Overview

Dataset statistics

Number of variables5
Number of observations360
Missing cells123
Missing cells (%)6.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.5 KiB
Average record size in memory41.4 B

Variable types

Numeric1
Categorical1
Text3

Dataset

Description이 공공데이터는 전라북도 완주군 미용업, 이용업, 목욕탕업, 숙박업에 관한 항목 등을 공공데이터의 정보를 제공합니다.
Author전북특별자치도 완주군
URLhttps://www.data.go.kr/data/15007179/fileData.do

Alerts

연번 is highly overall correlated with 업종명High correlation
업종명 is highly overall correlated with 연번High correlation
소재지전화 has 123 (34.2%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-04-21 01:00:10.522493
Analysis finished2024-04-21 01:00:12.064816
Duration1.54 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct360
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean180.5
Minimum1
Maximum360
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2024-04-21T10:00:12.134333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile18.95
Q190.75
median180.5
Q3270.25
95-th percentile342.05
Maximum360
Range359
Interquartile range (IQR)179.5

Descriptive statistics

Standard deviation104.06729
Coefficient of variation (CV)0.57655006
Kurtosis-1.2
Mean180.5
Median Absolute Deviation (MAD)90
Skewness0
Sum64980
Variance10830
MonotonicityStrictly increasing
2024-04-21T10:00:12.257590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
249 1
 
0.3%
247 1
 
0.3%
246 1
 
0.3%
245 1
 
0.3%
244 1
 
0.3%
243 1
 
0.3%
242 1
 
0.3%
241 1
 
0.3%
240 1
 
0.3%
Other values (350) 350
97.2%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
360 1
0.3%
359 1
0.3%
358 1
0.3%
357 1
0.3%
356 1
0.3%
355 1
0.3%
354 1
0.3%
353 1
0.3%
352 1
0.3%
351 1
0.3%

업종명
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
일반미용업
133 
숙박업(일반)
61 
세탁업
31 
건물위생관리업
29 
피부미용업
26 
Other values (12)
80 

Length

Max length23
Median length5
Mean length5.5138889
Min length3

Unique

Unique4 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
일반미용업 133
36.9%
숙박업(일반) 61
16.9%
세탁업 31
 
8.6%
건물위생관리업 29
 
8.1%
피부미용업 26
 
7.2%
이용업 25
 
6.9%
종합미용업 13
 
3.6%
목욕장업 13
 
3.6%
네일미용업 13
 
3.6%
숙박업(생활) 6
 
1.7%
Other values (7) 10
 
2.8%

Length

2024-04-21T10:00:12.405875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반미용업 139
36.7%
숙박업(일반 61
16.1%
세탁업 31
 
8.2%
피부미용업 30
 
7.9%
건물위생관리업 29
 
7.7%
이용업 25
 
6.6%
네일미용업 22
 
5.8%
종합미용업 13
 
3.4%
목욕장업 13
 
3.4%
숙박업(생활 6
 
1.6%
Other values (2) 10
 
2.6%

업소명
Text

Distinct355
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
2024-04-21T10:00:12.668584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length21
Mean length6.2083333
Min length1

Characters and Unicode

Total characters2235
Distinct characters405
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique352 ?
Unique (%)97.8%

Sample

1st row금강산장
2nd row황금산장
3rd row별빛산장
4th row러브모텔
5th row에이스모텔
ValueCountFrequency (%)
헤어 8
 
1.7%
hair 5
 
1.1%
모텔 5
 
1.1%
호텔 5
 
1.1%
형제이용원 3
 
0.7%
준헤어 3
 
0.7%
s 2
 
0.4%
무인텔 2
 
0.4%
nail 2
 
0.4%
미용실 2
 
0.4%
Other values (411) 422
91.9%
2024-04-21T10:00:13.058291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
99
 
4.4%
어 85
 
3.8%
헤 82
 
3.7%
이 56
 
2.5%
용 55
 
2.5%
미 48
 
2.1%
) 45
 
2.0%
( 45
 
2.0%
텔 40
 
1.8%
스 35
 
1.6%
Other values (395) 1645
73.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1816
81.3%
Lowercase Letter 113
 
5.1%
Space Separator 99
 
4.4%
Uppercase Letter 82
 
3.7%
Close Punctuation 45
 
2.0%
Open Punctuation 45
 
2.0%
Decimal Number 17
 
0.8%
Other Punctuation 17
 
0.8%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
어 85
 
4.7%
헤 82
 
4.5%
이 56
 
3.1%
용 55
 
3.0%
미 48
 
2.6%
텔 40
 
2.2%
스 35
 
1.9%
실 34
 
1.9%
리 34
 
1.9%
원 26
 
1.4%
Other values (339) 1321
72.7%
Uppercase Letter
ValueCountFrequency (%)
A 10
 
12.2%
H 7
 
8.5%
E 7
 
8.5%
N 6
 
7.3%
R 5
 
6.1%
Y 4
 
4.9%
B 4
 
4.9%
O 4
 
4.9%
D 4
 
4.9%
I 4
 
4.9%
Other values (13) 27
32.9%
Lowercase Letter
ValueCountFrequency (%)
a 15
13.3%
i 12
10.6%
s 11
9.7%
r 10
8.8%
o 9
8.0%
e 8
 
7.1%
h 8
 
7.1%
u 6
 
5.3%
t 6
 
5.3%
y 6
 
5.3%
Other values (9) 22
19.5%
Decimal Number
ValueCountFrequency (%)
2 6
35.3%
1 5
29.4%
8 3
17.6%
5 2
 
11.8%
9 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
& 6
35.3%
, 4
23.5%
. 4
23.5%
＃ 2
 
11.8%
' 1
 
5.9%
Space Separator
ValueCountFrequency (%)
99
100.0%
Close Punctuation
ValueCountFrequency (%)
) 45
100.0%
Open Punctuation
ValueCountFrequency (%)
( 45
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1816
81.3%
Common 224
 
10.0%
Latin 195
 
8.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
어 85
 
4.7%
헤 82
 
4.5%
이 56
 
3.1%
용 55
 
3.0%
미 48
 
2.6%
텔 40
 
2.2%
스 35
 
1.9%
실 34
 
1.9%
리 34
 
1.9%
원 26
 
1.4%
Other values (339) 1321
72.7%
Latin
ValueCountFrequency (%)
a 15
 
7.7%
i 12
 
6.2%
s 11
 
5.6%
A 10
 
5.1%
r 10
 
5.1%
o 9
 
4.6%
e 8
 
4.1%
h 8
 
4.1%
H 7
 
3.6%
E 7
 
3.6%
Other values (32) 98
50.3%
Common
ValueCountFrequency (%)
99
44.2%
) 45
20.1%
( 45
20.1%
2 6
 
2.7%
& 6
 
2.7%
1 5
 
2.2%
, 4
 
1.8%
. 4
 
1.8%
8 3
 
1.3%
＃ 2
 
0.9%
Other values (4) 5
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1816
81.3%
ASCII 417
 
18.7%
None 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
99
23.7%
) 45
 
10.8%
( 45
 
10.8%
a 15
 
3.6%
i 12
 
2.9%
s 11
 
2.6%
A 10
 
2.4%
r 10
 
2.4%
o 9
 
2.2%
e 8
 
1.9%
Other values (45) 153
36.7%
Hangul
ValueCountFrequency (%)
어 85
 
4.7%
헤 82
 
4.5%
이 56
 
3.1%
용 55
 
3.0%
미 48
 
2.6%
텔 40
 
2.2%
스 35
 
1.9%
실 34
 
1.9%
리 34
 
1.9%
원 26
 
1.4%
Other values (339) 1321
72.7%
None
ValueCountFrequency (%)
＃ 2
100.0%

영업소 주소(도로명)
Text

Distinct340
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
2024-04-21T10:00:13.301558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length47
Mean length28.241667
Min length21

Characters and Unicode

Total characters10167
Distinct characters194
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

Unique322 ?
Unique (%)89.4%

Sample

1st row전북특별자치도 완주군 운주면 대둔산공원길 22-12
2nd row전북특별자치도 완주군 운주면 대둔산공원길 22-9
3rd row전북특별자치도 완주군 운주면 대둔산공원길 22-13
4th row전북특별자치도 완주군 고산면 대아저수로 441
5th row전북특별자치도 완주군 삼례읍 동학로 36-13
ValueCountFrequency (%)
전북특별자치도 360
 
17.2%
완주군 359
 
17.2%
봉동읍 113
 
5.4%
이서면 77
 
3.7%
삼례읍 66
 
3.2%
1층 53
 
2.5%
고산면 30
 
1.4%
봉동로 26
 
1.2%
상관면 21
 
1.0%
동학로 21
 
1.0%
Other values (440) 965
46.2%
2024-04-21T10:00:13.687898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1732
 
17.0%
1 454
 
4.5%
주 392
 
3.9%
완 371
 
3.6%
전 365
 
3.6%
도 364
 
3.6%
북 363
 
3.6%
치 361
 
3.6%
군 360
 
3.5%
자 360
 
3.5%
Other values (184) 5045
49.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6573
64.7%
Space Separator 1732
 
17.0%
Decimal Number 1513
 
14.9%
Other Punctuation 153
 
1.5%
Dash Punctuation 111
 
1.1%
Close Punctuation 38
 
0.4%
Open Punctuation 38
 
0.4%
Uppercase Letter 7
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 392
 
6.0%
완 371
 
5.6%
전 365
 
5.6%
도 364
 
5.5%
북 363
 
5.5%
치 361
 
5.5%
군 360
 
5.5%
자 360
 
5.5%
별 360
 
5.5%
특 360
 
5.5%
Other values (163) 2917
44.4%
Decimal Number
ValueCountFrequency (%)
1 454
30.0%
2 188
12.4%
0 175
 
11.6%
3 166
 
11.0%
4 121
 
8.0%
5 102
 
6.7%
6 100
 
6.6%
9 72
 
4.8%
7 72
 
4.8%
8 63
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
T 2
28.6%
A 2
28.6%
P 1
14.3%
B 1
14.3%
K 1
14.3%
Space Separator
ValueCountFrequency (%)
1732
100.0%
Other Punctuation
ValueCountFrequency (%)
, 153
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 111
100.0%
Close Punctuation
ValueCountFrequency (%)
) 38
100.0%
Open Punctuation
ValueCountFrequency (%)
( 38
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6573
64.7%
Common 3587
35.3%
Latin 7
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 392
 
6.0%
완 371
 
5.6%
전 365
 
5.6%
도 364
 
5.5%
북 363
 
5.5%
치 361
 
5.5%
군 360
 
5.5%
자 360
 
5.5%
별 360
 
5.5%
특 360
 
5.5%
Other values (163) 2917
44.4%
Common
ValueCountFrequency (%)
1732
48.3%
1 454
 
12.7%
2 188
 
5.2%
0 175
 
4.9%
3 166
 
4.6%
, 153
 
4.3%
4 121
 
3.4%
- 111
 
3.1%
5 102
 
2.8%
6 100
 
2.8%
Other values (6) 285
 
7.9%
Latin
ValueCountFrequency (%)
T 2
28.6%
A 2
28.6%
P 1
14.3%
B 1
14.3%
K 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6573
64.7%
ASCII 3594
35.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1732
48.2%
1 454
 
12.6%
2 188
 
5.2%
0 175
 
4.9%
3 166
 
4.6%
, 153
 
4.3%
4 121
 
3.4%
- 111
 
3.1%
5 102
 
2.8%
6 100
 
2.8%
Other values (11) 292
 
8.1%
Hangul
ValueCountFrequency (%)
주 392
 
6.0%
완 371
 
5.6%
전 365
 
5.6%
도 364
 
5.5%
북 363
 
5.5%
치 361
 
5.5%
군 360
 
5.5%
자 360
 
5.5%
별 360
 
5.5%
특 360
 
5.5%
Other values (163) 2917
44.4%

소재지전화
Text

MISSING 

Distinct234
Distinct (%)98.7%
Missing123
Missing (%)34.2%
Memory size2.9 KiB
2024-04-21T10:00:13.896366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.008439
Min length12

Characters and Unicode

Total characters2846
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

Unique231 ?
Unique (%)97.5%

Sample

1st row063-261-1260
2nd row063-263-2294
3rd row063-263-0625
4th row063-263-3887
5th row063-291-6660
ValueCountFrequency (%)
063-241-6038 2
 
0.8%
063-261-1260 2
 
0.8%
063-263-1260 2
 
0.8%
063-908-2002 1
 
0.4%
063-214-0213 1
 
0.4%
063-232-6669 1
 
0.4%
063-261-3866 1
 
0.4%
063-291-0570 1
 
0.4%
063-263-2526 1
 
0.4%
063-261-7335 1
 
0.4%
Other values (224) 224
94.5%
2024-04-21T10:00:14.234842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 474
16.7%
6 452
15.9%
2 418
14.7%
3 396
13.9%
0 389
13.7%
1 172
 
6.0%
8 123
 
4.3%
9 120
 
4.2%
4 110
 
3.9%
5 101
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2372
83.3%
Dash Punctuation 474
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 452
19.1%
2 418
17.6%
3 396
16.7%
0 389
16.4%
1 172
 
7.3%
8 123
 
5.2%
9 120
 
5.1%
4 110
 
4.6%
5 101
 
4.3%
7 91
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 474
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2846
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 474
16.7%
6 452
15.9%
2 418
14.7%
3 396
13.9%
0 389
13.7%
1 172
 
6.0%
8 123
 
4.3%
9 120
 
4.2%
4 110
 
3.9%
5 101
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2846
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 474
16.7%
6 452
15.9%
2 418
14.7%
3 396
13.9%
0 389
13.7%
1 172
 
6.0%
8 123
 
4.3%
9 120
 
4.2%
4 110
 
3.9%
5 101
 
3.5%

Interactions

2024-04-21T10:00:11.773142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T10:00:14.322901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종명
연번1.0000.914
업종명0.9141.000
2024-04-21T10:00:14.395340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종명
연번1.0000.672
업종명0.6721.000

Missing values

2024-04-21T10:00:11.943515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T10:00:12.027604image/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

연번업종명업소명영업소 주소(도로명)소재지전화
01숙박업(일반)금강산장전북특별자치도 완주군 운주면 대둔산공원길 22-12063-261-1260
12숙박업(일반)황금산장전북특별자치도 완주군 운주면 대둔산공원길 22-9063-263-2294
23숙박업(일반)별빛산장전북특별자치도 완주군 운주면 대둔산공원길 22-13063-263-0625
34숙박업(일반)러브모텔전북특별자치도 완주군 고산면 대아저수로 441063-263-3887
45숙박업(일반)에이스모텔전북특별자치도 완주군 삼례읍 동학로 36-13063-291-6660
56숙박업(일반)리즈모텔전북특별자치도 완주군 고산면 읍내7길 42063-263-4599
67숙박업(일반)현대장여관전북특별자치도 완주군 고산면 읍내2길 5063-262-5086
78숙박업(일반)월성모텔전북특별자치도 완주군 봉동읍 하보상길 27063-261-7951
89숙박업(일반)모텔썬전북특별자치도 완주군 봉동읍 봉동로 48-4063-262-0100
910숙박업(일반)그린파크장전북특별자치도 완주군 봉동읍 봉동로 48-12063-261-7745
연번업종명업소명영업소 주소(도로명)소재지전화
350351일반미용업, 네일미용업주연헤어(JUYEON HAIR)전북특별자치도 완주군 봉동읍 봉동로 170, 1층<NA>
351352일반미용업, 네일미용업홍헤어 Asia전북특별자치도 완주군 삼례읍 삼례역로 16, 1층<NA>
352353피부미용업, 네일미용업DAON(다온)전북특별자치도 완주군 봉동읍 낙평장기로 43-2063-263-2135
353354피부미용업, 네일미용업엠뷰티전북특별자치도 완주군 삼례읍 삼례역로 4, 4호<NA>
354355일반미용업, 화장ㆍ분장 미용업Yes hair & make up(예스헤어메이크업)전북특별자치도 완주군 봉동읍 둔산1로 104<NA>
355356네일미용업, 화장ㆍ분장 미용업트윙클 Beauty Bar전북특별자치도 완주군 봉동읍 봉동동서로 79, 1층 2호<NA>
356357일반미용업, 피부미용업, 네일미용업92헤어전북특별자치도 완주군 구이면 구이로 1501-1<NA>
357358일반미용업, 네일미용업, 화장ㆍ분장 미용업머리하는 날전북특별자치도 완주군 봉동읍 봉동동서로 79<NA>
358359일반미용업, 네일미용업, 화장ㆍ분장 미용업헤어 125전북특별자치도 완주군 봉동읍 봉동동서로 125<NA>
359360피부미용업, 네일미용업, 화장ㆍ분장 미용업유엔아이네일바이엠엔(You&i nail by m.n)전북특별자치도 완주군 이서면 출판로 46-16, 1층 103호<NA>