Overview

Dataset statistics

Number of variables6
Number of observations4968
Missing cells100
Missing cells (%)0.3%
Duplicate rows491
Duplicate rows (%)9.9%
Total size in memory237.9 KiB
Average record size in memory49.0 B

Variable types

Categorical1
Text4
Numeric1

Dataset

Description부산광역시_동래구_식품위생업소현황_20220915
Author부산광역시 동래구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15026505

Alerts

Dataset has 491 (9.9%) duplicate rowsDuplicates
업종명 is highly imbalanced (51.7%)Imbalance
우편번호(도로명) has 76 (1.5%) missing valuesMissing

Reproduction

Analysis started2023-12-10 16:00:10.854554
Analysis finished2023-12-10 16:00:12.242495
Duration1.39 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.9 KiB
일반음식점
3589 
휴게음식점
950 
유흥주점영업
 
162
단란주점
 
147
제과점영업
 
108

Length

Max length6
Median length5
Mean length5.0054348
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반음식점 3589
72.2%
휴게음식점 950
 
19.1%
유흥주점영업 162
 
3.3%
단란주점 147
 
3.0%
제과점영업 108
 
2.2%
위탁급식영업 12
 
0.2%

Length

2023-12-11T01:00:12.323906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:00:12.433429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반음식점 3589
72.2%
휴게음식점 950
 
19.1%
유흥주점영업 162
 
3.3%
단란주점 147
 
3.0%
제과점영업 108
 
2.2%
위탁급식영업 12
 
0.2%

업소명
Text

Distinct4291
Distinct (%)86.4%
Missing0
Missing (%)0.0%
Memory size38.9 KiB
2023-12-11T01:00:12.737118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length25
Mean length6.1821659
Min length1

Characters and Unicode

Total characters30713
Distinct characters952
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3697 ?
Unique (%)74.4%

Sample

1st row열정국밥
2nd row한전구내식당
3rd row차밭골
4th row박가네
5th row한상
ValueCountFrequency (%)
교촌치킨 6
 
0.1%
부산식당 5
 
0.1%
연정 5
 
0.1%
수제맥주집 4
 
0.1%
33떡볶이 4
 
0.1%
아빠와돈까스 4
 
0.1%
남도푸드앤 4
 
0.1%
백두대간 4
 
0.1%
가마치통닭 4
 
0.1%
고봉민김밥인 4
 
0.1%
Other values (4281) 4924
99.1%
2023-12-11T01:00:13.205559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 1192
 
3.9%
이 611
 
2.0%
동 540
 
1.8%
래 511
 
1.7%
스 426
 
1.4%
식 406
 
1.3%
리 394
 
1.3%
( 386
 
1.3%
) 386
 
1.3%
장 370
 
1.2%
Other values (942) 25491
83.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 27417
89.3%
Uppercase Letter 1029
 
3.4%
Lowercase Letter 801
 
2.6%
Decimal Number 561
 
1.8%
Open Punctuation 386
 
1.3%
Close Punctuation 386
 
1.3%
Other Punctuation 119
 
0.4%
Dash Punctuation 11
 
< 0.1%
Math Symbol 1
 
< 0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 1192
 
4.3%
이 611
 
2.2%
동 540
 
2.0%
래 511
 
1.9%
스 426
 
1.6%
식 406
 
1.5%
리 394
 
1.4%
장 370
 
1.3%
사 352
 
1.3%
당 311
 
1.1%
Other values (865) 22304
81.4%
Uppercase Letter
ValueCountFrequency (%)
C 97
 
9.4%
E 92
 
8.9%
O 78
 
7.6%
S 68
 
6.6%
A 64
 
6.2%
B 64
 
6.2%
G 62
 
6.0%
F 53
 
5.2%
T 51
 
5.0%
P 40
 
3.9%
Other values (16) 360
35.0%
Lowercase Letter
ValueCountFrequency (%)
e 141
17.6%
o 68
 
8.5%
a 64
 
8.0%
c 52
 
6.5%
f 47
 
5.9%
i 43
 
5.4%
r 42
 
5.2%
s 40
 
5.0%
n 40
 
5.0%
t 38
 
4.7%
Other values (15) 226
28.2%
Decimal Number
ValueCountFrequency (%)
2 105
18.7%
1 83
14.8%
0 81
14.4%
5 73
13.0%
3 56
10.0%
9 48
8.6%
4 33
 
5.9%
7 32
 
5.7%
8 29
 
5.2%
6 21
 
3.7%
Other Punctuation
ValueCountFrequency (%)
& 50
42.0%
. 27
22.7%
, 19
 
16.0%
' 6
 
5.0%
: 5
 
4.2%
· 3
 
2.5%
/ 3
 
2.5%
! 3
 
2.5%
# 2
 
1.7%
; 1
 
0.8%
Open Punctuation
ValueCountFrequency (%)
( 386
100.0%
Close Punctuation
ValueCountFrequency (%)
) 386
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Math Symbol
ValueCountFrequency (%)
× 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 27380
89.1%
Latin 1831
 
6.0%
Common 1465
 
4.8%
Han 37
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 1192
 
4.4%
이 611
 
2.2%
동 540
 
2.0%
래 511
 
1.9%
스 426
 
1.6%
식 406
 
1.5%
리 394
 
1.4%
장 370
 
1.4%
사 352
 
1.3%
당 311
 
1.1%
Other values (839) 22267
81.3%
Latin
ValueCountFrequency (%)
e 141
 
7.7%
C 97
 
5.3%
E 92
 
5.0%
O 78
 
4.3%
S 68
 
3.7%
o 68
 
3.7%
a 64
 
3.5%
A 64
 
3.5%
B 64
 
3.5%
G 62
 
3.4%
Other values (42) 1033
56.4%
Han
ValueCountFrequency (%)
李 5
 
13.5%
大 2
 
5.4%
利 2
 
5.4%
火 2
 
5.4%
家 2
 
5.4%
眞 2
 
5.4%
氣 2
 
5.4%
高 2
 
5.4%
町 1
 
2.7%
漁 1
 
2.7%
Other values (16) 16
43.2%
Common
ValueCountFrequency (%)
( 386
26.3%
) 386
26.3%
2 105
 
7.2%
1 83
 
5.7%
0 81
 
5.5%
5 73
 
5.0%
3 56
 
3.8%
& 50
 
3.4%
9 48
 
3.3%
4 33
 
2.3%
Other values (15) 164
11.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 27379
89.1%
ASCII 3291
 
10.7%
CJK 32
 
0.1%
CJK Compat Ideographs 5
 
< 0.1%
None 4
 
< 0.1%
Number Forms 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 1192
 
4.4%
이 611
 
2.2%
동 540
 
2.0%
래 511
 
1.9%
스 426
 
1.6%
식 406
 
1.5%
리 394
 
1.4%
장 370
 
1.4%
사 352
 
1.3%
당 311
 
1.1%
Other values (838) 22266
81.3%
ASCII
ValueCountFrequency (%)
( 386
 
11.7%
) 386
 
11.7%
e 141
 
4.3%
2 105
 
3.2%
C 97
 
2.9%
E 92
 
2.8%
1 83
 
2.5%
0 81
 
2.5%
O 78
 
2.4%
5 73
 
2.2%
Other values (64) 1769
53.8%
CJK Compat Ideographs
ValueCountFrequency (%)
李 5
100.0%
None
ValueCountFrequency (%)
· 3
75.0%
× 1
 
25.0%
CJK
ValueCountFrequency (%)
大 2
 
6.2%
利 2
 
6.2%
火 2
 
6.2%
家 2
 
6.2%
眞 2
 
6.2%
氣 2
 
6.2%
高 2
 
6.2%
町 1
 
3.1%
漁 1
 
3.1%
萌 1
 
3.1%
Other values (15) 15
46.9%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅋ 1
100.0%

소재지주소(도로명)
Text

Distinct3871
Distinct (%)78.2%
Missing18
Missing (%)0.4%
Memory size38.9 KiB
2023-12-11T01:00:13.531581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length52
Mean length25.286465
Min length17

Characters and Unicode

Total characters125168
Distinct characters331
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

Unique3138 ?
Unique (%)63.4%

Sample

1st row부산광역시동래구동래로147번길26(복천동)
2nd row부산광역시동래구충렬대로429-5(안락동)
3rd row부산광역시동래구미남로137(온천동)
4th row부산광역시동래구금정마을로105(온천동)
5th row부산광역시동래구금정마을로107-1(온천동)
ValueCountFrequency (%)
부산광역시동래구중앙대로1393,롯데백화점지하1층(온천동 14
 
0.3%
부산광역시동래구충렬대로197(명륜동 14
 
0.3%
부산광역시동래구중앙대로1367번길55(온천동 11
 
0.2%
부산광역시동래구명륜로103번길20(명륜동 11
 
0.2%
부산광역시동래구중앙대로1393,롯데백화점1층(온천동 10
 
0.2%
부산광역시동래구금강로124번길18(온천동 9
 
0.2%
부산광역시동래구삼성대길44(명륜동 9
 
0.2%
부산광역시동래구금강공원로34-12(온천동 8
 
0.2%
부산광역시동래구명륜로129번길20(명륜동 8
 
0.2%
부산광역시동래구안락로27(안락동 8
 
0.2%
Other values (3861) 4848
97.9%
2023-12-11T01:00:14.047679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 10619
 
8.5%
1 6885
 
5.5%
시 5428
 
4.3%
래 5309
 
4.2%
( 4996
 
4.0%
) 4996
 
4.0%
역 4981
 
4.0%
산 4979
 
4.0%
구 4975
 
4.0%
부 4968
 
4.0%
Other values (321) 67032
53.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 86743
69.3%
Decimal Number 23919
 
19.1%
Open Punctuation 4996
 
4.0%
Close Punctuation 4996
 
4.0%
Other Punctuation 3015
 
2.4%
Dash Punctuation 1032
 
0.8%
Uppercase Letter 409
 
0.3%
Math Symbol 43
 
< 0.1%
Lowercase Letter 15
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 10619
 
12.2%
시 5428
 
6.3%
래 5309
 
6.1%
역 4981
 
5.7%
산 4979
 
5.7%
구 4975
 
5.7%
부 4968
 
5.7%
광 4959
 
5.7%
로 4865
 
5.6%
길 2938
 
3.4%
Other values (277) 32722
37.7%
Uppercase Letter
ValueCountFrequency (%)
B 80
19.6%
K 61
14.9%
A 59
14.4%
S 55
13.4%
C 24
 
5.9%
U 19
 
4.6%
Y 19
 
4.6%
H 19
 
4.6%
V 14
 
3.4%
E 14
 
3.4%
Other values (10) 45
11.0%
Decimal Number
ValueCountFrequency (%)
1 6885
28.8%
2 3407
14.2%
3 2595
 
10.8%
4 1932
 
8.1%
5 1678
 
7.0%
0 1602
 
6.7%
9 1551
 
6.5%
7 1521
 
6.4%
8 1412
 
5.9%
6 1336
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 3008
99.8%
. 3
 
0.1%
· 2
 
0.1%
/ 1
 
< 0.1%
@ 1
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
e 11
73.3%
s 1
 
6.7%
c 1
 
6.7%
k 1
 
6.7%
n 1
 
6.7%
Open Punctuation
ValueCountFrequency (%)
( 4996
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4996
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1032
100.0%
Math Symbol
ValueCountFrequency (%)
~ 43
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 86743
69.3%
Common 38001
30.4%
Latin 424
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 10619
 
12.2%
시 5428
 
6.3%
래 5309
 
6.1%
역 4981
 
5.7%
산 4979
 
5.7%
구 4975
 
5.7%
부 4968
 
5.7%
광 4959
 
5.7%
로 4865
 
5.6%
길 2938
 
3.4%
Other values (277) 32722
37.7%
Latin
ValueCountFrequency (%)
B 80
18.9%
K 61
14.4%
A 59
13.9%
S 55
13.0%
C 24
 
5.7%
U 19
 
4.5%
Y 19
 
4.5%
H 19
 
4.5%
V 14
 
3.3%
E 14
 
3.3%
Other values (15) 60
14.2%
Common
ValueCountFrequency (%)
1 6885
18.1%
( 4996
13.1%
) 4996
13.1%
2 3407
9.0%
, 3008
7.9%
3 2595
 
6.8%
4 1932
 
5.1%
5 1678
 
4.4%
0 1602
 
4.2%
9 1551
 
4.1%
Other values (9) 5351
14.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 86743
69.3%
ASCII 38423
30.7%
None 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 10619
 
12.2%
시 5428
 
6.3%
래 5309
 
6.1%
역 4981
 
5.7%
산 4979
 
5.7%
구 4975
 
5.7%
부 4968
 
5.7%
광 4959
 
5.7%
로 4865
 
5.6%
길 2938
 
3.4%
Other values (277) 32722
37.7%
ASCII
ValueCountFrequency (%)
1 6885
17.9%
( 4996
13.0%
) 4996
13.0%
2 3407
8.9%
, 3008
7.8%
3 2595
 
6.8%
4 1932
 
5.0%
5 1678
 
4.4%
0 1602
 
4.2%
9 1551
 
4.0%
Other values (33) 5773
15.0%
None
ValueCountFrequency (%)
· 2
100.0%

소재지주소(지번)
Text

Distinct3164
Distinct (%)63.7%
Missing3
Missing (%)0.1%
Memory size38.9 KiB
2023-12-11T01:00:14.363735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length38
Mean length17.6
Min length12

Characters and Unicode

Total characters87384
Distinct characters309
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

Unique2123 ?
Unique (%)42.8%

Sample

1st row부산광역시동래구복천동164-3
2nd row부산광역시동래구안락동304-3
3rd row부산광역시동래구온천동1422-25
4th row부산광역시동래구온천동1123-1
5th row부산광역시동래구온천동1123-6
ValueCountFrequency (%)
부산광역시동래구복천동229-42동래시장 48
 
1.0%
부산광역시동래구온천동502-3롯데백화점 33
 
0.7%
부산광역시동래구온천동707-1 19
 
0.4%
부산광역시동래구사직동93-6사직동자이언츠파크 18
 
0.4%
부산광역시동래구온천동153-8skhubsky 17
 
0.3%
부산광역시동래구명륜동506-3메가마트 16
 
0.3%
부산광역시동래구명륜동553-12 14
 
0.3%
부산광역시동래구사직동930사직야구장 14
 
0.3%
부산광역시동래구명륜동450-4 14
 
0.3%
부산광역시동래구사직동93-6 11
 
0.2%
Other values (3154) 4761
95.9%
2023-12-11T01:00:14.837694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 10243
 
11.7%
래 5157
 
5.9%
시 5062
 
5.8%
산 5002
 
5.7%
역 4995
 
5.7%
구 4986
 
5.7%
부 4985
 
5.7%
광 4971
 
5.7%
- 4714
 
5.4%
1 4483
 
5.1%
Other values (299) 32786
37.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 59333
67.9%
Decimal Number 22844
 
26.1%
Dash Punctuation 4714
 
5.4%
Uppercase Letter 299
 
0.3%
Other Punctuation 67
 
0.1%
Close Punctuation 54
 
0.1%
Open Punctuation 54
 
0.1%
Lowercase Letter 14
 
< 0.1%
Math Symbol 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 10243
17.3%
래 5157
8.7%
시 5062
8.5%
산 5002
8.4%
역 4995
8.4%
구 4986
8.4%
부 4985
8.4%
광 4971
8.4%
천 1736
 
2.9%
온 1579
 
2.7%
Other values (258) 10617
17.9%
Uppercase Letter
ValueCountFrequency (%)
K 62
20.7%
S 56
18.7%
B 32
10.7%
Y 19
 
6.4%
H 19
 
6.4%
U 19
 
6.4%
C 15
 
5.0%
V 14
 
4.7%
E 14
 
4.7%
W 13
 
4.3%
Other values (8) 36
12.0%
Decimal Number
ValueCountFrequency (%)
1 4483
19.6%
2 2938
12.9%
4 2921
12.8%
3 2605
11.4%
5 2440
10.7%
6 1719
 
7.5%
7 1631
 
7.1%
9 1461
 
6.4%
0 1453
 
6.4%
8 1193
 
5.2%
Other Punctuation
ValueCountFrequency (%)
, 61
91.0%
. 2
 
3.0%
· 2
 
3.0%
@ 1
 
1.5%
/ 1
 
1.5%
Lowercase Letter
ValueCountFrequency (%)
e 11
78.6%
s 1
 
7.1%
k 1
 
7.1%
n 1
 
7.1%
Dash Punctuation
ValueCountFrequency (%)
- 4714
100.0%
Close Punctuation
ValueCountFrequency (%)
) 54
100.0%
Open Punctuation
ValueCountFrequency (%)
( 54
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 59333
67.9%
Common 27738
31.7%
Latin 313
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 10243
17.3%
래 5157
8.7%
시 5062
8.5%
산 5002
8.4%
역 4995
8.4%
구 4986
8.4%
부 4985
8.4%
광 4971
8.4%
천 1736
 
2.9%
온 1579
 
2.7%
Other values (258) 10617
17.9%
Latin
ValueCountFrequency (%)
K 62
19.8%
S 56
17.9%
B 32
10.2%
Y 19
 
6.1%
H 19
 
6.1%
U 19
 
6.1%
C 15
 
4.8%
V 14
 
4.5%
E 14
 
4.5%
W 13
 
4.2%
Other values (12) 50
16.0%
Common
ValueCountFrequency (%)
- 4714
17.0%
1 4483
16.2%
2 2938
10.6%
4 2921
10.5%
3 2605
9.4%
5 2440
8.8%
6 1719
 
6.2%
7 1631
 
5.9%
9 1461
 
5.3%
0 1453
 
5.2%
Other values (9) 1373
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 59333
67.9%
ASCII 28049
32.1%
None 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 10243
17.3%
래 5157
8.7%
시 5062
8.5%
산 5002
8.4%
역 4995
8.4%
구 4986
8.4%
부 4985
8.4%
광 4971
8.4%
천 1736
 
2.9%
온 1579
 
2.7%
Other values (258) 10617
17.9%
ASCII
ValueCountFrequency (%)
- 4714
16.8%
1 4483
16.0%
2 2938
10.5%
4 2921
10.4%
3 2605
9.3%
5 2440
8.7%
6 1719
 
6.1%
7 1631
 
5.8%
9 1461
 
5.2%
0 1453
 
5.2%
Other values (30) 1684
 
6.0%
None
ValueCountFrequency (%)
· 2
100.0%

우편번호(도로명)
Real number (ℝ)

MISSING 

Distinct191
Distinct (%)3.9%
Missing76
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean47794.162
Minimum47700
Maximum47905
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.8 KiB
2023-12-11T01:00:15.027400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum47700
5-th percentile47709
Q147736
median47793
Q347846
95-th percentile47893
Maximum47905
Range205
Interquartile range (IQR)110

Descriptive statistics

Standard deviation60.607777
Coefficient of variation (CV)0.0012681
Kurtosis-1.2727368
Mean47794.162
Median Absolute Deviation (MAD)57
Skewness0.090049764
Sum2.3380904 × 108
Variance3673.3026
MonotonicityNot monotonic
2023-12-11T01:00:15.172787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
47736 239
 
4.8%
47709 218
 
4.4%
47865 178
 
3.6%
47712 116
 
2.3%
47813 114
 
2.3%
47728 99
 
2.0%
47708 92
 
1.9%
47810 88
 
1.8%
47738 87
 
1.8%
47808 86
 
1.7%
Other values (181) 3575
72.0%
ValueCountFrequency (%)
47700 7
 
0.1%
47701 12
 
0.2%
47702 9
 
0.2%
47703 10
 
0.2%
47704 11
 
0.2%
47705 18
 
0.4%
47706 20
 
0.4%
47707 1
 
< 0.1%
47708 92
1.9%
47709 218
4.4%
ValueCountFrequency (%)
47905 15
 
0.3%
47904 2
 
< 0.1%
47903 5
 
0.1%
47902 2
 
< 0.1%
47901 57
1.1%
47900 82
1.7%
47899 8
 
0.2%
47898 14
 
0.3%
47896 6
 
0.1%
47895 26
 
0.5%

우편번호(지번)
Text

Distinct71
Distinct (%)1.4%
Missing3
Missing (%)0.1%
Memory size38.9 KiB
2023-12-11T01:00:15.405272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters34755
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

Unique5 ?
Unique (%)0.1%

Sample

1st row607-020
2nd row607-826
3rd row607-842
4th row607-838
5th row607-838
ValueCountFrequency (%)
607-804 535
 
10.8%
607-833 289
 
5.8%
607-815 285
 
5.7%
607-831 248
 
5.0%
607-824 191
 
3.8%
607-817 177
 
3.6%
607-830 168
 
3.4%
607-827 165
 
3.3%
607-826 157
 
3.2%
607-835 156
 
3.1%
Other values (61) 2594
52.2%
2023-12-11T01:00:15.786696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6769
19.5%
7 5598
16.1%
6 5334
15.3%
8 4981
14.3%
- 4965
14.3%
3 1869
 
5.4%
2 1612
 
4.6%
1 1464
 
4.2%
4 1286
 
3.7%
5 586
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 29790
85.7%
Dash Punctuation 4965
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6769
22.7%
7 5598
18.8%
6 5334
17.9%
8 4981
16.7%
3 1869
 
6.3%
2 1612
 
5.4%
1 1464
 
4.9%
4 1286
 
4.3%
5 586
 
2.0%
9 291
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 4965
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 34755
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6769
19.5%
7 5598
16.1%
6 5334
15.3%
8 4981
14.3%
- 4965
14.3%
3 1869
 
5.4%
2 1612
 
4.6%
1 1464
 
4.2%
4 1286
 
3.7%
5 586
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 34755
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6769
19.5%
7 5598
16.1%
6 5334
15.3%
8 4981
14.3%
- 4965
14.3%
3 1869
 
5.4%
2 1612
 
4.6%
1 1464
 
4.2%
4 1286
 
3.7%
5 586
 
1.7%

Interactions

2023-12-11T01:00:11.795486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:00:15.886123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명우편번호(도로명)우편번호(지번)
업종명1.0000.2340.446
우편번호(도로명)0.2341.0000.984
우편번호(지번)0.4460.9841.000
2023-12-11T01:00:15.965270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호(도로명)업종명
우편번호(도로명)1.0000.124
업종명0.1241.000

Missing values

2023-12-11T01:00:11.940118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:00:12.059857image/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.
2023-12-11T01:00:12.172227image/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

업종명업소명소재지주소(도로명)소재지주소(지번)우편번호(도로명)우편번호(지번)
0일반음식점열정국밥부산광역시동래구동래로147번길26(복천동)부산광역시동래구복천동164-347802607-020
1일반음식점한전구내식당부산광역시동래구충렬대로429-5(안락동)부산광역시동래구안락동304-347790607-826
2일반음식점차밭골부산광역시동래구미남로137(온천동)부산광역시동래구온천동1422-2547837607-842
3일반음식점박가네부산광역시동래구금정마을로105(온천동)부산광역시동래구온천동1123-147718607-838
4일반음식점한상부산광역시동래구금정마을로107-1(온천동)부산광역시동래구온천동1123-647718607-838
5일반음식점최부자집부산광역시동래구중앙대로1381번길66-6(온천동)부산광역시동래구온천동771-1547725607-835
6일반음식점대궐집부산광역시동래구동래로136번길26(복천동)부산광역시동래구복천동319-347809607-020
7일반음식점우리들식당<NA>부산광역시동래구명륜동680-5<NA>607-806
8일반음식점눈물떡볶이부산사직점부산광역시동래구사직북로48번길25(사직동)부산광역시동래구사직동16-147855607-120
9일반음식점대관원부산광역시동래구충렬대로137번길30(온천동)부산광역시동래구온천동1435-147734607-837
업종명업소명소재지주소(도로명)소재지주소(지번)우편번호(도로명)우편번호(지번)
4958제과점영업로카보어테이블부산광역시동래구중앙대로1393,롯데백화점1층(온천동)부산광역시동래구온천동502-3롯데백화점47727607-716
4959제과점영업버터풀앤크리멀러스쁘띠부산광역시동래구중앙대로1393,롯데백화점1층(온천동)부산광역시동래구온천동502-3롯데백화점47727607-716
4960제과점영업버터풀앤크리멀러스부산광역시동래구중앙대로1393,롯데백화점1층(온천동)부산광역시동래구온천동502-3롯데백화점47727607-716
4961제과점영업오블롱(OBLONG)부산광역시동래구아시아드대로202,1층3호(온천동,e편한세상동래아시아드아파트)부산광역시동래구온천동1550-3e편한세상동래아시아드아파트47839607-841
4962제과점영업미정(米情)제과부산광역시동래구우장춘로10,동림빌딩2층(온천동)부산광역시동래구온천동1401-1447731607-837
4963제과점영업뚜레쥬르부산동래래미안점부산광역시동래구충렬대로107번길65,317동113,114호(온천동,동래래미안아이파크)부산광역시동래구온천동835동래래미안아이파크317동47730607-837
4964제과점영업파리바게뜨동래래미안아이파크점부산광역시동래구충렬대로107번길65,316동108,109호(온천동,동래래미안아이파크)부산광역시동래구온천동835동래래미안아이파크316동47730607-837
4965제과점영업이응시옷이응부산광역시동래구중앙대로1523,SKHUBSKY제5층제B5-01호(온천동)부산광역시동래구온천동153-8SKHUBSKY47710607-831
4966제과점영업더빵부산광역시동래구차밭골로13,메디컬센터빌딩1층101호(온천동)부산광역시동래구온천동185-647713607-833
4967제과점영업글로어동래미남점부산광역시동래구충렬대로107번길65,상가318동111호(온천동,동래래미안아이파크)부산광역시동래구온천동835동래래미안아이파크47730607-837

Duplicate rows

Most frequently occurring

업종명업소명소재지주소(도로명)소재지주소(지번)우편번호(도로명)우편번호(지번)# duplicates
490휴게음식점롯데쇼핑(주)롯데마트동래점부산광역시동래구중앙대로1393(온천동,롯데마트내)부산광역시동래구온천동502-3롯데마트내47727607-8353
0일반음식점(신)조방낙지부산광역시동래구종합운동장로54번길5(사직동)부산광역시동래구사직동99-3447875607-8172
1일반음식점303화덕온천본점부산광역시동래구차밭골로37(온천동)부산광역시동래구온천동303-447706607-8342
2일반음식점700장식당부산광역시동래구미남로67(사직동)부산광역시동래구사직동136-647841607-8162
3일반음식점7080라이브부산광역시동래구중앙대로1367번길52(온천동)부산광역시동래구온천동751-1347728607-8352
4일반음식점BHC치킨부산광역시동래구사직북로34번길6(사직동)부산광역시동래구사직동48-1447859607-8142
5일반음식점BHC치킨부산광역시동래구안락로27(안락동)부산광역시동래구안락동428-347783607-8282
6일반음식점DK치킨부산광역시동래구충렬대로108번길46(온천동)부산광역시동래구온천동1451-5947826607-8432
7일반음식점FM(에프엠)부산광역시동래구사직로56,1~2층(사직동)부산광역시동래구사직동92-1847865607-8152
8일반음식점OK식육식당부산광역시동래구사직북로5번길18-2(사직동)부산광역시동래구사직동91-1847865607-8152