Overview

Dataset statistics

Number of variables7
Number of observations166
Missing cells102
Missing cells (%)8.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.4 KiB
Average record size in memory57.8 B

Variable types

Categorical2
Text4
Numeric1

Dataset

Description경기도 가평군 미용업 현황 ( 업종명, 업소명, 업소소재지, 소재지전화번호, 우편번호(도로명) ) 데이터 입니다. 총 125건의 데이터가 있습니다.
Author경기도 가평군
URLhttps://www.data.go.kr/data/15029890/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
소재지우편번호 has 4 (2.4%) missing valuesMissing
소재지도로명주소 has 4 (2.4%) missing valuesMissing
소재지전화번호 has 94 (56.6%) missing valuesMissing

Reproduction

Analysis started2024-03-14 10:04:37.129894
Analysis finished2024-03-14 10:04:38.893148
Duration1.76 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

Distinct12
Distinct (%)7.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
일반미용업
63 
미용업
53 
피부미용업
17 
네일미용업
14 
종합미용업
10 
Other values (7)
9 

Length

Max length23
Median length5
Mean length4.8855422
Min length3

Unique

Unique6 ?
Unique (%)3.6%

Sample

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

Common Values

ValueCountFrequency (%)
일반미용업 63
38.0%
미용업 53
31.9%
피부미용업 17
 
10.2%
네일미용업 14
 
8.4%
종합미용업 10
 
6.0%
일반미용업, 화장ㆍ분장 미용업 3
 
1.8%
일반미용업, 피부미용업 1
 
0.6%
일반미용업, 네일미용업 1
 
0.6%
피부미용업, 네일미용업 1
 
0.6%
화장ㆍ분장 미용업 1
 
0.6%
Other values (2) 2
 
1.2%

Length

2024-03-14T19:04:39.148701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반미용업 69
38.1%
미용업 59
32.6%
피부미용업 20
 
11.0%
네일미용업 17
 
9.4%
종합미용업 10
 
5.5%
화장ㆍ분장 6
 
3.3%

업소명
Text

Distinct164
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-03-14T19:04:40.216244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length23
Mean length6.0180723
Min length2

Characters and Unicode

Total characters999
Distinct characters278
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

Unique162 ?
Unique (%)97.6%

Sample

1st row예쁘다미장원
2nd row제일미용실
3rd row클래식헤어
4th row캐리헤어
5th row오미용실
ValueCountFrequency (%)
헤어 4
 
2.1%
hair 3
 
1.6%
가위소리 2
 
1.0%
정미용실 2
 
1.0%
예쁨 2
 
1.0%
미용실 2
 
1.0%
studio 1
 
0.5%
허밍헤어(humming 1
 
0.5%
talk 1
 
0.5%
헤어플러스 1
 
0.5%
Other values (173) 173
90.1%
2024-03-14T19:04:41.697870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
어 57
 
5.7%
헤 56
 
5.6%
미 39
 
3.9%
용 30
 
3.0%
실 30
 
3.0%
26
 
2.6%
리 24
 
2.4%
스 20
 
2.0%
( 18
 
1.8%
) 18
 
1.8%
Other values (268) 681
68.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 799
80.0%
Lowercase Letter 85
 
8.5%
Uppercase Letter 36
 
3.6%
Space Separator 26
 
2.6%
Open Punctuation 18
 
1.8%
Close Punctuation 18
 
1.8%
Decimal Number 8
 
0.8%
Other Punctuation 7
 
0.7%
Connector Punctuation 1
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
어 57
 
7.1%
헤 56
 
7.0%
미 39
 
4.9%
용 30
 
3.8%
실 30
 
3.8%
리 24
 
3.0%
스 20
 
2.5%
이 15
 
1.9%
아 14
 
1.8%
가 12
 
1.5%
Other values (219) 502
62.8%
Lowercase Letter
ValueCountFrequency (%)
i 11
12.9%
a 9
10.6%
n 8
9.4%
o 7
 
8.2%
r 6
 
7.1%
l 5
 
5.9%
m 5
 
5.9%
e 5
 
5.9%
d 5
 
5.9%
u 5
 
5.9%
Other values (8) 19
22.4%
Uppercase Letter
ValueCountFrequency (%)
H 5
13.9%
A 4
11.1%
J 3
8.3%
U 3
8.3%
B 3
8.3%
T 3
8.3%
S 2
 
5.6%
L 2
 
5.6%
N 2
 
5.6%
E 2
 
5.6%
Other values (6) 7
19.4%
Decimal Number
ValueCountFrequency (%)
0 3
37.5%
2 2
25.0%
9 1
 
12.5%
1 1
 
12.5%
7 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
# 2
28.6%
. 2
28.6%
· 1
14.3%
' 1
14.3%
, 1
14.3%
Space Separator
ValueCountFrequency (%)
26
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 799
80.0%
Latin 121
 
12.1%
Common 79
 
7.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
어 57
 
7.1%
헤 56
 
7.0%
미 39
 
4.9%
용 30
 
3.8%
실 30
 
3.8%
리 24
 
3.0%
스 20
 
2.5%
이 15
 
1.9%
아 14
 
1.8%
가 12
 
1.5%
Other values (219) 502
62.8%
Latin
ValueCountFrequency (%)
i 11
 
9.1%
a 9
 
7.4%
n 8
 
6.6%
o 7
 
5.8%
r 6
 
5.0%
l 5
 
4.1%
m 5
 
4.1%
H 5
 
4.1%
e 5
 
4.1%
d 5
 
4.1%
Other values (24) 55
45.5%
Common
ValueCountFrequency (%)
26
32.9%
( 18
22.8%
) 18
22.8%
0 3
 
3.8%
# 2
 
2.5%
. 2
 
2.5%
2 2
 
2.5%
· 1
 
1.3%
9 1
 
1.3%
' 1
 
1.3%
Other values (5) 5
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 799
80.0%
ASCII 199
 
19.9%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
어 57
 
7.1%
헤 56
 
7.0%
미 39
 
4.9%
용 30
 
3.8%
실 30
 
3.8%
리 24
 
3.0%
스 20
 
2.5%
이 15
 
1.9%
아 14
 
1.8%
가 12
 
1.5%
Other values (219) 502
62.8%
ASCII
ValueCountFrequency (%)
26
 
13.1%
( 18
 
9.0%
) 18
 
9.0%
i 11
 
5.5%
a 9
 
4.5%
n 8
 
4.0%
o 7
 
3.5%
r 6
 
3.0%
l 5
 
2.5%
m 5
 
2.5%
Other values (38) 86
43.2%
None
ValueCountFrequency (%)
· 1
100.0%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct23
Distinct (%)14.2%
Missing4
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean12435.679
Minimum12403
Maximum12467
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-03-14T19:04:42.078582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12403
5-th percentile12413
Q112419
median12437
Q312452
95-th percentile12465
Maximum12467
Range64
Interquartile range (IQR)33

Descriptive statistics

Standard deviation17.42193
Coefficient of variation (CV)0.0014009633
Kurtosis-1.2774757
Mean12435.679
Median Absolute Deviation (MAD)16
Skewness0.16484082
Sum2014580
Variance303.52366
MonotonicityNot monotonic
2024-03-14T19:04:42.474136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
12437 27
16.3%
12452 19
11.4%
12420 16
9.6%
12453 14
8.4%
12413 10
 
6.0%
12419 9
 
5.4%
12417 9
 
5.4%
12418 8
 
4.8%
12438 8
 
4.8%
12467 8
 
4.8%
Other values (13) 34
20.5%
ValueCountFrequency (%)
12403 1
 
0.6%
12412 4
 
2.4%
12413 10
6.0%
12414 3
 
1.8%
12416 2
 
1.2%
12417 9
5.4%
12418 8
4.8%
12419 9
5.4%
12420 16
9.6%
12422 4
 
2.4%
ValueCountFrequency (%)
12467 8
4.8%
12465 6
 
3.6%
12461 1
 
0.6%
12454 3
 
1.8%
12453 14
8.4%
12452 19
11.4%
12451 2
 
1.2%
12449 3
 
1.8%
12447 2
 
1.2%
12444 2
 
1.2%

소재지도로명주소
Text

MISSING 

Distinct157
Distinct (%)96.9%
Missing4
Missing (%)2.4%
Memory size1.4 KiB
2024-03-14T19:04:43.994341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length34
Mean length24.277778
Min length17

Characters and Unicode

Total characters3933
Distinct characters136
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

Unique152 ?
Unique (%)93.8%

Sample

1st row경기도 가평군 가평읍 가화로 104-1
2nd row경기도 가평군 가평읍 오리나무길 13
3rd row경기도 가평군 청평면 잠곡로 37, 1층
4th row경기도 가평군 청평면 청평중앙로 37-1
5th row경기도 가평군 조종면 현창로56번길 19
ValueCountFrequency (%)
경기도 162
17.0%
가평군 162
17.0%
1층 86
 
9.0%
가평읍 65
 
6.8%
청평면 41
 
4.3%
조종면 36
 
3.8%
가화로 19
 
2.0%
2층 16
 
1.7%
청평중앙로 15
 
1.6%
설악면 15
 
1.6%
Other values (190) 337
35.3%
2024-03-14T19:04:45.838477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
792
20.1%
평 289
 
7.3%
가 251
 
6.4%
1 241
 
6.1%
군 168
 
4.3%
경 166
 
4.2%
기 163
 
4.1%
도 162
 
4.1%
로 134
 
3.4%
, 109
 
2.8%
Other values (126) 1458
37.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2351
59.8%
Space Separator 792
 
20.1%
Decimal Number 624
 
15.9%
Other Punctuation 109
 
2.8%
Dash Punctuation 40
 
1.0%
Close Punctuation 6
 
0.2%
Open Punctuation 6
 
0.2%
Uppercase Letter 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
평 289
 
12.3%
가 251
 
10.7%
군 168
 
7.1%
경 166
 
7.1%
기 163
 
6.9%
도 162
 
6.9%
로 134
 
5.7%
층 104
 
4.4%
면 97
 
4.1%
청 66
 
2.8%
Other values (108) 751
31.9%
Decimal Number
ValueCountFrequency (%)
1 241
38.6%
2 99
15.9%
3 47
 
7.5%
0 42
 
6.7%
8 41
 
6.6%
4 39
 
6.2%
7 38
 
6.1%
5 32
 
5.1%
6 28
 
4.5%
9 17
 
2.7%
Uppercase Letter
ValueCountFrequency (%)
A 3
60.0%
E 1
 
20.0%
B 1
 
20.0%
Space Separator
ValueCountFrequency (%)
792
100.0%
Other Punctuation
ValueCountFrequency (%)
, 109
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 40
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2351
59.8%
Common 1577
40.1%
Latin 5
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
평 289
 
12.3%
가 251
 
10.7%
군 168
 
7.1%
경 166
 
7.1%
기 163
 
6.9%
도 162
 
6.9%
로 134
 
5.7%
층 104
 
4.4%
면 97
 
4.1%
청 66
 
2.8%
Other values (108) 751
31.9%
Common
ValueCountFrequency (%)
792
50.2%
1 241
 
15.3%
, 109
 
6.9%
2 99
 
6.3%
3 47
 
3.0%
0 42
 
2.7%
8 41
 
2.6%
- 40
 
2.5%
4 39
 
2.5%
7 38
 
2.4%
Other values (5) 89
 
5.6%
Latin
ValueCountFrequency (%)
A 3
60.0%
E 1
 
20.0%
B 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2351
59.8%
ASCII 1582
40.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
792
50.1%
1 241
 
15.2%
, 109
 
6.9%
2 99
 
6.3%
3 47
 
3.0%
0 42
 
2.7%
8 41
 
2.6%
- 40
 
2.5%
4 39
 
2.5%
7 38
 
2.4%
Other values (8) 94
 
5.9%
Hangul
ValueCountFrequency (%)
평 289
 
12.3%
가 251
 
10.7%
군 168
 
7.1%
경 166
 
7.1%
기 163
 
6.9%
도 162
 
6.9%
로 134
 
5.7%
층 104
 
4.4%
면 97
 
4.1%
청 66
 
2.8%
Other values (108) 751
31.9%

소재지지번주소
Text

Distinct163
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-03-14T19:04:47.228264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length38
Mean length25.566265
Min length19

Characters and Unicode

Total characters4244
Distinct characters96
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

Unique160 ?
Unique (%)96.4%

Sample

1st row경기도 가평군 가평읍 읍내리 476
2nd row경기도 가평군 가평읍 대곡리 234-6
3rd row경기도 가평군 청평면 청평리 388-17 외 1필지, 1층
4th row경기도 가평군 청평면 청평리 463-1
5th row경기도 가평군 조종면 현리 262-63
ValueCountFrequency (%)
경기도 166
17.0%
가평군 166
17.0%
가평읍 67
 
6.9%
1층 62
 
6.3%
청평면 42
 
4.3%
청평리 39
 
4.0%
읍내리 38
 
3.9%
조종면 37
 
3.8%
현리 36
 
3.7%
대곡리 25
 
2.6%
Other values (212) 299
30.6%
2024-03-14T19:04:48.803982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
973
22.9%
평 316
 
7.4%
가 237
 
5.6%
1 190
 
4.5%
리 167
 
3.9%
군 167
 
3.9%
기 166
 
3.9%
경 166
 
3.9%
도 166
 
3.9%
- 162
 
3.8%
Other values (86) 1534
36.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2172
51.2%
Space Separator 973
22.9%
Decimal Number 883
20.8%
Dash Punctuation 162
 
3.8%
Other Punctuation 41
 
1.0%
Close Punctuation 5
 
0.1%
Open Punctuation 5
 
0.1%
Uppercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
평 316
14.5%
가 237
10.9%
리 167
 
7.7%
군 167
 
7.7%
기 166
 
7.6%
경 166
 
7.6%
도 166
 
7.6%
읍 105
 
4.8%
면 99
 
4.6%
청 82
 
3.8%
Other values (68) 501
23.1%
Decimal Number
ValueCountFrequency (%)
1 190
21.5%
2 143
16.2%
4 133
15.1%
3 91
10.3%
6 81
9.2%
7 70
 
7.9%
0 53
 
6.0%
5 48
 
5.4%
9 38
 
4.3%
8 36
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
B 1
33.3%
E 1
33.3%
A 1
33.3%
Space Separator
ValueCountFrequency (%)
973
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 162
100.0%
Other Punctuation
ValueCountFrequency (%)
, 41
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2172
51.2%
Common 2069
48.8%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
평 316
14.5%
가 237
10.9%
리 167
 
7.7%
군 167
 
7.7%
기 166
 
7.6%
경 166
 
7.6%
도 166
 
7.6%
읍 105
 
4.8%
면 99
 
4.6%
청 82
 
3.8%
Other values (68) 501
23.1%
Common
ValueCountFrequency (%)
973
47.0%
1 190
 
9.2%
- 162
 
7.8%
2 143
 
6.9%
4 133
 
6.4%
3 91
 
4.4%
6 81
 
3.9%
7 70
 
3.4%
0 53
 
2.6%
5 48
 
2.3%
Other values (5) 125
 
6.0%
Latin
ValueCountFrequency (%)
B 1
33.3%
E 1
33.3%
A 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2172
51.2%
ASCII 2072
48.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
973
47.0%
1 190
 
9.2%
- 162
 
7.8%
2 143
 
6.9%
4 133
 
6.4%
3 91
 
4.4%
6 81
 
3.9%
7 70
 
3.4%
0 53
 
2.6%
5 48
 
2.3%
Other values (8) 128
 
6.2%
Hangul
ValueCountFrequency (%)
평 316
14.5%
가 237
10.9%
리 167
 
7.7%
군 167
 
7.7%
기 166
 
7.6%
경 166
 
7.6%
도 166
 
7.6%
읍 105
 
4.8%
면 99
 
4.6%
청 82
 
3.8%
Other values (68) 501
23.1%

소재지전화번호
Text

MISSING 

Distinct72
Distinct (%)100.0%
Missing94
Missing (%)56.6%
Memory size1.4 KiB
2024-03-14T19:04:49.861273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.027778
Min length12

Characters and Unicode

Total characters866
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique72 ?
Unique (%)100.0%

Sample

1st row031-582-2718
2nd row031-582-3995
3rd row031-584-2145
4th row031-584-3062
5th row031-585-0364
ValueCountFrequency (%)
031-584-3447 1
 
1.4%
031-584-2145 1
 
1.4%
031-584-7731 1
 
1.4%
031-584-7760 1
 
1.4%
031-581-0508 1
 
1.4%
031-585-4235 1
 
1.4%
031-584-5476 1
 
1.4%
031-581-5430 1
 
1.4%
031-582-2898 1
 
1.4%
031-582-2718 1
 
1.4%
Other values (62) 62
86.1%
2024-03-14T19:04:51.301330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 144
16.6%
5 119
13.7%
1 105
12.1%
8 105
12.1%
0 102
11.8%
3 101
11.7%
4 56
 
6.5%
2 49
 
5.7%
6 32
 
3.7%
7 28
 
3.2%
Other values (2) 25
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 721
83.3%
Dash Punctuation 144
 
16.6%
Space Separator 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 119
16.5%
1 105
14.6%
8 105
14.6%
0 102
14.1%
3 101
14.0%
4 56
7.8%
2 49
6.8%
6 32
 
4.4%
7 28
 
3.9%
9 24
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 144
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 866
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 144
16.6%
5 119
13.7%
1 105
12.1%
8 105
12.1%
0 102
11.8%
3 101
11.7%
4 56
 
6.5%
2 49
 
5.7%
6 32
 
3.7%
7 28
 
3.2%
Other values (2) 25
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 866
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 144
16.6%
5 119
13.7%
1 105
12.1%
8 105
12.1%
0 102
11.8%
3 101
11.7%
4 56
 
6.5%
2 49
 
5.7%
6 32
 
3.7%
7 28
 
3.2%
Other values (2) 25
 
2.9%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-02-14
166 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-02-14
2nd row2024-02-14
3rd row2024-02-14
4th row2024-02-14
5th row2024-02-14

Common Values

ValueCountFrequency (%)
2024-02-14 166
100.0%

Length

2024-03-14T19:04:51.716729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:04:52.030332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-02-14 166
100.0%

Interactions

2024-03-14T19:04:37.669912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T19:04:52.217089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명소재지우편번호소재지전화번호
업종명1.0000.0001.000
소재지우편번호0.0001.0001.000
소재지전화번호1.0001.0001.000
2024-03-14T19:04:52.458667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호업종명
소재지우편번호1.0000.000
업종명0.0001.000

Missing values

2024-03-14T19:04:38.043390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T19:04:38.429769image/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.
2024-03-14T19:04:38.747354image/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

업종명업소명소재지우편번호소재지도로명주소소재지지번주소소재지전화번호데이터기준일자
0미용업예쁘다미장원12419경기도 가평군 가평읍 가화로 104-1경기도 가평군 가평읍 읍내리 476031-582-27182024-02-14
1미용업제일미용실12420경기도 가평군 가평읍 오리나무길 13경기도 가평군 가평읍 대곡리 234-6031-582-39952024-02-14
2미용업클래식헤어12452경기도 가평군 청평면 잠곡로 37, 1층경기도 가평군 청평면 청평리 388-17 외 1필지, 1층031-584-21452024-02-14
3미용업캐리헤어12452경기도 가평군 청평면 청평중앙로 37-1경기도 가평군 청평면 청평리 463-1031-584-30622024-02-14
4미용업오미용실12437경기도 가평군 조종면 현창로56번길 19경기도 가평군 조종면 현리 262-63031-585-03642024-02-14
5미용업정순미미용실12420경기도 가평군 가평읍 오리나무길 27, 1층경기도 가평군 가평읍 대곡리 230-3 외 1필지, 1층031-582-18842024-02-14
6미용업유미미용실12413경기도 가평군 가평읍 가화로 135 (외1필지)경기도 가평군 가평읍 읍내리 453-3 외1필지031-582-25152024-02-14
7미용업지영미장원<NA><NA>경기도 가평군 가평읍 대곡리 179031-582-36832024-02-14
8미용업여왕미용실12420경기도 가평군 가평읍 오리나무길 22경기도 가평군 가평읍 대곡리 240-10031-582-14262024-02-14
9미용업명동헤어클럽12418경기도 가평군 가평읍 연인2길 1-1경기도 가평군 가평읍 읍내리 468-19<NA>2024-02-14
업종명업소명소재지우편번호소재지도로명주소소재지지번주소소재지전화번호데이터기준일자
156네일미용업리아풋케어12418경기도 가평군 가평읍 석봉로 166, 1층경기도 가평군 가평읍 읍내리 493-4 1층<NA>2024-02-14
157일반미용업, 피부미용업제이제이헤어(J.J hair)12437경기도 가평군 조종면 현창로38번길 9, 1층경기도 가평군 조종면 현리 264-48<NA>2024-02-14
158일반미용업, 네일미용업스위트네일12437경기도 가평군 조종면 조종새싹로 11경기도 가평군 조종면 현리 274-8<NA>2024-02-14
159피부미용업, 네일미용업키·키12453경기도 가평군 청평면 잠곡로 12, 1층경기도 가평군 청평면 청평리 413-10 외1필지, 1층<NA>2024-02-14
160화장ㆍ분장 미용업유브로우12420경기도 가평군 가평읍 오리나무길 20, 1층경기도 가평군 가평읍 대곡리 240-9 1층<NA>2024-02-14
161일반미용업, 화장ㆍ분장 미용업헤어스케치12419경기도 가평군 가평읍 가화로 122, 1층경기도 가평군 가평읍 읍내리 471-2 , 1층<NA>2024-02-14
162일반미용업, 화장ㆍ분장 미용업진아염색방12452경기도 가평군 청평면 청평중앙로 52, 106동 1층경기도 가평군 청평면 청평리 432-10 청평프라자<NA>2024-02-14
163일반미용업, 화장ㆍ분장 미용업아이유헤어12444경기도 가평군 상면 비룡로 2219, 1층경기도 가평군 상면 연하리 475-3 1층<NA>2024-02-14
164피부미용업, 화장ㆍ분장 미용업지원뷰티12437경기도 가평군 조종면 조종새싹로 20-5, 1층경기도 가평군 조종면 현리 277-4 1층<NA>2024-02-14
165일반미용업, 네일미용업, 화장ㆍ분장 미용업뷰티그리다12437경기도 가평군 조종면 조종새싹로 20-8, 캐쉬박스 1층경기도 가평군 조종면 현리 262-3<NA>2024-02-14