Overview

Dataset statistics

Number of variables16
Number of observations8589
Missing cells4
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 MiB
Average record size in memory138.0 B

Variable types

Categorical7
Numeric6
Text2
DateTime1

Dataset

Description일반건축물시가표준액(시도명, 시군구명, 과세연도, 주소지번, 물건지, 시가표준액, 연면적, 기분일자 등) 정보 공개
URLhttps://www.data.go.kr/data/15080106/fileData.do

Alerts

시도 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
과세연도 has constant value ""Constant
법정리 has constant value ""Constant
기준일자 has constant value ""Constant
시가표준액(원) is highly overall correlated with 연면적High correlation
연면적 is highly overall correlated with 시가표준액(원) High correlation
특수지 is highly imbalanced (94.0%)Imbalance
용도구분 is highly imbalanced (51.2%)Imbalance
동 is highly skewed (γ1 = 32.99211312)Skewed
시가표준액(원) is highly skewed (γ1 = 29.41707628)Skewed
부번 has 1543 (18.0%) zerosZeros
동 has 2418 (28.2%) zerosZeros

Reproduction

Analysis started2023-12-12 08:44:23.401161
Analysis finished2023-12-12 08:44:29.918875
Duration6.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
경기도
8589 

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 8589
100.0%

Length

2023-12-12T17:44:29.982606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:44:30.088937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 8589
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
동두천시
8589 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
동두천시 8589
100.0%

Length

2023-12-12T17:44:30.199104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:44:30.294196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
동두천시 8589
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
41250
8589 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row41250
2nd row41250
3rd row41250
4th row41250
5th row41250

Common Values

ValueCountFrequency (%)
41250 8589
100.0%

Length

2023-12-12T17:44:30.391747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:44:30.489221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
41250 8589
100.0%

과세연도
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
2023
8589 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2023 8589
100.0%

Length

2023-12-12T17:44:30.584783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:44:30.677511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023 8589
100.0%

법정동
Real number (ℝ)

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean104.86483
Minimum101
Maximum112
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size75.6 KiB
2023-12-12T17:44:30.763020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile101
Q1102
median103
Q3107
95-th percentile112
Maximum112
Range11
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.5621775
Coefficient of variation (CV)0.033969231
Kurtosis-0.58606211
Mean104.86483
Median Absolute Deviation (MAD)1
Skewness0.97284854
Sum900684
Variance12.689109
MonotonicityIncreasing
2023-12-12T17:44:30.878973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
103 3302
38.4%
102 1614
18.8%
112 819
 
9.5%
101 575
 
6.7%
111 427
 
5.0%
107 392
 
4.6%
106 359
 
4.2%
109 311
 
3.6%
110 305
 
3.6%
104 258
 
3.0%
Other values (2) 227
 
2.6%
ValueCountFrequency (%)
101 575
 
6.7%
102 1614
18.8%
103 3302
38.4%
104 258
 
3.0%
105 15
 
0.2%
106 359
 
4.2%
107 392
 
4.6%
108 212
 
2.5%
109 311
 
3.6%
110 305
 
3.6%
ValueCountFrequency (%)
112 819
 
9.5%
111 427
 
5.0%
110 305
 
3.6%
109 311
 
3.6%
108 212
 
2.5%
107 392
 
4.6%
106 359
 
4.2%
105 15
 
0.2%
104 258
 
3.0%
103 3302
38.4%

법정리
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
0
8589 

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 8589
100.0%

Length

2023-12-12T17:44:31.004195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:44:31.102900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 8589
100.0%

특수지
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
1
8529 
2
 
60

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 8529
99.3%
2 60
 
0.7%

Length

2023-12-12T17:44:31.206419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:44:31.319055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 8529
99.3%
2 60
 
0.7%

본번
Real number (ℝ)

Distinct819
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean504.82489
Minimum1
Maximum9999
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size75.6 KiB
2023-12-12T17:44:31.461143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile52
Q1324
median557
Q3703
95-th percentile820
Maximum9999
Range9998
Interquartile range (IQR)379

Descriptive statistics

Standard deviation264.58532
Coefficient of variation (CV)0.52411305
Kurtosis191.72138
Mean504.82489
Median Absolute Deviation (MAD)164
Skewness5.019548
Sum4335941
Variance70005.39
MonotonicityNot monotonic
2023-12-12T17:44:31.975079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
809 378
 
4.4%
718 270
 
3.1%
721 242
 
2.8%
695 204
 
2.4%
722 159
 
1.9%
689 113
 
1.3%
693 112
 
1.3%
691 107
 
1.2%
719 102
 
1.2%
714 79
 
0.9%
Other values (809) 6823
79.4%
ValueCountFrequency (%)
1 39
0.5%
2 11
 
0.1%
3 9
 
0.1%
4 3
 
< 0.1%
5 5
 
0.1%
6 3
 
< 0.1%
7 2
 
< 0.1%
8 8
 
0.1%
9 3
 
< 0.1%
10 16
0.2%
ValueCountFrequency (%)
9999 1
 
< 0.1%
1107 4
< 0.1%
1100 2
< 0.1%
1086 1
 
< 0.1%
1083 1
 
< 0.1%
1080 4
< 0.1%
1073 4
< 0.1%
1070 2
< 0.1%
1068 1
 
< 0.1%
1050 1
 
< 0.1%

부번
Real number (ℝ)

ZEROS 

Distinct156
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.65188
Minimum0
Maximum225
Zeros1543
Zeros (%)18.0%
Negative0
Negative (%)0.0%
Memory size75.6 KiB
2023-12-12T17:44:32.179965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median4
Q312
95-th percentile50
Maximum225
Range225
Interquartile range (IQR)11

Descriptive statistics

Standard deviation21.543997
Coefficient of variation (CV)1.8489717
Kurtosis21.847211
Mean11.65188
Median Absolute Deviation (MAD)4
Skewness4.006184
Sum100078
Variance464.14382
MonotonicityNot monotonic
2023-12-12T17:44:32.409860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1543
18.0%
1 985
 
11.5%
2 883
 
10.3%
3 757
 
8.8%
4 590
 
6.9%
5 479
 
5.6%
6 280
 
3.3%
7 208
 
2.4%
9 176
 
2.0%
10 170
 
2.0%
Other values (146) 2518
29.3%
ValueCountFrequency (%)
0 1543
18.0%
1 985
11.5%
2 883
10.3%
3 757
8.8%
4 590
 
6.9%
5 479
 
5.6%
6 280
 
3.3%
7 208
 
2.4%
8 156
 
1.8%
9 176
 
2.0%
ValueCountFrequency (%)
225 1
< 0.1%
224 2
< 0.1%
209 1
< 0.1%
208 1
< 0.1%
207 1
< 0.1%
197 1
< 0.1%
191 1
< 0.1%
190 1
< 0.1%
188 1
< 0.1%
187 1
< 0.1%

동
Real number (ℝ)

SKEWED  ZEROS 

Distinct46
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.3258819
Minimum0
Maximum9006
Zeros2418
Zeros (%)28.2%
Negative0
Negative (%)0.0%
Memory size75.6 KiB
2023-12-12T17:44:32.605591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile2
Maximum9006
Range9006
Interquartile range (IQR)1

Descriptive statistics

Standard deviation264.09885
Coefficient of variation (CV)28.318914
Kurtosis1092.4686
Mean9.3258819
Median Absolute Deviation (MAD)0
Skewness32.992113
Sum80100
Variance69748.201
MonotonicityNot monotonic
2023-12-12T17:44:32.794220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
1 5213
60.7%
0 2418
28.2%
2 626
 
7.3%
3 86
 
1.0%
4 61
 
0.7%
5 38
 
0.4%
6 18
 
0.2%
7 15
 
0.2%
8 13
 
0.2%
9 11
 
0.1%
Other values (36) 90
 
1.0%
ValueCountFrequency (%)
0 2418
28.2%
1 5213
60.7%
2 626
 
7.3%
3 86
 
1.0%
4 61
 
0.7%
5 38
 
0.4%
6 18
 
0.2%
7 15
 
0.2%
8 13
 
0.2%
9 11
 
0.1%
ValueCountFrequency (%)
9006 1
 
< 0.1%
9005 1
 
< 0.1%
9004 1
 
< 0.1%
9003 1
 
< 0.1%
9002 2
 
< 0.1%
8001 1
 
< 0.1%
7001 1
 
< 0.1%
210 1
 
< 0.1%
112 10
0.1%
103 2
 
< 0.1%

호
Text

Distinct367
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
2023-12-12T17:44:33.106175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length1
Mean length1.5614158
Min length1

Characters and Unicode

Total characters13411
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique116 ?
Unique (%)1.4%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 6139
71.5%
101 134
 
1.6%
102 111
 
1.3%
103 88
 
1.0%
201 86
 
1.0%
104 75
 
0.9%
301 67
 
0.8%
202 62
 
0.7%
105 59
 
0.7%
401 52
 
0.6%
Other values (357) 1716
 
20.0%
2023-12-12T17:44:33.602767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 7855
58.6%
0 2090
 
15.6%
2 857
 
6.4%
3 617
 
4.6%
4 491
 
3.7%
5 429
 
3.2%
8 349
 
2.6%
6 308
 
2.3%
7 255
 
1.9%
9 151
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13402
99.9%
Dash Punctuation 9
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7855
58.6%
0 2090
 
15.6%
2 857
 
6.4%
3 617
 
4.6%
4 491
 
3.7%
5 429
 
3.2%
8 349
 
2.6%
6 308
 
2.3%
7 255
 
1.9%
9 151
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13411
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 7855
58.6%
0 2090
 
15.6%
2 857
 
6.4%
3 617
 
4.6%
4 491
 
3.7%
5 429
 
3.2%
8 349
 
2.6%
6 308
 
2.3%
7 255
 
1.9%
9 151
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13411
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 7855
58.6%
0 2090
 
15.6%
2 857
 
6.4%
3 617
 
4.6%
4 491
 
3.7%
5 429
 
3.2%
8 349
 
2.6%
6 308
 
2.3%
7 255
 
1.9%
9 151
 
1.1%

용도구분
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
Ⅱ. 상업용 건물
6168 
Ⅲ. 공업용 건물
1309 
Ⅴ. 사회문화용 건물
 
509
Ⅵ. 공공용 건물
 
263
Ⅳ. 농수산용 건물
 
256
Other values (2)
 
84

Length

Max length11
Median length9
Mean length9.1483293
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowⅤ. 사회문화용 건물
2nd rowⅣ. 농수산용 건물
3rd rowⅣ. 농수산용 건물
4th rowⅢ. 공업용 건물
5th rowⅡ. 상업용 건물

Common Values

ValueCountFrequency (%)
Ⅱ. 상업용 건물 6168
71.8%
Ⅲ. 공업용 건물 1309
 
15.2%
Ⅴ. 사회문화용 건물 509
 
5.9%
Ⅵ. 공공용 건물 263
 
3.1%
Ⅳ. 농수산용 건물 256
 
3.0%
Ⅰ. 주거용 건물 80
 
0.9%
Ⅶ. 그 외 건물 4
 
< 0.1%

Length

2023-12-12T17:44:33.805067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:44:34.006706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물 8589
33.3%
ⅱ 6168
23.9%
상업용 6168
23.9%
ⅲ 1309
 
5.1%
공업용 1309
 
5.1%
ⅴ 509
 
2.0%
사회문화용 509
 
2.0%
ⅵ 263
 
1.0%
공공용 263
 
1.0%
ⅳ 256
 
1.0%
Other values (6) 428
 
1.7%

물건지
Text

Distinct5081
Distinct (%)59.2%
Missing4
Missing (%)< 0.1%
Memory size67.2 KiB
2023-12-12T17:44:34.582900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length18
Mean length18.341875
Min length16

Characters and Unicode

Total characters157465
Distinct characters37
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4117 ?
Unique (%)48.0%

Sample

1st row경기도 동두천시 송내동 29-1
2nd row경기도 동두천시 송내동 36-0
3rd row경기도 동두천시 송내동 36-0
4th row경기도 동두천시 송내동 45-1
5th row경기도 동두천시 송내동 45-4
ValueCountFrequency (%)
경기도 8585
25.0%
동두천시 8585
25.0%
생연동 3300
 
9.6%
지행동 1612
 
4.7%
상패동 819
 
2.4%
송내동 575
 
1.7%
탑동동 427
 
1.2%
동두천동 392
 
1.1%
809-0 369
 
1.1%
보산동 359
 
1.0%
Other values (4511) 9377
27.3%
2023-12-12T17:44:35.255260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25815
16.4%
동 17989
 
11.4%
두 8977
 
5.7%
천 8977
 
5.7%
경 8585
 
5.5%
도 8585
 
5.5%
시 8585
 
5.5%
기 8585
 
5.5%
- 8583
 
5.5%
1 5356
 
3.4%
Other values (27) 47428
30.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 86918
55.2%
Decimal Number 36149
23.0%
Space Separator 25815
 
16.4%
Dash Punctuation 8583
 
5.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 17989
20.7%
두 8977
10.3%
천 8977
10.3%
경 8585
9.9%
도 8585
9.9%
시 8585
9.9%
기 8585
9.9%
연 3300
 
3.8%
생 3300
 
3.8%
행 1612
 
1.9%
Other values (15) 8423
9.7%
Decimal Number
ValueCountFrequency (%)
1 5356
14.8%
2 4455
12.3%
4 3588
9.9%
0 3552
9.8%
6 3543
9.8%
3 3436
9.5%
8 3285
9.1%
5 3205
8.9%
7 3026
8.4%
9 2703
7.5%
Space Separator
ValueCountFrequency (%)
25815
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8583
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 86918
55.2%
Common 70547
44.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 17989
20.7%
두 8977
10.3%
천 8977
10.3%
경 8585
9.9%
도 8585
9.9%
시 8585
9.9%
기 8585
9.9%
연 3300
 
3.8%
생 3300
 
3.8%
행 1612
 
1.9%
Other values (15) 8423
9.7%
Common
ValueCountFrequency (%)
25815
36.6%
- 8583
 
12.2%
1 5356
 
7.6%
2 4455
 
6.3%
4 3588
 
5.1%
0 3552
 
5.0%
6 3543
 
5.0%
3 3436
 
4.9%
8 3285
 
4.7%
5 3205
 
4.5%
Other values (2) 5729
 
8.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 86918
55.2%
ASCII 70547
44.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25815
36.6%
- 8583
 
12.2%
1 5356
 
7.6%
2 4455
 
6.3%
4 3588
 
5.1%
0 3552
 
5.0%
6 3543
 
5.0%
3 3436
 
4.9%
8 3285
 
4.7%
5 3205
 
4.5%
Other values (2) 5729
 
8.1%
Hangul
ValueCountFrequency (%)
동 17989
20.7%
두 8977
10.3%
천 8977
10.3%
경 8585
9.9%
도 8585
9.9%
시 8585
9.9%
기 8585
9.9%
연 3300
 
3.8%
생 3300
 
3.8%
행 1612
 
1.9%
Other values (15) 8423
9.7%

시가표준액(원)
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct7219
Distinct (%)84.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2581018 × 108
Minimum28000
Maximum3.0952565 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size75.6 KiB
2023-12-12T17:44:35.421049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum28000
5-th percentile1513566
Q17272720
median33631200
Q31.018814 × 108
95-th percentile4.1878749 × 108
Maximum3.0952565 × 1010
Range3.0952537 × 1010
Interquartile range (IQR)94608680

Descriptive statistics

Standard deviation5.4606238 × 108
Coefficient of variation (CV)4.3403671
Kurtosis1382.0956
Mean1.2581018 × 108
Median Absolute Deviation (MAD)30689730
Skewness29.417076
Sum1.0805837 × 1012
Variance2.9818412 × 1017
MonotonicityNot monotonic
2023-12-12T17:44:35.596593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2908442 76
 
0.9%
2803320 37
 
0.4%
2628111 29
 
0.3%
5394292 26
 
0.3%
15888431 21
 
0.2%
13233520 16
 
0.2%
1915200 14
 
0.2%
1958400 14
 
0.2%
2131200 13
 
0.2%
64495020 12
 
0.1%
Other values (7209) 8331
97.0%
ValueCountFrequency (%)
28000 1
 
< 0.1%
38000 1
 
< 0.1%
39000 1
 
< 0.1%
66000 1
 
< 0.1%
72000 1
 
< 0.1%
100800 3
< 0.1%
108000 1
 
< 0.1%
120960 1
 
< 0.1%
126000 7
0.1%
140000 1
 
< 0.1%
ValueCountFrequency (%)
30952564902 1
< 0.1%
18769165501 1
< 0.1%
9870145900 1
< 0.1%
8873618825 1
< 0.1%
8240778980 1
< 0.1%
6760348629 1
< 0.1%
6061369148 1
< 0.1%
5929290783 1
< 0.1%
5112994023 1
< 0.1%
5100604450 1
< 0.1%

연면적
Real number (ℝ)

HIGH CORRELATION 

Distinct5860
Distinct (%)68.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean328.33734
Minimum1
Maximum49237.17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size75.6 KiB
2023-12-12T17:44:35.780139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile18
Q145
median103.83
Q3243.027
95-th percentile1077.358
Maximum49237.17
Range49236.17
Interquartile range (IQR)198.027

Descriptive statistics

Standard deviation1170.104
Coefficient of variation (CV)3.563725
Kurtosis579.87931
Mean328.33734
Median Absolute Deviation (MAD)72.185
Skewness18.819895
Sum2820089.4
Variance1369143.3
MonotonicityNot monotonic
2023-12-12T17:44:35.980525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18.0 317
 
3.7%
29.95 161
 
1.9%
59.9 55
 
0.6%
36.0 43
 
0.5%
198.0 32
 
0.4%
27.0 30
 
0.3%
40.0 28
 
0.3%
33.542 22
 
0.3%
54.0 18
 
0.2%
9.0 15
 
0.2%
Other values (5850) 7868
91.6%
ValueCountFrequency (%)
1.0 4
< 0.1%
1.04 1
 
< 0.1%
2.0 1
 
< 0.1%
2.1 2
< 0.1%
3.0 1
 
< 0.1%
3.3 1
 
< 0.1%
4.0 1
 
< 0.1%
4.2 1
 
< 0.1%
4.5 1
 
< 0.1%
4.86 1
 
< 0.1%
ValueCountFrequency (%)
49237.17 1
< 0.1%
39176.5 1
< 0.1%
27017.45 1
< 0.1%
21278.9 1
< 0.1%
21166.67 1
< 0.1%
17896.71 1
< 0.1%
16972.33 1
< 0.1%
15139.64 1
< 0.1%
14855.93 1
< 0.1%
11344.12 1
< 0.1%

기준일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
Minimum2023-07-28 00:00:00
Maximum2023-07-28 00:00:00
2023-12-12T17:44:36.125021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:44:36.238744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T17:44:28.813651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:44:25.168315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:44:25.864707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:44:26.621503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:44:27.421352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:44:28.134174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:44:28.916726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:44:25.286984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:44:25.992897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:44:26.790266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:44:27.545265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:44:28.253824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:44:29.064472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:44:25.389633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:44:26.132384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:44:26.911407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:44:27.708646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:44:28.391854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:44:29.162624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:44:25.485771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:44:26.248057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:44:27.014207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:44:27.832656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:44:28.496680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:44:29.272347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:44:25.600059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:44:26.375344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:44:27.118105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:44:27.923437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:44:28.588116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:44:29.386604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:44:25.737314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:44:26.505790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:44:27.287812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:44:28.031298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:44:28.706027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:44:36.325689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동특수지본번부번동용도구분시가표준액(원)연면적
법정동1.0000.2290.1780.3390.1010.3940.0310.087
특수지0.2291.0000.0000.0000.3900.1330.0000.000
본번0.1780.0001.0000.0000.0000.1130.0000.081
부번0.3390.0000.0001.0000.0000.0890.0000.000
동0.1010.3900.0000.0001.0000.0640.0000.000
용도구분0.3940.1330.1130.0890.0641.0000.0860.114
시가표준액(원)0.0310.0000.0000.0000.0000.0861.0000.902
연면적0.0870.0000.0810.0000.0000.1140.9021.000
2023-12-12T17:44:36.461909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
용도구분특수지
용도구분1.0000.142
특수지0.1421.000
2023-12-12T17:44:36.591587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동본번부번동시가표준액(원)연면적특수지용도구분
법정동1.000-0.4510.032-0.045-0.1930.0300.1750.212
본번-0.4511.000-0.0610.2020.111-0.0290.0000.075
부번0.032-0.0611.000-0.110-0.142-0.0910.0000.045
동-0.0450.202-0.1101.000-0.022-0.0240.2620.044
시가표준액(원)-0.1930.111-0.142-0.0221.0000.8190.0000.051
연면적0.030-0.029-0.091-0.0240.8191.0000.0000.061
특수지0.1750.0000.0000.2620.0000.0001.0000.142
용도구분0.2120.0750.0450.0440.0510.0610.1421.000

Missing values

2023-12-12T17:44:29.565611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:44:29.814128image/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

시도시군구명자치단체코드과세연도법정동법정리특수지본번부번동호용도구분물건지시가표준액(원)연면적기준일자
0경기도동두천시4125020231010129101Ⅴ. 사회문화용 건물경기도 동두천시 송내동 29-14659712097.282023-07-28
1경기도동두천시4125020231010136011Ⅳ. 농수산용 건물경기도 동두천시 송내동 36-0647640001458.02023-07-28
2경기도동두천시4125020231010136021Ⅳ. 농수산용 건물경기도 동두천시 송내동 36-0516983501116.832023-07-28
3경기도동두천시4125020231010145101Ⅲ. 공업용 건물경기도 동두천시 송내동 45-186400018.02023-07-28
4경기도동두천시4125020231010145401Ⅱ. 상업용 건물경기도 동두천시 송내동 45-44252800096.02023-07-28
5경기도동두천시4125020231010154201Ⅳ. 농수산용 건물경기도 동두천시 송내동 54-259040018.02023-07-28
6경기도동두천시4125020231010154411Ⅱ. 상업용 건물경기도 동두천시 송내동 54-47773080099.42023-07-28
7경기도동두천시4125020231010154711Ⅲ. 공업용 건물경기도 동두천시 송내동 54-7213120018.02023-07-28
8경기도동두천시4125020231010170001Ⅲ. 공업용 건물경기도 동두천시 송내동 70-027000018.02023-07-28
9경기도동두천시4125020231010184001Ⅲ. 공업용 건물경기도 동두천시 송내동 84-015360012.02023-07-28
시도시군구명자치단체코드과세연도법정동법정리특수지본번부번동호용도구분물건지시가표준액(원)연면적기준일자
8579경기도동두천시412502023112011100011Ⅵ. 공공용 건물경기도 동두천시 상패동 1100-01952286059.342023-07-28
8580경기도동두천시412502023112011107101Ⅰ. 주거용 건물경기도 동두천시 상패동 1107-19436500002330.02023-07-28
8581경기도동두천시412502023112011107201Ⅰ. 주거용 건물경기도 동두천시 상패동 1107-23879300001005.02023-07-28
8582경기도동두천시412502023112011107311Ⅴ. 사회문화용 건물경기도 동두천시 상패동 1107-328692080142.042023-07-28
8583경기도동두천시412502023112011107401Ⅵ. 공공용 건물경기도 동두천시 상패동 1107-43750400064.02023-07-28
8584경기도동두천시4125020231120282911Ⅱ. 상업용 건물경기도 동두천시 상패동 산 8-292029500099.02023-07-28
8585경기도동두천시4125020231120282911Ⅵ. 공공용 건물경기도 동두천시 상패동 산 8-29301950016.52023-07-28
8586경기도동두천시4125020231120282911Ⅴ. 사회문화용 건물경기도 동두천시 상패동 산 8-291237500099.02023-07-28
8587경기도동두천시4125020231120211011Ⅴ. 사회문화용 건물경기도 동두천시 상패동 산 11-0299628073.082023-07-28
8588경기도동두천시4125020231120219011Ⅲ. 공업용 건물경기도 동두천시 상패동 산 19-027000018.02023-07-28