
실내주차장 11
15.5%
인터넷컴퓨터게임시설제공업 8
11.3%
지하역사 7
 
9.9%
노인요양시설 4
 
5.6%
목욕장업 3
 
4.2%
대규모점포 2
 
2.8%
지하상가 1
 
1.4%
장례식장 1
 
1.4%
Other values (2) 2
 
2.8%

연면적
Real number (ℝ)

UNIQUE 

Distinct71
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5943.7085
Minimum300.05
Maximum38044
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size771.0 B
2023-12-11T01:36:51.046697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum300.05
5-th percentile352.46
Q1829.5
median3006.79
Q36254.21
95-th percentile23316.365
Maximum38044
Range37743.95
Interquartile range (IQR)5424.71

Descriptive statistics

Standard deviation8013.8284
Coefficient of variation (CV)1.3482876
Kurtosis6.4227519
Mean5943.7085
Median Absolute Deviation (MAD)2387.67
Skewness2.4422223
Sum422003.3
Variance64221446
MonotonicityNot monotonic
2023-12-11T01:36:51.177553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10474.0 1
 
1.4%
14095.0 1
 
1.4%
384.73 1
 
1.4%
536.16 1
 
1.4%
13380.66 1
 
1.4%
26458.0 1
 
1.4%
21755.73 1
 
1.4%
38044.0 1
 
1.4%
826.0 1
 
1.4%
552.0 1
 
1.4%
Other values (61) 61
85.9%
ValueCountFrequency (%)
300.05 1
1.4%
310.38 1
1.4%
317.89 1
1.4%
320.19 1
1.4%
384.73 1
1.4%
426.27 1
1.4%
475.0 1
1.4%
493.59 1
1.4%
509.0 1
1.4%
517.0 1
1.4%
ValueCountFrequency (%)
38044.0 1
1.4%
37875.73 1
1.4%
26458.0 1
1.4%
24877.0 1
1.4%
21755.73 1
1.4%
17282.08 1
1.4%
14778.93 1
1.4%
14561.0 1
1.4%
14095.0 1
1.4%
13524.0 1
1.4%

Interactions

2023-12-11T01:36:48.519388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:36:48.174894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:36:48.635023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:36:48.382872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:36:51.280519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호업소명(건물명)주소시설군연면적
번호1.0001.0000.9760.8710.530
업소명(건물명)1.0001.0001.0001.0001.000
주소0.9761.0001.0000.0000.000
시설군0.8711.0000.0001.0000.624
연면적0.5301.0000.0000.6241.000
2023-12-11T01:36:51.400466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호연면적시설군
번호1.000-0.3160.599
연면적-0.3161.0000.312
시설군0.5990.3121.000

Missing values

2023-12-11T01:36:48.805040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:36:48.929152image/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

번호업소명(건물명)주소시설군연면적
01남천역부산광역시 수영구 수영로 지하 410 (남천동)지하역사10474.0
12금련산역부산광역시 수영구 수영로 지하 482( 남천동)지하역사14095.0
23광안역부산광역시 수영구 수영로 지하 576 (광안동)지하역사14561.0
34수영역(2호선)부산광역시 수영구 수영로 지하 677 (광안동)지하역사13524.0
45민락역부산광역시 수영구 수영로 지하 769 (민락동)지하역사10147.0
56망미역부산광역시 수영구 연수로 지하 337 (망미동)지하역사12484.0
67수영역(3호선)부산광역시 수영구 수영로 지하 677 (광안동)지하역사2633.0
78수영지하상가부산광역시 수영구 수영로 지하 677 (광안동)지하상가6673.0
89BHS한서병원부산광역시 수영구 수영로 615 (광안동)의료기관17282.08
910의료법인 센텀의료재단 부산센텀병원부산광역시 수영구 수영로 677 부산센텀병원 지하1~6층 (광안동)의료기관6437.67
번호업소명(건물명)주소시설군연면적
6162엑슬루타워상가부산광역시 수영구 황령대로473번길 15(남천동,남천엑슬루타워)실내주차장8764.0
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