Overview

Dataset statistics

Number of variables6
Number of observations26
Missing cells16
Missing cells (%)10.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 KiB
Average record size in memory55.1 B

Variable types

Text3
Numeric2
DateTime1

Dataset

Description경상북도 김천시 관내 반려동물 미용업체(업소명, 소재지, 전화번호)에 대한 안내 및 정보를 제공하고자 이자료를 공공데이터 시스템에 업로드 합니다
Author경상북도 김천시
URLhttps://www.data.go.kr/data/15127085/fileData.do

Alerts

데이터기준일 has constant value ""Constant
전화번호 has 16 (61.5%) missing valuesMissing
업소명 has unique valuesUnique

Reproduction

Analysis started2024-03-16 04:16:56.900755
Analysis finished2024-03-16 04:16:58.112723
Duration1.21 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2024-03-16T13:16:58.308441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length8
Mean length5.6153846
Min length2

Characters and Unicode

Total characters146
Distinct characters88
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)100.0%

Sample

1st row가야동물병원
2nd row강아지살롱
3rd row개편하개
4th row꼬리치는 강아지
5th row도그샵
ValueCountFrequency (%)
가야동물병원 1
 
2.9%
팜 1
 
2.9%
베이비독 1
 
2.9%
복똥이강아지 1
 
2.9%
뽀송하개 1
 
2.9%
애견샾 1
 
2.9%
애견미용실 1
 
2.9%
우정 1
 
2.9%
크리닉 1
 
2.9%
강아지살롱 1
 
2.9%
Other values (24) 24
70.6%
2024-03-16T13:16:58.847580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8
 
5.5%
개 6
 
4.1%
아 5
 
3.4%
견 4
 
2.7%
지 4
 
2.7%
멍 4
 
2.7%
강 3
 
2.1%
용 3
 
2.1%
애 3
 
2.1%
독 3
 
2.1%
Other values (78) 103
70.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 122
83.6%
Lowercase Letter 11
 
7.5%
Space Separator 8
 
5.5%
Uppercase Letter 2
 
1.4%
Open Punctuation 1
 
0.7%
Close Punctuation 1
 
0.7%
Other Punctuation 1
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
개 6
 
4.9%
아 5
 
4.1%
견 4
 
3.3%
지 4
 
3.3%
멍 4
 
3.3%
강 3
 
2.5%
용 3
 
2.5%
애 3
 
2.5%
독 3
 
2.5%
이 3
 
2.5%
Other values (63) 84
68.9%
Lowercase Letter
ValueCountFrequency (%)
e 2
18.2%
f 2
18.2%
a 1
9.1%
r 1
9.1%
k 1
9.1%
i 1
9.1%
n 1
9.1%
g 1
9.1%
o 1
9.1%
Uppercase Letter
ValueCountFrequency (%)
M 1
50.0%
C 1
50.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 122
83.6%
Latin 13
 
8.9%
Common 11
 
7.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
개 6
 
4.9%
아 5
 
4.1%
견 4
 
3.3%
지 4
 
3.3%
멍 4
 
3.3%
강 3
 
2.5%
용 3
 
2.5%
애 3
 
2.5%
독 3
 
2.5%
이 3
 
2.5%
Other values (63) 84
68.9%
Latin
ValueCountFrequency (%)
e 2
15.4%
f 2
15.4%
M 1
7.7%
a 1
7.7%
r 1
7.7%
k 1
7.7%
i 1
7.7%
n 1
7.7%
g 1
7.7%
C 1
7.7%
Common
ValueCountFrequency (%)
8
72.7%
( 1
 
9.1%
) 1
 
9.1%
, 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 122
83.6%
ASCII 24
 
16.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8
33.3%
e 2
 
8.3%
f 2
 
8.3%
( 1
 
4.2%
M 1
 
4.2%
a 1
 
4.2%
r 1
 
4.2%
k 1
 
4.2%
i 1
 
4.2%
n 1
 
4.2%
Other values (5) 5
20.8%
Hangul
ValueCountFrequency (%)
개 6
 
4.9%
아 5
 
4.1%
견 4
 
3.3%
지 4
 
3.3%
멍 4
 
3.3%
강 3
 
2.5%
용 3
 
2.5%
애 3
 
2.5%
독 3
 
2.5%
이 3
 
2.5%
Other values (63) 84
68.9%

사업장소재지(도로명)
Text

Distinct25
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Memory size340.0 B
2024-03-16T13:16:59.096999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length25
Mean length20.038462
Min length16

Characters and Unicode

Total characters521
Distinct characters55
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

Unique24 ?
Unique (%)92.3%

Sample

1st row경상북도 김천시 남산동 12-3
2nd row경상북도 김천시 신음동 776-3
3rd row경상북도 김천시 교동 640-6
4th row경상북도 김천시 부곡동 364-10
5th row경상북도 김천시 평화동 147-14
ValueCountFrequency (%)
경상북도 26
23.2%
김천시 26
23.2%
율곡동 7
 
6.2%
평화동 5
 
4.5%
신음동 4
 
3.6%
부곡동 4
 
3.6%
245-19 2
 
1.8%
아포읍 2
 
1.8%
792-4 1
 
0.9%
1285-6 1
 
0.9%
Other values (34) 34
30.4%
2024-03-16T13:16:59.666511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
111
21.3%
천 28
 
5.4%
상 27
 
5.2%
시 27
 
5.2%
도 27
 
5.2%
김 27
 
5.2%
경 26
 
5.0%
북 26
 
5.0%
동 23
 
4.4%
1 20
 
3.8%
Other values (45) 179
34.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 289
55.5%
Space Separator 111
 
21.3%
Decimal Number 104
 
20.0%
Dash Punctuation 17
 
3.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 28
9.7%
상 27
9.3%
시 27
9.3%
도 27
9.3%
김 27
9.3%
경 26
9.0%
북 26
9.0%
동 23
 
8.0%
곡 13
 
4.5%
율 7
 
2.4%
Other values (33) 58
20.1%
Decimal Number
ValueCountFrequency (%)
1 20
19.2%
4 13
12.5%
7 12
11.5%
3 12
11.5%
2 11
10.6%
9 11
10.6%
6 10
9.6%
8 6
 
5.8%
5 5
 
4.8%
0 4
 
3.8%
Space Separator
ValueCountFrequency (%)
111
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 289
55.5%
Common 232
44.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 28
9.7%
상 27
9.3%
시 27
9.3%
도 27
9.3%
김 27
9.3%
경 26
9.0%
북 26
9.0%
동 23
 
8.0%
곡 13
 
4.5%
율 7
 
2.4%
Other values (33) 58
20.1%
Common
ValueCountFrequency (%)
111
47.8%
1 20
 
8.6%
- 17
 
7.3%
4 13
 
5.6%
7 12
 
5.2%
3 12
 
5.2%
2 11
 
4.7%
9 11
 
4.7%
6 10
 
4.3%
8 6
 
2.6%
Other values (2) 9
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 289
55.5%
ASCII 232
44.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
111
47.8%
1 20
 
8.6%
- 17
 
7.3%
4 13
 
5.6%
7 12
 
5.2%
3 12
 
5.2%
2 11
 
4.7%
9 11
 
4.7%
6 10
 
4.3%
8 6
 
2.6%
Other values (2) 9
 
3.9%
Hangul
ValueCountFrequency (%)
천 28
9.7%
상 27
9.3%
시 27
9.3%
도 27
9.3%
김 27
9.3%
경 26
9.0%
북 26
9.0%
동 23
 
8.0%
곡 13
 
4.5%
율 7
 
2.4%
Other values (33) 58
20.1%

위도
Real number (ℝ)

Distinct25
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.127022
Minimum36.104011
Maximum36.158515
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2024-03-16T13:16:59.850851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.104011
5-th percentile36.11545
Q136.122038
median36.124651
Q336.129983
95-th percentile36.152383
Maximum36.158515
Range0.05450405
Interquartile range (IQR)0.007945305

Descriptive statistics

Standard deviation0.011400617
Coefficient of variation (CV)0.00031557035
Kurtosis3.0182735
Mean36.127022
Median Absolute Deviation (MAD)0.003009945
Skewness1.3010859
Sum939.30257
Variance0.00012997407
MonotonicityNot monotonic
2024-03-16T13:17:00.091377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
36.12576307 2
 
7.7%
36.11939907 1
 
3.8%
36.13890709 1
 
3.8%
36.10401105 1
 
3.8%
36.11959213 1
 
3.8%
36.15687509 1
 
3.8%
36.13619436 1
 
3.8%
36.13382 1
 
3.8%
36.125955 1
 
3.8%
36.12420908 1
 
3.8%
Other values (15) 15
57.7%
ValueCountFrequency (%)
36.10401105 1
3.8%
36.11496759 1
3.8%
36.11689698 1
3.8%
36.11939907 1
3.8%
36.11959213 1
3.8%
36.12141204 1
3.8%
36.12186909 1
3.8%
36.12254287 1
3.8%
36.12316508 1
3.8%
36.12325158 1
3.8%
ValueCountFrequency (%)
36.1585151 1
3.8%
36.15687509 1
3.8%
36.13890709 1
3.8%
36.13619436 1
3.8%
36.13382 1
3.8%
36.13344497 1
3.8%
36.13108214 1
3.8%
36.12668494 1
3.8%
36.125955 1
3.8%
36.12576307 2
7.7%

경도
Real number (ℝ)

Distinct25
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.14545
Minimum128.093
Maximum128.26923
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2024-03-16T13:17:00.297836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.093
5-th percentile128.09491
Q1128.11096
median128.1192
Q3128.18029
95-th percentile128.24475
Maximum128.26923
Range0.1762279
Interquartile range (IQR)0.06932735

Descriptive statistics

Standard deviation0.049112033
Coefficient of variation (CV)0.00038325226
Kurtosis0.69401607
Mean128.14545
Median Absolute Deviation (MAD)0.02392765
Skewness1.1057293
Sum3331.7817
Variance0.0024119917
MonotonicityNot monotonic
2024-03-16T13:17:00.524966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
128.1109634 2
 
7.7%
128.1210077 1
 
3.8%
128.1170934 1
 
3.8%
128.1740288 1
 
3.8%
128.1756631 1
 
3.8%
128.2692268 1
 
3.8%
128.1169227 1
 
3.8%
128.1208523 1
 
3.8%
128.1175406 1
 
3.8%
128.0945526 1
 
3.8%
Other values (15) 15
57.7%
ValueCountFrequency (%)
128.0929989 1
3.8%
128.0945526 1
3.8%
128.095985 1
3.8%
128.0992384 1
3.8%
128.1056743 1
3.8%
128.1082095 1
3.8%
128.1109634 2
7.7%
128.1133371 1
3.8%
128.1169227 1
3.8%
128.1170934 1
3.8%
ValueCountFrequency (%)
128.2692268 1
3.8%
128.2612858 1
3.8%
128.1951314 1
3.8%
128.1873472 1
3.8%
128.1821216 1
3.8%
128.1820717 1
3.8%
128.1818333 1
3.8%
128.1756631 1
3.8%
128.1740288 1
3.8%
128.1732813 1
3.8%

전화번호
Text

MISSING 

Distinct10
Distinct (%)100.0%
Missing16
Missing (%)61.5%
Memory size340.0 B
2024-03-16T13:17:00.826723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters120
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

Unique10 ?
Unique (%)100.0%

Sample

1st row054-430-8275
2nd row054-431-8911
3rd row054-436-3337
4th row054-435-4490
5th row054-439-0117
ValueCountFrequency (%)
054-430-8275 1
10.0%
054-431-8911 1
10.0%
054-436-3337 1
10.0%
054-435-4490 1
10.0%
054-439-0117 1
10.0%
054-433-0028 1
10.0%
054-437-6019 1
10.0%
053-436-3337 1
10.0%
054-434-4978 1
10.0%
054-434-8852 1
10.0%
2024-03-16T13:17:01.252342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 24
20.0%
- 20
16.7%
3 18
15.0%
0 16
13.3%
5 13
10.8%
8 6
 
5.0%
7 6
 
5.0%
1 6
 
5.0%
9 5
 
4.2%
2 3
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 100
83.3%
Dash Punctuation 20
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 24
24.0%
3 18
18.0%
0 16
16.0%
5 13
13.0%
8 6
 
6.0%
7 6
 
6.0%
1 6
 
6.0%
9 5
 
5.0%
2 3
 
3.0%
6 3
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 120
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 24
20.0%
- 20
16.7%
3 18
15.0%
0 16
13.3%
5 13
10.8%
8 6
 
5.0%
7 6
 
5.0%
1 6
 
5.0%
9 5
 
4.2%
2 3
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 120
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 24
20.0%
- 20
16.7%
3 18
15.0%
0 16
13.3%
5 13
10.8%
8 6
 
5.0%
7 6
 
5.0%
1 6
 
5.0%
9 5
 
4.2%
2 3
 
2.5%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size340.0 B
Minimum2024-03-12 00:00:00
Maximum2024-03-12 00:00:00
2024-03-16T13:17:01.460053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:17:01.606581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-16T13:16:57.469762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:57.190133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:57.594369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:57.344601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-16T13:17:01.758013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명사업장소재지(도로명)위도경도전화번호
업소명1.0001.0001.0001.0001.000
사업장소재지(도로명)1.0001.0001.0001.0001.000
위도1.0001.0001.0000.6681.000
경도1.0001.0000.6681.0001.000
전화번호1.0001.0001.0001.0001.000
2024-03-16T13:17:01.937076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.000-0.206
경도-0.2061.000

Missing values

2024-03-16T13:16:57.795223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-16T13:16:58.033828image/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

업소명사업장소재지(도로명)위도경도전화번호데이터기준일
0가야동물병원경상북도 김천시 남산동 12-336.119399128.121008054-430-82752024-03-12
1강아지살롱경상북도 김천시 신음동 776-336.138907128.117093<NA>2024-03-12
2개편하개경상북도 김천시 교동 640-636.131082128.099238<NA>2024-03-12
3꼬리치는 강아지경상북도 김천시 부곡동 364-1036.125092128.105674<NA>2024-03-12
4도그샵경상북도 김천시 평화동 147-1436.126685128.108209054-431-89112024-03-12
5띠아몽경상북도 김천시 덕곡동 698-336.114968128.156969<NA>2024-03-12
6러브아지경상북도 김천시 아포읍 국사리 1118-1736.158515128.261286<NA>2024-03-12
7마킹경상북도 김천시 율곡동 73936.121869128.195131<NA>2024-03-12
8마킹커피(Marking Coffee)경상북도 김천시 율곡동 36436.121412128.182122<NA>2024-03-12
9멍그랑경상북도 김천시 부곡동 144636.125607128.092999<NA>2024-03-12
업소명사업장소재지(도로명)위도경도전화번호데이터기준일
16애견샾경상북도 김천시 평화동 268-1936.123165128.113337054-435-44902024-03-12
17애견미용실경상북도 김천시 부곡동 152736.124209128.094553<NA>2024-03-12
18우정 팜 크리닉경상북도 김천시 평화동 14-3736.125955128.117541054-439-01172024-03-12
19쫄랭쫄랭경상북도 김천시 평화동 245-1936.125763128.110963054-433-00282024-03-12
20채리애견샵경상북도 김천시 신음동 439-336.13382128.120852054-437-60192024-03-12
21컴온독경상북도 김천시 신음동 792-436.136194128.116923053-436-33372024-03-12
22코코앤잭슨경상북도 김천시 아포읍 송천리 1035-11 코코앤잭슨 2층36.156875128.269227<NA>2024-03-12
23플라잉독경상북도 김천시 율곡동 8936.119592128.175663054-434-49782024-03-12
24플란다스의개경상북도 김천시 평화동 245-1936.125763128.110963<NA>2024-03-12
25햇살이네경상북도 김천시 농소면 월곡리 763-236.104011128.174029054-434-88522024-03-12