Overview

Dataset statistics

Number of variables8
Number of observations4964
Missing cells2836
Missing cells (%)7.1%
Duplicate rows2
Duplicate rows (%)< 0.1%
Total size in memory315.2 KiB
Average record size in memory65.0 B

Variable types

DateTime1
Categorical1
Text5
Numeric1

Dataset

Description부산광역시_동래구_식품위생업소현황_20230915
Author부산광역시 동래구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15026505

Alerts

Dataset has 2 (< 0.1%) duplicate rowsDuplicates
소재지전화 has 2745 (55.3%) missing valuesMissing
우편번호(도로명) has 72 (1.5%) missing valuesMissing

Reproduction

Analysis started2023-12-10 15:59:59.002742
Analysis finished2023-12-10 16:00:00.892765
Duration1.89 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

신고일자
Date

Distinct2408
Distinct (%)48.5%
Missing0
Missing (%)0.0%
Memory size38.9 KiB
Minimum1968-12-29 00:00:00
Maximum2023-09-01 00:00:00
2023-12-11T01:00:00.981949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:00:01.171429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업종명
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.9 KiB
일반음식점
3471 
휴게음식점
984 
유흥주점영업
 
211
단란주점
 
163
제과점영업
 
118

Length

Max length6
Median length5
Mean length5.0130943
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반음식점 3471
69.9%
휴게음식점 984
 
19.8%
유흥주점영업 211
 
4.3%
단란주점 163
 
3.3%
제과점영업 118
 
2.4%
위탁급식영업 17
 
0.3%

Length

2023-12-11T01:00:01.341339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:00:01.473796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반음식점 3471
69.9%
휴게음식점 984
 
19.8%
유흥주점영업 211
 
4.3%
단란주점 163
 
3.3%
제과점영업 118
 
2.4%
위탁급식영업 17
 
0.3%

업소명
Text

Distinct4744
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Memory size38.9 KiB
2023-12-11T01:00:01.818964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length28
Mean length6.5380741
Min length1

Characters and Unicode

Total characters32455
Distinct characters958
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4568 ?
Unique (%)92.0%

Sample

1st row너랑나랑노란
2nd row달콤왕가탕후루 동래래미안아이파크점
3rd row96분식
4th row달콤왕가탕후루 동래역점
5th row로우라이즈
ValueCountFrequency (%)
동래점 99
 
1.6%
사직점 62
 
1.0%
안락점 46
 
0.7%
부산사직점 32
 
0.5%
세븐일레븐 30
 
0.5%
명륜점 23
 
0.4%
온천점 22
 
0.4%
부산동래점 20
 
0.3%
coffee 18
 
0.3%
동래역점 17
 
0.3%
Other values (5001) 5826
94.0%
2023-12-11T01:00:02.386926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 1302
 
4.0%
1233
 
3.8%
이 615
 
1.9%
동 600
 
1.8%
래 597
 
1.8%
스 455
 
1.4%
리 417
 
1.3%
) 390
 
1.2%
( 390
 
1.2%
식 373
 
1.1%
Other values (948) 26083
80.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 28014
86.3%
Space Separator 1233
 
3.8%
Uppercase Letter 971
 
3.0%
Lowercase Letter 781
 
2.4%
Decimal Number 562
 
1.7%
Close Punctuation 390
 
1.2%
Open Punctuation 390
 
1.2%
Other Punctuation 101
 
0.3%
Dash Punctuation 9
 
< 0.1%
Letter Number 2
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 1302
 
4.6%
이 615
 
2.2%
동 600
 
2.1%
래 597
 
2.1%
스 455
 
1.6%
리 417
 
1.5%
식 373
 
1.3%
장 372
 
1.3%
사 357
 
1.3%
산 335
 
1.2%
Other values (870) 22591
80.6%
Uppercase Letter
ValueCountFrequency (%)
C 91
 
9.4%
E 82
 
8.4%
O 73
 
7.5%
S 72
 
7.4%
A 66
 
6.8%
G 57
 
5.9%
B 52
 
5.4%
T 47
 
4.8%
F 45
 
4.6%
N 40
 
4.1%
Other values (16) 346
35.6%
Lowercase Letter
ValueCountFrequency (%)
e 131
16.8%
a 74
 
9.5%
o 73
 
9.3%
c 46
 
5.9%
i 45
 
5.8%
s 42
 
5.4%
n 42
 
5.4%
f 41
 
5.2%
r 37
 
4.7%
t 34
 
4.4%
Other values (14) 216
27.7%
Decimal Number
ValueCountFrequency (%)
2 111
19.8%
1 77
13.7%
5 75
13.3%
0 66
11.7%
3 59
10.5%
9 47
8.4%
4 39
 
6.9%
8 32
 
5.7%
7 31
 
5.5%
6 25
 
4.4%
Other Punctuation
ValueCountFrequency (%)
& 43
42.6%
, 18
17.8%
. 16
 
15.8%
' 10
 
9.9%
· 6
 
5.9%
# 2
 
2.0%
: 2
 
2.0%
/ 2
 
2.0%
; 1
 
1.0%
! 1
 
1.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
50.0%
Ⅰ 1
50.0%
Space Separator
ValueCountFrequency (%)
1233
100.0%
Close Punctuation
ValueCountFrequency (%)
) 390
100.0%
Open Punctuation
ValueCountFrequency (%)
( 390
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Math Symbol
ValueCountFrequency (%)
× 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 27982
86.2%
Common 2687
 
8.3%
Latin 1754
 
5.4%
Han 32
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 1302
 
4.7%
이 615
 
2.2%
동 600
 
2.1%
래 597
 
2.1%
스 455
 
1.6%
리 417
 
1.5%
식 373
 
1.3%
장 372
 
1.3%
사 357
 
1.3%
산 335
 
1.2%
Other values (845) 22559
80.6%
Latin
ValueCountFrequency (%)
e 131
 
7.5%
C 91
 
5.2%
E 82
 
4.7%
a 74
 
4.2%
O 73
 
4.2%
o 73
 
4.2%
S 72
 
4.1%
A 66
 
3.8%
G 57
 
3.2%
B 52
 
3.0%
Other values (42) 983
56.0%
Common
ValueCountFrequency (%)
1233
45.9%
) 390
 
14.5%
( 390
 
14.5%
2 111
 
4.1%
1 77
 
2.9%
5 75
 
2.8%
0 66
 
2.5%
3 59
 
2.2%
9 47
 
1.7%
& 43
 
1.6%
Other values (16) 196
 
7.3%
Han
ValueCountFrequency (%)
李 2
 
6.2%
利 2
 
6.2%
大 2
 
6.2%
火 2
 
6.2%
高 2
 
6.2%
家 2
 
6.2%
情 2
 
6.2%
眞 1
 
3.1%
水 1
 
3.1%
木 1
 
3.1%
Other values (15) 15
46.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 27981
86.2%
ASCII 4432
 
13.7%
CJK 30
 
0.1%
None 7
 
< 0.1%
CJK Compat Ideographs 2
 
< 0.1%
Number Forms 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 1302
 
4.7%
이 615
 
2.2%
동 600
 
2.1%
래 597
 
2.1%
스 455
 
1.6%
리 417
 
1.5%
식 373
 
1.3%
장 372
 
1.3%
사 357
 
1.3%
산 335
 
1.2%
Other values (844) 22558
80.6%
ASCII
ValueCountFrequency (%)
1233
27.8%
) 390
 
8.8%
( 390
 
8.8%
e 131
 
3.0%
2 111
 
2.5%
C 91
 
2.1%
E 82
 
1.9%
1 77
 
1.7%
5 75
 
1.7%
a 74
 
1.7%
Other values (64) 1778
40.1%
None
ValueCountFrequency (%)
· 6
85.7%
× 1
 
14.3%
CJK Compat Ideographs
ValueCountFrequency (%)
李 2
100.0%
CJK
ValueCountFrequency (%)
利 2
 
6.7%
大 2
 
6.7%
火 2
 
6.7%
高 2
 
6.7%
家 2
 
6.7%
情 2
 
6.7%
眞 1
 
3.3%
水 1
 
3.3%
木 1
 
3.3%
氣 1
 
3.3%
Other values (14) 14
46.7%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
50.0%
Ⅰ 1
50.0%
Compat Jamo
ValueCountFrequency (%)
ㅋ 1
100.0%

소재지(도로명)
Text

Distinct4227
Distinct (%)85.4%
Missing13
Missing (%)0.3%
Memory size38.9 KiB
2023-12-11T01:00:02.710048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length60
Mean length30.314078
Min length21

Characters and Unicode

Total characters150085
Distinct characters347
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

Unique3710 ?
Unique (%)74.9%

Sample

1st row부산광역시 동래구 온천천로471번가길 13, 1층 (안락동)
2nd row부산광역시 동래구 충렬대로107번길 65, 317동 1층 107호 (온천동, 동래 래미안 아이파크)
3rd row부산광역시 동래구 명안로85번길 5, 1층 (명장동)
4th row부산광역시 동래구 명륜로129번길 46, 1층 (명륜동)
5th row부산광역시 동래구 충렬대로 413, 1층 (안락동)
ValueCountFrequency (%)
동래구 4952
 
17.1%
부산광역시 4951
 
17.1%
1층 1618
 
5.6%
온천동 1440
 
5.0%
사직동 911
 
3.1%
안락동 885
 
3.1%
명륜동 754
 
2.6%
명장동 322
 
1.1%
수안동 311
 
1.1%
2층 276
 
1.0%
Other values (2073) 12535
43.3%
2023-12-11T01:00:03.288900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
24008
 
16.0%
동 10620
 
7.1%
1 7128
 
4.7%
시 5440
 
3.6%
래 5310
 
3.5%
부 5003
 
3.3%
) 5002
 
3.3%
( 5002
 
3.3%
역 4985
 
3.3%
구 4978
 
3.3%
Other values (337) 72609
48.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 87222
58.1%
Decimal Number 24121
 
16.1%
Space Separator 24008
 
16.0%
Close Punctuation 5002
 
3.3%
Open Punctuation 5002
 
3.3%
Other Punctuation 3180
 
2.1%
Dash Punctuation 1032
 
0.7%
Uppercase Letter 466
 
0.3%
Math Symbol 39
 
< 0.1%
Lowercase Letter 13
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 10620
 
12.2%
시 5440
 
6.2%
래 5310
 
6.1%
부 5003
 
5.7%
역 4985
 
5.7%
구 4978
 
5.7%
산 4978
 
5.7%
광 4961
 
5.7%
로 4852
 
5.6%
길 2921
 
3.3%
Other values (292) 33174
38.0%
Uppercase Letter
ValueCountFrequency (%)
B 85
18.2%
K 74
15.9%
S 71
15.2%
A 57
12.2%
U 21
 
4.5%
H 21
 
4.5%
Y 21
 
4.5%
V 21
 
4.5%
E 21
 
4.5%
I 20
 
4.3%
Other values (10) 54
11.6%
Decimal Number
ValueCountFrequency (%)
1 7128
29.6%
2 3392
14.1%
3 2622
 
10.9%
4 1945
 
8.1%
5 1702
 
7.1%
0 1592
 
6.6%
7 1505
 
6.2%
9 1495
 
6.2%
8 1411
 
5.8%
6 1329
 
5.5%
Other Punctuation
ValueCountFrequency (%)
, 3174
99.8%
· 2
 
0.1%
. 2
 
0.1%
/ 1
 
< 0.1%
@ 1
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
e 9
69.2%
c 1
 
7.7%
s 1
 
7.7%
k 1
 
7.7%
n 1
 
7.7%
Space Separator
ValueCountFrequency (%)
24008
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5002
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5002
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1032
100.0%
Math Symbol
ValueCountFrequency (%)
~ 39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 87222
58.1%
Common 62384
41.6%
Latin 479
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 10620
 
12.2%
시 5440
 
6.2%
래 5310
 
6.1%
부 5003
 
5.7%
역 4985
 
5.7%
구 4978
 
5.7%
산 4978
 
5.7%
광 4961
 
5.7%
로 4852
 
5.6%
길 2921
 
3.3%
Other values (292) 33174
38.0%
Latin
ValueCountFrequency (%)
B 85
17.7%
K 74
15.4%
S 71
14.8%
A 57
11.9%
U 21
 
4.4%
H 21
 
4.4%
Y 21
 
4.4%
V 21
 
4.4%
E 21
 
4.4%
I 20
 
4.2%
Other values (15) 67
14.0%
Common
ValueCountFrequency (%)
24008
38.5%
1 7128
 
11.4%
) 5002
 
8.0%
( 5002
 
8.0%
2 3392
 
5.4%
, 3174
 
5.1%
3 2622
 
4.2%
4 1945
 
3.1%
5 1702
 
2.7%
0 1592
 
2.6%
Other values (10) 6817
 
10.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 87222
58.1%
ASCII 62861
41.9%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
24008
38.2%
1 7128
 
11.3%
) 5002
 
8.0%
( 5002
 
8.0%
2 3392
 
5.4%
, 3174
 
5.0%
3 2622
 
4.2%
4 1945
 
3.1%
5 1702
 
2.7%
0 1592
 
2.5%
Other values (34) 7294
 
11.6%
Hangul
ValueCountFrequency (%)
동 10620
 
12.2%
시 5440
 
6.2%
래 5310
 
6.1%
부 5003
 
5.7%
역 4985
 
5.7%
구 4978
 
5.7%
산 4978
 
5.7%
광 4961
 
5.7%
로 4852
 
5.6%
길 2921
 
3.3%
Other values (292) 33174
38.0%
None
ValueCountFrequency (%)
· 2
100.0%

소재지(지번)
Text

Distinct3446
Distinct (%)69.5%
Missing3
Missing (%)0.1%
Memory size38.9 KiB
2023-12-11T01:00:03.763724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length44
Mean length21.892562
Min length16

Characters and Unicode

Total characters108609
Distinct characters325
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

Unique2561 ?
Unique (%)51.6%

Sample

1st row부산광역시 동래구 안락동 221-15
2nd row부산광역시 동래구 온천동 1853 동래 래미안 아이파크
3rd row부산광역시 동래구 명장동 132-4
4th row부산광역시 동래구 명륜동 539-6
5th row부산광역시 동래구 안락동 580-1
ValueCountFrequency (%)
동래구 4962
23.4%
부산광역시 4961
23.4%
온천동 1498
 
7.1%
사직동 925
 
4.4%
안락동 893
 
4.2%
명륜동 793
 
3.7%
명장동 327
 
1.5%
수안동 319
 
1.5%
복천동 131
 
0.6%
낙민동 98
 
0.5%
Other values (3562) 6327
29.8%
2023-12-11T01:00:04.377183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21171
19.5%
동 10232
 
9.4%
래 5160
 
4.8%
시 5061
 
4.7%
역 4994
 
4.6%
산 4992
 
4.6%
구 4983
 
4.6%
부 4981
 
4.6%
광 4968
 
4.6%
- 4699
 
4.3%
Other values (315) 37368
34.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 59441
54.7%
Decimal Number 22745
 
20.9%
Space Separator 21171
 
19.5%
Dash Punctuation 4699
 
4.3%
Uppercase Letter 364
 
0.3%
Other Punctuation 58
 
0.1%
Open Punctuation 57
 
0.1%
Close Punctuation 57
 
0.1%
Lowercase Letter 12
 
< 0.1%
Math Symbol 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 10232
17.2%
래 5160
8.7%
시 5061
8.5%
역 4994
8.4%
산 4992
8.4%
구 4983
8.4%
부 4981
8.4%
광 4968
8.4%
천 1687
 
2.8%
온 1536
 
2.6%
Other values (273) 10847
18.2%
Uppercase Letter
ValueCountFrequency (%)
K 77
21.2%
S 74
20.3%
B 36
9.9%
H 22
 
6.0%
U 22
 
6.0%
Y 22
 
6.0%
E 21
 
5.8%
V 21
 
5.8%
W 20
 
5.5%
I 20
 
5.5%
Other values (8) 29
 
8.0%
Decimal Number
ValueCountFrequency (%)
1 4425
19.5%
2 2931
12.9%
4 2904
12.8%
3 2585
11.4%
5 2466
10.8%
6 1718
 
7.6%
7 1594
 
7.0%
0 1446
 
6.4%
9 1431
 
6.3%
8 1245
 
5.5%
Other Punctuation
ValueCountFrequency (%)
, 52
89.7%
. 2
 
3.4%
· 2
 
3.4%
@ 1
 
1.7%
/ 1
 
1.7%
Lowercase Letter
ValueCountFrequency (%)
e 9
75.0%
k 1
 
8.3%
s 1
 
8.3%
n 1
 
8.3%
Space Separator
ValueCountFrequency (%)
21171
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4699
100.0%
Open Punctuation
ValueCountFrequency (%)
( 57
100.0%
Close Punctuation
ValueCountFrequency (%)
) 57
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 59441
54.7%
Common 48792
44.9%
Latin 376
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 10232
17.2%
래 5160
8.7%
시 5061
8.5%
역 4994
8.4%
산 4992
8.4%
구 4983
8.4%
부 4981
8.4%
광 4968
8.4%
천 1687
 
2.8%
온 1536
 
2.6%
Other values (273) 10847
18.2%
Latin
ValueCountFrequency (%)
K 77
20.5%
S 74
19.7%
B 36
9.6%
H 22
 
5.9%
U 22
 
5.9%
Y 22
 
5.9%
E 21
 
5.6%
V 21
 
5.6%
W 20
 
5.3%
I 20
 
5.3%
Other values (12) 41
10.9%
Common
ValueCountFrequency (%)
21171
43.4%
- 4699
 
9.6%
1 4425
 
9.1%
2 2931
 
6.0%
4 2904
 
6.0%
3 2585
 
5.3%
5 2466
 
5.1%
6 1718
 
3.5%
7 1594
 
3.3%
0 1446
 
3.0%
Other values (10) 2853
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 59441
54.7%
ASCII 49166
45.3%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21171
43.1%
- 4699
 
9.6%
1 4425
 
9.0%
2 2931
 
6.0%
4 2904
 
5.9%
3 2585
 
5.3%
5 2466
 
5.0%
6 1718
 
3.5%
7 1594
 
3.2%
0 1446
 
2.9%
Other values (31) 3227
 
6.6%
Hangul
ValueCountFrequency (%)
동 10232
17.2%
래 5160
8.7%
시 5061
8.5%
역 4994
8.4%
산 4992
8.4%
구 4983
8.4%
부 4981
8.4%
광 4968
8.4%
천 1687
 
2.8%
온 1536
 
2.6%
Other values (273) 10847
18.2%
None
ValueCountFrequency (%)
· 2
100.0%

소재지전화
Text

MISSING 

Distinct2107
Distinct (%)95.0%
Missing2745
Missing (%)55.3%
Memory size38.9 KiB
2023-12-11T01:00:04.686462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.863452
Min length5

Characters and Unicode

Total characters26325
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2043 ?
Unique (%)92.1%

Sample

1st row051-556-0451
2nd row051-553-1050
3rd row051-532-9180
4th row051-558-2383
5th row051-505-6330
ValueCountFrequency (%)
051 41
 
1.8%
051-550-2100 4
 
0.2%
051-550-6000 4
 
0.2%
051-668-2500 4
 
0.2%
051-556-3659 3
 
0.1%
051-553-6325 3
 
0.1%
051-559-5501 3
 
0.1%
051-501-7172 2
 
0.1%
051-507-7890 2
 
0.1%
051-554-7600 2
 
0.1%
Other values (2097) 2151
96.9%
2023-12-11T01:00:05.286278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 6637
25.2%
- 4437
16.9%
0 3848
14.6%
1 3189
12.1%
2 1829
 
6.9%
3 1302
 
4.9%
8 1106
 
4.2%
7 1063
 
4.0%
4 979
 
3.7%
6 974
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21888
83.1%
Dash Punctuation 4437
 
16.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 6637
30.3%
0 3848
17.6%
1 3189
14.6%
2 1829
 
8.4%
3 1302
 
5.9%
8 1106
 
5.1%
7 1063
 
4.9%
4 979
 
4.5%
6 974
 
4.4%
9 961
 
4.4%
Dash Punctuation
ValueCountFrequency (%)
- 4437
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 26325
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 6637
25.2%
- 4437
16.9%
0 3848
14.6%
1 3189
12.1%
2 1829
 
6.9%
3 1302
 
4.9%
8 1106
 
4.2%
7 1063
 
4.0%
4 979
 
3.7%
6 974
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26325
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 6637
25.2%
- 4437
16.9%
0 3848
14.6%
1 3189
12.1%
2 1829
 
6.9%
3 1302
 
4.9%
8 1106
 
4.2%
7 1063
 
4.0%
4 979
 
3.7%
6 974
 
3.7%

우편번호(도로명)
Real number (ℝ)

MISSING 

Distinct191
Distinct (%)3.9%
Missing72
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean47793.83
Minimum47700
Maximum47905
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.8 KiB
2023-12-11T01:00:05.501688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum47700
5-th percentile47709
Q147736
median47791.5
Q347849.25
95-th percentile47894
Maximum47905
Range205
Interquartile range (IQR)113.25

Descriptive statistics

Standard deviation61.116504
Coefficient of variation (CV)0.001278753
Kurtosis-1.290792
Mean47793.83
Median Absolute Deviation (MAD)55.5
Skewness0.11371123
Sum2.3380741 × 108
Variance3735.2271
MonotonicityNot monotonic
2023-12-11T01:00:05.660589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
47736 271
 
5.5%
47709 220
 
4.4%
47865 188
 
3.8%
47712 130
 
2.6%
47813 105
 
2.1%
47728 104
 
2.1%
47738 95
 
1.9%
47808 90
 
1.8%
47810 89
 
1.8%
47864 88
 
1.8%
Other values (181) 3512
70.7%
ValueCountFrequency (%)
47700 4
 
0.1%
47701 12
 
0.2%
47702 7
 
0.1%
47703 8
 
0.2%
47704 11
 
0.2%
47705 18
 
0.4%
47706 20
 
0.4%
47707 1
 
< 0.1%
47708 87
 
1.8%
47709 220
4.4%
ValueCountFrequency (%)
47905 17
 
0.3%
47904 3
 
0.1%
47903 5
 
0.1%
47902 2
 
< 0.1%
47901 60
1.2%
47900 84
1.7%
47899 8
 
0.2%
47898 17
 
0.3%
47896 8
 
0.2%
47895 28
 
0.6%

우편번호(지번)
Text

Distinct71
Distinct (%)1.4%
Missing3
Missing (%)0.1%
Memory size38.9 KiB
2023-12-11T01:00:06.217674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters34727
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)0.1%

Sample

1st row607-825
2nd row607-838
3rd row607-809
4th row607-804
5th row607-828
ValueCountFrequency (%)
607-804 593
 
12.0%
607-815 306
 
6.2%
607-833 292
 
5.9%
607-831 252
 
5.1%
607-817 182
 
3.7%
607-824 177
 
3.6%
607-826 169
 
3.4%
607-830 158
 
3.2%
607-827 157
 
3.2%
607-829 152
 
3.1%
Other values (61) 2523
50.9%
2023-12-11T01:00:06.637492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6784
19.5%
7 5590
16.1%
6 5336
15.4%
8 4966
14.3%
- 4961
14.3%
3 1819
 
5.2%
2 1616
 
4.7%
1 1461
 
4.2%
4 1307
 
3.8%
5 597
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 29766
85.7%
Dash Punctuation 4961
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6784
22.8%
7 5590
18.8%
6 5336
17.9%
8 4966
16.7%
3 1819
 
6.1%
2 1616
 
5.4%
1 1461
 
4.9%
4 1307
 
4.4%
5 597
 
2.0%
9 290
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 4961
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 34727
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6784
19.5%
7 5590
16.1%
6 5336
15.4%
8 4966
14.3%
- 4961
14.3%
3 1819
 
5.2%
2 1616
 
4.7%
1 1461
 
4.2%
4 1307
 
3.8%
5 597
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 34727
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6784
19.5%
7 5590
16.1%
6 5336
15.4%
8 4966
14.3%
- 4961
14.3%
3 1819
 
5.2%
2 1616
 
4.7%
1 1461
 
4.2%
4 1307
 
3.8%
5 597
 
1.7%

Interactions

2023-12-11T01:00:00.217529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:00:06.749721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명우편번호(도로명)우편번호(지번)
업종명1.0000.2420.461
우편번호(도로명)0.2421.0000.984
우편번호(지번)0.4610.9841.000
2023-12-11T01:00:06.871810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호(도로명)업종명
우편번호(도로명)1.0000.129
업종명0.1291.000

Missing values

2023-12-11T01:00:00.376196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:00:00.565240image/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.
2023-12-11T01:00:00.769869image/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

신고일자업종명업소명소재지(도로명)소재지(지번)소재지전화우편번호(도로명)우편번호(지번)
02023-09-01휴게음식점너랑나랑노란부산광역시 동래구 온천천로471번가길 13, 1층 (안락동)부산광역시 동래구 안락동 221-15<NA>47900607-825
12023-08-28휴게음식점달콤왕가탕후루 동래래미안아이파크점부산광역시 동래구 충렬대로107번길 65, 317동 1층 107호 (온천동, 동래 래미안 아이파크)부산광역시 동래구 온천동 1853 동래 래미안 아이파크<NA>47730607-838
22023-08-28휴게음식점96분식부산광역시 동래구 명안로85번길 5, 1층 (명장동)부산광역시 동래구 명장동 132-4<NA>47773607-809
32023-08-28휴게음식점달콤왕가탕후루 동래역점부산광역시 동래구 명륜로129번길 46, 1층 (명륜동)부산광역시 동래구 명륜동 539-6<NA>47736607-804
42023-08-25휴게음식점로우라이즈부산광역시 동래구 충렬대로 413, 1층 (안락동)부산광역시 동래구 안락동 580-1<NA>47796607-828
52023-08-25휴게음식점댄싱컵 동래문화상사점부산광역시 동래구 중앙대로1335번길 77, 1층 일부호 (온천동)부산광역시 동래구 온천동 1429-29<NA>47733607-837
62023-08-25휴게음식점지에스25 미남사거리부산광역시 동래구 석사북로 90, 1층 (온천동)부산광역시 동래구 온천동 1247-1<NA>47850607-841
72023-08-23휴게음식점달콤 왕가 탕후루 안락점부산광역시 동래구 삼어로 1, 1층 (안락동)부산광역시 동래구 안락동 471-48<NA>47770607-826
82023-08-17휴게음식점수상한 김밥부산광역시 동래구 명장로 69-3, 1층 (명장동)부산광역시 동래구 명장동 147-9<NA>47769607-809
92023-08-16휴게음식점모브커피(Mov coffee)부산광역시 동래구 명륜로 81, 1층 (수안동)부산광역시 동래구 수안동 3-5 1층<NA>47818607-822
신고일자업종명업소명소재지(도로명)소재지(지번)소재지전화우편번호(도로명)우편번호(지번)
49542004-11-29단란주점파라다이스부산광역시 동래구 온천장로 81 (온천동)부산광역시 동래구 온천동 182-3051-554-556847712607-833
49552004-11-15단란주점조양노래주점부산광역시 동래구 반송로 292 (명장동)부산광역시 동래구 명장동 57-13051-524-151647772607-808
49562003-07-15단란주점해성 단란주점부산광역시 동래구 금강공원로 35-1 (온천동)부산광역시 동래구 온천동 210-38051-555-355047712607-833
49572003-03-05단란주점발리부산광역시 동래구 온천장로 60 (온천동)부산광역시 동래구 온천동 184-15051-554-421247711607-833
49582001-08-21단란주점그린로즈부산광역시 동래구 금강로 83 (온천동)부산광역시 동래구 온천동 197-1051-553-033347706607-833
49592001-01-15단란주점호수부산광역시 동래구 금강공원로 29-2 (온천동)부산광역시 동래구 온천동 210-46051-555-245247712607-833
49601999-11-12단란주점초이스부산광역시 동래구 금강공원로 39 (온천동)부산광역시 동래구 온천동 210-40051-558-363547712607-833
49611999-07-12단란주점은하수포장타운부산광역시 동래구 안락로 17 (안락동)부산광역시 동래구 안락동 426-25051-528-842347782607-827
49621999-05-07단란주점쉬리부산광역시 동래구 금강로124번길 3 (온천동)부산광역시 동래구 온천동 220-1051-554-823347709607-833
49631998-05-27단란주점월드포장센타부산광역시 동래구 충렬대로86번길 32 (온천동)부산광역시 동래구 온천동 1447-4051-506-891147822607-842

Duplicate rows

Most frequently occurring

신고일자업종명업소명소재지(도로명)소재지(지번)소재지전화우편번호(도로명)우편번호(지번)# duplicates
12022-04-19휴게음식점롯데쇼핑(주)롯데마트동래점부산광역시 동래구 중앙대로 1393 (온천동, 롯데마트내)부산광역시 동래구 온천동 502-3 롯데마트내051-668-250047727607-8353
02019-01-18일반음식점메리움컨벤션금강뷔페부산광역시 동래구 충렬대로 63 (온천동)부산광역시 동래구 온천동 1387051-554-760047724607-8372