Overview

Dataset statistics

Number of variables4
Number of observations2184
Missing cells11
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory70.5 KiB
Average record size in memory33.1 B

Variable types

Categorical1
Text2
Numeric1

Dataset

Description진주시 공중위생업소 현황(숙박업,목욕, 이용, 미용, 세탁, 위생관리, 위생처리, 기타용품제조)을 업종명, 업소명, 소재지 정보 제공
Author경상남도 진주시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15004452

Alerts

영업장면적 has 36 (1.6%) zerosZeros

Reproduction

Analysis started2023-12-11 00:32:32.113303
Analysis finished2023-12-11 00:32:32.850948
Duration0.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

Distinct22
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
일반미용업
811 
숙박업(일반)
271 
피부미용업
193 
세탁업
137 
이용업
133 
Other values (17)
639 

Length

Max length23
Median length5
Mean length5.6895604
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row숙박업(일반)
2nd row숙박업(일반)
3rd row숙박업(일반)
4th row숙박업(일반)
5th row숙박업(일반)

Common Values

ValueCountFrequency (%)
일반미용업 811
37.1%
숙박업(일반) 271
 
12.4%
피부미용업 193
 
8.8%
세탁업 137
 
6.3%
이용업 133
 
6.1%
네일미용업 129
 
5.9%
건물위생관리업 99
 
4.5%
미용업 98
 
4.5%
목욕장업 94
 
4.3%
종합미용업 42
 
1.9%
Other values (12) 177
 
8.1%

Length

2023-12-11T09:32:32.936130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반미용업 883
36.0%
숙박업(일반 271
 
11.0%
피부미용업 269
 
11.0%
네일미용업 219
 
8.9%
미용업 201
 
8.2%
세탁업 137
 
5.6%
이용업 133
 
5.4%
화장ㆍ분장 103
 
4.2%
건물위생관리업 99
 
4.0%
목욕장업 94
 
3.8%
Other values (2) 46
 
1.9%

업소명
Text

Distinct2098
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
2023-12-11T09:32:33.207380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length28
Mean length5.9308608
Min length2

Characters and Unicode

Total characters12953
Distinct characters674
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2022 ?
Unique (%)92.6%

Sample

1st row진주스토리
2nd row진성모텔
3rd row휴모텔
4th row진양장여관
5th row삼학여관
ValueCountFrequency (%)
미용실 43
 
1.8%
hair 16
 
0.7%
nail 8
 
0.3%
진주점 6
 
0.2%
헤어 5
 
0.2%
네일 5
 
0.2%
현대세탁소 4
 
0.2%
에이바헤어 4
 
0.2%
salon 4
 
0.2%
beauty 4
 
0.2%
Other values (2212) 2340
95.9%
2023-12-11T09:32:33.924977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
어 627
 
4.8%
헤 601
 
4.6%
미 337
 
2.6%
이 333
 
2.6%
용 311
 
2.4%
스 259
 
2.0%
255
 
2.0%
리 235
 
1.8%
일 195
 
1.5%
실 193
 
1.5%
Other values (664) 9607
74.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11230
86.7%
Lowercase Letter 551
 
4.3%
Uppercase Letter 429
 
3.3%
Space Separator 255
 
2.0%
Open Punctuation 189
 
1.5%
Close Punctuation 189
 
1.5%
Decimal Number 52
 
0.4%
Other Punctuation 50
 
0.4%
Connector Punctuation 3
 
< 0.1%
Dash Punctuation 3
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
어 627
 
5.6%
헤 601
 
5.4%
미 337
 
3.0%
이 333
 
3.0%
용 311
 
2.8%
스 259
 
2.3%
리 235
 
2.1%
일 195
 
1.7%
실 193
 
1.7%
모 189
 
1.7%
Other values (590) 7950
70.8%
Uppercase Letter
ValueCountFrequency (%)
A 39
 
9.1%
E 35
 
8.2%
H 32
 
7.5%
N 32
 
7.5%
S 32
 
7.5%
L 28
 
6.5%
I 24
 
5.6%
B 22
 
5.1%
J 22
 
5.1%
T 21
 
4.9%
Other values (16) 142
33.1%
Lowercase Letter
ValueCountFrequency (%)
a 82
14.9%
i 72
13.1%
e 55
10.0%
l 45
8.2%
n 44
8.0%
r 38
 
6.9%
o 36
 
6.5%
t 31
 
5.6%
u 23
 
4.2%
h 23
 
4.2%
Other values (12) 102
18.5%
Decimal Number
ValueCountFrequency (%)
1 13
25.0%
2 7
13.5%
7 7
13.5%
6 5
 
9.6%
0 4
 
7.7%
5 4
 
7.7%
9 4
 
7.7%
8 3
 
5.8%
4 3
 
5.8%
3 2
 
3.8%
Other Punctuation
ValueCountFrequency (%)
, 17
34.0%
& 10
20.0%
. 8
16.0%
: 5
 
10.0%
' 3
 
6.0%
# 3
 
6.0%
＆ 2
 
4.0%
; 1
 
2.0%
! 1
 
2.0%
Space Separator
ValueCountFrequency (%)
255
100.0%
Open Punctuation
ValueCountFrequency (%)
( 189
100.0%
Close Punctuation
ValueCountFrequency (%)
) 189
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Symbol
ValueCountFrequency (%)
° 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11226
86.7%
Latin 980
 
7.6%
Common 743
 
5.7%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
어 627
 
5.6%
헤 601
 
5.4%
미 337
 
3.0%
이 333
 
3.0%
용 311
 
2.8%
스 259
 
2.3%
리 235
 
2.1%
일 195
 
1.7%
실 193
 
1.7%
모 189
 
1.7%
Other values (587) 7946
70.8%
Latin
ValueCountFrequency (%)
a 82
 
8.4%
i 72
 
7.3%
e 55
 
5.6%
l 45
 
4.6%
n 44
 
4.5%
A 39
 
4.0%
r 38
 
3.9%
o 36
 
3.7%
E 35
 
3.6%
H 32
 
3.3%
Other values (38) 502
51.2%
Common
ValueCountFrequency (%)
255
34.3%
( 189
25.4%
) 189
25.4%
, 17
 
2.3%
1 13
 
1.7%
& 10
 
1.3%
. 8
 
1.1%
2 7
 
0.9%
7 7
 
0.9%
: 5
 
0.7%
Other values (16) 43
 
5.8%
Han
ValueCountFrequency (%)
美 2
50.0%
炎 1
25.0%
家 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11226
86.7%
ASCII 1720
 
13.3%
CJK 4
 
< 0.1%
None 3
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
어 627
 
5.6%
헤 601
 
5.4%
미 337
 
3.0%
이 333
 
3.0%
용 311
 
2.8%
스 259
 
2.3%
리 235
 
2.1%
일 195
 
1.7%
실 193
 
1.7%
모 189
 
1.7%
Other values (587) 7946
70.8%
ASCII
ValueCountFrequency (%)
255
 
14.8%
( 189
 
11.0%
) 189
 
11.0%
a 82
 
4.8%
i 72
 
4.2%
e 55
 
3.2%
l 45
 
2.6%
n 44
 
2.6%
A 39
 
2.3%
r 38
 
2.2%
Other values (62) 712
41.4%
None
ValueCountFrequency (%)
＆ 2
66.7%
° 1
33.3%
CJK
ValueCountFrequency (%)
美 2
50.0%
炎 1
25.0%
家 1
25.0%

영업소 주소(도로명)
Text

Distinct2145
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
2023-12-11T09:32:34.197523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length75
Median length55
Mean length31.320513
Min length19

Characters and Unicode

Total characters68404
Distinct characters333
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

Unique2106 ?
Unique (%)96.4%

Sample

1st row경상남도 진주시 비봉로54번길 8 (계동)
2nd row경상남도 진주시 진주대로1032번길 11 (동성동)
3rd row경상남도 진주시 진주대로1040번길 10 (동성동)
4th row경상남도 진주시 진주대로891번길 41 (강남동)
5th row경상남도 진주시 진주대로879번길 14-16 (강남동)
ValueCountFrequency (%)
경상남도 2184
 
16.1%
진주시 2184
 
16.1%
1층 479
 
3.5%
1층일부 408
 
3.0%
일부 265
 
2.0%
2층 186
 
1.4%
평거동 182
 
1.3%
하대동 172
 
1.3%
상대동 163
 
1.2%
초전동 155
 
1.1%
Other values (1909) 7198
53.0%
2023-12-11T09:32:34.624708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11411
 
16.7%
1 3660
 
5.4%
진 2765
 
4.0%
상 2751
 
4.0%
주 2590
 
3.8%
동 2440
 
3.6%
남 2408
 
3.5%
도 2317
 
3.4%
경 2292
 
3.4%
시 2292
 
3.4%
Other values (323) 33478
48.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 38876
56.8%
Space Separator 11411
 
16.7%
Decimal Number 11328
 
16.6%
Open Punctuation 2144
 
3.1%
Close Punctuation 2143
 
3.1%
Other Punctuation 1789
 
2.6%
Dash Punctuation 631
 
0.9%
Uppercase Letter 50
 
0.1%
Math Symbol 21
 
< 0.1%
Lowercase Letter 11
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
진 2765
 
7.1%
상 2751
 
7.1%
주 2590
 
6.7%
동 2440
 
6.3%
남 2408
 
6.2%
도 2317
 
6.0%
경 2292
 
5.9%
시 2292
 
5.9%
로 2013
 
5.2%
층 1434
 
3.7%
Other values (280) 15574
40.1%
Uppercase Letter
ValueCountFrequency (%)
A 13
26.0%
C 6
12.0%
B 6
12.0%
S 4
 
8.0%
Z 3
 
6.0%
Y 3
 
6.0%
K 2
 
4.0%
E 2
 
4.0%
O 2
 
4.0%
N 2
 
4.0%
Other values (6) 7
14.0%
Decimal Number
ValueCountFrequency (%)
1 3660
32.3%
2 1696
15.0%
0 955
 
8.4%
3 939
 
8.3%
5 818
 
7.2%
4 758
 
6.7%
6 710
 
6.3%
9 658
 
5.8%
7 591
 
5.2%
8 543
 
4.8%
Lowercase Letter
ValueCountFrequency (%)
i 2
18.2%
e 2
18.2%
y 2
18.2%
t 2
18.2%
a 1
9.1%
u 1
9.1%
c 1
9.1%
Other Punctuation
ValueCountFrequency (%)
, 1776
99.3%
. 6
 
0.3%
@ 5
 
0.3%
: 1
 
0.1%
/ 1
 
0.1%
Space Separator
ValueCountFrequency (%)
11411
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2144
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2143
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 631
100.0%
Math Symbol
ValueCountFrequency (%)
~ 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 38876
56.8%
Common 29467
43.1%
Latin 61
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
진 2765
 
7.1%
상 2751
 
7.1%
주 2590
 
6.7%
동 2440
 
6.3%
남 2408
 
6.2%
도 2317
 
6.0%
경 2292
 
5.9%
시 2292
 
5.9%
로 2013
 
5.2%
층 1434
 
3.7%
Other values (280) 15574
40.1%
Latin
ValueCountFrequency (%)
A 13
21.3%
C 6
 
9.8%
B 6
 
9.8%
S 4
 
6.6%
Z 3
 
4.9%
Y 3
 
4.9%
i 2
 
3.3%
K 2
 
3.3%
e 2
 
3.3%
E 2
 
3.3%
Other values (13) 18
29.5%
Common
ValueCountFrequency (%)
11411
38.7%
1 3660
 
12.4%
( 2144
 
7.3%
) 2143
 
7.3%
, 1776
 
6.0%
2 1696
 
5.8%
0 955
 
3.2%
3 939
 
3.2%
5 818
 
2.8%
4 758
 
2.6%
Other values (10) 3167
 
10.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 38875
56.8%
ASCII 29528
43.2%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11411
38.6%
1 3660
 
12.4%
( 2144
 
7.3%
) 2143
 
7.3%
, 1776
 
6.0%
2 1696
 
5.7%
0 955
 
3.2%
3 939
 
3.2%
5 818
 
2.8%
4 758
 
2.6%
Other values (33) 3228
 
10.9%
Hangul
ValueCountFrequency (%)
진 2765
 
7.1%
상 2751
 
7.1%
주 2590
 
6.7%
동 2440
 
6.3%
남 2408
 
6.2%
도 2317
 
6.0%
경 2292
 
5.9%
시 2292
 
5.9%
로 2013
 
5.2%
층 1434
 
3.7%
Other values (279) 15573
40.1%
Compat Jamo
ValueCountFrequency (%)
ㄹ 1
100.0%

영업장면적
Real number (ℝ)

ZEROS 

Distinct1418
Distinct (%)65.3%
Missing11
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean152.89183
Minimum0
Maximum5954
Zeros36
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size19.3 KiB
2023-12-11T09:32:34.767707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile12
Q125.55
median40.04
Q384.92
95-th percentile675.948
Maximum5954
Range5954
Interquartile range (IQR)59.37

Descriptive statistics

Standard deviation384.96739
Coefficient of variation (CV)2.5179069
Kurtosis84.559421
Mean152.89183
Median Absolute Deviation (MAD)19.24
Skewness7.6609112
Sum332233.94
Variance148199.89
MonotonicityNot monotonic
2023-12-11T09:32:34.905017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.0 54
 
2.5%
0.0 36
 
1.6%
26.4 22
 
1.0%
6.6 19
 
0.9%
30.0 19
 
0.9%
20.0 18
 
0.8%
66.0 18
 
0.8%
49.5 17
 
0.8%
23.1 17
 
0.8%
16.5 16
 
0.7%
Other values (1408) 1937
88.7%
ValueCountFrequency (%)
0.0 36
1.6%
2.83 1
 
< 0.1%
3.3 1
 
< 0.1%
3.6 1
 
< 0.1%
3.96 1
 
< 0.1%
5.0 1
 
< 0.1%
5.61 1
 
< 0.1%
5.76 1
 
< 0.1%
5.94 1
 
< 0.1%
6.0 2
 
0.1%
ValueCountFrequency (%)
5954.0 1
< 0.1%
5803.8 1
< 0.1%
4892.52 1
< 0.1%
4875.33 1
< 0.1%
4563.33 1
< 0.1%
4115.42 1
< 0.1%
2800.95 1
< 0.1%
2800.52 1
< 0.1%
2615.09 1
< 0.1%
2436.56 1
< 0.1%

Interactions

2023-12-11T09:32:32.626951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:32:34.996102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명영업장면적
업종명1.0000.601
영업장면적0.6011.000
2023-12-11T09:32:35.068439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업장면적업종명
영업장면적1.0000.281
업종명0.2811.000

Missing values

2023-12-11T09:32:32.732014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:32:32.811832image/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

업종명업소명영업소 주소(도로명)영업장면적
0숙박업(일반)진주스토리경상남도 진주시 비봉로54번길 8 (계동)272.0
1숙박업(일반)진성모텔경상남도 진주시 진주대로1032번길 11 (동성동)454.92
2숙박업(일반)휴모텔경상남도 진주시 진주대로1040번길 10 (동성동)139.37
3숙박업(일반)진양장여관경상남도 진주시 진주대로891번길 41 (강남동)147.11
4숙박업(일반)삼학여관경상남도 진주시 진주대로879번길 14-16 (강남동)158.68
5숙박업(일반)백만장여관경상남도 진주시 장대로10번길 10 (장대동)116.2
6숙박업(일반)삼성여관경상남도 진주시 장대로6번길 5-1 (장대동)69.38
7숙박업(일반)유명장여관경상남도 진주시 진양호로564번길 12 (장대동)400.59
8숙박업(일반)선화장여관경상남도 진주시 장대로15번길 5-2 (장대동)206.28
9숙박업(일반)이화장 여관경상남도 진주시 장대로6번길 5 (장대동)157.69
업종명업소명영업소 주소(도로명)영업장면적
2174일반미용업, 네일미용업, 화장ㆍ분장 미용업지니헤어경상남도 진주시 에나로175번길 12, 센트럴에비뉴동 1층 1015호 (충무공동, 혁신도시중흥에스-클래스센트럴시티3단지)32.09
2175일반미용업, 네일미용업, 화장ㆍ분장 미용업오늘,하루경상남도 진주시 솔밭로140번길 7-2, 1층 (상대동)34.45
2176피부미용업, 네일미용업, 화장ㆍ분장 미용업네일스토리경상남도 진주시 진주대로948번길 12-2, 1층 일부 (칠암동)26.42
2177피부미용업, 네일미용업, 화장ㆍ분장 미용업윙스네일경상남도 진주시 동부로169번길 12, 윙스타워 1층 C114 (충무공동)36.96
2178피부미용업, 네일미용업, 화장ㆍ분장 미용업몬트네일경상남도 진주시 새들말로22번길 5-14, 1층일부 (평거동)60.0
2179피부미용업, 네일미용업, 화장ㆍ분장 미용업비채사 스킨랩( VICHESA SKINLAB)경상남도 진주시 진양호로328번길 7, 1층일부 (신안동)15.99
2180피부미용업, 네일미용업, 화장ㆍ분장 미용업사월의네일경상남도 진주시 촉석로 179-1, 2층 (중안동)48.66
2181피부미용업, 네일미용업, 화장ㆍ분장 미용업바나고경상남도 진주시 초북로20번길 20, 1층일부 (초전동)52.94
2182피부미용업, 네일미용업, 화장ㆍ분장 미용업아름담다경상남도 진주시 창렬로 92, 1층 (상봉동)67.06
2183피부미용업, 네일미용업, 화장ㆍ분장 미용업네일이특별해경상남도 진주시 진주역로 116, 더퍼스트웰가시티 2층 220호 (가좌동)26.66