Overview

Dataset statistics

Number of variables8
Number of observations51
Missing cells15
Missing cells (%)3.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 KiB
Average record size in memory68.6 B

Variable types

Numeric2
Text5
DateTime1

Dataset

Description전라북도 전주시 동물판매업소 현황입니다.
Author전라북도
URLhttps://www.bigdatahub.go.kr/index.jeonbuk?startPage=6&menuCd=DOM_000000103007001000&pListTypeStr=&pId=15053266

Alerts

데이터기준일자 has constant value ""Constant
소재지 지번주소 has 2 (3.9%) missing valuesMissing
소재지전화번호 has 13 (25.5%) missing valuesMissing
연번 has unique valuesUnique
사업장명칭 has unique valuesUnique
소재지주소(도로명) has unique valuesUnique
위도 has unique valuesUnique

Reproduction

Analysis started2024-03-14 01:00:24.190486
Analysis finished2024-03-14 01:00:25.266046
Duration1.08 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26
Minimum1
Maximum51
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size591.0 B
2024-03-14T10:00:25.348136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.5
Q113.5
median26
Q338.5
95-th percentile48.5
Maximum51
Range50
Interquartile range (IQR)25

Descriptive statistics

Standard deviation14.866069
Coefficient of variation (CV)0.57177187
Kurtosis-1.2
Mean26
Median Absolute Deviation (MAD)13
Skewness0
Sum1326
Variance221
MonotonicityStrictly increasing
2024-03-14T10:00:25.490161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
2.0%
2 1
 
2.0%
29 1
 
2.0%
30 1
 
2.0%
31 1
 
2.0%
32 1
 
2.0%
33 1
 
2.0%
34 1
 
2.0%
35 1
 
2.0%
36 1
 
2.0%
Other values (41) 41
80.4%
ValueCountFrequency (%)
1 1
2.0%
2 1
2.0%
3 1
2.0%
4 1
2.0%
5 1
2.0%
6 1
2.0%
7 1
2.0%
8 1
2.0%
9 1
2.0%
10 1
2.0%
ValueCountFrequency (%)
51 1
2.0%
50 1
2.0%
49 1
2.0%
48 1
2.0%
47 1
2.0%
46 1
2.0%
45 1
2.0%
44 1
2.0%
43 1
2.0%
42 1
2.0%

사업장명칭
Text

UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
2024-03-14T10:00:25.688822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length8
Mean length5.6470588
Min length2

Characters and Unicode

Total characters288
Distinct characters126
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

Unique51 ?
Unique (%)100.0%

Sample

1st row다사랑애견
2nd row애견나라
3rd row완산애견
4th row하나애견샵
5th row벤지애견
ValueCountFrequency (%)
헬로펫 3
 
4.8%
탤렌트 2
 
3.2%
펫샵 2
 
3.2%
애견용품 2
 
3.2%
할인마트 2
 
3.2%
애견샵 2
 
3.2%
다사랑애견 1
 
1.6%
애니몰하우스 1
 
1.6%
현이펫 1
 
1.6%
제임스독 1
 
1.6%
Other values (45) 45
72.6%
2024-03-14T10:00:26.002085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21
 
7.3%
20
 
6.9%
11
 
3.8%
11
 
3.8%
9
 
3.1%
9
 
3.1%
9
 
3.1%
8
 
2.8%
6
 
2.1%
6
 
2.1%
Other values (116) 178
61.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 264
91.7%
Space Separator 11
 
3.8%
Lowercase Letter 6
 
2.1%
Decimal Number 3
 
1.0%
Modifier Symbol 1
 
0.3%
Uppercase Letter 1
 
0.3%
Close Punctuation 1
 
0.3%
Open Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
21
 
8.0%
20
 
7.6%
11
 
4.2%
9
 
3.4%
9
 
3.4%
9
 
3.4%
8
 
3.0%
6
 
2.3%
6
 
2.3%
4
 
1.5%
Other values (102) 161
61.0%
Lowercase Letter
ValueCountFrequency (%)
s 1
16.7%
m 1
16.7%
i 1
16.7%
t 1
16.7%
e 1
16.7%
p 1
16.7%
Decimal Number
ValueCountFrequency (%)
5 1
33.3%
6 1
33.3%
3 1
33.3%
Space Separator
ValueCountFrequency (%)
11
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
L 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 264
91.7%
Common 17
 
5.9%
Latin 7
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
21
 
8.0%
20
 
7.6%
11
 
4.2%
9
 
3.4%
9
 
3.4%
9
 
3.4%
8
 
3.0%
6
 
2.3%
6
 
2.3%
4
 
1.5%
Other values (102) 161
61.0%
Common
ValueCountFrequency (%)
11
64.7%
` 1
 
5.9%
5 1
 
5.9%
6 1
 
5.9%
3 1
 
5.9%
) 1
 
5.9%
( 1
 
5.9%
Latin
ValueCountFrequency (%)
s 1
14.3%
m 1
14.3%
i 1
14.3%
L 1
14.3%
t 1
14.3%
e 1
14.3%
p 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 264
91.7%
ASCII 24
 
8.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
21
 
8.0%
20
 
7.6%
11
 
4.2%
9
 
3.4%
9
 
3.4%
9
 
3.4%
8
 
3.0%
6
 
2.3%
6
 
2.3%
4
 
1.5%
Other values (102) 161
61.0%
ASCII
ValueCountFrequency (%)
11
45.8%
s 1
 
4.2%
` 1
 
4.2%
m 1
 
4.2%
i 1
 
4.2%
L 1
 
4.2%
t 1
 
4.2%
5 1
 
4.2%
6 1
 
4.2%
3 1
 
4.2%
Other values (4) 4
 
16.7%
Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
2024-03-14T10:00:26.289952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length29
Mean length25.843137
Min length21

Characters and Unicode

Total characters1318
Distinct characters52
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

Unique51 ?
Unique (%)100.0%

Sample

1st row전라북도 전주시 완산구 평화동1가 709-1
2nd row전라북도 전주시 완산구 중노송동 498-22
3rd row전라북도 전주시 완산구 서완산동2가 360-19
4th row전라북도 전주시 덕진구 덕진동2가 167-156번지
5th row전라북도 전주시 완산구 경원동3가 201
ValueCountFrequency (%)
전라북도 51
19.6%
전주시 51
19.6%
완산구 35
13.5%
덕진구 16
 
6.2%
효자동1가 6
 
2.3%
송천동1가 6
 
2.3%
서신동 6
 
2.3%
평화동1가 4
 
1.5%
중노송동 4
 
1.5%
효자동3가 3
 
1.2%
Other values (71) 78
30.0%
2024-03-14T10:00:26.622206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
248
18.8%
102
 
7.7%
1 59
 
4.5%
51
 
3.9%
51
 
3.9%
51
 
3.9%
51
 
3.9%
51
 
3.9%
51
 
3.9%
50
 
3.8%
Other values (42) 553
42.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 768
58.3%
Decimal Number 258
 
19.6%
Space Separator 248
 
18.8%
Dash Punctuation 44
 
3.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
102
13.3%
51
 
6.6%
51
 
6.6%
51
 
6.6%
51
 
6.6%
51
 
6.6%
51
 
6.6%
50
 
6.5%
39
 
5.1%
39
 
5.1%
Other values (30) 232
30.2%
Decimal Number
ValueCountFrequency (%)
1 59
22.9%
2 33
12.8%
3 32
12.4%
8 23
 
8.9%
7 23
 
8.9%
6 22
 
8.5%
4 20
 
7.8%
5 19
 
7.4%
9 15
 
5.8%
0 12
 
4.7%
Space Separator
ValueCountFrequency (%)
248
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 44
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 768
58.3%
Common 550
41.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
102
13.3%
51
 
6.6%
51
 
6.6%
51
 
6.6%
51
 
6.6%
51
 
6.6%
51
 
6.6%
50
 
6.5%
39
 
5.1%
39
 
5.1%
Other values (30) 232
30.2%
Common
ValueCountFrequency (%)
248
45.1%
1 59
 
10.7%
- 44
 
8.0%
2 33
 
6.0%
3 32
 
5.8%
8 23
 
4.2%
7 23
 
4.2%
6 22
 
4.0%
4 20
 
3.6%
5 19
 
3.5%
Other values (2) 27
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 768
58.3%
ASCII 550
41.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
248
45.1%
1 59
 
10.7%
- 44
 
8.0%
2 33
 
6.0%
3 32
 
5.8%
8 23
 
4.2%
7 23
 
4.2%
6 22
 
4.0%
4 20
 
3.6%
5 19
 
3.5%
Other values (2) 27
 
4.9%
Hangul
ValueCountFrequency (%)
102
13.3%
51
 
6.6%
51
 
6.6%
51
 
6.6%
51
 
6.6%
51
 
6.6%
51
 
6.6%
50
 
6.5%
39
 
5.1%
39
 
5.1%
Other values (30) 232
30.2%
Distinct48
Distinct (%)98.0%
Missing2
Missing (%)3.9%
Memory size540.0 B
2024-03-14T10:00:26.844861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length34
Mean length29.122449
Min length25

Characters and Unicode

Total characters1427
Distinct characters105
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

Unique47 ?
Unique (%)95.9%

Sample

1st row전라북도 전주시 완산구 장승배기로 194 (평화동1가)
2nd row전라북도 전주시 완산구 기린대로 165 (중노송동)
3rd row전라북도 전주시 완산구 용머리로 203 (서완산동2가)
4th row전라북도 전주시 덕진구 송천중앙로 17 (덕진동2가)
5th row전라북도 전주시 완산구 서곡로 69 (효자동3가)
ValueCountFrequency (%)
전주시 49
16.3%
전라북도 48
 
16.0%
완산구 34
 
11.3%
덕진구 15
 
5.0%
기린대로 6
 
2.0%
서신동 6
 
2.0%
송천동1가 6
 
2.0%
송천중앙로 6
 
2.0%
거마평로 5
 
1.7%
효자동1가 5
 
1.7%
Other values (93) 120
40.0%
2024-03-14T10:00:27.194422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
251
 
17.6%
99
 
6.9%
1 54
 
3.8%
52
 
3.6%
49
 
3.4%
49
 
3.4%
49
 
3.4%
) 49
 
3.4%
( 49
 
3.4%
48
 
3.4%
Other values (95) 678
47.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 890
62.4%
Space Separator 251
 
17.6%
Decimal Number 172
 
12.1%
Close Punctuation 49
 
3.4%
Open Punctuation 49
 
3.4%
Other Punctuation 10
 
0.7%
Dash Punctuation 4
 
0.3%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
99
 
11.1%
52
 
5.8%
49
 
5.5%
49
 
5.5%
49
 
5.5%
48
 
5.4%
48
 
5.4%
48
 
5.4%
46
 
5.2%
40
 
4.5%
Other values (77) 362
40.7%
Decimal Number
ValueCountFrequency (%)
1 54
31.4%
3 25
14.5%
2 22
12.8%
7 12
 
7.0%
4 12
 
7.0%
0 11
 
6.4%
9 10
 
5.8%
5 9
 
5.2%
6 9
 
5.2%
8 8
 
4.7%
Other Punctuation
ValueCountFrequency (%)
, 9
90.0%
' 1
 
10.0%
Uppercase Letter
ValueCountFrequency (%)
S 1
50.0%
C 1
50.0%
Space Separator
ValueCountFrequency (%)
251
100.0%
Close Punctuation
ValueCountFrequency (%)
) 49
100.0%
Open Punctuation
ValueCountFrequency (%)
( 49
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 890
62.4%
Common 535
37.5%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
99
 
11.1%
52
 
5.8%
49
 
5.5%
49
 
5.5%
49
 
5.5%
48
 
5.4%
48
 
5.4%
48
 
5.4%
46
 
5.2%
40
 
4.5%
Other values (77) 362
40.7%
Common
ValueCountFrequency (%)
251
46.9%
1 54
 
10.1%
) 49
 
9.2%
( 49
 
9.2%
3 25
 
4.7%
2 22
 
4.1%
7 12
 
2.2%
4 12
 
2.2%
0 11
 
2.1%
9 10
 
1.9%
Other values (6) 40
 
7.5%
Latin
ValueCountFrequency (%)
S 1
50.0%
C 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 890
62.4%
ASCII 537
37.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
251
46.7%
1 54
 
10.1%
) 49
 
9.1%
( 49
 
9.1%
3 25
 
4.7%
2 22
 
4.1%
7 12
 
2.2%
4 12
 
2.2%
0 11
 
2.0%
9 10
 
1.9%
Other values (8) 42
 
7.8%
Hangul
ValueCountFrequency (%)
99
 
11.1%
52
 
5.8%
49
 
5.5%
49
 
5.5%
49
 
5.5%
48
 
5.4%
48
 
5.4%
48
 
5.4%
46
 
5.2%
40
 
4.5%
Other values (77) 362
40.7%

위도
Text

UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
2024-03-14T10:00:27.411075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/