Overview

Dataset statistics

Number of variables13
Number of observations10000
Missing cells9488
Missing cells (%)7.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 MiB
Average record size in memory119.0 B

Variable types

Numeric7
Text2
Categorical3
DateTime1

Dataset

Description개별주택가격은 국토교통부장관이 매년 공시하는 표준주택가격을 기준으로 시장·군수·구청장이 조사한 개별주택의 특성과 비교표준주택의 특성을 비교하여 국토교통부장관이 작성·공급한 「주택가격비준표」 상의 주택특성 차이에 따른 가격배율을 산출하고 이를 표준주택가격에 곱하여 산정한 후 한국부동산원의 검증을 받아 주택소유자 등의 의견수렴과 시·군·구 부동산가격공시위원회 심의 등의 절차를 거쳐 시장·군수 ·구청장이 결정 공시하는 개별주택의 가격
Author경상남도 하동군
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15013457

Alerts

데이터기준일자 has constant value ""Constant
전체면적(제곱미터) is highly overall correlated with 대지면적High correlation
공시면적(제곱미터) is highly overall correlated with 건물연면적High correlation
대지면적 is highly overall correlated with 전체면적(제곱미터) and 1 other fieldsHigh correlation
건물연면적 is highly overall correlated with 공시면적(제곱미터) and 1 other fieldsHigh correlation
가격 is highly overall correlated with 대지면적 and 1 other fieldsHigh correlation
용도지역 is highly imbalanced (55.5%)Imbalance
건물용도 is highly imbalanced (90.7%)Imbalance
비고 has 9488 (94.9%) missing valuesMissing
동 번호 is highly skewed (γ1 = 99.99975131)Skewed
전체면적(제곱미터) is highly skewed (γ1 = 44.0442252)Skewed
일련 번호 has unique valuesUnique
동 번호 has 178 (1.8%) zerosZeros

Reproduction

Analysis started2023-12-11 00:31:24.048020
Analysis finished2023-12-11 00:31:32.217361
Duration8.17 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일련 번호
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8352.9085
Minimum3
Maximum16668
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T09:31:32.290029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile825.95
Q14222.5
median8354.5
Q312502.5
95-th percentile15844.05
Maximum16668
Range16665
Interquartile range (IQR)8280

Descriptive statistics

Standard deviation4808.4738
Coefficient of variation (CV)0.5756646
Kurtosis-1.1923836
Mean8352.9085
Median Absolute Deviation (MAD)4139.5
Skewness-0.00062029501
Sum83529085
Variance23121420
MonotonicityNot monotonic
2023-12-11T09:31:32.436523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16419 1
 
< 0.1%
7485 1
 
< 0.1%
9849 1
 
< 0.1%
14600 1
 
< 0.1%
3887 1
 
< 0.1%
10337 1
 
< 0.1%
12355 1
 
< 0.1%
13543 1
 
< 0.1%
10593 1
 
< 0.1%
12208 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
3 1
< 0.1%
4 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
15 1
< 0.1%
16 1
< 0.1%
ValueCountFrequency (%)
16668 1
< 0.1%
16666 1
< 0.1%
16665 1
< 0.1%
16663 1
< 0.1%
16662 1
< 0.1%
16660 1
< 0.1%
16658 1
< 0.1%
16657 1
< 0.1%
16655 1
< 0.1%
16654 1
< 0.1%

소재지
Text

Distinct9883
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T09:31:32.822058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length16.2371
Min length13

Characters and Unicode

Total characters162371
Distinct characters127
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

Unique9786 ?
Unique (%)97.9%

Sample

1st row하동군 금성면 갈사리 463
2nd row하동군 청암면 평촌리 698-1
3rd row하동군 금남면 계천리 222-3
4th row하동군 적량면 관리 356-1
5th row하동군 금남면 진정리 802
ValueCountFrequency (%)
하동군 10000
25.0%
하동읍 1329
 
3.3%
악양면 1107
 
2.8%
진교면 1079
 
2.7%
옥종면 1014
 
2.5%
금남면 863
 
2.2%
화개면 785
 
2.0%
금성면 613
 
1.5%
고전면 602
 
1.5%
적량면 590
 
1.5%
Other values (5644) 22082
55.1%
2023-12-11T09:31:33.322905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
30064
18.5%
동 11678
 
7.2%
하 11412
 
7.0%
군 10000
 
6.2%
리 10000
 
6.2%
면 8671
 
5.3%
1 7262
 
4.5%
- 5683
 
3.5%
2 4633
 
2.9%
3 4120
 
2.5%
Other values (117) 58848
36.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 89600
55.2%
Decimal Number 37024
22.8%
Space Separator 30064
 
18.5%
Dash Punctuation 5683
 
3.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 11678
 
13.0%
하 11412
 
12.7%
군 10000
 
11.2%
리 10000
 
11.2%
면 8671
 
9.7%
양 1964
 
2.2%
읍 1850
 
2.1%
금 1560
 
1.7%
천 1513
 
1.7%
진 1412
 
1.6%
Other values (105) 29540
33.0%
Decimal Number
ValueCountFrequency (%)
1 7262
19.6%
2 4633
12.5%
3 4120
11.1%
4 3800
10.3%
5 3323
9.0%
6 3266
8.8%
7 2950
8.0%
8 2618
 
7.1%
9 2579
 
7.0%
0 2473
 
6.7%
Space Separator
ValueCountFrequency (%)
30064
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5683
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 89600
55.2%
Common 72771
44.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 11678
 
13.0%
하 11412
 
12.7%
군 10000
 
11.2%
리 10000
 
11.2%
면 8671
 
9.7%
양 1964
 
2.2%
읍 1850
 
2.1%
금 1560
 
1.7%
천 1513
 
1.7%
진 1412
 
1.6%
Other values (105) 29540
33.0%
Common
ValueCountFrequency (%)
30064
41.3%
1 7262
 
10.0%
- 5683
 
7.8%
2 4633
 
6.4%
3 4120
 
5.7%
4 3800
 
5.2%
5 3323
 
4.6%
6 3266
 
4.5%
7 2950
 
4.1%
8 2618
 
3.6%
Other values (2) 5052
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 89600
55.2%
ASCII 72771
44.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
30064
41.3%
1 7262
 
10.0%
- 5683
 
7.8%
2 4633
 
6.4%
3 4120
 
5.7%
4 3800
 
5.2%
5 3323
 
4.6%
6 3266
 
4.5%
7 2950
 
4.1%
8 2618
 
3.6%
Other values (2) 5052
 
6.9%
Hangul
ValueCountFrequency (%)
동 11678
 
13.0%
하 11412
 
12.7%
군 10000
 
11.2%
리 10000
 
11.2%
면 8671
 
9.7%
양 1964
 
2.2%
읍 1850
 
2.1%
금 1560
 
1.7%
천 1513
 
1.7%
진 1412
 
1.6%
Other values (105) 29540
33.0%

동 번호
Real number (ℝ)

SKEWED  ZEROS 

Distinct13
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.8948
Minimum0
Maximum38023
Zeros178
Zeros (%)1.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T09:31:33.444494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile2
Maximum38023
Range38023
Interquartile range (IQR)0

Descriptive statistics

Standard deviation380.21939
Coefficient of variation (CV)77.678228
Kurtosis9999.9668
Mean4.8948
Median Absolute Deviation (MAD)0
Skewness99.999751
Sum48948
Variance144566.78
MonotonicityNot monotonic
2023-12-11T09:31:33.564999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
1 8980
89.8%
2 701
 
7.0%
0 178
 
1.8%
3 91
 
0.9%
4 23
 
0.2%
5 11
 
0.1%
6 4
 
< 0.1%
7 4
 
< 0.1%
8 3
 
< 0.1%
11 2
 
< 0.1%
Other values (3) 3
 
< 0.1%
ValueCountFrequency (%)
0 178
 
1.8%
1 8980
89.8%
2 701
 
7.0%
3 91
 
0.9%
4 23
 
0.2%
5 11
 
0.1%
6 4
 
< 0.1%
7 4
 
< 0.1%
8 3
 
< 0.1%
11 2
 
< 0.1%
ValueCountFrequency (%)
38023 1
 
< 0.1%
13 1
 
< 0.1%
12 1
 
< 0.1%
11 2
 
< 0.1%
8 3
 
< 0.1%
7 4
 
< 0.1%
6 4
 
< 0.1%
5 11
 
0.1%
4 23
 
0.2%
3 91
0.9%

전체면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct1701
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean581.30363
Minimum9
Maximum220752
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T09:31:33.751522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile116
Q1242
median374
Q3576
95-th percentile1015
Maximum220752
Range220743
Interquartile range (IQR)334

Descriptive statistics

Standard deviation3626.7328
Coefficient of variation (CV)6.2389647
Kurtosis2288.5305
Mean581.30363
Median Absolute Deviation (MAD)155
Skewness44.044225
Sum5813036.3
Variance13153191
MonotonicityNot monotonic
2023-12-11T09:31:33.893680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
660.0 176
 
1.8%
330.0 62
 
0.6%
298.0 54
 
0.5%
198.0 49
 
0.5%
165.0 47
 
0.5%
347.0 46
 
0.5%
218.0 46
 
0.5%
248.0 46
 
0.5%
271.0 45
 
0.4%
231.0 45
 
0.4%
Other values (1691) 9384
93.8%
ValueCountFrequency (%)
9.0 1
 
< 0.1%
11.0 1
 
< 0.1%
17.0 3
< 0.1%
20.0 1
 
< 0.1%
23.0 3
< 0.1%
27.0 1
 
< 0.1%
28.0 1
 
< 0.1%
30.0 3
< 0.1%
31.0 1
 
< 0.1%
33.0 2
< 0.1%
ValueCountFrequency (%)
220752.0 1
< 0.1%
190043.0 1
< 0.1%
108210.0 2
< 0.1%
69985.0 1
< 0.1%
58658.0 1
< 0.1%
54753.0 1
< 0.1%
42294.0 1
< 0.1%
39853.0 1
< 0.1%
37292.0 1
< 0.1%
34215.0 1
< 0.1%

공시면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct5135
Distinct (%)51.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean109.25222
Minimum8.2
Maximum3863.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T09:31:34.050178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8.2
5-th percentile33
Q162
median89.3
Q3127.11
95-th percentile243.52
Maximum3863.2
Range3855
Interquartile range (IQR)65.11

Descriptive statistics

Standard deviation102.32251
Coefficient of variation (CV)0.93657145
Kurtosis282.61547
Mean109.25222
Median Absolute Deviation (MAD)30.7
Skewness11.221642
Sum1092522.2
Variance10469.897
MonotonicityNot monotonic
2023-12-11T09:31:34.186689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
49.5 58
 
0.6%
59.5 41
 
0.4%
60.0 35
 
0.4%
66.0 30
 
0.3%
82.6 29
 
0.3%
33.0 26
 
0.3%
66.1 26
 
0.3%
50.0 24
 
0.2%
26.4 24
 
0.2%
99.0 23
 
0.2%
Other values (5125) 9684
96.8%
ValueCountFrequency (%)
8.2 1
< 0.1%
8.6 1
< 0.1%
8.9 1
< 0.1%
9.9 1
< 0.1%
10.2 1
< 0.1%
10.6 1
< 0.1%
10.9 1
< 0.1%
11.9 1
< 0.1%
12.5 1
< 0.1%
12.8 2
< 0.1%
ValueCountFrequency (%)
3863.2 1
< 0.1%
2966.68 1
< 0.1%
2061.96 1
< 0.1%
1553.48 1
< 0.1%
1551.28 1
< 0.1%
1332.59 1
< 0.1%
1309.73 1
< 0.1%
1281.37 1
< 0.1%
1238.34 1
< 0.1%
1181.73 1
< 0.1%

대지면적
Real number (ℝ)

HIGH CORRELATION 

Distinct2887
Distinct (%)28.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean386.54666
Minimum3.44
Maximum4105.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T09:31:34.351279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.44
5-th percentile86
Q1210
median332
Q3508
95-th percentile849.715
Maximum4105.8
Range4102.36
Interquartile range (IQR)298

Descriptive statistics

Standard deviation253.51159
Coefficient of variation (CV)0.65583699
Kurtosis10.042319
Mean386.54666
Median Absolute Deviation (MAD)144
Skewness1.9239552
Sum3865466.6
Variance64268.128
MonotonicityNot monotonic
2023-12-11T09:31:34.533303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
660.0 154
 
1.5%
330.0 55
 
0.5%
298.0 48
 
0.5%
198.0 44
 
0.4%
165.0 43
 
0.4%
271.0 43
 
0.4%
231.0 43
 
0.4%
347.0 41
 
0.4%
258.0 41
 
0.4%
238.0 41
 
0.4%
Other values (2877) 9447
94.5%
ValueCountFrequency (%)
3.44 1
< 0.1%
8.52 1
< 0.1%
9.0 1
< 0.1%
9.4 1
< 0.1%
10.12 1
< 0.1%
11.13 1
< 0.1%
11.3 1
< 0.1%
12.58 1
< 0.1%
13.24 1
< 0.1%
14.22 1
< 0.1%
ValueCountFrequency (%)
4105.8 1
< 0.1%
2917.0 1
< 0.1%
2555.0 1
< 0.1%
2363.0 1
< 0.1%
2188.0 1
< 0.1%
2184.0 1
< 0.1%
2150.0 1
< 0.1%
2142.14 1
< 0.1%
2070.0 1
< 0.1%
1944.0 1
< 0.1%

건물연면적
Real number (ℝ)

HIGH CORRELATION 

Distinct4757
Distinct (%)47.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean91.764544
Minimum8.2
Maximum693
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T09:31:34.676105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8.2
5-th percentile31.797
Q159.5
median84.41
Q3111.1925
95-th percentile178.1065
Maximum693
Range684.8
Interquartile range (IQR)51.6925

Descriptive statistics

Standard deviation49.929945
Coefficient of variation (CV)0.54410934
Kurtosis17.359603
Mean91.764544
Median Absolute Deviation (MAD)25.31
Skewness2.6194072
Sum917645.44
Variance2492.9995
MonotonicityNot monotonic
2023-12-11T09:31:34.859607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
49.5 60
 
0.6%
59.5 45
 
0.4%
60.0 35
 
0.4%
82.6 32
 
0.3%
66.0 30
 
0.3%
66.1 28
 
0.3%
50.0 26
 
0.3%
33.0 26
 
0.3%
26.4 25
 
0.2%
99.0 24
 
0.2%
Other values (4747) 9669
96.7%
ValueCountFrequency (%)
8.2 1
< 0.1%
8.6 1
< 0.1%
8.9 1
< 0.1%
9.9 1
< 0.1%
10.2 1
< 0.1%
10.6 1
< 0.1%
10.9 1
< 0.1%
11.9 1
< 0.1%
12.5 1
< 0.1%
12.8 2
< 0.1%
ValueCountFrequency (%)
693.0 1
< 0.1%
657.28 1
< 0.1%
655.2 1
< 0.1%
647.92 1
< 0.1%
617.98 1
< 0.1%
594.31 1
< 0.1%
593.2 1
< 0.1%
566.91 1
< 0.1%
541.71 1
< 0.1%
540.91 1
< 0.1%

용도지역
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
계관
7253 
보관
854 
2주
816 
생관
 
352
농림
 
335
Other values (6)
 
390

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
계관 7253
72.5%
보관 854
 
8.5%
2주 816
 
8.2%
생관 352
 
3.5%
농림 335
 
3.4%
일상 143
 
1.4%
자연 116
 
1.2%
준주 40
 
0.4%
1주 33
 
0.3%
자보 31
 
0.3%

Length

2023-12-11T09:31:35.014053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
계관 7253
72.5%
보관 854
 
8.5%
2주 816
 
8.2%
생관 352
 
3.5%
농림 335
 
3.4%
일상 143
 
1.4%
자연 116
 
1.2%
준주 40
 
0.4%
1주 33
 
0.3%
자보 31
 
0.3%

건물용도
Categorical

IMBALANCE 

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
단독
9507 
주상
 
276
주산
 
125
다가구
 
63
기타복합
 
11
Other values (11)
 
18

Length

Max length4
Median length2
Mean length2.0104
Min length2

Unique

Unique7 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
단독 9507
95.1%
주상 276
 
2.8%
주산 125
 
1.2%
다가구 63
 
0.6%
기타복합 11
 
0.1%
1종근생 5
 
0.1%
주거단독 2
 
< 0.1%
종교 2
 
< 0.1%
공장 2
 
< 0.1%
동식물 1
 
< 0.1%
Other values (6) 6
 
0.1%

Length

2023-12-11T09:31:35.160385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
단독 9507
95.1%
주상 276
 
2.8%
주산 125
 
1.2%
다가구 63
 
0.6%
기타복합 11
 
0.1%
1종근생 5
 
< 0.1%
주거단독 2
 
< 0.1%
종교 2
 
< 0.1%
공장 2
 
< 0.1%
동식물 1
 
< 0.1%
Other values (6) 6
 
0.1%

건물구조
Categorical

Distinct23
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
목
3127 
블록
2313 
벽돌
1370 
연와
913 
경철
910 
Other values (18)
1367 

Length

Max length3
Median length2
Mean length1.6899
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row연와
2nd row철근
3rd row블록
4th row연와
5th row벽돌

Common Values

ValueCountFrequency (%)
목 3127
31.3%
블록 2313
23.1%
벽돌 1370
13.7%
연와 913
 
9.1%
경철 910
 
9.1%
철근 781
 
7.8%
목구 382
 
3.8%
철골 86
 
0.9%
조판 30
 
0.3%
보블 19
 
0.2%
Other values (13) 69
 
0.7%

Length

2023-12-11T09:31:35.299832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
목 3127
31.3%
블록 2313
23.1%
벽돌 1370
13.7%
연와 913
 
9.1%
경철 910
 
9.1%
철근 781
 
7.8%
목구 382
 
3.8%
철골 86
 
0.9%
조판 30
 
0.3%
보블 19
 
0.2%
Other values (13) 69
 
0.7%

가격
Real number (ℝ)

HIGH CORRELATION 

Distinct1617
Distinct (%)16.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38810777
Minimum411000
Maximum6.66 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T09:31:35.444646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum411000
5-th percentile6950000
Q114800000
median26800000
Q349600000
95-th percentile1.07 × 108
Maximum6.66 × 108
Range6.65589 × 108
Interquartile range (IQR)34800000

Descriptive statistics

Standard deviation38807278
Coefficient of variation (CV)0.99990985
Kurtosis29.946622
Mean38810777
Median Absolute Deviation (MAD)14700000
Skewness3.8434177
Sum3.8810777 × 1011
Variance1.5060048 × 1015
MonotonicityNot monotonic
2023-12-11T09:31:35.608876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14000000 39
 
0.4%
12400000 39
 
0.4%
11200000 38
 
0.4%
14100000 37
 
0.4%
21700000 33
 
0.3%
12800000 33
 
0.3%
13800000 33
 
0.3%
19800000 32
 
0.3%
10000000 31
 
0.3%
16500000 31
 
0.3%
Other values (1607) 9654
96.5%
ValueCountFrequency (%)
411000 1
< 0.1%
551000 1
< 0.1%
564000 1
< 0.1%
610000 1
< 0.1%
822000 1
< 0.1%
882000 1
< 0.1%
893000 1
< 0.1%
904000 1
< 0.1%
1000000 1
< 0.1%
1040000 1
< 0.1%
ValueCountFrequency (%)
666000000 1
< 0.1%
568000000 1
< 0.1%
540000000 1
< 0.1%
492000000 1
< 0.1%
480000000 1
< 0.1%
468000000 1
< 0.1%
399000000 1
< 0.1%
397000000 1
< 0.1%
392000000 1
< 0.1%
382000000 1
< 0.1%

비고
Text

MISSING 

Distinct444
Distinct (%)86.7%
Missing9488
Missing (%)94.9%
Memory size156.2 KiB
2023-12-11T09:31:36.034589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length17
Mean length6.4472656
Min length2

Characters and Unicode

Total characters3301
Distinct characters39
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

Unique430 ?
Unique (%)84.0%

Sample

1st row910-2, 924-156
2nd row563-1, 564-4
3rd row817-9
4th row364-2
5th row366-5, 366-7 외 1
ValueCountFrequency (%)
건물만공시 38
 
5.9%
외 21
 
3.3%
국불미공시 16
 
2.5%
1 15
 
2.3%
국공유미공시 6
 
0.9%
2 4
 
0.6%
837-2 2
 
0.3%
113 2
 
0.3%
272-3 2
 
0.3%
3 2
 
0.3%
Other values (519) 532
83.1%
2023-12-11T09:31:36.942780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 438
13.3%
- 437
13.2%
2 302
 
9.1%
3 275
 
8.3%
4 194
 
5.9%
190
 
5.8%
5 190
 
5.8%
8 183
 
5.5%
9 169
 
5.1%
7 166
 
5.0%
Other values (29) 757
22.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2209
66.9%
Dash Punctuation 437
 
13.2%
Other Letter 339
 
10.3%
Space Separator 190
 
5.8%
Other Punctuation 84
 
2.5%
Lowercase Letter 28
 
0.8%
Uppercase Letter 14
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 68
20.1%
시 62
18.3%
물 38
11.2%
건 38
11.2%
만 38
11.2%
미 24
 
7.1%
국 22
 
6.5%
외 21
 
6.2%
불 16
 
4.7%
유 6
 
1.8%
Other values (4) 6
 
1.8%
Decimal Number
ValueCountFrequency (%)
1 438
19.8%
2 302
13.7%
3 275
12.4%
4 194
8.8%
5 190
8.6%
8 183
8.3%
9 169
 
7.7%
7 166
 
7.5%
6 152
 
6.9%
0 140
 
6.3%
Lowercase Letter
ValueCountFrequency (%)
e 8
28.6%
b 7
25.0%
a 5
17.9%
n 3
 
10.7%
r 2
 
7.1%
p 1
 
3.6%
y 1
 
3.6%
u 1
 
3.6%
Uppercase Letter
ValueCountFrequency (%)
F 7
50.0%
M 3
21.4%
J 3
21.4%
S 1
 
7.1%
Dash Punctuation
ValueCountFrequency (%)
- 437
100.0%
Space Separator
ValueCountFrequency (%)
190
100.0%
Other Punctuation
ValueCountFrequency (%)
, 84
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2920
88.5%
Hangul 339
 
10.3%
Latin 42
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 68
20.1%
시 62
18.3%
물 38
11.2%
건 38
11.2%
만 38
11.2%
미 24
 
7.1%
국 22
 
6.5%
외 21
 
6.2%
불 16
 
4.7%
유 6
 
1.8%
Other values (4) 6
 
1.8%
Common
ValueCountFrequency (%)
1 438
15.0%
- 437
15.0%
2 302
10.3%
3 275
9.4%
4 194
6.6%
190
6.5%
5 190
6.5%
8 183
6.3%
9 169
 
5.8%
7 166
 
5.7%
Other values (3) 376
12.9%
Latin
ValueCountFrequency (%)
e 8
19.0%
b 7
16.7%
F 7
16.7%
a 5
11.9%
M 3
 
7.1%
J 3
 
7.1%
n 3
 
7.1%
r 2
 
4.8%
S 1
 
2.4%
p 1
 
2.4%
Other values (2) 2
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2962
89.7%
Hangul 339
 
10.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 438
14.8%
- 437
14.8%
2 302
10.2%
3 275
9.3%
4 194
6.5%
190
6.4%
5 190
6.4%
8 183
6.2%
9 169
 
5.7%
7 166
 
5.6%
Other values (15) 418
14.1%
Hangul
ValueCountFrequency (%)
공 68
20.1%
시 62
18.3%
물 38
11.2%
건 38
11.2%
만 38
11.2%
미 24
 
7.1%
국 22
 
6.5%
외 21
 
6.2%
불 16
 
4.7%
유 6
 
1.8%
Other values (4) 6
 
1.8%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-06-19 00:00:00
Maximum2023-06-19 00:00:00
2023-12-11T09:31:37.069290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:37.156766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-11T09:31:31.155798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:26.119762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:26.871327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:27.682764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:28.575144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:29.392781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:30.422054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:31.248746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:26.233078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:26.975316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:27.806178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:28.689339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:29.523716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:30.523939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:31.344815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:26.334986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:27.075915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:27.931906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:28.820158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:29.647487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:30.646271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:31.435624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:26.424414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:27.180793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:28.054803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:28.937364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:29.764637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:30.762327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:31.542393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:26.536449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:27.327328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:28.204287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:29.061317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:30.127520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:30.884698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:31.636218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:26.631162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:27.438550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:28.327164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:29.162778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:30.209021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:30.975535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:31.749894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:26.755112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:27.568205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:28.457808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:29.280758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:30.332666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:31:31.062783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:31:37.241782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련 번호동 번호전체면적(제곱미터)공시면적(제곱미터)대지면적건물연면적용도지역건물용도건물구조가격
일련 번호1.0000.0030.0360.0580.1450.1020.5800.1740.2600.140
동 번호0.0031.0000.0000.0000.0000.0100.0000.0000.0000.000
전체면적(제곱미터)0.0360.0001.0000.0000.0000.0000.1810.0000.0000.000
공시면적(제곱미터)0.0580.0000.0001.0000.0440.3740.1940.4490.1880.351
대지면적0.1450.0000.0000.0441.0000.3430.1830.1220.1780.461
건물연면적0.1020.0100.0000.3740.3431.0000.1430.3500.4180.745
용도지역0.5800.0000.1810.1940.1830.1431.0000.3370.2690.215
건물용도0.1740.0000.0000.4490.1220.3500.3371.0000.4120.376
건물구조0.2600.0000.0000.1880.1780.4180.2690.4121.0000.489
가격0.1400.0000.0000.3510.4610.7450.2150.3760.4891.000
2023-12-11T09:31:37.371918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
용도지역건물용도건물구조
용도지역1.0000.1340.097
건물용도0.1341.0000.136
건물구조0.0970.1361.000
2023-12-11T09:31:37.469169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련 번호동 번호전체면적(제곱미터)공시면적(제곱미터)대지면적건물연면적가격용도지역건물용도건물구조
일련 번호1.000-0.0360.1250.0010.1360.024-0.0980.2920.0690.099
동 번호-0.0361.000-0.000-0.049-0.052-0.044-0.0160.0000.0000.000
전체면적(제곱미터)0.125-0.0001.0000.3560.8480.3540.4540.0900.0000.000
공시면적(제곱미터)0.001-0.0490.3561.0000.2190.8810.4780.0920.1730.076
대지면적0.136-0.0520.8480.2191.0000.3900.5090.0840.0500.069
건물연면적0.024-0.0440.3540.8810.3901.0000.5430.0610.1450.168
가격-0.098-0.0160.4540.4780.5090.5431.0000.0980.1650.212
용도지역0.2920.0000.0900.0920.0840.0610.0981.0000.1340.097
건물용도0.0690.0000.0000.1730.0500.1450.1650.1341.0000.136
건물구조0.0990.0000.0000.0760.0690.1680.2120.0970.1361.000

Missing values

2023-12-11T09:31:31.917756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:31:32.136918image/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

일련 번호소재지동 번호전체면적(제곱미터)공시면적(제곱미터)대지면적건물연면적용도지역건물용도건물구조가격비고데이터기준일자
1641816419하동군 금성면 갈사리 4631424.0125.5424.0125.5계관단독연와36800000910-2, 924-1562023-06-19
1342213423하동군 청암면 평촌리 698-12346.086.34346.086.34계관단독철근65100000<NA>2023-06-19
95029503하동군 금남면 계천리 222-31152.082.6152.082.6계관단독블록23100000<NA>2023-06-19
54965497하동군 적량면 관리 356-11337.0120.4337.0120.4계관단독연와14500000<NA>2023-06-19
94299430하동군 금남면 진정리 8021479.063.8479.063.8계관단독벽돌34700000<NA>2023-06-19
90919092하동군 금남면 대송리 5301448.083.25448.083.25계관단독경철67400000<NA>2023-06-19
76057606하동군 고전면 신월리 563-41526.073.35526.073.35생관단독목구56100000563-1, 564-42023-06-19
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