Overview

Dataset statistics

Number of variables12
Number of observations240
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory24.0 KiB
Average record size in memory102.5 B

Variable types

Numeric4
Categorical5
Text2
DateTime1

Dataset

Description강원특별자치도 춘천시 내 원룸 및 오피스텔 형태 주택에 대한 데이터로, 시군구명, 주소, 주 용도, 세부 용도, 가구수, 연면적, 층수, 구조 등에 관한 데이터이다.
Author강원특별자치도 춘천시
URLhttps://www.data.go.kr/data/15127063/fileData.do

Alerts

시군구명 has constant value ""Constant
주_용도 has constant value ""Constant
데이터기준일 has constant value ""Constant
다가구주택 가구수 is highly overall correlated with 연면적(제곱미터)High correlation
연면적(제곱미터) is highly overall correlated with 다가구주택 가구수 and 1 other fieldsHigh correlation
지상층수 is highly overall correlated with 연면적(제곱미터) and 1 other fieldsHigh correlation
구조 is highly overall correlated with 지상층수High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2024-03-23 06:05:17.859199
Analysis finished2024-03-23 06:05:25.227446
Duration7.37 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct240
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean120.5
Minimum1
Maximum240
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-03-23T06:05:25.613000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile12.95
Q160.75
median120.5
Q3180.25
95-th percentile228.05
Maximum240
Range239
Interquartile range (IQR)119.5

Descriptive statistics

Standard deviation69.42622
Coefficient of variation (CV)0.5761512
Kurtosis-1.2
Mean120.5
Median Absolute Deviation (MAD)60
Skewness0
Sum28920
Variance4820
MonotonicityStrictly increasing
2024-03-23T06:05:26.211568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
122 1
 
0.4%
154 1
 
0.4%
155 1
 
0.4%
156 1
 
0.4%
157 1
 
0.4%
158 1
 
0.4%
159 1
 
0.4%
160 1
 
0.4%
161 1
 
0.4%
Other values (230) 230
95.8%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
240 1
0.4%
239 1
0.4%
238 1
0.4%
237 1
0.4%
236 1
0.4%
235 1
0.4%
234 1
0.4%
233 1
0.4%
232 1
0.4%
231 1
0.4%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
강원특별자치도 춘천시
240 

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row강원특별자치도 춘천시
2nd row강원특별자치도 춘천시
3rd row강원특별자치도 춘천시
4th row강원특별자치도 춘천시
5th row강원특별자치도 춘천시

Common Values

ValueCountFrequency (%)
강원특별자치도 춘천시 240
100.0%

Length

2024-03-23T06:05:26.771612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T06:05:27.035031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강원특별자치도 240
50.0%
춘천시 240
50.0%

주소
Text

Distinct229
Distinct (%)95.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-03-23T06:05:28.258757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length25
Mean length22.258333
Min length18

Characters and Unicode

Total characters5342
Distinct characters67
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

Unique221 ?
Unique (%)92.1%

Sample

1st row강원특별자치도 춘천시 교동 4-35
2nd row강원특별자치도 춘천시 교동 11-16
3rd row강원특별자치도 춘천시 교동 11-193
4th row강원특별자치도 춘천시 교동 15-42
5th row강원특별자치도 춘천시 교동 31-4
ValueCountFrequency (%)
강원특별자치도 240
23.4%
춘천시 240
23.4%
효자동 98
 
9.6%
남산면 52
 
5.1%
교동 22
 
2.1%
후평동 16
 
1.6%
백양리 15
 
1.5%
석사동 14
 
1.4%
방곡리 13
 
1.3%
강촌리 10
 
1.0%
Other values (254) 305
29.8%
2024-03-23T06:05:29.816498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
785
 
14.7%
자 338
 
6.3%
강 250
 
4.7%
천 249
 
4.7%
1 243
 
4.5%
원 242
 
4.5%
특 240
 
4.5%
별 240
 
4.5%
치 240
 
4.5%
도 240
 
4.5%
Other values (57) 2275
42.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3303
61.8%
Decimal Number 1038
 
19.4%
Space Separator 785
 
14.7%
Dash Punctuation 216
 
4.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
자 338
10.2%
강 250
 
7.6%
천 249
 
7.5%
원 242
 
7.3%
특 240
 
7.3%
별 240
 
7.3%
치 240
 
7.3%
도 240
 
7.3%
춘 240
 
7.3%
시 240
 
7.3%
Other values (45) 784
23.7%
Decimal Number
ValueCountFrequency (%)
1 243
23.4%
4 116
11.2%
2 111
10.7%
7 111
10.7%
3 107
10.3%
6 88
 
8.5%
9 68
 
6.6%
8 66
 
6.4%
5 64
 
6.2%
0 64
 
6.2%
Space Separator
ValueCountFrequency (%)
785
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 216
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3303
61.8%
Common 2039
38.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
자 338
10.2%
강 250
 
7.6%
천 249
 
7.5%
원 242
 
7.3%
특 240
 
7.3%
별 240
 
7.3%
치 240
 
7.3%
도 240
 
7.3%
춘 240
 
7.3%
시 240
 
7.3%
Other values (45) 784
23.7%
Common
ValueCountFrequency (%)
785
38.5%
1 243
 
11.9%
- 216
 
10.6%
4 116
 
5.7%
2 111
 
5.4%
7 111
 
5.4%
3 107
 
5.2%
6 88
 
4.3%
9 68
 
3.3%
8 66
 
3.2%
Other values (2) 128
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3303
61.8%
ASCII 2039
38.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
785
38.5%
1 243
 
11.9%
- 216
 
10.6%
4 116
 
5.7%
2 111
 
5.4%
7 111
 
5.4%
3 107
 
5.2%
6 88
 
4.3%
9 68
 
3.3%
8 66
 
3.2%
Other values (2) 128
 
6.3%
Hangul
ValueCountFrequency (%)
자 338
10.2%
강 250
 
7.6%
천 249
 
7.5%
원 242
 
7.3%
특 240
 
7.3%
별 240
 
7.3%
치 240
 
7.3%
도 240
 
7.3%
춘 240
 
7.3%
시 240
 
7.3%
Other values (45) 784
23.7%

주_용도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
단독주택
240 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
단독주택 240
100.0%

Length

2024-03-23T06:05:30.364960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T06:05:30.754400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
단독주택 240
100.0%

세부_용도
Text

Distinct58
Distinct (%)24.2%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-03-23T06:05:31.242958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length4
Mean length5.65
Min length2

Characters and Unicode

Total characters1356
Distinct characters41
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)18.8%

Sample

1st row다가구주택(12)
2nd row주택(5가구)
3rd row다가구단독주택(13가구)
4th row다가구용 단독주택(15가구)
5th row단독주택(다가구)
ValueCountFrequency (%)
단독주택 126
50.0%
주택 23
 
9.1%
다가구주택 14
 
5.6%
단독주택(다가구주택 11
 
4.4%
단독주택(다가구 9
 
3.6%
다가구주택(5 5
 
2.0%
주택(다가구 3
 
1.2%
주택(17 3
 
1.2%
주택(7 2
 
0.8%
주 2
 
0.8%
Other values (49) 54
21.4%
2024-03-23T06:05:32.463699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 256
18.9%
택 256
18.9%
단 160
11.8%
독 160
11.8%
가 83
 
6.1%
구 83
 
6.1%
( 74
 
5.5%
) 74
 
5.5%
다 62
 
4.6%
1 30
 
2.2%
Other values (31) 118
8.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1104
81.4%
Decimal Number 82
 
6.0%
Open Punctuation 74
 
5.5%
Close Punctuation 74
 
5.5%
Space Separator 12
 
0.9%
Other Punctuation 10
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 256
23.2%
택 256
23.2%
단 160
14.5%
독 160
14.5%
가 83
 
7.5%
구 83
 
7.5%
다 62
 
5.6%
점 3
 
0.3%
식 3
 
0.3%
음 3
 
0.3%
Other values (17) 35
 
3.2%
Decimal Number
ValueCountFrequency (%)
1 30
36.6%
5 10
 
12.2%
7 9
 
11.0%
9 8
 
9.8%
2 6
 
7.3%
6 6
 
7.3%
8 4
 
4.9%
3 4
 
4.9%
4 3
 
3.7%
0 2
 
2.4%
Open Punctuation
ValueCountFrequency (%)
( 74
100.0%
Close Punctuation
ValueCountFrequency (%)
) 74
100.0%
Space Separator
ValueCountFrequency (%)
12
100.0%
Other Punctuation
ValueCountFrequency (%)
, 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1104
81.4%
Common 252
 
18.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 256
23.2%
택 256
23.2%
단 160
14.5%
독 160
14.5%
가 83
 
7.5%
구 83
 
7.5%
다 62
 
5.6%
점 3
 
0.3%
식 3
 
0.3%
음 3
 
0.3%
Other values (17) 35
 
3.2%
Common
ValueCountFrequency (%)
( 74
29.4%
) 74
29.4%
1 30
11.9%
12
 
4.8%
, 10
 
4.0%
5 10
 
4.0%
7 9
 
3.6%
9 8
 
3.2%
2 6
 
2.4%
6 6
 
2.4%
Other values (4) 13
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1104
81.4%
ASCII 252
 
18.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 256
23.2%
택 256
23.2%
단 160
14.5%
독 160
14.5%
가 83
 
7.5%
구 83
 
7.5%
다 62
 
5.6%
점 3
 
0.3%
식 3
 
0.3%
음 3
 
0.3%
Other values (17) 35
 
3.2%
ASCII
ValueCountFrequency (%)
( 74
29.4%
) 74
29.4%
1 30
11.9%
12
 
4.8%
, 10
 
4.0%
5 10
 
4.0%
7 9
 
3.6%
9 8
 
3.2%
2 6
 
2.4%
6 6
 
2.4%
Other values (4) 13
 
5.2%

다가구주택 가구수
Real number (ℝ)

HIGH CORRELATION 

Distinct19
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.4083333
Minimum1
Maximum19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-03-23T06:05:32.997498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.95
Q16
median9
Q312
95-th percentile18
Maximum19
Range18
Interquartile range (IQR)6

Descriptive statistics

Standard deviation4.5884991
Coefficient of variation (CV)0.48770583
Kurtosis-0.69446735
Mean9.4083333
Median Absolute Deviation (MAD)3
Skewness0.3564457
Sum2258
Variance21.054324
MonotonicityNot monotonic
2024-03-23T06:05:33.485395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
6 35
14.6%
8 24
 
10.0%
4 24
 
10.0%
12 20
 
8.3%
9 20
 
8.3%
10 16
 
6.7%
11 11
 
4.6%
13 10
 
4.2%
15 9
 
3.8%
14 9
 
3.8%
Other values (9) 62
25.8%
ValueCountFrequency (%)
1 5
 
2.1%
2 7
 
2.9%
3 2
 
0.8%
4 24
10.0%
5 9
 
3.8%
6 35
14.6%
7 8
 
3.3%
8 24
10.0%
9 20
8.3%
10 16
6.7%
ValueCountFrequency (%)
19 8
 
3.3%
18 8
 
3.3%
17 6
 
2.5%
16 9
3.8%
15 9
3.8%
14 9
3.8%
13 10
4.2%
12 20
8.3%
11 11
4.6%
10 16
6.7%

연면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct231
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean204.09717
Minimum16.5
Maximum464.16
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-03-23T06:05:34.044844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16.5
5-th percentile41.7375
Q1111.98
median196.36
Q3286.0725
95-th percentile391.1675
Maximum464.16
Range447.66
Interquartile range (IQR)174.0925

Descriptive statistics

Standard deviation106.68927
Coefficient of variation (CV)0.52273761
Kurtosis-0.57140878
Mean204.09717
Median Absolute Deviation (MAD)84.76
Skewness0.38104037
Sum48983.32
Variance11382.599
MonotonicityNot monotonic
2024-03-23T06:05:34.616486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
84.86 4
 
1.7%
22.68 3
 
1.2%
39.6 2
 
0.8%
16.5 2
 
0.8%
195.54 2
 
0.8%
111.6 2
 
0.8%
250.74 1
 
0.4%
295.95 1
 
0.4%
389.3 1
 
0.4%
434.28 1
 
0.4%
Other values (221) 221
92.1%
ValueCountFrequency (%)
16.5 2
0.8%
18.0 1
 
0.4%
20.4 1
 
0.4%
22.68 3
1.2%
27.0 1
 
0.4%
28.28 1
 
0.4%
39.3 1
 
0.4%
39.6 2
0.8%
41.85 1
 
0.4%
47.56 1
 
0.4%
ValueCountFrequency (%)
464.16 1
0.4%
463.24 1
0.4%
461.34 1
0.4%
459.53 1
0.4%
448.74 1
0.4%
447.93 1
0.4%
442.29 1
0.4%
434.28 1
0.4%
409.99 1
0.4%
399.22 1
0.4%

가구당면적(제곱미터)
Real number (ℝ)

Distinct229
Distinct (%)95.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.391728
Minimum3.4
Maximum25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-03-23T06:05:35.181964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.4
5-th percentile15.150812
Q119.8075
median22.118333
Q323.92025
95-th percentile24.888208
Maximum25
Range21.6
Interquartile range (IQR)4.11275

Descriptive statistics

Standard deviation3.3110018
Coefficient of variation (CV)0.15477954
Kurtosis4.1247368
Mean21.391728
Median Absolute Deviation (MAD)2.013125
Skewness-1.62523
Sum5134.0147
Variance10.962733
MonotonicityNot monotonic
2024-03-23T06:05:36.012189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21.215 4
 
1.7%
22.68 3
 
1.2%
16.5 3
 
1.2%
25.0 2
 
0.8%
22.32 2
 
0.8%
24.99333333 2
 
0.8%
19.8 2
 
0.8%
18.61833333 1
 
0.4%
24.84 1
 
0.4%
23.88181818 1
 
0.4%
Other values (219) 219
91.2%
ValueCountFrequency (%)
3.4 1
0.4%
9.0 1
0.4%
10.46275 1
0.4%
10.61875 1
0.4%
13.018 1
0.4%
13.5 1
0.4%
14.01166667 1
0.4%
14.01857143 1
0.4%
14.1405 1
0.4%
14.546 1
0.4%
ValueCountFrequency (%)
25.0 2
0.8%
24.99818182 1
0.4%
24.99333333 2
0.8%
24.983 1
0.4%
24.96416667 1
0.4%
24.95857143 1
0.4%
24.95625 1
0.4%
24.95 1
0.4%
24.93818182 1
0.4%
24.90166667 1
0.4%

지상층수
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
3
98 
2
98 
1
42 
4
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row2
3rd row3
4th row2
5th row2

Common Values

ValueCountFrequency (%)
3 98
40.8%
2 98
40.8%
1 42
17.5%
4 2
 
0.8%

Length

2024-03-23T06:05:36.609500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T06:05:36.981824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 98
40.8%
2 98
40.8%
1 42
17.5%
4 2
 
0.8%

지하층수
Categorical

Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
0
148 
1
65 
<NA>
27 

Length

Max length4
Median length1
Mean length1.3375
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
0 148
61.7%
1 65
27.1%
<NA> 27
 
11.2%

Length

2024-03-23T06:05:37.401570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T06:05:37.908005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 148
61.7%
1 65
27.1%
na 27
 
11.2%

구조
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
벽돌구조
92 
철근콘크리트구조
85 
경량철골구조
17 
일반목구조
15 
일반철골구조
12 
Other values (7)
19 

Length

Max length8
Median length6
Mean length5.8333333
Min length3

Unique

Unique4 ?
Unique (%)1.7%

Sample

1st row철근콘크리트구조
2nd row벽돌구조
3rd row철근콘크리트구조
4th row철근콘크리트구조
5th row일반철골구조

Common Values

ValueCountFrequency (%)
벽돌구조 92
38.3%
철근콘크리트구조 85
35.4%
경량철골구조 17
 
7.1%
일반목구조 15
 
6.2%
일반철골구조 12
 
5.0%
기타조적구조 11
 
4.6%
블록구조 2
 
0.8%
강파이프구조 2
 
0.8%
석구조 1
 
0.4%
통나무구조 1
 
0.4%
Other values (2) 2
 
0.8%

Length

2024-03-23T06:05:38.400973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
벽돌구조 92
38.3%
철근콘크리트구조 85
35.4%
경량철골구조 17
 
7.1%
일반목구조 15
 
6.2%
일반철골구조 12
 
5.0%
기타조적구조 11
 
4.6%
블록구조 2
 
0.8%
강파이프구조 2
 
0.8%
석구조 1
 
0.4%
통나무구조 1
 
0.4%
Other values (2) 2
 
0.8%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Minimum2024-03-08 00:00:00
Maximum2024-03-08 00:00:00
2024-03-23T06:05:38.842602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:05:39.142355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-23T06:05:22.578684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:05:19.079026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:05:20.244322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:05:21.370733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:05:22.870600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:05:19.351064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:05:20.558589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:05:21.711509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:05:23.186437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:05:19.669042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:05:20.863221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:05:21.975300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:05:23.521605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:05:19.902625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:05:21.126062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:05:22.273740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T06:05:39.459793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번세부_용도다가구주택 가구수연면적(제곱미터)가구당면적(제곱미터)지상층수지하층수구조
연번1.0000.6260.4910.3670.0000.5140.3380.506
세부_용도0.6261.0000.6690.5810.0000.0000.0000.000
다가구주택 가구수0.4910.6691.0000.9550.2890.7000.3320.576
연면적(제곱미터)0.3670.5810.9551.0000.2580.7220.3940.560
가구당면적(제곱미터)0.0000.0000.2890.2581.0000.2810.0000.361
지상층수0.5140.0000.7000.7220.2811.0000.4070.851
지하층수0.3380.0000.3320.3940.0000.4071.0000.338
구조0.5060.0000.5760.5600.3610.8510.3381.000
2024-03-23T06:05:39.786307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지상층수지하층수구조
지상층수1.0000.2720.541
지하층수0.2721.0000.254
구조0.5410.2541.000
2024-03-23T06:05:40.194705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번다가구주택 가구수연면적(제곱미터)가구당면적(제곱미터)지상층수지하층수구조
연번1.0000.2560.2660.0790.3280.2540.238
다가구주택 가구수0.2561.0000.9690.1450.5000.2420.287
연면적(제곱미터)0.2660.9691.0000.3510.5190.2960.273
가구당면적(제곱미터)0.0790.1450.3511.0000.1810.0000.160
지상층수0.3280.5000.5190.1811.0000.2720.541
지하층수0.2540.2420.2960.0000.2721.0000.254
구조0.2380.2870.2730.1600.5410.2541.000

Missing values

2024-03-23T06:05:23.929259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T06:05:24.839170image/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

연번시군구명주소주_용도세부_용도다가구주택 가구수연면적(제곱미터)가구당면적(제곱미터)지상층수지하층수구조데이터기준일
01강원특별자치도 춘천시강원특별자치도 춘천시 교동 4-35단독주택다가구주택(12)12223.4218.61833330철근콘크리트구조2024-03-08
12강원특별자치도 춘천시강원특별자치도 춘천시 교동 11-16단독주택주택(5가구)15328.1421.87621벽돌구조2024-03-08
23강원특별자치도 춘천시강원특별자치도 춘천시 교동 11-193단독주택다가구단독주택(13가구)13304.123.39230831철근콘크리트구조2024-03-08
34강원특별자치도 춘천시강원특별자치도 춘천시 교동 15-42단독주택다가구용 단독주택(15가구)15297.9519.86333321철근콘크리트구조2024-03-08
45강원특별자치도 춘천시강원특별자치도 춘천시 교동 31-4단독주택단독주택(다가구)10239.7623.97621일반철골구조2024-03-08
56강원특별자치도 춘천시강원특별자치도 춘천시 교동 50-1단독주택단독주택6104.2817.3820벽돌구조2024-03-08
67강원특별자치도 춘천시강원특별자치도 춘천시 교동 50-1단독주택단독주택684.0714.01166721벽돌구조2024-03-08
78강원특별자치도 춘천시강원특별자치도 춘천시 교동 93-119단독주택다가구주택(8)8198.6424.8320벽돌구조2024-03-08
89강원특별자치도 춘천시강원특별자치도 춘천시 교동 100-25단독주택단독주택6118.8619.8120벽돌구조2024-03-08
910강원특별자치도 춘천시강원특별자치도 춘천시 교동 100-26단독주택단독주택6103.5317.25521벽돌구조2024-03-08
연번시군구명주소주_용도세부_용도다가구주택 가구수연면적(제곱미터)가구당면적(제곱미터)지상층수지하층수구조데이터기준일
230231강원특별자치도 춘천시강원특별자치도 춘천시 후평동 723-15단독주택단독주택494.2723.567520벽돌구조2024-03-08
231232강원특별자치도 춘천시강원특별자치도 춘천시 후평동 723-27단독주택주택6140.1623.3621벽돌구조2024-03-08
232233강원특별자치도 춘천시강원특별자치도 춘천시 후평동 742-21단독주택주택(다가구)18394.521.91666730일반철골구조2024-03-08
233234강원특별자치도 춘천시강원특별자치도 춘천시 후평동 744-9단독주택주택6137.1422.85666721벽돌구조2024-03-08
234235강원특별자치도 춘천시강원특별자치도 춘천시 후평동 748-6단독주택단독주택19461.3424.28105331철근콘크리트구조2024-03-08
235236강원특별자치도 춘천시강원특별자치도 춘천시 후평동 802-9단독주택주택, 대중음식점, 일반음식점8194.2824.28521벽돌구조2024-03-08
236237강원특별자치도 춘천시강원특별자치도 춘천시 후평동 817-5단독주택주택, 창고7164.9623.56571421벽돌구조2024-03-08
237238강원특별자치도 춘천시강원특별자치도 춘천시 후평동 849-9단독주택단독주택9214.6923.85444421벽돌구조2024-03-08
238239강원특별자치도 춘천시강원특별자치도 춘천시 후평동 850-1단독주택단독주택16318.6219.9137530벽돌구조2024-03-08
239240강원특별자치도 춘천시강원특별자치도 춘천시 후평동 850-10단독주택주택(16)16329.620.630기타조적구조2024-03-08