Overview

Dataset statistics

Number of variables8
Number of observations99
Missing cells78
Missing cells (%)9.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.9 KiB
Average record size in memory71.3 B

Variable types

Categorical2
Numeric6

Dataset

Description인천광역시 연면적별 주택현황, 주택유형별(단독주택/아파트/연립주택/다세대주택/비거주용건물 내 주택) 등의 항목 주택수 현황 정보입니다.
Author인천광역시
URLhttps://www.data.go.kr/data/15055215/fileData.do

Alerts

계 is highly overall correlated with 아파트 and 3 other fieldsHigh correlation
단독주택 is highly overall correlated with 비거주용 건물내 주택High correlation
아파트 is highly overall correlated with 계 and 2 other fieldsHigh correlation
연립주택 is highly overall correlated with 계 and 2 other fieldsHigh correlation
다세대주택 is highly overall correlated with 계 and 2 other fieldsHigh correlation
비거주용 건물내 주택 is highly overall correlated with 계 and 1 other fieldsHigh correlation
아파트 has 17 (17.2%) missing valuesMissing
연립주택 has 31 (31.3%) missing valuesMissing
다세대주택 has 26 (26.3%) missing valuesMissing
비거주용 건물내 주택 has 4 (4.0%) missing valuesMissing

Reproduction

Analysis started2023-12-23 08:04:45.148816
Analysis finished2023-12-23 08:04:59.893371
Duration14.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

행정구역별(시군구)
Categorical

Distinct11
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size924.0 B
인천광역시
9 
중구
9 
동구
9 
미추홀구
9 
연수구
9 
Other values (6)
54 

Length

Max length6
Median length3
Mean length3.0909091
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row 인천광역시
2nd row 인천광역시
3rd row 인천광역시
4th row 인천광역시
5th row 인천광역시

Common Values

ValueCountFrequency (%)
인천광역시 9
9.1%
중구 9
9.1%
동구 9
9.1%
미추홀구 9
9.1%
연수구 9
9.1%
남동구 9
9.1%
부평구 9
9.1%
계양구 9
9.1%
서구 9
9.1%
강화군 9
9.1%

Length

2023-12-23T08:05:00.088490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
인천광역시 9
9.1%
중구 9
9.1%
동구 9
9.1%
미추홀구 9
9.1%
연수구 9
9.1%
남동구 9
9.1%
부평구 9
9.1%
계양구 9
9.1%
서구 9
9.1%
강화군 9
9.1%

연면적
Categorical

Distinct9
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size924.0 B
20㎡ 이하
11 
20㎡ ~ 40㎡
11 
40㎡ ~ 60㎡
11 
60㎡ ~ 85㎡
11 
85㎡ ~ 100㎡
11 
Other values (4)
44 

Length

Max length11
Median length10
Mean length9.2222222
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20㎡ 이하
2nd row20㎡ ~ 40㎡
3rd row40㎡ ~ 60㎡
4th row60㎡ ~ 85㎡
5th row85㎡ ~ 100㎡

Common Values

ValueCountFrequency (%)
20㎡ 이하 11
11.1%
20㎡ ~ 40㎡ 11
11.1%
40㎡ ~ 60㎡ 11
11.1%
60㎡ ~ 85㎡ 11
11.1%
85㎡ ~ 100㎡ 11
11.1%
100㎡ ~ 130㎡ 11
11.1%
130㎡ ~ 165㎡ 11
11.1%
165㎡ ~ 230㎡ 11
11.1%
230㎡ 초과 11
11.1%

Length

2023-12-23T08:05:00.639495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-23T08:05:01.158597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
77
28.0%
20㎡ 22
 
8.0%
40㎡ 22
 
8.0%
60㎡ 22
 
8.0%
85㎡ 22
 
8.0%
100㎡ 22
 
8.0%
130㎡ 22
 
8.0%
165㎡ 22
 
8.0%
230㎡ 22
 
8.0%
이하 11
 
4.0%

계
Real number (ℝ)

HIGH CORRELATION 

Distinct98
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21976.505
Minimum84
Maximum380887
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-23T08:05:01.624911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum84
5-th percentile251.3
Q11293
median3699
Q318318.5
95-th percentile72357
Maximum380887
Range380803
Interquartile range (IQR)17025.5

Descriptive statistics

Standard deviation55923.869
Coefficient of variation (CV)2.5447117
Kurtosis29.730411
Mean21976.505
Median Absolute Deviation (MAD)3218
Skewness5.1791887
Sum2175674
Variance3.1274791 × 109
MonotonicityNot monotonic
2023-12-23T08:05:02.048633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1192 2
 
2.0%
12164 1
 
1.0%
209 1
 
1.0%
23862 1
 
1.0%
861 1
 
1.0%
1118 1
 
1.0%
853 1
 
1.0%
3987 1
 
1.0%
1712 1
 
1.0%
28853 1
 
1.0%
Other values (88) 88
88.9%
ValueCountFrequency (%)
84 1
1.0%
116 1
1.0%
140 1
1.0%
149 1
1.0%
209 1
1.0%
256 1
1.0%
320 1
1.0%
344 1
1.0%
373 1
1.0%
382 1
1.0%
ValueCountFrequency (%)
380887 1
1.0%
356669 1
1.0%
162749 1
1.0%
90428 1
1.0%
79872 1
1.0%
71522 1
1.0%
60255 1
1.0%
58994 1
1.0%
58840 1
1.0%
58683 1
1.0%

단독주택
Real number (ℝ)

HIGH CORRELATION 

Distinct97
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1885.2525
Minimum5
Maximum17672
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-23T08:05:02.429665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile62.5
Q1310
median868
Q31838
95-th percentile10278.2
Maximum17672
Range17667
Interquartile range (IQR)1528

Descriptive statistics

Standard deviation3207.1431
Coefficient of variation (CV)1.7011743
Kurtosis9.9787405
Mean1885.2525
Median Absolute Deviation (MAD)629
Skewness3.1082167
Sum186640
Variance10285767
MonotonicityNot monotonic
2023-12-23T08:05:02.874156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
110 2
 
2.0%
84 2
 
2.0%
788 1
 
1.0%
6 1
 
1.0%
5 1
 
1.0%
1034 1
 
1.0%
746 1
 
1.0%
493 1
 
1.0%
305 1
 
1.0%
255 1
 
1.0%
Other values (87) 87
87.9%
ValueCountFrequency (%)
5 1
1.0%
6 1
1.0%
9 1
1.0%
17 1
1.0%
49 1
1.0%
64 1
1.0%
71 1
1.0%
80 1
1.0%
84 2
2.0%
92 1
1.0%
ValueCountFrequency (%)
17672 1
1.0%
15305 1
1.0%
11986 1
1.0%
10965 1
1.0%
10658 1
1.0%
10236 1
1.0%
9898 1
1.0%
5812 1
1.0%
5112 1
1.0%
5082 1
1.0%

아파트
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct80
Distinct (%)97.6%
Missing17
Missing (%)17.2%
Infinite0
Infinite (%)0.0%
Mean17507.768
Minimum6
Maximum323144
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-23T08:05:03.291246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile34.85
Q1434.25
median2983
Q317165.25
95-th percentile57186.85
Maximum323144
Range323138
Interquartile range (IQR)16731

Descriptive statistics

Standard deviation44793.524
Coefficient of variation (CV)2.5584942
Kurtosis31.527811
Mean17507.768
Median Absolute Deviation (MAD)2906
Skewness5.2672291
Sum1435637
Variance2.0064597 × 109
MonotonicityNot monotonic
2023-12-23T08:05:03.648923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 2
 
2.0%
34 2
 
2.0%
146 1
 
1.0%
998 1
 
1.0%
25353 1
 
1.0%
32124 1
 
1.0%
8941 1
 
1.0%
404 1
 
1.0%
191 1
 
1.0%
4004 1
 
1.0%
Other values (70) 70
70.7%
(Missing) 17
 
17.2%
ValueCountFrequency (%)
6 2
2.0%
14 1
1.0%
34 2
2.0%
51 1
1.0%
59 1
1.0%
67 1
1.0%
75 1
1.0%
146 1
1.0%
162 1
1.0%
168 1
1.0%
ValueCountFrequency (%)
323144 1
1.0%
221515 1
1.0%
78940 1
1.0%
66521 1
1.0%
57271 1
1.0%
55588 1
1.0%
53789 1
1.0%
47632 1
1.0%
45561 1
1.0%
38348 1
1.0%

연립주택
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct60
Distinct (%)88.2%
Missing31
Missing (%)31.3%
Infinite0
Infinite (%)0.0%
Mean876.51471
Minimum5
Maximum14523
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-23T08:05:04.065617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile6.35
Q125.5
median118.5
Q3502.25
95-th percentile3628.6
Maximum14523
Range14518
Interquartile range (IQR)476.75

Descriptive statistics

Standard deviation2342.0709
Coefficient of variation (CV)2.6720269
Kurtosis22.629507
Mean876.51471
Median Absolute Deviation (MAD)107.5
Skewness4.5630127
Sum59603
Variance5485296
MonotonicityNot monotonic
2023-12-23T08:05:04.462047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 3
 
3.0%
14 2
 
2.0%
24 2
 
2.0%
11 2
 
2.0%
9 2
 
2.0%
83 2
 
2.0%
30 2
 
2.0%
178 1
 
1.0%
1852 1
 
1.0%
1098 1
 
1.0%
Other values (50) 50
50.5%
(Missing) 31
31.3%
ValueCountFrequency (%)
5 3
3.0%
6 1
 
1.0%
7 1
 
1.0%
9 2
2.0%
11 2
2.0%
13 1
 
1.0%
14 2
2.0%
19 1
 
1.0%
21 1
 
1.0%
22 1
 
1.0%
ValueCountFrequency (%)
14523 1
1.0%
11422 1
1.0%
5001 1
1.0%
4106 1
1.0%
2742 1
1.0%
2629 1
1.0%
2539 1
1.0%
1956 1
1.0%
1852 1
1.0%
1357 1
1.0%

다세대주택
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct66
Distinct (%)90.4%
Missing26
Missing (%)26.3%
Infinite0
Infinite (%)0.0%
Mean6525.4384
Minimum5
Maximum109174
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-23T08:05:04.977589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile5.6
Q138
median253
Q33049
95-th percentile23320.2
Maximum109174
Range109169
Interquartile range (IQR)3011

Descriptive statistics

Standard deviation17897.667
Coefficient of variation (CV)2.7427532
Kurtosis23.728035
Mean6525.4384
Median Absolute Deviation (MAD)247
Skewness4.6649869
Sum476357
Variance3.2032648 × 108
MonotonicityNot monotonic
2023-12-23T08:05:05.447332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 4
 
4.0%
28 2
 
2.0%
38 2
 
2.0%
8 2
 
2.0%
20 2
 
2.0%
2685 1
 
1.0%
15946 1
 
1.0%
13416 1
 
1.0%
199 1
 
1.0%
25 1
 
1.0%
Other values (56) 56
56.6%
(Missing) 26
26.3%
ValueCountFrequency (%)
5 4
4.0%
6 1
 
1.0%
8 2
2.0%
11 1
 
1.0%
13 1
 
1.0%
14 1
 
1.0%
16 1
 
1.0%
17 1
 
1.0%
18 1
 
1.0%
20 2
2.0%
ValueCountFrequency (%)
109174 1
1.0%
98304 1
1.0%
27072 1
1.0%
23751 1
1.0%
23033 1
1.0%
20107 1
1.0%
20106 1
1.0%
18715 1
1.0%
18671 1
1.0%
18118 1
1.0%

비거주용 건물내 주택
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct84
Distinct (%)88.4%
Missing4
Missing (%)4.0%
Infinite0
Infinite (%)0.0%
Mean183.05263
Minimum5
Maximum1681
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-23T08:05:06.130333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile11.1
Q136
median75
Q3170
95-th percentile879.1
Maximum1681
Range1676
Interquartile range (IQR)134

Descriptive statistics

Standard deviation310.82007
Coefficient of variation (CV)1.697982
Kurtosis11.255076
Mean183.05263
Median Absolute Deviation (MAD)51
Skewness3.290873
Sum17390
Variance96609.114
MonotonicityNot monotonic
2023-12-23T08:05:06.706984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
66 2
 
2.0%
46 2
 
2.0%
70 2
 
2.0%
18 2
 
2.0%
81 2
 
2.0%
73 2
 
2.0%
50 2
 
2.0%
29 2
 
2.0%
42 2
 
2.0%
75 2
 
2.0%
Other values (74) 75
75.8%
(Missing) 4
 
4.0%
ValueCountFrequency (%)
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
12 1
1.0%
13 1
1.0%
15 1
1.0%
16 1
1.0%
17 1
1.0%
ValueCountFrequency (%)
1681 1
1.0%
1577 1
1.0%
1259 1
1.0%
1141 1
1.0%
1066 1
1.0%
799 1
1.0%
533 1
1.0%
506 1
1.0%
495 1
1.0%
478 1
1.0%

Interactions

2023-12-23T08:04:57.153927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:04:45.790610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:04:48.242824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:04:50.928972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:04:53.170480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:04:55.439894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:04:57.411624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:04:46.075495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:04:48.713831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:04:51.311054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:04:53.673031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:04:55.838879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:04:57.666741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:04:46.581190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:04:49.219108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:04:51.636729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:04:54.060761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:04:56.204361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:04:57.919979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:04:46.950462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:04:49.539881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:04:51.968704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:04:54.508017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:04:56.487907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:04:58.178908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:04:47.360867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:04:50.102294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:04:52.452595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:04:54.906640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:04:56.729158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:04:58.434428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:04:47.717617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:04:50.510224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:04:52.815851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:04:55.152426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T08:04:56.947415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-23T08:05:07.098895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정구역별(시군구)연면적계단독주택아파트연립주택다세대주택비거주용 건물내 주택
행정구역별(시군구)1.0000.0000.3390.5890.0000.0000.2610.552
연면적0.0001.0000.4130.2730.2550.0000.4910.000
계0.3390.4131.0000.7920.9830.8030.6670.693
단독주택0.5890.2730.7921.0000.7530.6870.6780.950
아파트0.0000.2550.9830.7531.0000.9030.6010.792
연립주택0.0000.0000.8030.6870.9031.0000.7430.719
다세대주택0.2610.4910.6670.6780.6010.7431.0000.596
비거주용 건물내 주택0.5520.0000.6930.9500.7920.7190.5961.000
2023-12-23T08:05:07.556828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연면적행정구역별(시군구)
연면적1.0000.000
행정구역별(시군구)0.0001.000
2023-12-23T08:05:07.893203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
계단독주택아파트연립주택다세대주택비거주용 건물내 주택행정구역별(시군구)연면적
계1.0000.3610.9120.7600.6640.5410.1850.246
단독주택0.3611.0000.0180.2330.0330.7130.3200.133
아파트0.9120.0181.0000.6690.5600.3420.0000.142
연립주택0.7600.2330.6691.0000.8080.2120.0000.000
다세대주택0.6640.0330.5600.8081.0000.0200.1450.227
비거주용 건물내 주택0.5410.7130.3420.2120.0201.0000.2930.000
행정구역별(시군구)0.1850.3200.0000.0000.1450.2931.0000.000
연면적0.2460.1330.1420.0000.2270.0000.0001.000

Missing values

2023-12-23T08:04:58.883723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-23T08:04:59.378000image/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.
2023-12-23T08:04:59.742656image/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

행정구역별(시군구)연면적계단독주택아파트연립주택다세대주택비거주용 건물내 주택
0인천광역시20㎡ 이하1216478879823832872139
1인천광역시20㎡ ~ 40㎡162749581255588253998304506
2인천광역시40㎡ ~ 60㎡3566691065822151514523109174799
3인천광역시60㎡ ~ 85㎡3808871767232314411422270721577
4인천광역시85㎡ ~ 100㎡2905810236170761794261141
5인천광역시100㎡ ~ 130㎡7987210965665214522531681
6인천광역시130㎡ ~ 165㎡34508989823118162711259
7인천광역시165㎡ ~ 230㎡15586119862372145171066
8인천광역시230㎡ 초과1634415305504<NA><NA>533
9중구20㎡ 이하578182243448227
행정구역별(시군구)연면적계단독주택아파트연립주택다세대주택비거주용 건물내 주택
89강화군230㎡ 초과344315<NA><NA><NA>29
90옹진군20㎡ 이하8471<NA><NA>85
91옹진군20㎡ ~ 40㎡10134233424328528
92옹진군40㎡ ~ 60㎡17238883055944130
93옹진군60㎡ ~ 85㎡2328177114625410255
94옹진군85㎡ ~ 100㎡1080969755526
95옹진군100㎡ ~ 130㎡748726<NA><NA><NA>18
96옹진군130㎡ ~ 165㎡481446<NA>51317
97옹진군165㎡ ~ 230㎡654621<NA><NA><NA>33
98옹진군230㎡ 초과320308<NA><NA><NA>12