Overview

Dataset statistics

Number of variables5
Number of observations963
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory38.7 KiB
Average record size in memory41.1 B

Variable types

Numeric1
Categorical1
Text2
DateTime1

Dataset

Description부산광역시 부산진구 관내에 존재하는 소독의무대상시설 현황에 대한 정보로 연번 , 시설구분, 시설명, 주소(도로명) 등의 항목을 제공하고 있습니다.
Author부산광역시 부산진구
URLhttps://www.data.go.kr/data/15127421/fileData.do

Alerts

기준일 has constant value ""Constant
연번 is highly overall correlated with 시설구분(종류)High correlation
시설구분(종류) is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2024-05-18 08:31:36.866059
Analysis finished2024-05-18 08:31:38.369918
Duration1.5 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct963
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean482
Minimum1
Maximum963
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.6 KiB
2024-05-18T17:31:38.519418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile49.1
Q1241.5
median482
Q3722.5
95-th percentile914.9
Maximum963
Range962
Interquartile range (IQR)481

Descriptive statistics

Standard deviation278.13845
Coefficient of variation (CV)0.57705074
Kurtosis-1.2
Mean482
Median Absolute Deviation (MAD)241
Skewness0
Sum464166
Variance77361
MonotonicityStrictly increasing
2024-05-18T17:31:38.981044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
604 1
 
0.1%
636 1
 
0.1%
637 1
 
0.1%
638 1
 
0.1%
639 1
 
0.1%
640 1
 
0.1%
641 1
 
0.1%
642 1
 
0.1%
643 1
 
0.1%
Other values (953) 953
99.0%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
963 1
0.1%
962 1
0.1%
961 1
0.1%
960 1
0.1%
959 1
0.1%
958 1
0.1%
957 1
0.1%
956 1
0.1%
955 1
0.1%
954 1
0.1%

시설구분(종류)
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
복합건축물
349 
식품업소
170 
숙박업소
126 
공동주택 등
90 
학교, 기숙사 등
73 
Other values (7)
155 

Length

Max length9
Median length6
Mean length5.3738318
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
복합건축물 349
36.2%
식품업소 170
17.7%
숙박업소 126
 
13.1%
공동주택 등 90
 
9.3%
학교, 기숙사 등 73
 
7.6%
영유아보육시설 등 52
 
5.4%
병원 등 43
 
4.5%
시장, 백화점 등 25
 
2.6%
교통시설 등 21
 
2.2%
집단급식시설 6
 
0.6%
Other values (2) 8
 
0.8%

Length

2024-05-18T17:31:39.526117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
복합건축물 349
25.6%
등 304
22.3%
식품업소 170
12.5%
숙박업소 126
 
9.2%
공동주택 90
 
6.6%
학교 73
 
5.3%
기숙사 73
 
5.3%
영유아보육시설 52
 
3.8%
병원 43
 
3.2%
시장 25
 
1.8%
Other values (5) 60
 
4.4%

시설명
Text

Distinct959
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
2024-05-18T17:31:39.979853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length23
Mean length9.4215992
Min length2

Characters and Unicode

Total characters9073
Distinct characters555
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique955 ?
Unique (%)99.2%

Sample

1st row(주)부산롯데호텔
2nd row스테이 에비뉴호텔
3rd row호텔밴드
4th row서면 덴바스타 센트럴
5th row호텔 하이든
ValueCountFrequency (%)
포함 109
 
8.3%
호텔 15
 
1.1%
서면점 9
 
0.7%
오피스텔 5
 
0.4%
서면 5
 
0.4%
부산 4
 
0.3%
모텔 4
 
0.3%
부산서면점 4
 
0.3%
더 3
 
0.2%
대규모 3
 
0.2%
Other values (1114) 1151
87.7%
2024-05-18T17:31:41.103000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
384
 
4.2%
) 286
 
3.2%
( 274
 
3.0%
스 208
 
2.3%
텔 156
 
1.7%
부 153
 
1.7%
이 147
 
1.6%
포 146
 
1.6%
원 145
 
1.6%
산 141
 
1.6%
Other values (545) 7033
77.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7729
85.2%
Space Separator 384
 
4.2%
Close Punctuation 286
 
3.2%
Open Punctuation 274
 
3.0%
Uppercase Letter 148
 
1.6%
Decimal Number 122
 
1.3%
Other Punctuation 43
 
0.5%
Other Symbol 38
 
0.4%
Lowercase Letter 31
 
0.3%
Dash Punctuation 18
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 208
 
2.7%
텔 156
 
2.0%
부 153
 
2.0%
이 147
 
1.9%
포 146
 
1.9%
원 145
 
1.9%
산 141
 
1.8%
서 132
 
1.7%
빌 121
 
1.6%
식 119
 
1.5%
Other values (486) 6261
81.0%
Uppercase Letter
ValueCountFrequency (%)
K 12
 
8.1%
T 12
 
8.1%
C 12
 
8.1%
L 12
 
8.1%
G 11
 
7.4%
H 10
 
6.8%
S 8
 
5.4%
O 8
 
5.4%
V 7
 
4.7%
B 7
 
4.7%
Other values (15) 49
33.1%
Lowercase Letter
ValueCountFrequency (%)
e 8
25.8%
o 3
 
9.7%
r 3
 
9.7%
n 2
 
6.5%
i 2
 
6.5%
s 2
 
6.5%
a 2
 
6.5%
f 2
 
6.5%
c 2
 
6.5%
x 1
 
3.2%
Other values (4) 4
12.9%
Decimal Number
ValueCountFrequency (%)
2 41
33.6%
1 28
23.0%
3 13
 
10.7%
5 10
 
8.2%
4 6
 
4.9%
9 6
 
4.9%
7 5
 
4.1%
0 5
 
4.1%
6 4
 
3.3%
8 4
 
3.3%
Other Punctuation
ValueCountFrequency (%)
. 24
55.8%
/ 9
 
20.9%
& 5
 
11.6%
, 4
 
9.3%
: 1
 
2.3%
Space Separator
ValueCountFrequency (%)
384
100.0%
Close Punctuation
ValueCountFrequency (%)
) 286
100.0%
Open Punctuation
ValueCountFrequency (%)
( 274
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 38
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7767
85.6%
Common 1127
 
12.4%
Latin 179
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 208
 
2.7%
텔 156
 
2.0%
부 153
 
2.0%
이 147
 
1.9%
포 146
 
1.9%
원 145
 
1.9%
산 141
 
1.8%
서 132
 
1.7%
빌 121
 
1.6%
식 119
 
1.5%
Other values (487) 6299
81.1%
Latin
ValueCountFrequency (%)
K 12
 
6.7%
T 12
 
6.7%
C 12
 
6.7%
L 12
 
6.7%
G 11
 
6.1%
H 10
 
5.6%
e 8
 
4.5%
S 8
 
4.5%
O 8
 
4.5%
V 7
 
3.9%
Other values (29) 79
44.1%
Common
ValueCountFrequency (%)
384
34.1%
) 286
25.4%
( 274
24.3%
2 41
 
3.6%
1 28
 
2.5%
. 24
 
2.1%
- 18
 
1.6%
3 13
 
1.2%
5 10
 
0.9%
/ 9
 
0.8%
Other values (9) 40
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7729
85.2%
ASCII 1306
 
14.4%
None 38
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
384
29.4%
) 286
21.9%
( 274
21.0%
2 41
 
3.1%
1 28
 
2.1%
. 24
 
1.8%
- 18
 
1.4%
3 13
 
1.0%
K 12
 
0.9%
T 12
 
0.9%
Other values (48) 214
16.4%
Hangul
ValueCountFrequency (%)
스 208
 
2.7%
텔 156
 
2.0%
부 153
 
2.0%
이 147
 
1.9%
포 146
 
1.9%
원 145
 
1.9%
산 141
 
1.8%
서 132
 
1.7%
빌 121
 
1.6%
식 119
 
1.5%
Other values (486) 6261
81.0%
None
ValueCountFrequency (%)
㈜ 38
100.0%

주소(도로명)
Text

Distinct938
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
2024-05-18T17:31:41.647725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length34
Mean length16.8027
Min length6

Characters and Unicode

Total characters16181
Distinct characters193
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique914 ?
Unique (%)94.9%

Sample

1st row가야대로 772 (부전동)
2nd row동평로406번길 57 (양정동)
3rd row새싹로29번길 14-9 (부전동)
4th row중앙대로691번길 53 (부전동)
5th row서면문화로 23 (부전동) MJ빌딩 7-12층
ValueCountFrequency (%)
부전동 294
 
9.5%
중앙대로 107
 
3.5%
전포동 100
 
3.2%
범천동 83
 
2.7%
양정동 80
 
2.6%
가야대로 70
 
2.3%
개금동 68
 
2.2%
당감동 59
 
1.9%
부암동 49
 
1.6%
서면로 39
 
1.3%
Other values (887) 2138
69.3%
2024-05-18T17:31:42.675846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2204
 
13.6%
동 997
 
6.2%
로 948
 
5.9%
( 906
 
5.6%
) 905
 
5.6%
1 726
 
4.5%
전 565
 
3.5%
2 517
 
3.2%
부 446
 
2.8%
대 428
 
2.6%
Other values (183) 7539
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7905
48.9%
Decimal Number 3836
23.7%
Space Separator 2204
 
13.6%
Open Punctuation 906
 
5.6%
Close Punctuation 905
 
5.6%
Other Punctuation 216
 
1.3%
Dash Punctuation 168
 
1.0%
Math Symbol 25
 
0.2%
Uppercase Letter 15
 
0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 997
 
12.6%
로 948
 
12.0%
전 565
 
7.1%
부 446
 
5.6%
대 428
 
5.4%
번 405
 
5.1%
길 371
 
4.7%
층 205
 
2.6%
중 187
 
2.4%
앙 185
 
2.3%
Other values (155) 3168
40.1%
Decimal Number
ValueCountFrequency (%)
1 726
18.9%
2 517
13.5%
6 384
10.0%
7 364
9.5%
3 363
9.5%
5 318
8.3%
4 318
8.3%
0 311
8.1%
9 281
 
7.3%
8 254
 
6.6%
Uppercase Letter
ValueCountFrequency (%)
B 4
26.7%
A 3
20.0%
D 1
 
6.7%
R 1
 
6.7%
J 1
 
6.7%
M 1
 
6.7%
Y 1
 
6.7%
C 1
 
6.7%
G 1
 
6.7%
V 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
, 194
89.8%
. 22
 
10.2%
Space Separator
ValueCountFrequency (%)
2204
100.0%
Open Punctuation
ValueCountFrequency (%)
( 906
100.0%
Close Punctuation
ValueCountFrequency (%)
) 905
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 168
100.0%
Math Symbol
ValueCountFrequency (%)
~ 25
100.0%
Lowercase Letter
ValueCountFrequency (%)
c 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8260
51.0%
Hangul 7905
48.9%
Latin 16
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 997
 
12.6%
로 948
 
12.0%
전 565
 
7.1%
부 446
 
5.6%
대 428
 
5.4%
번 405
 
5.1%
길 371
 
4.7%
층 205
 
2.6%
중 187
 
2.4%
앙 185
 
2.3%
Other values (155) 3168
40.1%
Common
ValueCountFrequency (%)
2204
26.7%
( 906
11.0%
) 905
11.0%
1 726
 
8.8%
2 517
 
6.3%
6 384
 
4.6%
7 364
 
4.4%
3 363
 
4.4%
5 318
 
3.8%
4 318
 
3.8%
Other values (7) 1255
15.2%
Latin
ValueCountFrequency (%)
B 4
25.0%
A 3
18.8%
D 1
 
6.2%
R 1
 
6.2%
J 1
 
6.2%
M 1
 
6.2%
c 1
 
6.2%
Y 1
 
6.2%
C 1
 
6.2%
G 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8276
51.1%
Hangul 7905
48.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2204
26.6%
( 906
10.9%
) 905
10.9%
1 726
 
8.8%
2 517
 
6.2%
6 384
 
4.6%
7 364
 
4.4%
3 363
 
4.4%
5 318
 
3.8%
4 318
 
3.8%
Other values (18) 1271
15.4%
Hangul
ValueCountFrequency (%)
동 997
 
12.6%
로 948
 
12.0%
전 565
 
7.1%
부 446
 
5.6%
대 428
 
5.4%
번 405
 
5.1%
길 371
 
4.7%
층 205
 
2.6%
중 187
 
2.4%
앙 185
 
2.3%
Other values (155) 3168
40.1%

기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
Minimum2024-03-28 00:00:00
Maximum2024-03-28 00:00:00
2024-05-18T17:31:43.017709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T17:31:43.316911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-05-18T17:31:37.821036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T17:31:43.440837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시설구분(종류)
연번1.0000.920
시설구분(종류)0.9201.000
2024-05-18T17:31:43.586501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시설구분(종류)
연번1.0000.722
시설구분(종류)0.7221.000

Missing values

2024-05-18T17:31:38.118871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T17:31:38.302238image/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

연번시설구분(종류)시설명주소(도로명)기준일
01숙박업소(주)부산롯데호텔가야대로 772 (부전동)2024-03-28
12숙박업소스테이 에비뉴호텔동평로406번길 57 (양정동)2024-03-28
23숙박업소호텔밴드새싹로29번길 14-9 (부전동)2024-03-28
34숙박업소서면 덴바스타 센트럴중앙대로691번길 53 (부전동)2024-03-28
45숙박업소호텔 하이든서면문화로 23 (부전동) MJ빌딩 7-12층2024-03-28
56숙박업소놈모텔새싹로29번길 33 (부전동)2024-03-28
67숙박업소다뉴브호텔동천로85번길 13-5 (부전동)2024-03-28
78숙박업소더클럽호텔중앙대로691번길 46 (부전동)2024-03-28
89숙박업소덴바스타자유평화로37번길 41 (범천동)2024-03-28
910숙박업소브라운도트호텔 초읍점새싹로278번길 11 (초읍동)2024-03-28
연번시설구분(종류)시설명주소(도로명)기준일
953954공동주택 등이진젠시티가야대로 4972024-03-28
954955공동주택 등양산롯데캐슬골드센트부암동 5672024-03-28
955956공동주택 등삼정그린코아더시티중앙대로 7972024-03-28
956957공동주택 등당감주공1단지(임대)백양산로53번길 125 (당감동)2024-03-28
957958공동주택 등개금2지구도개공영구임대아파트백양관문로77번길 145 (개금동)2024-03-28
958959공동주택 등범천LH(임대주택)신암로 66 (범천동)2024-03-28
959960공동주택 등서면쌍용플래티넘동천로 70 (전포동)2024-03-28
960961공동주택 등전포동 부영아파트동성로 82 (전포동)2024-03-28
961962공동주택 등화승삼성아파트당감로 79 (부암동)2024-03-28
962963공동주택 등전포LH아파트중앙대로 862 (전포동)2024-03-28