Overview

Dataset statistics

Number of variables7
Number of observations50
Missing cells1
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 KiB
Average record size in memory61.6 B

Variable types

Numeric3
Text3
Categorical1

Dataset

Description전라북도 전주시 내 동물병원을 제공하며 동물병원명, 인허가일자, 영업상태명 등을 제공합니다.
Author전라북도
URLhttps://www.bigdatahub.go.kr/index.jeonbuk?startPage=3&menuCd=DOM_000000103007001000&pListTypeStr=&pId=15053269

Alerts

데이터기준일자 has constant value ""Constant
소재지전화번호 has 1 (2.0%) missing valuesMissing
연번 has unique valuesUnique
대행업소명 has unique valuesUnique
소재지도로명주소 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2024-03-14 00:11:48.571581
Analysis finished2024-03-14 00:11:49.605865
Duration1.03 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.5
Minimum1
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-14T09:11:49.675259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.45
Q113.25
median25.5
Q337.75
95-th percentile47.55
Maximum50
Range49
Interquartile range (IQR)24.5

Descriptive statistics

Standard deviation14.57738
Coefficient of variation (CV)0.57166195
Kurtosis-1.2
Mean25.5
Median Absolute Deviation (MAD)12.5
Skewness0
Sum1275
Variance212.5
MonotonicityStrictly increasing
2024-03-14T09:11:49.791223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
2.0%
39 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 (40) 40
80.0%
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 (%)
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%
41 1
2.0%

대행업소명
Text

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2024-03-14T09:11:49.967994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length7.32
Min length5

Characters and Unicode

Total characters366
Distinct characters98
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)100.0%

Sample

1st row홍 동물병원
2nd row초원 동물병원
3rd row푸른 동물병원
4th row박영재 동물병원
5th row아리랑 동물병원
ValueCountFrequency (%)
동물병원 24
31.2%
홍 1
 
1.3%
하트동물병원 1
 
1.3%
웰동물병원 1
 
1.3%
하루동물병원 1
 
1.3%
대영동물병원 1
 
1.3%
펫동물병원 1
 
1.3%
아프리카 1
 
1.3%
힐링동물병원 1
 
1.3%
전주동물병원 1
 
1.3%
Other values (44) 44
57.1%
2024-03-14T09:11:50.300409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 49
 
13.4%
물 48
 
13.1%
원 45
 
12.3%
병 44
 
12.0%
29
 
7.9%
리 6
 
1.6%
이 5
 
1.4%
터 5
 
1.4%
스 5
 
1.4%
펫 4
 
1.1%
Other values (88) 126
34.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 331
90.4%
Space Separator 29
 
7.9%
Decimal Number 6
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 49
14.8%
물 48
14.5%
원 45
 
13.6%
병 44
 
13.3%
리 6
 
1.8%
이 5
 
1.5%
터 5
 
1.5%
스 5
 
1.5%
펫 4
 
1.2%
하 4
 
1.2%
Other values (84) 116
35.0%
Decimal Number
ValueCountFrequency (%)
2 3
50.0%
4 2
33.3%
1 1
 
16.7%
Space Separator
ValueCountFrequency (%)
29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 331
90.4%
Common 35
 
9.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 49
14.8%
물 48
14.5%
원 45
 
13.6%
병 44
 
13.3%
리 6
 
1.8%
이 5
 
1.5%
터 5
 
1.5%
스 5
 
1.5%
펫 4
 
1.2%
하 4
 
1.2%
Other values (84) 116
35.0%
Common
ValueCountFrequency (%)
29
82.9%
2 3
 
8.6%
4 2
 
5.7%
1 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 331
90.4%
ASCII 35
 
9.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 49
14.8%
물 48
14.5%
원 45
 
13.6%
병 44
 
13.3%
리 6
 
1.8%
이 5
 
1.5%
터 5
 
1.5%
스 5
 
1.5%
펫 4
 
1.2%
하 4
 
1.2%
Other values (84) 116
35.0%
ASCII
ValueCountFrequency (%)
29
82.9%
2 3
 
8.6%
4 2
 
5.7%
1 1
 
2.9%

소재지도로명주소
Text

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2024-03-14T09:11:50.534733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length22.5
Mean length19.42
Min length15

Characters and Unicode

Total characters971
Distinct characters93
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

Unique50 ?
Unique (%)100.0%

Sample

1st row완산구 팔달로 99-2 (전동)
2nd row완산구 팔달로 286-11 (서노송동)
3rd row덕진구 쪽구름로 71-2 (반월동)
4th row완산구 전주천서로 111 (서서학동)
5th row완산구 서원로 294 (중화산동2가)
ValueCountFrequency (%)
완산구 27
 
13.6%
덕진구 23
 
11.6%
인후동1가 5
 
2.5%
송천동1가 5
 
2.5%
서신동 5
 
2.5%
백제대로 4
 
2.0%
서원로 3
 
1.5%
효자동2가 3
 
1.5%
견훤로 3
 
1.5%
송천중앙로 3
 
1.5%
Other values (95) 118
59.3%
2024-03-14T09:11:50.859094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
149
 
15.3%
1 54
 
5.6%
동 54
 
5.6%
구 53
 
5.5%
( 50
 
5.1%
) 50
 
5.1%
로 46
 
4.7%
가 36
 
3.7%
2 36
 
3.7%
산 36
 
3.7%
Other values (83) 407
41.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 530
54.6%
Decimal Number 184
 
18.9%
Space Separator 149
 
15.3%
Open Punctuation 50
 
5.1%
Close Punctuation 50
 
5.1%
Dash Punctuation 6
 
0.6%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 54
 
10.2%
구 53
 
10.0%
로 46
 
8.7%
가 36
 
6.8%
산 36
 
6.8%
덕 27
 
5.1%
완 27
 
5.1%
진 26
 
4.9%
서 15
 
2.8%
천 13
 
2.5%
Other values (68) 197
37.2%
Decimal Number
ValueCountFrequency (%)
1 54
29.3%
2 36
19.6%
3 16
 
8.7%
6 15
 
8.2%
7 13
 
7.1%
8 12
 
6.5%
9 12
 
6.5%
4 12
 
6.5%
0 9
 
4.9%
5 5
 
2.7%
Space Separator
ValueCountFrequency (%)
149
100.0%
Open Punctuation
ValueCountFrequency (%)
( 50
100.0%
Close Punctuation
ValueCountFrequency (%)
) 50
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 530
54.6%
Common 441
45.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 54
 
10.2%
구 53
 
10.0%
로 46
 
8.7%
가 36
 
6.8%
산 36
 
6.8%
덕 27
 
5.1%
완 27
 
5.1%
진 26
 
4.9%
서 15
 
2.8%
천 13
 
2.5%
Other values (68) 197
37.2%
Common
ValueCountFrequency (%)
149
33.8%
1 54
 
12.2%
( 50
 
11.3%
) 50
 
11.3%
2 36
 
8.2%
3 16
 
3.6%
6 15
 
3.4%
7 13
 
2.9%
8 12
 
2.7%
9 12
 
2.7%
Other values (5) 34
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 530
54.6%
ASCII 441
45.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
149
33.8%
1 54
 
12.2%
( 50
 
11.3%
) 50
 
11.3%
2 36
 
8.2%
3 16
 
3.6%
6 15
 
3.4%
7 13
 
2.9%
8 12
 
2.7%
9 12
 
2.7%
Other values (5) 34
 
7.7%
Hangul
ValueCountFrequency (%)
동 54
 
10.2%
구 53
 
10.0%
로 46
 
8.7%
가 36
 
6.8%
산 36
 
6.8%
덕 27
 
5.1%
완 27
 
5.1%
진 26
 
4.9%
서 15
 
2.8%
천 13
 
2.5%
Other values (68) 197
37.2%

소재지전화번호
Text

MISSING 

Distinct48
Distinct (%)98.0%
Missing1
Missing (%)2.0%
Memory size532.0 B
2024-03-14T09:11:51.054744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.938776
Min length9

Characters and Unicode

Total characters585
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

Unique47 ?
Unique (%)95.9%

Sample

1st row063-284-6520
2nd row063-254-3266
3rd row063-284-9491
4th row063-284-7774
5th row063-223-5311
ValueCountFrequency (%)
063-902-7975 2
 
4.1%
063-254-3266 1
 
2.0%
063-227-8275 1
 
2.0%
063-243-3200 1
 
2.0%
063-246-7155 1
 
2.0%
063-221-7582 1
 
2.0%
063-247-8874 1
 
2.0%
063-272-8575 1
 
2.0%
063-255-0630 1
 
2.0%
063-275-7553 1
 
2.0%
Other values (38) 38
77.6%
2024-03-14T09:11:51.360473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 97
16.6%
2 81
13.8%
0 73
12.5%
6 72
12.3%
3 70
12.0%
7 62
10.6%
5 45
7.7%
4 28
 
4.8%
8 21
 
3.6%
9 20
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 488
83.4%
Dash Punctuation 97
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 81
16.6%
0 73
15.0%
6 72
14.8%
3 70
14.3%
7 62
12.7%
5 45
9.2%
4 28
 
5.7%
8 21
 
4.3%
9 20
 
4.1%
1 16
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 97
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 585
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 97
16.6%
2 81
13.8%
0 73
12.5%
6 72
12.3%
3 70
12.0%
7 62
10.6%
5 45
7.7%
4 28
 
4.8%
8 21
 
3.6%
9 20
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 585
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 97
16.6%
2 81
13.8%
0 73
12.5%
6 72
12.3%
3 70
12.0%
7 62
10.6%
5 45
7.7%
4 28
 
4.8%
8 21
 
3.6%
9 20
 
3.4%

위도
Real number (ℝ)

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.829762
Minimum35.788506
Maximum35.874088
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-14T09:11:51.782941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.788506
5-th percentile35.795314
Q135.811744
median35.828202
Q335.844285
95-th percentile35.869258
Maximum35.874088
Range0.085582
Interquartile range (IQR)0.0325415

Descriptive statistics

Standard deviation0.023671441
Coefficient of variation (CV)0.00066066422
Kurtosis-0.86428249
Mean35.829762
Median Absolute Deviation (MAD)0.0166765
Skewness0.27188658
Sum1791.4881
Variance0.00056033714
MonotonicityNot monotonic
2024-03-14T09:11:51.889111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.811473 1
 
2.0%
35.874088 1
 
2.0%
35.807696 1
 
2.0%
35.825511 1
 
2.0%
35.862772 1
 
2.0%
35.832154 1
 
2.0%
35.834122 1
 
2.0%
35.817696 1
 
2.0%
35.795037 1
 
2.0%
35.807712 1
 
2.0%
Other values (40) 40
80.0%
ValueCountFrequency (%)
35.788506 1
2.0%
35.789173 1
2.0%
35.795037 1
2.0%
35.795652 1
2.0%
35.799965 1
2.0%
35.801348 1
2.0%
35.803737 1
2.0%
35.806139 1
2.0%
35.807696 1
2.0%
35.807712 1
2.0%
ValueCountFrequency (%)
35.874088 1
2.0%
35.873501 1
2.0%
35.871762 1
2.0%
35.866198 1
2.0%
35.865166 1
2.0%
35.8648 1
2.0%
35.862772 1
2.0%
35.861518 1
2.0%
35.858605 1
2.0%
35.856633 1
2.0%

경도
Real number (ℝ)

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.12682
Minimum127.06116
Maximum127.16718
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-14T09:11:52.014863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.06116
5-th percentile127.07617
Q1127.11649
median127.12369
Q3127.1456
95-th percentile127.16087
Maximum127.16718
Range0.106026
Interquartile range (IQR)0.0291025

Descriptive statistics

Standard deviation0.023638751
Coefficient of variation (CV)0.00018594622
Kurtosis0.59911417
Mean127.12682
Median Absolute Deviation (MAD)0.011433
Skewness-0.61520339
Sum6356.3408
Variance0.00055879054
MonotonicityNot monotonic
2024-03-14T09:11:52.150602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.149248 1
 
2.0%
127.076178 1
 
2.0%
127.116758 1
 
2.0%
127.165301 1
 
2.0%
127.121241 1
 
2.0%
127.10284 1
 
2.0%
127.111728 1
 
2.0%
127.102759 1
 
2.0%
127.132154 1
 
2.0%
127.116404 1
 
2.0%
Other values (40) 40
80.0%
ValueCountFrequency (%)
127.061156 1
2.0%
127.075473 1
2.0%
127.076161 1
2.0%
127.076178 1
2.0%
127.102366 1
2.0%
127.102759 1
2.0%
127.10284 1
2.0%
127.111728 1
2.0%
127.112779 1
2.0%
127.112886 1
2.0%
ValueCountFrequency (%)
127.167182 1
2.0%
127.165301 1
2.0%
127.163598 1
2.0%
127.157532 1
2.0%
127.15635 1
2.0%
127.155078 1
2.0%
127.153596 1
2.0%
127.153047 1
2.0%
127.15209 1
2.0%
127.149248 1
2.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2019-08-30
50 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019-08-30
2nd row2019-08-30
3rd row2019-08-30
4th row2019-08-30
5th row2019-08-30

Common Values

ValueCountFrequency (%)
2019-08-30 50
100.0%

Length

2024-03-14T09:11:52.246695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:11:52.337864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019-08-30 50
100.0%

Interactions

2024-03-14T09:11:49.165823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:11:48.808414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:11:49.001042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:11:49.230820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:11:48.866244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:11:49.055853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:11:49.292346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:11:48.928389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:11:49.108847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T09:11:52.395903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번대행업소명소재지도로명주소소재지전화번호위도경도
연번1.0001.0001.0000.9170.3640.408
대행업소명1.0001.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.0001.000
소재지전화번호0.9171.0001.0001.0000.8910.975
위도0.3641.0001.0000.8911.0000.652
경도0.4081.0001.0000.9750.6521.000
2024-03-14T09:11:52.500282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도
연번1.0000.154-0.362
위도0.1541.000-0.080
경도-0.362-0.0801.000

Missing values

2024-03-14T09:11:49.435974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T09:11:49.569830image/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

연번대행업소명소재지도로명주소소재지전화번호위도경도데이터기준일자
01홍 동물병원완산구 팔달로 99-2 (전동)063-284-652035.811473127.1492482019-08-30
12초원 동물병원완산구 팔달로 286-11 (서노송동)063-254-326635.828058127.1429952019-08-30
23푸른 동물병원덕진구 쪽구름로 71-2 (반월동)063-284-949135.871762127.0761612019-08-30
34박영재 동물병원완산구 전주천서로 111 (서서학동)063-284-777435.810075127.1491742019-08-30
45아리랑 동물병원완산구 서원로 294 (중화산동2가)063-223-531135.811553127.1264752019-08-30
56효자 동물병원완산구 백제대로 121 (효자동1가)063-224-667235.803737127.123752019-08-30
67우리동물병원완산구 용머리로 86 (효자동1가)063-226-333335.806139127.1194312019-08-30
78서신 동물병원완산구 서신로 33 (서신동)063-253-274735.828346127.1155892019-08-30
89동부 동물병원완산구 기린대로 139 (경원동3가)063-231-245635.820966127.152092019-08-30
910전주김제완주축협덕진구 동부대로 769 (호성동1가)063-240-288835.856633127.156352019-08-30
연번대행업소명소재지도로명주소소재지전화번호위도경도데이터기준일자
4041동물치유쉼터덕진구 소리로 68(덕진동1가, 전주동물원)063-281-674035.8561127.1446532019-08-30
4142맘편한동물의료센터완산구 유연로 289 (서신동)063-252-250835.825743127.11712019-08-30
4243혁신동물병원덕진구 기지로 72 (중동)063-229-533335.838644127.0611562019-08-30
4344스마일동물병원덕진구 천마산로 65(송천동2가)063-273-120235.865166127.1282622019-08-30
444524시 올리몰스덕진구 송천중앙로 213 (송천동1가)063-275-797935.866198127.1211372019-08-30
4546더펫 동물병원덕진구 한배미1길 61 (인후동1가)063-247-756635.813536127.1127792019-08-30
4647더펫동물병원완산구 서원로 168 (효자동2가)1599-876435.813606127.1128862019-08-30
4748코끼리동물병원완산구 중화산로 100 (중화산동2가)063-902-797535.819404127.1183092019-08-30
4849하루동물병원완산구 모악로 4692 (평화동2가)063-232-590035.788506127.1309332019-08-30
4950사랑플러스 동물병원덕진구 쪽구름2길 3 (반월동)<NA>35.873501127.0754732019-08-30