Overview

Dataset statistics

Number of variables8
Number of observations42
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 KiB
Average record size in memory73.1 B

Variable types

Text1
Numeric6
DateTime1

Dataset

Description경상남도 김해시 반려동물등록 현황에 대한 데이터로 지역구분,등록형태,등록품종수,동물소유자수,동물소유자당 동물등록수,동물등록수의 정보를 제공하고 있습니다.
Author경상남도 김해시
URLhttps://www.data.go.kr/data/15092354/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
내장형(RFID종류) is highly overall correlated with 외장형(RFID종류) and 3 other fieldsHigh correlation
외장형(RFID종류) is highly overall correlated with 내장형(RFID종류) and 3 other fieldsHigh correlation
인식표(RFID종류) is highly overall correlated with 내장형(RFID종류) and 3 other fieldsHigh correlation
등록품종수 is highly overall correlated with 내장형(RFID종류) and 3 other fieldsHigh correlation
동물소유자수 is highly overall correlated with 내장형(RFID종류) and 3 other fieldsHigh correlation
읍면동(법정동) has unique valuesUnique
인식표(RFID종류) has unique valuesUnique

Reproduction

Analysis started2023-12-12 09:00:05.383246
Analysis finished2023-12-12 09:00:09.783839
Duration4.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

읍면동(법정동)
Text

UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size468.0 B
2023-12-12T18:00:09.981575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.8571429
Min length2

Characters and Unicode

Total characters120
Distinct characters56
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)100.0%

Sample

1st row강동
2nd row내동
3rd row안동
4th row외동
5th row이동
ValueCountFrequency (%)
강동 1
 
2.4%
율하동 1
 
2.4%
한림면 1
 
2.4%
상동면 1
 
2.4%
생림면 1
 
2.4%
서상동 1
 
2.4%
수가동 1
 
2.4%
신문동 1
 
2.4%
어방동 1
 
2.4%
유하동 1
 
2.4%
Other values (32) 32
76.2%
2023-12-12T18:00:10.404058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 38
31.7%
면 7
 
5.8%
삼 4
 
3.3%
유 4
 
3.3%
하 3
 
2.5%
대 3
 
2.5%
상 3
 
2.5%
내 3
 
2.5%
진 2
 
1.7%
장 2
 
1.7%
Other values (46) 51
42.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 120
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 38
31.7%
면 7
 
5.8%
삼 4
 
3.3%
유 4
 
3.3%
하 3
 
2.5%
대 3
 
2.5%
상 3
 
2.5%
내 3
 
2.5%
진 2
 
1.7%
장 2
 
1.7%
Other values (46) 51
42.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 120
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 38
31.7%
면 7
 
5.8%
삼 4
 
3.3%
유 4
 
3.3%
하 3
 
2.5%
대 3
 
2.5%
상 3
 
2.5%
내 3
 
2.5%
진 2
 
1.7%
장 2
 
1.7%
Other values (46) 51
42.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 120
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 38
31.7%
면 7
 
5.8%
삼 4
 
3.3%
유 4
 
3.3%
하 3
 
2.5%
대 3
 
2.5%
상 3
 
2.5%
내 3
 
2.5%
진 2
 
1.7%
장 2
 
1.7%
Other values (46) 51
42.5%

내장형(RFID종류)
Real number (ℝ)

HIGH CORRELATION 

Distinct41
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean328.71429
Minimum1
Maximum1285
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-12T18:00:10.565948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.15
Q163
median192
Q3484.75
95-th percentile1055.5
Maximum1285
Range1284
Interquartile range (IQR)421.75

Descriptive statistics

Standard deviation344.31496
Coefficient of variation (CV)1.0474597
Kurtosis0.62046769
Mean328.71429
Median Absolute Deviation (MAD)166
Skewness1.2297373
Sum13806
Variance118552.79
MonotonicityNot monotonic
2023-12-12T18:00:11.004288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
120 2
 
4.8%
7 1
 
2.4%
311 1
 
2.4%
179 1
 
2.4%
30 1
 
2.4%
1 1
 
2.4%
229 1
 
2.4%
506 1
 
2.4%
22 1
 
2.4%
715 1
 
2.4%
Other values (31) 31
73.8%
ValueCountFrequency (%)
1 1
2.4%
2 1
2.4%
4 1
2.4%
7 1
2.4%
12 1
2.4%
21 1
2.4%
22 1
2.4%
30 1
2.4%
35 1
2.4%
36 1
2.4%
ValueCountFrequency (%)
1285 1
2.4%
1089 1
2.4%
1058 1
2.4%
1008 1
2.4%
781 1
2.4%
748 1
2.4%
715 1
2.4%
705 1
2.4%
663 1
2.4%
619 1
2.4%

외장형(RFID종류)
Real number (ℝ)

HIGH CORRELATION 

Distinct41
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean297.21429
Minimum2
Maximum1299
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-12T18:00:11.143495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile4.05
Q160
median179
Q3393.5
95-th percentile1161.15
Maximum1299
Range1297
Interquartile range (IQR)333.5

Descriptive statistics

Standard deviation344.15861
Coefficient of variation (CV)1.1579477
Kurtosis2.5292978
Mean297.21429
Median Absolute Deviation (MAD)150.5
Skewness1.7520731
Sum12483
Variance118445.15
MonotonicityNot monotonic
2023-12-12T18:00:11.281029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
4 2
 
4.8%
5 1
 
2.4%
246 1
 
2.4%
85 1
 
2.4%
136 1
 
2.4%
55 1
 
2.4%
176 1
 
2.4%
607 1
 
2.4%
395 1
 
2.4%
2 1
 
2.4%
Other values (31) 31
73.8%
ValueCountFrequency (%)
2 1
2.4%
4 2
4.8%
5 1
2.4%
8 1
2.4%
10 1
2.4%
18 1
2.4%
20 1
2.4%
37 1
2.4%
55 1
2.4%
56 1
2.4%
ValueCountFrequency (%)
1299 1
2.4%
1286 1
2.4%
1174 1
2.4%
917 1
2.4%
795 1
2.4%
627 1
2.4%
607 1
2.4%
475 1
2.4%
433 1
2.4%
400 1
2.4%

인식표(RFID종류)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean173.71429
Minimum1
Maximum853
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-12T18:00:11.449510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.05
Q150.5
median112
Q3251.5
95-th percentile479
Maximum853
Range852
Interquartile range (IQR)201

Descriptive statistics

Standard deviation179.52978
Coefficient of variation (CV)1.0334773
Kurtosis4.0249306
Mean173.71429
Median Absolute Deviation (MAD)94.5
Skewness1.7682297
Sum7296
Variance32230.941
MonotonicityNot monotonic
2023-12-12T18:00:11.627602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
10 1
 
2.4%
71 1
 
2.4%
76 1
 
2.4%
26 1
 
2.4%
1 1
 
2.4%
72 1
 
2.4%
292 1
 
2.4%
4 1
 
2.4%
206 1
 
2.4%
3 1
 
2.4%
Other values (32) 32
76.2%
ValueCountFrequency (%)
1 1
2.4%
3 1
2.4%
4 1
2.4%
5 1
2.4%
10 1
2.4%
13 1
2.4%
16 1
2.4%
17 1
2.4%
18 1
2.4%
26 1
2.4%
ValueCountFrequency (%)
853 1
2.4%
577 1
2.4%
480 1
2.4%
460 1
2.4%
393 1
2.4%
327 1
2.4%
318 1
2.4%
301 1
2.4%
292 1
2.4%
264 1
2.4%

등록품종수
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42.119048
Minimum3
Maximum82
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-12T18:00:11.786988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile6.2
Q129.75
median42.5
Q355.75
95-th percentile74.85
Maximum82
Range79
Interquartile range (IQR)26

Descriptive statistics

Standard deviation20.901864
Coefficient of variation (CV)0.49625681
Kurtosis-0.66691334
Mean42.119048
Median Absolute Deviation (MAD)13.5
Skewness-0.25979564
Sum1769
Variance436.88792
MonotonicityNot monotonic
2023-12-12T18:00:11.973272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
56 3
 
7.1%
39 3
 
7.1%
42 3
 
7.1%
14 2
 
4.8%
75 2
 
4.8%
36 2
 
4.8%
55 2
 
4.8%
54 2
 
4.8%
66 2
 
4.8%
11 2
 
4.8%
Other values (18) 19
45.2%
ValueCountFrequency (%)
3 1
2.4%
5 1
2.4%
6 1
2.4%
10 1
2.4%
11 2
4.8%
14 2
4.8%
22 1
2.4%
23 1
2.4%
28 1
2.4%
35 1
2.4%
ValueCountFrequency (%)
82 1
 
2.4%
75 2
4.8%
72 1
 
2.4%
66 2
4.8%
64 1
 
2.4%
60 1
 
2.4%
56 3
7.1%
55 2
4.8%
54 2
4.8%
51 2
4.8%

동물소유자수
Real number (ℝ)

HIGH CORRELATION 

Distinct40
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean586.85714
Minimum6
Maximum2445
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-12T18:00:12.171412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile10.25
Q1127.75
median349.5
Q3885.25
95-th percentile2184.8
Maximum2445
Range2439
Interquartile range (IQR)757.5

Descriptive statistics

Standard deviation637.97001
Coefficient of variation (CV)1.0870959
Kurtosis1.7981636
Mean586.85714
Median Absolute Deviation (MAD)295
Skewness1.5063321
Sum24648
Variance407005.74
MonotonicityNot monotonic
2023-12-12T18:00:12.356931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
15 2
 
4.8%
6 2
 
4.8%
1421 1
 
2.4%
186 1
 
2.4%
207 1
 
2.4%
70 1
 
2.4%
350 1
 
2.4%
1086 1
 
2.4%
1045 1
 
2.4%
486 1
 
2.4%
Other values (30) 30
71.4%
ValueCountFrequency (%)
6 2
4.8%
10 1
2.4%
15 2
4.8%
24 1
2.4%
35 1
2.4%
52 1
2.4%
57 1
2.4%
70 1
2.4%
113 1
2.4%
172 1
2.4%
ValueCountFrequency (%)
2445 1
2.4%
2249 1
2.4%
2225 1
2.4%
1421 1
2.4%
1405 1
2.4%
1363 1
2.4%
1133 1
2.4%
1103 1
2.4%
1086 1
2.4%
1045 1
2.4%

동물소유자당 동물등록수
Real number (ℝ)

Distinct29
Distinct (%)69.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4378571
Minimum1
Maximum2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-12T18:00:12.564741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.2605
Q11.3025
median1.37
Q31.5675
95-th percentile1.7675
Maximum2
Range1
Interquartile range (IQR)0.265

Descriptive statistics

Standard deviation0.19262672
Coefficient of variation (CV)0.13396791
Kurtosis1.1681979
Mean1.4378571
Median Absolute Deviation (MAD)0.095
Skewness0.79650765
Sum60.39
Variance0.037105052
MonotonicityNot monotonic
2023-12-12T18:00:12.706360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
1.29 4
 
9.5%
1.34 3
 
7.1%
1.4 2
 
4.8%
1.5 2
 
4.8%
1.37 2
 
4.8%
1.3 2
 
4.8%
1.31 2
 
4.8%
1.59 2
 
4.8%
1.27 2
 
4.8%
1.36 2
 
4.8%
Other values (19) 19
45.2%
ValueCountFrequency (%)
1.0 1
 
2.4%
1.18 1
 
2.4%
1.26 1
 
2.4%
1.27 2
4.8%
1.29 4
9.5%
1.3 2
4.8%
1.31 2
4.8%
1.32 1
 
2.4%
1.34 3
7.1%
1.35 1
 
2.4%
ValueCountFrequency (%)
2.0 1
2.4%
1.89 1
2.4%
1.77 1
2.4%
1.72 1
2.4%
1.67 1
2.4%
1.62 1
2.4%
1.6 1
2.4%
1.59 2
4.8%
1.58 1
2.4%
1.57 1
2.4%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size468.0 B
Minimum2023-09-20 00:00:00
Maximum2023-09-20 00:00:00
2023-12-12T18:00:12.874442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:00:13.017957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T18:00:08.975616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:00:05.633395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:00:06.302708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:00:07.013822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:00:07.616750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:00:08.337529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:00:09.082154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:00:05.735168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:00:06.408540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:00:07.127622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:00:07.721104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:00:08.458985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:00:09.164951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:00:05.827805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:00:06.530898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:00:07.233740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:00:07.830755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:00:08.573773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:00:09.251457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:00:05.920367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:00:06.642627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:00:07.324680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:00:07.948175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:00:08.673238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:00:09.356346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:00:06.076872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:00:06.760889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:00:07.423372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:00:08.073739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:00:08.799537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:00:09.471368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:00:06.215109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:00:06.878975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:00:07.510477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:00:08.205280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:00:08.885114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:00:13.127541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동(법정동)내장형(RFID종류)외장형(RFID종류)인식표(RFID종류)등록품종수동물소유자수동물소유자당 동물등록수
읍면동(법정동)1.0001.0001.0001.0001.0001.0001.000
내장형(RFID종류)1.0001.0000.8000.8810.7780.8600.000
외장형(RFID종류)1.0000.8001.0000.9450.7670.8890.000
인식표(RFID종류)1.0000.8810.9451.0000.7420.7690.000
등록품종수1.0000.7780.7670.7421.0000.7410.238
동물소유자수1.0000.8600.8890.7690.7411.0000.000
동물소유자당 동물등록수1.0000.0000.0000.0000.2380.0001.000
2023-12-12T18:00:13.294027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
내장형(RFID종류)외장형(RFID종류)인식표(RFID종류)등록품종수동물소유자수동물소유자당 동물등록수
내장형(RFID종류)1.0000.9650.8830.9250.975-0.469
외장형(RFID종류)0.9651.0000.9150.9420.988-0.493
인식표(RFID종류)0.8830.9151.0000.9280.935-0.291
등록품종수0.9250.9420.9281.0000.950-0.362
동물소유자수0.9750.9880.9350.9501.000-0.497
동물소유자당 동물등록수-0.469-0.493-0.291-0.362-0.4971.000

Missing values

2023-12-12T18:00:09.592744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:00:09.725330image/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

읍면동(법정동)내장형(RFID종류)외장형(RFID종류)인식표(RFID종류)등록품종수동물소유자수동물소유자당 동물등록수데이터기준일자
0강동75106151.472023-09-20
1내동6637953936614051.322023-09-20
2안동12617096392861.372023-09-20
3외동100812995777522251.32023-09-20
4이동12101310241.462023-09-20
5흥동12011066351771.672023-09-20
6관동동7484752536011031.342023-09-20
7구산동10586274606613631.572023-09-20
8내덕동1447258361721.592023-09-20
9대동면114119318553491.582023-09-20
읍면동(법정동)내장형(RFID종류)외장형(RFID종류)인식표(RFID종류)등록품종수동물소유자수동물소유자당 동물등록수데이터기준일자
32장유동31124671514861.292023-09-20
33장유면285222159365631.182023-09-20
34전하동465649281131.342023-09-20
35주촌면421338190546541.452023-09-20
36지내동12018255402741.32023-09-20
37진례면173120145422701.622023-09-20
38진영읍128511748538224451.352023-09-20
39풍유동35201814521.42023-09-20
40한림면205205301484011.772023-09-20
41화목동36371623571.562023-09-20