Overview

Dataset statistics

Number of variables14
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 MiB
Average record size in memory127.0 B

Variable types

Categorical4
Text2
Numeric7
DateTime1

Dataset

Description관내 주택외 건물 시가표준액 정보에 대한 데이터로 건물형태, 건물용도, 건물구조, 건물위치, 건물지붕, 물건지 지번주소, 연면적, 전용면적, 공용면적, 준공일자, 공부상 지목, 시가표준액 등의 항목을 제공합니다.
Author경기도 양주시
URLhttps://www.data.go.kr/data/3077277/fileData.do

Alerts

시군명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
건물구조 is highly overall correlated with 공용면적 and 1 other fieldsHigh correlation
건물위치 is highly overall correlated with 공용면적 and 1 other fieldsHigh correlation
연면적 is highly overall correlated with 전용면적 and 1 other fieldsHigh correlation
전용면적 is highly overall correlated with 연면적 and 1 other fieldsHigh correlation
공용면적 is highly overall correlated with 건물구조 and 1 other fieldsHigh correlation
시가표준액 is highly overall correlated with 건물구조 and 2 other fieldsHigh correlation
건물형태 is highly overall correlated with 건물위치High correlation
시가표준액 is highly skewed (γ1 = 25.34207839)Skewed
전용면적 has 463 (4.6%) zerosZeros
공용면적 has 7852 (78.5%) zerosZeros

Reproduction

Analysis started2023-12-12 20:28:04.579464
Analysis finished2023-12-12 20:28:13.183218
Duration8.6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

CONSTANT 

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

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도 양주시
2nd row경기도 양주시
3rd row경기도 양주시
4th row경기도 양주시
5th row경기도 양주시

Common Values

ValueCountFrequency (%)
경기도 양주시 10000
100.0%

Length

2023-12-13T05:28:13.261876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:28:13.355724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 10000
50.0%
양주시 10000
50.0%

건물형태
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반
8354 
집합
1646 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반 8354
83.5%
집합 1646
 
16.5%

Length

2023-12-13T05:28:13.461030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:28:13.559263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반 8354
83.5%
집합 1646
 
16.5%

건물용도
Text

Distinct131
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T05:28:13.816541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters30000
Distinct characters32
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)0.2%

Sample

1st row5AC
2nd row311
3rd row511
4th row511
5th row511
ValueCountFrequency (%)
511 2204
22.0%
512 1436
14.4%
345 1378
13.8%
711 843
 
8.4%
362 673
 
6.7%
311 635
 
6.3%
53z 441
 
4.4%
199 233
 
2.3%
31b 154
 
1.5%
421 121
 
1.2%
Other values (121) 1882
18.8%
2023-12-13T05:28:14.298829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 10695
35.6%
5 6072
20.2%
3 4377
14.6%
2 2450
 
8.2%
4 2304
 
7.7%
7 1110
 
3.7%
9 875
 
2.9%
6 872
 
2.9%
Z 463
 
1.5%
B 173
 
0.6%
Other values (22) 609
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 28947
96.5%
Uppercase Letter 1053
 
3.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
Z 463
44.0%
B 173
 
16.4%
A 127
 
12.1%
G 69
 
6.6%
D 57
 
5.4%
V 31
 
2.9%
C 30
 
2.8%
T 16
 
1.5%
Q 14
 
1.3%
F 13
 
1.2%
Other values (12) 60
 
5.7%
Decimal Number
ValueCountFrequency (%)
1 10695
36.9%
5 6072
21.0%
3 4377
15.1%
2 2450
 
8.5%
4 2304
 
8.0%
7 1110
 
3.8%
9 875
 
3.0%
6 872
 
3.0%
0 128
 
0.4%
8 64
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 28947
96.5%
Latin 1053
 
3.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
Z 463
44.0%
B 173
 
16.4%
A 127
 
12.1%
G 69
 
6.6%
D 57
 
5.4%
V 31
 
2.9%
C 30
 
2.8%
T 16
 
1.5%
Q 14
 
1.3%
F 13
 
1.2%
Other values (12) 60
 
5.7%
Common
ValueCountFrequency (%)
1 10695
36.9%
5 6072
21.0%
3 4377
15.1%
2 2450
 
8.5%
4 2304
 
8.0%
7 1110
 
3.8%
9 875
 
3.0%
6 872
 
3.0%
0 128
 
0.4%
8 64
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 10695
35.6%
5 6072
20.2%
3 4377
14.6%
2 2450
 
8.2%
4 2304
 
7.7%
7 1110
 
3.7%
9 875
 
2.9%
6 872
 
2.9%
Z 463
 
1.5%
B 173
 
0.6%
Other values (22) 609
 
2.0%

건물구조
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.5393
Minimum11
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:28:14.471547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile21
Q121
median22
Q361
95-th percentile81
Maximum99
Range88
Interquartile range (IQR)40

Descriptive statistics

Standard deviation22.941087
Coefficient of variation (CV)0.59526476
Kurtosis-1.1222167
Mean38.5393
Median Absolute Deviation (MAD)1
Skewness0.76242238
Sum385393
Variance526.29348
MonotonicityNot monotonic
2023-12-13T05:28:14.618248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
21 3613
36.1%
22 2263
22.6%
81 1081
 
10.8%
61 929
 
9.3%
62 927
 
9.3%
31 376
 
3.8%
74 288
 
2.9%
51 138
 
1.4%
63 137
 
1.4%
41 101
 
1.0%
Other values (16) 147
 
1.5%
ValueCountFrequency (%)
11 50
 
0.5%
12 3
 
< 0.1%
21 3613
36.1%
22 2263
22.6%
23 5
 
0.1%
25 33
 
0.3%
26 8
 
0.1%
27 2
 
< 0.1%
31 376
 
3.8%
33 1
 
< 0.1%
ValueCountFrequency (%)
99 1
 
< 0.1%
83 4
 
< 0.1%
82 17
 
0.2%
81 1081
10.8%
77 3
 
< 0.1%
74 288
 
2.9%
73 5
 
0.1%
71 11
 
0.1%
65 2
 
< 0.1%
64 1
 
< 0.1%

건물위치
Real number (ℝ)

HIGH CORRELATION 

Distinct19
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.9762
Minimum1
Maximum19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:28:14.747243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q17
median8
Q310
95-th percentile17
Maximum19
Range18
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.4676557
Coefficient of variation (CV)0.38631667
Kurtosis0.28820546
Mean8.9762
Median Absolute Deviation (MAD)1
Skewness1.0113926
Sum89762
Variance12.024636
MonotonicityNot monotonic
2023-12-13T05:28:14.864234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
7 3116
31.2%
8 1740
17.4%
9 792
 
7.9%
17 688
 
6.9%
6 666
 
6.7%
10 497
 
5.0%
15 453
 
4.5%
5 417
 
4.2%
11 398
 
4.0%
13 299
 
3.0%
Other values (9) 934
 
9.3%
ValueCountFrequency (%)
1 43
 
0.4%
2 45
 
0.4%
3 29
 
0.3%
4 235
 
2.4%
5 417
 
4.2%
6 666
 
6.7%
7 3116
31.2%
8 1740
17.4%
9 792
 
7.9%
10 497
 
5.0%
ValueCountFrequency (%)
19 1
 
< 0.1%
18 12
 
0.1%
17 688
6.9%
16 139
 
1.4%
15 453
4.5%
14 158
 
1.6%
13 299
3.0%
12 272
 
2.7%
11 398
4.0%
10 497
5.0%

건물지붕
Real number (ℝ)

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean63.2372
Minimum11
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:28:15.005584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile11
Q131
median99
Q399
95-th percentile99
Maximum99
Range88
Interquartile range (IQR)68

Descriptive statistics

Standard deviation39.32737
Coefficient of variation (CV)0.62190245
Kurtosis-1.826377
Mean63.2372
Median Absolute Deviation (MAD)0
Skewness-0.24965767
Sum632372
Variance1546.642
MonotonicityNot monotonic
2023-12-13T05:28:15.119497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
99 5395
53.9%
11 2228
22.3%
31 2219
22.2%
41 76
 
0.8%
21 46
 
0.5%
22 34
 
0.3%
98 1
 
< 0.1%
42 1
 
< 0.1%
ValueCountFrequency (%)
11 2228
22.3%
21 46
 
0.5%
22 34
 
0.3%
31 2219
22.2%
41 76
 
0.8%
42 1
 
< 0.1%
98 1
 
< 0.1%
99 5395
53.9%
ValueCountFrequency (%)
99 5395
53.9%
98 1
 
< 0.1%
42 1
 
< 0.1%
41 76
 
0.8%
31 2219
22.2%
22 34
 
0.3%
21 46
 
0.5%
11 2228
22.3%

물건지 지번주소
Text

Distinct7455
Distinct (%)74.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T05:28:15.413975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length46
Mean length21.998
Min length13

Characters and Unicode

Total characters219980
Distinct characters303
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5771 ?
Unique (%)57.7%

Sample

1st row경기도 양주시 남방동 121-10
2nd row경기도 양주시 광적면 가납리 842-5
3rd row경기도 양주시 은현면 운암리 24-4
4th row경기도 양주시 광적면 덕도리 695
5th row경기도 양주시 은현면 운암리 467-8
ValueCountFrequency (%)
경기도 10000
19.7%
양주시 10000
19.7%
광적면 1493
 
2.9%
은현면 1355
 
2.7%
0001동 1247
 
2.5%
남면 1154
 
2.3%
백석읍 1086
 
2.1%
옥정동 936
 
1.8%
장흥면 835
 
1.6%
가납리 556
 
1.1%
Other values (5141) 22167
43.6%
2023-12-13T05:28:15.839331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
40829
18.6%
도 10529
 
4.8%
양 10528
 
4.8%
경 10210
 
4.6%
시 10171
 
4.6%
주 10160
 
4.6%
기 10099
 
4.6%
0 9947
 
4.5%
1 9309
 
4.2%
- 7810
 
3.6%
Other values (293) 90388
41.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 117754
53.5%
Decimal Number 51572
23.4%
Space Separator 40829
 
18.6%
Dash Punctuation 7810
 
3.6%
Other Punctuation 1792
 
0.8%
Uppercase Letter 136
 
0.1%
Letter Number 76
 
< 0.1%
Math Symbol 6
 
< 0.1%
Lowercase Letter 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 10529
 
8.9%
양 10528
 
8.9%
경 10210
 
8.7%
시 10171
 
8.6%
주 10160
 
8.6%
기 10099
 
8.6%
리 6126
 
5.2%
동 5807
 
4.9%
면 4843
 
4.1%
광 1993
 
1.7%
Other values (256) 37288
31.7%
Uppercase Letter
ValueCountFrequency (%)
V 54
39.7%
I 22
16.2%
M 20
 
14.7%
S 8
 
5.9%
A 6
 
4.4%
D 3
 
2.2%
U 3
 
2.2%
L 3
 
2.2%
P 3
 
2.2%
N 2
 
1.5%
Other values (8) 12
 
8.8%
Decimal Number
ValueCountFrequency (%)
0 9947
19.3%
1 9309
18.1%
2 5824
11.3%
3 4977
9.7%
4 4469
8.7%
6 4438
8.6%
5 4020
7.8%
9 3145
 
6.1%
7 2805
 
5.4%
8 2638
 
5.1%
Letter Number
ValueCountFrequency (%)
Ⅲ 31
40.8%
Ⅱ 30
39.5%
Ⅰ 15
19.7%
Other Punctuation
ValueCountFrequency (%)
, 1790
99.9%
. 2
 
0.1%
Space Separator
ValueCountFrequency (%)
40829
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7810
100.0%
Math Symbol
ValueCountFrequency (%)
+ 6
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 117754
53.5%
Common 102009
46.4%
Latin 217
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 10529
 
8.9%
양 10528
 
8.9%
경 10210
 
8.7%
시 10171
 
8.6%
주 10160
 
8.6%
기 10099
 
8.6%
리 6126
 
5.2%
동 5807
 
4.9%
면 4843
 
4.1%
광 1993
 
1.7%
Other values (256) 37288
31.7%
Latin
ValueCountFrequency (%)
V 54
24.9%
Ⅲ 31
14.3%
Ⅱ 30
13.8%
I 22
10.1%
M 20
 
9.2%
Ⅰ 15
 
6.9%
S 8
 
3.7%
A 6
 
2.8%
e 5
 
2.3%
D 3
 
1.4%
Other values (12) 23
10.6%
Common
ValueCountFrequency (%)
40829
40.0%
0 9947
 
9.8%
1 9309
 
9.1%
- 7810
 
7.7%
2 5824
 
5.7%
3 4977
 
4.9%
4 4469
 
4.4%
6 4438
 
4.4%
5 4020
 
3.9%
9 3145
 
3.1%
Other values (5) 7241
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 117754
53.5%
ASCII 102150
46.4%
Number Forms 76
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
40829
40.0%
0 9947
 
9.7%
1 9309
 
9.1%
- 7810
 
7.6%
2 5824
 
5.7%
3 4977
 
4.9%
4 4469
 
4.4%
6 4438
 
4.3%
5 4020
 
3.9%
9 3145
 
3.1%
Other values (24) 7382
 
7.2%
Hangul
ValueCountFrequency (%)
도 10529
 
8.9%
양 10528
 
8.9%
경 10210
 
8.7%
시 10171
 
8.6%
주 10160
 
8.6%
기 10099
 
8.6%
리 6126
 
5.2%
동 5807
 
4.9%
면 4843
 
4.1%
광 1993
 
1.7%
Other values (256) 37288
31.7%
Number Forms
ValueCountFrequency (%)
Ⅲ 31
40.8%
Ⅱ 30
39.5%
Ⅰ 15
19.7%

연면적
Real number (ℝ)

HIGH CORRELATION 

Distinct6125
Distinct (%)61.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean197.85324
Minimum0.8
Maximum21354.301
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:28:15.974098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.8
5-th percentile13.7975
Q147.29405
median108
Q3199.505
95-th percentile630.835
Maximum21354.301
Range21353.501
Interquartile range (IQR)152.21095

Descriptive statistics

Standard deviation418.20049
Coefficient of variation (CV)2.1136904
Kurtosis756.8543
Mean197.85324
Median Absolute Deviation (MAD)76
Skewness19.524875
Sum1978532.4
Variance174891.65
MonotonicityNot monotonic
2023-12-13T05:28:16.090996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18.0 193
 
1.9%
198.0 182
 
1.8%
27.0 57
 
0.6%
36.0 36
 
0.4%
330.0 35
 
0.4%
99.0 35
 
0.4%
96.0 34
 
0.3%
192.0 33
 
0.3%
196.0 32
 
0.3%
60.0 32
 
0.3%
Other values (6115) 9331
93.3%
ValueCountFrequency (%)
0.8 1
 
< 0.1%
1.0 1
 
< 0.1%
1.05 1
 
< 0.1%
1.4 3
< 0.1%
1.44 4
< 0.1%
1.49 1
 
< 0.1%
1.5 2
< 0.1%
1.65 1
 
< 0.1%
1.8217 1
 
< 0.1%
1.9 1
 
< 0.1%
ValueCountFrequency (%)
21354.3014 1
< 0.1%
10612.98 1
< 0.1%
9160.5139 1
< 0.1%
8009.88 1
< 0.1%
6926.1099 1
< 0.1%
6200.0 1
< 0.1%
5747.8 1
< 0.1%
4977.78 1
< 0.1%
4973.78 1
< 0.1%
4947.18 1
< 0.1%

전용면적
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct5457
Distinct (%)54.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean190.49039
Minimum0
Maximum21265.87
Zeros463
Zeros (%)4.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:28:16.216219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.795
Q140
median100
Q3198
95-th percentile629.126
Maximum21265.87
Range21265.87
Interquartile range (IQR)158

Descriptive statistics

Standard deviation416.77815
Coefficient of variation (CV)2.1879222
Kurtosis756.31487
Mean190.49039
Median Absolute Deviation (MAD)74.1
Skewness19.522459
Sum1904903.9
Variance173704.03
MonotonicityNot monotonic
2023-12-13T05:28:16.324800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 463
 
4.6%
18.0 194
 
1.9%
198.0 184
 
1.8%
27.0 58
 
0.6%
36.0 40
 
0.4%
48.0 40
 
0.4%
96.0 39
 
0.4%
60.0 39
 
0.4%
99.0 35
 
0.4%
330.0 35
 
0.4%
Other values (5447) 8873
88.7%
ValueCountFrequency (%)
0.0 463
4.6%
0.05 1
 
< 0.1%
0.08 1
 
< 0.1%
0.3 1
 
< 0.1%
0.8 1
 
< 0.1%
1.0 1
 
< 0.1%
1.05 1
 
< 0.1%
1.4 3
 
< 0.1%
1.44 4
 
< 0.1%
1.49 1
 
< 0.1%
ValueCountFrequency (%)
21265.87 1
< 0.1%
10612.98 1
< 0.1%
9145.29 1
< 0.1%
8009.88 1
< 0.1%
6681.33 1
< 0.1%
6200.0 1
< 0.1%
5747.8 1
< 0.1%
4977.78 1
< 0.1%
4973.78 1
< 0.1%
4947.18 1
< 0.1%

공용면적
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct1639
Distinct (%)16.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.3628507
Minimum0
Maximum544.01
Zeros7852
Zeros (%)78.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:28:16.436606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile41.11723
Maximum544.01
Range544.01
Interquartile range (IQR)0

Descriptive statistics

Standard deviation25.966254
Coefficient of variation (CV)3.5266577
Kurtosis112.28209
Mean7.3628507
Median Absolute Deviation (MAD)0
Skewness8.5410832
Sum73628.507
Variance674.24636
MonotonicityNot monotonic
2023-12-13T05:28:16.558841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 7852
78.5%
16.234 21
 
0.2%
9.2264 16
 
0.2%
18.667 15
 
0.1%
81.354 15
 
0.1%
23.284 13
 
0.1%
13.4785 12
 
0.1%
15.9028 10
 
0.1%
10.6666 10
 
0.1%
13.298 9
 
0.1%
Other values (1629) 2027
 
20.3%
ValueCountFrequency (%)
0.0 7852
78.5%
0.0236 1
 
< 0.1%
0.1129 1
 
< 0.1%
0.1417 1
 
< 0.1%
0.1773 1
 
< 0.1%
0.2129 1
 
< 0.1%
0.2423 1
 
< 0.1%
0.2792 1
 
< 0.1%
0.2916 1
 
< 0.1%
0.2946 1
 
< 0.1%
ValueCountFrequency (%)
544.01 1
 
< 0.1%
534.06 1
 
< 0.1%
480.742 1
 
< 0.1%
480.45 1
 
< 0.1%
445.96 1
 
< 0.1%
402.08 1
 
< 0.1%
381.782 1
 
< 0.1%
368.35 1
 
< 0.1%
365.9707 1
 
< 0.1%
361.81 3
< 0.1%

준공일자
Date

Distinct3055
Distinct (%)30.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1900-01-01 00:00:00
Maximum2021-06-01 00:00:00
2023-12-13T05:28:16.675924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:16.830519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

공부상 지목
Categorical

Distinct24
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
08 대지
4716 
09 공장용지
2864 
28 잡종지
572 
04 목장용지
 
392
01 전
 
388
Other values (19)
1068 

Length

Max length8
Median length7
Mean length5.7936
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row08 대지
2nd row08 대지
3rd row09 공장용지
4th row09 공장용지
5th row09 공장용지

Common Values

ValueCountFrequency (%)
08 대지 4716
47.2%
09 공장용지 2864
28.6%
28 잡종지 572
 
5.7%
04 목장용지 392
 
3.9%
01 전 388
 
3.9%
13 창고용지 253
 
2.5%
02 답 158
 
1.6%
05 임야 132
 
1.3%
25 종교용지 114
 
1.1%
10 학교용지 95
 
0.9%
Other values (14) 316
 
3.2%

Length

2023-12-13T05:28:16.958591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
08 4716
23.6%
대지 4716
23.6%
09 2864
14.3%
공장용지 2864
14.3%
28 572
 
2.9%
잡종지 572
 
2.9%
04 392
 
2.0%
목장용지 392
 
2.0%
01 388
 
1.9%
전 388
 
1.9%
Other values (38) 2136
10.7%

시가표준액
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct8899
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean71076313
Minimum12600
Maximum1.1872992 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:28:17.084299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12600
5-th percentile692431.2
Q15009850
median26042860
Q379554576
95-th percentile2.3844612 × 108
Maximum1.1872992 × 1010
Range1.1872979 × 1010
Interquartile range (IQR)74544726

Descriptive statistics

Standard deviation2.0939088 × 108
Coefficient of variation (CV)2.9460009
Kurtosis1150.7223
Mean71076313
Median Absolute Deviation (MAD)24068260
Skewness25.342078
Sum7.1076313 × 1011
Variance4.3844542 × 1016
MonotonicityNot monotonic
2023-12-13T05:28:17.214515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10276122 21
 
0.2%
28406582 16
 
0.2%
57392370 15
 
0.1%
96499516 15
 
0.1%
14273092 13
 
0.1%
720000 12
 
0.1%
17729501 12
 
0.1%
39852820 10
 
0.1%
33265755 10
 
0.1%
748800 9
 
0.1%
Other values (8889) 9867
98.7%
ValueCountFrequency (%)
12600 1
< 0.1%
15400 1
< 0.1%
24750 1
< 0.1%
34000 1
< 0.1%
41250 1
< 0.1%
47520 1
< 0.1%
48000 1
< 0.1%
51480 1
< 0.1%
54000 1
< 0.1%
57200 1
< 0.1%
ValueCountFrequency (%)
11872991578 1
< 0.1%
6348126028 1
< 0.1%
4130475717 1
< 0.1%
4121274990 1
< 0.1%
3759856800 1
< 0.1%
3343088700 1
< 0.1%
3063577400 1
< 0.1%
2523112200 1
< 0.1%
2279672100 1
< 0.1%
2217085920 1
< 0.1%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2022-11-02
10000 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-11-02
2nd row2022-11-02
3rd row2022-11-02
4th row2022-11-02
5th row2022-11-02

Common Values

ValueCountFrequency (%)
2022-11-02 10000
100.0%

Length

2023-12-13T05:28:17.708196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:28:17.801339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-11-02 10000
100.0%

Interactions

2023-12-13T05:28:11.895661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:06.860605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:07.565704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:08.409745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:09.174002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:10.047150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:10.829067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:11.998652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:06.952934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:07.674564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:08.501812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:09.292536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:10.165272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:10.948631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:12.139844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:07.058810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:07.810168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:08.600942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:09.400709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:10.291698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:11.370684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:12.237954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:07.170409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:07.946978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:08.696033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:09.521140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:10.427398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:11.475828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:12.346414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:07.285966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:08.051934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:08.789956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:09.626582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:10.536983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:11.597999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:12.492011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:07.378029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:08.181556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:08.912349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:09.731454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:10.625304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:11.703539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:12.625816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:07.467267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:08.298149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:09.040150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:09.918041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:10.721648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:28:11.797038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:28:17.882859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건물형태건물구조건물위치건물지붕연면적전용면적공용면적공부상 지목시가표준액
건물형태1.0000.4630.9090.2270.0410.0410.5100.5290.032
건물구조0.4631.0000.4390.6590.0000.0000.1630.4380.000
건물위치0.9090.4391.0000.3910.0000.0000.3850.7330.042
건물지붕0.2270.6590.3911.0000.0000.0000.1500.3720.008
연면적0.0410.0000.0000.0001.0001.0000.1750.1750.967
전용면적0.0410.0000.0000.0001.0001.0000.1750.1750.967
공용면적0.5100.1630.3850.1500.1750.1751.0000.2420.239
공부상 지목0.5290.4380.7330.3720.1750.1750.2421.0000.214
시가표준액0.0320.0000.0420.0080.9670.9670.2390.2141.000
2023-12-13T05:28:18.017706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건물형태공부상 지목
건물형태1.0000.421
공부상 지목0.4211.000
2023-12-13T05:28:18.116219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건물구조건물위치건물지붕연면적전용면적공용면적시가표준액건물형태공부상 지목
건물구조1.000-0.4890.155-0.0680.020-0.541-0.6300.3560.176
건물위치-0.4891.0000.006-0.154-0.2470.5770.2920.7480.372
건물지붕0.1550.0061.0000.0610.0200.2160.1590.2770.189
연면적-0.068-0.1540.0611.0000.972-0.0770.6490.0290.071
전용면적0.020-0.2470.0200.9721.000-0.2390.5760.0290.071
공용면적-0.5410.5770.216-0.077-0.2391.0000.3270.3920.091
시가표준액-0.6300.2920.1590.6490.5760.3271.0000.0230.087
건물형태0.3560.7480.2770.0290.0290.3920.0231.0000.421
공부상 지목0.1760.3720.1890.0710.0710.0910.0870.4211.000

Missing values

2023-12-13T05:28:12.832690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:28:13.076086image/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

시군명건물형태건물용도건물구조건물위치건물지붕물건지 지번주소연면적전용면적공용면적준공일자공부상 지목시가표준액데이터기준일자
666경기도 양주시일반5AC221199경기도 양주시 남방동 121-1038.9538.950.02016-07-0608 대지108670502022-11-02
35158경기도 양주시일반311211011경기도 양주시 광적면 가납리 842-5116.58116.580.02004-03-2508 대지749434532022-11-02
21660경기도 양주시일반51122631경기도 양주시 은현면 운암리 24-4197.01197.010.02001-06-1809 공장용지419631302022-11-02
38423경기도 양주시일반51173731경기도 양주시 광적면 덕도리 69518.018.00.01991-01-0109 공장용지3780002022-11-02
22731경기도 양주시일반51162711경기도 양주시 은현면 운암리 467-8164.93164.930.02005-09-0909 공장용지163280702022-11-02
39651경기도 양주시일반51161731경기도 양주시 광적면 석우리 485-2262.95262.950.01991-01-0109 공장용지84144002022-11-02
33564경기도 양주시집합51121999경기도 양주시 광적면 가납리 428, 0001동 0307호212.554131.281.3542011-10-1909 공장용지964995162022-11-02
55012경기도 양주시집합384211799경기도 양주시 옥정동 966-2, 폴리프라자 0001동 0207호221.7475124.5497.20752017-05-1908 대지2082209022022-11-02
17046경기도 양주시일반51274799경기도 양주시 백석읍 가업리 401-818.018.00.02013-12-3102 답6480002022-11-02
29042경기도 양주시일반51162731경기도 양주시 남면 경신리 273198.0198.00.02002-02-0109 공장용지100980002022-11-02
시군명건물형태건물용도건물구조건물위치건물지붕물건지 지번주소연면적전용면적공용면적준공일자공부상 지목시가표준액데이터기준일자
20768경기도 양주시일반33321899경기도 양주시 은현면 선암리 171-140.3240.320.02008-10-1712 주유소용지103703042022-11-02
22317경기도 양주시일반51241499경기도 양주시 은현면 운암리 360-123.023.00.02008-08-2504 목장용지64170002022-11-02
39699경기도 양주시일반51162731경기도 양주시 광적면 석우리 498-1127.5127.50.01998-01-0109 공장용지44625002022-11-02
54186경기도 양주시집합53Z211799경기도 양주시 옥정동 963-14, 센타프라자 0001동 0803호36.9810.036.9812018-02-0508 대지202027202022-11-02
48329경기도 양주시일반31B211311경기도 양주시 광사동 679-4152.145147.634.5152010-10-2008 대지870269402022-11-02
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