Overview

Dataset statistics

Number of variables10
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows581
Duplicate rows (%)5.8%
Total size in memory957.0 KiB
Average record size in memory98.0 B

Variable types

Categorical4
Numeric6

Dataset

Description일반건축물 대한 지방세 부과기준인 시가표준액을 제공합니다.활용업무: 시가표준액을 통해 물건별로 재산가액이 확인 가능합니다.
Author부산광역시 금정구
URLhttps://www.data.go.kr/data/15080091/fileData.do

Alerts

자치단체 has constant value ""Constant
관리년도 has constant value ""Constant
법정리 has constant value ""Constant
Dataset has 581 (5.8%) duplicate rowsDuplicates
건물시가표준액 is highly overall correlated with 연면적High correlation
연면적 is highly overall correlated with 건물시가표준액High correlation
특수지 is highly imbalanced (94.0%)Imbalance
건물동 is highly skewed (γ1 = 26.37082932)Skewed
건물시가표준액 is highly skewed (γ1 = 20.5870104)Skewed
부번 has 977 (9.8%) zerosZeros
건물동 has 121 (1.2%) zerosZeros

Reproduction

Analysis started2024-04-20 05:22:21.125146
Analysis finished2024-04-20 05:22:33.607637
Duration12.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

자치단체
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
26410
10000 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row26410
2nd row26410
3rd row26410
4th row26410
5th row26410

Common Values

ValueCountFrequency (%)
26410 10000
100.0%

Length

2024-04-20T05:22:33.778311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T05:22:33.992026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
26410 10000
100.0%

관리년도
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023
10000 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023
2nd row2023
3rd row2023
4th row2023
5th row2023

Common Values

ValueCountFrequency (%)
2023 10000
100.0%

Length

2024-04-20T05:22:34.238895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T05:22:34.529135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023 10000
100.0%

법정동
Real number (ℝ)

Distinct13
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean107.6258
Minimum101
Maximum113
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-20T05:22:34.795574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile103
Q1107
median108
Q3109
95-th percentile111
Maximum113
Range12
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.5437023
Coefficient of variation (CV)0.023634689
Kurtosis0.25903233
Mean107.6258
Median Absolute Deviation (MAD)1
Skewness-0.65223693
Sum1076258
Variance6.4704214
MonotonicityNot monotonic
2024-04-20T05:22:35.153779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
107 2261
22.6%
108 2015
20.2%
109 1647
16.5%
110 1263
12.6%
104 1063
10.6%
111 460
 
4.6%
103 318
 
3.2%
112 313
 
3.1%
101 310
 
3.1%
113 131
 
1.3%
Other values (3) 219
 
2.2%
ValueCountFrequency (%)
101 310
 
3.1%
102 103
 
1.0%
103 318
 
3.2%
104 1063
10.6%
105 79
 
0.8%
106 37
 
0.4%
107 2261
22.6%
108 2015
20.2%
109 1647
16.5%
110 1263
12.6%
ValueCountFrequency (%)
113 131
 
1.3%
112 313
 
3.1%
111 460
 
4.6%
110 1263
12.6%
109 1647
16.5%
108 2015
20.2%
107 2261
22.6%
106 37
 
0.4%
105 79
 
0.8%
104 1063
10.6%

법정리
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
10000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 10000
100.0%

Length

2024-04-20T05:22:35.551448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T05:22:35.840849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 10000
100.0%

특수지
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
9930 
2
 
70

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 9930
99.3%
2 70
 
0.7%

Length

2024-04-20T05:22:36.143529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T05:22:36.443466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 9930
99.3%
2 70
 
0.7%

본번
Real number (ℝ)

Distinct855
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean387.2029
Minimum1
Maximum1641
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-20T05:22:36.773654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile33
Q1145.75
median297
Q3556
95-th percentile1027
Maximum1641
Range1640
Interquartile range (IQR)410.25

Descriptive statistics

Standard deviation315.06724
Coefficient of variation (CV)0.81370061
Kurtosis-0.092570193
Mean387.2029
Median Absolute Deviation (MAD)182
Skewness0.95916879
Sum3872029
Variance99267.363
MonotonicityNot monotonic
2024-04-20T05:22:37.259210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1027 573
 
5.7%
302 318
 
3.2%
87 249
 
2.5%
292 155
 
1.6%
207 147
 
1.5%
162 129
 
1.3%
420 128
 
1.3%
981 124
 
1.2%
297 119
 
1.2%
652 118
 
1.2%
Other values (845) 7940
79.4%
ValueCountFrequency (%)
1 8
 
0.1%
2 9
 
0.1%
3 13
 
0.1%
4 5
 
0.1%
5 8
 
0.1%
6 1
 
< 0.1%
7 4
 
< 0.1%
8 21
0.2%
9 36
0.4%
10 2
 
< 0.1%
ValueCountFrequency (%)
1641 3
< 0.1%
1575 1
 
< 0.1%
1520 3
< 0.1%
1496 1
 
< 0.1%
1494 3
< 0.1%
1482 1
 
< 0.1%
1466 2
< 0.1%
1462 1
 
< 0.1%
1449 1
 
< 0.1%
1421 3
< 0.1%

부번
Real number (ℝ)

ZEROS 

Distinct382
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.3425
Minimum0
Maximum1918
Zeros977
Zeros (%)9.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-20T05:22:37.681521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median7
Q319
95-th percentile75
Maximum1918
Range1918
Interquartile range (IQR)18

Descriptive statistics

Standard deviation160.32243
Coefficient of variation (CV)4.5362504
Kurtosis78.004208
Mean35.3425
Median Absolute Deviation (MAD)6
Skewness8.5053717
Sum353425
Variance25703.282
MonotonicityNot monotonic
2024-04-20T05:22:38.167221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1667
 
16.7%
0 977
 
9.8%
2 530
 
5.3%
4 494
 
4.9%
9 456
 
4.6%
3 383
 
3.8%
7 374
 
3.7%
6 317
 
3.2%
11 316
 
3.2%
5 314
 
3.1%
Other values (372) 4172
41.7%
ValueCountFrequency (%)
0 977
9.8%
1 1667
16.7%
2 530
 
5.3%
3 383
 
3.8%
4 494
 
4.9%
5 314
 
3.1%
6 317
 
3.2%
7 374
 
3.7%
8 248
 
2.5%
9 456
 
4.6%
ValueCountFrequency (%)
1918 1
< 0.1%
1916 1
< 0.1%
1907 1
< 0.1%
1902 1
< 0.1%
1885 1
< 0.1%
1877 1
< 0.1%
1862 1
< 0.1%
1849 1
< 0.1%
1843 1
< 0.1%
1840 1
< 0.1%

건물동
Real number (ℝ)

SKEWED  ZEROS 

Distinct98
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.8902
Minimum0
Maximum9999
Zeros121
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-20T05:22:38.616450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile109
Maximum9999
Range9999
Interquartile range (IQR)0

Descriptive statistics

Standard deviation332.35172
Coefficient of variation (CV)11.503961
Kurtosis715.99005
Mean28.8902
Median Absolute Deviation (MAD)0
Skewness26.370829
Sum288902
Variance110457.67
MonotonicityNot monotonic
2024-04-20T05:22:39.186829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 7871
78.7%
2 429
 
4.3%
101 229
 
2.3%
3 153
 
1.5%
0 121
 
1.2%
102 85
 
0.9%
103 83
 
0.8%
201 81
 
0.8%
301 55
 
0.5%
105 52
 
0.5%
Other values (88) 841
 
8.4%
ValueCountFrequency (%)
0 121
 
1.2%
1 7871
78.7%
2 429
 
4.3%
3 153
 
1.5%
4 51
 
0.5%
5 48
 
0.5%
6 24
 
0.2%
7 15
 
0.1%
8 17
 
0.2%
9 5
 
0.1%
ValueCountFrequency (%)
9999 1
 
< 0.1%
9002 1
 
< 0.1%
9001 11
 
0.1%
1000 19
 
0.2%
401 5
 
0.1%
302 7
 
0.1%
301 55
0.5%
216 8
 
0.1%
212 7
 
0.1%
208 7
 
0.1%

건물시가표준액
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct7516
Distinct (%)75.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2901682 × 108
Minimum0
Maximum2.4019915 × 1010
Zeros4
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-20T05:22:39.606887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile498560
Q17952100
median35513317
Q399738199
95-th percentile4.2741761 × 108
Maximum2.4019915 × 1010
Range2.4019915 × 1010
Interquartile range (IQR)91786099

Descriptive statistics

Standard deviation5.5592492 × 108
Coefficient of variation (CV)4.3089338
Kurtosis633.41591
Mean1.2901682 × 108
Median Absolute Deviation (MAD)31490038
Skewness20.58701
Sum1.2901682 × 1012
Variance3.0905252 × 1017
MonotonicityNot monotonic
2024-04-20T05:22:40.072064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
498560 553
 
5.5%
39872400 41
 
0.4%
991800 40
 
0.4%
43346690 33
 
0.3%
34654567 33
 
0.3%
2528543 33
 
0.3%
47472546 33
 
0.3%
96183400 32
 
0.3%
34655983 26
 
0.3%
1561400 24
 
0.2%
Other values (7506) 9152
91.5%
ValueCountFrequency (%)
0 4
< 0.1%
12000 1
 
< 0.1%
42000 1
 
< 0.1%
90000 1
 
< 0.1%
100000 1
 
< 0.1%
105000 1
 
< 0.1%
157500 1
 
< 0.1%
160000 1
 
< 0.1%
162000 3
< 0.1%
168000 1
 
< 0.1%
ValueCountFrequency (%)
24019915094 1
< 0.1%
18321946201 1
< 0.1%
17424322933 1
< 0.1%
11248074387 1
< 0.1%
10429578644 1
< 0.1%
9706452071 1
< 0.1%
9369463243 1
< 0.1%
9184008069 1
< 0.1%
8849190120 1
< 0.1%
8771127680 1
< 0.1%

연면적
Real number (ℝ)

HIGH CORRELATION 

Distinct6465
Distinct (%)64.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean290.50691
Minimum1
Maximum38941.86
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-20T05:22:40.439910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.558
Q134.39
median73.65
Q3198.815
95-th percentile979.069
Maximum38941.86
Range38940.86
Interquartile range (IQR)164.425

Descriptive statistics

Standard deviation1045.6576
Coefficient of variation (CV)3.5994243
Kurtosis381.11336
Mean290.50691
Median Absolute Deviation (MAD)55.45
Skewness15.309606
Sum2905069.1
Variance1093399.9
MonotonicityNot monotonic
2024-04-20T05:22:40.873617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.558 553
 
5.5%
18.0 58
 
0.6%
44.7 41
 
0.4%
8.7 40
 
0.4%
12.29 33
 
0.3%
50.22 33
 
0.3%
39.202 33
 
0.3%
51.9345 33
 
0.3%
615.4 32
 
0.3%
39.248 26
 
0.3%
Other values (6455) 9118
91.2%
ValueCountFrequency (%)
1.0 2
 
< 0.1%
1.558 553
5.5%
2.0 1
 
< 0.1%
2.1 3
 
< 0.1%
2.4 3
 
< 0.1%
2.8 1
 
< 0.1%
3.0 8
 
0.1%
3.08 1
 
< 0.1%
3.15 1
 
< 0.1%
3.4 1
 
< 0.1%
ValueCountFrequency (%)
38941.86 1
< 0.1%
32554.33 1
< 0.1%
25863.71 1
< 0.1%
21969.33 1
< 0.1%
18467.5 1
< 0.1%
17147.26 1
< 0.1%
16655.64 1
< 0.1%
15067.3 1
< 0.1%
13590.06 1
< 0.1%
12285.82 1
< 0.1%

Interactions

2024-04-20T05:22:31.280644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:23.096365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:24.694751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:26.267605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:28.052481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:29.648690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:31.479965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:23.298280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:24.939898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:26.554783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:28.318958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:29.918175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:31.738220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:23.513887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:25.302806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:26.794852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:28.599164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:30.213759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:32.034261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:23.874690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:25.564987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:27.148648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:28.833644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:30.459271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:32.312268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:24.139321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:25.843775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:27.404091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:29.087176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:30.792067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:32.714805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:24.408996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:26.047515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:27.759661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:29.364619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:22:31.005327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-20T05:22:41.159619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동특수지본번부번건물동건물시가표준액연면적
법정동1.0000.1740.7510.3860.1240.0060.060
특수지0.1741.0000.1650.0000.0780.0000.000
본번0.7510.1651.0000.2130.0660.1870.307
부번0.3860.0000.2131.0000.0000.0000.000
건물동0.1240.0780.0660.0001.0000.0000.000
건물시가표준액0.0060.0000.1870.0000.0001.0000.911
연면적0.0600.0000.3070.0000.0000.9111.000
2024-04-20T05:22:41.457892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동본번부번건물동건물시가표준액연면적특수지
법정동1.000-0.1190.119-0.1060.0050.0750.133
본번-0.1191.000-0.1710.244-0.115-0.1560.127
부번0.119-0.1711.000-0.3430.0990.1440.000
건물동-0.1060.244-0.3431.000-0.247-0.2980.129
건물시가표준액0.005-0.1150.099-0.2471.0000.8270.000
연면적0.075-0.1560.144-0.2980.8271.0000.000
특수지0.1330.1270.0000.1290.0000.0001.000

Missing values

2024-04-20T05:22:33.127361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-20T05:22:33.480763image/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

자치단체관리년도법정동법정리특수지본번부번건물동건물시가표준액연면적
6717264102023107011026121227807774507.52
1031826410202310801422321132552156387.06
11250264102023108016502163294720149.28
735126410202310701102711104985601.558
1102226410202310801617111217752749698.14
85382641020231080115432114091342138.11
56182641020231070141361223310712.08
632641020231010120321135283500163.98
782326410202310701102711164985601.558
13217264102023109012871117167589185.72
자치단체관리년도법정동법정리특수지본번부번건물동건물시가표준액연면적
1125126410202310801650111018375651470.1635
744326410202310701102711114985601.558
157862641020231100120111122308370296.4
86542641020231080120391203091673195.1201
16783264102023110013021081558646382.64
1267626410202310901225361184000189408.24
2376264102023104011161022370936053.52
1437426410202310901579612063716160.2
182492641020231110113481120579671399.39
521626410202310701185110001343347155.2

Duplicate rows

Most frequently occurring

자치단체관리년도법정동법정리특수지본번부번건물동건물시가표준액연면적# duplicates
22026410202310701102711054985601.55848
21826410202310701102711024985601.55847
21726410202310701102711014985601.55846
22826410202310701102711144985601.55845
23026410202310701102711164985601.55844
22626410202310701102711114985601.55843
22726410202310701102711124985601.55843
22526410202310701102711104985601.55842
35226410202310801652451013987240044.741
22926410202310701102711154985601.55840