Overview

Dataset statistics

Number of variables15
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows8
Duplicate rows (%)0.1%
Total size in memory1.3 MiB
Average record size in memory137.0 B

Variable types

Categorical6
Numeric5
Unsupported1
Text2
DateTime1

Dataset

Description경기도 고양시_일반건축물시가표준액(시도명,시군구명,자치단체코드,과세년도,법정동,법정리,특수지,본번,부번,동,호,물건지,시가표준액,연면적,기준일자)
URLhttps://www.data.go.kr/data/15080343/fileData.do

Alerts

시도명 has constant value ""Constant
과세년도 has constant value ""Constant
법정리 has constant value ""Constant
기준일자 has constant value ""Constant
Dataset has 8 (0.1%) duplicate rowsDuplicates
시군구명 is highly overall correlated with 법정동 and 2 other fieldsHigh correlation
자치단체코드 is highly overall correlated with 법정동 and 2 other fieldsHigh correlation
법정동 is highly overall correlated with 시군구명 and 1 other fieldsHigh correlation
본번 is highly overall correlated with 시군구명 and 1 other fieldsHigh correlation
시가표준액 is highly overall correlated with 연면적High correlation
연면적 is highly overall correlated with 시가표준액High correlation
특수지 is highly imbalanced (90.1%)Imbalance
부번 is highly skewed (γ1 = 22.3932517)Skewed
시가표준액 is highly skewed (γ1 = 37.9155413)Skewed
연면적 is highly skewed (γ1 = 26.7790585)Skewed
동 is an unsupported type, check if it needs cleaning or further analysisUnsupported
부번 has 4736 (47.4%) zerosZeros

Reproduction

Analysis started2023-12-12 09:11:56.441345
Analysis finished2023-12-12 09:12:01.773852
Duration5.33 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
경기도
10000 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 10000
100.0%

Length

2023-12-12T18:12:01.874447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:12:01.979859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 10000
100.0%

시군구명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
고양시덕양구
8132 
고양시일산동구
1868 

Length

Max length7
Median length6
Mean length6.1868
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row고양시덕양구
2nd row고양시일산동구
3rd row고양시일산동구
4th row고양시덕양구
5th row고양시덕양구

Common Values

ValueCountFrequency (%)
고양시덕양구 8132
81.3%
고양시일산동구 1868
 
18.7%

Length

2023-12-12T18:12:02.098879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:12:02.197213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
고양시덕양구 8132
81.3%
고양시일산동구 1868
 
18.7%

자치단체코드
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
41281
8132 
41285
1868 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row41281
2nd row41285
3rd row41285
4th row41281
5th row41281

Common Values

ValueCountFrequency (%)
41281 8132
81.3%
41285 1868
 
18.7%

Length

2023-12-12T18:12:02.302293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:12:02.396464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
41281 8132
81.3%
41285 1868
 
18.7%

과세년도
Categorical

CONSTANT 

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

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 10000
100.0%

Length

2023-12-12T18:12:02.499093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:12:02.897806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 10000
100.0%

법정동
Real number (ℝ)

HIGH CORRELATION 

Distinct32
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean114.0522
Minimum101
Maximum132
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T18:12:03.007175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile102
Q1104
median112
Q3123
95-th percentile130
Maximum132
Range31
Interquartile range (IQR)19

Descriptive statistics

Standard deviation9.9274836
Coefficient of variation (CV)0.087043333
Kurtosis-1.3728282
Mean114.0522
Median Absolute Deviation (MAD)8
Skewness0.31641966
Sum1140522
Variance98.554931
MonotonicityNot monotonic
2023-12-12T18:12:03.178892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
104 1717
17.2%
123 1243
12.4%
128 954
 
9.5%
105 759
 
7.6%
112 560
 
5.6%
111 541
 
5.4%
106 530
 
5.3%
102 398
 
4.0%
120 355
 
3.5%
101 343
 
3.4%
Other values (22) 2600
26.0%
ValueCountFrequency (%)
101 343
 
3.4%
102 398
 
4.0%
103 276
 
2.8%
104 1717
17.2%
105 759
7.6%
106 530
 
5.3%
107 7
 
0.1%
108 14
 
0.1%
109 164
 
1.6%
110 39
 
0.4%
ValueCountFrequency (%)
132 340
 
3.4%
131 139
 
1.4%
130 125
 
1.2%
129 158
 
1.6%
128 954
9.5%
127 13
 
0.1%
126 44
 
0.4%
125 56
 
0.6%
124 71
 
0.7%
123 1243
12.4%

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

2023-12-12T18:12:03.351112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:12:03.453467image/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
9796 
3
 
173
2
 
31

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 9796
98.0%
3 173
 
1.7%
2 31
 
0.3%

Length

2023-12-12T18:12:03.590592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:12:03.699207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 9796
98.0%
3 173
 
1.7%
2 31
 
0.3%

본번
Real number (ℝ)

HIGH CORRELATION 

Distinct1056
Distinct (%)10.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean664.765
Minimum1
Maximum1813
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T18:12:03.829441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile104
Q1372
median704
Q3903
95-th percentile1145
Maximum1813
Range1812
Interquartile range (IQR)531

Descriptive statistics

Standard deviation342.7092
Coefficient of variation (CV)0.51553437
Kurtosis0.38626791
Mean664.765
Median Absolute Deviation (MAD)248
Skewness0.32694174
Sum6647650
Variance117449.6
MonotonicityNot monotonic
2023-12-12T18:12:03.970981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
376 186
 
1.9%
294 151
 
1.5%
970 122
 
1.2%
706 116
 
1.2%
372 116
 
1.2%
950 104
 
1.0%
951 97
 
1.0%
727 96
 
1.0%
869 95
 
0.9%
295 94
 
0.9%
Other values (1046) 8823
88.2%
ValueCountFrequency (%)
1 26
 
0.3%
2 4
 
< 0.1%
3 77
0.8%
4 11
 
0.1%
5 1
 
< 0.1%
6 2
 
< 0.1%
7 7
 
0.1%
9 6
 
0.1%
10 3
 
< 0.1%
11 5
 
0.1%
ValueCountFrequency (%)
1813 17
0.2%
1808 11
0.1%
1806 4
 
< 0.1%
1801 1
 
< 0.1%
1800 1
 
< 0.1%
1796 2
 
< 0.1%
1730 1
 
< 0.1%
1717 2
 
< 0.1%
1700 1
 
< 0.1%
1696 1
 
< 0.1%

부번
Real number (ℝ)

SKEWED  ZEROS 

Distinct147
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.5883
Minimum0
Maximum1304
Zeros4736
Zeros (%)47.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T18:12:04.140185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile20
Maximum1304
Range1304
Interquartile range (IQR)3

Descriptive statistics

Standard deviation29.261846
Coefficient of variation (CV)5.2362697
Kurtosis743.02785
Mean5.5883
Median Absolute Deviation (MAD)1
Skewness22.393252
Sum55883
Variance856.25563
MonotonicityNot monotonic
2023-12-12T18:12:04.351859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4736
47.4%
1 1521
 
15.2%
2 936
 
9.4%
3 620
 
6.2%
4 298
 
3.0%
5 257
 
2.6%
6 180
 
1.8%
7 174
 
1.7%
8 167
 
1.7%
9 116
 
1.2%
Other values (137) 995
 
10.0%
ValueCountFrequency (%)
0 4736
47.4%
1 1521
 
15.2%
2 936
 
9.4%
3 620
 
6.2%
4 298
 
3.0%
5 257
 
2.6%
6 180
 
1.8%
7 174
 
1.7%
8 167
 
1.7%
9 116
 
1.2%
ValueCountFrequency (%)
1304 1
< 0.1%
1002 1
< 0.1%
907 1
< 0.1%
902 1
< 0.1%
534 1
< 0.1%
522 1
< 0.1%
476 1
< 0.1%
361 1
< 0.1%
346 1
< 0.1%
318 2
< 0.1%

동
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size156.2 KiB

호
Text

Distinct1400
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T18:12:04.764548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.2658
Min length1

Characters and Unicode

Total characters32658
Distinct characters31
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique819 ?
Unique (%)8.2%

Sample

1st row401
2nd row402
3rd row8103
4th row4207
5th row203
ValueCountFrequency (%)
101 1721
 
17.2%
102 599
 
6.0%
201 485
 
4.9%
8101 317
 
3.2%
103 258
 
2.6%
301 251
 
2.5%
104 180
 
1.8%
401 147
 
1.5%
202 134
 
1.3%
501 113
 
1.1%
Other values (1390) 5795
58.0%
2023-12-12T18:12:05.405849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 10205
31.2%
0 8426
25.8%
2 3824
 
11.7%
3 2225
 
6.8%
4 1674
 
5.1%
8 1484
 
4.5%
5 1349
 
4.1%
6 1041
 
3.2%
7 862
 
2.6%
9 767
 
2.3%
Other values (21) 801
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31857
97.5%
Dash Punctuation 452
 
1.4%
Uppercase Letter 322
 
1.0%
Lowercase Letter 18
 
0.1%
Other Letter 9
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 10205
32.0%
0 8426
26.4%
2 3824
 
12.0%
3 2225
 
7.0%
4 1674
 
5.3%
8 1484
 
4.7%
5 1349
 
4.2%
6 1041
 
3.3%
7 862
 
2.7%
9 767
 
2.4%
Uppercase Letter
ValueCountFrequency (%)
B 109
33.9%
A 103
32.0%
T 50
15.5%
K 38
 
11.8%
C 13
 
4.0%
J 4
 
1.2%
I 3
 
0.9%
F 1
 
0.3%
O 1
 
0.3%
Lowercase Letter
ValueCountFrequency (%)
a 4
22.2%
n 4
22.2%
r 3
16.7%
p 3
16.7%
e 1
 
5.6%
b 1
 
5.6%
c 1
 
5.6%
t 1
 
5.6%
Other Letter
ValueCountFrequency (%)
매 3
33.3%
층 3
33.3%
판 3
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 452
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 32309
98.9%
Latin 340
 
1.0%
Hangul 9
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
B 109
32.1%
A 103
30.3%
T 50
14.7%
K 38
 
11.2%
C 13
 
3.8%
J 4
 
1.2%
a 4
 
1.2%
n 4
 
1.2%
r 3
 
0.9%
p 3
 
0.9%
Other values (7) 9
 
2.6%
Common
ValueCountFrequency (%)
1 10205
31.6%
0 8426
26.1%
2 3824
 
11.8%
3 2225
 
6.9%
4 1674
 
5.2%
8 1484
 
4.6%
5 1349
 
4.2%
6 1041
 
3.2%
7 862
 
2.7%
9 767
 
2.4%
Hangul
ValueCountFrequency (%)
매 3
33.3%
층 3
33.3%
판 3
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 32649
> 99.9%
Hangul 9
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 10205
31.3%
0 8426
25.8%
2 3824
 
11.7%
3 2225
 
6.8%
4 1674
 
5.1%
8 1484
 
4.5%
5 1349
 
4.1%
6 1041
 
3.2%
7 862
 
2.6%
9 767
 
2.3%
Other values (18) 792
 
2.4%
Hangul
ValueCountFrequency (%)
매 3
33.3%
층 3
33.3%
판 3
33.3%

물건지
Text

Distinct9666
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T18:12:05.817286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length30
Mean length24.9788
Min length20

Characters and Unicode

Total characters249788
Distinct characters164
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9355 ?
Unique (%)93.5%

Sample

1st row[ 백양로 47 ] 0000동 0401호
2nd row[ 중앙로1261번길 59 ] 0000동 0402호
3rd row[ 중앙로 1192 ] 0001동 8103호
4th row경기도 고양시덕양구 원흥동 623 101동 4207호
5th row[ 권율대로 903 ] 0000동 0203호
ValueCountFrequency (%)
14102
24.0%
0000동 6079
 
10.4%
경기도 2949
 
5.0%
고양시덕양구 2523
 
4.3%
0101호 990
 
1.7%
0001동 747
 
1.3%
101호 731
 
1.2%
1동 696
 
1.2%
고양시일산동구 426
 
0.7%
중앙로 409
 
0.7%
Other values (4337) 29015
49.5%
2023-12-12T18:12:06.441019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
48667
19.5%
0 44245
17.7%
1 18766
 
7.5%
동 12274
 
4.9%
호 10291
 
4.1%
2 9289
 
3.7%
] 7051
 
2.8%
[ 7051
 
2.8%
로 6781
 
2.7%
3 6343
 
2.5%
Other values (154) 79030
31.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 102774
41.1%
Other Letter 80769
32.3%
Space Separator 48667
19.5%
Close Punctuation 7051
 
2.8%
Open Punctuation 7051
 
2.8%
Dash Punctuation 3163
 
1.3%
Uppercase Letter 313
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 12274
15.2%
호 10291
 
12.7%
로 6781
 
8.4%
양 5915
 
7.3%
고 3329
 
4.1%
도 3288
 
4.1%
기 3099
 
3.8%
경 3008
 
3.7%
시 2972
 
3.7%
구 2949
 
3.7%
Other values (134) 26863
33.3%
Decimal Number
ValueCountFrequency (%)
0 44245
43.1%
1 18766
18.3%
2 9289
 
9.0%
3 6343
 
6.2%
4 4913
 
4.8%
5 4500
 
4.4%
6 4093
 
4.0%
8 3955
 
3.8%
7 3707
 
3.6%
9 2963
 
2.9%
Uppercase Letter
ValueCountFrequency (%)
B 109
34.8%
A 100
31.9%
T 50
16.0%
K 38
 
12.1%
C 13
 
4.2%
I 3
 
1.0%
Space Separator
ValueCountFrequency (%)
48667
100.0%
Close Punctuation
ValueCountFrequency (%)
] 7051
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 7051
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3163
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 168706
67.5%
Hangul 80769
32.3%
Latin 313
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 12274
15.2%
호 10291
 
12.7%
로 6781
 
8.4%
양 5915
 
7.3%
고 3329
 
4.1%
도 3288
 
4.1%
기 3099
 
3.8%
경 3008
 
3.7%
시 2972
 
3.7%
구 2949
 
3.7%
Other values (134) 26863
33.3%
Common
ValueCountFrequency (%)
48667
28.8%
0 44245
26.2%
1 18766
 
11.1%
2 9289
 
5.5%
] 7051
 
4.2%
[ 7051
 
4.2%
3 6343
 
3.8%
4 4913
 
2.9%
5 4500
 
2.7%
6 4093
 
2.4%
Other values (4) 13788
 
8.2%
Latin
ValueCountFrequency (%)
B 109
34.8%
A 100
31.9%
T 50
16.0%
K 38
 
12.1%
C 13
 
4.2%
I 3
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 169019
67.7%
Hangul 80769
32.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
48667
28.8%
0 44245
26.2%
1 18766
 
11.1%
2 9289
 
5.5%
] 7051
 
4.2%
[ 7051
 
4.2%
3 6343
 
3.8%
4 4913
 
2.9%
5 4500
 
2.7%
6 4093
 
2.4%
Other values (10) 14101
 
8.3%
Hangul
ValueCountFrequency (%)
동 12274
15.2%
호 10291
 
12.7%
로 6781
 
8.4%
양 5915
 
7.3%
고 3329
 
4.1%
도 3288
 
4.1%
기 3099
 
3.8%
경 3008
 
3.7%
시 2972
 
3.7%
구 2949
 
3.7%
Other values (134) 26863
33.3%

시가표준액
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct8079
Distinct (%)80.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean86453236
Minimum66310
Maximum2.6062341 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T18:12:06.618316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum66310
5-th percentile1981976
Q113678842
median39798000
Q380442902
95-th percentile2.1915282 × 108
Maximum2.6062341 × 1010
Range2.6062274 × 1010
Interquartile range (IQR)66764060

Descriptive statistics

Standard deviation4.655869 × 108
Coefficient of variation (CV)5.385419
Kurtosis1751.603
Mean86453236
Median Absolute Deviation (MAD)29788000
Skewness37.915541
Sum8.6453236 × 1011
Variance2.1677116 × 1017
MonotonicityNot monotonic
2023-12-12T18:12:06.780291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
60092090 73
 
0.7%
61784050 50
 
0.5%
77735970 37
 
0.4%
65120870 32
 
0.3%
40554320 32
 
0.3%
8322210 31
 
0.3%
39409050 29
 
0.3%
54514770 26
 
0.3%
174502200 25
 
0.2%
37382360 25
 
0.2%
Other values (8069) 9640
96.4%
ValueCountFrequency (%)
66310 1
< 0.1%
82000 1
< 0.1%
90000 1
< 0.1%
93000 1
< 0.1%
108190 1
< 0.1%
129130 1
< 0.1%
139600 1
< 0.1%
142800 2
< 0.1%
145600 1
< 0.1%
167640 1
< 0.1%
ValueCountFrequency (%)
26062340640 1
< 0.1%
21289750450 1
< 0.1%
17715622150 1
< 0.1%
15515706720 1
< 0.1%
9266308770 1
< 0.1%
6820345410 1
< 0.1%
6791045820 1
< 0.1%
4380652600 1
< 0.1%
4240719200 1
< 0.1%
4093581000 1
< 0.1%

연면적
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct6519
Distinct (%)65.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean136.20685
Minimum0.19
Maximum24171.95
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T18:12:06.955595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.19
5-th percentile9.3375
Q134.67435
median64.84
Q3129.005
95-th percentile366.4055
Maximum24171.95
Range24171.76
Interquartile range (IQR)94.33065

Descriptive statistics

Standard deviation504.08568
Coefficient of variation (CV)3.7008835
Kurtosis973.73598
Mean136.20685
Median Absolute Deviation (MAD)39.605
Skewness26.779059
Sum1362068.5
Variance254102.37
MonotonicityNot monotonic
2023-12-12T18:12:07.134447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18.0 84
 
0.8%
61.6314 73
 
0.7%
198.0 68
 
0.7%
63.3667 50
 
0.5%
75.1824 37
 
0.4%
27.0 34
 
0.3%
60.68 32
 
0.3%
61.089 32
 
0.3%
12.8034 31
 
0.3%
55.25 29
 
0.3%
Other values (6509) 9530
95.3%
ValueCountFrequency (%)
0.19 1
 
< 0.1%
0.31 1
 
< 0.1%
0.37 1
 
< 0.1%
0.4 1
 
< 0.1%
0.42 1
 
< 0.1%
0.44 1
 
< 0.1%
0.4784 1
 
< 0.1%
0.52 1
 
< 0.1%
0.55 2
< 0.1%
0.62 4
< 0.1%
ValueCountFrequency (%)
24171.95 1
< 0.1%
19507.74 1
< 0.1%
16353.0 1
< 0.1%
13074.03 1
< 0.1%
12040.8614 1
< 0.1%
10957.42 1
< 0.1%
9305.97 1
< 0.1%
9187.0 1
< 0.1%
7893.61 1
< 0.1%
6372.88 1
< 0.1%

기준일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2022-06-01 00:00:00
Maximum2022-06-01 00:00:00
2023-12-12T18:12:07.293850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:12:07.427749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T18:12:00.595894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:58.067078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:58.659039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:59.275969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:59.914217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:12:00.734493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:58.177996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:58.790016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:59.421911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:12:00.068843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:12:00.876792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:58.311732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:58.894525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:59.569973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:12:00.214482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:12:01.025700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:58.425161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:59.001459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:59.684107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:12:00.334229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:12:01.166911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:58.536636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:59.155822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:11:59.793529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:12:00.462286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:12:07.534136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명자치단체코드법정동특수지본번부번시가표준액연면적
시군구명1.0001.0000.7610.0390.8980.0350.0230.034
자치단체코드1.0001.0000.7610.0390.8980.0350.0230.034
법정동0.7610.7611.0000.5460.7940.1060.0000.000
특수지0.0390.0390.5461.0000.3440.1640.0000.000
본번0.8980.8980.7940.3441.0000.0840.0380.037
부번0.0350.0350.1060.1640.0841.0000.0000.000
시가표준액0.0230.0230.0000.0000.0380.0001.0000.941
연면적0.0340.0340.0000.0000.0370.0000.9411.000
2023-12-12T18:12:07.686943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
특수지시군구명자치단체코드
특수지1.0000.0650.065
시군구명0.0651.0001.000
자치단체코드0.0651.0001.000
2023-12-12T18:12:07.808972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동본번부번시가표준액연면적시군구명자치단체코드특수지
법정동1.000-0.0900.111-0.061-0.0050.5990.5990.390
본번-0.0901.000-0.220-0.030-0.1520.7350.7350.220
부번0.111-0.2201.000-0.0680.1200.0260.0260.105
시가표준액-0.061-0.030-0.0681.0000.7940.0170.0170.000
연면적-0.005-0.1520.1200.7941.0000.0340.0340.000
시군구명0.5990.7350.0260.0170.0341.0001.0000.065
자치단체코드0.5990.7350.0260.0170.0341.0001.0000.065
특수지0.3900.2200.1050.0000.0000.0650.0651.000

Missing values

2023-12-12T18:12:01.330262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:12:01.662606image/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

시도명시군구명자치단체코드과세년도법정동법정리특수지본번부번동호물건지시가표준액연면적기준일자
23404경기도고양시덕양구41281202212301100090401[ 백양로 47 ] 0000동 0401호1198665034.152022-06-01
54427경기도고양시일산동구4128520221040186410402[ 중앙로1261번길 59 ] 0000동 0402호1797192039.242022-06-01
57787경기도고양시일산동구41285202210501798518103[ 중앙로 1192 ] 0001동 8103호1134360032.882022-06-01
37220경기도고양시덕양구4128120221040162301014207경기도 고양시덕양구 원흥동 623 101동 4207호174502200169.92942022-06-01
48137경기도고양시덕양구4128120221030161920203[ 권율대로 903 ] 0000동 0203호2441790041.742022-06-01
26195경기도고양시덕양구41281202212301972008150경기도 고양시덕양구 화정동 972 8150호857635012.282022-06-01
27551경기도고양시덕양구4128120221280176240706[ 충장로 2 ] 0000동 0706호70570850105.112022-06-01
26107경기도고양시덕양구4128120221230196730212[ 화정로 53-1 ] 0000동 0212호1106417019.322022-06-01
67297경기도고양시덕양구41281202212801109700201[ 소원로 251 ] 0000동 0201호18855103402471.182022-06-01
57821경기도고양시일산동구4128520221050180602117경기도 고양시일산동구 마두동 806 2동 117호5058013082.832022-06-01
시도명시군구명자치단체코드과세년도법정동법정리특수지본번부번동호물건지시가표준액연면적기준일자
30840경기도고양시덕양구4128120221230196800107[ 화중로 100 ] 0000동 0107호16350004.362022-06-01
64066경기도고양시일산동구4128520221040156631103경기도 고양시일산동구 장항동 566-3 1동 103호108026530153.242022-06-01
61251경기도고양시일산동구4128520221040172710911[ 중앙로 1347 ] 0000동 0911호5022879071.932022-06-01
11993경기도고양시덕양구412812022111012950301914경기도 고양시덕양구 삼송동 295 301동 914호4882861050.07942022-06-01
66645경기도고양시덕양구41281202211901301610107경기도 고양시덕양구 내유동 301-6 10동 107호433434030.742022-06-01
34108경기도고양시덕양구41281202212301114800405[ 성신로 4 ] 0000동 0405호2162176032.962022-06-01
43073경기도고양시덕양구4128120221040162700128[ 권율대로 672 ] 0000동 0128호4035540029.822022-06-01
85158경기도고양시일산동구4128520221040173000523[ 무궁화로 43-50 ] 0000동 0523호6470661097.992022-06-01
10989경기도고양시덕양구412812022111012940201519경기도 고양시덕양구 삼송동 294 201동 519호6009209061.63142022-06-01
68508경기도고양시덕양구41281202210502881020101경기도 고양시덕양구 도내동 산 88-10 20동 101호3483008.12022-06-01

Duplicate rows

Most frequently occurring

시도명시군구명자치단체코드과세년도법정동법정리특수지본번부번호물건지시가표준액연면적기준일자# duplicates
0경기도고양시덕양구412812022101014870101경기도 고양시덕양구 주교동 487 1동 101호19116009.02022-06-013
1경기도고양시덕양구412812022104013660101[ 서오릉로 704-1 ] 0003동 0101호9954000126.02022-06-012
2경기도고양시덕양구412812022113013622101경기도 고양시덕양구 용두동 362-2 101호39798000148.52022-06-012
3경기도고양시덕양구4128120221180157612101경기도 고양시덕양구 관산동 576-12 101호11088000198.02022-06-012
4경기도고양시덕양구412812022118016022101경기도 고양시덕양구 관산동 602-2 1동 101호7524000198.02022-06-012
5경기도고양시덕양구412812022118018601101경기도 고양시덕양구 관산동 860-1 1동 101호2574000198.02022-06-012
6경기도고양시덕양구412812022129011643101경기도 고양시덕양구 화전동 164-3 1동 101호180455000193.02022-06-012
7경기도고양시일산동구4128520221040152527101경기도 고양시일산동구 장항동 525-27 1동 101호107632800198.02022-06-012