Overview

Dataset statistics

Number of variables8
Number of observations48
Missing cells27
Missing cells (%)7.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.2 KiB
Average record size in memory67.8 B

Variable types

Text6
Categorical1
Numeric1

Dataset

Description부산광역시 동래구 관내 식품제조가공업소 현황에 대한 데이터로 업소명, 업종, 전화번호, 도로명주소, 지번주소, 우편번호, 식품종류 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/3081201/fileData.do

Alerts

업종 has constant value ""Constant
전화번호 has 26 (54.2%) missing valuesMissing
우편번호(도로명) has 1 (2.1%) missing valuesMissing
업소명 has unique valuesUnique
소재지(도로명) has unique valuesUnique
소재지(지번) has unique valuesUnique

Reproduction

Analysis started2023-12-12 18:17:49.129417
Analysis finished2023-12-12 18:17:49.930453
Duration0.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

UNIQUE 

Distinct48
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size516.0 B
2023-12-13T03:17:50.078580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length12
Mean length6.3541667
Min length2

Characters and Unicode

Total characters305
Distinct characters146
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)100.0%

Sample

1st row(주)달콤나라앨리스
2nd row(주)메가마트동래점 바스키아
3rd row(주)명진푸드
4th row(주)순곱이네프렌차이즈
5th row(주)씨케이케이코리아
ValueCountFrequency (%)
주식회사 2
 
3.7%
수안커피컴퍼니 1
 
1.9%
푸드드림 1
 
1.9%
스무스푼 1
 
1.9%
스톡데일커피로스터스 1
 
1.9%
신성씨푸드 1
 
1.9%
아코마 1
 
1.9%
영진식품 1
 
1.9%
오라 1
 
1.9%
원조미성왕만두 1
 
1.9%
Other values (43) 43
79.6%
2023-12-13T03:17:50.496109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 14
 
4.6%
( 13
 
4.3%
) 12
 
3.9%
이 9
 
3.0%
리 8
 
2.6%
스 8
 
2.6%
커 7
 
2.3%
피 6
 
2.0%
식 6
 
2.0%
6
 
2.0%
Other values (136) 216
70.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 269
88.2%
Open Punctuation 13
 
4.3%
Close Punctuation 12
 
3.9%
Space Separator 6
 
2.0%
Uppercase Letter 3
 
1.0%
Decimal Number 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 14
 
5.2%
이 9
 
3.3%
리 8
 
3.0%
스 8
 
3.0%
커 7
 
2.6%
피 6
 
2.2%
식 6
 
2.2%
드 5
 
1.9%
아 4
 
1.5%
품 4
 
1.5%
Other values (128) 198
73.6%
Uppercase Letter
ValueCountFrequency (%)
S 1
33.3%
N 1
33.3%
D 1
33.3%
Decimal Number
ValueCountFrequency (%)
4 1
50.0%
2 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 269
88.2%
Common 33
 
10.8%
Latin 3
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 14
 
5.2%
이 9
 
3.3%
리 8
 
3.0%
스 8
 
3.0%
커 7
 
2.6%
피 6
 
2.2%
식 6
 
2.2%
드 5
 
1.9%
아 4
 
1.5%
품 4
 
1.5%
Other values (128) 198
73.6%
Common
ValueCountFrequency (%)
( 13
39.4%
) 12
36.4%
6
18.2%
4 1
 
3.0%
2 1
 
3.0%
Latin
ValueCountFrequency (%)
S 1
33.3%
N 1
33.3%
D 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 269
88.2%
ASCII 36
 
11.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 14
 
5.2%
이 9
 
3.3%
리 8
 
3.0%
스 8
 
3.0%
커 7
 
2.6%
피 6
 
2.2%
식 6
 
2.2%
드 5
 
1.9%
아 4
 
1.5%
품 4
 
1.5%
Other values (128) 198
73.6%
ASCII
ValueCountFrequency (%)
( 13
36.1%
) 12
33.3%
6
16.7%
S 1
 
2.8%
N 1
 
2.8%
D 1
 
2.8%
4 1
 
2.8%
2 1
 
2.8%

업종
Categorical

CONSTANT 

Distinct1
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size516.0 B
식품제조가공업
48 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 48
100.0%

Length

2023-12-13T03:17:50.621521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:17:50.715971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 48
100.0%

전화번호
Text

MISSING 

Distinct22
Distinct (%)100.0%
Missing26
Missing (%)54.2%
Memory size516.0 B
2023-12-13T03:17:50.885129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters264
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

Unique22 ?
Unique (%)100.0%

Sample

1st row051-550-6021
2nd row051-555-6611
3rd row051-504-9020
4th row051-506-6565
5th row051-507-7833
ValueCountFrequency (%)
051-550-6021 1
 
4.5%
051-555-6611 1
 
4.5%
051-507-8995 1
 
4.5%
051-867-5325 1
 
4.5%
051-552-6002 1
 
4.5%
051-557-7776 1
 
4.5%
051-527-5414 1
 
4.5%
051-556-8508 1
 
4.5%
051-555-2219 1
 
4.5%
051-527-0711 1
 
4.5%
Other values (12) 12
54.5%
2023-12-13T03:17:51.226824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 66
25.0%
- 44
16.7%
0 40
15.2%
1 33
12.5%
7 18
 
6.8%
2 15
 
5.7%
6 13
 
4.9%
3 13
 
4.9%
9 8
 
3.0%
4 7
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 220
83.3%
Dash Punctuation 44
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 66
30.0%
0 40
18.2%
1 33
15.0%
7 18
 
8.2%
2 15
 
6.8%
6 13
 
5.9%
3 13
 
5.9%
9 8
 
3.6%
4 7
 
3.2%
8 7
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 44
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 264
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 66
25.0%
- 44
16.7%
0 40
15.2%
1 33
12.5%
7 18
 
6.8%
2 15
 
5.7%
6 13
 
4.9%
3 13
 
4.9%
9 8
 
3.0%
4 7
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 264
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 66
25.0%
- 44
16.7%
0 40
15.2%
1 33
12.5%
7 18
 
6.8%
2 15
 
5.7%
6 13
 
4.9%
3 13
 
4.9%
9 8
 
3.0%
4 7
 
2.7%

소재지(도로명)
Text

UNIQUE 

Distinct48
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size516.0 B
2023-12-13T03:17:51.536208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length37
Mean length30.520833
Min length22

Characters and Unicode

Total characters1465
Distinct characters94
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

Unique48 ?
Unique (%)100.0%

Sample

1st row부산광역시 동래구 온천장로 108-6, 3층 (온천동)
2nd row부산광역시 동래구 충렬대로 197 (명륜동)
3rd row부산광역시 동래구 명안로10번길 82, 1층 (안락동)
4th row부산광역시 동래구 명륜로 105, 502호 (명륜동, 동일빌딩)
5th row부산광역시 동래구 명안로26번길 140-4, 1층 (안락동)
ValueCountFrequency (%)
부산광역시 48
16.8%
동래구 48
16.8%
1층 18
 
6.3%
안락동 16
 
5.6%
온천동 10
 
3.5%
사직동 10
 
3.5%
2층 7
 
2.5%
명륜동 5
 
1.8%
명장동 3
 
1.1%
49 3
 
1.1%
Other values (105) 117
41.1%
2023-12-13T03:17:52.005862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
237
 
16.2%
동 100
 
6.8%
1 66
 
4.5%
시 53
 
3.6%
래 51
 
3.5%
산 49
 
3.3%
부 48
 
3.3%
로 48
 
3.3%
) 48
 
3.3%
( 48
 
3.3%
Other values (84) 717
48.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 842
57.5%
Space Separator 237
 
16.2%
Decimal Number 237
 
16.2%
Close Punctuation 48
 
3.3%
Open Punctuation 48
 
3.3%
Other Punctuation 38
 
2.6%
Dash Punctuation 11
 
0.8%
Math Symbol 2
 
0.1%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 100
 
11.9%
시 53
 
6.3%
래 51
 
6.1%
산 49
 
5.8%
부 48
 
5.7%
로 48
 
5.7%
구 48
 
5.7%
역 48
 
5.7%
광 48
 
5.7%
층 31
 
3.7%
Other values (66) 318
37.8%
Decimal Number
ValueCountFrequency (%)
1 66
27.8%
2 33
13.9%
4 25
 
10.5%
5 23
 
9.7%
3 22
 
9.3%
9 17
 
7.2%
0 14
 
5.9%
6 13
 
5.5%
8 12
 
5.1%
7 12
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
L 1
50.0%
G 1
50.0%
Space Separator
ValueCountFrequency (%)
237
100.0%
Close Punctuation
ValueCountFrequency (%)
) 48
100.0%
Open Punctuation
ValueCountFrequency (%)
( 48
100.0%
Other Punctuation
ValueCountFrequency (%)
, 38
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 842
57.5%
Common 621
42.4%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 100
 
11.9%
시 53
 
6.3%
래 51
 
6.1%
산 49
 
5.8%
부 48
 
5.7%
로 48
 
5.7%
구 48
 
5.7%
역 48
 
5.7%
광 48
 
5.7%
층 31
 
3.7%
Other values (66) 318
37.8%
Common
ValueCountFrequency (%)
237
38.2%
1 66
 
10.6%
) 48
 
7.7%
( 48
 
7.7%
, 38
 
6.1%
2 33
 
5.3%
4 25
 
4.0%
5 23
 
3.7%
3 22
 
3.5%
9 17
 
2.7%
Other values (6) 64
 
10.3%
Latin
ValueCountFrequency (%)
L 1
50.0%
G 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 842
57.5%
ASCII 623
42.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
237
38.0%
1 66
 
10.6%
) 48
 
7.7%
( 48
 
7.7%
, 38
 
6.1%
2 33
 
5.3%
4 25
 
4.0%
5 23
 
3.7%
3 22
 
3.5%
9 17
 
2.7%
Other values (8) 66
 
10.6%
Hangul
ValueCountFrequency (%)
동 100
 
11.9%
시 53
 
6.3%
래 51
 
6.1%
산 49
 
5.8%
부 48
 
5.7%
로 48
 
5.7%
구 48
 
5.7%
역 48
 
5.7%
광 48
 
5.7%
층 31
 
3.7%
Other values (66) 318
37.8%

소재지(지번)
Text

UNIQUE 

Distinct48
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size516.0 B
2023-12-13T03:17:52.263929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length31
Mean length22.354167
Min length19

Characters and Unicode

Total characters1073
Distinct characters63
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)100.0%

Sample

1st row부산광역시 동래구 온천동 155-12
2nd row부산광역시 동래구 명륜동 506-3
3rd row부산광역시 동래구 안락동 459-9
4th row부산광역시 동래구 명륜동 418
5th row부산광역시 동래구 안락동 470-56
ValueCountFrequency (%)
부산광역시 48
23.8%
동래구 48
23.8%
안락동 16
 
7.9%
온천동 10
 
5.0%
사직동 10
 
5.0%
명륜동 5
 
2.5%
명장동 3
 
1.5%
수안동 2
 
1.0%
43-12 1
 
0.5%
981-47 1
 
0.5%
Other values (58) 58
28.7%
2023-12-13T03:17:52.688089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
243
22.6%
동 98
 
9.1%
래 50
 
4.7%
산 49
 
4.6%
부 48
 
4.5%
광 48
 
4.5%
역 48
 
4.5%
시 48
 
4.5%
구 48
 
4.5%
- 45
 
4.2%
Other values (53) 348
32.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 565
52.7%
Space Separator 243
22.6%
Decimal Number 218
 
20.3%
Dash Punctuation 45
 
4.2%
Uppercase Letter 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 98
17.3%
래 50
8.8%
산 49
8.7%
부 48
8.5%
광 48
8.5%
역 48
8.5%
시 48
8.5%
구 48
8.5%
안 18
 
3.2%
락 16
 
2.8%
Other values (39) 94
16.6%
Decimal Number
ValueCountFrequency (%)
1 44
20.2%
4 33
15.1%
2 27
12.4%
5 23
10.6%
3 21
9.6%
6 19
8.7%
0 15
 
6.9%
8 14
 
6.4%
9 13
 
6.0%
7 9
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
G 1
50.0%
L 1
50.0%
Space Separator
ValueCountFrequency (%)
243
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 45
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 565
52.7%
Common 506
47.2%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 98
17.3%
래 50
8.8%
산 49
8.7%
부 48
8.5%
광 48
8.5%
역 48
8.5%
시 48
8.5%
구 48
8.5%
안 18
 
3.2%
락 16
 
2.8%
Other values (39) 94
16.6%
Common
ValueCountFrequency (%)
243
48.0%
- 45
 
8.9%
1 44
 
8.7%
4 33
 
6.5%
2 27
 
5.3%
5 23
 
4.5%
3 21
 
4.2%
6 19
 
3.8%
0 15
 
3.0%
8 14
 
2.8%
Other values (2) 22
 
4.3%
Latin
ValueCountFrequency (%)
G 1
50.0%
L 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 565
52.7%
ASCII 508
47.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
243
47.8%
- 45
 
8.9%
1 44
 
8.7%
4 33
 
6.5%
2 27
 
5.3%
5 23
 
4.5%
3 21
 
4.1%
6 19
 
3.7%
0 15
 
3.0%
8 14
 
2.8%
Other values (4) 24
 
4.7%
Hangul
ValueCountFrequency (%)
동 98
17.3%
래 50
8.8%
산 49
8.7%
부 48
8.5%
광 48
8.5%
역 48
8.5%
시 48
8.5%
구 48
8.5%
안 18
 
3.2%
락 16
 
2.8%
Other values (39) 94
16.6%

우편번호(도로명)
Real number (ℝ)

MISSING 

Distinct41
Distinct (%)87.2%
Missing1
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean47810.681
Minimum47706
Maximum47905
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-13T03:17:52.857493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum47706
5-th percentile47710.6
Q147758
median47809
Q347860
95-th percentile47900.7
Maximum47905
Range199
Interquartile range (IQR)102

Descriptive statistics

Standard deviation62.502907
Coefficient of variation (CV)0.0013073001
Kurtosis-1.1350931
Mean47810.681
Median Absolute Deviation (MAD)52
Skewness-0.15763364
Sum2247102
Variance3906.6133
MonotonicityNot monotonic
2023-12-13T03:17:53.033444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
47843 2
 
4.2%
47846 2
 
4.2%
47712 2
 
4.2%
47791 2
 
4.2%
47901 2
 
4.2%
47856 2
 
4.2%
47710 1
 
2.1%
47889 1
 
2.1%
47841 1
 
2.1%
47776 1
 
2.1%
Other values (31) 31
64.6%
ValueCountFrequency (%)
47706 1
2.1%
47708 1
2.1%
47710 1
2.1%
47712 2
4.2%
47713 1
2.1%
47735 1
2.1%
47737 1
2.1%
47738 1
2.1%
47747 1
2.1%
47753 1
2.1%
ValueCountFrequency (%)
47905 1
2.1%
47901 2
4.2%
47900 1
2.1%
47899 1
2.1%
47898 1
2.1%
47889 1
2.1%
47882 1
2.1%
47877 1
2.1%
47873 1
2.1%
47865 1
2.1%

우편번호(지번)
Text

Distinct28
Distinct (%)58.3%
Missing0
Missing (%)0.0%
Memory size516.0 B
2023-12-13T03:17:53.252958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters336
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

Unique16 ?
Unique (%)33.3%

Sample

1st row607-831
2nd row607-804
3rd row607-826
4th row607-804
5th row607-826
ValueCountFrequency (%)
607-826 4
 
8.3%
607-825 4
 
8.3%
607-834 3
 
6.2%
607-804 3
 
6.2%
607-829 3
 
6.2%
607-818 3
 
6.2%
607-833 2
 
4.2%
607-827 2
 
4.2%
607-828 2
 
4.2%
607-815 2
 
4.2%
Other values (18) 20
41.7%
2023-12-13T03:17:53.566093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 62
18.5%
6 55
16.4%
7 51
15.2%
8 51
15.2%
- 48
14.3%
2 19
 
5.7%
3 15
 
4.5%
1 13
 
3.9%
4 9
 
2.7%
5 8
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 288
85.7%
Dash Punctuation 48
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 62
21.5%
6 55
19.1%
7 51
17.7%
8 51
17.7%
2 19
 
6.6%
3 15
 
5.2%
1 13
 
4.5%
4 9
 
3.1%
5 8
 
2.8%
9 5
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 336
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 62
18.5%
6 55
16.4%
7 51
15.2%
8 51
15.2%
- 48
14.3%
2 19
 
5.7%
3 15
 
4.5%
1 13
 
3.9%
4 9
 
2.7%
5 8
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 336
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 62
18.5%
6 55
16.4%
7 51
15.2%
8 51
15.2%
- 48
14.3%
2 19
 
5.7%
3 15
 
4.5%
1 13
 
3.9%
4 9
 
2.7%
5 8
 
2.4%

식품의종류
Text

Distinct35
Distinct (%)72.9%
Missing0
Missing (%)0.0%
Memory size516.0 B
2023-12-13T03:17:53.770613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length16
Mean length11.520833
Min length2

Characters and Unicode

Total characters553
Distinct characters45
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)56.2%

Sample

1st row수산가공식품류, 기타식품류
2nd row과자류, 빵또는떡류, 빵또는떡류, 과자류, 빵류 또는 떡류
3rd row조미식품, 절임류 또는 조림류
4th row소스류
5th row조미식품, 즉석식품류
ValueCountFrequency (%)
음료류 20
16.9%
조미식품 10
 
8.5%
또는 9
 
7.6%
기타식품류 9
 
7.6%
과자류 8
 
6.8%
커피 7
 
5.9%
빵류 6
 
5.1%
규격외일반가공식품 6
 
5.1%
빵또는떡류 6
 
5.1%
다류 5
 
4.2%
Other values (14) 32
27.1%
2023-12-13T03:17:54.092058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
류 83
15.0%
72
 
13.0%
, 52
 
9.4%
식 36
 
6.5%
품 36
 
6.5%
음 20
 
3.6%
료 20
 
3.6%
는 15
 
2.7%
또 15
 
2.7%
조 14
 
2.5%
Other values (35) 190
34.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 429
77.6%
Space Separator 72
 
13.0%
Other Punctuation 52
 
9.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
류 83
19.3%
식 36
 
8.4%
품 36
 
8.4%
음 20
 
4.7%
료 20
 
4.7%
는 15
 
3.5%
또 15
 
3.5%
조 14
 
3.3%
빵 12
 
2.8%
가 12
 
2.8%
Other values (33) 166
38.7%
Space Separator
ValueCountFrequency (%)
72
100.0%
Other Punctuation
ValueCountFrequency (%)
, 52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 429
77.6%
Common 124
 
22.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
류 83
19.3%
식 36
 
8.4%
품 36
 
8.4%
음 20
 
4.7%
료 20
 
4.7%
는 15
 
3.5%
또 15
 
3.5%
조 14
 
3.3%
빵 12
 
2.8%
가 12
 
2.8%
Other values (33) 166
38.7%
Common
ValueCountFrequency (%)
72
58.1%
, 52
41.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 429
77.6%
ASCII 124
 
22.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
류 83
19.3%
식 36
 
8.4%
품 36
 
8.4%
음 20
 
4.7%
료 20
 
4.7%
는 15
 
3.5%
또 15
 
3.5%
조 14
 
3.3%
빵 12
 
2.8%
가 12
 
2.8%
Other values (33) 166
38.7%
ASCII
ValueCountFrequency (%)
72
58.1%
, 52
41.9%

Interactions

2023-12-13T03:17:49.559287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:17:54.191433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명전화번호소재지(도로명)소재지(지번)우편번호(도로명)우편번호(지번)식품의종류
업소명1.0001.0001.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.000
소재지(도로명)1.0001.0001.0001.0001.0001.0001.000
소재지(지번)1.0001.0001.0001.0001.0001.0001.000
우편번호(도로명)1.0001.0001.0001.0001.0000.9800.769
우편번호(지번)1.0001.0001.0001.0000.9801.0000.731
식품의종류1.0001.0001.0001.0000.7690.7311.000

Missing values

2023-12-13T03:17:49.676753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:17:49.783587image/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.
2023-12-13T03:17:49.877836image/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

업소명업종전화번호소재지(도로명)소재지(지번)우편번호(도로명)우편번호(지번)식품의종류
0(주)달콤나라앨리스식품제조가공업<NA>부산광역시 동래구 온천장로 108-6, 3층 (온천동)부산광역시 동래구 온천동 155-1247710607-831수산가공식품류, 기타식품류
1(주)메가마트동래점 바스키아식품제조가공업051-550-6021부산광역시 동래구 충렬대로 197 (명륜동)부산광역시 동래구 명륜동 506-347737607-804과자류, 빵또는떡류, 빵또는떡류, 과자류, 빵류 또는 떡류
2(주)명진푸드식품제조가공업<NA>부산광역시 동래구 명안로10번길 82, 1층 (안락동)부산광역시 동래구 안락동 459-947795607-826조미식품, 절임류 또는 조림류
3(주)순곱이네프렌차이즈식품제조가공업051-555-6611부산광역시 동래구 명륜로 105, 502호 (명륜동, 동일빌딩)부산광역시 동래구 명륜동 41847738607-804소스류
4(주)씨케이케이코리아식품제조가공업<NA>부산광역시 동래구 명안로26번길 140-4, 1층 (안락동)부산광역시 동래구 안락동 470-5647794607-826조미식품, 즉석식품류
5(주)제이알지코리아식품제조가공업051-504-9020부산광역시 동래구 아시아드대로255번길 9, 5층 (온천동)부산광역시 동래구 온천동 128647846607-839음료류, 음료류, 음료류
6(주)제이에이치더블유케익앤브레드봉식품제조가공업<NA>부산광역시 동래구 연안로 49, 삼영빌딩 1층 (안락동)부산광역시 동래구 안락동 152-111 삼영빌딩47899607-825과자류, 빵류 또는 떡류
7(주)헬씨코식품제조가공업051-506-6565부산광역시 동래구 충렬대로 154, 지하1층 (온천동)부산광역시 동래구 온천동 1441-1747824607-836음료류, 기타식품류
8(주내츄럴웰테크식품제조가공업<NA>부산광역시 동래구 동래로 181, 2층 (칠산동)부산광역시 동래구 칠산동 177-2147807607-030커피, 커피
924시부산순대식품제조가공업051-507-7833부산광역시 동래구 아시아드대로 166, 2층 (사직동)부산광역시 동래구 사직동 63-1647840607-816기타식품류, 김치류
업소명업종전화번호소재지(도로명)소재지(지번)우편번호(도로명)우편번호(지번)식품의종류
38천삼명가(주)식품제조가공업051-867-5325부산광역시 동래구 여고로113번길 11, 2층 (사직동)부산광역시 동래구 사직동 157-4447835607-818다류, 음료류, 기타식품류, 음료류
39콩과두부식품제조가공업<NA>부산광역시 동래구 차밭골로 19, 1층 (온천동)부산광역시 동래구 온천동 451-347713607-834두부류 또는 묵류, 음료류, 농산가공식품류, 기타식품류
40쿰에프앤비식품제조가공업<NA>부산광역시 동래구 명서로130번길 1-24 (명장동)부산광역시 동래구 명장동 506-8647759607-811다류, 음료류, 농산가공식품류
41토백이식품식품제조가공업<NA>부산광역시 동래구 명안로25번길 45, 1층 (안락동)부산광역시 동래구 안락동 440-4047788607-828조미식품
42팀프리식품제조가공업<NA>부산광역시 동래구 명륜로138번길 30, 101호 (명륜동)부산광역시 동래구 명륜동 326-247809607-804조미식품, 즉석식품류
43푸자식품제조가공업051-507-8995부산광역시 동래구 여고로63번길 28, 1층 (사직동)부산광역시 동래구 사직동 134-1447843607-818빵또는떡류, 즉석식품류
44한산원식품제조가공업051-553-3133부산광역시 동래구 금강공원로 71 (온천동)부산광역시 동래구 온천동 300-9<NA>607-834다류, 다류
45한정에프앤비(주)식품제조가공업<NA>부산광역시 동래구 사직북로5번길 49, 1층 (사직동)부산광역시 동래구 사직동 89-147865607-815음료류
46홀릭식품제조가공업<NA>부산광역시 동래구 온천천로431번길 5, 1층 (안락동)부산광역시 동래구 안락동 633-9847901607-829음료류
47훌리건베이커리식품제조가공업<NA>부산광역시 동래구 문화로 5-3, 1층 (명륜동)부산광역시 동래구 명륜동 676-9947747607-853과자류, 빵류 또는 떡류