Overview

Dataset statistics

Number of variables5
Number of observations68
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.9 KiB
Average record size in memory43.9 B

Variable types

Numeric2
Text2
Categorical1

Dataset

Description부산광역시 수영구 다중이용시설 실내 공기질 관리 대상 데이터로 업소명, 주소, 시설군, 연면적 정보를 제공하고 있다.
Author부산광역시 수영구
URLhttps://www.data.go.kr/data/15026343/fileData.do

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 started2024-03-15 02:07:28.132175
Analysis finished2024-03-15 02:07:29.923122
Duration1.79 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct68
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.5
Minimum1
Maximum68
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size740.0 B
2024-03-15T11:07:30.140033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.35
Q117.75
median34.5
Q351.25
95-th percentile64.65
Maximum68
Range67
Interquartile range (IQR)33.5

Descriptive statistics

Standard deviation19.77372
Coefficient of variation (CV)0.5731513
Kurtosis-1.2
Mean34.5
Median Absolute Deviation (MAD)17
Skewness0
Sum2346
Variance391
MonotonicityStrictly increasing
2024-03-15T11:07:30.604601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.5%
45 1
 
1.5%
51 1
 
1.5%
50 1
 
1.5%
49 1
 
1.5%
48 1
 
1.5%
47 1
 
1.5%
46 1
 
1.5%
44 1
 
1.5%
36 1
 
1.5%
Other values (58) 58
85.3%
ValueCountFrequency (%)
1 1
1.5%
2 1
1.5%
3 1
1.5%
4 1
1.5%
5 1
1.5%
6 1
1.5%
7 1
1.5%
8 1
1.5%
9 1
1.5%
10 1
1.5%
ValueCountFrequency (%)
68 1
1.5%
67 1
1.5%
66 1
1.5%
65 1
1.5%
64 1
1.5%
63 1
1.5%
62 1
1.5%
61 1
1.5%
60 1
1.5%
59 1
1.5%

업소명(건물명)
Text

UNIQUE 

Distinct68
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size672.0 B
2024-03-15T11:07:31.578562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length8.3088235
Min length3

Characters and Unicode

Total characters565
Distinct characters160
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

Unique68 ?
Unique (%)100.0%

Sample

1st row남천역
2nd row금련산역
3rd row광안역
4th row수영역(2호선)
5th row민락역
ValueCountFrequency (%)
pc 3
 
3.3%
좋은강안병원 3
 
3.3%
광안자모병원 2
 
2.2%
실내주차장 2
 
2.2%
의료법인 2
 
2.2%
코스트코부산점 2
 
2.2%
메가마트 2
 
2.2%
동산어린이집 1
 
1.1%
피플pc방 1
 
1.1%
세림어린이집 1
 
1.1%
Other values (72) 72
79.1%
2024-03-15T11:07:33.044723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
23
 
4.1%
원 22
 
3.9%
이 20
 
3.5%
병 19
 
3.4%
집 15
 
2.7%
어 15
 
2.7%
린 14
 
2.5%
안 13
 
2.3%
영 13
 
2.3%
의 13
 
2.3%
Other values (150) 398
70.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 507
89.7%
Uppercase Letter 26
 
4.6%
Space Separator 23
 
4.1%
Close Punctuation 3
 
0.5%
Open Punctuation 3
 
0.5%
Decimal Number 2
 
0.4%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 22
 
4.3%
이 20
 
3.9%
병 19
 
3.7%
집 15
 
3.0%
어 15
 
3.0%
린 14
 
2.8%
안 13
 
2.6%
영 13
 
2.6%
의 13
 
2.6%
수 12
 
2.4%
Other values (132) 351
69.2%
Uppercase Letter
ValueCountFrequency (%)
C 7
26.9%
P 7
26.9%
E 2
 
7.7%
S 2
 
7.7%
X 1
 
3.8%
O 1
 
3.8%
K 1
 
3.8%
H 1
 
3.8%
B 1
 
3.8%
L 1
 
3.8%
Other values (2) 2
 
7.7%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
3 1
50.0%
Space Separator
ValueCountFrequency (%)
23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 507
89.7%
Common 32
 
5.7%
Latin 26
 
4.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 22
 
4.3%
이 20
 
3.9%
병 19
 
3.7%
집 15
 
3.0%
어 15
 
3.0%
린 14
 
2.8%
안 13
 
2.6%
영 13
 
2.6%
의 13
 
2.6%
수 12
 
2.4%
Other values (132) 351
69.2%
Latin
ValueCountFrequency (%)
C 7
26.9%
P 7
26.9%
E 2
 
7.7%
S 2
 
7.7%
X 1
 
3.8%
O 1
 
3.8%
K 1
 
3.8%
H 1
 
3.8%
B 1
 
3.8%
L 1
 
3.8%
Other values (2) 2
 
7.7%
Common
ValueCountFrequency (%)
23
71.9%
) 3
 
9.4%
( 3
 
9.4%
2 1
 
3.1%
3 1
 
3.1%
& 1
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 507
89.7%
ASCII 58
 
10.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
23
39.7%
C 7
 
12.1%
P 7
 
12.1%
) 3
 
5.2%
( 3
 
5.2%
E 2
 
3.4%
S 2
 
3.4%
X 1
 
1.7%
O 1
 
1.7%
2 1
 
1.7%
Other values (8) 8
 
13.8%
Hangul
ValueCountFrequency (%)
원 22
 
4.3%
이 20
 
3.9%
병 19
 
3.7%
집 15
 
3.0%
어 15
 
3.0%
린 14
 
2.8%
안 13
 
2.6%
영 13
 
2.6%
의 13
 
2.6%
수 12
 
2.4%
Other values (132) 351
69.2%

주소
Text

Distinct61
Distinct (%)89.7%
Missing0
Missing (%)0.0%
Memory size672.0 B
2024-03-15T11:07:33.900626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length37
Mean length27.352941
Min length20

Characters and Unicode

Total characters1860
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

Unique56 ?
Unique (%)82.4%

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 68
18.3%
수영구 68
18.3%
광안동 29
 
7.8%
수영로 20
 
5.4%
남천동 17
 
4.6%
망미동 10
 
2.7%
지하 8
 
2.2%
민락동 6
 
1.6%
677 4
 
1.1%
수영동 4
 
1.1%
Other values (113) 137
36.9%
2024-03-15T11:07:35.064165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
307
 
16.5%
광 111
 
6.0%
수 104
 
5.6%
영 98
 
5.3%
산 75
 
4.0%
동 71
 
3.8%
구 70
 
3.8%
부 69
 
3.7%
시 68
 
3.7%
역 68
 
3.7%
Other values (85) 819
44.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1140
61.3%
Space Separator 307
 
16.5%
Decimal Number 259
 
13.9%
Close Punctuation 68
 
3.7%
Open Punctuation 68
 
3.7%
Math Symbol 8
 
0.4%
Other Punctuation 5
 
0.3%
Dash Punctuation 3
 
0.2%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 111
 
9.7%
수 104
 
9.1%
영 98
 
8.6%
산 75
 
6.6%
동 71
 
6.2%
구 70
 
6.1%
부 69
 
6.1%
시 68
 
6.0%
역 68
 
6.0%
로 67
 
5.9%
Other values (67) 339
29.7%
Decimal Number
ValueCountFrequency (%)
1 38
14.7%
2 31
12.0%
7 31
12.0%
5 31
12.0%
3 29
11.2%
6 28
10.8%
4 27
10.4%
0 16
6.2%
9 14
 
5.4%
8 14
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
K 1
50.0%
S 1
50.0%
Space Separator
ValueCountFrequency (%)
307
100.0%
Close Punctuation
ValueCountFrequency (%)
) 68
100.0%
Open Punctuation
ValueCountFrequency (%)
( 68
100.0%
Math Symbol
ValueCountFrequency (%)
~ 8
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1140
61.3%
Common 718
38.6%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 111
 
9.7%
수 104
 
9.1%
영 98
 
8.6%
산 75
 
6.6%
동 71
 
6.2%
구 70
 
6.1%
부 69
 
6.1%
시 68
 
6.0%
역 68
 
6.0%
로 67
 
5.9%
Other values (67) 339
29.7%
Common
ValueCountFrequency (%)
307
42.8%
) 68
 
9.5%
( 68
 
9.5%
1 38
 
5.3%
2 31
 
4.3%
7 31
 
4.3%
5 31
 
4.3%
3 29
 
4.0%
6 28
 
3.9%
4 27
 
3.8%
Other values (6) 60
 
8.4%
Latin
ValueCountFrequency (%)
K 1
50.0%
S 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1140
61.3%
ASCII 720
38.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
307
42.6%
) 68
 
9.4%
( 68
 
9.4%
1 38
 
5.3%
2 31
 
4.3%
7 31
 
4.3%
5 31
 
4.3%
3 29
 
4.0%
6 28
 
3.9%
4 27
 
3.8%
Other values (8) 62
 
8.6%
Hangul
ValueCountFrequency (%)
광 111
 
9.7%
수 104
 
9.1%
영 98
 
8.6%
산 75
 
6.6%
동 71
 
6.2%
구 70
 
6.1%
부 69
 
6.1%
시 68
 
6.0%
역 68
 
6.0%
로 67
 
5.9%
Other values (67) 339
29.7%

시설군
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)17.6%
Missing0
Missing (%)0.0%
Memory size672.0 B
의료기관
16 
어린이집
14 
실내주차장
10 
인터넷컴퓨터게임시설제공업
8 
지하역사
7 
Other values (7)
13 

Length

Max length13
Median length4
Mean length5.3529412
Min length3

Unique

Unique4 ?
Unique (%)5.9%

Sample

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

Common Values

ValueCountFrequency (%)
의료기관 16
23.5%
어린이집 14
20.6%
실내주차장 10
14.7%
인터넷컴퓨터게임시설제공업 8
11.8%
지하역사 7
10.3%
노인요양시설 4
 
5.9%
목욕장업 3
 
4.4%
대규모점포 2
 
2.9%
지하상가 1
 
1.5%
장례식장 1
 
1.5%
Other values (2) 2
 
2.9%

Length

2024-03-15T11:07:35.312650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
의료기관 16
23.5%
어린이집 14
20.6%
실내주차장 10
14.7%
인터넷컴퓨터게임시설제공업 8
11.8%
지하역사 7
10.3%
노인요양시설 4
 
5.9%
목욕장업 3
 
4.4%
대규모점포 2
 
2.9%
지하상가 1
 
1.5%
장례식장 1
 
1.5%
Other values (2) 2
 
2.9%

연면적
Real number (ℝ)

UNIQUE 

Distinct68
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6043.4204
Minimum300.05
Maximum38044
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size740.0 B
2024-03-15T11:07:35.674711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum300.05
5-th percentile342.779
Q1784.5375
median2934.97
Q36496.5025
95-th percentile23784.555
Maximum38044
Range37743.95
Interquartile range (IQR)5711.965

Descriptive statistics

Standard deviation8175.4516
Coefficient of variation (CV)1.3527855
Kurtosis5.9894145
Mean6043.4204
Median Absolute Deviation (MAD)2362.97
Skewness2.3698162
Sum410952.59
Variance66838008
MonotonicityNot monotonic
2024-03-15T11:07:36.120953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10474.0 1
 
1.5%
826.0 1
 
1.5%
384.73 1
 
1.5%
536.16 1
 
1.5%
13380.66 1
 
1.5%
26458.0 1
 
1.5%
21755.73 1
 
1.5%
38044.0 1
 
1.5%
552.0 1
 
1.5%
517.0 1
 
1.5%
Other values (58) 58
85.3%
ValueCountFrequency (%)
300.05 1
1.5%
310.38 1
1.5%
317.89 1
1.5%
320.19 1
1.5%
384.73 1
1.5%
426.27 1
1.5%
475.0 1
1.5%
493.59 1
1.5%
509.0 1
1.5%
517.0 1
1.5%
ValueCountFrequency (%)
38044.0 1
1.5%
37875.73 1
1.5%
26458.0 1
1.5%
24877.0 1
1.5%
21755.73 1
1.5%
17282.08 1
1.5%
14778.93 1
1.5%
14561.0 1
1.5%
14095.0 1
1.5%
13524.0 1
1.5%

Interactions

2024-03-15T11:07:28.934637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:07:28.617639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:07:29.124368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:07:28.776268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T11:07:36.395248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호업소명(건물명)주소시설군연면적
번호1.0001.0000.9910.8560.519
업소명(건물명)1.0001.0001.0001.0001.000
주소0.9911.0001.0000.0000.000
시설군0.8561.0000.0001.0000.631
연면적0.5191.0000.0000.6311.000
2024-03-15T11:07:36.660228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호연면적시설군
번호1.000-0.3140.574
연면적-0.3141.0000.316
시설군0.5740.3161.000

Missing values

2024-03-15T11:07:29.471137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T11:07:29.800248image/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
5859씨드이 빌딩부산광역시 수영구 수영로 480 (남천동)실내주차장5007.75
5960엑슬루타워상가부산광역시 수영구 황령대로473번길 15(남천동,남천엑슬루타워)실내주차장8764.0
6061힐탑더블시티부산광역시 수영구 수영로 641 (광안동)실내주차장8239.96
6162망미동 노외공영주차장부산광역시 수영구 금련로43번길 17 (망미동)실내주차장6070.75
6263서희스타힐스센텀프리모부산광역시 수영구 광안해변로 311 (민락동)실내주차장14778.93
6364호메르스관광호텔부산광역시 수영구 광안해변로 217 (광안동)실내주차장2483.69
6465광안해수월드부산광역시 수영구 광안해변로370번길 7 (민락동)목욕장업2810.0
6566리치웰찜질방부산광역시 수영구 남천바다로21번길 85 (광안동)목욕장업1343.0
6667호텔아쿠아펠리스부산광역시 수영구 광안해변로 225 (광안동)목욕장업4352.0
6768수영구도서관부산광역시 수영구 남천서로 33 (남천동)도서관4290.0