Overview

Dataset statistics

Number of variables14
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows3
Duplicate rows (%)< 0.1%
Total size in memory1.2 MiB
Average record size in memory130.0 B

Variable types

Categorical6
Numeric6
Text2

Dataset

Description일반건축물에 대한 지방세 부과기준인 시가표준액을 물건지 및 금액으로 제공합니다. (물건지, 시가표준금액, 연면적, 결정일자 등)
URLhttps://www.data.go.kr/data/15080511/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
과세연도 has constant value ""Constant
법정리 has constant value ""Constant
Dataset has 3 (< 0.1%) duplicate rowsDuplicates
시가표준액 is highly overall correlated with 연면적High correlation
연면적 is highly overall correlated with 시가표준액High correlation
특수지 is highly imbalanced (97.2%)Imbalance
시가표준액 is highly skewed (γ1 = 34.71680853)Skewed
연면적 is highly skewed (γ1 = 27.53016821)Skewed
부번 has 2659 (26.6%) zerosZeros

Reproduction

Analysis started2023-12-12 03:26:38.942112
Analysis finished2023-12-12 03:26:47.580025
Duration8.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

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

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
광주광역시 10000
100.0%

Length

2023-12-12T12:26:47.691957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:26:47.853559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
광주광역시 10000
100.0%

시군구명
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
광산구 10000
100.0%

Length

2023-12-12T12:26:48.018786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:26:48.171332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
광산구 10000
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
29200
10000 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row29200
2nd row29200
3rd row29200
4th row29200
5th row29200

Common Values

ValueCountFrequency (%)
29200 10000
100.0%

Length

2023-12-12T12:26:48.345095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:26:48.511550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
29200 10000
100.0%

과세연도
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2021
10000 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021
2nd row2021
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2021 10000
100.0%

Length

2023-12-12T12:26:48.647964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:26:48.796045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 10000
100.0%

법정동
Real number (ℝ)

Distinct78
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean124.3562
Minimum101
Maximum202
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:26:48.947210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile101
Q1112
median119
Q3127
95-th percentile171
Maximum202
Range101
Interquartile range (IQR)15

Descriptive statistics

Standard deviation22.007048
Coefficient of variation (CV)0.17696784
Kurtosis4.5047847
Mean124.3562
Median Absolute Deviation (MAD)7
Skewness2.0805587
Sum1243562
Variance484.31015
MonotonicityNot monotonic
2023-12-12T12:26:49.172998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
109 764
 
7.6%
123 653
 
6.5%
115 607
 
6.1%
101 539
 
5.4%
119 520
 
5.2%
116 516
 
5.2%
114 510
 
5.1%
202 439
 
4.4%
118 415
 
4.2%
108 414
 
4.1%
Other values (68) 4623
46.2%
ValueCountFrequency (%)
101 539
5.4%
102 235
 
2.4%
104 110
 
1.1%
105 34
 
0.3%
106 75
 
0.8%
107 165
 
1.7%
108 414
4.1%
109 764
7.6%
110 11
 
0.1%
111 9
 
0.1%
ValueCountFrequency (%)
202 439
4.4%
178 6
 
0.1%
177 5
 
0.1%
176 31
 
0.3%
175 6
 
0.1%
174 4
 
< 0.1%
173 4
 
< 0.1%
172 3
 
< 0.1%
171 4
 
< 0.1%
170 7
 
0.1%

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

2023-12-12T12:26:49.348640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:26:49.467566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 10000
100.0%

특수지
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
9956 
2
 
33
7
 
11

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 9956
99.6%
2 33
 
0.3%
7 11
 
0.1%

Length

2023-12-12T12:26:49.609419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:26:49.733071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 9956
99.6%
2 33
 
0.3%
7 11
 
0.1%

본번
Real number (ℝ)

Distinct1415
Distinct (%)14.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean772.226
Minimum1
Maximum3206
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:26:49.871057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile89
Q1529.75
median755
Q3999
95-th percentile1576
Maximum3206
Range3205
Interquartile range (IQR)469.25

Descriptive statistics

Standard deviation392.96966
Coefficient of variation (CV)0.50887908
Kurtosis-0.11959748
Mean772.226
Median Absolute Deviation (MAD)237
Skewness0.20555446
Sum7722260
Variance154425.15
MonotonicityNot monotonic
2023-12-12T12:26:50.056207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
694 150
 
1.5%
273 127
 
1.3%
270 89
 
0.9%
688 80
 
0.8%
992 78
 
0.8%
668 62
 
0.6%
1 53
 
0.5%
735 50
 
0.5%
621 50
 
0.5%
683 49
 
0.5%
Other values (1405) 9212
92.1%
ValueCountFrequency (%)
1 53
0.5%
2 11
 
0.1%
3 12
 
0.1%
4 8
 
0.1%
5 10
 
0.1%
6 4
 
< 0.1%
7 2
 
< 0.1%
8 1
 
< 0.1%
9 8
 
0.1%
10 6
 
0.1%
ValueCountFrequency (%)
3206 1
 
< 0.1%
1771 5
0.1%
1770 1
 
< 0.1%
1769 2
 
< 0.1%
1757 1
 
< 0.1%
1753 1
 
< 0.1%
1752 1
 
< 0.1%
1734 1
 
< 0.1%
1731 1
 
< 0.1%
1727 1
 
< 0.1%

부번
Real number (ℝ)

ZEROS 

Distinct130
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.2604
Minimum0
Maximum321
Zeros2659
Zeros (%)26.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:26:50.222637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q39
95-th percentile33
Maximum321
Range321
Interquartile range (IQR)9

Descriptive statistics

Standard deviation17.120476
Coefficient of variation (CV)2.0725965
Kurtosis53.285586
Mean8.2604
Median Absolute Deviation (MAD)3
Skewness5.7979766
Sum82604
Variance293.1107
MonotonicityNot monotonic
2023-12-12T12:26:50.378021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2659
26.6%
1 1297
13.0%
2 689
 
6.9%
3 605
 
6.0%
4 536
 
5.4%
5 536
 
5.4%
6 377
 
3.8%
7 355
 
3.5%
8 326
 
3.3%
9 296
 
3.0%
Other values (120) 2324
23.2%
ValueCountFrequency (%)
0 2659
26.6%
1 1297
13.0%
2 689
 
6.9%
3 605
 
6.0%
4 536
 
5.4%
5 536
 
5.4%
6 377
 
3.8%
7 355
 
3.5%
8 326
 
3.3%
9 296
 
3.0%
ValueCountFrequency (%)
321 1
 
< 0.1%
295 1
 
< 0.1%
273 1
 
< 0.1%
210 1
 
< 0.1%
209 3
< 0.1%
207 1
 
< 0.1%
190 1
 
< 0.1%
189 1
 
< 0.1%
187 1
 
< 0.1%
179 1
 
< 0.1%

동
Real number (ℝ)

Distinct47
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.3084
Minimum0
Maximum7005
Zeros36
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:26:50.575955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum7005
Range7005
Interquartile range (IQR)0

Descriptive statistics

Standard deviation488.02707
Coefficient of variation (CV)12.739427
Kurtosis198.26069
Mean38.3084
Median Absolute Deviation (MAD)0
Skewness14.127818
Sum383084
Variance238170.42
MonotonicityNot monotonic
2023-12-12T12:26:50.793231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
1 9545
95.5%
2 138
 
1.4%
7001 44
 
0.4%
3 41
 
0.4%
0 36
 
0.4%
101 22
 
0.2%
110 22
 
0.2%
107 15
 
0.1%
401 11
 
0.1%
213 8
 
0.1%
Other values (37) 118
 
1.2%
ValueCountFrequency (%)
0 36
 
0.4%
1 9545
95.5%
2 138
 
1.4%
3 41
 
0.4%
4 4
 
< 0.1%
5 3
 
< 0.1%
6 1
 
< 0.1%
7 2
 
< 0.1%
8 1
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
7005 1
 
< 0.1%
7003 1
 
< 0.1%
7002 2
 
< 0.1%
7001 44
0.4%
6001 1
 
< 0.1%
617 2
 
< 0.1%
401 11
 
0.1%
313 7
 
0.1%
303 4
 
< 0.1%
302 4
 
< 0.1%

호
Text

Distinct566
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T12:26:51.374202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length4
Mean length4.1409
Min length4

Characters and Unicode

Total characters41409
Distinct characters19
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique316 ?
Unique (%)3.2%

Sample

1st row901011
2nd row0104
3rd row0101
4th row0001
5th row0113
ValueCountFrequency (%)
0101 1737
17.4%
0001 869
 
8.7%
0201 804
 
8.0%
0102 787
 
7.9%
0002 660
 
6.6%
0003 396
 
4.0%
0301 314
 
3.1%
0103 302
 
3.0%
0004 266
 
2.7%
0202 250
 
2.5%
Other values (556) 3615
36.1%
2023-12-12T12:26:52.113520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 21947
53.0%
1 10181
24.6%
2 3808
 
9.2%
3 1675
 
4.0%
4 974
 
2.4%
6 645
 
1.6%
5 639
 
1.5%
9 569
 
1.4%
8 520
 
1.3%
7 392
 
0.9%
Other values (9) 59
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 41350
99.9%
Uppercase Letter 35
 
0.1%
Dash Punctuation 19
 
< 0.1%
Lowercase Letter 5
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 21947
53.1%
1 10181
24.6%
2 3808
 
9.2%
3 1675
 
4.1%
4 974
 
2.4%
6 645
 
1.6%
5 639
 
1.5%
9 569
 
1.4%
8 520
 
1.3%
7 392
 
0.9%
Lowercase Letter
ValueCountFrequency (%)
m 1
20.0%
o 1
20.0%
v 1
20.0%
i 1
20.0%
e 1
20.0%
Uppercase Letter
ValueCountFrequency (%)
C 16
45.7%
A 11
31.4%
B 8
22.9%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 41369
99.9%
Latin 40
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 21947
53.1%
1 10181
24.6%
2 3808
 
9.2%
3 1675
 
4.0%
4 974
 
2.4%
6 645
 
1.6%
5 639
 
1.5%
9 569
 
1.4%
8 520
 
1.3%
7 392
 
0.9%
Latin
ValueCountFrequency (%)
C 16
40.0%
A 11
27.5%
B 8
20.0%
m 1
 
2.5%
o 1
 
2.5%
v 1
 
2.5%
i 1
 
2.5%
e 1
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41409
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 21947
53.0%
1 10181
24.6%
2 3808
 
9.2%
3 1675
 
4.0%
4 974
 
2.4%
6 645
 
1.6%
5 639
 
1.5%
9 569
 
1.4%
8 520
 
1.3%
7 392
 
0.9%
Other values (9) 59
 
0.1%

물건지
Text

Distinct9816
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T12:26:52.579812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length34
Mean length29.5684
Min length21

Characters and Unicode

Total characters295684
Distinct characters174
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9657 ?
Unique (%)96.6%

Sample

1st row광주광역시 광산구 진곡동 562 1동 901011호
2nd row광주광역시 광산구 신가동 1058 1동 104호
3rd row광주광역시 광산구 신창동 10-91 1동 101호
4th row광주광역시 광산구 안청동 730-19 1동 1호
5th row광주광역시 광산구 월계로 223-20 0001동 0113호
ValueCountFrequency (%)
광주광역시 10000
 
16.7%
광산구 10000
 
16.7%
0001동 5379
 
9.0%
1동 4166
 
6.9%
0101호 1161
 
1.9%
101호 576
 
1.0%
0201호 520
 
0.9%
0102호 467
 
0.8%
0001호 462
 
0.8%
1호 407
 
0.7%
Other values (4936) 26888
44.8%
2023-12-12T12:26:53.312903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
50837
17.2%
0 34470
 
11.7%
광 30115
 
10.2%
1 27402
 
9.3%
동 14919
 
5.0%
산 11334
 
3.8%
호 10032
 
3.4%
구 10016
 
3.4%
역 10000
 
3.4%
시 10000
 
3.4%
Other values (164) 86559
29.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 139103
47.0%
Decimal Number 100656
34.0%
Space Separator 50837
 
17.2%
Dash Punctuation 5048
 
1.7%
Uppercase Letter 35
 
< 0.1%
Lowercase Letter 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 30115
21.6%
동 14919
10.7%
산 11334
 
8.1%
호 10032
 
7.2%
구 10016
 
7.2%
역 10000
 
7.2%
시 10000
 
7.2%
주 10000
 
7.2%
로 5018
 
3.6%
길 2890
 
2.1%
Other values (144) 24779
17.8%
Decimal Number
ValueCountFrequency (%)
0 34470
34.2%
1 27402
27.2%
2 9353
 
9.3%
3 5700
 
5.7%
5 4473
 
4.4%
6 4001
 
4.0%
4 3981
 
4.0%
8 3873
 
3.8%
7 3825
 
3.8%
9 3578
 
3.6%
Lowercase Letter
ValueCountFrequency (%)
v 1
20.0%
e 1
20.0%
i 1
20.0%
o 1
20.0%
m 1
20.0%
Uppercase Letter
ValueCountFrequency (%)
C 16
45.7%
A 11
31.4%
B 8
22.9%
Space Separator
ValueCountFrequency (%)
50837
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5048
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 156541
52.9%
Hangul 139103
47.0%
Latin 40
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 30115
21.6%
동 14919
10.7%
산 11334
 
8.1%
호 10032
 
7.2%
구 10016
 
7.2%
역 10000
 
7.2%
시 10000
 
7.2%
주 10000
 
7.2%
로 5018
 
3.6%
길 2890
 
2.1%
Other values (144) 24779
17.8%
Common
ValueCountFrequency (%)
50837
32.5%
0 34470
22.0%
1 27402
17.5%
2 9353
 
6.0%
3 5700
 
3.6%
- 5048
 
3.2%
5 4473
 
2.9%
6 4001
 
2.6%
4 3981
 
2.5%
8 3873
 
2.5%
Other values (2) 7403
 
4.7%
Latin
ValueCountFrequency (%)
C 16
40.0%
A 11
27.5%
B 8
20.0%
v 1
 
2.5%
e 1
 
2.5%
i 1
 
2.5%
o 1
 
2.5%
m 1
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 156581
53.0%
Hangul 139103
47.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
50837
32.5%
0 34470
22.0%
1 27402
17.5%
2 9353
 
6.0%
3 5700
 
3.6%
- 5048
 
3.2%
5 4473
 
2.9%
6 4001
 
2.6%
4 3981
 
2.5%
8 3873
 
2.5%
Other values (10) 7443
 
4.8%
Hangul
ValueCountFrequency (%)
광 30115
21.6%
동 14919
10.7%
산 11334
 
8.1%
호 10032
 
7.2%
구 10016
 
7.2%
역 10000
 
7.2%
시 10000
 
7.2%
주 10000
 
7.2%
로 5018
 
3.6%
길 2890
 
2.1%
Other values (144) 24779
17.8%

시가표준액
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct9245
Distinct (%)92.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1315566 × 108
Minimum17010
Maximum2.3574188 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:26:53.528363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum17010
5-th percentile1309875
Q113506725
median45810385
Q31.1249955 × 108
95-th percentile4.0053075 × 108
Maximum2.3574188 × 1010
Range2.3574171 × 1010
Interquartile range (IQR)98992825

Descriptive statistics

Standard deviation3.4940629 × 108
Coefficient of variation (CV)3.0878376
Kurtosis2101.6399
Mean1.1315566 × 108
Median Absolute Deviation (MAD)38946885
Skewness34.716809
Sum1.1315566 × 1012
Variance1.2208476 × 1017
MonotonicityNot monotonic
2023-12-12T12:26:53.747703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
71219390 18
 
0.2%
35853950 16
 
0.2%
22954400 13
 
0.1%
12349340 12
 
0.1%
40514320 11
 
0.1%
31187570 11
 
0.1%
39965050 9
 
0.1%
54715750 9
 
0.1%
27566530 9
 
0.1%
36536370 8
 
0.1%
Other values (9235) 9884
98.8%
ValueCountFrequency (%)
17010 1
< 0.1%
18090 1
< 0.1%
20260 1
< 0.1%
20950 1
< 0.1%
28330 1
< 0.1%
31680 1
< 0.1%
36000 1
< 0.1%
39460 1
< 0.1%
39610 2
< 0.1%
40270 1
< 0.1%
ValueCountFrequency (%)
23574187560 1
< 0.1%
9279149990 1
< 0.1%
5841537360 1
< 0.1%
4138171530 1
< 0.1%
3789754060 1
< 0.1%
3637148480 1
< 0.1%
3582243670 1
< 0.1%
3581940560 1
< 0.1%
3513090670 1
< 0.1%
3435321240 1
< 0.1%

연면적
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct7032
Distinct (%)70.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean260.52573
Minimum0.3
Maximum45686.41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:26:54.282225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.3
5-th percentile12
Q148.80075
median107.0163
Q3231
95-th percentile938.412
Maximum45686.41
Range45686.11
Interquartile range (IQR)182.19925

Descriptive statistics

Standard deviation745.41442
Coefficient of variation (CV)2.8611931
Kurtosis1446.7363
Mean260.52573
Median Absolute Deviation (MAD)70.755
Skewness27.530168
Sum2605257.3
Variance555642.65
MonotonicityNot monotonic
2023-12-12T12:26:54.456897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18.0 56
 
0.6%
2.0 31
 
0.3%
36.0 28
 
0.3%
30.0 26
 
0.3%
60.0 26
 
0.3%
15.0 25
 
0.2%
12.0 23
 
0.2%
88.6144 22
 
0.2%
72.0 20
 
0.2%
33.0 20
 
0.2%
Other values (7022) 9723
97.2%
ValueCountFrequency (%)
0.3 1
 
< 0.1%
0.64 1
 
< 0.1%
0.8 1
 
< 0.1%
0.81 1
 
< 0.1%
0.8507 1
 
< 0.1%
0.88 1
 
< 0.1%
0.9526 1
 
< 0.1%
1.0 13
0.1%
1.013 1
 
< 0.1%
1.0627 1
 
< 0.1%
ValueCountFrequency (%)
45686.41 1
< 0.1%
19176.366 1
< 0.1%
10291.87 1
< 0.1%
10048.4 1
< 0.1%
9195.79 1
< 0.1%
8454.67 1
< 0.1%
8316.0 1
< 0.1%
8288.06 1
< 0.1%
8042.79 1
< 0.1%
7961.85 1
< 0.1%

Interactions

2023-12-12T12:26:46.140310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:26:41.078545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:26:42.002059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:26:42.844890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:26:44.037564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:26:45.124941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:26:46.284610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:26:41.236361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:26:42.150623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:26:42.994352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:26:44.219775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:26:45.324222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:26:46.439171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:26:41.410015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:26:42.319121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:26:43.169899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:26:44.342689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:26:45.507769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:26:46.590163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:26:41.555706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:26:42.454511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:26:43.326699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:26:44.518445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:26:45.648206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:26:46.738729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:26:41.714654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:26:42.588788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:26:43.472756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:26:44.772372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:26:45.824200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:26:46.900115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:26:41.858633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:26:42.717605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:26:43.599116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:26:44.950547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:26:45.990073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:26:54.603807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동특수지본번부번동시가표준액연면적
법정동1.0000.4240.4060.3000.1100.1090.120
특수지0.4241.0000.3300.0000.1000.2840.279
본번0.4060.3301.0000.1740.0570.0000.000
부번0.3000.0000.1741.0000.0000.0000.000
동0.1100.1000.0570.0001.0000.0000.000
시가표준액0.1090.2840.0000.0000.0001.0000.936
연면적0.1200.2790.0000.0000.0000.9361.000
2023-12-12T12:26:54.740684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동본번부번동시가표준액연면적특수지
법정동1.000-0.209-0.044-0.027-0.0090.0920.207
본번-0.2091.000-0.214-0.0070.1400.0100.235
부번-0.044-0.2141.000-0.036-0.126-0.0340.000
동-0.027-0.007-0.0361.000-0.035-0.0840.030
시가표준액-0.0090.140-0.126-0.0351.0000.8400.223
연면적0.0920.010-0.034-0.0840.8401.0000.219
특수지0.2070.2350.0000.0300.2230.2191.000

Missing values

2023-12-12T12:26:47.129980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:26:47.423685image/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

시도명시군구명자치단체코드과세연도법정동법정리특수지본번부번동호물건지시가표준액연면적
53975광주광역시광산구2920020211220156201901011광주광역시 광산구 진곡동 562 1동 901011호56602850136.13
48913광주광역시광산구292002021119011058010104광주광역시 광산구 신가동 1058 1동 104호3716979042.9808
56368광주광역시광산구29200202111801109110101광주광역시 광산구 신창동 10-91 1동 101호244296800284.0
15188광주광역시광산구292002021121017301910001광주광역시 광산구 안청동 730-19 1동 1호122472000810.0
43318광주광역시광산구292002021116016947010113광주광역시 광산구 월계로 223-20 0001동 0113호6316694060.2106
49518광주광역시광산구29200202112701939020206광주광역시 광산구 산정동 939 2동 206호1203840041.8
28616광주광역시광산구2920020211090110351110001광주광역시 광산구 사암로130번길 71 0001동 0001호486486090.09
43000광주광역시광산구29200202112001782510203광주광역시 광산구 목련로153번길 124 0001동 0203호66983920124.97
26556광주광역시광산구292002021118011172310001광주광역시 광산구 왕버들로 319 0001동 0001호55512608.58
21259광주광역시광산구292002021116016671110301광주광역시 광산구 첨단중앙로152번길 47 0001동 0301호166129600254.8
시도명시군구명자치단체코드과세연도법정동법정리특수지본번부번동호물건지시가표준액연면적
44651광주광역시광산구29200202112301992920301광주광역시 광산구 하남산단3번로 138 0002동 0301호113801910167.11
35219광주광역시광산구292002021125011278010201광주광역시 광산구 하남대로 87 0001동 0201호376379460404.7091
43273광주광역시광산구29200202111601687510103광주광역시 광산구 쌍암동 687-5 1동 103호8914767087.9906
12918광주광역시광산구29200202112101735970010001광주광역시 광산구 안청동 735-9 7001동 1호63875000250.0
56587광주광역시광산구2920020211220158901901031광주광역시 광산구 진곡동 589 1동 901031호125697820267.3
41550광주광역시광산구29200202110101863610201광주광역시 광산구 송정동 863-6 1동 201호404028046.44
41526광주광역시광산구292002021101018521010202광주광역시 광산구 송정로 5-1 0001동 0202호3209220042.45
6486광주광역시광산구29200202116101532110006광주광역시 광산구 대산로 275-2 0001동 0006호194627047.47
38962광주광역시광산구292002021102011000210003광주광역시 광산구 도산동 1000-2 1동 3호329400091.5
2944광주광역시광산구29200202114001427010003광주광역시 광산구 본덕동 427 1동 3호7920000144.0

Duplicate rows

Most frequently occurring

시도명시군구명자치단체코드과세연도법정동법정리특수지본번부번동호물건지시가표준액연면적# duplicates
0광주광역시광산구29200202110101884110001광주광역시 광산구 송정동 884-1 1동 1호61516800172.82
1광주광역시광산구292002021114011412010105광주광역시 광산구 장신로 120 0001동 0105호3043252086.262
2광주광역시광산구29200202112101523110001광주광역시 광산구 안청동 523-1 1동 1호136897890481.952