Overview

Dataset statistics

Number of variables8
Number of observations78
Missing cells21
Missing cells (%)3.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.2 KiB
Average record size in memory67.7 B

Variable types

Categorical3
Text3
Numeric1
DateTime1

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

업종명 has constant value ""Constant
데이터기준일 has constant value ""Constant
침대수 is highly overall correlated with 의자수 and 1 other fieldsHigh correlation
업태명 is highly overall correlated with 침대수High correlation
의자수 is highly overall correlated with 침대수High correlation
업태명 is highly imbalanced (76.5%)Imbalance
소재지전화 has 13 (16.7%) missing valuesMissing
의자수 has 8 (10.3%) missing valuesMissing
업소소재지(도로명) has unique valuesUnique
의자수 has 2 (2.6%) zerosZeros

Reproduction

Analysis started2024-01-09 21:32:06.624182
Analysis finished2024-01-09 21:32:07.526732
Duration0.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size756.0 B
이용업
78 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
이용업 78
100.0%

Length

2024-01-10T06:32:07.573862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:32:07.643099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
이용업 78
100.0%

업소명
Text

Distinct67
Distinct (%)85.9%
Missing0
Missing (%)0.0%
Memory size756.0 B
2024-01-10T06:32:07.828464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length5
Mean length5.5769231
Min length3

Characters and Unicode

Total characters435
Distinct characters117
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)76.9%

Sample

1st row공림이용원
2nd row월성이용원
3rd row신성이용원
4th row대천이용원
5th row서동이용원
ValueCountFrequency (%)
이용원 5
 
5.7%
현대이용원 4
 
4.5%
중앙이용원 4
 
4.5%
신성이용원 2
 
2.3%
대중이용원 2
 
2.3%
고등이용원 2
 
2.3%
제일이용원 2
 
2.3%
태후사랑 2
 
2.3%
서울이용원 2
 
2.3%
금메달이용원 1
 
1.1%
Other values (62) 62
70.5%
2024-01-10T06:32:08.146247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 74
17.0%
용 73
16.8%
원 72
16.6%
성 12
 
2.8%
대 10
 
2.3%
10
 
2.3%
서 8
 
1.8%
중 6
 
1.4%
일 5
 
1.1%
사 4
 
0.9%
Other values (107) 161
37.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 419
96.3%
Space Separator 10
 
2.3%
Decimal Number 5
 
1.1%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 74
17.7%
용 73
17.4%
원 72
17.2%
성 12
 
2.9%
대 10
 
2.4%
서 8
 
1.9%
중 6
 
1.4%
일 5
 
1.2%
사 4
 
1.0%
앙 4
 
1.0%
Other values (102) 151
36.0%
Decimal Number
ValueCountFrequency (%)
1 3
60.0%
2 1
 
20.0%
9 1
 
20.0%
Space Separator
ValueCountFrequency (%)
10
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 419
96.3%
Common 16
 
3.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 74
17.7%
용 73
17.4%
원 72
17.2%
성 12
 
2.9%
대 10
 
2.4%
서 8
 
1.9%
중 6
 
1.4%
일 5
 
1.2%
사 4
 
1.0%
앙 4
 
1.0%
Other values (102) 151
36.0%
Common
ValueCountFrequency (%)
10
62.5%
1 3
 
18.8%
. 1
 
6.2%
2 1
 
6.2%
9 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 419
96.3%
ASCII 16
 
3.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 74
17.7%
용 73
17.4%
원 72
17.2%
성 12
 
2.9%
대 10
 
2.4%
서 8
 
1.9%
중 6
 
1.4%
일 5
 
1.2%
사 4
 
1.0%
앙 4
 
1.0%
Other values (102) 151
36.0%
ASCII
ValueCountFrequency (%)
10
62.5%
1 3
 
18.8%
. 1
 
6.2%
2 1
 
6.2%
9 1
 
6.2%

업소소재지(도로명)
Text

UNIQUE 

Distinct78
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size756.0 B
2024-01-10T06:32:08.396553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length38
Mean length25.25641
Min length19

Characters and Unicode

Total characters1970
Distinct characters102
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique78 ?
Unique (%)100.0%

Sample

1st row충청남도 서산시 서해로 3203 (예천동)
2nd row충청남도 서산시 음암면 도당리 858번지
3rd row충청남도 서산시 성연면 고남리 496번지
4th row충청남도 서산시 동헌로 104, 1층 (읍내동)
5th row충청남도 서산시 율지12길 20 (동문동,(1층))
ValueCountFrequency (%)
충청남도 78
 
17.8%
서산시 78
 
17.8%
동문동 20
 
4.6%
1층 19
 
4.3%
읍내동 12
 
2.7%
대산읍 7
 
1.6%
석림동 6
 
1.4%
해미면 5
 
1.1%
부석면 5
 
1.1%
지하 5
 
1.1%
Other values (154) 203
46.3%
2024-01-10T06:32:08.751995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
388
19.7%
산 92
 
4.7%
남 87
 
4.4%
서 85
 
4.3%
시 85
 
4.3%
충 82
 
4.2%
1 81
 
4.1%
도 79
 
4.0%
동 78
 
4.0%
청 78
 
4.0%
Other values (92) 835
42.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1133
57.5%
Space Separator 388
 
19.7%
Decimal Number 294
 
14.9%
Close Punctuation 55
 
2.8%
Open Punctuation 55
 
2.8%
Other Punctuation 33
 
1.7%
Dash Punctuation 12
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 92
 
8.1%
남 87
 
7.7%
서 85
 
7.5%
시 85
 
7.5%
충 82
 
7.2%
도 79
 
7.0%
동 78
 
6.9%
청 78
 
6.9%
로 54
 
4.8%
층 29
 
2.6%
Other values (77) 384
33.9%
Decimal Number
ValueCountFrequency (%)
1 81
27.6%
2 48
16.3%
3 35
11.9%
4 34
11.6%
7 20
 
6.8%
0 18
 
6.1%
6 16
 
5.4%
5 15
 
5.1%
9 14
 
4.8%
8 13
 
4.4%
Space Separator
ValueCountFrequency (%)
388
100.0%
Close Punctuation
ValueCountFrequency (%)
) 55
100.0%
Open Punctuation
ValueCountFrequency (%)
( 55
100.0%
Other Punctuation
ValueCountFrequency (%)
, 33
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1133
57.5%
Common 837
42.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 92
 
8.1%
남 87
 
7.7%
서 85
 
7.5%
시 85
 
7.5%
충 82
 
7.2%
도 79
 
7.0%
동 78
 
6.9%
청 78
 
6.9%
로 54
 
4.8%
층 29
 
2.6%
Other values (77) 384
33.9%
Common
ValueCountFrequency (%)
388
46.4%
1 81
 
9.7%
) 55
 
6.6%
( 55
 
6.6%
2 48
 
5.7%
3 35
 
4.2%
4 34
 
4.1%
, 33
 
3.9%
7 20
 
2.4%
0 18
 
2.2%
Other values (5) 70
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1133
57.5%
ASCII 837
42.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
388
46.4%
1 81
 
9.7%
) 55
 
6.6%
( 55
 
6.6%
2 48
 
5.7%
3 35
 
4.2%
4 34
 
4.1%
, 33
 
3.9%
7 20
 
2.4%
0 18
 
2.2%
Other values (5) 70
 
8.4%
Hangul
ValueCountFrequency (%)
산 92
 
8.1%
남 87
 
7.7%
서 85
 
7.5%
시 85
 
7.5%
충 82
 
7.2%
도 79
 
7.0%
동 78
 
6.9%
청 78
 
6.9%
로 54
 
4.8%
층 29
 
2.6%
Other values (77) 384
33.9%

소재지전화
Text

MISSING 

Distinct64
Distinct (%)98.5%
Missing13
Missing (%)16.7%
Memory size756.0 B
2024-01-10T06:32:08.948971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.015385
Min length12

Characters and Unicode

Total characters781
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

Unique63 ?
Unique (%)96.9%

Sample

1st row041-662-3365
2nd row041-663-6011
3rd row041-662-7816
4th row041-662-2198
5th row041-664-2503
ValueCountFrequency (%)
041-681-3922 2
 
3.1%
041-664-1841 1
 
1.5%
041-664-3722 1
 
1.5%
041-665-1201 1
 
1.5%
041-666-0903 1
 
1.5%
041-688-2209 1
 
1.5%
041-665-0162 1
 
1.5%
041-662-1599 1
 
1.5%
041-665-6073 1
 
1.5%
041-667-3173 1
 
1.5%
Other values (54) 54
83.1%
2024-01-10T06:32:09.252457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 140
17.9%
- 130
16.6%
0 103
13.2%
1 92
11.8%
4 90
11.5%
2 55
 
7.0%
3 40
 
5.1%
8 38
 
4.9%
5 33
 
4.2%
7 32
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 651
83.4%
Dash Punctuation 130
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 140
21.5%
0 103
15.8%
1 92
14.1%
4 90
13.8%
2 55
 
8.4%
3 40
 
6.1%
8 38
 
5.8%
5 33
 
5.1%
7 32
 
4.9%
9 28
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 130
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 781
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 140
17.9%
- 130
16.6%
0 103
13.2%
1 92
11.8%
4 90
11.5%
2 55
 
7.0%
3 40
 
5.1%
8 38
 
4.9%
5 33
 
4.2%
7 32
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 781
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 140
17.9%
- 130
16.6%
0 103
13.2%
1 92
11.8%
4 90
11.5%
2 55
 
7.0%
3 40
 
5.1%
8 38
 
4.9%
5 33
 
4.2%
7 32
 
4.1%

업태명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size756.0 B
일반이용업
75 
이용업 기타
 
3

Length

Max length6
Median length5
Mean length5.0384615
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 75
96.2%
이용업 기타 3
 
3.8%

Length

2024-01-10T06:32:09.364137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:32:09.441033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 75
92.6%
이용업 3
 
3.7%
기타 3
 
3.7%

의자수
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct7
Distinct (%)10.0%
Missing8
Missing (%)10.3%
Infinite0
Infinite (%)0.0%
Mean2.7
Minimum0
Maximum10
Zeros2
Zeros (%)2.6%
Negative0
Negative (%)0.0%
Memory size834.0 B
2024-01-10T06:32:09.511203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q33
95-th percentile4
Maximum10
Range10
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.3550763
Coefficient of variation (CV)0.50188013
Kurtosis12.576111
Mean2.7
Median Absolute Deviation (MAD)1
Skewness2.5117699
Sum189
Variance1.8362319
MonotonicityNot monotonic
2024-01-10T06:32:09.590647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
3 28
35.9%
2 26
33.3%
4 8
 
10.3%
1 4
 
5.1%
0 2
 
2.6%
10 1
 
1.3%
7 1
 
1.3%
(Missing) 8
 
10.3%
ValueCountFrequency (%)
0 2
 
2.6%
1 4
 
5.1%
2 26
33.3%
3 28
35.9%
4 8
 
10.3%
7 1
 
1.3%
10 1
 
1.3%
ValueCountFrequency (%)
10 1
 
1.3%
7 1
 
1.3%
4 8
 
10.3%
3 28
35.9%
2 26
33.3%
1 4
 
5.1%
0 2
 
2.6%

침대수
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size756.0 B
<NA>
61 
0
17 

Length

Max length4
Median length4
Mean length3.3461538
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 61
78.2%
0 17
 
21.8%

Length

2024-01-10T06:32:09.686106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:32:09.764211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 61
78.2%
0 17
 
21.8%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size756.0 B
Minimum2016-05-16 00:00:00
Maximum2016-05-16 00:00:00
2024-01-10T06:32:09.828190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:09.894861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-01-10T06:32:07.024958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:32:09.951165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명업소소재지(도로명)소재지전화업태명의자수
업소명1.0001.0000.9941.0000.173
업소소재지(도로명)1.0001.0001.0001.0001.000
소재지전화0.9941.0001.0001.0001.000
업태명1.0001.0001.0001.0000.000
의자수0.1731.0001.0000.0001.000
2024-01-10T06:32:10.026337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
침대수업태명
침대수1.0001.000
업태명1.0001.000
2024-01-10T06:32:10.093330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
의자수업태명침대수
의자수1.0000.0581.000
업태명0.0581.0001.000
침대수1.0001.0001.000

Missing values

2024-01-10T06:32:07.317599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:32:07.412167image/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.
2024-01-10T06:32:07.487029image/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

업종명업소명업소소재지(도로명)소재지전화업태명의자수침대수데이터기준일
0이용업공림이용원충청남도 서산시 서해로 3203 (예천동)041-662-3365일반이용업3<NA>2016-05-16
1이용업월성이용원충청남도 서산시 음암면 도당리 858번지041-663-6011일반이용업3<NA>2016-05-16
2이용업신성이용원충청남도 서산시 성연면 고남리 496번지041-662-7816일반이용업2<NA>2016-05-16
3이용업대천이용원충청남도 서산시 동헌로 104, 1층 (읍내동)041-662-2198일반이용업2<NA>2016-05-16
4이용업서동이용원충청남도 서산시 율지12길 20 (동문동,(1층))<NA>일반이용업2<NA>2016-05-16
5이용업미용각이용원충청남도 서산시 읍내동 175번지 1호 175-2, 176, 176-2(2층)041-664-2503일반이용업4<NA>2016-05-16
6이용업광성이용원충청남도 서산시 부석면 취평2길 18-1041-662-4070일반이용업3<NA>2016-05-16
7이용업대원이용원충청남도 서산시 학동11로 지하 4, 1층 (동문동)041-665-4327일반이용업2<NA>2016-05-16
8이용업성연이용원충청남도 서산시 성연면 성연로 210-5041-662-8275일반이용업2<NA>2016-05-16
9이용업석남이용원충청남도 서산시 안견로 237, 1층 (동문동)041-665-4422일반이용업3<NA>2016-05-16
업종명업소명업소소재지(도로명)소재지전화업태명의자수침대수데이터기준일
68이용업명성이용원충청남도 서산시 중앙로 지하 51, 1층 (동문동)041-681-8023일반이용업702016-05-16
69이용업오땡큐염색방 죽성.양대점충청남도 서산시 남부순환로 767, 상가동 1층 32호 (죽성동, 삼성아파트)041-667-5494이용업 기타202016-05-16
70이용업제일이용원충청남도 서산시 대산읍 충의로 1942, 114호 (대산종합시장)041-681-3922일반이용업302016-05-16
71이용업태후사랑 서산동문점충청남도 서산시 율지3로 36, 1층 (동문동)041-667-4294이용업 기타202016-05-16
72이용업나성이발소충청남도 서산시 시장8로 1-4, 1층 (동문동)<NA>일반이용업202016-05-16
73이용업태후사랑충청남도 서산시 중앙로 102, 1층 (동문동)<NA>이용업 기타202016-05-16
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75이용업서산스포츠타운 이용원충청남도 서산시 충의로 지하 49, 1층 (예천동)<NA>일반이용업202016-05-16
76이용업학돌이용원충청남도 서산시 부춘2로 지하 24, 1층 (읍내동)<NA>일반이용업102016-05-16
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