Overview

Dataset statistics

Number of variables16
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 MiB
Average record size in memory145.0 B

Variable types

Numeric8
Categorical5
Text2
DateTime1

Dataset

Description경기도 구리시 지역내 주택을 제외한 건물들의 시가표준액 정보를 제공(주소, 면적, 준공일자, 시가표준액 등)합니다.
URLhttps://www.data.go.kr/data/15029571/fileData.do

Alerts

관리기관명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
번호 is highly overall correlated with 기준년월일High 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
시가표준액 is highly overall correlated with 연면적 and 1 other fieldsHigh correlation
기준년월일 is highly overall correlated with 번호High correlation
공부상_지목 is highly imbalanced (72.5%)Imbalance
연면적 is highly skewed (γ1 = 44.09989858)Skewed
전용면적 is highly skewed (γ1 = 46.61814281)Skewed
공용면적 is highly skewed (γ1 = 26.42886946)Skewed
번호 has unique valuesUnique
전용면적 has 1704 (17.0%) zerosZeros
공용면적 has 5049 (50.5%) zerosZeros

Reproduction

Analysis started2023-12-12 13:19:41.734919
Analysis finished2023-12-12 13:19:52.299534
Duration10.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31887.853
Minimum1
Maximum63685
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T22:19:52.386898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3137.7
Q115904.75
median31931.5
Q347960.25
95-th percentile60496.2
Maximum63685
Range63684
Interquartile range (IQR)32055.5

Descriptive statistics

Standard deviation18430.697
Coefficient of variation (CV)0.57798489
Kurtosis-1.2104815
Mean31887.853
Median Absolute Deviation (MAD)16029
Skewness-0.0062745028
Sum3.1887853 × 108
Variance3.396906 × 108
MonotonicityNot monotonic
2023-12-12T22:19:52.526871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
49479 1
 
< 0.1%
2471 1
 
< 0.1%
29741 1
 
< 0.1%
40093 1
 
< 0.1%
43838 1
 
< 0.1%
58953 1
 
< 0.1%
48440 1
 
< 0.1%
18100 1
 
< 0.1%
47418 1
 
< 0.1%
20915 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
37 1
< 0.1%
38 1
< 0.1%
60 1
< 0.1%
64 1
< 0.1%
70 1
< 0.1%
75 1
< 0.1%
92 1
< 0.1%
ValueCountFrequency (%)
63685 1
< 0.1%
63670 1
< 0.1%
63668 1
< 0.1%
63658 1
< 0.1%
63649 1
< 0.1%
63636 1
< 0.1%
63626 1
< 0.1%
63625 1
< 0.1%
63623 1
< 0.1%
63619 1
< 0.1%

기준년월일
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2018
3650 
2017
3437 
2019
2913 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019
2nd row2018
3rd row2019
4th row2019
5th row2017

Common Values

ValueCountFrequency (%)
2018 3650
36.5%
2017 3437
34.4%
2019 2913
29.1%

Length

2023-12-12T22:19:52.665873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:19:52.753103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018 3650
36.5%
2017 3437
34.4%
2019 2913
29.1%

건물형태
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반
6027 
집합
3973 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반 6027
60.3%
집합 3973
39.7%

Length

2023-12-12T22:19:52.868804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:19:52.973707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반 6027
60.3%
집합 3973
39.7%
Distinct113
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T22:19:53.172653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters30000
Distinct characters28
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

Unique22 ?
Unique (%)0.2%

Sample

1st row512
2nd row362
3rd row311
4th row362
5th row362
ValueCountFrequency (%)
345 3007
30.1%
512 1241
12.4%
533 1072
 
10.7%
311 802
 
8.0%
362 782
 
7.8%
911 444
 
4.4%
53z 280
 
2.8%
302 275
 
2.8%
344 235
 
2.4%
421 170
 
1.7%
Other values (103) 1692
16.9%
2023-12-12T22:19:53.527262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 8478
28.3%
5 5885
19.6%
1 5495
18.3%
4 4491
15.0%
2 2635
 
8.8%
6 1005
 
3.4%
9 709
 
2.4%
0 362
 
1.2%
Z 294
 
1.0%
B 149
 
0.5%
Other values (18) 497
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 29192
97.3%
Uppercase Letter 808
 
2.7%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
Z 294
36.4%
B 149
18.4%
A 111
 
13.7%
D 69
 
8.5%
V 38
 
4.7%
C 27
 
3.3%
G 20
 
2.5%
Q 19
 
2.4%
K 18
 
2.2%
I 15
 
1.9%
Other values (8) 48
 
5.9%
Decimal Number
ValueCountFrequency (%)
3 8478
29.0%
5 5885
20.2%
1 5495
18.8%
4 4491
15.4%
2 2635
 
9.0%
6 1005
 
3.4%
9 709
 
2.4%
0 362
 
1.2%
8 67
 
0.2%
7 65
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 29192
97.3%
Latin 808
 
2.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
Z 294
36.4%
B 149
18.4%
A 111
 
13.7%
D 69
 
8.5%
V 38
 
4.7%
C 27
 
3.3%
G 20
 
2.5%
Q 19
 
2.4%
K 18
 
2.2%
I 15
 
1.9%
Other values (8) 48
 
5.9%
Common
ValueCountFrequency (%)
3 8478
29.0%
5 5885
20.2%
1 5495
18.8%
4 4491
15.4%
2 2635
 
9.0%
6 1005
 
3.4%
9 709
 
2.4%
0 362
 
1.2%
8 67
 
0.2%
7 65
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 8478
28.3%
5 5885
19.6%
1 5495
18.3%
4 4491
15.0%
2 2635
 
8.8%
6 1005
 
3.4%
9 709
 
2.4%
0 362
 
1.2%
Z 294
 
1.0%
B 149
 
0.5%
Other values (18) 497
 
1.7%

건물구조
Real number (ℝ)

Distinct21
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.3687
Minimum11
Maximum81
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T22:19:53.662241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile21
Q121
median21
Q321
95-th percentile63
Maximum81
Range70
Interquartile range (IQR)0

Descriptive statistics

Standard deviation14.71222
Coefficient of variation (CV)0.55794255
Kurtosis4.1341632
Mean26.3687
Median Absolute Deviation (MAD)0
Skewness2.3156689
Sum263687
Variance216.44941
MonotonicityNot monotonic
2023-12-12T22:19:53.799419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
21 7118
71.2%
22 702
 
7.0%
31 480
 
4.8%
11 442
 
4.4%
61 271
 
2.7%
74 229
 
2.3%
62 217
 
2.2%
67 146
 
1.5%
63 116
 
1.2%
41 115
 
1.1%
Other values (11) 164
 
1.6%
ValueCountFrequency (%)
11 442
 
4.4%
12 3
 
< 0.1%
21 7118
71.2%
22 702
 
7.0%
25 5
 
0.1%
26 15
 
0.1%
27 1
 
< 0.1%
31 480
 
4.8%
41 115
 
1.1%
45 11
 
0.1%
ValueCountFrequency (%)
81 82
 
0.8%
74 229
2.3%
71 6
 
0.1%
69 1
 
< 0.1%
67 146
1.5%
65 3
 
< 0.1%
63 116
1.2%
62 217
2.2%
61 271
2.7%
51 36
 
0.4%

건물위치
Real number (ℝ)

Distinct22
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.5016
Minimum1
Maximum22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T22:19:53.950965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9
Q114
median16
Q318
95-th percentile20
Maximum22
Range21
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.1968452
Coefficient of variation (CV)0.20622679
Kurtosis2.1229707
Mean15.5016
Median Absolute Deviation (MAD)2
Skewness-0.97186494
Sum155016
Variance10.219819
MonotonicityNot monotonic
2023-12-12T22:19:54.061932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
17 1693
16.9%
14 1421
14.2%
15 1176
11.8%
16 1158
11.6%
18 1021
10.2%
19 771
7.7%
13 765
7.6%
21 485
 
4.9%
12 353
 
3.5%
20 236
 
2.4%
Other values (12) 921
9.2%
ValueCountFrequency (%)
1 27
 
0.3%
2 18
 
0.2%
3 4
 
< 0.1%
4 59
 
0.6%
5 19
 
0.2%
6 11
 
0.1%
7 44
 
0.4%
8 143
1.4%
9 202
2.0%
10 170
1.7%
ValueCountFrequency (%)
22 14
 
0.1%
21 485
 
4.9%
20 236
 
2.4%
19 771
7.7%
18 1021
10.2%
17 1693
16.9%
16 1158
11.6%
15 1176
11.8%
14 1421
14.2%
13 765
7.6%

건물지붕
Real number (ℝ)

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.2641
Minimum11
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T22:19:54.176298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile11
Q111
median11
Q399
95-th percentile99
Maximum99
Range88
Interquartile range (IQR)88

Descriptive statistics

Standard deviation39.572525
Coefficient of variation (CV)1.0619477
Kurtosis-1.158022
Mean37.2641
Median Absolute Deviation (MAD)0
Skewness0.90172128
Sum372641
Variance1565.9847
MonotonicityNot monotonic
2023-12-12T22:19:54.278705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
11 6664
66.6%
99 2890
28.9%
31 223
 
2.2%
21 112
 
1.1%
41 80
 
0.8%
22 31
 
0.3%
ValueCountFrequency (%)
11 6664
66.6%
21 112
 
1.1%
22 31
 
0.3%
31 223
 
2.2%
41 80
 
0.8%
99 2890
28.9%
ValueCountFrequency (%)
99 2890
28.9%
41 80
 
0.8%
31 223
 
2.2%
22 31
 
0.3%
21 112
 
1.1%
11 6664
66.6%
Distinct6010
Distinct (%)60.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T22:19:54.591813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length43
Mean length24.29
Min length13

Characters and Unicode

Total characters242900
Distinct characters290
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3829 ?
Unique (%)38.3%

Sample

1st row경기도 구리시 사노동 110
2nd row경기도 구리시 수택동 453-16
3rd row경기도 구리시 교문동 731-10
4th row경기도 구리시 교문동 737-15
5th row경기도 구리시 인창동 672-4 9000동 8121호
ValueCountFrequency (%)
구리시 10008
19.4%
경기도 10000
19.4%
수택동 2736
 
5.3%
인창동 2735
 
5.3%
교문동 2263
 
4.4%
0000동 1871
 
3.6%
갈매동 1204
 
2.3%
0001동 965
 
1.9%
9000동 829
 
1.6%
사노동 463
 
0.9%
Other values (3903) 18580
36.0%
2023-12-12T22:19:55.070510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
41654
17.1%
0 22446
 
9.2%
14405
 
5.9%
10658
 
4.4%
10562
 
4.3%
10026
 
4.1%
10015
 
4.1%
10012
 
4.1%
10007
 
4.1%
1 9306
 
3.8%
Other values (280) 93809
38.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 120288
49.5%
Decimal Number 72088
29.7%
Space Separator 41654
 
17.1%
Dash Punctuation 8305
 
3.4%
Uppercase Letter 369
 
0.2%
Lowercase Letter 122
 
0.1%
Open Punctuation 34
 
< 0.1%
Close Punctuation 34
 
< 0.1%
Letter Number 4
 
< 0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
14405
12.0%
10658
 
8.9%
10562
 
8.8%
10026
 
8.3%
10015
 
8.3%
10012
 
8.3%
10007
 
8.3%
4020
 
3.3%
2895
 
2.4%
2879
 
2.4%
Other values (245) 34809
28.9%
Uppercase Letter
ValueCountFrequency (%)
C 112
30.4%
A 77
20.9%
B 66
17.9%
W 28
 
7.6%
T 28
 
7.6%
K 18
 
4.9%
D 12
 
3.3%
M 8
 
2.2%
S 5
 
1.4%
I 4
 
1.1%
Other values (5) 11
 
3.0%
Decimal Number
ValueCountFrequency (%)
0 22446
31.1%
1 9306
12.9%
2 7053
 
9.8%
4 5924
 
8.2%
6 5802
 
8.0%
3 5083
 
7.1%
7 4571
 
6.3%
5 4347
 
6.0%
8 4201
 
5.8%
9 3355
 
4.7%
Lowercase Letter
ValueCountFrequency (%)
e 38
31.1%
o 28
23.0%
w 28
23.0%
r 28
23.0%
Space Separator
ValueCountFrequency (%)
41654
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8305
100.0%
Open Punctuation
ValueCountFrequency (%)
( 34
100.0%
Close Punctuation
ValueCountFrequency (%)
) 34
100.0%
Letter Number
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 122117
50.3%
Hangul 120288
49.5%
Latin 495
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
14405
12.0%
10658
 
8.9%
10562
 
8.8%
10026
 
8.3%
10015
 
8.3%
10012
 
8.3%
10007
 
8.3%
4020
 
3.3%
2895
 
2.4%
2879
 
2.4%
Other values (245) 34809
28.9%
Latin
ValueCountFrequency (%)
C 112
22.6%
A 77
15.6%
B 66
13.3%
e 38
 
7.7%
W 28
 
5.7%
T 28
 
5.7%
o 28
 
5.7%
w 28
 
5.7%
r 28
 
5.7%
K 18
 
3.6%
Other values (10) 44
 
8.9%
Common
ValueCountFrequency (%)
41654
34.1%
0 22446
18.4%
1 9306
 
7.6%
- 8305
 
6.8%
2 7053
 
5.8%
4 5924
 
4.9%
6 5802
 
4.8%
3 5083
 
4.2%
7 4571
 
3.7%
5 4347
 
3.6%
Other values (5) 7626
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 122608
50.5%
Hangul 120288
49.5%
Number Forms 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
41654
34.0%
0 22446
18.3%
1 9306
 
7.6%
- 8305
 
6.8%
2 7053
 
5.8%
4 5924
 
4.8%
6 5802
 
4.7%
3 5083
 
4.1%
7 4571
 
3.7%
5 4347
 
3.5%
Other values (24) 8117
 
6.6%
Hangul
ValueCountFrequency (%)
14405
12.0%
10658
 
8.9%
10562
 
8.8%
10026
 
8.3%
10015
 
8.3%
10012
 
8.3%
10007
 
8.3%
4020
 
3.3%
2895
 
2.4%
2879
 
2.4%
Other values (245) 34809
28.9%
Number Forms
ValueCountFrequency (%)
4
100.0%

연면적
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct5695
Distinct (%)57.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean159.38586
Minimum0.5
Maximum40186.57
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T22:19:55.251668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.5
5-th percentile10.04
Q135.58
median75.28
Q3157.305
95-th percentile482.0025
Maximum40186.57
Range40186.07
Interquartile range (IQR)121.725

Descriptive statistics

Standard deviation553.7325
Coefficient of variation (CV)3.4741632
Kurtosis2898.7474
Mean159.38586
Median Absolute Deviation (MAD)48.38
Skewness44.099899
Sum1593858.6
Variance306619.69
MonotonicityNot monotonic
2023-12-12T22:19:55.408073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11.28 86
 
0.9%
42.82 77
 
0.8%
18.0 77
 
0.8%
27.0 37
 
0.4%
13.32 32
 
0.3%
49.53 30
 
0.3%
40.65 27
 
0.3%
7.73 25
 
0.2%
2.53 23
 
0.2%
7.13 22
 
0.2%
Other values (5685) 9564
95.6%
ValueCountFrequency (%)
0.5 1
< 0.1%
0.5982 1
< 0.1%
0.668 1
< 0.1%
0.8 2
< 0.1%
0.89 2
< 0.1%
1.0 1
< 0.1%
1.2 1
< 0.1%
1.3 1
< 0.1%
1.44 1
< 0.1%
1.7 1
< 0.1%
ValueCountFrequency (%)
40186.57 1
 
< 0.1%
19660.29 1
 
< 0.1%
6029.86 1
 
< 0.1%
6026.94 3
< 0.1%
5794.7 1
 
< 0.1%
5735.46 1
 
< 0.1%
5405.08 1
 
< 0.1%
5362.98 1
 
< 0.1%
5280.31 1
 
< 0.1%
5068.8 1
 
< 0.1%

전용면적
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct4580
Distinct (%)45.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean134.53541
Minimum0
Maximum40186.57
Zeros1704
Zeros (%)17.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T22:19:55.561902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q118
median54
Q3130.53
95-th percentile431.709
Maximum40186.57
Range40186.57
Interquartile range (IQR)112.53

Descriptive statistics

Standard deviation542.94775
Coefficient of variation (CV)4.0357237
Kurtosis3142.3538
Mean134.53541
Median Absolute Deviation (MAD)49.5
Skewness46.618143
Sum1345354.1
Variance294792.25
MonotonicityNot monotonic
2023-12-12T22:19:55.717128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1704
 
17.0%
18.0 80
 
0.8%
32.16 78
 
0.8%
27.0 50
 
0.5%
36.0 32
 
0.3%
34.79 30
 
0.3%
29.25 28
 
0.3%
3.6 26
 
0.3%
72.0 22
 
0.2%
73.5 21
 
0.2%
Other values (4570) 7929
79.3%
ValueCountFrequency (%)
0.0 1704
17.0%
0.01 2
 
< 0.1%
0.06 1
 
< 0.1%
0.5 1
 
< 0.1%
0.5982 1
 
< 0.1%
0.668 1
 
< 0.1%
1.0 1
 
< 0.1%
1.3 1
 
< 0.1%
1.44 1
 
< 0.1%
1.9727 1
 
< 0.1%
ValueCountFrequency (%)
40186.57 1
 
< 0.1%
19660.29 1
 
< 0.1%
6029.86 1
 
< 0.1%
6026.94 3
< 0.1%
5794.7 1
 
< 0.1%
5362.98 1
 
< 0.1%
5280.31 1
 
< 0.1%
5068.8 1
 
< 0.1%
4650.4 3
< 0.1%
4534.3 1
 
< 0.1%

공용면적
Real number (ℝ)

SKEWED  ZEROS 

Distinct2712
Distinct (%)27.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.850453
Minimum0
Maximum5735.46
Zeros5049
Zeros (%)50.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T22:19:55.913606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q319.06
95-th percentile100.256
Maximum5735.46
Range5735.46
Interquartile range (IQR)19.06

Descriptive statistics

Standard deviation122.51461
Coefficient of variation (CV)4.9300755
Kurtosis1000.1228
Mean24.850453
Median Absolute Deviation (MAD)0
Skewness26.428869
Sum248504.53
Variance15009.829
MonotonicityNot monotonic
2023-12-12T22:19:56.058221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 5049
50.5%
11.28 88
 
0.9%
10.66 81
 
0.8%
13.32 32
 
0.3%
14.74 30
 
0.3%
4.13 28
 
0.3%
11.4 27
 
0.3%
2.53 23
 
0.2%
7.13 22
 
0.2%
11.93 20
 
0.2%
Other values (2702) 4600
46.0%
ValueCountFrequency (%)
0.0 5049
50.5%
0.0546 1
 
< 0.1%
0.1671 1
 
< 0.1%
0.2186 1
 
< 0.1%
0.253 1
 
< 0.1%
0.2541 1
 
< 0.1%
0.2603 1
 
< 0.1%
0.3508 1
 
< 0.1%
0.3736 1
 
< 0.1%
0.3974 1
 
< 0.1%
ValueCountFrequency (%)
5735.46 1
< 0.1%
5405.08 1
< 0.1%
3524.98 1
< 0.1%
3276.26 1
< 0.1%
1994.0 2
< 0.1%
1993.32 1
< 0.1%
1655.94 1
< 0.1%
1511.77 1
< 0.1%
1428.85 1
< 0.1%
1424.94 1
< 0.1%

공부상_지목
Categorical

IMBALANCE 

Distinct24
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
08 대지
8261 
01 전
 
382
28 잡종지
 
351
02 답
 
244
10 학교용지
 
151
Other values (19)
 
611

Length

Max length8
Median length5
Mean length5.0935
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row04 목장용지
2nd row08 대지
3rd row08 대지
4th row08 대지
5th row08 대지

Common Values

ValueCountFrequency (%)
08 대지 8261
82.6%
01 전 382
 
3.8%
28 잡종지 351
 
3.5%
02 답 244
 
2.4%
10 학교용지 151
 
1.5%
25 종교용지 99
 
1.0%
05 임야 92
 
0.9%
09 공장용지 81
 
0.8%
04 목장용지 78
 
0.8%
13 창고용지 60
 
0.6%
Other values (14) 201
 
2.0%

Length

2023-12-12T22:19:56.195194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
08 8261
41.3%
대지 8261
41.3%
01 382
 
1.9%
382
 
1.9%
28 351
 
1.8%
잡종지 351
 
1.8%
02 244
 
1.2%
244
 
1.2%
10 151
 
0.8%
학교용지 151
 
0.8%
Other values (38) 1222
 
6.1%

시가표준액
Real number (ℝ)

HIGH CORRELATION 

Distinct8682
Distinct (%)86.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean77973465
Minimum37440
Maximum2.1474836 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T22:19:56.327684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37440
5-th percentile1633795.5
Q111659221
median34159248
Q382227945
95-th percentile2.5917724 × 108
Maximum2.1474836 × 109
Range2.1474462 × 109
Interquartile range (IQR)70568724

Descriptive statistics

Standard deviation1.6496929 × 108
Coefficient of variation (CV)2.1157106
Kurtosis70.527963
Mean77973465
Median Absolute Deviation (MAD)27688608
Skewness7.2512101
Sum7.7973465 × 1011
Variance2.7214866 × 1016
MonotonicityNot monotonic
2023-12-12T22:19:56.501571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
32115000 55
 
0.5%
5106456 35
 
0.4%
5116608 26
 
0.3%
5126760 25
 
0.2%
31172960 22
 
0.2%
45125520 16
 
0.2%
2147483647 15
 
0.1%
34423350 14
 
0.1%
5778216 12
 
0.1%
5754240 12
 
0.1%
Other values (8672) 9768
97.7%
ValueCountFrequency (%)
37440 1
< 0.1%
73200 1
< 0.1%
74880 1
< 0.1%
82800 1
< 0.1%
92000 1
< 0.1%
97920 1
< 0.1%
99000 1
< 0.1%
106920 1
< 0.1%
117000 1
< 0.1%
120000 1
< 0.1%
ValueCountFrequency (%)
2147483647 15
0.1%
2115537379 1
 
< 0.1%
2092680000 2
 
< 0.1%
2040435000 1
 
< 0.1%
2011590000 1
 
< 0.1%
1962044040 1
 
< 0.1%
1914940656 1
 
< 0.1%
1886966340 1
 
< 0.1%
1814662080 1
 
< 0.1%
1810505060 1
 
< 0.1%

관리기관명
Categorical

CONSTANT 

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

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 구리시 10000
100.0%

Length

2023-12-12T22:19:56.631613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:19:56.720026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 10000
50.0%
구리시 10000
50.0%
Distinct1177
Distinct (%)11.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1923-12-31 00:00:00
Maximum2019-02-19 00:00:00
2023-12-12T22:19:57.107837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:57.237728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-06-29
10000 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-06-29
2nd row2023-06-29
3rd row2023-06-29
4th row2023-06-29
5th row2023-06-29

Common Values

ValueCountFrequency (%)
2023-06-29 10000
100.0%

Length

2023-12-12T22:19:57.377385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:19:57.478318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-06-29 10000
100.0%

Interactions

2023-12-12T22:19:51.032803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:44.256340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:45.162551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:46.035352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:47.007830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:47.867457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:48.782070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:49.775804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:51.135501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:44.374165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:45.270939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:46.196779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:47.125986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:47.972070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:48.890611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:49.892605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:51.254245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:44.468568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:45.385708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:46.325879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:47.227261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:48.067095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:48.993116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:50.308906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:51.359014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:44.546352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:45.487204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:46.422091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:47.326507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:48.162547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:49.123168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:50.416647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:51.473699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:44.629257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:45.573679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:46.545033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:47.442477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:48.279827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:49.244345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:50.535474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:51.589943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:44.744378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:45.688277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:46.657081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:47.557884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:48.408828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:49.386129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:50.691961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:51.710589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:44.924970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:45.802064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:46.792779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:47.652816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:48.533865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:49.527731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:50.828506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:51.818795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:45.039367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:45.909087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:46.903058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:47.756288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:48.663866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:49.654436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:50.934495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:19:57.543756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호기준년월일건물형태건물구조건물위치건물지붕연면적전용면적공용면적공부상_지목시가표준액
번호1.0000.9530.3170.1910.3830.3470.0420.0420.0320.1980.119
기준년월일0.9531.0000.0380.0780.0510.0930.0000.0110.0240.0000.013
건물형태0.3170.0381.0000.4890.5870.1670.0480.0450.0250.3500.146
건물구조0.1910.0780.4891.0000.4500.4830.0730.0810.0000.5970.107
건물위치0.3830.0510.5870.4501.0000.4570.0650.0690.0390.7440.109
건물지붕0.3470.0930.1670.4830.4571.0000.0000.0000.0090.3990.074
연면적0.0420.0000.0480.0730.0650.0001.0001.0000.2730.1060.672
전용면적0.0420.0110.0450.0810.0690.0001.0001.0000.0000.0780.653
공용면적0.0320.0240.0250.0000.0390.0090.2730.0001.0000.1720.484
공부상_지목0.1980.0000.3500.5970.7440.3990.1060.0780.1721.0000.306
시가표준액0.1190.0130.1460.1070.1090.0740.6720.6530.4840.3061.000
2023-12-12T22:19:57.721634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건물형태공부상_지목기준년월일
건물형태1.0000.2780.064
공부상_지목0.2781.0000.000
기준년월일0.0640.0001.000
2023-12-12T22:19:57.827709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호건물구조건물위치건물지붕연면적전용면적공용면적시가표준액기준년월일건물형태공부상_지목
번호1.000-0.0180.055-0.014-0.052-0.028-0.038-0.0470.9480.2430.073
건물구조-0.0181.000-0.4410.1920.0310.159-0.422-0.2860.0480.3670.254
건물위치0.055-0.4411.000-0.204-0.205-0.2810.366-0.0240.0300.4530.384
건물지붕-0.0140.192-0.2041.0000.0710.0920.0390.1130.0700.2040.205
연면적-0.0520.031-0.2050.0711.0000.824-0.0540.8540.0000.0320.050
전용면적-0.0280.159-0.2810.0920.8241.000-0.4460.6950.0110.0300.037
공용면적-0.038-0.4220.3660.039-0.054-0.4461.0000.1270.0160.0270.074
시가표준액-0.047-0.286-0.0240.1130.8540.6950.1271.0000.0080.1120.117
기준년월일0.9480.0480.0300.0700.0000.0110.0160.0081.0000.0640.000
건물형태0.2430.3670.4530.2040.0320.0300.0270.1120.0641.0000.278
공부상_지목0.0730.2540.3840.2050.0500.0370.0740.1170.0000.2781.000

Missing values

2023-12-12T22:19:51.972187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:19:52.197619image/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

번호기준년월일건물형태건물용도건물구조건물위치건물지붕물건지_지번주소연면적전용면적공용면적공부상_지목시가표준액관리기관명준공일자데이터기준일자
49478494792019일반51222811경기도 구리시 사노동 110198.0198.00.004 목장용지54846000경기도 구리시2003-03-272023-06-29
42083420842018일반362211411경기도 구리시 수택동 453-1675.975.90.008 대지25350600경기도 구리시1986-12-312023-06-29
56453564542019일반311311511경기도 구리시 교문동 731-1028.217227.360.857208 대지5711161경기도 구리시1991-12-312023-06-29
58847588482019일반362261511경기도 구리시 교문동 737-1564.8364.830.008 대지30492790경기도 구리시1990-12-312023-06-29
547354742017집합362211711경기도 구리시 인창동 672-4 9000동 8121호32.880.032.8808 대지14598720경기도 구리시1996-12-312023-06-29
23950239512018집합302211799경기도 구리시 갈매동 604-3 아름터프라자 0000동 0303호277.9149.13128.7708 대지254000600경기도 구리시2016-08-012023-06-29
14657146582017일반345211611경기도 구리시 수택동 561-3133.7438130.13.643808 대지104159671경기도 구리시2003-06-182023-06-29
12274122752017집합911211611경기도 구리시 교문동 735-7 구리미래타워 0001동 1203호42.8430.8212.0208 대지23219280경기도 구리시1998-12-312023-06-29
58111581122019일반302211711경기도 구리시 교문동 228287.3614269.218.161408 대지125979237경기도 구리시1996-12-312023-06-29
25337253382018집합345211511경기도 구리시 인창동 667-1 9000동 0103호32.8325.067.7708 대지18273178경기도 구리시1995-12-312023-06-29
번호기준년월일건물형태건물용도건물구조건물위치건물지붕물건지_지번주소연면적전용면적공용면적공부상_지목시가표준액관리기관명준공일자데이터기준일자
26676266772018집합533211599경기도 구리시 인창동 495-26 0000동 0106호8.820.08.8208 대지3445092경기도 구리시2005-10-242023-06-29
49609496102019일반51241899경기도 구리시 사노동 573-23158.4158.40.004 목장용지46411200경기도 구리시2006-05-112023-06-29
52764527652019일반311741099경기도 구리시 사노동 23018.018.00.001 전432000경기도 구리시2007-12-312023-06-29
33928339292018일반362211711경기도 구리시 교문동 228646.1605.2740.8308 대지356647200경기도 구리시1996-12-312023-06-29
32933329342018일반345211711경기도 구리시 교문동 735-1209.04209.040.008 대지91559520경기도 구리시1990-12-312023-06-29
59526595272019집합431211799경기도 구리시 교문동 282-1 중앙하이츠티움B동 0002동 0205호102.666.536.108 대지73051200경기도 구리시2006-10-012023-06-29
31179311802018일반345211411경기도 구리시 인창동 610-84195.310.0195.3108 대지57655512경기도 구리시1988-12-312023-06-29
15033150342017집합533211999경기도 구리시 수택동 534-2 0000동 0203호29.9120.029.91208 대지12895063경기도 구리시2005-10-302023-06-29
42807428082018일반512411099경기도 구리시 토평동 459-2246.84246.840.004 목장용지76767240경기도 구리시2006-07-242023-06-29
33228332292018일반423511222경기도 구리시 교문동 346-2266.066.00.008 대지14520000경기도 구리시1995-12-312023-06-29