Overview

Dataset statistics

Number of variables14
Number of observations165
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory19.9 KiB
Average record size in memory123.8 B

Variable types

Categorical2
Text1
Numeric10
DateTime1

Dataset

Description경기도 수원시_반려동물현황은 시도명, 시군구명, 구청명, 법정동명, 등록품종수, 등록개체수, 소유자수, 관리부서명, 관리부서연락처, 데이터기준일자를 포함합니다.
Author경기도 수원시
URLhttps://www.data.go.kr/data/15040321/fileData.do

Alerts

시군명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
등록동물수 is highly overall correlated with (등록주체)시군구등록 and 7 other fieldsHigh correlation
(등록주체)시군구등록 is highly overall correlated with 등록동물수 and 7 other fieldsHigh correlation
(등록주체)대행업체등록 is highly overall correlated with 등록동물수 and 7 other fieldsHigh correlation
(등록주체)기타 is highly overall correlated with 등록동물수 and 7 other fieldsHigh correlation
(RFID종류)내장형 is highly overall correlated with 등록동물수 and 7 other fieldsHigh correlation
(RFID종류)외장형 is highly overall correlated with 등록동물수 and 7 other fieldsHigh correlation
(RFID종류)인식표 is highly overall correlated with 등록동물수 and 7 other fieldsHigh correlation
등록품종수 is highly overall correlated with 등록동물수 and 7 other fieldsHigh correlation
등록소유자수 is highly overall correlated with 등록동물수 and 8 other fieldsHigh correlation
동물소유자당등록동물수 is highly overall correlated with 등록소유자수High correlation
(등록주체)시군구등록 has 14 (8.5%) zerosZeros
(등록주체)기타 has 63 (38.2%) zerosZeros
(RFID종류)외장형 has 3 (1.8%) zerosZeros
(RFID종류)인식표 has 12 (7.3%) zerosZeros

Reproduction

Analysis started2023-12-12 06:46:10.605640
Analysis finished2023-12-12 06:46:22.014165
Duration11.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년도
Categorical

Distinct3
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2020
55 
2021
55 
2022
55 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2020 55
33.3%
2021 55
33.3%
2022 55
33.3%

Length

2023-12-12T15:46:22.067088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:46:22.153166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 55
33.3%
2021 55
33.3%
2022 55
33.3%

시군명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
수원시
165 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
수원시 165
100.0%

Length

2023-12-12T15:46:22.254625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:46:22.392427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수원시 165
100.0%
Distinct55
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-12T15:46:22.597253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.1636364
Min length2

Characters and Unicode

Total characters522
Distinct characters72
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

Unique0 ?
Unique (%)0.0%

Sample

1st row탑동
2nd row평동
3rd row고색동
4th row구운동
5th row권선동
ValueCountFrequency (%)
탑동 3
 
1.8%
조원동 3
 
1.8%
파장동 3
 
1.8%
상광교동 3
 
1.8%
하광교동 3
 
1.8%
교동 3
 
1.8%
영동 3
 
1.8%
중동 3
 
1.8%
지동 3
 
1.8%
고등동 3
 
1.8%
Other values (45) 135
81.8%
2023-12-12T15:46:23.054218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
147
28.2%
21
 
4.0%
18
 
3.4%
18
 
3.4%
15
 
2.9%
12
 
2.3%
9
 
1.7%
9
 
1.7%
9
 
1.7%
9
 
1.7%
Other values (62) 255
48.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 504
96.6%
Decimal Number 18
 
3.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
147
29.2%
21
 
4.2%
18
 
3.6%
18
 
3.6%
15
 
3.0%
12
 
2.4%
9
 
1.8%
9
 
1.8%
9
 
1.8%
9
 
1.8%
Other values (59) 237
47.0%
Decimal Number
ValueCountFrequency (%)
1 6
33.3%
2 6
33.3%
3 6
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 504
96.6%
Common 18
 
3.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
147
29.2%
21
 
4.2%
18
 
3.6%
18
 
3.6%
15
 
3.0%
12
 
2.4%
9
 
1.8%
9
 
1.8%
9
 
1.8%
9
 
1.8%
Other values (59) 237
47.0%
Common
ValueCountFrequency (%)
1 6
33.3%
2 6
33.3%
3 6
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 504
96.6%
ASCII 18
 
3.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
147
29.2%
21
 
4.2%
18
 
3.6%
18
 
3.6%
15
 
3.0%
12
 
2.4%
9
 
1.8%
9
 
1.8%
9
 
1.8%
9
 
1.8%
Other values (59) 237
47.0%
ASCII
ValueCountFrequency (%)
1 6
33.3%
2 6
33.3%
3 6
33.3%

등록동물수
Real number (ℝ)

HIGH CORRELATION 

Distinct154
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1304.8788
Minimum1
Maximum6101
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T15:46:23.230847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile17.2
Q1106
median1014
Q31774
95-th percentile4577.6
Maximum6101
Range6100
Interquartile range (IQR)1668

Descriptive statistics

Standard deviation1463.7196
Coefficient of variation (CV)1.1217284
Kurtosis1.2397736
Mean1304.8788
Median Absolute Deviation (MAD)888
Skewness1.3468657
Sum215305
Variance2142475.2
MonotonicityNot monotonic
2023-12-12T15:46:23.437475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
31 3
 
1.8%
45 2
 
1.2%
83 2
 
1.2%
41 2
 
1.2%
1377 2
 
1.2%
15 2
 
1.2%
100 2
 
1.2%
3 2
 
1.2%
1093 2
 
1.2%
22 2
 
1.2%
Other values (144) 144
87.3%
ValueCountFrequency (%)
1 1
0.6%
3 2
1.2%
6 1
0.6%
11 1
0.6%
14 1
0.6%
15 2
1.2%
16 1
0.6%
22 2
1.2%
25 1
0.6%
27 1
0.6%
ValueCountFrequency (%)
6101 1
0.6%
5951 1
0.6%
5576 1
0.6%
5495 1
0.6%
5333 1
0.6%
4878 1
0.6%
4688 1
0.6%
4641 1
0.6%
4631 1
0.6%
4364 1
0.6%

(등록주체)시군구등록
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct94
Distinct (%)57.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean96.412121
Minimum0
Maximum439
Zeros14
Zeros (%)8.5%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T15:46:23.588922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q19
median73
Q3153
95-th percentile308
Maximum439
Range439
Interquartile range (IQR)144

Descriptive statistics

Standard deviation107.621
Coefficient of variation (CV)1.1162601
Kurtosis1.1873658
Mean96.412121
Median Absolute Deviation (MAD)65
Skewness1.3199492
Sum15908
Variance11582.28
MonotonicityNot monotonic
2023-12-12T15:46:23.721139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 14
 
8.5%
8 11
 
6.7%
14 7
 
4.2%
91 5
 
3.0%
2 5
 
3.0%
13 4
 
2.4%
17 4
 
2.4%
3 4
 
2.4%
6 3
 
1.8%
19 3
 
1.8%
Other values (84) 105
63.6%
ValueCountFrequency (%)
0 14
8.5%
1 1
 
0.6%
2 5
 
3.0%
3 4
 
2.4%
6 3
 
1.8%
7 3
 
1.8%
8 11
6.7%
9 1
 
0.6%
13 4
 
2.4%
14 7
4.2%
ValueCountFrequency (%)
439 1
0.6%
427 1
0.6%
419 1
0.6%
411 1
0.6%
409 1
0.6%
399 1
0.6%
317 2
1.2%
309 1
0.6%
304 1
0.6%
300 1
0.6%

(등록주체)대행업체등록
Real number (ℝ)

HIGH CORRELATION 

Distinct154
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1205.5758
Minimum1
Maximum5675
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T15:46:23.876007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile15.2
Q198
median952
Q31655
95-th percentile4187.4
Maximum5675
Range5674
Interquartile range (IQR)1557

Descriptive statistics

Standard deviation1357.4522
Coefficient of variation (CV)1.1259784
Kurtosis1.2544945
Mean1205.5758
Median Absolute Deviation (MAD)841
Skewness1.353972
Sum198920
Variance1842676.6
MonotonicityNot monotonic
2023-12-12T15:46:24.014518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
75 3
 
1.8%
84 2
 
1.2%
3 2
 
1.2%
14 2
 
1.2%
31 2
 
1.2%
39 2
 
1.2%
29 2
 
1.2%
92 2
 
1.2%
130 2
 
1.2%
1190 2
 
1.2%
Other values (144) 144
87.3%
ValueCountFrequency (%)
1 1
0.6%
3 2
1.2%
6 1
0.6%
8 1
0.6%
12 1
0.6%
13 1
0.6%
14 2
1.2%
20 1
0.6%
22 1
0.6%
23 1
0.6%
ValueCountFrequency (%)
5675 1
0.6%
5501 1
0.6%
5160 1
0.6%
5057 1
0.6%
5008 1
0.6%
4566 1
0.6%
4335 1
0.6%
4266 1
0.6%
4225 1
0.6%
4037 1
0.6%

(등록주체)기타
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct12
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.8909091
Minimum0
Maximum18
Zeros63
Zeros (%)38.2%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T15:46:24.128024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q34
95-th percentile11
Maximum18
Range18
Interquartile range (IQR)4

Descriptive statistics

Standard deviation4.2798709
Coefficient of variation (CV)1.4804585
Kurtosis3.7380909
Mean2.8909091
Median Absolute Deviation (MAD)1
Skewness1.9722275
Sum477
Variance18.317295
MonotonicityNot monotonic
2023-12-12T15:46:24.231900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 63
38.2%
1 39
23.6%
4 12
 
7.3%
2 12
 
7.3%
7 9
 
5.5%
5 6
 
3.6%
11 6
 
3.6%
18 6
 
3.6%
10 3
 
1.8%
6 3
 
1.8%
Other values (2) 6
 
3.6%
ValueCountFrequency (%)
0 63
38.2%
1 39
23.6%
2 12
 
7.3%
4 12
 
7.3%
5 6
 
3.6%
6 3
 
1.8%
7 9
 
5.5%
8 3
 
1.8%
9 3
 
1.8%
10 3
 
1.8%
ValueCountFrequency (%)
18 6
3.6%
11 6
3.6%
10 3
 
1.8%
9 3
 
1.8%
8 3
 
1.8%
7 9
5.5%
6 3
 
1.8%
5 6
3.6%
4 12
7.3%
2 12
7.3%

(RFID종류)내장형
Real number (ℝ)

HIGH CORRELATION 

Distinct151
Distinct (%)91.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean793.50909
Minimum1
Maximum3460
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T15:46:24.369321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile11.2
Q170
median675
Q31051
95-th percentile2776
Maximum3460
Range3459
Interquartile range (IQR)981

Descriptive statistics

Standard deviation881.05952
Coefficient of variation (CV)1.1103332
Kurtosis1.1417453
Mean793.50909
Median Absolute Deviation (MAD)586
Skewness1.3307692
Sum130929
Variance776265.87
MonotonicityNot monotonic
2023-12-12T15:46:24.521402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21 3
 
1.8%
20 3
 
1.8%
52 2
 
1.2%
19 2
 
1.2%
11 2
 
1.2%
3 2
 
1.2%
70 2
 
1.2%
58 2
 
1.2%
833 2
 
1.2%
15 2
 
1.2%
Other values (141) 143
86.7%
ValueCountFrequency (%)
1 1
0.6%
3 2
1.2%
4 1
0.6%
5 1
0.6%
6 1
0.6%
8 1
0.6%
11 2
1.2%
12 1
0.6%
15 2
1.2%
16 1
0.6%
ValueCountFrequency (%)
3460 1
0.6%
3458 1
0.6%
3362 1
0.6%
3276 1
0.6%
3251 1
0.6%
3180 1
0.6%
2897 1
0.6%
2890 1
0.6%
2810 1
0.6%
2640 1
0.6%

(RFID종류)외장형
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct133
Distinct (%)80.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean390.38182
Minimum0
Maximum2178
Zeros3
Zeros (%)1.8%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T15:46:24.691522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5
Q129
median216
Q3607
95-th percentile1355.4
Maximum2178
Range2178
Interquartile range (IQR)578

Descriptive statistics

Standard deviation470.75838
Coefficient of variation (CV)1.2058922
Kurtosis2.1412321
Mean390.38182
Median Absolute Deviation (MAD)200
Skewness1.5593942
Sum64413
Variance221613.46
MonotonicityNot monotonic
2023-12-12T15:46:24.887721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9 4
 
2.4%
16 4
 
2.4%
12 4
 
2.4%
15 3
 
1.8%
41 3
 
1.8%
19 3
 
1.8%
32 3
 
1.8%
0 3
 
1.8%
5 3
 
1.8%
901 2
 
1.2%
Other values (123) 133
80.6%
ValueCountFrequency (%)
0 3
1.8%
2 2
1.2%
3 1
 
0.6%
4 2
1.2%
5 3
1.8%
9 4
2.4%
11 1
 
0.6%
12 4
2.4%
13 1
 
0.6%
14 2
1.2%
ValueCountFrequency (%)
2178 1
0.6%
2054 1
0.6%
1835 1
0.6%
1782 1
0.6%
1736 1
0.6%
1523 1
0.6%
1520 1
0.6%
1376 1
0.6%
1368 1
0.6%
1305 1
0.6%

(RFID종류)인식표
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct72
Distinct (%)43.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean120.98788
Minimum0
Maximum561
Zeros12
Zeros (%)7.3%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T15:46:25.035192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q112
median76
Q3189
95-th percentile364.8
Maximum561
Range561
Interquartile range (IQR)177

Descriptive statistics

Standard deviation130.83251
Coefficient of variation (CV)1.0813688
Kurtosis1.0043576
Mean120.98788
Median Absolute Deviation (MAD)69
Skewness1.2209199
Sum19963
Variance17117.146
MonotonicityNot monotonic
2023-12-12T15:46:25.472188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 12
 
7.3%
1 9
 
5.5%
12 7
 
4.2%
16 6
 
3.6%
23 6
 
3.6%
9 5
 
3.0%
8 4
 
2.4%
45 3
 
1.8%
107 3
 
1.8%
70 3
 
1.8%
Other values (62) 107
64.8%
ValueCountFrequency (%)
0 12
7.3%
1 9
5.5%
7 3
 
1.8%
8 4
 
2.4%
9 5
3.0%
10 3
 
1.8%
12 7
4.2%
13 2
 
1.2%
16 6
3.6%
21 3
 
1.8%
ValueCountFrequency (%)
561 2
1.2%
546 1
0.6%
437 2
1.2%
423 1
0.6%
377 2
1.2%
368 1
0.6%
352 2
1.2%
348 2
1.2%
346 1
0.6%
343 1
0.6%

등록품종수
Real number (ℝ)

HIGH CORRELATION 

Distinct77
Distinct (%)46.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48.715152
Minimum1
Maximum101
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T15:46:25.637704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7.2
Q128
median53
Q367
95-th percentile87
Maximum101
Range100
Interquartile range (IQR)39

Descriptive statistics

Standard deviation25.567416
Coefficient of variation (CV)0.52483499
Kurtosis-0.99324896
Mean48.715152
Median Absolute Deviation (MAD)20
Skewness-0.076477289
Sum8038
Variance653.69276
MonotonicityNot monotonic
2023-12-12T15:46:25.796891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16 7
 
4.2%
67 5
 
3.0%
70 5
 
3.0%
65 5
 
3.0%
36 4
 
2.4%
82 4
 
2.4%
25 4
 
2.4%
61 4
 
2.4%
42 4
 
2.4%
32 4
 
2.4%
Other values (67) 119
72.1%
ValueCountFrequency (%)
1 1
 
0.6%
2 2
1.2%
4 2
1.2%
5 2
1.2%
6 1
 
0.6%
7 1
 
0.6%
8 1
 
0.6%
10 2
1.2%
11 2
1.2%
13 3
1.8%
ValueCountFrequency (%)
101 1
 
0.6%
99 2
1.2%
98 1
 
0.6%
96 1
 
0.6%
95 1
 
0.6%
91 1
 
0.6%
89 1
 
0.6%
87 3
1.8%
84 1
 
0.6%
82 4
2.4%

등록소유자수
Real number (ℝ)

HIGH CORRELATION 

Distinct151
Distinct (%)91.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean996.47879
Minimum1
Maximum4646
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T15:46:25.935341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile12.6
Q176
median749
Q31353
95-th percentile3523.8
Maximum4646
Range4645
Interquartile range (IQR)1277

Descriptive statistics

Standard deviation1134.8261
Coefficient of variation (CV)1.1388362
Kurtosis1.3103143
Mean996.47879
Median Absolute Deviation (MAD)662
Skewness1.3763185
Sum164419
Variance1287830.4
MonotonicityNot monotonic
2023-12-12T15:46:26.097734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
26 4
 
2.4%
19 3
 
1.8%
1343 2
 
1.2%
29 2
 
1.2%
3 2
 
1.2%
72 2
 
1.2%
15 2
 
1.2%
11 2
 
1.2%
283 2
 
1.2%
30 2
 
1.2%
Other values (141) 142
86.1%
ValueCountFrequency (%)
1 1
 
0.6%
3 2
1.2%
4 1
 
0.6%
6 1
 
0.6%
7 1
 
0.6%
11 2
1.2%
12 1
 
0.6%
15 2
1.2%
17 1
 
0.6%
19 3
1.8%
ValueCountFrequency (%)
4646 1
0.6%
4598 1
0.6%
4320 1
0.6%
4222 1
0.6%
4186 1
0.6%
3871 1
0.6%
3766 1
0.6%
3739 1
0.6%
3527 1
0.6%
3511 1
0.6%

동물소유자당등록동물수
Real number (ℝ)

HIGH CORRELATION 

Distinct44
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3647879
Minimum1
Maximum2.33
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T15:46:26.252269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.222
Q11.29
median1.35
Q31.41
95-th percentile1.578
Maximum2.33
Range1.33
Interquartile range (IQR)0.12

Descriptive statistics

Standard deviation0.14828116
Coefficient of variation (CV)0.10864777
Kurtosis14.807989
Mean1.3647879
Median Absolute Deviation (MAD)0.06
Skewness2.5175033
Sum225.19
Variance0.021987302
MonotonicityNot monotonic
2023-12-12T15:46:26.399613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
1.28 9
 
5.5%
1.31 9
 
5.5%
1.36 9
 
5.5%
1.33 8
 
4.8%
1.32 8
 
4.8%
1.3 8
 
4.8%
1.26 7
 
4.2%
1.38 7
 
4.2%
1.25 7
 
4.2%
1.37 6
 
3.6%
Other values (34) 87
52.7%
ValueCountFrequency (%)
1.0 4
2.4%
1.2 2
 
1.2%
1.21 2
 
1.2%
1.22 1
 
0.6%
1.23 2
 
1.2%
1.24 1
 
0.6%
1.25 7
4.2%
1.26 7
4.2%
1.27 4
2.4%
1.28 9
5.5%
ValueCountFrequency (%)
2.33 1
 
0.6%
2.14 1
 
0.6%
1.73 1
 
0.6%
1.67 1
 
0.6%
1.66 1
 
0.6%
1.63 2
1.2%
1.62 1
 
0.6%
1.58 1
 
0.6%
1.57 1
 
0.6%
1.54 3
1.8%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Minimum2023-09-11 00:00:00
Maximum2023-09-11 00:00:00
2023-12-12T15:46:26.499178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:26.582252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T15:46:20.808427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:11.102373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:12.227964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:13.358641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:14.179446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:15.308675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:16.403687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:17.431467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:18.401064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:19.822884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:20.893433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:11.199500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:12.315503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:13.442473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:14.272641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:15.425603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:16.515250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:17.538208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:18.509379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:19.943152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:20.985561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:11.298057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:12.654848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:13.512758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:14.364127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:15.525710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:16.607074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:17.616296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:18.595842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:20.063763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:21.104827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:11.392839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:12.728728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:13.598740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:14.464206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:15.621579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:16.706164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:17.713296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:18.679461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:20.172051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:21.238231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:11.625810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:12.825520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:13.693756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:14.673191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:15.738595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:16.823605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:17.827984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:18.802912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:20.278607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:21.360498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:11.754286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:12.916523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:13.778693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:14.803918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:15.854107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:16.932188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:17.947568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:18.922678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:20.390955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:21.443437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:11.835535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:13.020037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:13.849496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:14.902493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:15.990076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:17.030751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:18.036601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:19.021240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:20.481551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:21.527183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:11.943311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:13.112127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:13.925715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:14.990251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:16.086247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:17.124466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:18.120117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:19.463337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:20.563702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:21.600110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:12.035483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:13.200575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:14.006150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:15.092128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:16.192431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:17.242373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:18.214870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:19.562417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:20.652360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:21.672252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:12.130678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:13.272497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:14.094302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:15.192276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:16.281621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:17.329848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:18.311836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:19.674227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:20.722410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:46:26.654881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도읍면동명등록동물수(등록주체)시군구등록(등록주체)대행업체등록(등록주체)기타(RFID종류)내장형(RFID종류)외장형(RFID종류)인식표등록품종수등록소유자수동물소유자당등록동물수
기준년도1.0000.0000.0000.0000.0000.0000.1720.0000.0000.0000.0000.000
읍면동명0.0001.0000.8880.9740.8931.0000.9070.7341.0000.9560.9010.923
등록동물수0.0000.8881.0000.8610.9980.6740.9650.9620.8630.9230.9910.193
(등록주체)시군구등록0.0000.9740.8611.0000.8380.6780.8660.8220.9680.8110.8540.309
(등록주체)대행업체등록0.0000.8930.9980.8381.0000.6950.9730.9580.8580.9180.9870.000
(등록주체)기타0.0001.0000.6740.6780.6951.0000.6920.5270.7620.5810.6680.258
(RFID종류)내장형0.1720.9070.9650.8660.9730.6921.0000.9200.8330.9170.9720.081
(RFID종류)외장형0.0000.7340.9620.8220.9580.5270.9201.0000.8140.9090.9490.000
(RFID종류)인식표0.0001.0000.8630.9680.8580.7620.8330.8141.0000.7770.8630.263
등록품종수0.0000.9560.9230.8110.9180.5810.9170.9090.7771.0000.9130.562
등록소유자수0.0000.9010.9910.8540.9870.6680.9720.9490.8630.9131.0000.270
동물소유자당등록동물수0.0000.9230.1930.3090.0000.2580.0810.0000.2630.5620.2701.000
2023-12-12T15:46:26.798853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록동물수(등록주체)시군구등록(등록주체)대행업체등록(등록주체)기타(RFID종류)내장형(RFID종류)외장형(RFID종류)인식표등록품종수등록소유자수동물소유자당등록동물수기준년도
등록동물수1.0000.9761.0000.6110.9950.9920.9850.9840.999-0.4890.000
(등록주체)시군구등록0.9761.0000.9720.6180.9750.9630.9830.9620.976-0.4900.000
(등록주체)대행업체등록1.0000.9721.0000.6090.9940.9920.9840.9830.999-0.4880.000
(등록주체)기타0.6110.6180.6091.0000.6330.5810.6200.6130.612-0.1920.000
(RFID종류)내장형0.9950.9750.9940.6331.0000.9780.9800.9820.994-0.4840.099
(RFID종류)외장형0.9920.9630.9920.5810.9781.0000.9750.9770.991-0.4890.000
(RFID종류)인식표0.9850.9830.9840.6200.9800.9751.0000.9680.985-0.4860.000
등록품종수0.9840.9620.9830.6130.9820.9770.9681.0000.978-0.4070.000
등록소유자수0.9990.9760.9990.6120.9940.9910.9850.9781.000-0.5150.000
동물소유자당등록동물수-0.489-0.490-0.488-0.192-0.484-0.489-0.486-0.407-0.5151.0000.000
기준년도0.0000.0000.0000.0000.0990.0000.0000.0000.0000.0001.000

Missing values

2023-12-12T15:46:21.798356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:46:21.955259image/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

기준년도시군명읍면동명등록동물수(등록주체)시군구등록(등록주체)대행업체등록(등록주체)기타(RFID종류)내장형(RFID종류)외장형(RFID종류)인식표등록품종수등록소유자수동물소유자당등록동물수데이터기준일자
02020수원시탑동1374157121078853141756710041.372023-09-11
12020수원시평동126131130823212261011.252023-09-11
22020수원시고색동90696809163220074496831.332023-09-11
32020수원시구운동1370178118848713351646210731.282023-09-11
42020수원시권선동463139942257281012755469135271.312023-09-11
52020수원시금곡동20902121873511766073076415721.332023-09-11
62020수원시당수동3774133602328956323001.252023-09-11
72020수원시서둔동9571228341579233145546941.382023-09-11
82020수원시세류동335229630461021778323438724561.362023-09-11
92020수원시입북동33029300118010644362631.252023-09-11
기준년도시군명읍면동명등록동물수(등록주체)시군구등록(등록주체)대행업체등록(등록주체)기타(RFID종류)내장형(RFID종류)외장형(RFID종류)인식표등록품종수등록소유자수동물소유자당등록동물수데이터기준일자
1552022수원시우만동26332352398015159012177919971.322023-09-11
1562022수원시인계동389818837019245911742658228331.382023-09-11
1572022수원시장안동8687805423925661.32023-09-11
1582022수원시화서동328522530421819829943097625491.292023-09-11
1592022수원시매산로1가172141571955423301121.542023-09-11
1602022수원시매산로2가39526365426210033422981.332023-09-11
1612022수원시매산로3가28816261111877625442021.432023-09-11
1622022수원시팔달로1가270252215111191.422023-09-11
1632022수원시팔달로2가5005003316118301.672023-09-11
1642022수원시팔달로3가4563902117716311.452023-09-11