Overview

Dataset statistics

Number of variables13
Number of observations214
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory23.1 KiB
Average record size in memory110.6 B

Variable types

Text4
Categorical4
Numeric5

Dataset

Description반지하 건축물의 건물 노후화 및 침수지역 비교 분석을 통하여 저층주거 취약지(반지하)를 도출하고 분석 결과를 통해 주거복지정책 수립 활용저소득층 주거복지 향상을 위한 주거급여 정책의 우선순위 선정의 기초자료로 활용주거급여 미달 가구와 침수지역 데이터를 매칭하여 침수이력이 있고 주거급여 미달 가구인 취약지원 대상 가구를 도출
Author국토교통부
URLhttps://www.data.go.kr/data/15123156/fileData.do

Alerts

면적 is highly overall correlated with 타입High correlation
기준년월일 is highly overall correlated with 비용 and 2 other fieldsHigh correlation
비용 is highly overall correlated with 기준년월일 and 2 other fieldsHigh correlation
계산면적 is highly overall correlated with 등급High correlation
타입 is highly overall correlated with 면적High correlation
등급 is highly overall correlated with 기준년월일 and 3 other fieldsHigh correlation
시도명 is highly overall correlated with 기준년월일 and 2 other fieldsHigh correlation
시도명 is highly imbalanced (62.5%)Imbalance
아이디 has unique valuesUnique
공간아이디 has 4 (1.9%) zerosZeros
계산면적 has 20 (9.3%) zerosZeros

Reproduction

Analysis started2023-12-12 01:20:44.620805
Analysis finished2023-12-12 01:20:48.729209
Duration4.11 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아이디
Text

UNIQUE 

Distinct214
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-12-12T10:20:48.969782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters2354
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique214 ?
Unique (%)100.0%

Sample

1st rowB0180460165
2nd rowB0155370262
3rd rowB0173161574
4th rowB0169833491
5th rowB0156694151
ValueCountFrequency (%)
b0180460165 1
 
0.5%
b0155168432 1
 
0.5%
b0155257317 1
 
0.5%
b0185546915 1
 
0.5%
b0155114141 1
 
0.5%
b0167299195 1
 
0.5%
b0155522953 1
 
0.5%
b0166857804 1
 
0.5%
b0155791132 1
 
0.5%
b0155915455 1
 
0.5%
Other values (204) 204
95.3%
2023-12-12T10:20:49.840208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 446
18.9%
1 341
14.5%
0 312
13.3%
B 214
9.1%
6 193
8.2%
8 153
 
6.5%
3 148
 
6.3%
7 145
 
6.2%
2 136
 
5.8%
4 135
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2140
90.9%
Uppercase Letter 214
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 446
20.8%
1 341
15.9%
0 312
14.6%
6 193
9.0%
8 153
 
7.1%
3 148
 
6.9%
7 145
 
6.8%
2 136
 
6.4%
4 135
 
6.3%
9 131
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
B 214
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2140
90.9%
Latin 214
 
9.1%

Most frequent character per script

Common
ValueCountFrequency (%)
5 446
20.8%
1 341
15.9%
0 312
14.6%
6 193
9.0%
8 153
 
7.1%
3 148
 
6.9%
7 145
 
6.8%
2 136
 
6.4%
4 135
 
6.3%
9 131
 
6.1%
Latin
ValueCountFrequency (%)
B 214
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2354
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 446
18.9%
1 341
14.5%
0 312
13.3%
B 214
9.1%
6 193
8.2%
8 153
 
6.5%
3 148
 
6.3%
7 145
 
6.2%
2 136
 
5.8%
4 135
 
5.7%

도로명상세주소
Text

Distinct210
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-12-12T10:20:50.234492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length37
Mean length28.705607
Min length14

Characters and Unicode

Total characters6143
Distinct characters191
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique206 ?
Unique (%)96.3%

Sample

1st row경기도 광명시 충현로32번길 12, A동 지하층1호 (소하동, 기아하이츠빌라)
2nd row경기도 광명시 광오로16번길 14, B01호 (광명동, 삼미빌라)
3rd row경기도 광명시 영우로 40, 다동 B02호 (소하동,명지빌라)
4th row경기도 광명시 충현로28번길 16, B동 B02호 (소하동 ,양지빌라 )
5th row경기도 시흥시 은행로12번길 38-2 , D동 B01호 (은행동, 혁성쉐르빌)
ValueCountFrequency (%)
경기도 164
 
12.9%
광명시 124
 
9.8%
60
 
4.7%
광명동 45
 
3.5%
b01호 29
 
2.3%
서울특별시 27
 
2.1%
부천시 17
 
1.3%
b02호 16
 
1.3%
하안동 14
 
1.1%
101호 13
 
1.0%
Other values (440) 762
60.0%
2023-12-12T10:20:50.740614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1057
 
17.2%
1 352
 
5.7%
광 242
 
3.9%
시 223
 
3.6%
로 213
 
3.5%
명 203
 
3.3%
, 188
 
3.1%
길 185
 
3.0%
도 184
 
3.0%
동 179
 
2.9%
Other values (181) 3117
50.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3295
53.6%
Decimal Number 1179
 
19.2%
Space Separator 1057
 
17.2%
Other Punctuation 188
 
3.1%
Close Punctuation 126
 
2.1%
Open Punctuation 126
 
2.1%
Dash Punctuation 103
 
1.7%
Uppercase Letter 67
 
1.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 242
 
7.3%
시 223
 
6.8%
로 213
 
6.5%
명 203
 
6.2%
길 185
 
5.6%
도 184
 
5.6%
동 179
 
5.4%
경 177
 
5.4%
기 166
 
5.0%
번 149
 
4.5%
Other values (159) 1374
41.7%
Decimal Number
ValueCountFrequency (%)
1 352
29.9%
2 162
13.7%
0 143
12.1%
3 108
 
9.2%
8 87
 
7.4%
5 77
 
6.5%
6 71
 
6.0%
4 68
 
5.8%
9 58
 
4.9%
7 53
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
B 58
86.6%
A 2
 
3.0%
D 2
 
3.0%
L 2
 
3.0%
G 2
 
3.0%
C 1
 
1.5%
Space Separator
ValueCountFrequency (%)
1057
100.0%
Other Punctuation
ValueCountFrequency (%)
, 188
100.0%
Close Punctuation
ValueCountFrequency (%)
) 126
100.0%
Open Punctuation
ValueCountFrequency (%)
( 126
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 103
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3295
53.6%
Common 2779
45.2%
Latin 69
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 242
 
7.3%
시 223
 
6.8%
로 213
 
6.5%
명 203
 
6.2%
길 185
 
5.6%
도 184
 
5.6%
동 179
 
5.4%
경 177
 
5.4%
기 166
 
5.0%
번 149
 
4.5%
Other values (159) 1374
41.7%
Common
ValueCountFrequency (%)
1057
38.0%
1 352
 
12.7%
, 188
 
6.8%
2 162
 
5.8%
0 143
 
5.1%
) 126
 
4.5%
( 126
 
4.5%
3 108
 
3.9%
- 103
 
3.7%
8 87
 
3.1%
Other values (5) 327
 
11.8%
Latin
ValueCountFrequency (%)
B 58
84.1%
b 2
 
2.9%
A 2
 
2.9%
D 2
 
2.9%
L 2
 
2.9%
G 2
 
2.9%
C 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3295
53.6%
ASCII 2848
46.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1057
37.1%
1 352
 
12.4%
, 188
 
6.6%
2 162
 
5.7%
0 143
 
5.0%
) 126
 
4.4%
( 126
 
4.4%
3 108
 
3.8%
- 103
 
3.6%
8 87
 
3.1%
Other values (12) 396
 
13.9%
Hangul
ValueCountFrequency (%)
광 242
 
7.3%
시 223
 
6.8%
로 213
 
6.5%
명 203
 
6.2%
길 185
 
5.6%
도 184
 
5.6%
동 179
 
5.4%
경 177
 
5.4%
기 166
 
5.0%
번 149
 
4.5%
Other values (159) 1374
41.7%

타입
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
1민간
125 
2공공
61 
3무료
28 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1민간
2nd row2공공
3rd row1민간
4th row1민간
5th row2공공

Common Values

ValueCountFrequency (%)
1민간 125
58.4%
2공공 61
28.5%
3무료 28
 
13.1%

Length

2023-12-12T10:20:50.872680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:20:50.991284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1민간 125
58.4%
2공공 61
28.5%
3무료 28
 
13.1%

면적
Real number (ℝ)

HIGH CORRELATION 

Distinct129
Distinct (%)60.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.644439
Minimum6
Maximum66
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-12T10:20:51.127320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile10
Q120
median32.245
Q340.935
95-th percentile56.8615
Maximum66
Range60
Interquartile range (IQR)20.935

Descriptive statistics

Standard deviation14.386295
Coefficient of variation (CV)0.45462317
Kurtosis-0.81177635
Mean31.644439
Median Absolute Deviation (MAD)11.765
Skewness0.18340891
Sum6771.91
Variance206.96549
MonotonicityNot monotonic
2023-12-12T10:20:51.259567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.0 19
 
8.9%
20.0 12
 
5.6%
25.0 9
 
4.2%
33.0 8
 
3.7%
30.0 8
 
3.7%
35.0 6
 
2.8%
40.0 6
 
2.8%
15.0 6
 
2.8%
32.0 3
 
1.4%
17.0 3
 
1.4%
Other values (119) 134
62.6%
ValueCountFrequency (%)
6.0 1
 
0.5%
6.6 1
 
0.5%
9.0 1
 
0.5%
9.92 1
 
0.5%
10.0 19
8.9%
12.0 2
 
0.9%
13.0 2
 
0.9%
13.2 2
 
0.9%
15.0 6
 
2.8%
16.0 2
 
0.9%
ValueCountFrequency (%)
66.0 1
0.5%
65.49 1
0.5%
59.92 1
0.5%
59.82 1
0.5%
59.7 1
0.5%
59.51 1
0.5%
59.5 1
0.5%
59.36 1
0.5%
58.4 1
0.5%
57.22 1
0.5%

준공일
Text

Distinct176
Distinct (%)82.2%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-12-12T10:20:51.552359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.4392523
Min length2

Characters and Unicode

Total characters1592
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique157 ?
Unique (%)73.4%

Sample

1st row\N
2nd row20001011
3rd row19911028
4th row19910708
5th row20011219
ValueCountFrequency (%)
n 20
 
9.3%
19901220 3
 
1.4%
19900724 2
 
0.9%
20031128 2
 
0.9%
19921031 2
 
0.9%
19930629 2
 
0.9%
19880603 2
 
0.9%
19901228 2
 
0.9%
19930731 2
 
0.9%
19911113 2
 
0.9%
Other values (166) 175
81.8%
2023-12-12T10:20:51.997740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 420
26.4%
9 359
22.6%
0 276
17.3%
2 161
 
10.1%
8 106
 
6.7%
3 71
 
4.5%
7 48
 
3.0%
4 39
 
2.4%
6 37
 
2.3%
5 35
 
2.2%
Other values (2) 40
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1552
97.5%
Other Punctuation 20
 
1.3%
Uppercase Letter 20
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 420
27.1%
9 359
23.1%
0 276
17.8%
2 161
 
10.4%
8 106
 
6.8%
3 71
 
4.6%
7 48
 
3.1%
4 39
 
2.5%
6 37
 
2.4%
5 35
 
2.3%
Other Punctuation
ValueCountFrequency (%)
\ 20
100.0%
Uppercase Letter
ValueCountFrequency (%)
N 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1572
98.7%
Latin 20
 
1.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 420
26.7%
9 359
22.8%
0 276
17.6%
2 161
 
10.2%
8 106
 
6.7%
3 71
 
4.5%
7 48
 
3.1%
4 39
 
2.5%
6 37
 
2.4%
5 35
 
2.2%
Latin
ValueCountFrequency (%)
N 20
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1592
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 420
26.4%
9 359
22.6%
0 276
17.3%
2 161
 
10.1%
8 106
 
6.7%
3 71
 
4.5%
7 48
 
3.0%
4 39
 
2.4%
6 37
 
2.3%
5 35
 
2.2%
Other values (2) 40
 
2.5%

건물형태
Categorical

Distinct9
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
다가구주택
73 
다세대주택
70 
단독주택
45 
\N
20 
기타제1종근린생활시설
 
2
Other values (4)
 
4

Length

Max length11
Median length5
Mean length4.5280374
Min length2

Unique

Unique4 ?
Unique (%)1.9%

Sample

1st row\N
2nd row다세대주택
3rd row다세대주택
4th row다세대주택
5th row다세대주택

Common Values

ValueCountFrequency (%)
다가구주택 73
34.1%
다세대주택 70
32.7%
단독주택 45
21.0%
\N 20
 
9.3%
기타제1종근린생활시설 2
 
0.9%
사무소 1
 
0.5%
여관 1
 
0.5%
연립주택 1
 
0.5%
독서실 1
 
0.5%

Length

2023-12-12T10:20:52.248117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:20:52.439573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
다가구주택 73
34.1%
다세대주택 70
32.7%
단독주택 45
21.0%
n 20
 
9.3%
기타제1종근린생활시설 2
 
0.9%
사무소 1
 
0.5%
여관 1
 
0.5%
연립주택 1
 
0.5%
독서실 1
 
0.5%

기준년월일
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17570179
Minimum2012
Maximum20170723
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-12T10:20:52.629872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2012
5-th percentile2012
Q120100921
median20100921
Q320100921
95-th percentile20140825
Maximum20170723
Range20168711
Interquartile range (IQR)0

Descriptive statistics

Standard deviation6691227.7
Coefficient of variation (CV)0.38082865
Kurtosis3.1717796
Mean17570179
Median Absolute Deviation (MAD)0
Skewness-2.2676359
Sum3.7600183 × 109
Variance4.4772528 × 1013
MonotonicityNot monotonic
2023-12-12T10:20:52.787401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
20100921 131
61.2%
20110727 23
 
10.7%
2012 20
 
9.3%
20140825 10
 
4.7%
2014 4
 
1.9%
20120706 4
 
1.9%
20161005 3
 
1.4%
2013 3
 
1.4%
20070916 3
 
1.4%
20170723 2
 
0.9%
Other values (10) 11
 
5.1%
ValueCountFrequency (%)
2012 20
 
9.3%
2013 3
 
1.4%
2014 4
 
1.9%
20060713 1
 
0.5%
20060716 1
 
0.5%
20070916 3
 
1.4%
20080723 1
 
0.5%
20100921 131
61.2%
20110710 1
 
0.5%
20110727 23
 
10.7%
ValueCountFrequency (%)
20170723 2
 
0.9%
20170716 2
 
0.9%
20161005 3
 
1.4%
20140825 10
4.7%
20130806 1
 
0.5%
20120816 1
 
0.5%
20120815 1
 
0.5%
20120814 1
 
0.5%
20120813 1
 
0.5%
20120706 4
 
1.9%

비용
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8710.6449
Minimum2
Maximum80723
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-12T10:20:53.023270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q1921
median921
Q310727
95-th percentile60817.15
Maximum80723
Range80721
Interquartile range (IQR)9806

Descriptive statistics

Standard deviation17847.105
Coefficient of variation (CV)2.0488845
Kurtosis5.5103129
Mean8710.6449
Median Absolute Deviation (MAD)0
Skewness2.5310402
Sum1864078
Variance3.1851917 × 108
MonotonicityNot monotonic
2023-12-12T10:20:53.170565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
921 131
61.2%
10727 23
 
10.7%
2 20
 
9.3%
40825 10
 
4.7%
4 4
 
1.9%
20706 4
 
1.9%
61005 3
 
1.4%
3 3
 
1.4%
70916 3
 
1.4%
70723 2
 
0.9%
Other values (10) 11
 
5.1%
ValueCountFrequency (%)
2 20
 
9.3%
3 3
 
1.4%
4 4
 
1.9%
921 131
61.2%
10710 1
 
0.5%
10727 23
 
10.7%
20706 4
 
1.9%
20813 1
 
0.5%
20814 1
 
0.5%
20815 1
 
0.5%
ValueCountFrequency (%)
80723 1
 
0.5%
70916 3
 
1.4%
70723 2
 
0.9%
70716 2
 
0.9%
61005 3
 
1.4%
60716 1
 
0.5%
60713 1
 
0.5%
40825 10
4.7%
30806 1
 
0.5%
20816 1
 
0.5%

공간아이디
Real number (ℝ)

ZEROS 

Distinct77
Distinct (%)36.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2813.6822
Minimum0
Maximum5288
Zeros4
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-12T10:20:53.352746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile26
Q11662
median3960
Q33960
95-th percentile4597.35
Maximum5288
Range5288
Interquartile range (IQR)2298

Descriptive statistics

Standard deviation1656.3483
Coefficient of variation (CV)0.5886764
Kurtosis-1.2451114
Mean2813.6822
Median Absolute Deviation (MAD)637
Skewness-0.52989718
Sum602128
Variance2743489.8
MonotonicityNot monotonic
2023-12-12T10:20:53.543974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3960 76
35.5%
1662 29
 
13.6%
4546 15
 
7.0%
1122 4
 
1.9%
0 4
 
1.9%
4597 4
 
1.9%
4598 3
 
1.4%
112 3
 
1.4%
25 2
 
0.9%
26 2
 
0.9%
Other values (67) 72
33.6%
ValueCountFrequency (%)
0 4
1.9%
13 1
 
0.5%
20 1
 
0.5%
22 2
0.9%
25 2
0.9%
26 2
0.9%
27 1
 
0.5%
28 1
 
0.5%
31 1
 
0.5%
56 1
 
0.5%
ValueCountFrequency (%)
5288 1
 
0.5%
5209 1
 
0.5%
5138 1
 
0.5%
5049 1
 
0.5%
5047 1
 
0.5%
5045 2
 
0.9%
5044 1
 
0.5%
4598 3
 
1.4%
4597 4
 
1.9%
4546 15
7.0%

계산면적
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct67
Distinct (%)31.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean179081.53
Minimum0
Maximum544700.75
Zeros20
Zeros (%)9.3%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-12T10:20:53.737906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11749.2109
median178021.35
Q3374674.25
95-th percentile374674.25
Maximum544700.75
Range544700.75
Interquartile range (IQR)372925.03

Descriptive statistics

Standard deviation165078.25
Coefficient of variation (CV)0.921805
Kurtosis-1.6457643
Mean179081.53
Median Absolute Deviation (MAD)177886.12
Skewness0.22263606
Sum38323447
Variance2.7250828 × 1010
MonotonicityNot monotonic
2023-12-12T10:20:53.925896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
374674.245772 76
35.5%
178021.352011 29
 
13.6%
0.0 20
 
9.3%
53867.114065 15
 
7.0%
7423.90299066 4
 
1.9%
17083.2704999 4
 
1.9%
19788.3721384 3
 
1.4%
4068.53448785 2
 
0.9%
299011.183624 2
 
0.9%
126768.412635 2
 
0.9%
Other values (57) 57
26.6%
ValueCountFrequency (%)
0.0 20
9.3%
75.807 1
 
0.5%
85.672 1
 
0.5%
87.201 1
 
0.5%
93.199 1
 
0.5%
107.714470002 1
 
0.5%
115.628 1
 
0.5%
120.556 1
 
0.5%
123.367830503 1
 
0.5%
123.864300001 1
 
0.5%
ValueCountFrequency (%)
544700.75446 1
 
0.5%
488594.3911 1
 
0.5%
374674.245772 76
35.5%
318477.263001 1
 
0.5%
299011.183624 2
 
0.9%
209513.255337 1
 
0.5%
178021.352011 29
 
13.6%
168822.670544 1
 
0.5%
153805.052069 1
 
0.5%
145190.553082 1
 
0.5%

등급
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2
155 
3
46 
4
 
7
1
 
6

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row4

Common Values

ValueCountFrequency (%)
2 155
72.4%
3 46
 
21.5%
4 7
 
3.3%
1 6
 
2.8%

Length

2023-12-12T10:20:54.116187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:20:54.252529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 155
72.4%
3 46
 
21.5%
4 7
 
3.3%
1 6
 
2.8%

시도명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct11
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
경기도
164 
서울특별시
27 
부산광역시
 
10
제주특별자치도
 
3
경상남도
 
2
Other values (6)
 
8

Length

Max length7
Median length3
Mean length3.4672897
Min length3

Unique

Unique4 ?
Unique (%)1.9%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 164
76.6%
서울특별시 27
 
12.6%
부산광역시 10
 
4.7%
제주특별자치도 3
 
1.4%
경상남도 2
 
0.9%
충청남도 2
 
0.9%
전라북도 2
 
0.9%
울산광역시 1
 
0.5%
경상북도 1
 
0.5%
세종특별자치시 1
 
0.5%

Length

2023-12-12T10:20:54.425128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 164
76.6%
서울특별시 27
 
12.6%
부산광역시 10
 
4.7%
제주특별자치도 3
 
1.4%
경상남도 2
 
0.9%
충청남도 2
 
0.9%
전라북도 2
 
0.9%
울산광역시 1
 
0.5%
경상북도 1
 
0.5%
세종특별자치시 1
 
0.5%

공간정보
Text

Distinct207
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-12-12T10:20:54.701952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length41
Mean length40.775701
Min length38

Characters and Unicode

Total characters8726
Distinct characters19
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique200 ?
Unique (%)93.5%

Sample

1st rowPOINT (126.883336262257 37.4347711109718)
2nd rowPOINT (126.851118824841 37.4765239271692)
3rd rowPOINT (126.875102467311 37.4328074825149)
4th rowPOINT (126.882816919537 37.4345543549557)
5th rowPOINT (126.797423514909 37.4326278583299)
ValueCountFrequency (%)
point 214
33.3%
37.474547767767 2
 
0.3%
126.850371997268 2
 
0.3%
37.4818298814268 2
 
0.3%
37.4995534576008 2
 
0.3%
126.850994018303 2
 
0.3%
37.4605378357044 2
 
0.3%
126.872411541116 2
 
0.3%
126.857677244981 2
 
0.3%
126.848850430385 2
 
0.3%
Other values (405) 410
63.9%
2023-12-12T10:20:55.181035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 782
 
9.0%
2 737
 
8.4%
3 696
 
8.0%
8 696
 
8.0%
1 681
 
7.8%
6 622
 
7.1%
4 622
 
7.1%
5 593
 
6.8%
9 522
 
6.0%
428
 
4.9%
Other values (9) 2347
26.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6372
73.0%
Uppercase Letter 1070
 
12.3%
Space Separator 428
 
4.9%
Other Punctuation 428
 
4.9%
Open Punctuation 214
 
2.5%
Close Punctuation 214
 
2.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 782
12.3%
2 737
11.6%
3 696
10.9%
8 696
10.9%
1 681
10.7%
6 622
9.8%
4 622
9.8%
5 593
9.3%
9 522
8.2%
0 421
6.6%
Uppercase Letter
ValueCountFrequency (%)
P 214
20.0%
O 214
20.0%
T 214
20.0%
N 214
20.0%
I 214
20.0%
Space Separator
ValueCountFrequency (%)
428
100.0%
Other Punctuation
ValueCountFrequency (%)
. 428
100.0%
Open Punctuation
ValueCountFrequency (%)
( 214
100.0%
Close Punctuation
ValueCountFrequency (%)
) 214
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7656
87.7%
Latin 1070
 
12.3%

Most frequent character per script

Common
ValueCountFrequency (%)
7 782
10.2%
2 737
9.6%
3 696
9.1%
8 696
9.1%
1 681
8.9%
6 622
8.1%
4 622
8.1%
5 593
7.7%
9 522
6.8%
428
 
5.6%
Other values (4) 1277
16.7%
Latin
ValueCountFrequency (%)
P 214
20.0%
O 214
20.0%
T 214
20.0%
N 214
20.0%
I 214
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8726
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 782
 
9.0%
2 737
 
8.4%
3 696
 
8.0%
8 696
 
8.0%
1 681
 
7.8%
6 622
 
7.1%
4 622
 
7.1%
5 593
 
6.8%
9 522
 
6.0%
428
 
4.9%
Other values (9) 2347
26.9%

Interactions

2023-12-12T10:20:47.702362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:20:45.249955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:20:45.875904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:20:46.475697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:20:47.123979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:20:47.814591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:20:45.418704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:20:45.983975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:20:46.586091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:20:47.235584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:20:47.952478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:20:45.551583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:20:46.099672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:20:46.719604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:20:47.373787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:20:48.077475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:20:45.678787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:20:46.233407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:20:46.861693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:20:47.482414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:20:48.175968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:20:45.773847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:20:46.363633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:20:46.992818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:20:47.600091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T10:20:55.341576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
타입면적건물형태기준년월일비용공간아이디계산면적등급시도명
타입1.0000.7320.6610.0480.2610.3330.3600.1250.244
면적0.7321.0000.4150.0000.1850.2660.2590.2770.492
건물형태0.6610.4151.0000.0000.4800.3410.6940.4660.578
기준년월일0.0480.0000.0001.0000.0000.6730.2300.6801.000
비용0.2610.1850.4800.0001.0000.6450.8070.9420.857
공간아이디0.3330.2660.3410.6730.6451.0000.8000.6950.765
계산면적0.3600.2590.6940.2300.8070.8001.0000.8780.737
등급0.1250.2770.4660.6800.9420.6950.8781.0000.908
시도명0.2440.4920.5781.0000.8570.7650.7370.9081.000
2023-12-12T10:20:55.500727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건물형태등급타입시도명
건물형태1.0000.3120.3680.305
등급0.3121.0000.1170.798
타입0.3680.1171.0000.142
시도명0.3050.7980.1421.000
2023-12-12T10:20:55.643044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
면적기준년월일비용공간아이디계산면적타입건물형태등급시도명
면적1.0000.0720.1090.2100.1330.5760.1890.1620.231
기준년월일0.0721.0000.8420.2600.0640.1110.1370.7180.979
비용0.1090.8421.0000.2790.0560.1690.2590.6800.632
공간아이디0.2100.2600.2791.0000.4750.2080.1610.4890.458
계산면적0.1330.0640.0560.4751.0000.2420.4310.5590.462
타입0.5760.1110.1690.2080.2421.0000.3680.1170.142
건물형태0.1890.1370.2590.1610.4310.3681.0000.3120.305
등급0.1620.7180.6800.4890.5590.1170.3121.0000.798
시도명0.2310.9790.6320.4580.4620.1420.3050.7981.000

Missing values

2023-12-12T10:20:48.357297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:20:48.603477image/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

아이디도로명상세주소타입면적준공일건물형태기준년월일비용공간아이디계산면적등급시도명공간정보
0B0180460165경기도 광명시 충현로32번길 12, A동 지하층1호 (소하동, 기아하이츠빌라)1민간47.49\N\N20100921921454653867.1140652경기도POINT (126.883336262257 37.4347711109718)
1B0155370262경기도 광명시 광오로16번길 14, B01호 (광명동, 삼미빌라)2공공41.5520001011다세대주택201009219213960374674.2457722경기도POINT (126.851118824841 37.4765239271692)
2B0173161574경기도 광명시 영우로 40, 다동 B02호 (소하동,명지빌라)1민간29.819911028다세대주택20100921921454653867.1140652경기도POINT (126.875102467311 37.4328074825149)
3B0169833491경기도 광명시 충현로28번길 16, B동 B02호 (소하동 ,양지빌라 )1민간49.6819910708다세대주택20100921921454653867.1140652경기도POINT (126.882816919537 37.4345543549557)
4B0156694151경기도 시흥시 은행로12번길 38-2 , D동 B01호 (은행동, 혁성쉐르빌)2공공59.3620011219다세대주택201707237072304068.5344884경기도POINT (126.797423514909 37.4326278583299)
5B0155655956경기도 광명시 안재로1번안길 12, 104호 (하안동)1민간20.019911014다가구주택201009219211662178021.3520112경기도POINT (126.87151953898 37.4599692493025)
6B0155862634경기도 광명시 광명로831번길 27-91민간33.019880902단독주택201009219213960374674.2457722경기도POINT (126.848636943311 37.4739078513691)
7B0155533322경기도 광명시 광화로 9-17 , 지층호 (광명동)1민간25.319891208단독주택201009219213960374674.2457722경기도POINT (126.849702953757 37.472251293935)
8B0170008692경기도 광명시 광오로23번길 12-13 , b01호 (광명동)2공공36.0319891028다세대주택201009219213960374674.2457722경기도POINT (126.848850430385 37.474547767767)
9B0165374789서울특별시 성동구 용답중앙11다길 9-41민간25.019930927다가구주택201442075.8073서울특별시POINT (127.052927309206 37.5661385001457)
아이디도로명상세주소타입면적준공일건물형태기준년월일비용공간아이디계산면적등급시도명공간정보
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