Overview

Dataset statistics

Number of variables6
Number of observations156
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.7 KiB
Average record size in memory50.8 B

Variable types

Numeric2
Categorical3
Text1

Dataset

Description인천광역시 동물등록 현황 건수를 군구별로 동물등록건수,집계시점, 기준일자 등의 항목 정보를 제공하는 데이터입니다.
Author인천광역시
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15049784&srcSe=7661IVAWM27C61E190

Alerts

집계시점 has constant value ""Constant
기준일자 has constant value ""Constant
연번 is highly overall correlated with 군구High correlation
군구 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2024-03-18 03:28:15.908095
Analysis finished2024-03-18 03:28:16.929277
Duration1.02 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct156
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean78.5
Minimum1
Maximum156
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-03-18T12:28:16.987787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.75
Q139.75
median78.5
Q3117.25
95-th percentile148.25
Maximum156
Range155
Interquartile range (IQR)77.5

Descriptive statistics

Standard deviation45.177428
Coefficient of variation (CV)0.57550864
Kurtosis-1.2
Mean78.5
Median Absolute Deviation (MAD)39
Skewness0
Sum12246
Variance2041
MonotonicityStrictly increasing
2024-03-18T12:28:17.113822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.6%
109 1
 
0.6%
102 1
 
0.6%
103 1
 
0.6%
104 1
 
0.6%
105 1
 
0.6%
106 1
 
0.6%
107 1
 
0.6%
108 1
 
0.6%
110 1
 
0.6%
Other values (146) 146
93.6%
ValueCountFrequency (%)
1 1
0.6%
2 1
0.6%
3 1
0.6%
4 1
0.6%
5 1
0.6%
6 1
0.6%
7 1
0.6%
8 1
0.6%
9 1
0.6%
10 1
0.6%
ValueCountFrequency (%)
156 1
0.6%
155 1
0.6%
154 1
0.6%
153 1
0.6%
152 1
0.6%
151 1
0.6%
150 1
0.6%
149 1
0.6%
148 1
0.6%
147 1
0.6%

군구
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
중구
46 
계양구
22 
서구
21 
미추홀구
14 
강화군
13 
Other values (5)
40 

Length

Max length4
Median length3
Mean length2.6153846
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row중구
2nd row중구
3rd row중구
4th row중구
5th row중구

Common Values

ValueCountFrequency (%)
중구 46
29.5%
계양구 22
14.1%
서구 21
13.5%
미추홀구 14
 
9.0%
강화군 13
 
8.3%
남동구 11
 
7.1%
부평구 9
 
5.8%
동구 7
 
4.5%
옹진군 7
 
4.5%
연수구 6
 
3.8%

Length

2024-03-18T12:28:17.277377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T12:28:17.430026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중구 46
29.5%
계양구 22
14.1%
서구 21
13.5%
미추홀구 14
 
9.0%
강화군 13
 
8.3%
남동구 11
 
7.1%
부평구 9
 
5.8%
동구 7
 
4.5%
옹진군 7
 
4.5%
연수구 6
 
3.8%

읍면동(법정동)
Text

Distinct147
Distinct (%)94.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-03-18T12:28:17.755945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.224359
Min length2

Characters and Unicode

Total characters503
Distinct characters127
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

Unique138 ?
Unique (%)88.5%

Sample

1st row경동
2nd row내동
3rd row답동
4th row사동
5th row용동
ValueCountFrequency (%)
주안동 2
 
1.3%
문학동 2
 
1.3%
도화동 2
 
1.3%
관교동 2
 
1.3%
오류동 2
 
1.3%
학익동 2
 
1.3%
금곡동 2
 
1.3%
용현동 2
 
1.3%
숭의동 2
 
1.3%
하야동 1
 
0.6%
Other values (137) 137
87.8%
2024-03-18T12:28:18.448997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 139
27.6%
가 27
 
5.4%
면 19
 
3.8%
송 10
 
2.0%
학 10
 
2.0%
도 9
 
1.8%
현 8
 
1.6%
화 8
 
1.6%
산 8
 
1.6%
3 7
 
1.4%
Other values (117) 258
51.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 479
95.2%
Decimal Number 24
 
4.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 139
29.0%
가 27
 
5.6%
면 19
 
4.0%
송 10
 
2.1%
학 10
 
2.1%
도 9
 
1.9%
현 8
 
1.7%
화 8
 
1.7%
산 8
 
1.7%
신 7
 
1.5%
Other values (111) 234
48.9%
Decimal Number
ValueCountFrequency (%)
3 7
29.2%
2 7
29.2%
1 7
29.2%
7 1
 
4.2%
5 1
 
4.2%
4 1
 
4.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 479
95.2%
Common 24
 
4.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 139
29.0%
가 27
 
5.6%
면 19
 
4.0%
송 10
 
2.1%
학 10
 
2.1%
도 9
 
1.9%
현 8
 
1.7%
화 8
 
1.7%
산 8
 
1.7%
신 7
 
1.5%
Other values (111) 234
48.9%
Common
ValueCountFrequency (%)
3 7
29.2%
2 7
29.2%
1 7
29.2%
7 1
 
4.2%
5 1
 
4.2%
4 1
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 479
95.2%
ASCII 24
 
4.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 139
29.0%
가 27
 
5.6%
면 19
 
4.0%
송 10
 
2.1%
학 10
 
2.1%
도 9
 
1.9%
현 8
 
1.7%
화 8
 
1.7%
산 8
 
1.7%
신 7
 
1.5%
Other values (111) 234
48.9%
ASCII
ValueCountFrequency (%)
3 7
29.2%
2 7
29.2%
1 7
29.2%
7 1
 
4.2%
5 1
 
4.2%
4 1
 
4.2%

동물등록건수
Real number (ℝ)

Distinct136
Distinct (%)87.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1350.6346
Minimum1
Maximum13104
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-03-18T12:28:18.604332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.75
Q147.75
median223.5
Q31481.5
95-th percentile6190.5
Maximum13104
Range13103
Interquartile range (IQR)1433.75

Descriptive statistics

Standard deviation2327.7014
Coefficient of variation (CV)1.7234131
Kurtosis7.3951825
Mean1350.6346
Median Absolute Deviation (MAD)210
Skewness2.5795093
Sum210699
Variance5418193.7
MonotonicityNot monotonic
2024-03-18T12:28:18.786817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25 3
 
1.9%
20 3
 
1.9%
130 3
 
1.9%
3 3
 
1.9%
43 3
 
1.9%
90 2
 
1.3%
373 2
 
1.3%
201 2
 
1.3%
126 2
 
1.3%
191 2
 
1.3%
Other values (126) 131
84.0%
ValueCountFrequency (%)
1 1
 
0.6%
2 1
 
0.6%
3 3
1.9%
6 1
 
0.6%
8 2
1.3%
9 1
 
0.6%
11 1
 
0.6%
12 1
 
0.6%
13 2
1.3%
14 1
 
0.6%
ValueCountFrequency (%)
13104 1
0.6%
11570 1
0.6%
9273 1
0.6%
9067 1
0.6%
8292 1
0.6%
7992 1
0.6%
7016 1
0.6%
6663 1
0.6%
6033 1
0.6%
5864 1
0.6%

집계시점
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2009-01-01
156 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2009-01-01
2nd row2009-01-01
3rd row2009-01-01
4th row2009-01-01
5th row2009-01-01

Common Values

ValueCountFrequency (%)
2009-01-01 156
100.0%

Length

2024-03-18T12:28:18.900178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T12:28:19.036048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2009-01-01 156
100.0%

기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2022-12-31
156 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-12-31
2nd row2022-12-31
3rd row2022-12-31
4th row2022-12-31
5th row2022-12-31

Common Values

ValueCountFrequency (%)
2022-12-31 156
100.0%

Length

2024-03-18T12:28:19.122806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T12:28:19.206490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-12-31 156
100.0%

Interactions

2024-03-18T12:28:16.647218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:28:16.472633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:28:16.722998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:28:16.576142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T12:28:19.273045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번군구동물등록건수
연번1.0000.9680.610
군구0.9681.0000.634
동물등록건수0.6100.6341.000
2024-03-18T12:28:19.395118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번동물등록건수군구
연번1.0000.2000.688
동물등록건수0.2001.0000.240
군구0.6880.2401.000

Missing values

2024-03-18T12:28:16.811192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T12:28:16.893008image/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

연번군구읍면동(법정동)동물등록건수집계시점기준일자
01중구경동902009-01-012022-12-31
12중구내동942009-01-012022-12-31
23중구답동882009-01-012022-12-31
34중구사동382009-01-012022-12-31
45중구용동322009-01-012022-12-31
56중구유동382009-01-012022-12-31
67중구전동2162009-01-012022-12-31
78중구남북동512009-01-012022-12-31
89중구덕교동152009-01-012022-12-31
910중구도원동3002009-01-012022-12-31
연번군구읍면동(법정동)동물등록건수집계시점기준일자
146147강화군양사면1572009-01-012022-12-31
147148강화군하점면3802009-01-012022-12-31
148149강화군화도면2752009-01-012022-12-31
149150옹진군대청면172009-01-012022-12-31
150151옹진군덕적면202009-01-012022-12-31
151152옹진군백령면832009-01-012022-12-31
152153옹진군북도면432009-01-012022-12-31
153154옹진군연평면442009-01-012022-12-31
154155옹진군영흥면2522009-01-012022-12-31
155156옹진군자월면202009-01-012022-12-31