Overview

Dataset statistics

Number of variables6
Number of observations70
Missing cells18
Missing cells (%)4.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.5 KiB
Average record size in memory50.9 B

Variable types

Categorical1
Text3
Numeric1
DateTime1

Dataset

Description경상북도 영양군 공중위생업에 대한 데이터로 업종명, 업소명, 업소소재지도로명주소, 전화번호정보를 제공합니다.
Author경상북도 영양군
URLhttps://www.data.go.kr/data/15006812/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
전화번호 has 18 (25.7%) missing valuesMissing
업소명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 19:44:33.045035
Analysis finished2023-12-12 19:44:33.757911
Duration0.71 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

Distinct10
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size692.0 B
일반미용업
15 
숙박업(일반)
10 
이용업
10 
세탁업
8 
건물위생관리업
7 
Other values (5)
20 

Length

Max length7
Median length5
Mean length4.7428571
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반미용업 15
21.4%
숙박업(일반) 10
14.3%
이용업 10
14.3%
세탁업 8
11.4%
건물위생관리업 7
10.0%
목욕장업 6
 
8.6%
미용업 5
 
7.1%
피부미용업 4
 
5.7%
종합미용업 3
 
4.3%
네일미용업 2
 
2.9%

Length

2023-12-13T04:44:33.851551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:44:34.013939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반미용업 15
21.4%
숙박업(일반 10
14.3%
이용업 10
14.3%
세탁업 8
11.4%
건물위생관리업 7
10.0%
목욕장업 6
 
8.6%
미용업 5
 
7.1%
피부미용업 4
 
5.7%
종합미용업 3
 
4.3%
네일미용업 2
 
2.9%

업소명
Text

UNIQUE 

Distinct70
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size692.0 B
2023-12-13T04:44:34.328852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length5.6
Min length2

Characters and Unicode

Total characters392
Distinct characters150
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)100.0%

Sample

1st row부산여인숙
2nd row목화모텔
3rd row궁전장 여관
4th row삼영모텔
5th row알토모텔
ValueCountFrequency (%)
부산여인숙 1
 
1.3%
금자 1
 
1.3%
은실미용실 1
 
1.3%
박미용실 1
 
1.3%
샘미용실 1
 
1.3%
정아머리방 1
 
1.3%
대구미용실 1
 
1.3%
다은종합환경 1
 
1.3%
미장원 1
 
1.3%
청아종합용역 1
 
1.3%
Other values (69) 69
87.3%
2023-12-13T04:44:34.832922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
용 23
 
5.9%
소 18
 
4.6%
미 15
 
3.8%
이 14
 
3.6%
실 10
 
2.6%
9
 
2.3%
세 9
 
2.3%
탁 8
 
2.0%
어 7
 
1.8%
영 7
 
1.8%
Other values (140) 272
69.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 372
94.9%
Space Separator 9
 
2.3%
Decimal Number 6
 
1.5%
Close Punctuation 2
 
0.5%
Open Punctuation 2
 
0.5%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
용 23
 
6.2%
소 18
 
4.8%
미 15
 
4.0%
이 14
 
3.8%
실 10
 
2.7%
세 9
 
2.4%
탁 8
 
2.2%
어 7
 
1.9%
영 7
 
1.9%
헤 6
 
1.6%
Other values (133) 255
68.5%
Decimal Number
ValueCountFrequency (%)
2 3
50.0%
1 2
33.3%
4 1
 
16.7%
Space Separator
ValueCountFrequency (%)
9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Other Punctuation
ValueCountFrequency (%)
: 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 372
94.9%
Common 20
 
5.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
용 23
 
6.2%
소 18
 
4.8%
미 15
 
4.0%
이 14
 
3.8%
실 10
 
2.7%
세 9
 
2.4%
탁 8
 
2.2%
어 7
 
1.9%
영 7
 
1.9%
헤 6
 
1.6%
Other values (133) 255
68.5%
Common
ValueCountFrequency (%)
9
45.0%
2 3
 
15.0%
1 2
 
10.0%
) 2
 
10.0%
( 2
 
10.0%
4 1
 
5.0%
: 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 372
94.9%
ASCII 20
 
5.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
용 23
 
6.2%
소 18
 
4.8%
미 15
 
4.0%
이 14
 
3.8%
실 10
 
2.7%
세 9
 
2.4%
탁 8
 
2.2%
어 7
 
1.9%
영 7
 
1.9%
헤 6
 
1.6%
Other values (133) 255
68.5%
ASCII
ValueCountFrequency (%)
9
45.0%
2 3
 
15.0%
1 2
 
10.0%
) 2
 
10.0%
( 2
 
10.0%
4 1
 
5.0%
: 1
 
5.0%

우편번호(도로명)
Real number (ℝ)

Distinct13
Distinct (%)18.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36541.257
Minimum36521
Maximum36560
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size762.0 B
2023-12-13T04:44:34.997674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36521
5-th percentile36532.6
Q136539.25
median36541
Q336541.75
95-th percentile36553.5
Maximum36560
Range39
Interquartile range (IQR)2.5

Descriptive statistics

Standard deviation6.8285117
Coefficient of variation (CV)0.00018687128
Kurtosis3.6596814
Mean36541.257
Median Absolute Deviation (MAD)1
Skewness0.088315269
Sum2557888
Variance46.628571
MonotonicityNot monotonic
2023-12-13T04:44:35.176236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
36541 28
40.0%
36548 8
 
11.4%
36538 8
 
11.4%
36540 6
 
8.6%
36537 5
 
7.1%
36542 5
 
7.1%
36560 3
 
4.3%
36522 2
 
2.9%
36539 1
 
1.4%
36558 1
 
1.4%
Other values (3) 3
 
4.3%
ValueCountFrequency (%)
36521 1
 
1.4%
36522 2
 
2.9%
36529 1
 
1.4%
36537 5
 
7.1%
36538 8
 
11.4%
36539 1
 
1.4%
36540 6
 
8.6%
36541 28
40.0%
36542 5
 
7.1%
36546 1
 
1.4%
ValueCountFrequency (%)
36560 3
 
4.3%
36558 1
 
1.4%
36548 8
 
11.4%
36546 1
 
1.4%
36542 5
 
7.1%
36541 28
40.0%
36540 6
 
8.6%
36539 1
 
1.4%
36538 8
 
11.4%
36537 5
 
7.1%

영업소 주소(도로명)
Text

Distinct65
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Memory size692.0 B
2023-12-13T04:44:35.545625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length30
Mean length21.214286
Min length19

Characters and Unicode

Total characters1485
Distinct characters79
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

Unique61 ?
Unique (%)87.1%

Sample

1st row경상북도 영양군 영양읍 황용천길 12
2nd row경상북도 영양군 영양읍 동서대로 52
3rd row경상북도 영양군 영양읍 낙원로 62
4th row경상북도 영양군 입암면 입암로 96
5th row경상북도 영양군 영양읍 중앙로 116-1
ValueCountFrequency (%)
경상북도 70
19.3%
영양군 70
19.3%
영양읍 54
14.9%
중앙로 14
 
3.9%
입암면 9
 
2.5%
시장길 9
 
2.5%
동서대로 7
 
1.9%
황용천길 6
 
1.7%
영양창수로 5
 
1.4%
입암로 4
 
1.1%
Other values (81) 115
31.7%
2023-12-13T04:44:36.087921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
293
19.7%
영 132
 
8.9%
양 132
 
8.9%
군 72
 
4.8%
경 71
 
4.8%
상 70
 
4.7%
도 70
 
4.7%
북 70
 
4.7%
1 55
 
3.7%
읍 54
 
3.6%
Other values (69) 466
31.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 981
66.1%
Space Separator 293
 
19.7%
Decimal Number 186
 
12.5%
Dash Punctuation 12
 
0.8%
Other Punctuation 11
 
0.7%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 132
13.5%
양 132
13.5%
군 72
 
7.3%
경 71
 
7.2%
상 70
 
7.1%
도 70
 
7.1%
북 70
 
7.1%
읍 54
 
5.5%
로 38
 
3.9%
길 32
 
3.3%
Other values (54) 240
24.5%
Decimal Number
ValueCountFrequency (%)
1 55
29.6%
2 26
14.0%
3 22
 
11.8%
4 20
 
10.8%
5 18
 
9.7%
6 12
 
6.5%
0 9
 
4.8%
7 9
 
4.8%
8 8
 
4.3%
9 7
 
3.8%
Space Separator
ValueCountFrequency (%)
293
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Other Punctuation
ValueCountFrequency (%)
, 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 981
66.1%
Common 504
33.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 132
13.5%
양 132
13.5%
군 72
 
7.3%
경 71
 
7.2%
상 70
 
7.1%
도 70
 
7.1%
북 70
 
7.1%
읍 54
 
5.5%
로 38
 
3.9%
길 32
 
3.3%
Other values (54) 240
24.5%
Common
ValueCountFrequency (%)
293
58.1%
1 55
 
10.9%
2 26
 
5.2%
3 22
 
4.4%
4 20
 
4.0%
5 18
 
3.6%
- 12
 
2.4%
6 12
 
2.4%
, 11
 
2.2%
0 9
 
1.8%
Other values (5) 26
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 981
66.1%
ASCII 504
33.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
293
58.1%
1 55
 
10.9%
2 26
 
5.2%
3 22
 
4.4%
4 20
 
4.0%
5 18
 
3.6%
- 12
 
2.4%
6 12
 
2.4%
, 11
 
2.2%
0 9
 
1.8%
Other values (5) 26
 
5.2%
Hangul
ValueCountFrequency (%)
영 132
13.5%
양 132
13.5%
군 72
 
7.3%
경 71
 
7.2%
상 70
 
7.1%
도 70
 
7.1%
북 70
 
7.1%
읍 54
 
5.5%
로 38
 
3.9%
길 32
 
3.3%
Other values (54) 240
24.5%

전화번호
Text

MISSING 

Distinct51
Distinct (%)98.1%
Missing18
Missing (%)25.7%
Memory size692.0 B
2023-12-13T04:44:36.427102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters624
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

Unique50 ?
Unique (%)96.2%

Sample

1st row054-683-2163
2nd row054-683-1515
3rd row054-682-6964
4th row054-682-7766
5th row054-683-3284
ValueCountFrequency (%)
054-682-4411 2
 
3.8%
054-682-1369 1
 
1.9%
054-683-2163 1
 
1.9%
054-682-0971 1
 
1.9%
054-682-9609 1
 
1.9%
054-682-1975 1
 
1.9%
054-683-3206 1
 
1.9%
054-683-4554 1
 
1.9%
054-682-3338 1
 
1.9%
054-683-7482 1
 
1.9%
Other values (41) 41
78.8%
2023-12-13T04:44:36.886091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 104
16.7%
0 77
12.3%
5 77
12.3%
4 77
12.3%
6 67
10.7%
8 63
10.1%
2 48
7.7%
3 46
7.4%
1 28
 
4.5%
7 20
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 520
83.3%
Dash Punctuation 104
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 77
14.8%
5 77
14.8%
4 77
14.8%
6 67
12.9%
8 63
12.1%
2 48
9.2%
3 46
8.8%
1 28
 
5.4%
7 20
 
3.8%
9 17
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 104
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 624
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 104
16.7%
0 77
12.3%
5 77
12.3%
4 77
12.3%
6 67
10.7%
8 63
10.1%
2 48
7.7%
3 46
7.4%
1 28
 
4.5%
7 20
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 624
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 104
16.7%
0 77
12.3%
5 77
12.3%
4 77
12.3%
6 67
10.7%
8 63
10.1%
2 48
7.7%
3 46
7.4%
1 28
 
4.5%
7 20
 
3.2%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size692.0 B
Minimum2023-09-01 00:00:00
Maximum2023-09-01 00:00:00
2023-12-13T04:44:37.015305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:44:37.109273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T04:44:33.395343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T04:44:37.188270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명업소명우편번호(도로명)영업소 주소(도로명)전화번호
업종명1.0001.0000.2140.7120.932
업소명1.0001.0001.0001.0001.000
우편번호(도로명)0.2141.0001.0001.0001.000
영업소 주소(도로명)0.7121.0001.0001.0001.000
전화번호0.9321.0001.0001.0001.000
2023-12-13T04:44:37.306652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호(도로명)업종명
우편번호(도로명)1.0000.062
업종명0.0621.000

Missing values

2023-12-13T04:44:33.566458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:44:33.705969image/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

업종명업소명우편번호(도로명)영업소 주소(도로명)전화번호데이터기준일자
0숙박업(일반)부산여인숙36540경상북도 영양군 영양읍 황용천길 12054-683-21632023-09-01
1숙박업(일반)목화모텔36540경상북도 영양군 영양읍 동서대로 52054-683-15152023-09-01
2숙박업(일반)궁전장 여관36539경상북도 영양군 영양읍 낙원로 62054-682-69642023-09-01
3숙박업(일반)삼영모텔36548경상북도 영양군 입암면 입암로 96054-682-77662023-09-01
4숙박업(일반)알토모텔36541경상북도 영양군 영양읍 중앙로 116-1054-683-32842023-09-01
5숙박업(일반)석보여관36560경상북도 영양군 석보면 원리길 18054-682-82652023-09-01
6숙박업(일반)청향소림산장36558경상북도 영양군 석보면 화무로 623054-683-88322023-09-01
7숙박업(일반)아이엠모텔36541경상북도 영양군 영양읍 중앙로 136054-683-00242023-09-01
8숙박업(일반)쇼호텔36538경상북도 영양군 영양읍 중앙로 117054-683-35332023-09-01
9숙박업(일반)필영양관광호텔36546경상북도 영양군 입암면 영양로 873<NA>2023-09-01
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