Overview

Dataset statistics

Number of variables10
Number of observations151
Missing cells82
Missing cells (%)5.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.1 KiB
Average record size in memory81.9 B

Variable types

Categorical2
Numeric1
DateTime1
Text6

Dataset

Description충청남도 아산시 식품제조가공업소 정보로서 업종명, 업소명, 영업자, 주소정보 등의 정보를 제공합니다-------------------------------
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=440&beforeMenuCd=DOM_000000201001001000&publicdatapk=15048002

Alerts

업종명 has constant value ""Constant
업소위치 is highly imbalanced (63.6%)Imbalance
영업자전화 has 82 (54.3%) missing valuesMissing
인허가번호 has unique valuesUnique
업소명 has unique valuesUnique

Reproduction

Analysis started2024-01-09 20:45:54.182041
Analysis finished2024-01-09 20:45:54.938054
Duration0.76 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
식품제조가공업
151 

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 151
100.0%

Length

2024-01-10T05:45:54.992314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:45:55.072019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 151
100.0%

인허가번호
Real number (ℝ)

UNIQUE 

Distinct151
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0122 × 1010
Minimum1.9830461 × 1010
Maximum2.0230651 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-01-10T05:45:55.161479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9830461 × 1010
5-th percentile1.9910461 × 1010
Q12.0070461 × 1010
median2.0160461 × 1010
Q32.0190468 × 1010
95-th percentile2.0220644 × 1010
Maximum2.0230651 × 1010
Range4.0019025 × 108
Interquartile range (IQR)1.2000673 × 108

Descriptive statistics

Standard deviation99445962
Coefficient of variation (CV)0.0049421511
Kurtosis0.42152252
Mean2.0122 × 1010
Median Absolute Deviation (MAD)49999737
Skewness-1.1815889
Sum3.0384219 × 1012
Variance9.8894994 × 1015
MonotonicityNot monotonic
2024-01-10T05:45:55.293079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19830461017 1
 
0.7%
20190467257 1
 
0.7%
20180468056 1
 
0.7%
20190467062 1
 
0.7%
20190467112 1
 
0.7%
20190467142 1
 
0.7%
20190467145 1
 
0.7%
20190467170 1
 
0.7%
20190467205 1
 
0.7%
20190467306 1
 
0.7%
Other values (141) 141
93.4%
ValueCountFrequency (%)
19830461017 1
0.7%
19840461098 1
0.7%
19860560029 1
0.7%
19870461068 1
0.7%
19890461032 1
0.7%
19900461103 1
0.7%
19910461045 1
0.7%
19910461077 1
0.7%
19910461101 1
0.7%
19920461126 1
0.7%
ValueCountFrequency (%)
20230651269 1
0.7%
20230651232 1
0.7%
20230651088 1
0.7%
20230651055 1
0.7%
20230651002 1
0.7%
20220644288 1
0.7%
20220643865 1
0.7%
20220643749 1
0.7%
20220643675 1
0.7%
20220643621 1
0.7%

인허가일자
Date

Distinct150
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum1983-05-21 00:00:00
Maximum2023-03-17 00:00:00
2024-01-10T05:45:55.411021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:45:55.528779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업소명
Text

UNIQUE 

Distinct151
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-10T05:45:55.768183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length16
Mean length8.397351
Min length2

Characters and Unicode

Total characters1268
Distinct characters265
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique151 ?
Unique (%)100.0%

Sample

1st row(주)한국파비스알엔디
2nd row(주)광일
3rd row해태제과식품(주)
4th row(주)한미에프쓰리
5th row(주)우리승진식품
ValueCountFrequency (%)
주식회사 12
 
5.9%
농업회사법인 5
 
2.5%
농업회사법인주식회사 3
 
1.5%
아산공장 3
 
1.5%
영농조합법인 2
 
1.0%
주)한미에프쓰리 2
 
1.0%
농업회사 2
 
1.0%
주)한국파비스알엔디 1
 
0.5%
둔포록야 1
 
0.5%
농업회사법인주식회사아주존 1
 
0.5%
Other values (170) 170
84.2%
2024-01-10T05:45:56.433921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 73
 
5.8%
52
 
4.1%
( 49
 
3.9%
) 49
 
3.9%
사 48
 
3.8%
회 43
 
3.4%
식 42
 
3.3%
농 40
 
3.2%
인 37
 
2.9%
법 29
 
2.3%
Other values (255) 806
63.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1077
84.9%
Space Separator 52
 
4.1%
Open Punctuation 49
 
3.9%
Close Punctuation 49
 
3.9%
Lowercase Letter 25
 
2.0%
Uppercase Letter 10
 
0.8%
Decimal Number 5
 
0.4%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 73
 
6.8%
사 48
 
4.5%
회 43
 
4.0%
식 42
 
3.9%
농 40
 
3.7%
인 37
 
3.4%
법 29
 
2.7%
업 27
 
2.5%
드 24
 
2.2%
푸 21
 
1.9%
Other values (226) 693
64.3%
Lowercase Letter
ValueCountFrequency (%)
a 4
16.0%
k 3
12.0%
e 3
12.0%
r 2
8.0%
n 2
8.0%
c 2
8.0%
o 2
8.0%
t 1
 
4.0%
d 1
 
4.0%
h 1
 
4.0%
Other values (4) 4
16.0%
Uppercase Letter
ValueCountFrequency (%)
C 2
20.0%
B 2
20.0%
F 2
20.0%
O 1
10.0%
T 1
10.0%
K 1
10.0%
D 1
10.0%
Decimal Number
ValueCountFrequency (%)
2 2
40.0%
8 1
20.0%
5 1
20.0%
1 1
20.0%
Space Separator
ValueCountFrequency (%)
52
100.0%
Open Punctuation
ValueCountFrequency (%)
( 49
100.0%
Close Punctuation
ValueCountFrequency (%)
) 49
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1077
84.9%
Common 156
 
12.3%
Latin 35
 
2.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 73
 
6.8%
사 48
 
4.5%
회 43
 
4.0%
식 42
 
3.9%
농 40
 
3.7%
인 37
 
3.4%
법 29
 
2.7%
업 27
 
2.5%
드 24
 
2.2%
푸 21
 
1.9%
Other values (226) 693
64.3%
Latin
ValueCountFrequency (%)
a 4
 
11.4%
k 3
 
8.6%
e 3
 
8.6%
r 2
 
5.7%
C 2
 
5.7%
n 2
 
5.7%
c 2
 
5.7%
B 2
 
5.7%
F 2
 
5.7%
o 2
 
5.7%
Other values (11) 11
31.4%
Common
ValueCountFrequency (%)
52
33.3%
( 49
31.4%
) 49
31.4%
2 2
 
1.3%
& 1
 
0.6%
8 1
 
0.6%
5 1
 
0.6%
1 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1077
84.9%
ASCII 191
 
15.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 73
 
6.8%
사 48
 
4.5%
회 43
 
4.0%
식 42
 
3.9%
농 40
 
3.7%
인 37
 
3.4%
법 29
 
2.7%
업 27
 
2.5%
드 24
 
2.2%
푸 21
 
1.9%
Other values (226) 693
64.3%
ASCII
ValueCountFrequency (%)
52
27.2%
( 49
25.7%
) 49
25.7%
a 4
 
2.1%
k 3
 
1.6%
e 3
 
1.6%
2 2
 
1.0%
r 2
 
1.0%
C 2
 
1.0%
n 2
 
1.0%
Other values (19) 23
12.0%

영업자
Text

Distinct146
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-10T05:45:56.707670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length3
Mean length3.4569536
Min length3

Characters and Unicode

Total characters522
Distinct characters161
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

Unique143 ?
Unique (%)94.7%

Sample

1st row최승한
2nd row조용걸
3rd row신정훈
4th row장덕철
5th row최평호
ValueCountFrequency (%)
1명 4
 
2.5%
외 4
 
2.5%
장덕철 3
 
1.8%
이주선 3
 
1.8%
양경호 2
 
1.2%
김영룡 1
 
0.6%
최승한 1
 
0.6%
김진수 1
 
0.6%
오진영 1
 
0.6%
한기홍 1
 
0.6%
Other values (142) 142
87.1%
2024-01-10T05:45:57.127158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 32
 
6.1%
이 30
 
5.7%
정 13
 
2.5%
12
 
2.3%
영 12
 
2.3%
호 10
 
1.9%
선 10
 
1.9%
주 9
 
1.7%
명 9
 
1.7%
재 8
 
1.5%
Other values (151) 377
72.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 475
91.0%
Uppercase Letter 23
 
4.4%
Space Separator 12
 
2.3%
Decimal Number 5
 
1.0%
Lowercase Letter 3
 
0.6%
Close Punctuation 2
 
0.4%
Open Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 32
 
6.7%
이 30
 
6.3%
정 13
 
2.7%
영 12
 
2.5%
호 10
 
2.1%
선 10
 
2.1%
주 9
 
1.9%
명 9
 
1.9%
재 8
 
1.7%
종 8
 
1.7%
Other values (131) 334
70.3%
Uppercase Letter
ValueCountFrequency (%)
I 4
17.4%
D 2
8.7%
V 2
8.7%
O 2
8.7%
L 2
8.7%
N 2
8.7%
E 2
8.7%
M 2
8.7%
B 1
 
4.3%
H 1
 
4.3%
Other values (3) 3
13.0%
Lowercase Letter
ValueCountFrequency (%)
a 1
33.3%
r 1
33.3%
k 1
33.3%
Space Separator
ValueCountFrequency (%)
12
100.0%
Decimal Number
ValueCountFrequency (%)
1 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 475
91.0%
Latin 26
 
5.0%
Common 21
 
4.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 32
 
6.7%
이 30
 
6.3%
정 13
 
2.7%
영 12
 
2.5%
호 10
 
2.1%
선 10
 
2.1%
주 9
 
1.9%
명 9
 
1.9%
재 8
 
1.7%
종 8
 
1.7%
Other values (131) 334
70.3%
Latin
ValueCountFrequency (%)
I 4
15.4%
D 2
 
7.7%
V 2
 
7.7%
O 2
 
7.7%
L 2
 
7.7%
N 2
 
7.7%
E 2
 
7.7%
M 2
 
7.7%
B 1
 
3.8%
H 1
 
3.8%
Other values (6) 6
23.1%
Common
ValueCountFrequency (%)
12
57.1%
1 5
23.8%
) 2
 
9.5%
( 2
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 475
91.0%
ASCII 47
 
9.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 32
 
6.7%
이 30
 
6.3%
정 13
 
2.7%
영 12
 
2.5%
호 10
 
2.1%
선 10
 
2.1%
주 9
 
1.9%
명 9
 
1.9%
재 8
 
1.7%
종 8
 
1.7%
Other values (131) 334
70.3%
ASCII
ValueCountFrequency (%)
12
25.5%
1 5
10.6%
I 4
 
8.5%
D 2
 
4.3%
V 2
 
4.3%
O 2
 
4.3%
L 2
 
4.3%
N 2
 
4.3%
E 2
 
4.3%
) 2
 
4.3%
Other values (10) 12
25.5%

소재지(도로명)
Text

Distinct149
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-10T05:45:57.427357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length40
Mean length25.245033
Min length19

Characters and Unicode

Total characters3812
Distinct characters158
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique148 ?
Unique (%)98.0%

Sample

1st row충청남도 아산시 둔포면 충무로 1600-10
2nd row충청남도 아산시 어의정로 157 (풍기동)
3rd row충청남도 아산시 음봉면 아산밸리로388번길 149-17
4th row충청남도 아산시 둔포면 충무로 1342
5th row충청남도 아산시 둔포면 관용로 190-9
ValueCountFrequency (%)
충청남도 151
 
18.3%
아산시 151
 
18.3%
둔포면 20
 
2.4%
배방읍 19
 
2.3%
1층 18
 
2.2%
음봉면 17
 
2.1%
영인면 12
 
1.5%
송악면 11
 
1.3%
염치읍 10
 
1.2%
탕정면 10
 
1.2%
Other values (289) 406
49.2%
2024-01-10T05:45:57.877336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
674
 
17.7%
산 185
 
4.9%
도 166
 
4.4%
아 165
 
4.3%
충 160
 
4.2%
남 158
 
4.1%
시 153
 
4.0%
청 152
 
4.0%
1 145
 
3.8%
2 117
 
3.1%
Other values (148) 1737
45.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2261
59.3%
Decimal Number 682
 
17.9%
Space Separator 674
 
17.7%
Dash Punctuation 62
 
1.6%
Other Punctuation 54
 
1.4%
Close Punctuation 33
 
0.9%
Open Punctuation 33
 
0.9%
Uppercase Letter 13
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 185
 
8.2%
도 166
 
7.3%
아 165
 
7.3%
충 160
 
7.1%
남 158
 
7.0%
시 153
 
6.8%
청 152
 
6.7%
로 117
 
5.2%
면 105
 
4.6%
길 79
 
3.5%
Other values (126) 821
36.3%
Decimal Number
ValueCountFrequency (%)
1 145
21.3%
2 117
17.2%
3 68
10.0%
8 58
 
8.5%
4 57
 
8.4%
5 53
 
7.8%
0 53
 
7.8%
9 47
 
6.9%
6 45
 
6.6%
7 39
 
5.7%
Uppercase Letter
ValueCountFrequency (%)
A 4
30.8%
B 4
30.8%
D 1
 
7.7%
F 1
 
7.7%
M 1
 
7.7%
C 1
 
7.7%
J 1
 
7.7%
Space Separator
ValueCountFrequency (%)
674
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 62
100.0%
Other Punctuation
ValueCountFrequency (%)
, 54
100.0%
Close Punctuation
ValueCountFrequency (%)
) 33
100.0%
Open Punctuation
ValueCountFrequency (%)
( 33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2261
59.3%
Common 1538
40.3%
Latin 13
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 185
 
8.2%
도 166
 
7.3%
아 165
 
7.3%
충 160
 
7.1%
남 158
 
7.0%
시 153
 
6.8%
청 152
 
6.7%
로 117
 
5.2%
면 105
 
4.6%
길 79
 
3.5%
Other values (126) 821
36.3%
Common
ValueCountFrequency (%)
674
43.8%
1 145
 
9.4%
2 117
 
7.6%
3 68
 
4.4%
- 62
 
4.0%
8 58
 
3.8%
4 57
 
3.7%
, 54
 
3.5%
5 53
 
3.4%
0 53
 
3.4%
Other values (5) 197
 
12.8%
Latin
ValueCountFrequency (%)
A 4
30.8%
B 4
30.8%
D 1
 
7.7%
F 1
 
7.7%
M 1
 
7.7%
C 1
 
7.7%
J 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2261
59.3%
ASCII 1551
40.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
674
43.5%
1 145
 
9.3%
2 117
 
7.5%
3 68
 
4.4%
- 62
 
4.0%
8 58
 
3.7%
4 57
 
3.7%
, 54
 
3.5%
5 53
 
3.4%
0 53
 
3.4%
Other values (12) 210
 
13.5%
Hangul
ValueCountFrequency (%)
산 185
 
8.2%
도 166
 
7.3%
아 165
 
7.3%
충 160
 
7.1%
남 158
 
7.0%
시 153
 
6.8%
청 152
 
6.7%
로 117
 
5.2%
면 105
 
4.6%
길 79
 
3.5%
Other values (126) 821
36.3%

소재지(지번)
Text

Distinct149
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-10T05:45:58.219421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length40
Mean length23.450331
Min length16

Characters and Unicode

Total characters3541
Distinct characters148
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique147 ?
Unique (%)97.4%

Sample

1st row충청남도 아산시 둔포면 관대리 84-26
2nd row충청남도 아산시 풍기동 226
3rd row충청남도 아산시 음봉면 신휴리 761
4th row충청남도 아산시 둔포면 관대리 207-21
5th row충청남도 아산시 둔포면 신양리 239-9
ValueCountFrequency (%)
충청남도 151
19.2%
아산시 151
19.2%
둔포면 20
 
2.5%
배방읍 19
 
2.4%
음봉면 18
 
2.3%
영인면 12
 
1.5%
송악면 11
 
1.4%
탕정면 10
 
1.3%
염치읍 10
 
1.3%
신창면 9
 
1.1%
Other values (256) 375
47.7%
2024-01-10T05:45:58.692144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
783
22.1%
산 182
 
5.1%
도 163
 
4.6%
남 157
 
4.4%
아 153
 
4.3%
시 153
 
4.3%
청 152
 
4.3%
충 151
 
4.3%
1 144
 
4.1%
리 128
 
3.6%
Other values (138) 1375
38.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2015
56.9%
Space Separator 783
 
22.1%
Decimal Number 613
 
17.3%
Dash Punctuation 97
 
2.7%
Other Punctuation 12
 
0.3%
Uppercase Letter 9
 
0.3%
Open Punctuation 6
 
0.2%
Close Punctuation 6
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 182
 
9.0%
도 163
 
8.1%
남 157
 
7.8%
아 153
 
7.6%
시 153
 
7.6%
청 152
 
7.5%
충 151
 
7.5%
리 128
 
6.4%
면 99
 
4.9%
동 56
 
2.8%
Other values (116) 621
30.8%
Decimal Number
ValueCountFrequency (%)
1 144
23.5%
2 103
16.8%
4 59
9.6%
3 53
 
8.6%
7 50
 
8.2%
6 48
 
7.8%
0 45
 
7.3%
5 44
 
7.2%
9 34
 
5.5%
8 33
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
B 2
22.2%
A 2
22.2%
D 1
11.1%
F 1
11.1%
M 1
11.1%
J 1
11.1%
C 1
11.1%
Space Separator
ValueCountFrequency (%)
783
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 97
100.0%
Other Punctuation
ValueCountFrequency (%)
, 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2015
56.9%
Common 1517
42.8%
Latin 9
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 182
 
9.0%
도 163
 
8.1%
남 157
 
7.8%
아 153
 
7.6%
시 153
 
7.6%
청 152
 
7.5%
충 151
 
7.5%
리 128
 
6.4%
면 99
 
4.9%
동 56
 
2.8%
Other values (116) 621
30.8%
Common
ValueCountFrequency (%)
783
51.6%
1 144
 
9.5%
2 103
 
6.8%
- 97
 
6.4%
4 59
 
3.9%
3 53
 
3.5%
7 50
 
3.3%
6 48
 
3.2%
0 45
 
3.0%
5 44
 
2.9%
Other values (5) 91
 
6.0%
Latin
ValueCountFrequency (%)
B 2
22.2%
A 2
22.2%
D 1
11.1%
F 1
11.1%
M 1
11.1%
J 1
11.1%
C 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2015
56.9%
ASCII 1526
43.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
783
51.3%
1 144
 
9.4%
2 103
 
6.7%
- 97
 
6.4%
4 59
 
3.9%
3 53
 
3.5%
7 50
 
3.3%
6 48
 
3.1%
0 45
 
2.9%
5 44
 
2.9%
Other values (12) 100
 
6.6%
Hangul
ValueCountFrequency (%)
산 182
 
9.0%
도 163
 
8.1%
남 157
 
7.8%
아 153
 
7.6%
시 153
 
7.6%
청 152
 
7.5%
충 151
 
7.5%
리 128
 
6.4%
면 99
 
4.9%
동 56
 
2.8%
Other values (116) 621
30.8%

영업장면적(건물내외부)
Text

Distinct149
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-10T05:45:58.994377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length5.4304636
Min length1

Characters and Unicode

Total characters820
Distinct characters12
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

Unique147 ?
Unique (%)97.4%

Sample

1st row147.95
2nd row146.85
3rd row44,820.47
4th row5,758.80
5th row1,323.72
ValueCountFrequency (%)
0 2
 
1.3%
156 2
 
1.3%
36 1
 
0.7%
1,495.90 1
 
0.7%
324 1
 
0.7%
33.6 1
 
0.7%
1,950 1
 
0.7%
147.95 1
 
0.7%
14.17 1
 
0.7%
64.39 1
 
0.7%
Other values (139) 139
92.1%
2024-01-10T05:45:59.435952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 114
13.9%
1 90
11.0%
2 87
10.6%
3 82
10.0%
5 71
8.7%
7 62
7.6%
4 61
7.4%
9 60
7.3%
6 55
6.7%
8 52
6.3%
Other values (2) 86
10.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 667
81.3%
Other Punctuation 153
 
18.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 90
13.5%
2 87
13.0%
3 82
12.3%
5 71
10.6%
7 62
9.3%
4 61
9.1%
9 60
9.0%
6 55
8.2%
8 52
7.8%
0 47
7.0%
Other Punctuation
ValueCountFrequency (%)
. 114
74.5%
, 39
 
25.5%

Most occurring scripts

ValueCountFrequency (%)
Common 820
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 114
13.9%
1 90
11.0%
2 87
10.6%
3 82
10.0%
5 71
8.7%
7 62
7.6%
4 61
7.4%
9 60
7.3%
6 55
6.7%
8 52
6.3%
Other values (2) 86
10.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 820
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 114
13.9%
1 90
11.0%
2 87
10.6%
3 82
10.0%
5 71
8.7%
7 62
7.6%
4 61
7.4%
9 60
7.3%
6 55
6.7%
8 52
6.3%
Other values (2) 86
10.5%

영업자전화
Text

MISSING 

Distinct67
Distinct (%)97.1%
Missing82
Missing (%)54.3%
Memory size1.3 KiB
2024-01-10T05:45:59.671955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.942029
Min length9

Characters and Unicode

Total characters824
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

Unique65 ?
Unique (%)94.2%

Sample

1st row041-531-3967
2nd row053-852-8051
3rd row041-531-5289
4th row041-546-9317
5th row041-542-0159
ValueCountFrequency (%)
041-544-1397 2
 
2.9%
041-546-9317 2
 
2.9%
041-920-2127 1
 
1.4%
041-546-6466 1
 
1.4%
02-2232-1994 1
 
1.4%
041-534-2040 1
 
1.4%
041-545-8970 1
 
1.4%
041-549-1102 1
 
1.4%
041-542-8686 1
 
1.4%
041-531-0105 1
 
1.4%
Other values (57) 57
82.6%
2024-01-10T05:46:00.019018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 136
16.5%
0 126
15.3%
4 125
15.2%
1 111
13.5%
5 94
11.4%
3 59
7.2%
2 45
 
5.5%
6 39
 
4.7%
9 36
 
4.4%
7 27
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 688
83.5%
Dash Punctuation 136
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 126
18.3%
4 125
18.2%
1 111
16.1%
5 94
13.7%
3 59
8.6%
2 45
 
6.5%
6 39
 
5.7%
9 36
 
5.2%
7 27
 
3.9%
8 26
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 136
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 824
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 136
16.5%
0 126
15.3%
4 125
15.2%
1 111
13.5%
5 94
11.4%
3 59
7.2%
2 45
 
5.5%
6 39
 
4.7%
9 36
 
4.4%
7 27
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 824
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 136
16.5%
0 126
15.3%
4 125
15.2%
1 111
13.5%
5 94
11.4%
3 59
7.2%
2 45
 
5.5%
6 39
 
4.7%
9 36
 
4.4%
7 27
 
3.3%

업소위치
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
지상
130 
<NA>
15 
지상2층이상
 
5
지하
 
1

Length

Max length6
Median length2
Mean length2.3311258
Min length2

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
지상 130
86.1%
<NA> 15
 
9.9%
지상2층이상 5
 
3.3%
지하 1
 
0.7%

Length

2024-01-10T05:46:00.152912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:46:00.259691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지상 130
86.1%
na 15
 
9.9%
지상2층이상 5
 
3.3%
지하 1
 
0.7%

Interactions

2024-01-10T05:45:54.671266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T05:46:00.328094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가번호영업자전화업소위치
인허가번호1.0000.1860.000
영업자전화0.1861.0001.000
업소위치0.0001.0001.000
2024-01-10T05:46:00.406447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가번호업소위치
인허가번호1.0000.000
업소위치0.0001.000

Missing values

2024-01-10T05:45:54.781362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T05:45:54.893453image/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

업종명인허가번호인허가일자업소명영업자소재지(도로명)소재지(지번)영업장면적(건물내외부)영업자전화업소위치
0식품제조가공업198304610171983-05-21(주)한국파비스알엔디최승한충청남도 아산시 둔포면 충무로 1600-10충청남도 아산시 둔포면 관대리 84-26147.95041-531-3967지상
1식품제조가공업198404610981984-09-03(주)광일조용걸충청남도 아산시 어의정로 157 (풍기동)충청남도 아산시 풍기동 226146.85<NA>지상
2식품제조가공업198605600291986-11-18해태제과식품(주)신정훈충청남도 아산시 음봉면 아산밸리로388번길 149-17충청남도 아산시 음봉면 신휴리 76144,820.47053-852-8051지상
3식품제조가공업198904610321989-06-14(주)한미에프쓰리장덕철충청남도 아산시 둔포면 충무로 1342충청남도 아산시 둔포면 관대리 207-215,758.80041-531-5289지상
4식품제조가공업199004611031990-11-14(주)우리승진식품최평호충청남도 아산시 둔포면 관용로 190-9충청남도 아산시 둔포면 신양리 239-91,323.72041-546-9317지상
5식품제조가공업199104610451991-05-27동진식품임재용외1인(임재익)충청남도 아산시 도고면 도고산로 349-7충청남도 아산시 도고면 도산리 160-10<NA>지상
6식품제조가공업199104610771991-09-14(주)삼아인터내셔날이재학 외 1명충청남도 아산시 신창면 서부남로790번길 48 (외2필지)충청남도 아산시 신창면 읍내리 72-2 외2필지5,781.61<NA>지상
7식품제조가공업199104611011991-11-19(주)농심이병학충청남도 아산시 탕정면 탕정면로 485충청남도 아산시 탕정면 동산리 177-1 외2 (음봉면 덕지리135,136-5)53,772.11<NA>지상
8식품제조가공업199204611261992-07-29선도농협김치가공공장박종호충청남도 아산시 선장면 서부남로 164충청남도 아산시 선장면 선창리 1853,612.98041-542-0159지상
9식품제조가공업199304610221993-02-27연세대학교 연세유업허동수충청남도 아산시 음봉면 음봉로 829충청남도 아산시 음봉면 산동리 42722,395<NA>지상
업종명인허가번호인허가일자업소명영업자소재지(도로명)소재지(지번)영업장면적(건물내외부)영업자전화업소위치
141식품제조가공업202206436212022-06-21키움농장김기수충청남도 아산시 염치읍 염성길 124충청남도 아산시 염치읍 염성리 269-41199.66041-920-2127<NA>
142식품제조가공업202206436752022-07-06(주)노아바이오텍손중호충청남도 아산시 배방읍 태화산길 22충청남도 아산시 배방읍 수철리 37-4150<NA><NA>
143식품제조가공업202206437492022-07-21농업회사법인 주식회사 다정성푸드나재성충청남도 아산시 둔포면 충무로 1693-6, A,B동충청남도 아산시 둔포면 송용리 2041,858.90041-534-2040<NA>
144식품제조가공업202206438652022-08-23아리엘미문김성문충청남도 아산시 도고면 아산만로 168, 1층충청남도 아산시 도고면 신언리 96-333<NA><NA>
145식품제조가공업202206442882022-12-21성강푸드강시원충청남도 아산시 순천향로 532 (신인동)충청남도 아산시 신인동 401103.55<NA><NA>
146식품제조가공업202306510022023-01-02청보 바이오텍황진영충청남도 아산시 배방읍 호서로79번길 20, 호서대학교 학생벤처창업관 103호충청남도 아산시 배방읍 세출리 165 호서대학교 학생벤처창업관 103호36<NA><NA>
147식품제조가공업202306510552023-01-17루츠랩김명원충청남도 아산시 온천대로1122번길 25-12 (득산동)충청남도 아산시 득산동 312-217202-2232-1994<NA>
148식품제조가공업202306510882023-01-27행복한광어 영어조합법인오기수충청남도 아산시 배방읍 용연로 156-7충청남도 아산시 배방읍 장재리 1559140.1<NA><NA>
149식품제조가공업202306512322023-03-08아산별곡김소양충청남도 아산시 번영로 20 (방축동)충청남도 아산시 방축동 135-2844.2<NA><NA>
150식품제조가공업202306512692023-03-17유니메드제약김건남충청남도 아산시 곡교천로125번길 31-36 (실옥동)충청남도 아산시 실옥동 239-11,565041-537-5500<NA>