Overview

Dataset statistics

Number of variables9
Number of observations25
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.1 KiB
Average record size in memory84.3 B

Variable types

Text1
Numeric7
DateTime1

Dataset

Description세종특별자치시의 반려동물등록현황 정보 입니다.데이터는 등록형태(내장형 RFID, 회장형 RFID, 인식표), 등록 품종수, 소유자수, 등록 동물수, 소유자별 동물등록수로 구성되어 있습니다.
Author세종특별자치시
URLhttps://www.data.go.kr/data/15040305/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
등록형태(내장형 RFID) is highly overall correlated with 등록형태(외장형 RFID) and 4 other fieldsHigh correlation
등록형태(외장형 RFID) is highly overall correlated with 등록형태(내장형 RFID) and 4 other fieldsHigh correlation
등록형태(인식표) is highly overall correlated with 등록형태(내장형 RFID) and 4 other fieldsHigh correlation
등록 품종수 is highly overall correlated with 등록형태(내장형 RFID) and 4 other fieldsHigh correlation
동물소유자수 is highly overall correlated with 등록형태(내장형 RFID) and 4 other fieldsHigh correlation
등록동물수 is highly overall correlated with 등록형태(내장형 RFID) and 4 other fieldsHigh correlation
읍면동 has unique valuesUnique
등록형태(내장형 RFID) has unique valuesUnique
등록형태(외장형 RFID) has unique valuesUnique
동물소유자수 has unique valuesUnique
등록동물수 has unique valuesUnique

Reproduction

Analysis started2023-12-12 22:17:00.506666
Analysis finished2023-12-12 22:17:05.394761
Duration4.89 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

읍면동
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-13T07:17:05.500862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.04
Min length3

Characters and Unicode

Total characters76
Distinct characters46
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

Unique25 ?
Unique (%)100.0%

Sample

1st row고운동
2nd row금남면
3rd row나성동
4th row다정동
5th row대평동
ValueCountFrequency (%)
고운동 1
 
4.0%
어진동 1
 
4.0%
해밀동 1
 
4.0%
한솔동 1
 
4.0%
집현동 1
 
4.0%
종촌동 1
 
4.0%
전의면 1
 
4.0%
전동면 1
 
4.0%
장군면 1
 
4.0%
연서면 1
 
4.0%
Other values (15) 15
60.0%
2023-12-13T07:17:05.756247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17
22.4%
9
 
11.8%
3
 
3.9%
2
 
2.6%
2
 
2.6%
2
 
2.6%
2
 
2.6%
1
 
1.3%
1
 
1.3%
1
 
1.3%
Other values (36) 36
47.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 76
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
17
22.4%
9
 
11.8%
3
 
3.9%
2
 
2.6%
2
 
2.6%
2
 
2.6%
2
 
2.6%
1
 
1.3%
1
 
1.3%
1
 
1.3%
Other values (36) 36
47.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 76
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
17
22.4%
9
 
11.8%
3
 
3.9%
2
 
2.6%
2
 
2.6%
2
 
2.6%
2
 
2.6%
1
 
1.3%
1
 
1.3%
1
 
1.3%
Other values (36) 36
47.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 76
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
17
22.4%
9
 
11.8%
3
 
3.9%
2
 
2.6%
2
 
2.6%
2
 
2.6%
2
 
2.6%
1
 
1.3%
1
 
1.3%
1
 
1.3%
Other values (36) 36
47.4%

등록형태(내장형 RFID)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean336.56
Minimum70
Maximum1197
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-13T07:17:05.860817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum70
5-th percentile72
Q1129
median195
Q3471
95-th percentile827.6
Maximum1197
Range1127
Interquartile range (IQR)342

Descriptive statistics

Standard deviation286.23185
Coefficient of variation (CV)0.85046307
Kurtosis2.0551643
Mean336.56
Median Absolute Deviation (MAD)119
Skewness1.4492223
Sum8414
Variance81928.673
MonotonicityNot monotonic
2023-12-13T07:17:05.949569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
848 1
 
4.0%
276 1
 
4.0%
1197 1
 
4.0%
71 1
 
4.0%
465 1
 
4.0%
114 1
 
4.0%
746 1
 
4.0%
129 1
 
4.0%
101 1
 
4.0%
301 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
70 1
4.0%
71 1
4.0%
76 1
4.0%
78 1
4.0%
101 1
4.0%
114 1
4.0%
129 1
4.0%
149 1
4.0%
152 1
4.0%
170 1
4.0%
ValueCountFrequency (%)
1197 1
4.0%
848 1
4.0%
746 1
4.0%
597 1
4.0%
574 1
4.0%
542 1
4.0%
471 1
4.0%
465 1
4.0%
388 1
4.0%
336 1
4.0%

등록형태(외장형 RFID)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean305.88
Minimum61
Maximum1238
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-13T07:17:06.040305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum61
5-th percentile74
Q1117
median200
Q3466
95-th percentile772
Maximum1238
Range1177
Interquartile range (IQR)349

Descriptive statistics

Standard deviation274.18946
Coefficient of variation (CV)0.89639551
Kurtosis4.6984463
Mean305.88
Median Absolute Deviation (MAD)114
Skewness1.9668425
Sum7647
Variance75179.86
MonotonicityNot monotonic
2023-12-13T07:17:06.131004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
832 1
 
4.0%
200 1
 
4.0%
1238 1
 
4.0%
96 1
 
4.0%
474 1
 
4.0%
117 1
 
4.0%
532 1
 
4.0%
103 1
 
4.0%
97 1
 
4.0%
236 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
61 1
4.0%
71 1
4.0%
86 1
4.0%
96 1
4.0%
97 1
4.0%
103 1
4.0%
117 1
4.0%
122 1
4.0%
141 1
4.0%
156 1
4.0%
ValueCountFrequency (%)
1238 1
4.0%
832 1
4.0%
532 1
4.0%
482 1
4.0%
475 1
4.0%
474 1
4.0%
466 1
4.0%
436 1
4.0%
349 1
4.0%
332 1
4.0%

등록형태(인식표)
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean69.4
Minimum11
Maximum405
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-13T07:17:06.220405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile12
Q121
median43
Q383
95-th percentile161
Maximum405
Range394
Interquartile range (IQR)62

Descriptive statistics

Standard deviation81.24141
Coefficient of variation (CV)1.1706255
Kurtosis12.404038
Mean69.4
Median Absolute Deviation (MAD)31
Skewness3.1766799
Sum1735
Variance6600.1667
MonotonicityNot monotonic
2023-12-13T07:17:06.313664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
12 2
 
8.0%
169 1
 
4.0%
20 1
 
4.0%
405 1
 
4.0%
72 1
 
4.0%
14 1
 
4.0%
129 1
 
4.0%
23 1
 
4.0%
28 1
 
4.0%
51 1
 
4.0%
Other values (14) 14
56.0%
ValueCountFrequency (%)
11 1
4.0%
12 2
8.0%
14 1
4.0%
16 1
4.0%
20 1
4.0%
21 1
4.0%
23 1
4.0%
26 1
4.0%
28 1
4.0%
35 1
4.0%
ValueCountFrequency (%)
405 1
4.0%
169 1
4.0%
129 1
4.0%
107 1
4.0%
98 1
4.0%
85 1
4.0%
83 1
4.0%
80 1
4.0%
77 1
4.0%
76 1
4.0%

등록 품종수
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48.72
Minimum22
Maximum79
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-13T07:17:06.402862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22
5-th percentile30.2
Q139
median48
Q360
95-th percentile70.8
Maximum79
Range57
Interquartile range (IQR)21

Descriptive statistics

Standard deviation14.249327
Coefficient of variation (CV)0.29247388
Kurtosis-0.4418399
Mean48.72
Median Absolute Deviation (MAD)11
Skewness0.25614045
Sum1218
Variance203.04333
MonotonicityNot monotonic
2023-12-13T07:17:06.489114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
63 2
 
8.0%
45 2
 
8.0%
71 1
 
4.0%
36 1
 
4.0%
79 1
 
4.0%
22 1
 
4.0%
60 1
 
4.0%
30 1
 
4.0%
70 1
 
4.0%
31 1
 
4.0%
Other values (13) 13
52.0%
ValueCountFrequency (%)
22 1
4.0%
30 1
4.0%
31 1
4.0%
32 1
4.0%
36 1
4.0%
37 1
4.0%
39 1
4.0%
40 1
4.0%
42 1
4.0%
43 1
4.0%
ValueCountFrequency (%)
79 1
4.0%
71 1
4.0%
70 1
4.0%
63 2
8.0%
61 1
4.0%
60 1
4.0%
56 1
4.0%
53 1
4.0%
52 1
4.0%
51 1
4.0%

동물소유자수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean530.6
Minimum89
Maximum2056
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-13T07:17:06.578309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum89
5-th percentile110
Q1183
median331
Q3799
95-th percentile1368.2
Maximum2056
Range1967
Interquartile range (IQR)616

Descriptive statistics

Standard deviation482.29711
Coefficient of variation (CV)0.90896553
Kurtosis2.9757772
Mean530.6
Median Absolute Deviation (MAD)213
Skewness1.6387567
Sum13265
Variance232610.5
MonotonicityNot monotonic
2023-12-13T07:17:06.673800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
1440 1
 
4.0%
331 1
 
4.0%
2056 1
 
4.0%
143 1
 
4.0%
799 1
 
4.0%
183 1
 
4.0%
1081 1
 
4.0%
171 1
 
4.0%
118 1
 
4.0%
348 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
89 1
4.0%
108 1
4.0%
118 1
4.0%
120 1
4.0%
143 1
4.0%
171 1
4.0%
183 1
4.0%
221 1
4.0%
232 1
4.0%
259 1
4.0%
ValueCountFrequency (%)
2056 1
4.0%
1440 1
4.0%
1081 1
4.0%
888 1
4.0%
887 1
4.0%
867 1
4.0%
799 1
4.0%
789 1
4.0%
632 1
4.0%
598 1
4.0%

등록동물수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean711.84
Minimum142
Maximum2840
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-13T07:17:06.774768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum142
5-th percentile169.6
Q1255
median440
Q31011
95-th percentile1760.6
Maximum2840
Range2698
Interquartile range (IQR)756

Descriptive statistics

Standard deviation634.44186
Coefficient of variation (CV)0.89127031
Kurtosis4.2263314
Mean711.84
Median Absolute Deviation (MAD)264
Skewness1.858969
Sum17796
Variance402516.47
MonotonicityNot monotonic
2023-12-13T07:17:06.863888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
1849 1
 
4.0%
556 1
 
4.0%
2840 1
 
4.0%
179 1
 
4.0%
1011 1
 
4.0%
245 1
 
4.0%
1407 1
 
4.0%
255 1
 
4.0%
226 1
 
4.0%
588 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
142 1
4.0%
168 1
4.0%
176 1
4.0%
179 1
4.0%
226 1
4.0%
245 1
4.0%
255 1
4.0%
291 1
4.0%
319 1
4.0%
342 1
4.0%
ValueCountFrequency (%)
2840 1
4.0%
1849 1
4.0%
1407 1
4.0%
1139 1
4.0%
1131 1
4.0%
1126 1
4.0%
1011 1
4.0%
1005 1
4.0%
805 1
4.0%
768 1
4.0%
Distinct17
Distinct (%)68.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4004
Minimum1.25
Maximum1.92
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-13T07:17:06.945364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.25
5-th percentile1.254
Q11.28
median1.3
Q31.49
95-th percentile1.688
Maximum1.92
Range0.67
Interquartile range (IQR)0.21

Descriptive statistics

Standard deviation0.17489235
Coefficient of variation (CV)0.12488742
Kurtosis1.8400334
Mean1.4004
Median Absolute Deviation (MAD)0.04
Skewness1.4788765
Sum35.01
Variance0.030587333
MonotonicityNot monotonic
2023-12-13T07:17:07.031672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
1.27 4
16.0%
1.28 3
12.0%
1.29 2
 
8.0%
1.3 2
 
8.0%
1.25 2
 
8.0%
1.51 1
 
4.0%
1.38 1
 
4.0%
1.34 1
 
4.0%
1.49 1
 
4.0%
1.92 1
 
4.0%
Other values (7) 7
28.0%
ValueCountFrequency (%)
1.25 2
8.0%
1.27 4
16.0%
1.28 3
12.0%
1.29 2
8.0%
1.3 2
8.0%
1.33 1
 
4.0%
1.34 1
 
4.0%
1.38 1
 
4.0%
1.44 1
 
4.0%
1.47 1
 
4.0%
ValueCountFrequency (%)
1.92 1
4.0%
1.69 1
4.0%
1.68 1
4.0%
1.6 1
4.0%
1.56 1
4.0%
1.51 1
4.0%
1.49 1
4.0%
1.47 1
4.0%
1.44 1
4.0%
1.38 1
4.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
Minimum2023-12-07 00:00:00
Maximum2023-12-07 00:00:00
2023-12-13T07:17:07.114856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:07.182915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T07:17:04.744104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:00.811750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:01.499514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:02.134550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:02.859418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:03.444954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:04.048315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:04.816994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:00.920838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:01.585614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:02.228175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:02.945252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:03.520838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:04.120865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:04.885803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:01.022743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:01.682441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:02.338302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:03.023610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:03.607443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:04.187210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:04.958198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:01.138093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:01.784923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:02.451974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:03.120925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:03.710456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:04.255649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:05.023534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:01.234953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:01.873963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:02.561193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:03.200010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:03.802273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:04.558781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:05.096398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:01.340774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:01.969775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:02.659811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:03.284943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:03.882607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:04.624460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:05.157830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:01.415852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:02.052155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:02.755582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:03.359610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:03.969687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:04.680336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:17:07.239615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동등록형태(내장형 RFID)등록형태(외장형 RFID)등록형태(인식표)등록 품종수동물소유자수등록동물수동물소유자당 동물등록수
읍면동1.0001.0001.0001.0001.0001.0001.0001.000
등록형태(내장형 RFID)1.0001.0000.9600.9210.7260.9960.9590.000
등록형태(외장형 RFID)1.0000.9601.0000.9150.8000.9821.0000.000
등록형태(인식표)1.0000.9210.9151.0000.9380.9140.9140.000
등록 품종수1.0000.7260.8000.9381.0000.7730.7880.232
동물소유자수1.0000.9960.9820.9140.7731.0000.9820.000
등록동물수1.0000.9591.0000.9140.7880.9821.0000.000
동물소유자당 동물등록수1.0000.0000.0000.0000.2320.0000.0001.000
2023-12-13T07:17:07.341127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록형태(내장형 RFID)등록형태(외장형 RFID)등록형태(인식표)등록 품종수동물소유자수등록동물수동물소유자당 동물등록수
등록형태(내장형 RFID)1.0000.9880.9280.9520.9880.996-0.353
등록형태(외장형 RFID)0.9881.0000.9210.9220.9920.992-0.389
등록형태(인식표)0.9280.9211.0000.9020.9010.924-0.243
등록 품종수0.9520.9220.9021.0000.9180.941-0.220
동물소유자수0.9880.9920.9010.9181.0000.994-0.443
등록동물수0.9960.9920.9240.9410.9941.000-0.387
동물소유자당 동물등록수-0.353-0.389-0.243-0.220-0.443-0.3871.000

Missing values

2023-12-13T07:17:05.248591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:17:05.353410image/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

읍면동등록형태(내장형 RFID)등록형태(외장형 RFID)등록형태(인식표)등록 품종수동물소유자수등록동물수동물소유자당 동물등록수데이터기준일자
0고운동84883216971144018491.282023-12-07
1금남면27620080523315561.682023-12-07
2나성동17015616402653421.292023-12-07
3다정동597466766388711391.282023-12-07
4대평동19316835453083961.292023-12-07
5도담동574475776186711261.32023-12-07
6반곡동19520342423324401.332023-12-07
7보람동33634983495987681.282023-12-07
8부강면15214126432213191.442023-12-07
9새롬동5424821075388811311.272023-12-07
읍면동등록형태(내장형 RFID)등록형태(외장형 RFID)등록형태(인식표)등록 품종수동물소유자수등록동물수동물소유자당 동물등록수데이터기준일자
15연동면767121371081681.562023-12-07
16연서면17517443482593921.512023-12-07
17장군면30123651563485881.692023-12-07
18전동면1019728311182261.922023-12-07
19전의면12910323451712551.492023-12-07
20종촌동74653212970108114071.32023-12-07
21집현동11411714301832451.342023-12-07
22한솔동465474726079910111.272023-12-07
23해밀동719612221431791.252023-12-07
24조치원읍1197123840579205628401.382023-12-07