Overview

Dataset statistics

Number of variables6
Number of observations618
Missing cells86
Missing cells (%)2.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory29.7 KiB
Average record size in memory49.2 B

Variable types

Numeric1
Categorical2
Text3

Dataset

Description서산시에 영업허가된 공중 위생업소(이발소. 미용실, 세탁소, 목욕탕, 사우나, 네일아트, 피부관리샵)정보로 업종명, 업소명, 업소소재지, 소재지에 대한 정보를 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=445&beforeMenuCd=DOM_000000201001001000&publicdatapk=15000677

Alerts

데이터기준일 has constant value ""Constant
소재지전화 has 86 (13.9%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-01-09 21:31:56.505472
Analysis finished2024-01-09 21:31:57.053201
Duration0.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct618
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean309.5
Minimum1
Maximum618
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2024-01-10T06:31:57.108957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile31.85
Q1155.25
median309.5
Q3463.75
95-th percentile587.15
Maximum618
Range617
Interquartile range (IQR)308.5

Descriptive statistics

Standard deviation178.54551
Coefficient of variation (CV)0.57688372
Kurtosis-1.2
Mean309.5
Median Absolute Deviation (MAD)154.5
Skewness0
Sum191271
Variance31878.5
MonotonicityStrictly increasing
2024-01-10T06:31:57.222558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
416 1
 
0.2%
409 1
 
0.2%
410 1
 
0.2%
411 1
 
0.2%
412 1
 
0.2%
413 1
 
0.2%
414 1
 
0.2%
415 1
 
0.2%
417 1
 
0.2%
Other values (608) 608
98.4%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
618 1
0.2%
617 1
0.2%
616 1
0.2%
615 1
0.2%
614 1
0.2%
613 1
0.2%
612 1
0.2%
611 1
0.2%
610 1
0.2%
609 1
0.2%

업종명
Categorical

Distinct15
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
미용업(일반)
360 
세탁업
107 
미용업(피부)
69 
미용업(손톱ㆍ발톱)
 
26
미용업
 
21
Other values (10)
 
35

Length

Max length31
Median length7
Mean length6.8656958
Min length3

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
미용업(일반) 360
58.3%
세탁업 107
 
17.3%
미용업(피부) 69
 
11.2%
미용업(손톱ㆍ발톱) 26
 
4.2%
미용업 21
 
3.4%
미용업(종합) 7
 
1.1%
미용업(피부), 미용업(손톱ㆍ발톱) 7
 
1.1%
미용업(일반), 미용업(피부) 4
 
0.6%
미용업(손톱ㆍ발톱), 미용업(화장ㆍ분장) 4
 
0.6%
미용업(일반), 미용업(손톱ㆍ발톱) 3
 
0.5%
Other values (5) 10
 
1.6%

Length

2024-01-10T06:31:57.328678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
미용업(일반 370
57.2%
세탁업 107
 
16.5%
미용업(피부 86
 
13.3%
미용업(손톱ㆍ발톱 42
 
6.5%
미용업 21
 
3.2%
미용업(화장ㆍ분장 14
 
2.2%
미용업(종합 7
 
1.1%

업소명
Text

Distinct612
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2024-01-10T06:31:57.479401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length5.6407767
Min length1

Characters and Unicode

Total characters3486
Distinct characters415
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

Unique606 ?
Unique (%)98.1%

Sample

1st row제일미용실
2nd row임명숙헤어미용실
3rd row쎄느미용실
4th row신정미용실
5th row명동미용실
ValueCountFrequency (%)
헤어샵 8
 
1.2%
미용실 7
 
1.0%
헤어 5
 
0.7%
서산점 4
 
0.6%
네일 4
 
0.6%
엘림미용실 2
 
0.3%
피부관리실 2
 
0.3%
헤어갤러리 2
 
0.3%
반헤어 2
 
0.3%
헤어겔러리 2
 
0.3%
Other values (647) 657
94.5%
2024-01-10T06:31:57.766189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
어 251
 
7.2%
헤 237
 
6.8%
미 132
 
3.8%
실 102
 
2.9%
용 95
 
2.7%
이 86
 
2.5%
리 82
 
2.4%
세 80
 
2.3%
77
 
2.2%
탁 77
 
2.2%
Other values (405) 2267
65.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3351
96.1%
Space Separator 77
 
2.2%
Close Punctuation 14
 
0.4%
Open Punctuation 14
 
0.4%
Decimal Number 10
 
0.3%
Lowercase Letter 8
 
0.2%
Uppercase Letter 6
 
0.2%
Other Punctuation 5
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
어 251
 
7.5%
헤 237
 
7.1%
미 132
 
3.9%
실 102
 
3.0%
용 95
 
2.8%
이 86
 
2.6%
리 82
 
2.4%
세 80
 
2.4%
탁 77
 
2.3%
스 72
 
2.1%
Other values (382) 2137
63.8%
Lowercase Letter
ValueCountFrequency (%)
i 2
25.0%
h 1
12.5%
l 1
12.5%
v 1
12.5%
e 1
12.5%
a 1
12.5%
r 1
12.5%
Uppercase Letter
ValueCountFrequency (%)
U 1
16.7%
P 1
16.7%
O 1
16.7%
Z 1
16.7%
E 1
16.7%
S 1
16.7%
Decimal Number
ValueCountFrequency (%)
2 5
50.0%
1 3
30.0%
9 1
 
10.0%
3 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
, 4
80.0%
& 1
 
20.0%
Space Separator
ValueCountFrequency (%)
77
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3351
96.1%
Common 121
 
3.5%
Latin 14
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
어 251
 
7.5%
헤 237
 
7.1%
미 132
 
3.9%
실 102
 
3.0%
용 95
 
2.8%
이 86
 
2.6%
리 82
 
2.4%
세 80
 
2.4%
탁 77
 
2.3%
스 72
 
2.1%
Other values (382) 2137
63.8%
Latin
ValueCountFrequency (%)
i 2
14.3%
U 1
 
7.1%
P 1
 
7.1%
h 1
 
7.1%
O 1
 
7.1%
l 1
 
7.1%
v 1
 
7.1%
e 1
 
7.1%
a 1
 
7.1%
r 1
 
7.1%
Other values (3) 3
21.4%
Common
ValueCountFrequency (%)
77
63.6%
) 14
 
11.6%
( 14
 
11.6%
2 5
 
4.1%
, 4
 
3.3%
1 3
 
2.5%
9 1
 
0.8%
3 1
 
0.8%
- 1
 
0.8%
& 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3351
96.1%
ASCII 135
 
3.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
어 251
 
7.5%
헤 237
 
7.1%
미 132
 
3.9%
실 102
 
3.0%
용 95
 
2.8%
이 86
 
2.6%
리 82
 
2.4%
세 80
 
2.4%
탁 77
 
2.3%
스 72
 
2.1%
Other values (382) 2137
63.8%
ASCII
ValueCountFrequency (%)
77
57.0%
) 14
 
10.4%
( 14
 
10.4%
2 5
 
3.7%
, 4
 
3.0%
1 3
 
2.2%
i 2
 
1.5%
U 1
 
0.7%
P 1
 
0.7%
9 1
 
0.7%
Other values (13) 13
 
9.6%

업소소재지(도로명)
Text

Distinct595
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2024-01-10T06:31:58.017824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length48
Mean length27.959547
Min length17

Characters and Unicode

Total characters17279
Distinct characters231
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique573 ?
Unique (%)92.7%

Sample

1st row충청남도 서산시 고운로 129 (읍내동)
2nd row충청남도 서산시 번화1로 45 (동문동)
3rd row충청남도 서산시 번화2로 33 (동문동)
4th row충청남도 서산시 번화2로 28 (읍내동)
5th row충청남도 서산시 읍내동 183,214-23번지 1호
ValueCountFrequency (%)
서산시 618
 
16.4%
충청남도 617
 
16.4%
1층 269
 
7.1%
동문동 219
 
5.8%
읍내동 95
 
2.5%
2층 63
 
1.7%
석림동 60
 
1.6%
상가동 52
 
1.4%
예천동 50
 
1.3%
안견로 36
 
1.0%
Other values (625) 1685
44.8%
2024-01-10T06:31:58.410565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3200
18.5%
동 898
 
5.2%
1 869
 
5.0%
서 691
 
4.0%
산 688
 
4.0%
남 682
 
3.9%
시 677
 
3.9%
충 637
 
3.7%
도 622
 
3.6%
청 620
 
3.6%
Other values (221) 7695
44.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9662
55.9%
Space Separator 3200
 
18.5%
Decimal Number 2716
 
15.7%
Close Punctuation 558
 
3.2%
Open Punctuation 558
 
3.2%
Other Punctuation 448
 
2.6%
Dash Punctuation 117
 
0.7%
Uppercase Letter 14
 
0.1%
Math Symbol 5
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 898
 
9.3%
서 691
 
7.2%
산 688
 
7.1%
남 682
 
7.1%
시 677
 
7.0%
충 637
 
6.6%
도 622
 
6.4%
청 620
 
6.4%
로 525
 
5.4%
층 376
 
3.9%
Other values (197) 3246
33.6%
Decimal Number
ValueCountFrequency (%)
1 869
32.0%
2 454
16.7%
3 280
 
10.3%
4 216
 
8.0%
0 194
 
7.1%
6 170
 
6.3%
5 159
 
5.9%
7 134
 
4.9%
9 125
 
4.6%
8 115
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
A 5
35.7%
C 3
21.4%
B 3
21.4%
F 1
 
7.1%
K 1
 
7.1%
J 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
, 447
99.8%
@ 1
 
0.2%
Space Separator
ValueCountFrequency (%)
3200
100.0%
Close Punctuation
ValueCountFrequency (%)
) 558
100.0%
Open Punctuation
ValueCountFrequency (%)
( 558
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 117
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9662
55.9%
Common 7602
44.0%
Latin 15
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 898
 
9.3%
서 691
 
7.2%
산 688
 
7.1%
남 682
 
7.1%
시 677
 
7.0%
충 637
 
6.6%
도 622
 
6.4%
청 620
 
6.4%
로 525
 
5.4%
층 376
 
3.9%
Other values (197) 3246
33.6%
Common
ValueCountFrequency (%)
3200
42.1%
1 869
 
11.4%
) 558
 
7.3%
( 558
 
7.3%
2 454
 
6.0%
, 447
 
5.9%
3 280
 
3.7%
4 216
 
2.8%
0 194
 
2.6%
6 170
 
2.2%
Other values (7) 656
 
8.6%
Latin
ValueCountFrequency (%)
A 5
33.3%
C 3
20.0%
B 3
20.0%
F 1
 
6.7%
K 1
 
6.7%
J 1
 
6.7%
e 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9662
55.9%
ASCII 7617
44.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3200
42.0%
1 869
 
11.4%
) 558
 
7.3%
( 558
 
7.3%
2 454
 
6.0%
, 447
 
5.9%
3 280
 
3.7%
4 216
 
2.8%
0 194
 
2.5%
6 170
 
2.2%
Other values (14) 671
 
8.8%
Hangul
ValueCountFrequency (%)
동 898
 
9.3%
서 691
 
7.2%
산 688
 
7.1%
남 682
 
7.1%
시 677
 
7.0%
충 637
 
6.6%
도 622
 
6.4%
청 620
 
6.4%
로 525
 
5.4%
층 376
 
3.9%
Other values (197) 3246
33.6%

소재지전화
Text

MISSING 

Distinct519
Distinct (%)97.6%
Missing86
Missing (%)13.9%
Memory size5.0 KiB
2024-01-10T06:31:58.603224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.035714
Min length12

Characters and Unicode

Total characters6403
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

Unique507 ?
Unique (%)95.3%

Sample

1st row041-664-7558
2nd row041-665-3594
3rd row041-665-4492
4th row041-664-0230
5th row041-665-8862
ValueCountFrequency (%)
041-664-1562 3
 
0.6%
041-662-6931 2
 
0.4%
041-666-7576 2
 
0.4%
041-664-1053 2
 
0.4%
041-666-4005 2
 
0.4%
041-665-0431 2
 
0.4%
041-669-5538 2
 
0.4%
041-663-1253 2
 
0.4%
041-665-8474 2
 
0.4%
041-665-6949 2
 
0.4%
Other values (511) 513
96.1%
2024-01-10T06:31:58.924562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 1201
18.8%
- 1064
16.6%
0 824
12.9%
4 795
12.4%
1 772
12.1%
5 333
 
5.2%
8 324
 
5.1%
7 304
 
4.7%
3 282
 
4.4%
2 258
 
4.0%
Other values (2) 246
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5337
83.4%
Dash Punctuation 1064
 
16.6%
Space Separator 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 1201
22.5%
0 824
15.4%
4 795
14.9%
1 772
14.5%
5 333
 
6.2%
8 324
 
6.1%
7 304
 
5.7%
3 282
 
5.3%
2 258
 
4.8%
9 244
 
4.6%
Dash Punctuation
ValueCountFrequency (%)
- 1064
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6403
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 1201
18.8%
- 1064
16.6%
0 824
12.9%
4 795
12.4%
1 772
12.1%
5 333
 
5.2%
8 324
 
5.1%
7 304
 
4.7%
3 282
 
4.4%
2 258
 
4.0%
Other values (2) 246
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6403
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 1201
18.8%
- 1064
16.6%
0 824
12.9%
4 795
12.4%
1 772
12.1%
5 333
 
5.2%
8 324
 
5.1%
7 304
 
4.7%
3 282
 
4.4%
2 258
 
4.0%
Other values (2) 246
 
3.8%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2021-10-27
618 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-10-27
2nd row2021-10-27
3rd row2021-10-27
4th row2021-10-27
5th row2021-10-27

Common Values

ValueCountFrequency (%)
2021-10-27 618
100.0%

Length

2024-01-10T06:31:59.037989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:31:59.110820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-10-27 618
100.0%

Interactions

2024-01-10T06:31:56.836850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:31:59.155564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종명
연번1.0000.694
업종명0.6941.000
2024-01-10T06:31:59.219920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종명
연번1.0000.340
업종명0.3401.000

Missing values

2024-01-10T06:31:56.932910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:31:57.018316image/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

연번업종명업소명업소소재지(도로명)소재지전화데이터기준일
01미용업(일반)제일미용실충청남도 서산시 고운로 129 (읍내동)041-664-75582021-10-27
12미용업(일반)임명숙헤어미용실충청남도 서산시 번화1로 45 (동문동)041-665-35942021-10-27
23미용업(일반)쎄느미용실충청남도 서산시 번화2로 33 (동문동)041-665-44922021-10-27
34미용업(일반)신정미용실충청남도 서산시 번화2로 28 (읍내동)041-664-02302021-10-27
45미용업(일반)명동미용실충청남도 서산시 읍내동 183,214-23번지 1호041-665-88622021-10-27
56미용업(일반)진주미용실충청남도 서산시 시장4길 21 (동문동)041-667-28932021-10-27
67미용업(일반)나라헤어샵충청남도 서산시 번화2로 21-1 (읍내동)041-664-14452021-10-27
78미용업(일반)수지미용실충청남도 서산시 운산면 운암로 1046-1041-663-44002021-10-27
89미용업(일반)평화미용실충청남도 서산시 해미면 읍내리 333번지 2호041-688-28122021-10-27
910미용업(일반)정머리방충청남도 서산시 시장4길 21 (동문동)041-664-04782021-10-27
연번업종명업소명업소소재지(도로명)소재지전화데이터기준일
608609세탁업로얄목욕탕충청남도 서산시 안견로 217 (동문동)041-664-77142021-10-27
609610세탁업서산사우나충청남도 서산시 덕지천로 124, 지하1~지상2층 (석남동)041-666-64002021-10-27
610611세탁업펜트힐더사우나충남 서산시 성연면 성연2로 45 이안큐브 오피스텔 B동 3층070-7335-11352021-10-27
611612세탁업용천휘트니스센터충청남도 서산시 율지7로 17 (동문동)041-669-92202021-10-27
612613세탁업유심천 헬스사우나충청남도 서산시 쌍연남2로 3-19, 2~3층 (동문동)041-681-56562021-10-27
613614세탁업제일목욕탕충청남도 서산시 시장4길 25-5 (동문동)041-662-19192021-10-27
614615세탁업하와이여성전용사우나충청남도 서산시 안견로 173, 지하층 (동문동)041-667-81882021-10-27
615616세탁업학돌사우나충청남도 서산시 부춘2로 24 (읍내동)041-669-44902021-10-27
616617세탁업한마음목욕탕충청남도 서산시 한마음13로 36 (석림동)041-666-02332021-10-27
617618세탁업한샘대중탕충청남도 서산시 대산읍 구진로 2041-669-91102021-10-27