Overview

Dataset statistics

Number of variables11
Number of observations102
Missing cells66
Missing cells (%)5.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.2 KiB
Average record size in memory92.3 B

Variable types

Numeric2
Categorical5
DateTime1
Text3

Dataset

Description충북혁신도시에 속해 있는 음성군과 진천군 일부 소재지의 미용업에 속해 있는 시설의 현황 데이터를 생성하여 제공합니다.
URLhttps://www.data.go.kr/data/15118742/fileData.do

Alerts

상세영업상태명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
지자체명 is highly overall correlated with 일련번호 and 2 other fieldsHigh correlation
개방자치단체코드 is highly overall correlated with 일련번호 and 2 other fieldsHigh correlation
일련번호 is highly overall correlated with 도로명우편번호 and 2 other fieldsHigh correlation
도로명우편번호 is highly overall correlated with 일련번호 and 2 other fieldsHigh correlation
소재지전화 has 66 (64.7%) missing valuesMissing
일련번호 has unique valuesUnique
사업장명 has unique valuesUnique

Reproduction

Analysis started2023-12-13 00:32:06.050187
Analysis finished2023-12-13 00:32:07.526275
Duration1.48 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일련번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct102
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51.5
Minimum1
Maximum102
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-13T09:32:07.589175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.05
Q126.25
median51.5
Q376.75
95-th percentile96.95
Maximum102
Range101
Interquartile range (IQR)50.5

Descriptive statistics

Standard deviation29.588849
Coefficient of variation (CV)0.57454076
Kurtosis-1.2
Mean51.5
Median Absolute Deviation (MAD)25.5
Skewness0
Sum5253
Variance875.5
MonotonicityStrictly increasing
2023-12-13T09:32:07.694152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
66 1
 
1.0%
76 1
 
1.0%
75 1
 
1.0%
74 1
 
1.0%
73 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
69 1
 
1.0%
Other values (92) 92
90.2%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
102 1
1.0%
101 1
1.0%
100 1
1.0%
99 1
1.0%
98 1
1.0%
97 1
1.0%
96 1
1.0%
95 1
1.0%
94 1
1.0%
93 1
1.0%

업태구분명
Categorical

Distinct5
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size948.0 B
일반미용업
55 
피부미용업
21 
네일아트업
18 
메이크업업
 
5
기타
 
3

Length

Max length5
Median length5
Mean length4.9117647
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기타
2nd row메이크업업
3rd row네일아트업
4th row일반미용업
5th row네일아트업

Common Values

ValueCountFrequency (%)
일반미용업 55
53.9%
피부미용업 21
 
20.6%
네일아트업 18
 
17.6%
메이크업업 5
 
4.9%
기타 3
 
2.9%

Length

2023-12-13T09:32:07.791391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:32:07.871176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반미용업 55
53.9%
피부미용업 21
 
20.6%
네일아트업 18
 
17.6%
메이크업업 5
 
4.9%
기타 3
 
2.9%

지자체명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size948.0 B
충청북도 음성군
58 
충청북도 진천군
44 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row충청북도 진천군
2nd row충청북도 진천군
3rd row충청북도 진천군
4th row충청북도 진천군
5th row충청북도 진천군

Common Values

ValueCountFrequency (%)
충청북도 음성군 58
56.9%
충청북도 진천군 44
43.1%

Length

2023-12-13T09:32:07.964525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:32:08.036600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청북도 102
50.0%
음성군 58
28.4%
진천군 44
21.6%

개방자치단체코드
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size948.0 B
4470000
58 
4450000
44 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4450000
2nd row4450000
3rd row4450000
4th row4450000
5th row4450000

Common Values

ValueCountFrequency (%)
4470000 58
56.9%
4450000 44
43.1%

Length

2023-12-13T09:32:08.113714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:32:08.187865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4470000 58
56.9%
4450000 44
43.1%

인허가일자
Date

Distinct98
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Memory size948.0 B
Minimum2012-05-18 00:00:00
Maximum2023-07-21 00:00:00
2023-12-13T09:32:08.274342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:32:08.381889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

상세영업상태명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size948.0 B
영업
102 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 102
100.0%

Length

2023-12-13T09:32:08.481211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:32:08.546833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 102
100.0%

소재지전화
Text

MISSING 

Distinct35
Distinct (%)97.2%
Missing66
Missing (%)64.7%
Memory size948.0 B
2023-12-13T09:32:08.687507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.944444
Min length11

Characters and Unicode

Total characters430
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

Unique34 ?
Unique (%)94.4%

Sample

1st row043-533-3990
2nd row043-881-2245
3rd row043-535-1420
4th row043-534-3840
5th row043-535-0992
ValueCountFrequency (%)
043-882-7842 2
 
5.6%
043-533-3990 1
 
2.8%
043-877-4179 1
 
2.8%
043-877-817 1
 
2.8%
043-878-0810 1
 
2.8%
043-881-2525 1
 
2.8%
043-883-5005 1
 
2.8%
043-881-1311 1
 
2.8%
043-878-0362 1
 
2.8%
043-882-3885 1
 
2.8%
Other values (25) 25
69.4%
2023-12-13T09:32:08.949765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 72
16.7%
0 63
14.7%
3 62
14.4%
8 61
14.2%
4 46
10.7%
2 28
 
6.5%
7 27
 
6.3%
5 27
 
6.3%
1 22
 
5.1%
9 13
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 358
83.3%
Dash Punctuation 72
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 63
17.6%
3 62
17.3%
8 61
17.0%
4 46
12.8%
2 28
7.8%
7 27
7.5%
5 27
7.5%
1 22
 
6.1%
9 13
 
3.6%
6 9
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 72
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 430
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 72
16.7%
0 63
14.7%
3 62
14.4%
8 61
14.2%
4 46
10.7%
2 28
 
6.5%
7 27
 
6.3%
5 27
 
6.3%
1 22
 
5.1%
9 13
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 430
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 72
16.7%
0 63
14.7%
3 62
14.4%
8 61
14.2%
4 46
10.7%
2 28
 
6.5%
7 27
 
6.3%
5 27
 
6.3%
1 22
 
5.1%
9 13
 
3.0%

도로명전체주소
Text

Distinct100
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size948.0 B
2023-12-13T09:32:09.236852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length41
Mean length29.333333
Min length19

Characters and Unicode

Total characters2992
Distinct characters117
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

Unique98 ?
Unique (%)96.1%

Sample

1st row충청북도 진천군 덕산읍 대하로 114 203호 (아모리움 내안애)
2nd row충청북도 진천군 덕산읍 시가로 39 302호
3rd row충청북도 진천군 덕산읍 대하로 114 1층 108호 (아모리움 내안애)
4th row충청북도 진천군 덕산읍 예지2길 16 B01호
5th row충청북도 진천군 덕산읍 공원로 48 청암갤러리 3층 303호
ValueCountFrequency (%)
충청북도 102
 
14.5%
맹동면 58
 
8.2%
음성군 58
 
8.2%
덕산읍 44
 
6.2%
진천군 44
 
6.2%
대하로 27
 
3.8%
1층 20
 
2.8%
201호 10
 
1.4%
108호 9
 
1.3%
시가로 9
 
1.3%
Other values (161) 323
45.9%
2023-12-13T09:32:09.626752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
602
20.1%
1 197
 
6.6%
도 106
 
3.5%
충 105
 
3.5%
북 105
 
3.5%
청 103
 
3.4%
2 103
 
3.4%
군 102
 
3.4%
0 99
 
3.3%
호 91
 
3.0%
Other values (107) 1379
46.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1731
57.9%
Space Separator 602
 
20.1%
Decimal Number 602
 
20.1%
Open Punctuation 16
 
0.5%
Close Punctuation 16
 
0.5%
Dash Punctuation 11
 
0.4%
Uppercase Letter 9
 
0.3%
Lowercase Letter 3
 
0.1%
Math Symbol 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 106
 
6.1%
충 105
 
6.1%
북 105
 
6.1%
청 103
 
6.0%
군 102
 
5.9%
호 91
 
5.3%
성 75
 
4.3%
동 69
 
4.0%
음 67
 
3.9%
로 61
 
3.5%
Other values (84) 847
48.9%
Decimal Number
ValueCountFrequency (%)
1 197
32.7%
2 103
17.1%
0 99
16.4%
3 52
 
8.6%
4 46
 
7.6%
8 27
 
4.5%
7 23
 
3.8%
5 23
 
3.8%
6 18
 
3.0%
9 14
 
2.3%
Uppercase Letter
ValueCountFrequency (%)
S 2
22.2%
C 2
22.2%
B 2
22.2%
A 2
22.2%
D 1
11.1%
Lowercase Letter
ValueCountFrequency (%)
v 1
33.3%
g 1
33.3%
c 1
33.3%
Space Separator
ValueCountFrequency (%)
602
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1731
57.9%
Common 1249
41.7%
Latin 12
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 106
 
6.1%
충 105
 
6.1%
북 105
 
6.1%
청 103
 
6.0%
군 102
 
5.9%
호 91
 
5.3%
성 75
 
4.3%
동 69
 
4.0%
음 67
 
3.9%
로 61
 
3.5%
Other values (84) 847
48.9%
Common
ValueCountFrequency (%)
602
48.2%
1 197
 
15.8%
2 103
 
8.2%
0 99
 
7.9%
3 52
 
4.2%
4 46
 
3.7%
8 27
 
2.2%
7 23
 
1.8%
5 23
 
1.8%
6 18
 
1.4%
Other values (5) 59
 
4.7%
Latin
ValueCountFrequency (%)
S 2
16.7%
C 2
16.7%
B 2
16.7%
A 2
16.7%
D 1
8.3%
v 1
8.3%
g 1
8.3%
c 1
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1731
57.9%
ASCII 1261
42.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
602
47.7%
1 197
 
15.6%
2 103
 
8.2%
0 99
 
7.9%
3 52
 
4.1%
4 46
 
3.6%
8 27
 
2.1%
7 23
 
1.8%
5 23
 
1.8%
6 18
 
1.4%
Other values (13) 71
 
5.6%
Hangul
ValueCountFrequency (%)
도 106
 
6.1%
충 105
 
6.1%
북 105
 
6.1%
청 103
 
6.0%
군 102
 
5.9%
호 91
 
5.3%
성 75
 
4.3%
동 69
 
4.0%
음 67
 
3.9%
로 61
 
3.5%
Other values (84) 847
48.9%

도로명우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27796.088
Minimum27735
Maximum27875
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-13T09:32:09.712959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum27735
5-th percentile27738
Q127738
median27738
Q327872
95-th percentile27875
Maximum27875
Range140
Interquartile range (IQR)134

Descriptive statistics

Standard deviation67.258641
Coefficient of variation (CV)0.0024197161
Kurtosis-1.9540443
Mean27796.088
Median Absolute Deviation (MAD)0
Skewness0.28418472
Sum2835201
Variance4523.7248
MonotonicityNot monotonic
2023-12-13T09:32:09.797041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
27738 54
52.9%
27875 18
 
17.6%
27871 11
 
10.8%
27874 7
 
6.9%
27872 7
 
6.9%
27735 3
 
2.9%
27854 1
 
1.0%
27737 1
 
1.0%
ValueCountFrequency (%)
27735 3
 
2.9%
27737 1
 
1.0%
27738 54
52.9%
27854 1
 
1.0%
27871 11
 
10.8%
27872 7
 
6.9%
27874 7
 
6.9%
27875 18
 
17.6%
ValueCountFrequency (%)
27875 18
 
17.6%
27874 7
 
6.9%
27872 7
 
6.9%
27871 11
 
10.8%
27854 1
 
1.0%
27738 54
52.9%
27737 1
 
1.0%
27735 3
 
2.9%

사업장명
Text

UNIQUE 

Distinct102
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size948.0 B
2023-12-13T09:32:09.972858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length16
Mean length7.5490196
Min length2

Characters and Unicode

Total characters770
Distinct characters228
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique102 ?
Unique (%)100.0%

Sample

1st row연(戀)에스테틱
2nd row밀키브로우
3rd row네일그리다
4th row니즈헤어
5th row레푸스 진천혁신도시점
ValueCountFrequency (%)
충북혁신도시점 3
 
2.1%
헤어 3
 
2.1%
hair 2
 
1.4%
에스테틱 2
 
1.4%
연(戀)에스테틱 1
 
0.7%
으나풋클린&네일 1
 
0.7%
에스테티아 1
 
0.7%
충북혁신1호점 1
 
0.7%
샤론뷰티 1
 
0.7%
오늘도 1
 
0.7%
Other values (129) 129
89.0%
2023-12-13T09:32:10.243002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
43
 
5.6%
헤 42
 
5.5%
어 39
 
5.1%
이 17
 
2.2%
) 15
 
1.9%
( 15
 
1.9%
일 13
 
1.7%
스 13
 
1.7%
네 12
 
1.6%
티 11
 
1.4%
Other values (218) 550
71.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 541
70.3%
Lowercase Letter 73
 
9.5%
Uppercase Letter 70
 
9.1%
Space Separator 43
 
5.6%
Close Punctuation 15
 
1.9%
Open Punctuation 15
 
1.9%
Other Punctuation 8
 
1.0%
Decimal Number 5
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
헤 42
 
7.8%
어 39
 
7.2%
이 17
 
3.1%
일 13
 
2.4%
스 13
 
2.4%
네 12
 
2.2%
티 11
 
2.0%
리 11
 
2.0%
신 11
 
2.0%
아 10
 
1.8%
Other values (166) 362
66.9%
Lowercase Letter
ValueCountFrequency (%)
i 10
13.7%
e 9
12.3%
o 7
9.6%
a 7
9.6%
r 6
 
8.2%
h 4
 
5.5%
b 4
 
5.5%
l 3
 
4.1%
n 3
 
4.1%
d 3
 
4.1%
Other values (10) 17
23.3%
Uppercase Letter
ValueCountFrequency (%)
A 10
14.3%
I 7
10.0%
R 7
10.0%
N 7
10.0%
H 6
 
8.6%
L 4
 
5.7%
O 4
 
5.7%
Y 3
 
4.3%
J 3
 
4.3%
S 3
 
4.3%
Other values (10) 16
22.9%
Other Punctuation
ValueCountFrequency (%)
& 4
50.0%
: 1
 
12.5%
, 1
 
12.5%
. 1
 
12.5%
· 1
 
12.5%
Decimal Number
ValueCountFrequency (%)
1 2
40.0%
9 1
20.0%
2 1
20.0%
0 1
20.0%
Space Separator
ValueCountFrequency (%)
43
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 540
70.1%
Latin 143
 
18.6%
Common 86
 
11.2%
Han 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
헤 42
 
7.8%
어 39
 
7.2%
이 17
 
3.1%
일 13
 
2.4%
스 13
 
2.4%
네 12
 
2.2%
티 11
 
2.0%
리 11
 
2.0%
신 11
 
2.0%
아 10
 
1.9%
Other values (165) 361
66.9%
Latin
ValueCountFrequency (%)
i 10
 
7.0%
A 10
 
7.0%
e 9
 
6.3%
I 7
 
4.9%
o 7
 
4.9%
a 7
 
4.9%
R 7
 
4.9%
N 7
 
4.9%
r 6
 
4.2%
H 6
 
4.2%
Other values (30) 67
46.9%
Common
ValueCountFrequency (%)
43
50.0%
) 15
 
17.4%
( 15
 
17.4%
& 4
 
4.7%
1 2
 
2.3%
: 1
 
1.2%
, 1
 
1.2%
9 1
 
1.2%
2 1
 
1.2%
0 1
 
1.2%
Other values (2) 2
 
2.3%
Han
ValueCountFrequency (%)
戀 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 540
70.1%
ASCII 228
29.6%
CJK Compat Ideographs 1
 
0.1%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
43
18.9%
) 15
 
6.6%
( 15
 
6.6%
i 10
 
4.4%
A 10
 
4.4%
e 9
 
3.9%
I 7
 
3.1%
o 7
 
3.1%
a 7
 
3.1%
R 7
 
3.1%
Other values (41) 98
43.0%
Hangul
ValueCountFrequency (%)
헤 42
 
7.8%
어 39
 
7.2%
이 17
 
3.1%
일 13
 
2.4%
스 13
 
2.4%
네 12
 
2.2%
티 11
 
2.0%
리 11
 
2.0%
신 11
 
2.0%
아 10
 
1.9%
Other values (165) 361
66.9%
CJK Compat Ideographs
ValueCountFrequency (%)
戀 1
100.0%
None
ValueCountFrequency (%)
· 1
100.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size948.0 B
2023-08-14
102 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-14
2nd row2023-08-14
3rd row2023-08-14
4th row2023-08-14
5th row2023-08-14

Common Values

ValueCountFrequency (%)
2023-08-14 102
100.0%

Length

2023-12-13T09:32:10.340485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:32:10.410882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-14 102
100.0%

Interactions

2023-12-13T09:32:07.186409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:32:07.062413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:32:07.248531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:32:07.119498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T09:32:10.456419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호업태구분명지자체명개방자치단체코드인허가일자소재지전화도로명전체주소도로명우편번호
일련번호1.0000.0450.9970.9970.9900.9670.9800.784
업태구분명0.0451.0000.0000.0000.9390.0000.6570.000
지자체명0.9970.0001.0000.9990.8961.0001.0001.000
개방자치단체코드0.9970.0000.9991.0000.8961.0001.0001.000
인허가일자0.9900.9390.8960.8961.0001.0000.9990.980
소재지전화0.9670.0001.0001.0001.0001.0001.0001.000
도로명전체주소0.9800.6571.0001.0000.9991.0001.0001.000
도로명우편번호0.7840.0001.0001.0000.9801.0001.0001.000
2023-12-13T09:32:10.558948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지자체명개방자치단체코드업태구분명
지자체명1.0000.9800.000
개방자치단체코드0.9801.0000.000
업태구분명0.0000.0001.000
2023-12-13T09:32:10.643459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호도로명우편번호업태구분명지자체명개방자치단체코드
일련번호1.000-0.8130.0000.9140.914
도로명우편번호-0.8131.0000.0000.9950.995
업태구분명0.0000.0001.0000.0000.000
지자체명0.9140.9950.0001.0000.980
개방자치단체코드0.9140.9950.0000.9801.000

Missing values

2023-12-13T09:32:07.359267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T09:32:07.471814image/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

일련번호업태구분명지자체명개방자치단체코드인허가일자상세영업상태명소재지전화도로명전체주소도로명우편번호사업장명데이터기준일자
01기타충청북도 진천군44500002023-07-11영업043-533-3990충청북도 진천군 덕산읍 대하로 114 203호 (아모리움 내안애)27874연(戀)에스테틱2023-08-14
12메이크업업충청북도 진천군44500002023-06-23영업<NA>충청북도 진천군 덕산읍 시가로 39 302호27871밀키브로우2023-08-14
23네일아트업충청북도 진천군44500002023-06-09영업<NA>충청북도 진천군 덕산읍 대하로 114 1층 108호 (아모리움 내안애)27874네일그리다2023-08-14
34일반미용업충청북도 진천군44500002023-05-24영업<NA>충청북도 진천군 덕산읍 예지2길 16 B01호27875니즈헤어2023-08-14
45네일아트업충청북도 진천군44500002023-04-18영업<NA>충청북도 진천군 덕산읍 공원로 48 청암갤러리 3층 303호27871레푸스 진천혁신도시점2023-08-14
56일반미용업충청북도 진천군44500002023-03-13영업<NA>충청북도 진천군 덕산읍 시가로 43 107호27871강민선헤어2023-08-14
67피부미용업충청북도 진천군44500002023-02-21영업<NA>충청북도 진천군 덕산읍 대월로 127 105호 (모아엘가 더 테라스아파트)27872the 윤 에스테틱2023-08-14
78일반미용업충청북도 진천군44500002023-02-13영업<NA>충청북도 진천군 덕산읍 예지1길 3-1 101호27875본투미 born to 미2023-08-14
89네일아트업충청북도 진천군44500002023-01-30영업<NA>충청북도 진천군 덕산읍 시가로 10 포스빌딩 108호27875네일또와2023-08-14
910일반미용업충청북도 진천군44500002022-11-21영업<NA>충청북도 진천군 덕산읍 대하로 147 301호27871Awe Hair(아위헤어)2023-08-14
일련번호업태구분명지자체명개방자치단체코드인허가일자상세영업상태명소재지전화도로명전체주소도로명우편번호사업장명데이터기준일자
9293일반미용업충청북도 음성군44700002017-02-23영업043-878-2012충청북도 음성군 맹동면 사예로 56 201호27738헤어살롱201 충북혁신도시점2023-08-14
9394일반미용업충청북도 음성군44700002016-12-27영업043-883-5088충청북도 음성군 맹동면 사예1길 5 101호27738포맨2023-08-14
9495일반미용업충청북도 음성군44700002016-09-23영업043-877-5054충청북도 음성군 맹동면 사예3길 9 102호27738최선헤어비스2023-08-14
9596일반미용업충청북도 음성군44700002016-09-12영업043-535-9519충청북도 음성군 맹동면 사예2길 10 201호27738지음헤어2023-08-14
9697피부미용업충청북도 음성군44700002016-06-14영업<NA>충청북도 음성군 맹동면 대하1길 4 위너스타워 3층 301호27738가올 스킨앤뷰티2023-08-14
9798네일아트업충청북도 음성군44700002016-02-22영업043-882-7842충청북도 음성군 맹동면 장성2길 9 2층 201호27738리즈네일2023-08-14
9899일반미용업충청북도 음성군44700002015-02-16영업<NA>충청북도 음성군 맹동면 사예로 20-1 202호27735헤어플러스2023-08-14
99100일반미용업충청북도 음성군44700002014-08-13영업043-878-0362충청북도 음성군 맹동면 학예로 51 203호27735뷰리스헤어2023-08-14
100101일반미용업충청북도 음성군44700002013-08-27영업043-882-3885충청북도 음성군 맹동면 대하로 253 203~204호27738제인헤어2023-08-14
101102일반미용업충청북도 음성군44700002012-12-13영업031-388-9661충청북도 음성군 맹동면 대하1길 427738박철우 HAIR2023-08-14