Overview

Dataset statistics

Number of variables10
Number of observations180
Missing cells161
Missing cells (%)8.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.1 KiB
Average record size in memory85.7 B

Variable types

Numeric4
Text2
Categorical2
DateTime2

Dataset

Description인천광역시 서구 제1종 근린생활시설 현황입니다. 항목명에는 주소, 건물명, 세대수, 가구수, 호수, 연면적, 사용승인일이 포함되어있습니다.
Author공공데이터포털
URLhttps://www.data.go.kr/data/15099864/fileData.do

Alerts

주용도 has constant value ""Constant
데이터기준일 has constant value ""Constant
호수 is highly overall correlated with 연면적High correlation
연면적 is highly overall correlated with 호수High correlation
건물명 has 30 (16.7%) missing valuesMissing
세대수 has 102 (56.7%) missing valuesMissing
호수 has 29 (16.1%) missing valuesMissing
순번 has unique valuesUnique
세대수 has 62 (34.4%) zerosZeros

Reproduction

Analysis started2024-04-17 09:42:54.962236
Analysis finished2024-04-17 09:42:56.775748
Duration1.81 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct180
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean90.5
Minimum1
Maximum180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-04-17T18:42:56.836118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9.95
Q145.75
median90.5
Q3135.25
95-th percentile171.05
Maximum180
Range179
Interquartile range (IQR)89.5

Descriptive statistics

Standard deviation52.105662
Coefficient of variation (CV)0.57575317
Kurtosis-1.2
Mean90.5
Median Absolute Deviation (MAD)45
Skewness0
Sum16290
Variance2715
MonotonicityStrictly increasing
2024-04-17T18:42:56.946721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.6%
115 1
 
0.6%
117 1
 
0.6%
118 1
 
0.6%
119 1
 
0.6%
120 1
 
0.6%
121 1
 
0.6%
122 1
 
0.6%
123 1
 
0.6%
124 1
 
0.6%
Other values (170) 170
94.4%
ValueCountFrequency (%)
1 1
0.6%
2 1
0.6%
3 1
0.6%
4 1
0.6%
5 1
0.6%
6 1
0.6%
7 1
0.6%
8 1
0.6%
9 1
0.6%
10 1
0.6%
ValueCountFrequency (%)
180 1
0.6%
179 1
0.6%
178 1
0.6%
177 1
0.6%
176 1
0.6%
175 1
0.6%
174 1
0.6%
173 1
0.6%
172 1
0.6%
171 1
0.6%

소재지 주소
Text

Distinct169
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-04-17T18:42:57.200087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length22
Mean length21.911111
Min length12

Characters and Unicode

Total characters3944
Distinct characters70
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique164 ?
Unique (%)91.1%

Sample

1st row인천광역시 서구 가정동 산 0021-0021
2nd row인천광역시 서구 석남동 0456-0006
3rd row인천광역시 서구 가좌동 0140-0013
4th row인천광역시 서구 당하동 1115-0003
5th row인천광역시 서구 왕길동 0662-0006
ValueCountFrequency (%)
인천광역시 180
24.2%
서구 180
24.2%
당하동 25
 
3.4%
청라동 23
 
3.1%
가정동 23
 
3.1%
원당동 21
 
2.8%
가좌동 17
 
2.3%
검암동 14
 
1.9%
왕길동 12
 
1.6%
석남동 12
 
1.6%
Other values (186) 236
31.8%
2024-04-17T18:42:57.536587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 630
16.0%
569
14.4%
시 196
 
5.0%
1 191
 
4.8%
서 185
 
4.7%
인 182
 
4.6%
천 182
 
4.6%
구 181
 
4.6%
동 181
 
4.6%
광 180
 
4.6%
Other values (60) 1267
32.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1916
48.6%
Decimal Number 1280
32.5%
Space Separator 569
 
14.4%
Dash Punctuation 155
 
3.9%
Uppercase Letter 24
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 196
10.2%
서 185
9.7%
인 182
9.5%
천 182
9.5%
구 181
9.4%
동 181
9.4%
광 180
9.4%
역 180
9.4%
당 46
 
2.4%
가 40
 
2.1%
Other values (45) 363
18.9%
Decimal Number
ValueCountFrequency (%)
0 630
49.2%
1 191
 
14.9%
2 71
 
5.5%
6 68
 
5.3%
5 65
 
5.1%
7 59
 
4.6%
3 56
 
4.4%
9 53
 
4.1%
4 53
 
4.1%
8 34
 
2.7%
Uppercase Letter
ValueCountFrequency (%)
B 12
50.0%
L 6
25.0%
A 6
25.0%
Space Separator
ValueCountFrequency (%)
569
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 155
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2004
50.8%
Hangul 1916
48.6%
Latin 24
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 196
10.2%
서 185
9.7%
인 182
9.5%
천 182
9.5%
구 181
9.4%
동 181
9.4%
광 180
9.4%
역 180
9.4%
당 46
 
2.4%
가 40
 
2.1%
Other values (45) 363
18.9%
Common
ValueCountFrequency (%)
0 630
31.4%
569
28.4%
1 191
 
9.5%
- 155
 
7.7%
2 71
 
3.5%
6 68
 
3.4%
5 65
 
3.2%
7 59
 
2.9%
3 56
 
2.8%
9 53
 
2.6%
Other values (2) 87
 
4.3%
Latin
ValueCountFrequency (%)
B 12
50.0%
L 6
25.0%
A 6
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2028
51.4%
Hangul 1916
48.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 630
31.1%
569
28.1%
1 191
 
9.4%
- 155
 
7.6%
2 71
 
3.5%
6 68
 
3.4%
5 65
 
3.2%
7 59
 
2.9%
3 56
 
2.8%
9 53
 
2.6%
Other values (5) 111
 
5.5%
Hangul
ValueCountFrequency (%)
시 196
10.2%
서 185
9.7%
인 182
9.5%
천 182
9.5%
구 181
9.4%
동 181
9.4%
광 180
9.4%
역 180
9.4%
당 46
 
2.4%
가 40
 
2.1%
Other values (45) 363
18.9%

건물명
Text

MISSING 

Distinct134
Distinct (%)89.3%
Missing30
Missing (%)16.7%
Memory size1.5 KiB
2024-04-17T18:42:58.028188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length24
Mean length7.64
Min length3

Characters and Unicode

Total characters1146
Distinct characters211
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique124 ?
Unique (%)82.7%

Sample

1st row대우자동차사원아파트상가
2nd row석남프라자
3rd row한양프라자
4th row장수프라자
5th row파인빌
ValueCountFrequency (%)
더 7
 
3.2%
루원시티 6
 
2.7%
sk 5
 
2.3%
leaders 5
 
2.3%
view 5
 
2.3%
2차 5
 
2.3%
우미린 4
 
1.8%
시그니처 4
 
1.8%
검단신도시 3
 
1.4%
디에트르 3
 
1.4%
Other values (157) 175
78.8%
2024-04-17T18:42:58.381192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
72
 
6.3%
라 65
 
5.7%
자 60
 
5.2%
프 56
 
4.9%
아 34
 
3.0%
트 24
 
2.1%
이 22
 
1.9%
파 21
 
1.8%
단 20
 
1.7%
타 20
 
1.7%
Other values (201) 752
65.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 951
83.0%
Space Separator 72
 
6.3%
Uppercase Letter 47
 
4.1%
Decimal Number 32
 
2.8%
Lowercase Letter 31
 
2.7%
Modifier Symbol 5
 
0.4%
Open Punctuation 2
 
0.2%
Close Punctuation 2
 
0.2%
Dash Punctuation 2
 
0.2%
Letter Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
라 65
 
6.8%
자 60
 
6.3%
프 56
 
5.9%
아 34
 
3.6%
트 24
 
2.5%
이 22
 
2.3%
파 21
 
2.2%
단 20
 
2.1%
타 20
 
2.1%
원 19
 
2.0%
Other values (168) 610
64.1%
Uppercase Letter
ValueCountFrequency (%)
K 7
14.9%
I 6
12.8%
S 6
12.8%
V 5
10.6%
E 5
10.6%
W 5
10.6%
L 5
10.6%
A 2
 
4.3%
J 2
 
4.3%
B 1
 
2.1%
Other values (3) 3
6.4%
Decimal Number
ValueCountFrequency (%)
2 11
34.4%
1 8
25.0%
3 5
15.6%
9 3
 
9.4%
8 2
 
6.2%
0 1
 
3.1%
5 1
 
3.1%
4 1
 
3.1%
Lowercase Letter
ValueCountFrequency (%)
e 11
35.5%
d 5
16.1%
s 5
16.1%
r 5
16.1%
a 5
16.1%
Space Separator
ValueCountFrequency (%)
72
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Letter Number
ValueCountFrequency (%)
Ⅲ 1
100.0%
Other Punctuation
ValueCountFrequency (%)
' 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 951
83.0%
Common 116
 
10.1%
Latin 79
 
6.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
라 65
 
6.8%
자 60
 
6.3%
프 56
 
5.9%
아 34
 
3.6%
트 24
 
2.5%
이 22
 
2.3%
파 21
 
2.2%
단 20
 
2.1%
타 20
 
2.1%
원 19
 
2.0%
Other values (168) 610
64.1%
Latin
ValueCountFrequency (%)
e 11
13.9%
K 7
 
8.9%
I 6
 
7.6%
S 6
 
7.6%
d 5
 
6.3%
s 5
 
6.3%
r 5
 
6.3%
V 5
 
6.3%
E 5
 
6.3%
W 5
 
6.3%
Other values (9) 19
24.1%
Common
ValueCountFrequency (%)
72
62.1%
2 11
 
9.5%
1 8
 
6.9%
` 5
 
4.3%
3 5
 
4.3%
9 3
 
2.6%
8 2
 
1.7%
( 2
 
1.7%
) 2
 
1.7%
- 2
 
1.7%
Other values (4) 4
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 951
83.0%
ASCII 194
 
16.9%
Number Forms 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
72
37.1%
e 11
 
5.7%
2 11
 
5.7%
1 8
 
4.1%
K 7
 
3.6%
I 6
 
3.1%
S 6
 
3.1%
d 5
 
2.6%
s 5
 
2.6%
r 5
 
2.6%
Other values (22) 58
29.9%
Hangul
ValueCountFrequency (%)
라 65
 
6.8%
자 60
 
6.3%
프 56
 
5.9%
아 34
 
3.6%
트 24
 
2.5%
이 22
 
2.3%
파 21
 
2.2%
단 20
 
2.1%
타 20
 
2.1%
원 19
 
2.0%
Other values (168) 610
64.1%
Number Forms
ValueCountFrequency (%)
Ⅲ 1
100.0%

주용도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
제1종근린생활시설
180 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row제1종근린생활시설
2nd row제1종근린생활시설
3rd row제1종근린생활시설
4th row제1종근린생활시설
5th row제1종근린생활시설

Common Values

ValueCountFrequency (%)
제1종근린생활시설 180
100.0%

Length

2024-04-17T18:42:58.497301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:42:58.581532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제1종근린생활시설 180
100.0%

세대수
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)15.4%
Missing102
Missing (%)56.7%
Infinite0
Infinite (%)0.0%
Mean2.8974359
Minimum0
Maximum33
Zeros62
Zeros (%)34.4%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-04-17T18:42:58.655571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile16.75
Maximum33
Range33
Interquartile range (IQR)0

Descriptive statistics

Standard deviation7.2355359
Coefficient of variation (CV)2.4972204
Kurtosis6.6820427
Mean2.8974359
Median Absolute Deviation (MAD)0
Skewness2.6703321
Sum226
Variance52.35298
MonotonicityNot monotonic
2024-04-17T18:42:58.746953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 62
34.4%
13 3
 
1.7%
1 3
 
1.7%
14 2
 
1.1%
15 1
 
0.6%
29 1
 
0.6%
16 1
 
0.6%
2 1
 
0.6%
28 1
 
0.6%
21 1
 
0.6%
Other values (2) 2
 
1.1%
(Missing) 102
56.7%
ValueCountFrequency (%)
0 62
34.4%
1 3
 
1.7%
2 1
 
0.6%
12 1
 
0.6%
13 3
 
1.7%
14 2
 
1.1%
15 1
 
0.6%
16 1
 
0.6%
21 1
 
0.6%
28 1
 
0.6%
ValueCountFrequency (%)
33 1
 
0.6%
29 1
 
0.6%
28 1
 
0.6%
21 1
 
0.6%
16 1
 
0.6%
15 1
 
0.6%
14 2
1.1%
13 3
1.7%
12 1
 
0.6%
2 1
 
0.6%

가구수
Categorical

Distinct4
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
116 
0
62 
1
 
1
8
 
1

Length

Max length4
Median length4
Mean length2.9333333
Min length1

Unique

Unique2 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 116
64.4%
0 62
34.4%
1 1
 
0.6%
8 1
 
0.6%

Length

2024-04-17T18:42:58.850399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:42:58.944487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 116
64.4%
0 62
34.4%
1 1
 
0.6%
8 1
 
0.6%

호수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct67
Distinct (%)44.4%
Missing29
Missing (%)16.1%
Infinite0
Infinite (%)0.0%
Mean32.304636
Minimum1
Maximum151
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-04-17T18:42:59.048062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.5
Q110
median19
Q347.5
95-th percentile100
Maximum151
Range150
Interquartile range (IQR)37.5

Descriptive statistics

Standard deviation32.018327
Coefficient of variation (CV)0.99113721
Kurtosis2.4067526
Mean32.304636
Median Absolute Deviation (MAD)13
Skewness1.6219444
Sum4878
Variance1025.1732
MonotonicityNot monotonic
2024-04-17T18:42:59.186222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 8
 
4.4%
11 8
 
4.4%
10 7
 
3.9%
18 7
 
3.9%
16 6
 
3.3%
9 6
 
3.3%
5 5
 
2.8%
1 4
 
2.2%
6 4
 
2.2%
13 3
 
1.7%
Other values (57) 93
51.7%
(Missing) 29
 
16.1%
ValueCountFrequency (%)
1 4
2.2%
2 1
 
0.6%
3 3
 
1.7%
4 8
4.4%
5 5
2.8%
6 4
2.2%
7 2
 
1.1%
8 2
 
1.1%
9 6
3.3%
10 7
3.9%
ValueCountFrequency (%)
151 1
 
0.6%
145 1
 
0.6%
133 1
 
0.6%
123 1
 
0.6%
122 1
 
0.6%
116 1
 
0.6%
102 1
 
0.6%
100 2
1.1%
97 3
1.7%
93 1
 
0.6%

연면적
Real number (ℝ)

HIGH CORRELATION 

Distinct179
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4075.6849
Minimum46.08
Maximum19852.72
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-04-17T18:42:59.308851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46.08
5-th percentile210.5435
Q1721.64
median2348.665
Q36857.665
95-th percentile13930.639
Maximum19852.72
Range19806.64
Interquartile range (IQR)6136.025

Descriptive statistics

Standard deviation4358.6869
Coefficient of variation (CV)1.0694367
Kurtosis1.8261705
Mean4075.6849
Median Absolute Deviation (MAD)1961.605
Skewness1.45601
Sum733623.28
Variance18998151
MonotonicityNot monotonic
2024-04-17T18:42:59.437911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5186.41 2
 
1.1%
758.97 1
 
0.6%
14316.98 1
 
0.6%
18687.09 1
 
0.6%
2527.29 1
 
0.6%
1003.85 1
 
0.6%
9377.15 1
 
0.6%
577.47 1
 
0.6%
13346.79 1
 
0.6%
728.42 1
 
0.6%
Other values (169) 169
93.9%
ValueCountFrequency (%)
46.08 1
0.6%
94.23 1
0.6%
108.84 1
0.6%
124.95 1
0.6%
144.88 1
0.6%
196.4 1
0.6%
199.74 1
0.6%
203.2 1
0.6%
208.9 1
0.6%
210.63 1
0.6%
ValueCountFrequency (%)
19852.72 1
0.6%
18687.09 1
0.6%
18581.73 1
0.6%
16748.13 1
0.6%
16652.85 1
0.6%
16081.17 1
0.6%
14316.98 1
0.6%
14104.93 1
0.6%
13997.69 1
0.6%
13927.11 1
0.6%

사용승인일
Date

Distinct163
Distinct (%)90.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
Minimum1981-02-20 00:00:00
Maximum2023-02-10 00:00:00
2024-04-17T18:42:59.569433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:42:59.687563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
Minimum2023-04-13 00:00:00
Maximum2023-04-13 00:00:00
2024-04-17T18:42:59.780916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:42:59.856494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-04-17T18:42:56.132732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:42:55.263759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:42:55.544522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:42:55.826433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:42:56.234512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:42:55.333729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:42:55.615762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:42:55.904775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:42:56.331085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:42:55.399713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:42:55.681010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:42:55.977555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:42:56.416387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:42:55.471449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:42:55.751872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:42:56.054715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T18:42:59.915595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번세대수가구수호수연면적
순번1.0000.0000.0000.0740.193
세대수0.0001.0000.0000.0000.123
가구수0.0000.0001.0000.0000.000
호수0.0740.0000.0001.0000.916
연면적0.1930.1230.0000.9161.000
2024-04-17T18:42:59.999447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번세대수호수연면적가구수
순번1.0000.102-0.052-0.0770.000
세대수0.1021.000-0.1330.0910.000
호수-0.052-0.1331.0000.9290.000
연면적-0.0770.0910.9291.0000.000
가구수0.0000.0000.0000.0001.000

Missing values

2024-04-17T18:42:56.525568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T18:42:56.638607image/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.
2024-04-17T18:42:56.727351image/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

순번소재지 주소건물명주용도세대수가구수호수연면적사용승인일데이터기준일
01인천광역시 서구 가정동 산 0021-0021대우자동차사원아파트상가제1종근린생활시설0016758.971990-07-022023-04-13
12인천광역시 서구 석남동 0456-0006석남프라자제1종근린생활시설00183384.272004-04-172023-04-13
23인천광역시 서구 가좌동 0140-0013<NA>제1종근린생활시설00<NA>337.621981-02-202023-04-13
34인천광역시 서구 당하동 1115-0003한양프라자제1종근린생활시설00213492.362005-01-192023-04-13
45인천광역시 서구 왕길동 0662-0006장수프라자제1종근린생활시설00286875.862003-12-102023-04-13
56인천광역시 서구 심곡동 0239파인빌제1종근린생활시설<NA><NA>91350.72017-07-282023-04-13
67인천광역시 서구 가정동 0619-0004드림타워제1종근린생활시설<NA><NA>539264.342018-06-182023-04-13
78인천광역시 서구 검암동 0610-0001서해프라자제1종근린생활시설<NA>0345431.352003-12-162023-04-13
89인천광역시 서구 경서동 0722-0001태평샹베르아파트제1종근린생활시설005241.22005-02-032023-04-13
910인천광역시 서구 가좌동 0140삼영아파트제1종근린생활시설004287.31985-03-042023-04-13
순번소재지 주소건물명주용도세대수가구수호수연면적사용승인일데이터기준일
170171인천광역시 서구 오류동 1747-0007에덴프라자제1종근린생활시설<NA><NA><NA>848.52018-09-042023-04-13
171172인천광역시 서구 원당동 1030-0010A플러스 타워제1종근린생활시설<NA><NA>445906.462021-10-132023-04-13
172173인천광역시 서구 경서동 0722-0001태평샹베르아파트제1종근린생활시설00<NA>769.352005-02-032023-04-13
173174인천광역시 서구 가정동 0494-0001서해프라자제1종근린생활시설00132093.22004-10-252023-04-13
174175인천광역시 서구 원당동 0824-0008원당메디칼프라자제1종근린생활시설330<NA>5276.22004-12-172023-04-13
175176인천광역시 서구 왕길동 0649-0001검단풍림아이원아파트제1종근린생활시설006336.02004-10-012023-04-13
176177인천광역시 서구 왕길동 0661-0001검단e-편한세상제1종근린생활시설120<NA>837.032007-06-042023-04-13
177178인천광역시 서구 왕길동 0639-0004<NA>제1종근린생활시설<NA><NA><NA>2571.642009-10-192023-04-13
178179인천광역시 서구 청라동 0193-0001청라자이제1종근린생활시설<NA><NA>10579.042010-06-112023-04-13
179180인천광역시 서구 당하동 1091-0001더 캐슬제1종근린생활시설<NA><NA>12665.792016-02-122023-04-13