Overview

Dataset statistics

Number of variables9
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows4
Duplicate rows (%)< 0.1%
Total size in memory839.8 KiB
Average record size in memory86.0 B

Variable types

Numeric6
Categorical2
Text1

Dataset

Description단독/다가구 매매 실거래 자료 현황
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=Z20D4ZHHJ4NS2TBN0HK523156598&infSeq=2

Alerts

Dataset has 4 (< 0.1%) duplicate rowsDuplicates
거래금액(만원) is highly overall correlated with 연면적(㎡)High correlation
연면적(㎡) is highly overall correlated with 거래금액(만원)High correlation

Reproduction

Analysis started2024-04-19 05:48:04.058104
Analysis finished2024-04-19 05:48:09.853725
Duration5.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년도
Real number (ℝ)

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2017.2442
Minimum2015
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-19T14:48:09.904907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2015
5-th percentile2015
Q12016
median2017
Q32018
95-th percentile2020
Maximum2021
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.8067354
Coefficient of variation (CV)0.00089564535
Kurtosis-0.81785957
Mean2017.2442
Median Absolute Deviation (MAD)1
Skewness0.50744302
Sum20172442
Variance3.2642928
MonotonicityNot monotonic
2024-04-19T14:48:10.014083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2016 2088
20.9%
2017 2008
20.1%
2015 1989
19.9%
2018 1584
15.8%
2020 1288
12.9%
2019 556
 
5.6%
2021 487
 
4.9%
ValueCountFrequency (%)
2015 1989
19.9%
2016 2088
20.9%
2017 2008
20.1%
2018 1584
15.8%
2019 556
 
5.6%
2020 1288
12.9%
2021 487
 
4.9%
ValueCountFrequency (%)
2021 487
 
4.9%
2020 1288
12.9%
2019 556
 
5.6%
2018 1584
15.8%
2017 2008
20.1%
2016 2088
20.9%
2015 1989
19.9%

기준월
Real number (ℝ)

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.4145
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-19T14:48:10.126007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q39
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.3597051
Coefficient of variation (CV)0.52376727
Kurtosis-1.1876866
Mean6.4145
Median Absolute Deviation (MAD)3
Skewness0.057226002
Sum64145
Variance11.287619
MonotonicityNot monotonic
2024-04-19T14:48:10.247676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
3 1074
10.7%
10 919
9.2%
6 893
8.9%
7 866
8.7%
5 864
8.6%
4 849
8.5%
8 810
8.1%
2 778
7.8%
9 765
7.6%
11 753
7.5%
Other values (2) 1429
14.3%
ValueCountFrequency (%)
1 705
7.0%
2 778
7.8%
3 1074
10.7%
4 849
8.5%
5 864
8.6%
6 893
8.9%
7 866
8.7%
8 810
8.1%
9 765
7.6%
10 919
9.2%
ValueCountFrequency (%)
12 724
7.2%
11 753
7.5%
10 919
9.2%
9 765
7.6%
8 810
8.1%
7 866
8.7%
6 893
8.9%
5 864
8.6%
4 849
8.5%
3 1074
10.7%

기준일
Real number (ℝ)

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.3581
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-19T14:48:10.379539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median11
Q331
95-th percentile31
Maximum31
Range30
Interquartile range (IQR)30

Descriptive statistics

Standard deviation11.708492
Coefficient of variation (CV)0.81546246
Kurtosis-1.3828328
Mean14.3581
Median Absolute Deviation (MAD)10
Skewness0.37063677
Sum143581
Variance137.08877
MonotonicityNot monotonic
2024-04-19T14:48:10.515715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
11 2733
27.3%
1 2677
26.8%
31 2618
26.2%
5 96
 
1.0%
16 88
 
0.9%
15 88
 
0.9%
3 86
 
0.9%
2 86
 
0.9%
10 85
 
0.9%
8 82
 
0.8%
Other values (21) 1361
13.6%
ValueCountFrequency (%)
1 2677
26.8%
2 86
 
0.9%
3 86
 
0.9%
4 76
 
0.8%
5 96
 
1.0%
6 73
 
0.7%
7 75
 
0.8%
8 82
 
0.8%
9 72
 
0.7%
10 85
 
0.9%
ValueCountFrequency (%)
31 2618
26.2%
30 40
 
0.4%
29 56
 
0.6%
28 53
 
0.5%
27 60
 
0.6%
26 55
 
0.5%
25 66
 
0.7%
24 63
 
0.6%
23 75
 
0.8%
22 70
 
0.7%

시군명
Categorical

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
성남시
1443 
수원시
1061 
부천시
614 
평택시
603 
용인시
 
554
Other values (26)
5725 

Length

Max length4
Median length3
Mean length3.0759
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row가평군
2nd row부천시
3rd row성남시
4th row부천시
5th row고양시

Common Values

ValueCountFrequency (%)
성남시 1443
 
14.4%
수원시 1061
 
10.6%
부천시 614
 
6.1%
평택시 603
 
6.0%
용인시 554
 
5.5%
고양시 446
 
4.5%
화성시 437
 
4.4%
안산시 392
 
3.9%
파주시 356
 
3.6%
의정부시 350
 
3.5%
Other values (21) 3744
37.4%

Length

2024-04-19T14:48:10.673456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
성남시 1443
 
14.4%
수원시 1061
 
10.6%
부천시 614
 
6.1%
평택시 603
 
6.0%
용인시 554
 
5.5%
고양시 446
 
4.5%
화성시 437
 
4.4%
안산시 392
 
3.9%
파주시 356
 
3.6%
의정부시 350
 
3.5%
Other values (21) 3744
37.4%

법정동명
Text

Distinct1749
Distinct (%)17.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-19T14:48:10.967572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length4.3791
Min length2

Characters and Unicode

Total characters43791
Distinct characters295
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique533 ?
Unique (%)5.3%

Sample

1st row가평읍 개곡리
2nd row내동
3rd row상대원동
4th row 원미동
5th row원흥동
ValueCountFrequency (%)
신흥동 266
 
2.0%
태평동 242
 
1.9%
상대원동 230
 
1.8%
세류동 156
 
1.2%
수진동 149
 
1.1%
금광동 134
 
1.0%
팽성읍 133
 
1.0%
안양동 127
 
1.0%
의정부동 118
 
0.9%
소사본동 107
 
0.8%
Other values (1456) 11344
87.2%
2024-04-19T14:48:11.429521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 7389
 
16.9%
4534
 
10.4%
리 3052
 
7.0%
면 1848
 
4.2%
읍 1188
 
2.7%
정 744
 
1.7%
산 731
 
1.7%
신 729
 
1.7%
원 680
 
1.6%
대 586
 
1.3%
Other values (285) 22310
50.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39242
89.6%
Space Separator 4534
 
10.4%
Decimal Number 15
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 7389
 
18.8%
리 3052
 
7.8%
면 1848
 
4.7%
읍 1188
 
3.0%
정 744
 
1.9%
산 731
 
1.9%
신 729
 
1.9%
원 680
 
1.7%
대 586
 
1.5%
양 566
 
1.4%
Other values (281) 21729
55.4%
Decimal Number
ValueCountFrequency (%)
3 11
73.3%
2 3
 
20.0%
1 1
 
6.7%
Space Separator
ValueCountFrequency (%)
4534
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39242
89.6%
Common 4549
 
10.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 7389
 
18.8%
리 3052
 
7.8%
면 1848
 
4.7%
읍 1188
 
3.0%
정 744
 
1.9%
산 731
 
1.9%
신 729
 
1.9%
원 680
 
1.7%
대 586
 
1.5%
양 566
 
1.4%
Other values (281) 21729
55.4%
Common
ValueCountFrequency (%)
4534
99.7%
3 11
 
0.2%
2 3
 
0.1%
1 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39242
89.6%
ASCII 4549
 
10.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 7389
 
18.8%
리 3052
 
7.8%
면 1848
 
4.7%
읍 1188
 
3.0%
정 744
 
1.9%
산 731
 
1.9%
신 729
 
1.9%
원 680
 
1.7%
대 586
 
1.5%
양 566
 
1.4%
Other values (281) 21729
55.4%
ASCII
ValueCountFrequency (%)
4534
99.7%
3 11
 
0.2%
2 3
 
0.1%
1 1
 
< 0.1%

주택유형명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
단독
7336 
다가구
2664 

Length

Max length3
Median length2
Mean length2.2664
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
단독 7336
73.4%
다가구 2664
 
26.6%

Length

2024-04-19T14:48:11.566561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:48:11.667652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
단독 7336
73.4%
다가구 2664
 
26.6%

거래금액(만원)
Real number (ℝ)

HIGH CORRELATION 

Distinct2265
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51137.238
Minimum1000
Maximum557877
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-19T14:48:11.790238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1000
5-th percentile10000
Q124500
median39000
Q367000
95-th percentile130000
Maximum557877
Range556877
Interquartile range (IQR)42500

Descriptive statistics

Standard deviation40351.116
Coefficient of variation (CV)0.789075
Kurtosis9.9636833
Mean51137.238
Median Absolute Deviation (MAD)18500
Skewness2.2661028
Sum5.1137238 × 108
Variance1.6282126 × 109
MonotonicityNot monotonic
2024-04-19T14:48:11.942055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30000 153
 
1.5%
20000 143
 
1.4%
25000 115
 
1.1%
40000 114
 
1.1%
35000 103
 
1.0%
50000 98
 
1.0%
60000 97
 
1.0%
29000 80
 
0.8%
15000 79
 
0.8%
28000 76
 
0.8%
Other values (2255) 8942
89.4%
ValueCountFrequency (%)
1000 1
 
< 0.1%
1100 1
 
< 0.1%
1150 1
 
< 0.1%
1336 1
 
< 0.1%
1500 1
 
< 0.1%
1577 1
 
< 0.1%
1709 1
 
< 0.1%
2000 3
< 0.1%
2100 1
 
< 0.1%
2160 1
 
< 0.1%
ValueCountFrequency (%)
557877 1
< 0.1%
485000 1
< 0.1%
410000 1
< 0.1%
389300 1
< 0.1%
350000 1
< 0.1%
349000 1
< 0.1%
337661 1
< 0.1%
330000 1
< 0.1%
310000 1
< 0.1%
309000 1
< 0.1%

대지면적(㎥)
Real number (ℝ)

Distinct2776
Distinct (%)27.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean280.98065
Minimum7.2
Maximum8040
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-19T14:48:12.076632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.2
5-th percentile64.1
Q1128.9
median214.35
Q3346.2
95-th percentile692.05
Maximum8040
Range8032.8
Interquartile range (IQR)217.3

Descriptive statistics

Standard deviation253.73744
Coefficient of variation (CV)0.90304241
Kurtosis112.85666
Mean280.98065
Median Absolute Deviation (MAD)97.65
Skewness6.0399867
Sum2809806.5
Variance64382.69
MonotonicityNot monotonic
2024-04-19T14:48:12.248812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
330.0 70
 
0.7%
660.0 64
 
0.6%
132.0 55
 
0.5%
64.5 52
 
0.5%
65.1 52
 
0.5%
65.5 49
 
0.5%
66.8 48
 
0.5%
231.0 46
 
0.5%
63.5 45
 
0.4%
63.1 43
 
0.4%
Other values (2766) 9476
94.8%
ValueCountFrequency (%)
7.2 1
< 0.1%
11.74 1
< 0.1%
17.0 1
< 0.1%
19.0 1
< 0.1%
22.27 1
< 0.1%
23.0 1
< 0.1%
24.05 1
< 0.1%
26.0 1
< 0.1%
27.0 1
< 0.1%
27.1 1
< 0.1%
ValueCountFrequency (%)
8040.0 1
< 0.1%
4191.8 1
< 0.1%
4190.14 1
< 0.1%
3860.0 1
< 0.1%
3230.0 1
< 0.1%
3003.0 1
< 0.1%
3000.0 1
< 0.1%
2543.0 1
< 0.1%
2467.0 1
< 0.1%
2243.0 1
< 0.1%

연면적(㎡)
Real number (ℝ)

HIGH CORRELATION 

Distinct8125
Distinct (%)81.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean208.42149
Minimum3.3
Maximum3412.62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-19T14:48:12.411620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.3
5-th percentile49.7475
Q198.9975
median155.31
Q3273.3175
95-th percentile512.091
Maximum3412.62
Range3409.32
Interquartile range (IQR)174.32

Descriptive statistics

Standard deviation161.69341
Coefficient of variation (CV)0.77580012
Kurtosis22.798592
Mean208.42149
Median Absolute Deviation (MAD)70.005
Skewness2.6612326
Sum2084214.9
Variance26144.76
MonotonicityNot monotonic
2024-04-19T14:48:12.576875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99.0 12
 
0.1%
66.0 11
 
0.1%
198.0 10
 
0.1%
84.9 8
 
0.1%
84.0 8
 
0.1%
96.0 7
 
0.1%
198.36 7
 
0.1%
84.78 6
 
0.1%
199.66 6
 
0.1%
133.02 6
 
0.1%
Other values (8115) 9919
99.2%
ValueCountFrequency (%)
3.3 1
< 0.1%
15.06 1
< 0.1%
15.19 1
< 0.1%
15.79 1
< 0.1%
15.83 1
< 0.1%
16.5 1
< 0.1%
16.53 1
< 0.1%
16.69 1
< 0.1%
16.9 1
< 0.1%
16.96 1
< 0.1%
ValueCountFrequency (%)
3412.62 1
< 0.1%
2160.02 1
< 0.1%
1664.38 1
< 0.1%
1652.39 1
< 0.1%
1614.11 1
< 0.1%
1605.0 1
< 0.1%
1525.0 1
< 0.1%
1412.72 1
< 0.1%
1390.47 1
< 0.1%
1307.46 1
< 0.1%

Interactions

2024-04-19T14:48:08.946274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:48:05.450481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:48:06.083560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:48:06.737985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:48:07.673739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:48:08.311733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:48:09.041702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:48:05.570957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:48:06.188983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:48:06.835973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:48:07.766037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:48:08.428942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:48:09.143255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:48:05.662507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:48:06.313260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:48:07.247772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:48:07.859055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:48:08.529304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:48:09.259441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:48:05.760869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:48:06.420499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:48:07.345927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:48:07.957870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:48:08.625987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:48:09.371132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:48:05.855740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:48:06.511924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:48:07.466842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:48:08.051467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:48:08.729890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:48:09.478873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:48:05.983287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:48:06.610888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:48:07.577226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:48:08.163372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:48:08.837470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-19T14:48:12.706722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도기준월기준일시군명주택유형명거래금액(만원)대지면적(㎥)연면적(㎡)
기준년도1.0000.3820.5720.3000.2580.0660.0330.120
기준월0.3821.0000.1500.0900.0000.0000.0050.000
기준일0.5720.1501.0000.2310.0000.1060.0000.033
시군명0.3000.0900.2311.0000.3880.3800.2210.357
주택유형명0.2580.0000.0000.3881.0000.4420.0710.378
거래금액(만원)0.0660.0000.1060.3800.4421.0000.5430.769
대지면적(㎥)0.0330.0050.0000.2210.0710.5431.0000.725
연면적(㎡)0.1200.0000.0330.3570.3780.7690.7251.000
2024-04-19T14:48:12.829445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주택유형명시군명
주택유형명1.0000.330
시군명0.3301.000
2024-04-19T14:48:13.280583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도기준월기준일거래금액(만원)대지면적(㎥)연면적(㎡)시군명주택유형명
기준년도1.000-0.0750.0450.0040.083-0.1210.1280.201
기준월-0.0751.000-0.0040.0110.023-0.0040.0320.000
기준일0.045-0.0041.0000.0110.015-0.0020.0810.000
거래금액(만원)0.0040.0110.0111.0000.1810.7260.1430.340
대지면적(㎥)0.0830.0230.0150.1811.0000.1770.0940.076
연면적(㎡)-0.121-0.004-0.0020.7260.1771.0000.1570.405
시군명0.1280.0320.0810.1430.0940.1571.0000.330
주택유형명0.2010.0000.0000.3400.0760.4050.3301.000

Missing values

2024-04-19T14:48:09.633940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-19T14:48:09.784451image/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

기준년도기준월기준일시군명법정동명주택유형명거래금액(만원)대지면적(㎥)연면적(㎡)
78317201521가평군가평읍 개곡리단독7900495.0135.0
686482015811부천시내동단독54000138.7239.76
240932018511성남시상대원동단독2650064.5111.78
1366020201028부천시원미동단독36600121.0150.48
432652017231고양시원흥동단독31900214.097.96
348272017831평택시지산동단독31000102.080.0
606552016231평택시서탄면 황구지리단독215001624.0378.0
619442016121가평군가평읍 달전리단독15000294.047.89
821902015101성남시태평동단독3400064.5149.72
344372017831성남시태평동단독60000124.4258.36
기준년도기준월기준일시군명법정동명주택유형명거래금액(만원)대지면적(㎥)연면적(㎡)
1428920201015수원시서둔동단독18000150.053.36
6467220161011수원시고색동단독24300143.0129.13
45532020923포천시내촌면 신팔리단독7000350.093.48
70486201571고양시백석동단독68000232.0337.77
564632016511안산시선부동다가구70000222.3488.58
483072017111시흥시매화동단독25300166.067.5
733982015511성남시정자동다가구118000224.9446.88
6268220161131평택시포승읍 도곡리다가구64000231.3391.48
6479820161011용인시중동단독68400224.0265.22
107702020212수원시천천동다가구72500193.0359.44

Duplicate rows

Most frequently occurring

기준년도기준월기준일시군명법정동명주택유형명거래금액(만원)대지면적(㎥)연면적(㎡)# duplicates
0201761수원시파장동단독34000155.0221.132
12017931성남시성남동다가구99700210.0464.642
22019131평택시팽성읍 노와리단독64900400.0267.772
32021327동두천시동두천동단독29000690.0120.522