Overview

Dataset statistics

Number of variables13
Number of observations119
Missing cells156
Missing cells (%)10.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.8 KiB
Average record size in memory110.1 B

Variable types

Categorical8
Text2
Numeric3

Dataset

Description영월군 관내 다가구주택 및 오피스텔 현황에 관한 데이터입니다.대지위치주소, 대지면적, 건축면적, 지상층수, 지하층수, 가구수의 정보가 포함되어있습니다.
Author강원특별자치도 영월군
URLhttps://www.data.go.kr/data/15126996/fileData.do

Alerts

시군구코드명 has constant value ""Constant
주용도코드명 is highly overall correlated with 대지면적(제곱미터) and 6 other fieldsHigh correlation
기타용도내용 is highly overall correlated with 대지면적(제곱미터) and 5 other fieldsHigh correlation
(층)주용도코드명 is highly overall correlated with 대지면적(제곱미터) and 6 other fieldsHigh correlation
지상층수 is highly overall correlated with 가구수 and 3 other fieldsHigh correlation
(층)기타용도내용 is highly overall correlated with 건축면적(제곱미터) and 4 other fieldsHigh correlation
구분 is highly overall correlated with 대지면적(제곱미터) and 6 other fieldsHigh correlation
지하층수 is highly overall correlated with 구분 and 2 other fieldsHigh correlation
대지면적(제곱미터) is highly overall correlated with 구분 and 3 other fieldsHigh correlation
건축면적(제곱미터) is highly overall correlated with 가구수 and 5 other fieldsHigh correlation
가구수 is highly overall correlated with 건축면적(제곱미터) and 4 other fieldsHigh correlation
구분 is highly imbalanced (93.0%)Imbalance
주용도코드명 is highly imbalanced (93.0%)Imbalance
기타용도내용 is highly imbalanced (67.5%)Imbalance
(층)주용도코드명 is highly imbalanced (93.0%)Imbalance
(층)기타용도내용 is highly imbalanced (84.5%)Imbalance
건물명 has 117 (98.3%) missing valuesMissing
대지면적(제곱미터) has 38 (31.9%) missing valuesMissing

Reproduction

Analysis started2024-03-14 19:09:40.792008
Analysis finished2024-03-14 19:09:45.862810
Duration5.07 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
다가구주택
118 
오피스텔
 
1

Length

Max length5
Median length5
Mean length4.9915966
Min length4

Unique

Unique1 ?
Unique (%)0.8%

Sample

1st row오피스텔
2nd row다가구주택
3rd row다가구주택
4th row다가구주택
5th row다가구주택

Common Values

ValueCountFrequency (%)
다가구주택 118
99.2%
오피스텔 1
 
0.8%

Length

2024-03-15T04:09:46.164194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T04:09:46.495292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
다가구주택 118
99.2%
오피스텔 1
 
0.8%

건물명
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing117
Missing (%)98.3%
Memory size1.1 KiB
2024-03-15T04:09:46.941441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters8
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row레스트힐
2nd row단독주택
ValueCountFrequency (%)
레스트힐 1
50.0%
단독주택 1
50.0%
2024-03-15T04:09:47.618000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
레 1
12.5%
스 1
12.5%
트 1
12.5%
힐 1
12.5%
단 1
12.5%
독 1
12.5%
주 1
12.5%
택 1
12.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
레 1
12.5%
스 1
12.5%
트 1
12.5%
힐 1
12.5%
단 1
12.5%
독 1
12.5%
주 1
12.5%
택 1
12.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
레 1
12.5%
스 1
12.5%
트 1
12.5%
힐 1
12.5%
단 1
12.5%
독 1
12.5%
주 1
12.5%
택 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
레 1
12.5%
스 1
12.5%
트 1
12.5%
힐 1
12.5%
단 1
12.5%
독 1
12.5%
주 1
12.5%
택 1
12.5%

시군구코드명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
강원영월군
119 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강원영월군 119
100.0%

Length

2024-03-15T04:09:47.842833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T04:09:48.029043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강원영월군 119
100.0%

대지위치주소
Text

Distinct114
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-03-15T04:09:49.494835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length30
Mean length27.731092
Min length23

Characters and Unicode

Total characters3300
Distinct characters85
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

Unique109 ?
Unique (%)91.6%

Sample

1st row강원특별자치도 영월군 영월읍 하송리 0053
2nd row강원특별자치도 영월군 남면 창원리 0890-0001
3rd row강원특별자치도 영월군 영월읍 하송리 0328-0006
4th row강원특별자치도 영월군 주천면 판운리 0493-0003
5th row강원특별자치도 영월군 산솔면 화원리 0443-0010
ValueCountFrequency (%)
강원특별자치도 119
20.0%
영월군 119
20.0%
영월읍 37
 
6.2%
무릉도원면 22
 
3.7%
김삿갓면 18
 
3.0%
삼옥리 15
 
2.5%
산솔면 11
 
1.8%
와석리 10
 
1.7%
한반도면 9
 
1.5%
남면 9
 
1.5%
Other values (152) 226
38.0%
2024-03-15T04:09:51.165927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
476
 
14.4%
0 363
 
11.0%
영 164
 
5.0%
월 156
 
4.7%
도 156
 
4.7%
원 149
 
4.5%
별 120
 
3.6%
리 119
 
3.6%
군 119
 
3.6%
강 119
 
3.6%
Other values (75) 1359
41.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1958
59.3%
Decimal Number 788
23.9%
Space Separator 476
 
14.4%
Dash Punctuation 78
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 164
 
8.4%
월 156
 
8.0%
도 156
 
8.0%
원 149
 
7.6%
별 120
 
6.1%
리 119
 
6.1%
군 119
 
6.1%
강 119
 
6.1%
치 119
 
6.1%
자 119
 
6.1%
Other values (63) 618
31.6%
Decimal Number
ValueCountFrequency (%)
0 363
46.1%
1 83
 
10.5%
2 55
 
7.0%
3 48
 
6.1%
6 48
 
6.1%
4 46
 
5.8%
7 42
 
5.3%
5 42
 
5.3%
8 35
 
4.4%
9 26
 
3.3%
Space Separator
ValueCountFrequency (%)
476
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 78
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1958
59.3%
Common 1342
40.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 164
 
8.4%
월 156
 
8.0%
도 156
 
8.0%
원 149
 
7.6%
별 120
 
6.1%
리 119
 
6.1%
군 119
 
6.1%
강 119
 
6.1%
치 119
 
6.1%
자 119
 
6.1%
Other values (63) 618
31.6%
Common
ValueCountFrequency (%)
476
35.5%
0 363
27.0%
1 83
 
6.2%
- 78
 
5.8%
2 55
 
4.1%
3 48
 
3.6%
6 48
 
3.6%
4 46
 
3.4%
7 42
 
3.1%
5 42
 
3.1%
Other values (2) 61
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1958
59.3%
ASCII 1342
40.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
476
35.5%
0 363
27.0%
1 83
 
6.2%
- 78
 
5.8%
2 55
 
4.1%
3 48
 
3.6%
6 48
 
3.6%
4 46
 
3.4%
7 42
 
3.1%
5 42
 
3.1%
Other values (2) 61
 
4.5%
Hangul
ValueCountFrequency (%)
영 164
 
8.4%
월 156
 
8.0%
도 156
 
8.0%
원 149
 
7.6%
별 120
 
6.1%
리 119
 
6.1%
군 119
 
6.1%
강 119
 
6.1%
치 119
 
6.1%
자 119
 
6.1%
Other values (63) 618
31.6%

대지면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct76
Distinct (%)93.8%
Missing38
Missing (%)31.9%
Infinite0
Infinite (%)0.0%
Mean2012.1154
Minimum160
Maximum11778
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-15T04:09:51.410679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum160
5-th percentile326
Q1770
median1300
Q31980
95-th percentile6846
Maximum11778
Range11618
Interquartile range (IQR)1210

Descriptive statistics

Standard deviation2328.3151
Coefficient of variation (CV)1.1571479
Kurtosis7.6607365
Mean2012.1154
Median Absolute Deviation (MAD)640
Skewness2.7076943
Sum162981.35
Variance5421051.3
MonotonicityNot monotonic
2024-03-15T04:09:51.711724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1320.0 3
 
2.5%
660.0 2
 
1.7%
495.0 2
 
1.7%
770.0 2
 
1.7%
2214.0 1
 
0.8%
919.0 1
 
0.8%
1740.0 1
 
0.8%
2476.0 1
 
0.8%
556.0 1
 
0.8%
1946.0 1
 
0.8%
Other values (66) 66
55.5%
(Missing) 38
31.9%
ValueCountFrequency (%)
160.0 1
0.8%
274.0 1
0.8%
276.43 1
0.8%
322.0 1
0.8%
326.0 1
0.8%
377.0 1
0.8%
446.0 1
0.8%
469.92 1
0.8%
493.0 1
0.8%
495.0 2
1.7%
ValueCountFrequency (%)
11778.0 1
0.8%
11660.0 1
0.8%
9505.0 1
0.8%
7470.0 1
0.8%
6846.0 1
0.8%
6834.0 1
0.8%
6452.0 1
0.8%
4616.0 1
0.8%
4112.0 1
0.8%
3960.0 1
0.8%

건축면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct118
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean251.61706
Minimum0
Maximum4330.62
Zeros1
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-15T04:09:52.140354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile59.142
Q1107.845
median179.72
Q3280.35
95-th percentile567.218
Maximum4330.62
Range4330.62
Interquartile range (IQR)172.505

Descriptive statistics

Standard deviation412.34484
Coefficient of variation (CV)1.6387794
Kurtosis82.538419
Mean251.61706
Median Absolute Deviation (MAD)74.54
Skewness8.4525584
Sum29942.43
Variance170028.27
MonotonicityNot monotonic
2024-03-15T04:09:52.624758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
176.56 2
 
1.7%
179.72 1
 
0.8%
321.78 1
 
0.8%
172.8 1
 
0.8%
70.07 1
 
0.8%
345.76 1
 
0.8%
168.0 1
 
0.8%
114.98 1
 
0.8%
207.36 1
 
0.8%
73.04 1
 
0.8%
Other values (108) 108
90.8%
ValueCountFrequency (%)
0.0 1
0.8%
27.4 1
0.8%
39.98 1
0.8%
49.2 1
0.8%
51.0 1
0.8%
54.48 1
0.8%
59.66 1
0.8%
63.54 1
0.8%
65.12 1
0.8%
68.4 1
0.8%
ValueCountFrequency (%)
4330.62 1
0.8%
1067.13 1
0.8%
887.15 1
0.8%
691.95 1
0.8%
669.27 1
0.8%
619.76 1
0.8%
561.38 1
0.8%
540.87 1
0.8%
447.3 1
0.8%
440.7 1
0.8%

주용도코드명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
단독주택
118 
공동주택
 
1

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique1 ?
Unique (%)0.8%

Sample

1st row공동주택
2nd row단독주택
3rd row단독주택
4th row단독주택
5th row단독주택

Common Values

ValueCountFrequency (%)
단독주택 118
99.2%
공동주택 1
 
0.8%

Length

2024-03-15T04:09:52.902873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T04:09:53.154564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
단독주택 118
99.2%
공동주택 1
 
0.8%

기타용도내용
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
다가구주택
102 
다가구
13 
다가구 주택
 
2
공동주택
 
1
다가구주태
 
1

Length

Max length6
Median length5
Mean length4.789916
Min length3

Unique

Unique2 ?
Unique (%)1.7%

Sample

1st row공동주택
2nd row다가구주택
3rd row다가구주택
4th row다가구주택
5th row다가구

Common Values

ValueCountFrequency (%)
다가구주택 102
85.7%
다가구 13
 
10.9%
다가구 주택 2
 
1.7%
공동주택 1
 
0.8%
다가구주태 1
 
0.8%

Length

2024-03-15T04:09:53.337239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T04:09:53.525047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
다가구주택 102
84.3%
다가구 15
 
12.4%
주택 2
 
1.7%
공동주택 1
 
0.8%
다가구주태 1
 
0.8%

지상층수
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2
62 
1
46 
3
 
6
4
 
4
<NA>
 
1

Length

Max length4
Median length1
Mean length1.0252101
Min length1

Unique

Unique1 ?
Unique (%)0.8%

Sample

1st row<NA>
2nd row1
3rd row3
4th row2
5th row1

Common Values

ValueCountFrequency (%)
2 62
52.1%
1 46
38.7%
3 6
 
5.0%
4 4
 
3.4%
<NA> 1
 
0.8%

Length

2024-03-15T04:09:53.827622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T04:09:54.173318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 62
52.1%
1 46
38.7%
3 6
 
5.0%
4 4
 
3.4%
na 1
 
0.8%

지하층수
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
0
74 
<NA>
41 
1
 
4

Length

Max length4
Median length1
Mean length2.0336134
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row0
3rd row<NA>
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 74
62.2%
<NA> 41
34.5%
1 4
 
3.4%

Length

2024-03-15T04:09:54.550160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T04:09:54.876881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 74
62.2%
na 41
34.5%
1 4
 
3.4%

가구수
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)15.3%
Missing1
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean6.7033898
Minimum2
Maximum48
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-15T04:09:55.096736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q12
median4
Q38
95-th percentile18
Maximum48
Range46
Interquartile range (IQR)6

Descriptive statistics

Standard deviation7.0192767
Coefficient of variation (CV)1.0471234
Kurtosis14.819017
Mean6.7033898
Median Absolute Deviation (MAD)2
Skewness3.3322651
Sum791
Variance49.270245
MonotonicityNot monotonic
2024-03-15T04:09:55.341181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
2 31
26.1%
4 17
14.3%
3 17
14.3%
8 13
10.9%
6 11
 
9.2%
12 10
 
8.4%
10 4
 
3.4%
5 3
 
2.5%
14 2
 
1.7%
18 2
 
1.7%
Other values (8) 8
 
6.7%
ValueCountFrequency (%)
2 31
26.1%
3 17
14.3%
4 17
14.3%
5 3
 
2.5%
6 11
 
9.2%
8 13
10.9%
9 1
 
0.8%
10 4
 
3.4%
12 10
 
8.4%
14 2
 
1.7%
ValueCountFrequency (%)
48 1
 
0.8%
42 1
 
0.8%
27 1
 
0.8%
24 1
 
0.8%
20 1
 
0.8%
18 2
 
1.7%
16 1
 
0.8%
15 1
 
0.8%
14 2
 
1.7%
12 10
8.4%

(층)주용도코드명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
다가구주택
118 
기타제2종근린생활시설
 
1

Length

Max length11
Median length5
Mean length5.0504202
Min length5

Unique

Unique1 ?
Unique (%)0.8%

Sample

1st row기타제2종근린생활시설
2nd row다가구주택
3rd row다가구주택
4th row다가구주택
5th row다가구주택

Common Values

ValueCountFrequency (%)
다가구주택 118
99.2%
기타제2종근린생활시설 1
 
0.8%

Length

2024-03-15T04:09:55.620470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T04:09:55.898184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
다가구주택 118
99.2%
기타제2종근린생활시설 1
 
0.8%

(층)기타용도내용
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
다가구주택
113 
다가구주택(2가구)
 
2
코아
 
1
다가구주택3가구
 
1
다가구주택(4가구)
 
1

Length

Max length10
Median length5
Mean length5.1344538
Min length2

Unique

Unique4 ?
Unique (%)3.4%

Sample

1st row코아
2nd row다가구주택
3rd row다가구주택
4th row다가구주택
5th row다가구주택

Common Values

ValueCountFrequency (%)
다가구주택 113
95.0%
다가구주택(2가구) 2
 
1.7%
코아 1
 
0.8%
다가구주택3가구 1
 
0.8%
다가구주택(4가구) 1
 
0.8%
다가구 주택 1
 
0.8%

Length

2024-03-15T04:09:56.133058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T04:09:56.334875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
다가구주택 113
94.2%
다가구주택(2가구 2
 
1.7%
코아 1
 
0.8%
다가구주택3가구 1
 
0.8%
다가구주택(4가구 1
 
0.8%
다가구 1
 
0.8%
주택 1
 
0.8%

Interactions

2024-03-15T04:09:43.833883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:09:41.680748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:09:42.963911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:09:44.130036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:09:42.396273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:09:43.223420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:09:44.404234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:09:42.686414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:09:43.473628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T04:09:56.559447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분건물명대지면적(제곱미터)건축면적(제곱미터)주용도코드명기타용도내용지상층수지하층수가구수(층)주용도코드명(층)기타용도내용
구분1.0000.0001.0001.0000.6951.000NaNNaNNaN0.6951.000
건물명0.0001.0000.0000.0000.0000.000NaNNaNNaN0.0000.000
대지면적(제곱미터)1.0000.0001.0000.9161.0000.7980.3230.0000.4041.0000.613
건축면적(제곱미터)1.0000.0000.9161.0001.0000.6640.2410.0000.7471.0000.720
주용도코드명0.6950.0001.0001.0001.0001.000NaNNaNNaN0.6951.000
기타용도내용1.0000.0000.7980.6641.0001.0000.0000.2060.2421.0000.722
지상층수NaNNaN0.3230.241NaN0.0001.0000.4840.899NaN0.000
지하층수NaNNaN0.0000.000NaN0.2060.4841.0000.297NaN0.000
가구수NaNNaN0.4040.747NaN0.2420.8990.2971.000NaN0.000
(층)주용도코드명0.6950.0001.0001.0000.6951.000NaNNaNNaN1.0001.000
(층)기타용도내용1.0000.0000.6130.7201.0000.7220.0000.0000.0001.0001.000
2024-03-15T04:09:57.127508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주용도코드명기타용도내용(층)주용도코드명지상층수(층)기타용도내용구분지하층수
주용도코드명1.0000.9870.4891.0000.9830.4891.000
기타용도내용0.9871.0000.9870.0000.5870.9870.335
(층)주용도코드명0.4890.9871.0001.0000.9830.4891.000
지상층수1.0000.0001.0001.0000.0001.0000.323
(층)기타용도내용0.9830.5870.9830.0001.0000.9830.000
구분0.4890.9870.4891.0000.9831.0001.000
지하층수1.0000.3351.0000.3230.0001.0001.000
2024-03-15T04:09:57.425858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대지면적(제곱미터)건축면적(제곱미터)가구수구분주용도코드명기타용도내용지상층수지하층수(층)주용도코드명(층)기타용도내용
대지면적(제곱미터)1.0000.4180.4090.9610.9610.6970.2240.0000.9610.427
건축면적(제곱미터)0.4181.0000.7520.9910.9910.5930.2290.0000.9910.548
가구수0.4090.7521.0001.0001.0000.1060.5860.3061.0000.000
구분0.9610.9911.0001.0000.4890.9871.0001.0000.4890.983
주용도코드명0.9610.9911.0000.4891.0000.9871.0001.0000.4890.983
기타용도내용0.6970.5930.1060.9870.9871.0000.0000.3350.9870.587
지상층수0.2240.2290.5861.0001.0000.0001.0000.3231.0000.000
지하층수0.0000.0000.3061.0001.0000.3350.3231.0001.0000.000
(층)주용도코드명0.9610.9911.0000.4890.4890.9871.0001.0001.0000.983
(층)기타용도내용0.4270.5480.0000.9830.9830.5870.0000.0000.9831.000

Missing values

2024-03-15T04:09:44.639238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T04:09:45.253116image/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.
2024-03-15T04:09:45.656843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

구분건물명시군구코드명대지위치주소대지면적(제곱미터)건축면적(제곱미터)주용도코드명기타용도내용지상층수지하층수가구수(층)주용도코드명(층)기타용도내용
0오피스텔레스트힐강원영월군강원특별자치도 영월군 영월읍 하송리 00537470.04330.62공동주택공동주택<NA><NA><NA>기타제2종근린생활시설코아
1다가구주택<NA>강원영월군강원특별자치도 영월군 남면 창원리 0890-0001<NA>51.0단독주택다가구주택102다가구주택다가구주택
2다가구주택<NA>강원영월군강원특별자치도 영월군 영월읍 하송리 0328-0006<NA>281.58단독주택다가구주택3<NA>16다가구주택다가구주택
3다가구주택<NA>강원영월군강원특별자치도 영월군 주천면 판운리 0493-0003<NA>75.84단독주택다가구주택202다가구주택다가구주택
4다가구주택<NA>강원영월군강원특별자치도 영월군 산솔면 화원리 0443-0010880.098.0단독주택다가구102다가구주택다가구주택
5다가구주택<NA>강원영월군강원특별자치도 영월군 산솔면 녹전리 0886-0001<NA>238.98단독주택다가구주택208다가구주택다가구주택
6다가구주택<NA>강원영월군강원특별자치도 영월군 무릉도원면 두산리 0727276.43109.99단독주택다가구주택202다가구주택다가구주택
7다가구주택<NA>강원영월군강원특별자치도 영월군 김삿갓면 와석리 0775<NA>128.96단독주택다가구주택2<NA>4다가구주택다가구주택
8다가구주택<NA>강원영월군강원특별자치도 영월군 김삿갓면 예밀리 0008-0011<NA>163.36단독주택다가구주택1<NA>3다가구주택다가구주택
9다가구주택<NA>강원영월군강원특별자치도 영월군 영월읍 문산리 06206834.0285.12단독주택다가구주택206다가구주택다가구주택
구분건물명시군구코드명대지위치주소대지면적(제곱미터)건축면적(제곱미터)주용도코드명기타용도내용지상층수지하층수가구수(층)주용도코드명(층)기타용도내용
109다가구주택<NA>강원영월군강원특별자치도 영월군 산솔면 녹전리 0318377.0128.48단독주택다가구주택203다가구주택다가구주택(2가구)
110다가구주택<NA>강원영월군강원특별자치도 영월군 주천면 판운리 0493-0003<NA>89.62단독주택다가구주택103다가구주택다가구주택
111다가구주택<NA>강원영월군강원특별자치도 영월군 산솔면 이목리 0067<NA>93.7단독주택다가구주택102다가구주택다가구주택
112다가구주택<NA>강원영월군강원특별자치도 영월군 김삿갓면 와석리 0601-00061974.0285.42단독주택다가구216다가구주택다가구주택
113다가구주택<NA>강원영월군강원특별자치도 영월군 영월읍 삼옥리 1578-00041580.0306.92단독주택다가구주택2014다가구주택다가구주택
114다가구주택<NA>강원영월군강원특별자치도 영월군 영월읍 삼옥리 1589-00092040.0249.12단독주택다가구주택202다가구주택다가구주택
115다가구주택<NA>강원영월군강원특별자치도 영월군 상동읍 내덕리 0246-0008842.0136.68단독주택다가구주택1<NA>4다가구주택다가구주택
116다가구주택<NA>강원영월군강원특별자치도 영월군 남면 북쌍리 0024-0004555.083.67단독주택다가구주택102다가구주택다가구주택
117다가구주택<NA>강원영월군강원특별자치도 영월군 김삿갓면 내리 05374112.0121.52단독주택다가구주택102다가구주택다가구주택
118다가구주택<NA>강원영월군강원특별자치도 영월군 한반도면 후탄리 0561-0005<NA>182.86단독주택다가구주택2<NA>8다가구주택다가구주택