Overview

Dataset statistics

Number of variables6
Number of observations45
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.3 KiB
Average record size in memory51.9 B

Variable types

Categorical2
Text3
Numeric1

Dataset

Description울산광역시_기타서비스(문화시설, 개인위생 및 숙박 서비스, 가격, 전화번호, 소재지, 특징 등 ) 물가동향을 제공
Author울산광역시
URLhttps://www.data.go.kr/data/15065100/fileData.do

Alerts

품목별 is highly overall correlated with 구분High correlation
구분 is highly overall correlated with 품목별High correlation
소재지 has unique valuesUnique

Reproduction

Analysis started2023-12-12 05:42:54.134724
Analysis finished2023-12-12 05:42:54.926730
Duration0.79 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

품목별
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size492.0 B
이 용 료
5 
미용료(파마)
5 
목 욕 료
5 
숙박료 (호텔제외)
5 
세 탁 료
5 
Other values (4)
20 

Length

Max length10
Median length5
Mean length6
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row이 용 료
2nd row이 용 료
3rd row이 용 료
4th row이 용 료
5th row이 용 료

Common Values

ValueCountFrequency (%)
이 용 료 5
11.1%
미용료(파마) 5
11.1%
목 욕 료 5
11.1%
숙박료 (호텔제외) 5
11.1%
세 탁 료 5
11.1%
노래방이용료 5
11.1%
의복수선료 5
11.1%
사진촬영료 5
11.1%
PC방이용료 5
11.1%

Length

2023-12-12T14:42:55.011566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:42:55.179088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
료 15
18.8%
이 5
 
6.2%
용 5
 
6.2%
미용료(파마 5
 
6.2%
목 5
 
6.2%
욕 5
 
6.2%
숙박료 5
 
6.2%
호텔제외 5
 
6.2%
세 5
 
6.2%
탁 5
 
6.2%
Other values (4) 20
25.0%

구분
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size492.0 B
성인중급 1회
5 
성인여자 중급1회
5 
일반대중탕 성인1회
5 
갑류 1인1박, 모텔
5 
신사복 상.하 1벌 드라이크리닝
5 
Other values (4)
20 

Length

Max length17
Median length10
Mean length9.5555556
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row성인중급 1회
2nd row성인중급 1회
3rd row성인중급 1회
4th row성인중급 1회
5th row성인중급 1회

Common Values

ValueCountFrequency (%)
성인중급 1회 5
11.1%
성인여자 중급1회 5
11.1%
일반대중탕 성인1회 5
11.1%
갑류 1인1박, 모텔 5
11.1%
신사복 상.하 1벌 드라이크리닝 5
11.1%
일반실1시간 5
11.1%
신사복바지 밑단 줄임 5
11.1%
명함판칼라 기본1조 5
11.1%
성인1시간 5
11.1%

Length

2023-12-12T14:42:55.355100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:42:55.504180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
성인중급 5
 
5.0%
1회 5
 
5.0%
기본1조 5
 
5.0%
명함판칼라 5
 
5.0%
줄임 5
 
5.0%
밑단 5
 
5.0%
신사복바지 5
 
5.0%
일반실1시간 5
 
5.0%
드라이크리닝 5
 
5.0%
1벌 5
 
5.0%
Other values (10) 50
50.0%

업소명
Text

Distinct44
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size492.0 B
2023-12-12T14:42:55.771518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length5.1333333
Min length3

Characters and Unicode

Total characters231
Distinct characters117
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)95.6%

Sample

1st row블루클럽
2nd row남성커트클럽
3rd row진성이용원
4th row포맨헤어컷
5th row남일이용원
ValueCountFrequency (%)
크린토피아 2
 
4.1%
남성커트클럽 1
 
2.0%
유니온노래방 1
 
2.0%
서울노래연습장 1
 
2.0%
탑코인노래연습장 1
 
2.0%
뱅뱅 1
 
2.0%
동전 1
 
2.0%
노래방 1
 
2.0%
우정옷수선 1
 
2.0%
유진옷수선 1
 
2.0%
Other values (38) 38
77.6%
2023-12-12T14:42:56.143917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
진 7
 
3.0%
장 6
 
2.6%
6
 
2.6%
래 5
 
2.2%
노 5
 
2.2%
사 5
 
2.2%
옷 5
 
2.2%
선 5
 
2.2%
수 5
 
2.2%
탕 4
 
1.7%
Other values (107) 178
77.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 213
92.2%
Space Separator 6
 
2.6%
Lowercase Letter 6
 
2.6%
Uppercase Letter 4
 
1.7%
Open Punctuation 1
 
0.4%
Close Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
진 7
 
3.3%
장 6
 
2.8%
래 5
 
2.3%
노 5
 
2.3%
사 5
 
2.3%
옷 5
 
2.3%
선 5
 
2.3%
수 5
 
2.3%
탕 4
 
1.9%
방 4
 
1.9%
Other values (100) 162
76.1%
Lowercase Letter
ValueCountFrequency (%)
c 3
50.0%
p 3
50.0%
Uppercase Letter
ValueCountFrequency (%)
C 2
50.0%
P 2
50.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 213
92.2%
Latin 10
 
4.3%
Common 8
 
3.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
진 7
 
3.3%
장 6
 
2.8%
래 5
 
2.3%
노 5
 
2.3%
사 5
 
2.3%
옷 5
 
2.3%
선 5
 
2.3%
수 5
 
2.3%
탕 4
 
1.9%
방 4
 
1.9%
Other values (100) 162
76.1%
Latin
ValueCountFrequency (%)
c 3
30.0%
p 3
30.0%
C 2
20.0%
P 2
20.0%
Common
ValueCountFrequency (%)
6
75.0%
( 1
 
12.5%
) 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 213
92.2%
ASCII 18
 
7.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
진 7
 
3.3%
장 6
 
2.8%
래 5
 
2.3%
노 5
 
2.3%
사 5
 
2.3%
옷 5
 
2.3%
선 5
 
2.3%
수 5
 
2.3%
탕 4
 
1.9%
방 4
 
1.9%
Other values (100) 162
76.1%
ASCII
ValueCountFrequency (%)
6
33.3%
c 3
16.7%
p 3
16.7%
C 2
 
11.1%
P 2
 
11.1%
( 1
 
5.6%
) 1
 
5.6%

소재지
Text

UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size492.0 B
2023-12-12T14:42:56.438888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length23
Mean length18.2
Min length15

Characters and Unicode

Total characters819
Distinct characters96
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

Unique45 ?
Unique (%)100.0%

Sample

1st row울산광역시 중구 평동길 6-1
2nd row울산광역시 남구 수암로224번길 23
3rd row울산광역시 동구 진성12길 115
4th row울산광역시 북구 염포로 471
5th row울산광역시 울주군 남창1길 40-1
ValueCountFrequency (%)
울산광역시 45
23.8%
중구 9
 
4.8%
남구 9
 
4.8%
동구 9
 
4.8%
북구 9
 
4.8%
울주군 9
 
4.8%
범서읍 4
 
2.1%
수암로 2
 
1.1%
팔등로 2
 
1.1%
언양읍 2
 
1.1%
Other values (83) 89
47.1%
2023-12-12T14:42:56.955499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
147
17.9%
울 54
 
6.6%
산 49
 
6.0%
시 47
 
5.7%
광 45
 
5.5%
역 45
 
5.5%
구 38
 
4.6%
1 36
 
4.4%
길 26
 
3.2%
2 22
 
2.7%
Other values (86) 310
37.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 517
63.1%
Space Separator 147
 
17.9%
Decimal Number 141
 
17.2%
Dash Punctuation 9
 
1.1%
Other Punctuation 3
 
0.4%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
울 54
 
10.4%
산 49
 
9.5%
시 47
 
9.1%
광 45
 
8.7%
역 45
 
8.7%
구 38
 
7.4%
길 26
 
5.0%
로 21
 
4.1%
동 14
 
2.7%
중 12
 
2.3%
Other values (71) 166
32.1%
Decimal Number
ValueCountFrequency (%)
1 36
25.5%
2 22
15.6%
4 22
15.6%
0 13
 
9.2%
3 12
 
8.5%
5 10
 
7.1%
7 8
 
5.7%
8 7
 
5.0%
6 7
 
5.0%
9 4
 
2.8%
Space Separator
ValueCountFrequency (%)
147
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 517
63.1%
Common 302
36.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
울 54
 
10.4%
산 49
 
9.5%
시 47
 
9.1%
광 45
 
8.7%
역 45
 
8.7%
구 38
 
7.4%
길 26
 
5.0%
로 21
 
4.1%
동 14
 
2.7%
중 12
 
2.3%
Other values (71) 166
32.1%
Common
ValueCountFrequency (%)
147
48.7%
1 36
 
11.9%
2 22
 
7.3%
4 22
 
7.3%
0 13
 
4.3%
3 12
 
4.0%
5 10
 
3.3%
- 9
 
3.0%
7 8
 
2.6%
8 7
 
2.3%
Other values (5) 16
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 517
63.1%
ASCII 302
36.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
147
48.7%
1 36
 
11.9%
2 22
 
7.3%
4 22
 
7.3%
0 13
 
4.3%
3 12
 
4.0%
5 10
 
3.3%
- 9
 
3.0%
7 8
 
2.6%
8 7
 
2.3%
Other values (5) 16
 
5.3%
Hangul
ValueCountFrequency (%)
울 54
 
10.4%
산 49
 
9.5%
시 47
 
9.1%
광 45
 
8.7%
역 45
 
8.7%
구 38
 
7.4%
길 26
 
5.0%
로 21
 
4.1%
동 14
 
2.7%
중 12
 
2.3%
Other values (71) 166
32.1%

가격
Real number (ℝ)

Distinct23
Distinct (%)51.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12280
Minimum1000
Maximum40000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T14:42:57.104921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1000
5-th percentile1020
Q15000
median7000
Q320000
95-th percentile35000
Maximum40000
Range39000
Interquartile range (IQR)15000

Descriptive statistics

Standard deviation11134.031
Coefficient of variation (CV)0.90668001
Kurtosis0.35201734
Mean12280
Median Absolute Deviation (MAD)5000
Skewness1.1499571
Sum552600
Variance1.2396664 × 108
MonotonicityNot monotonic
2023-12-12T14:42:57.244069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
20000 6
 
13.3%
5000 5
 
11.1%
15000 4
 
8.9%
1000 3
 
6.7%
10000 2
 
4.4%
2000 2
 
4.4%
3000 2
 
4.4%
8000 2
 
4.4%
35000 2
 
4.4%
30000 2
 
4.4%
Other values (13) 15
33.3%
ValueCountFrequency (%)
1000 3
6.7%
1100 1
 
2.2%
1500 1
 
2.2%
2000 2
 
4.4%
3000 2
 
4.4%
4000 1
 
2.2%
5000 5
11.1%
5600 1
 
2.2%
5700 1
 
2.2%
6000 2
 
4.4%
ValueCountFrequency (%)
40000 2
 
4.4%
35000 2
 
4.4%
30000 2
 
4.4%
25000 1
 
2.2%
20000 6
13.3%
15000 4
8.9%
10000 2
 
4.4%
8000 2
 
4.4%
7500 1
 
2.2%
7000 1
 
2.2%

전화번호
Text

Distinct32
Distinct (%)71.1%
Missing0
Missing (%)0.0%
Memory size492.0 B
2023-12-12T14:42:57.485294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.022222
Min length9

Characters and Unicode

Total characters496
Distinct characters20
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

Unique31 ?
Unique (%)68.9%

Sample

1st row052-246-5114
2nd row070-4220-1999
3rd row개인정보로 미기재
4th row052-287-2858
5th row052-242-1336
ValueCountFrequency (%)
개인정보로 14
23.7%
미기재 14
23.7%
052-262-3811 1
 
1.7%
052-232-6649 1
 
1.7%
052-262-0078 1
 
1.7%
052-239-4901 1
 
1.7%
052-268-4594 1
 
1.7%
052-291-1006 1
 
1.7%
052-287-9428 1
 
1.7%
052-289-9898 1
 
1.7%
Other values (23) 23
39.0%
2023-12-12T14:42:57.893982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 82
16.5%
- 61
12.3%
5 45
 
9.1%
0 45
 
9.1%
1 27
 
5.4%
8 24
 
4.8%
6 21
 
4.2%
9 21
 
4.2%
3 18
 
3.6%
4 17
 
3.4%
Other values (10) 135
27.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 309
62.3%
Other Letter 112
 
22.6%
Dash Punctuation 61
 
12.3%
Space Separator 14
 
2.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 82
26.5%
5 45
14.6%
0 45
14.6%
1 27
 
8.7%
8 24
 
7.8%
6 21
 
6.8%
9 21
 
6.8%
3 18
 
5.8%
4 17
 
5.5%
7 9
 
2.9%
Other Letter
ValueCountFrequency (%)
재 14
12.5%
기 14
12.5%
인 14
12.5%
미 14
12.5%
로 14
12.5%
보 14
12.5%
정 14
12.5%
개 14
12.5%
Dash Punctuation
ValueCountFrequency (%)
- 61
100.0%
Space Separator
ValueCountFrequency (%)
14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 384
77.4%
Hangul 112
 
22.6%

Most frequent character per script

Common
ValueCountFrequency (%)
2 82
21.4%
- 61
15.9%
5 45
11.7%
0 45
11.7%
1 27
 
7.0%
8 24
 
6.2%
6 21
 
5.5%
9 21
 
5.5%
3 18
 
4.7%
4 17
 
4.4%
Other values (2) 23
 
6.0%
Hangul
ValueCountFrequency (%)
재 14
12.5%
기 14
12.5%
인 14
12.5%
미 14
12.5%
로 14
12.5%
보 14
12.5%
정 14
12.5%
개 14
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 384
77.4%
Hangul 112
 
22.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 82
21.4%
- 61
15.9%
5 45
11.7%
0 45
11.7%
1 27
 
7.0%
8 24
 
6.2%
6 21
 
5.5%
9 21
 
5.5%
3 18
 
4.7%
4 17
 
4.4%
Other values (2) 23
 
6.0%
Hangul
ValueCountFrequency (%)
재 14
12.5%
기 14
12.5%
인 14
12.5%
미 14
12.5%
로 14
12.5%
보 14
12.5%
정 14
12.5%
개 14
12.5%

Interactions

2023-12-12T14:42:54.561287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:42:58.013683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
품목별구분업소명소재지가격전화번호
품목별1.0001.0001.0001.0000.8460.513
구분1.0001.0001.0001.0000.8460.513
업소명1.0001.0001.0001.0001.0000.990
소재지1.0001.0001.0001.0001.0001.000
가격0.8460.8461.0001.0001.0000.208
전화번호0.5130.5130.9901.0000.2081.000
2023-12-12T14:42:58.131387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
품목별구분
품목별1.0001.000
구분1.0001.000
2023-12-12T14:42:58.218241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가격품목별구분
가격1.0000.4380.438
품목별0.4381.0001.000
구분0.4381.0001.000

Missing values

2023-12-12T14:42:54.720317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:42:54.879658image/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

품목별구분업소명소재지가격전화번호
0이 용 료성인중급 1회블루클럽울산광역시 중구 평동길 6-110000052-246-5114
1이 용 료성인중급 1회남성커트클럽울산광역시 남구 수암로224번길 238000070-4220-1999
2이 용 료성인중급 1회진성이용원울산광역시 동구 진성12길 1158000개인정보로 미기재
3이 용 료성인중급 1회포맨헤어컷울산광역시 북구 염포로 4716000052-287-2858
4이 용 료성인중급 1회남일이용원울산광역시 울주군 남창1길 40-17000052-242-1336
5미용료(파마)성인여자 중급1회나나미용실울산광역시 중구 화진4길2040000052-211-8995
6미용료(파마)성인여자 중급1회오드리햅번울산광역시 남구 수암로 22315000052-276-8422
7미용료(파마)성인여자 중급1회정헤어샵울산광역시 동구 명덕3길4030000052-233-1334
8미용료(파마)성인여자 중급1회정자미용실울산광역시 북구 정자7길 4425000개인정보로 미기재
9미용료(파마)성인여자 중급1회에덴헤어샵울산광역시 울주군 범서읍 천상중앙길 1120000052-268-2893
품목별구분업소명소재지가격전화번호
35사진촬영료명함판칼라 기본1조디지털월드울산광역시 중구 번영로 47520000개인정보로 미기재
36사진촬영료명함판칼라 기본1조성사진관울산광역시 남구 수암로 119-1(신정동)15000052-268-4594
37사진촬영료명함판칼라 기본1조사진마당울산광역시 동구 미포1길 4520000052-239-4901
38사진촬영료명함판칼라 기본1조에이린의 사진관울산광역시 북구 호계매곡1로 3210000개인정보로 미기재
39사진촬영료명함판칼라 기본1조사진동네울산광역시 울주군 언양읍 동문길 7415000052-262-0078
40PC방이용료성인1시간티오PC존울산광역시 중구 구교12길 11500개인정보로 미기재
41PC방이용료성인1시간킹PC울산광역시 남구 삼산로 201000개인정보로 미기재
42PC방이용료성인1시간차칸pc울산광역시 동구 방어진순환도로 7831100052-232-6649
43PC방이용료성인1시간쎈pc방울산광역시 북구 강동산하5로 26-2, 3층1000개인정보로 미기재
44PC방이용료성인1시간스타덤 pc방울산광역시 울주군 범서읍 천상중앙길 10410001600-5890