Overview

Dataset statistics

Number of variables5
Number of observations21
Missing cells11
Missing cells (%)10.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory993.0 B
Average record size in memory47.3 B

Variable types

Numeric1
Text4

Dataset

Description부산광역시중구_소독업소현황_20230915
Author부산광역시 중구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3075229

Alerts

영업소전화번호 has 5 (23.8%) missing valuesMissing
팩스번호 has 6 (28.6%) missing valuesMissing
순번 has unique valuesUnique
소독업소명칭 has unique valuesUnique
사무실소재지(도로명) has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:45:25.718191
Analysis finished2023-12-10 16:45:26.465651
Duration0.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11
Minimum1
Maximum21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-11T01:45:26.546682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q16
median11
Q316
95-th percentile20
Maximum21
Range20
Interquartile range (IQR)10

Descriptive statistics

Standard deviation6.2048368
Coefficient of variation (CV)0.56407607
Kurtosis-1.2
Mean11
Median Absolute Deviation (MAD)5
Skewness0
Sum231
Variance38.5
MonotonicityStrictly increasing
2023-12-11T01:45:26.672734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1 1
 
4.8%
2 1
 
4.8%
21 1
 
4.8%
20 1
 
4.8%
19 1
 
4.8%
18 1
 
4.8%
17 1
 
4.8%
16 1
 
4.8%
15 1
 
4.8%
14 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
1 1
4.8%
2 1
4.8%
3 1
4.8%
4 1
4.8%
5 1
4.8%
6 1
4.8%
7 1
4.8%
8 1
4.8%
9 1
4.8%
10 1
4.8%
ValueCountFrequency (%)
21 1
4.8%
20 1
4.8%
19 1
4.8%
18 1
4.8%
17 1
4.8%
16 1
4.8%
15 1
4.8%
14 1
4.8%
13 1
4.8%
12 1
4.8%

소독업소명칭
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-11T01:45:26.923281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8
Mean length6.952381
Min length4

Characters and Unicode

Total characters146
Distinct characters84
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

Unique21 ?
Unique (%)100.0%

Sample

1st rowBUG Cleanse
2nd row하이진코리아
3rd row엠더블유(MW)
4th row주식회사 수호코리아
5th row제일산업
ValueCountFrequency (%)
주식회사 2
 
7.1%
bug 1
 
3.6%
중앙점 1
 
3.6%
대진방역공사 1
 
3.6%
강남종합환경 1
 
3.6%
주)범양기업 1
 
3.6%
주)백경 1
 
3.6%
주)하나기업 1
 
3.6%
주)재덕 1
 
3.6%
주)썬앤문 1
 
3.6%
Other values (17) 17
60.7%
2023-12-11T01:45:27.384111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 9
 
6.2%
( 8
 
5.5%
) 8
 
5.5%
7
 
4.8%
사 4
 
2.7%
업 4
 
2.7%
방 4
 
2.7%
역 4
 
2.7%
기 3
 
2.1%
공 3
 
2.1%
Other values (74) 92
63.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 111
76.0%
Open Punctuation 8
 
5.5%
Close Punctuation 8
 
5.5%
Space Separator 7
 
4.8%
Lowercase Letter 6
 
4.1%
Uppercase Letter 6
 
4.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 9
 
8.1%
사 4
 
3.6%
업 4
 
3.6%
방 4
 
3.6%
역 4
 
3.6%
기 3
 
2.7%
공 3
 
2.7%
경 3
 
2.7%
남 2
 
1.8%
환 2
 
1.8%
Other values (60) 73
65.8%
Uppercase Letter
ValueCountFrequency (%)
B 1
16.7%
G 1
16.7%
C 1
16.7%
M 1
16.7%
W 1
16.7%
U 1
16.7%
Lowercase Letter
ValueCountFrequency (%)
e 2
33.3%
l 1
16.7%
a 1
16.7%
n 1
16.7%
s 1
16.7%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 111
76.0%
Common 23
 
15.8%
Latin 12
 
8.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 9
 
8.1%
사 4
 
3.6%
업 4
 
3.6%
방 4
 
3.6%
역 4
 
3.6%
기 3
 
2.7%
공 3
 
2.7%
경 3
 
2.7%
남 2
 
1.8%
환 2
 
1.8%
Other values (60) 73
65.8%
Latin
ValueCountFrequency (%)
e 2
16.7%
B 1
8.3%
G 1
8.3%
C 1
8.3%
l 1
8.3%
a 1
8.3%
n 1
8.3%
s 1
8.3%
M 1
8.3%
W 1
8.3%
Common
ValueCountFrequency (%)
( 8
34.8%
) 8
34.8%
7
30.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 111
76.0%
ASCII 35
 
24.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 9
 
8.1%
사 4
 
3.6%
업 4
 
3.6%
방 4
 
3.6%
역 4
 
3.6%
기 3
 
2.7%
공 3
 
2.7%
경 3
 
2.7%
남 2
 
1.8%
환 2
 
1.8%
Other values (60) 73
65.8%
ASCII
ValueCountFrequency (%)
( 8
22.9%
) 8
22.9%
7
20.0%
e 2
 
5.7%
B 1
 
2.9%
G 1
 
2.9%
C 1
 
2.9%
l 1
 
2.9%
a 1
 
2.9%
n 1
 
2.9%
Other values (4) 4
11.4%

사무실소재지(도로명)
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-11T01:45:27.728799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length38
Mean length35.047619
Min length27

Characters and Unicode

Total characters736
Distinct characters69
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row부산광역시 중구 중앙대로 80, 노블리안2 415호 (중앙동4가)
2nd row부산광역시 중구 충장대로9번길 23-2, 403호 (중앙동4가)
3rd row부산광역시 중구 중구로29번길 22, 301호, 302호 (부평동1가)
4th row부산광역시 중구 중앙대로20번길 3, 401호, 405호 (중앙동6가)
5th row부산광역시 중구 중앙대로116번길 7-1, 202호 (중앙동4가)
ValueCountFrequency (%)
부산광역시 21
 
15.3%
중구 21
 
15.3%
중앙동4가 10
 
7.3%
충장대로9번길 6
 
4.4%
해관로 3
 
2.2%
영주동 2
 
1.5%
65 2
 
1.5%
일부호 2
 
1.5%
3 2
 
1.5%
52 2
 
1.5%
Other values (60) 66
48.2%
2023-12-11T01:45:28.318067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
118
 
16.0%
중 41
 
5.6%
1 26
 
3.5%
부 25
 
3.4%
, 25
 
3.4%
광 24
 
3.3%
동 23
 
3.1%
4 23
 
3.1%
2 23
 
3.1%
산 23
 
3.1%
Other values (59) 385
52.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 401
54.5%
Decimal Number 137
 
18.6%
Space Separator 118
 
16.0%
Other Punctuation 25
 
3.4%
Open Punctuation 21
 
2.9%
Close Punctuation 21
 
2.9%
Dash Punctuation 10
 
1.4%
Uppercase Letter 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 41
 
10.2%
부 25
 
6.2%
광 24
 
6.0%
동 23
 
5.7%
산 23
 
5.7%
로 22
 
5.5%
시 22
 
5.5%
구 22
 
5.5%
역 21
 
5.2%
앙 19
 
4.7%
Other values (41) 159
39.7%
Decimal Number
ValueCountFrequency (%)
1 26
19.0%
4 23
16.8%
2 23
16.8%
3 16
11.7%
9 14
10.2%
0 13
9.5%
5 8
 
5.8%
7 7
 
5.1%
6 6
 
4.4%
8 1
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
P 1
33.3%
A 1
33.3%
T 1
33.3%
Space Separator
ValueCountFrequency (%)
118
100.0%
Other Punctuation
ValueCountFrequency (%)
, 25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 401
54.5%
Common 332
45.1%
Latin 3
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 41
 
10.2%
부 25
 
6.2%
광 24
 
6.0%
동 23
 
5.7%
산 23
 
5.7%
로 22
 
5.5%
시 22
 
5.5%
구 22
 
5.5%
역 21
 
5.2%
앙 19
 
4.7%
Other values (41) 159
39.7%
Common
ValueCountFrequency (%)
118
35.5%
1 26
 
7.8%
, 25
 
7.5%
4 23
 
6.9%
2 23
 
6.9%
( 21
 
6.3%
) 21
 
6.3%
3 16
 
4.8%
9 14
 
4.2%
0 13
 
3.9%
Other values (5) 32
 
9.6%
Latin
ValueCountFrequency (%)
P 1
33.3%
A 1
33.3%
T 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 401
54.5%
ASCII 335
45.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
118
35.2%
1 26
 
7.8%
, 25
 
7.5%
4 23
 
6.9%
2 23
 
6.9%
( 21
 
6.3%
) 21
 
6.3%
3 16
 
4.8%
9 14
 
4.2%
0 13
 
3.9%
Other values (8) 35
 
10.4%
Hangul
ValueCountFrequency (%)
중 41
 
10.2%
부 25
 
6.2%
광 24
 
6.0%
동 23
 
5.7%
산 23
 
5.7%
로 22
 
5.5%
시 22
 
5.5%
구 22
 
5.5%
역 21
 
5.2%
앙 19
 
4.7%
Other values (41) 159
39.7%

영업소전화번호
Text

MISSING 

Distinct16
Distinct (%)100.0%
Missing5
Missing (%)23.8%
Memory size300.0 B
2023-12-11T01:45:28.603424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.0625
Min length12

Characters and Unicode

Total characters193
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

Unique16 ?
Unique (%)100.0%

Sample

1st row051-242-8810
2nd row070-7576-0503
3rd row051-441-4414
4th row051-245-5529
5th row051-465-8548
ValueCountFrequency (%)
051-242-8810 1
 
6.2%
070-7576-0503 1
 
6.2%
051-441-4414 1
 
6.2%
051-245-5529 1
 
6.2%
051-465-8548 1
 
6.2%
051-986-0012 1
 
6.2%
051-951-2804 1
 
6.2%
051-468-0264 1
 
6.2%
051-203-2993 1
 
6.2%
051-413-4370 1
 
6.2%
Other values (6) 6
37.5%
2023-12-11T01:45:29.062056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 32
16.6%
0 30
15.5%
5 30
15.5%
1 24
12.4%
4 22
11.4%
2 13
6.7%
6 12
 
6.2%
8 9
 
4.7%
9 9
 
4.7%
3 7
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 161
83.4%
Dash Punctuation 32
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 30
18.6%
5 30
18.6%
1 24
14.9%
4 22
13.7%
2 13
8.1%
6 12
 
7.5%
8 9
 
5.6%
9 9
 
5.6%
3 7
 
4.3%
7 5
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 193
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 32
16.6%
0 30
15.5%
5 30
15.5%
1 24
12.4%
4 22
11.4%
2 13
6.7%
6 12
 
6.2%
8 9
 
4.7%
9 9
 
4.7%
3 7
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 193
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 32
16.6%
0 30
15.5%
5 30
15.5%
1 24
12.4%
4 22
11.4%
2 13
6.7%
6 12
 
6.2%
8 9
 
4.7%
9 9
 
4.7%
3 7
 
3.6%

팩스번호
Text

MISSING 

Distinct13
Distinct (%)86.7%
Missing6
Missing (%)28.6%
Memory size300.0 B
2023-12-11T01:45:29.298345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters180
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

Unique11 ?
Unique (%)73.3%

Sample

1st row051-248-8810
2nd row051-441-4883
3rd row051-245-7889
4th row051-465-8549
5th row051-986-0012
ValueCountFrequency (%)
051-441-4883 2
13.3%
051-465-5656 2
13.3%
051-248-8810 1
 
6.7%
051-245-7889 1
 
6.7%
051-465-8549 1
 
6.7%
051-986-0012 1
 
6.7%
051-951-2807 1
 
6.7%
051-468-0265 1
 
6.7%
051-206-2992 1
 
6.7%
051-416-4374 1
 
6.7%
Other values (3) 3
20.0%
2023-12-11T01:45:29.675420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 30
16.7%
5 29
16.1%
1 24
13.3%
0 23
12.8%
4 18
10.0%
6 15
8.3%
8 14
7.8%
2 10
 
5.6%
9 9
 
5.0%
3 4
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 150
83.3%
Dash Punctuation 30
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 29
19.3%
1 24
16.0%
0 23
15.3%
4 18
12.0%
6 15
10.0%
8 14
9.3%
2 10
 
6.7%
9 9
 
6.0%
3 4
 
2.7%
7 4
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 180
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 30
16.7%
5 29
16.1%
1 24
13.3%
0 23
12.8%
4 18
10.0%
6 15
8.3%
8 14
7.8%
2 10
 
5.6%
9 9
 
5.0%
3 4
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 180
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 30
16.7%
5 29
16.1%
1 24
13.3%
0 23
12.8%
4 18
10.0%
6 15
8.3%
8 14
7.8%
2 10
 
5.6%
9 9
 
5.0%
3 4
 
2.2%

Interactions

2023-12-11T01:45:26.022415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:45:29.826664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번소독업소명칭사무실소재지(도로명)영업소전화번호팩스번호
순번1.0001.0001.0001.0000.918
소독업소명칭1.0001.0001.0001.0001.000
사무실소재지(도로명)1.0001.0001.0001.0001.000
영업소전화번호1.0001.0001.0001.0001.000
팩스번호0.9181.0001.0001.0001.000

Missing values

2023-12-11T01:45:26.189653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:45:26.302466image/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.
2023-12-11T01:45:26.404775image/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

순번소독업소명칭사무실소재지(도로명)영업소전화번호팩스번호
01BUG Cleanse부산광역시 중구 중앙대로 80, 노블리안2 415호 (중앙동4가)<NA><NA>
12하이진코리아부산광역시 중구 충장대로9번길 23-2, 403호 (중앙동4가)051-242-8810051-248-8810
23엠더블유(MW)부산광역시 중구 중구로29번길 22, 301호, 302호 (부평동1가)<NA><NA>
34주식회사 수호코리아부산광역시 중구 중앙대로20번길 3, 401호, 405호 (중앙동6가)070-7576-0503<NA>
45제일산업부산광역시 중구 중앙대로116번길 7-1, 202호 (중앙동4가)051-441-4414051-441-4883
56벌레잡는 총각들부산광역시 중구 광복로39번길 37, 3층, 4층 일부호 (신창동2가)051-245-5529<NA>
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