Overview

Dataset statistics

Number of variables8
Number of observations3648
Missing cells3917
Missing cells (%)13.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory231.7 KiB
Average record size in memory65.0 B

Variable types

Text4
Categorical2
DateTime1
Numeric1

Dataset

Description경기도 평택시 미용업현황(업소명, 영업상태명, 폐업일자, 도로명우편번호, 소재지도로명주소, 소재지지번주소, 지번우편번호, 업태명) 정보입니다.
Author경기도 평택시
URLhttps://www.data.go.kr/data/15039666/fileData.do

Alerts

폐업일자 has 1919 (52.6%) missing valuesMissing
도로명우편번호 has 923 (25.3%) missing valuesMissing
소재지도로명주소 has 899 (24.6%) missing valuesMissing
지번우편번호 has 163 (4.5%) missing valuesMissing

Reproduction

Analysis started2023-12-12 08:17:09.762070
Analysis finished2023-12-12 08:17:11.459830
Duration1.7 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

Distinct3301
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Memory size28.6 KiB
2023-12-12T17:17:11.741775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length32
Mean length6.1134868
Min length1

Characters and Unicode

Total characters22302
Distinct characters741
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3024 ?
Unique (%)82.9%

Sample

1st row#블레스헤어
2nd row#삐삐살롱
3rd row#오늘,꾸밈헤어(HAIR)
4th row(Heather's)헤더스
5th row(주)코리아나화장품
ValueCountFrequency (%)
hair 27
 
0.7%
nail 16
 
0.4%
헤어 15
 
0.4%
미용실 13
 
0.3%
네일 12
 
0.3%
평택점 11
 
0.3%
beauty 11
 
0.3%
salon 9
 
0.2%
헤어클럽 7
 
0.2%
포맨 7
 
0.2%
Other values (3437) 3917
96.8%
2023-12-12T17:17:12.178159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
어 1631
 
7.3%
헤 1551
 
7.0%
미 755
 
3.4%
스 542
 
2.4%
리 537
 
2.4%
실 500
 
2.2%
용 497
 
2.2%
이 460
 
2.1%
411
 
1.8%
일 404
 
1.8%
Other values (731) 15014
67.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19302
86.5%
Lowercase Letter 931
 
4.2%
Uppercase Letter 782
 
3.5%
Space Separator 411
 
1.8%
Close Punctuation 272
 
1.2%
Open Punctuation 272
 
1.2%
Decimal Number 162
 
0.7%
Other Punctuation 153
 
0.7%
Dash Punctuation 7
 
< 0.1%
Modifier Symbol 4
 
< 0.1%
Other values (3) 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
어 1631
 
8.4%
헤 1551
 
8.0%
미 755
 
3.9%
스 542
 
2.8%
리 537
 
2.8%
실 500
 
2.6%
용 497
 
2.6%
이 460
 
2.4%
일 404
 
2.1%
네 361
 
1.9%
Other values (651) 12064
62.5%
Lowercase Letter
ValueCountFrequency (%)
a 125
13.4%
e 108
11.6%
i 100
10.7%
o 76
8.2%
l 73
7.8%
r 68
 
7.3%
h 56
 
6.0%
n 52
 
5.6%
s 50
 
5.4%
t 43
 
4.6%
Other values (16) 180
19.3%
Uppercase Letter
ValueCountFrequency (%)
A 73
 
9.3%
N 68
 
8.7%
S 57
 
7.3%
I 56
 
7.2%
E 47
 
6.0%
H 46
 
5.9%
L 44
 
5.6%
O 42
 
5.4%
M 38
 
4.9%
B 38
 
4.9%
Other values (15) 273
34.9%
Decimal Number
ValueCountFrequency (%)
1 43
26.5%
2 37
22.8%
0 21
13.0%
3 17
 
10.5%
7 10
 
6.2%
4 9
 
5.6%
8 9
 
5.6%
9 7
 
4.3%
5 6
 
3.7%
6 3
 
1.9%
Other Punctuation
ValueCountFrequency (%)
& 45
29.4%
. 30
19.6%
, 29
19.0%
' 22
14.4%
# 18
 
11.8%
: 7
 
4.6%
· 1
 
0.7%
; 1
 
0.7%
Modifier Symbol
ValueCountFrequency (%)
` 2
50.0%
´ 1
25.0%
˚ 1
25.0%
Math Symbol
ValueCountFrequency (%)
> 1
50.0%
< 1
50.0%
Space Separator
ValueCountFrequency (%)
411
100.0%
Close Punctuation
ValueCountFrequency (%)
) 272
100.0%
Open Punctuation
ValueCountFrequency (%)
( 272
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19292
86.5%
Latin 1713
 
7.7%
Common 1287
 
5.8%
Han 10
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
어 1631
 
8.5%
헤 1551
 
8.0%
미 755
 
3.9%
스 542
 
2.8%
리 537
 
2.8%
실 500
 
2.6%
용 497
 
2.6%
이 460
 
2.4%
일 404
 
2.1%
네 361
 
1.9%
Other values (646) 12054
62.5%
Latin
ValueCountFrequency (%)
a 125
 
7.3%
e 108
 
6.3%
i 100
 
5.8%
o 76
 
4.4%
A 73
 
4.3%
l 73
 
4.3%
r 68
 
4.0%
N 68
 
4.0%
S 57
 
3.3%
h 56
 
3.3%
Other values (41) 909
53.1%
Common
ValueCountFrequency (%)
411
31.9%
) 272
21.1%
( 272
21.1%
& 45
 
3.5%
1 43
 
3.3%
2 37
 
2.9%
. 30
 
2.3%
, 29
 
2.3%
' 22
 
1.7%
0 21
 
1.6%
Other values (19) 105
 
8.2%
Han
ValueCountFrequency (%)
美 6
60.0%
本 1
 
10.0%
粧 1
 
10.0%
秀 1
 
10.0%
愛 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19292
86.5%
ASCII 2996
 
13.4%
CJK 10
 
< 0.1%
None 2
 
< 0.1%
Punctuation 1
 
< 0.1%
Modifier Letters 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
어 1631
 
8.5%
헤 1551
 
8.0%
미 755
 
3.9%
스 542
 
2.8%
리 537
 
2.8%
실 500
 
2.6%
용 497
 
2.6%
이 460
 
2.4%
일 404
 
2.1%
네 361
 
1.9%
Other values (646) 12054
62.5%
ASCII
ValueCountFrequency (%)
411
 
13.7%
) 272
 
9.1%
( 272
 
9.1%
a 125
 
4.2%
e 108
 
3.6%
i 100
 
3.3%
o 76
 
2.5%
A 73
 
2.4%
l 73
 
2.4%
r 68
 
2.3%
Other values (66) 1418
47.3%
CJK
ValueCountFrequency (%)
美 6
60.0%
本 1
 
10.0%
粧 1
 
10.0%
秀 1
 
10.0%
愛 1
 
10.0%
None
ValueCountFrequency (%)
´ 1
50.0%
· 1
50.0%
Punctuation
ValueCountFrequency (%)
’ 1
100.0%
Modifier Letters
ValueCountFrequency (%)
˚ 1
100.0%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.6 KiB
영업
1919 
폐업
1729 

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 1919
52.6%
폐업 1729
47.4%

Length

2023-12-12T17:17:12.316698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:17:12.430066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 1919
52.6%
폐업 1729
47.4%

폐업일자
Date

MISSING 

Distinct1308
Distinct (%)75.7%
Missing1919
Missing (%)52.6%
Memory size28.6 KiB
Minimum1996-08-07 00:00:00
Maximum2023-02-07 00:00:00
2023-12-12T17:17:12.548060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:17:12.684583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

도로명우편번호
Real number (ℝ)

MISSING 

Distinct220
Distinct (%)8.1%
Missing923
Missing (%)25.3%
Infinite0
Infinite (%)0.0%
Mean17866.697
Minimum17707
Maximum18034
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size32.2 KiB
2023-12-12T17:17:12.826421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum17707
5-th percentile17734
Q117782
median17870
Q317921
95-th percentile18014
Maximum18034
Range327
Interquartile range (IQR)139

Descriptive statistics

Standard deviation82.818729
Coefficient of variation (CV)0.0046353688
Kurtosis-0.8716387
Mean17866.697
Median Absolute Deviation (MAD)66
Skewness0.038528885
Sum48686749
Variance6858.9419
MonotonicityNot monotonic
2023-12-12T17:17:12.982249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17854 110
 
3.0%
17941 65
 
1.8%
17955 63
 
1.7%
17774 61
 
1.7%
17909 59
 
1.6%
17779 57
 
1.6%
17936 54
 
1.5%
17855 52
 
1.4%
17758 52
 
1.4%
17911 51
 
1.4%
Other values (210) 2101
57.6%
(Missing) 923
25.3%
ValueCountFrequency (%)
17707 5
 
0.1%
17708 1
 
< 0.1%
17712 1
 
< 0.1%
17713 2
 
0.1%
17714 9
 
0.2%
17719 1
 
< 0.1%
17720 17
0.5%
17726 8
 
0.2%
17727 6
 
0.2%
17729 25
0.7%
ValueCountFrequency (%)
18034 4
 
0.1%
18033 35
1.0%
18032 13
 
0.4%
18031 8
 
0.2%
18030 1
 
< 0.1%
18029 5
 
0.1%
18028 5
 
0.1%
18025 13
 
0.4%
18018 9
 
0.2%
18017 14
 
0.4%

소재지도로명주소
Text

MISSING 

Distinct2555
Distinct (%)92.9%
Missing899
Missing (%)24.6%
Memory size28.6 KiB
2023-12-12T17:17:13.329213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length54
Mean length30.027283
Min length17

Characters and Unicode

Total characters82545
Distinct characters385
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2392 ?
Unique (%)87.0%

Sample

1st row경기도 평택시 평남로 722, 1동 1층 (비전동)
2nd row경기도 평택시 안중읍 안현로서3길 90, 1층
3rd row경기도 평택시 송탄로 270, 201호 (서정동)
4th row경기도 평택시 팽성읍 안정순환로138번길 80, 1층
5th row경기도 평택시 안중읍 안현로서8길 23, 2층
ValueCountFrequency (%)
경기도 2749
 
15.5%
평택시 2749
 
15.5%
1층 981
 
5.5%
비전동 470
 
2.7%
서정동 306
 
1.7%
2층 289
 
1.6%
안중읍 235
 
1.3%
상가동 211
 
1.2%
합정동 184
 
1.0%
평택동 175
 
1.0%
Other values (2031) 9334
52.8%
2023-12-12T17:17:13.899269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14935
 
18.1%
1 4017
 
4.9%
평 3444
 
4.2%
택 3303
 
4.0%
시 2875
 
3.5%
경 2806
 
3.4%
기 2797
 
3.4%
도 2779
 
3.4%
동 2773
 
3.4%
, 2666
 
3.2%
Other values (375) 40150
48.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 44907
54.4%
Space Separator 14935
 
18.1%
Decimal Number 14465
 
17.5%
Other Punctuation 2687
 
3.3%
Close Punctuation 2312
 
2.8%
Open Punctuation 2312
 
2.8%
Dash Punctuation 633
 
0.8%
Uppercase Letter 254
 
0.3%
Lowercase Letter 31
 
< 0.1%
Math Symbol 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
평 3444
 
7.7%
택 3303
 
7.4%
시 2875
 
6.4%
경 2806
 
6.2%
기 2797
 
6.2%
도 2779
 
6.2%
동 2773
 
6.2%
로 2350
 
5.2%
층 1464
 
3.3%
길 1323
 
2.9%
Other values (322) 18993
42.3%
Uppercase Letter
ValueCountFrequency (%)
A 52
20.5%
B 25
9.8%
K 19
 
7.5%
S 18
 
7.1%
T 17
 
6.7%
E 16
 
6.3%
L 16
 
6.3%
C 11
 
4.3%
I 11
 
4.3%
D 9
 
3.5%
Other values (11) 60
23.6%
Lowercase Letter
ValueCountFrequency (%)
e 6
19.4%
l 4
12.9%
r 4
12.9%
h 4
12.9%
a 3
9.7%
d 2
 
6.5%
i 2
 
6.5%
p 2
 
6.5%
m 1
 
3.2%
o 1
 
3.2%
Other values (2) 2
 
6.5%
Decimal Number
ValueCountFrequency (%)
1 4017
27.8%
2 2446
16.9%
0 1595
 
11.0%
3 1501
 
10.4%
5 1165
 
8.1%
4 1048
 
7.2%
6 894
 
6.2%
7 639
 
4.4%
9 584
 
4.0%
8 576
 
4.0%
Other Punctuation
ValueCountFrequency (%)
, 2666
99.2%
@ 19
 
0.7%
. 2
 
0.1%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
50.0%
ⅵ 1
50.0%
Space Separator
ValueCountFrequency (%)
14935
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2312
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2312
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 633
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 44906
54.4%
Common 37351
45.2%
Latin 287
 
0.3%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
평 3444
 
7.7%
택 3303
 
7.4%
시 2875
 
6.4%
경 2806
 
6.2%
기 2797
 
6.2%
도 2779
 
6.2%
동 2773
 
6.2%
로 2350
 
5.2%
층 1464
 
3.3%
길 1323
 
2.9%
Other values (321) 18992
42.3%
Latin
ValueCountFrequency (%)
A 52
18.1%
B 25
 
8.7%
K 19
 
6.6%
S 18
 
6.3%
T 17
 
5.9%
E 16
 
5.6%
L 16
 
5.6%
C 11
 
3.8%
I 11
 
3.8%
D 9
 
3.1%
Other values (25) 93
32.4%
Common
ValueCountFrequency (%)
14935
40.0%
1 4017
 
10.8%
, 2666
 
7.1%
2 2446
 
6.5%
) 2312
 
6.2%
( 2312
 
6.2%
0 1595
 
4.3%
3 1501
 
4.0%
5 1165
 
3.1%
4 1048
 
2.8%
Other values (8) 3354
 
9.0%
Han
ValueCountFrequency (%)
家 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 44905
54.4%
ASCII 37636
45.6%
Number Forms 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14935
39.7%
1 4017
 
10.7%
, 2666
 
7.1%
2 2446
 
6.5%
) 2312
 
6.1%
( 2312
 
6.1%
0 1595
 
4.2%
3 1501
 
4.0%
5 1165
 
3.1%
4 1048
 
2.8%
Other values (41) 3639
 
9.7%
Hangul
ValueCountFrequency (%)
평 3444
 
7.7%
택 3303
 
7.4%
시 2875
 
6.4%
경 2806
 
6.2%
기 2797
 
6.2%
도 2779
 
6.2%
동 2773
 
6.2%
로 2350
 
5.2%
층 1464
 
3.3%
길 1323
 
2.9%
Other values (320) 18991
42.3%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
50.0%
ⅵ 1
50.0%
Compat Jamo
ValueCountFrequency (%)
ㅠ 1
100.0%
CJK
ValueCountFrequency (%)
家 1
100.0%

소재지지번주소
Text

Distinct3027
Distinct (%)83.3%
Missing13
Missing (%)0.4%
Memory size28.6 KiB
2023-12-12T17:17:14.192552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length50
Mean length22.630536
Min length15

Characters and Unicode

Total characters82262
Distinct characters356
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2594 ?
Unique (%)71.4%

Sample

1st row경기도 평택시 비전동 878-2
2nd row경기도 평택시 안중읍 현화리 297
3rd row경기도 평택시 서정동 822-9 201호
4th row경기도 평택시 팽성읍 안정리 133-14
5th row경기도 평택시 안중읍 현화리 836-3
ValueCountFrequency (%)
경기도 3635
20.2%
평택시 3635
20.2%
비전동 591
 
3.3%
서정동 477
 
2.6%
1층 414
 
2.3%
안중읍 286
 
1.6%
평택동 282
 
1.6%
합정동 246
 
1.4%
신장동 214
 
1.2%
지산동 191
 
1.1%
Other values (3125) 8047
44.7%
2023-12-12T17:17:14.673744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17616
21.4%
1 4371
 
5.3%
평 4015
 
4.9%
택 4002
 
4.9%
도 3759
 
4.6%
시 3668
 
4.5%
경 3645
 
4.4%
기 3639
 
4.4%
동 3267
 
4.0%
- 2971
 
3.6%
Other values (346) 31309
38.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 42149
51.2%
Decimal Number 18444
22.4%
Space Separator 17616
21.4%
Dash Punctuation 2971
 
3.6%
Close Punctuation 349
 
0.4%
Open Punctuation 349
 
0.4%
Uppercase Letter 218
 
0.3%
Other Punctuation 136
 
0.2%
Lowercase Letter 28
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
평 4015
 
9.5%
택 4002
 
9.5%
도 3759
 
8.9%
시 3668
 
8.7%
경 3645
 
8.6%
기 3639
 
8.6%
동 3267
 
7.8%
정 863
 
2.0%
리 768
 
1.8%
층 717
 
1.7%
Other values (294) 13806
32.8%
Uppercase Letter
ValueCountFrequency (%)
A 46
21.1%
B 23
10.6%
S 16
 
7.3%
L 16
 
7.3%
T 15
 
6.9%
D 13
 
6.0%
E 13
 
6.0%
C 11
 
5.0%
K 9
 
4.1%
I 7
 
3.2%
Other values (11) 49
22.5%
Lowercase Letter
ValueCountFrequency (%)
e 6
21.4%
r 4
14.3%
h 4
14.3%
a 3
10.7%
d 3
10.7%
p 2
 
7.1%
i 2
 
7.1%
m 1
 
3.6%
w 1
 
3.6%
c 1
 
3.6%
Decimal Number
ValueCountFrequency (%)
1 4371
23.7%
2 2278
12.4%
3 1765
9.6%
8 1588
 
8.6%
0 1571
 
8.5%
4 1479
 
8.0%
7 1450
 
7.9%
5 1449
 
7.9%
6 1446
 
7.8%
9 1047
 
5.7%
Other Punctuation
ValueCountFrequency (%)
, 120
88.2%
@ 13
 
9.6%
. 2
 
1.5%
/ 1
 
0.7%
Space Separator
ValueCountFrequency (%)
17616
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2971
100.0%
Close Punctuation
ValueCountFrequency (%)
) 349
100.0%
Open Punctuation
ValueCountFrequency (%)
( 349
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 42149
51.2%
Common 39866
48.5%
Latin 247
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
평 4015
 
9.5%
택 4002
 
9.5%
도 3759
 
8.9%
시 3668
 
8.7%
경 3645
 
8.6%
기 3639
 
8.6%
동 3267
 
7.8%
정 863
 
2.0%
리 768
 
1.8%
층 717
 
1.7%
Other values (294) 13806
32.8%
Latin
ValueCountFrequency (%)
A 46
18.6%
B 23
 
9.3%
S 16
 
6.5%
L 16
 
6.5%
T 15
 
6.1%
D 13
 
5.3%
E 13
 
5.3%
C 11
 
4.5%
K 9
 
3.6%
I 7
 
2.8%
Other values (23) 78
31.6%
Common
ValueCountFrequency (%)
17616
44.2%
1 4371
 
11.0%
- 2971
 
7.5%
2 2278
 
5.7%
3 1765
 
4.4%
8 1588
 
4.0%
0 1571
 
3.9%
4 1479
 
3.7%
7 1450
 
3.6%
5 1449
 
3.6%
Other values (9) 3328
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 42149
51.2%
ASCII 40112
48.8%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17616
43.9%
1 4371
 
10.9%
- 2971
 
7.4%
2 2278
 
5.7%
3 1765
 
4.4%
8 1588
 
4.0%
0 1571
 
3.9%
4 1479
 
3.7%
7 1450
 
3.6%
5 1449
 
3.6%
Other values (41) 3574
 
8.9%
Hangul
ValueCountFrequency (%)
평 4015
 
9.5%
택 4002
 
9.5%
도 3759
 
8.9%
시 3668
 
8.7%
경 3645
 
8.6%
기 3639
 
8.6%
동 3267
 
7.8%
정 863
 
2.0%
리 768
 
1.8%
층 717
 
1.7%
Other values (294) 13806
32.8%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%

지번우편번호
Text

MISSING 

Distinct117
Distinct (%)3.4%
Missing163
Missing (%)4.5%
Memory size28.6 KiB
2023-12-12T17:17:14.983876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters24395
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

Unique29 ?
Unique (%)0.8%

Sample

1st row450-811
2nd row451-885
3rd row459-813
4th row451-807
5th row451-885
ValueCountFrequency (%)
459-813 296
 
8.5%
450-150 258
 
7.4%
459-110 181
 
5.2%
450-130 163
 
4.7%
450-826 150
 
4.3%
459-120 144
 
4.1%
459-812 136
 
3.9%
450-040 131
 
3.8%
451-885 127
 
3.6%
451-822 112
 
3.2%
Other values (107) 1787
51.3%
2023-12-12T17:17:15.409982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 4047
16.6%
4 3947
16.2%
0 3799
15.6%
- 3485
14.3%
1 2752
11.3%
8 2681
11.0%
9 1180
 
4.8%
2 1168
 
4.8%
3 827
 
3.4%
7 263
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20910
85.7%
Dash Punctuation 3485
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 4047
19.4%
4 3947
18.9%
0 3799
18.2%
1 2752
13.2%
8 2681
12.8%
9 1180
 
5.6%
2 1168
 
5.6%
3 827
 
4.0%
7 263
 
1.3%
6 246
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 3485
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24395
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 4047
16.6%
4 3947
16.2%
0 3799
15.6%
- 3485
14.3%
1 2752
11.3%
8 2681
11.0%
9 1180
 
4.8%
2 1168
 
4.8%
3 827
 
3.4%
7 263
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24395
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 4047
16.6%
4 3947
16.2%
0 3799
15.6%
- 3485
14.3%
1 2752
11.3%
8 2681
11.0%
9 1180
 
4.8%
2 1168
 
4.8%
3 827
 
3.4%
7 263
 
1.1%

업태명
Categorical

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size28.6 KiB
일반미용업
2584 
피부미용업
543 
네일아트업
394 
메이크업업
 
83
기타
 
42

Length

Max length6
Median length5
Mean length4.9660088
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일반미용업
2nd row일반미용업
3rd row일반미용업
4th row네일아트업
5th row피부미용업

Common Values

ValueCountFrequency (%)
일반미용업 2584
70.8%
피부미용업 543
 
14.9%
네일아트업 394
 
10.8%
메이크업업 83
 
2.3%
기타 42
 
1.2%
미용업 기타 2
 
0.1%

Length

2023-12-12T17:17:15.619022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:17:15.798344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반미용업 2584
70.8%
피부미용업 543
 
14.9%
네일아트업 394
 
10.8%
메이크업업 83
 
2.3%
기타 44
 
1.2%
미용업 2
 
0.1%

Interactions

2023-12-12T17:17:10.882048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:17:15.904253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업상태명도로명우편번호업태명
영업상태명1.0000.2210.262
도로명우편번호0.2211.0000.121
업태명0.2620.1211.000
2023-12-12T17:17:16.018239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업상태명업태명
영업상태명1.0000.188
업태명0.1881.000
2023-12-12T17:17:16.130762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도로명우편번호영업상태명업태명
도로명우편번호1.0000.1690.064
영업상태명0.1691.0000.188
업태명0.0640.1881.000

Missing values

2023-12-12T17:17:11.036202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:17:11.214238image/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.
2023-12-12T17:17:11.383389image/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

업소명영업상태명폐업일자도로명우편번호소재지도로명주소소재지지번주소지번우편번호업태명
0#블레스헤어영업<NA>17872경기도 평택시 평남로 722, 1동 1층 (비전동)경기도 평택시 비전동 878-2450-811일반미용업
1#삐삐살롱영업<NA>17932경기도 평택시 안중읍 안현로서3길 90, 1층경기도 평택시 안중읍 현화리 297451-885일반미용업
2#오늘,꾸밈헤어(HAIR)영업<NA>17774경기도 평택시 송탄로 270, 201호 (서정동)경기도 평택시 서정동 822-9 201호459-813일반미용업
3(Heather's)헤더스영업<NA>17983경기도 평택시 팽성읍 안정순환로138번길 80, 1층경기도 평택시 팽성읍 안정리 133-14451-807네일아트업
4(주)코리아나화장품영업<NA>17943경기도 평택시 안중읍 안현로서8길 23, 2층경기도 평택시 안중읍 현화리 836-3451-885피부미용업
5101피부영업<NA>17941경기도 평택시 안중읍 송담8길 33-15경기도 평택시 안중읍 안중리 468-2451-884피부미용업
611.8헤어영업<NA>18032경기도 평택시 상서재로4길 13, 110호 (동삭동, 평택센트럴자이 2단지)경기도 평택시 동삭동 33 평택센트럴자이 2단지450-802일반미용업
7123 네일(123 nail)영업<NA>17783경기도 평택시 송탄로 113, 1층 (이충동)경기도 평택시 이충동 495-1 1층459-825네일아트업
8123헤어영업<NA>17852경기도 평택시 비전3로 32, 203호 (비전동, 강일프라자-1)경기도 평택시 비전동 1070-1450-150일반미용업
91st헤어샾 오산공군기지점영업<NA><NA><NA>경기도 평택시 신장동 298-19 2층459-120일반미용업
업소명영업상태명폐업일자도로명우편번호소재지도로명주소소재지지번주소지번우편번호업태명
3638희선미용실폐업2021-10-1917908경기도 평택시 평택3로 36 (합정동)경기도 평택시 합정동 742-13450-831일반미용업
3639희영헤어샆폐업2015-03-3017720경기도 평택시 경기대로 1578, 105호 (독곡동, 삼익상가상가동)경기도 평택시 독곡동 468 삼익상가상가동 105호459-801일반미용업
3640힐링두피케어폐업2020-12-1417871경기도 평택시 문화촌로11번길 51-9 (비전동)경기도 평택시 비전동 866-12450-810일반미용업
3641힐링라이프폐업2015-05-1217921경기도 평택시 원평2로 34, 1층 (평택동)경기도 평택시 평택동 95-5 1층450-827피부미용업
3642힐링밸런스맛사지폐업2021-12-1317913경기도 평택시 평택3로 20, 상가동 201호 (합정동, 주공아파트)경기도 평택시 합정동 834450-833피부미용업
3643힐링순스킨앤바디폐업2022-07-0517756경기도 평택시 송탄로 410, 4층 (지산동)경기도 평택시 지산동 761-12 4층459-110피부미용업
3644힐링타운폐업2014-04-0817915경기도 평택시 중앙2로 150, 2층 (합정동)경기도 평택시 합정동 917-5 2층450-020피부미용업
3645힐링타임365폐업2018-08-0717855경기도 평택시 비전2로 195, 211호 (비전동, 티에스원주차빌딩)경기도 평택시 비전동 1066450-150피부미용업
3646힐링피부폐업2017-11-1417869경기도 평택시 현촌1로 54, 503호 (용이동, 현촌프라자)경기도 평택시 용이동 597-7450-130피부미용업
3647힐링헤어폐업2017-04-0317733경기도 평택시 이충로108번길 6, 1층 (서정동)경기도 평택시 서정동 806459-813일반미용업