Overview

Dataset statistics

Number of variables5
Number of observations252
Missing cells17
Missing cells (%)1.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.7 KiB
Average record size in memory43.5 B

Variable types

Categorical1
Text1
Numeric3

Dataset

Description"2022년 동물 보호복지 실태조사"를 바탕으로 작성한 동물등록 현황입니다.2022년까지 시도, 시군구별 축종(개, 고양이)에 따른 동물 등록 누계(사망 제외) 자료입니다.개 등록 누계(A), 고양이 등록 누계(B), 총 등록 누계(C=A+B)
Author농림축산식품부 농림축산검역본부
URLhttps://www.data.go.kr/data/15125454/fileData.do

Alerts

개등록 누계 is highly overall correlated with 고양이등록 누계 and 2 other fieldsHigh correlation
고양이등록 누계 is highly overall correlated with 개등록 누계 and 2 other fieldsHigh correlation
총 등록 누계 is highly overall correlated with 개등록 누계 and 2 other fieldsHigh correlation
시도 is highly overall correlated with 개등록 누계 and 2 other fieldsHigh correlation
시군구 has 17 (6.7%) missing valuesMissing
고양이등록 누계 has 16 (6.3%) zerosZeros

Reproduction

Analysis started2023-12-16 15:40:06.914332
Analysis finished2023-12-16 15:40:13.457481
Duration6.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도
Categorical

HIGH CORRELATION 

Distinct34
Distinct (%)13.5%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
경기도
32 
서울특별시
25 
경상북도
23 
전라남도
22 
경상남도
20 
Other values (29)
130 

Length

Max length7
Median length5
Mean length4.0079365
Min length2

Unique

Unique17 ?
Unique (%)6.7%

Sample

1st row서울
2nd row서울특별시
3rd row서울특별시
4th row서울특별시
5th row서울특별시

Common Values

ValueCountFrequency (%)
경기도 32
12.7%
서울특별시 25
9.9%
경상북도 23
9.1%
전라남도 22
8.7%
경상남도 20
 
7.9%
강원도 18
 
7.1%
부산광역시 16
 
6.3%
충청남도 16
 
6.3%
전라북도 14
 
5.6%
충청북도 12
 
4.8%
Other values (24) 54
21.4%

Length

2023-12-16T15:40:13.889498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 32
12.7%
서울특별시 25
9.9%
경상북도 23
9.1%
전라남도 22
8.7%
경상남도 20
 
7.9%
강원도 18
 
7.1%
부산광역시 16
 
6.3%
충청남도 16
 
6.3%
전라북도 14
 
5.6%
충청북도 12
 
4.8%
Other values (24) 54
21.4%

시군구
Text

MISSING 

Distinct213
Distinct (%)90.6%
Missing17
Missing (%)6.7%
Memory size2.1 KiB
2023-12-16T15:40:15.067649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length3
Mean length3.0212766
Min length2

Characters and Unicode

Total characters710
Distinct characters140
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique206 ?
Unique (%)87.7%

Sample

1st row강남구
2nd row강동구
3rd row강북구
4th row강서구
5th row관악구
ValueCountFrequency (%)
동구 6
 
2.5%
중구 6
 
2.5%
서구 5
 
2.1%
남구 4
 
1.7%
북구 4
 
1.7%
창원 3
 
1.3%
강서구 2
 
0.8%
고성군 2
 
0.8%
익산시 1
 
0.4%
전주시 1
 
0.4%
Other values (204) 204
85.7%
2023-12-16T15:40:17.426072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
군 88
 
12.4%
시 78
 
11.0%
구 77
 
10.8%
천 22
 
3.1%
주 21
 
3.0%
성 19
 
2.7%
산 18
 
2.5%
양 18
 
2.5%
동 17
 
2.4%
서 13
 
1.8%
Other values (130) 339
47.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 707
99.6%
Space Separator 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 88
 
12.4%
시 78
 
11.0%
구 77
 
10.9%
천 22
 
3.1%
주 21
 
3.0%
성 19
 
2.7%
산 18
 
2.5%
양 18
 
2.5%
동 17
 
2.4%
서 13
 
1.8%
Other values (129) 336
47.5%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 707
99.6%
Common 3
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 88
 
12.4%
시 78
 
11.0%
구 77
 
10.9%
천 22
 
3.1%
주 21
 
3.0%
성 19
 
2.7%
산 18
 
2.5%
양 18
 
2.5%
동 17
 
2.4%
서 13
 
1.8%
Other values (129) 336
47.5%
Common
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 707
99.6%
ASCII 3
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
군 88
 
12.4%
시 78
 
11.0%
구 77
 
10.9%
천 22
 
3.1%
주 21
 
3.0%
성 19
 
2.7%
산 18
 
2.5%
양 18
 
2.5%
동 17
 
2.4%
서 13
 
1.8%
Other values (129) 336
47.5%
ASCII
ValueCountFrequency (%)
3
100.0%

개등록 누계
Real number (ℝ)

HIGH CORRELATION 

Distinct248
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24014.754
Minimum0
Maximum898590
Zeros1
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2023-12-16T15:40:17.996821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile827.4
Q12713.75
median10174
Q321005.75
95-th percentile78790.35
Maximum898590
Range898590
Interquartile range (IQR)18292

Descriptive statistics

Standard deviation70304.717
Coefficient of variation (CV)2.9275635
Kurtosis106.78812
Mean24014.754
Median Absolute Deviation (MAD)7991
Skewness9.5040243
Sum6051718
Variance4.9427532 × 109
MonotonicityNot monotonic
2023-12-16T15:40:18.982367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2894 2
 
0.8%
5630 2
 
0.8%
14670 2
 
0.8%
6324 2
 
0.8%
537884 1
 
0.4%
1413 1
 
0.4%
1033 1
 
0.4%
2938 1
 
0.4%
4171 1
 
0.4%
14293 1
 
0.4%
Other values (238) 238
94.4%
ValueCountFrequency (%)
0 1
0.4%
1 1
0.4%
10 1
0.4%
87 1
0.4%
157 1
0.4%
458 1
0.4%
470 1
0.4%
585 1
0.4%
604 1
0.4%
609 1
0.4%
ValueCountFrequency (%)
898590 1
0.4%
537884 1
0.4%
202883 1
0.4%
195988 1
0.4%
168121 1
0.4%
128224 1
0.4%
121215 1
0.4%
117876 1
0.4%
98090 1
0.4%
94725 1
0.4%

고양이등록 누계
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct146
Distinct (%)57.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean226.05556
Minimum0
Maximum8953
Zeros16
Zeros (%)6.3%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2023-12-16T15:40:19.756498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median41
Q3201.25
95-th percentile797.35
Maximum8953
Range8953
Interquartile range (IQR)196.25

Descriptive statistics

Standard deviation778.20906
Coefficient of variation (CV)3.4425567
Kurtosis89.967449
Mean226.05556
Median Absolute Deviation (MAD)40
Skewness8.9497519
Sum56966
Variance605609.34
MonotonicityNot monotonic
2023-12-16T15:40:20.891666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 16
 
6.3%
3 16
 
6.3%
1 10
 
4.0%
2 9
 
3.6%
5 8
 
3.2%
4 7
 
2.8%
6 5
 
2.0%
9 5
 
2.0%
11 4
 
1.6%
31 4
 
1.6%
Other values (136) 168
66.7%
ValueCountFrequency (%)
0 16
6.3%
1 10
4.0%
2 9
3.6%
3 16
6.3%
4 7
2.8%
5 8
3.2%
6 5
 
2.0%
7 2
 
0.8%
8 3
 
1.2%
9 5
 
2.0%
ValueCountFrequency (%)
8953 1
0.4%
7278 1
0.4%
2965 1
0.4%
2499 1
0.4%
1185 1
0.4%
1061 1
0.4%
894 1
0.4%
861 1
0.4%
855 1
0.4%
854 1
0.4%

총 등록 누계
Real number (ℝ)

HIGH CORRELATION 

Distinct250
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24240.81
Minimum0
Maximum907543
Zeros1
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2023-12-16T15:40:22.352645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile828.5
Q12723.75
median10226
Q321145.25
95-th percentile79401.1
Maximum907543
Range907543
Interquartile range (IQR)18421.5

Descriptive statistics

Standard deviation71029.477
Coefficient of variation (CV)2.9301611
Kurtosis106.80782
Mean24240.81
Median Absolute Deviation (MAD)8058
Skewness9.5088656
Sum6108684
Variance5.0451866 × 109
MonotonicityNot monotonic
2023-12-16T15:40:23.063866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15007 2
 
0.8%
2730 2
 
0.8%
545162 1
 
0.4%
1822 1
 
0.4%
1414 1
 
0.4%
1034 1
 
0.4%
2977 1
 
0.4%
4181 1
 
0.4%
14324 1
 
0.4%
83833 1
 
0.4%
Other values (240) 240
95.2%
ValueCountFrequency (%)
0 1
0.4%
1 1
0.4%
10 1
0.4%
87 1
0.4%
157 1
0.4%
460 1
0.4%
475 1
0.4%
585 1
0.4%
604 1
0.4%
609 1
0.4%
ValueCountFrequency (%)
907543 1
0.4%
545162 1
0.4%
203777 1
0.4%
196842 1
0.4%
168976 1
0.4%
129285 1
0.4%
122076 1
0.4%
118729 1
0.4%
98559 1
0.4%
95910 1
0.4%

Interactions

2023-12-16T15:40:11.366437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:40:08.147923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:40:10.017369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:40:11.814125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:40:08.778162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:40:10.389695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:40:12.320096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:40:09.631770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:40:10.917503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-16T15:40:23.317560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도개등록 누계고양이등록 누계총 등록 누계
시도1.0001.0000.9901.000
개등록 누계1.0001.0000.8381.000
고양이등록 누계0.9900.8381.0000.838
총 등록 누계1.0001.0000.8381.000
2023-12-16T15:40:23.817296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
개등록 누계고양이등록 누계총 등록 누계시도
개등록 누계1.0000.9181.0000.939
고양이등록 누계0.9181.0000.9200.885
총 등록 누계1.0000.9201.0000.939
시도0.9390.8850.9391.000

Missing values

2023-12-16T15:40:12.855474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-16T15:40:13.249189image/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

시도시군구개등록 누계고양이등록 누계총 등록 누계
0서울<NA>5378847278545162
1서울특별시강남구3440244134843
2서울특별시강동구2529222325515
3서울특별시강북구1844414118585
4서울특별시강서구3328035633636
5서울특별시관악구2602738126408
6서울특별시광진구1992634620272
7서울특별시구로구1917923319412
8서울특별시금천구1279113412925
9서울특별시노원구2694219627138
시도시군구개등록 누계고양이등록 누계총 등록 누계
242경상남도창원 의창성산구2320414123345
243경상남도창원 진해구109393010969
244경상남도통영시7769487817
245경상남도하동군170681714
246경상남도함안군2704202724
247경상남도함양군153731540
248경상남도합천군170411705
249제주<NA>52807296555772
250제주특별자치도서귀포시1336746613833
251제주특별자치도제주시39440249941939