Overview

Dataset statistics

Number of variables7
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory683.6 KiB
Average record size in memory70.0 B

Variable types

Numeric4
Categorical3

Dataset

Description한국부동산원(구.한국감정원)에서 제공하는 부동산 거래 통계를 조회할 수 있는 서비스로 충남의 외국인거래 면적 정보를 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/bigdata/collect/view.chungnam?menuCd=DOM_000000201001001000&apiIdx=2567

Alerts

지역명 is highly overall correlated with 번호 and 2 other fieldsHigh correlation
지역구분 레벨 is highly overall correlated with 번호 and 2 other fieldsHigh correlation
번호 is highly overall correlated with 지역코드 and 2 other fieldsHigh correlation
지역코드 is highly overall correlated with 번호 and 2 other fieldsHigh correlation
번호 has unique valuesUnique
외국인거래_면적 has 5783 (57.8%) zerosZeros

Reproduction

Analysis started2024-01-14 06:16:56.845599
Analysis finished2024-01-14 06:17:15.373671
Duration18.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6011.7946
Minimum1
Maximum12012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-14T15:17:15.533042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile587.95
Q13006.75
median6033.5
Q39009.25
95-th percentile11409.05
Maximum12012
Range12011
Interquartile range (IQR)6002.5

Descriptive statistics

Standard deviation3466.8198
Coefficient of variation (CV)0.5766697
Kurtosis-1.1995488
Mean6011.7946
Median Absolute Deviation (MAD)3001
Skewness-0.0068082752
Sum60117946
Variance12018839
MonotonicityNot monotonic
2024-01-14T15:17:15.806303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9968 1
 
< 0.1%
7461 1
 
< 0.1%
11829 1
 
< 0.1%
2192 1
 
< 0.1%
6278 1
 
< 0.1%
3624 1
 
< 0.1%
11953 1
 
< 0.1%
3023 1
 
< 0.1%
5570 1
 
< 0.1%
10033 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
7 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
14 1
< 0.1%
15 1
< 0.1%
ValueCountFrequency (%)
12012 1
< 0.1%
12011 1
< 0.1%
12010 1
< 0.1%
12008 1
< 0.1%
12007 1
< 0.1%
12006 1
< 0.1%
12004 1
< 0.1%
12003 1
< 0.1%
12002 1
< 0.1%
12001 1
< 0.1%

지역코드
Real number (ℝ)

HIGH CORRELATION 

Distinct14
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44260.166
Minimum44000
Maximum44770
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-14T15:17:16.054468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum44000
5-th percentile44000
Q144133
median44200
Q344250
95-th percentile44760
Maximum44770
Range770
Interquartile range (IQR)117

Descriptive statistics

Standard deviation219.66219
Coefficient of variation (CV)0.0049629772
Kurtosis0.88757779
Mean44260.166
Median Absolute Deviation (MAD)67
Skewness1.4782123
Sum4.4260166 × 108
Variance48251.48
MonotonicityNot monotonic
2024-01-14T15:17:16.324638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
44000 832
 
8.3%
44180 820
 
8.2%
44230 817
 
8.2%
44130 812
 
8.1%
44210 811
 
8.1%
44200 805
 
8.1%
44250 796
 
8.0%
44150 783
 
7.8%
44710 731
 
7.3%
44131 694
 
6.9%
Other values (4) 2099
21.0%
ValueCountFrequency (%)
44000 832
8.3%
44130 812
8.1%
44131 694
6.9%
44133 692
6.9%
44150 783
7.8%
44180 820
8.2%
44200 805
8.1%
44210 811
8.1%
44230 817
8.2%
44250 796
8.0%
ValueCountFrequency (%)
44770 272
 
2.7%
44760 602
6.0%
44710 731
7.3%
44270 533
5.3%
44250 796
8.0%
44230 817
8.2%
44210 811
8.1%
44200 805
8.1%
44180 820
8.2%
44150 783
7.8%

지역명
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
충남
832 
보령시
820 
논산시
817 
천안시
812 
서산시
811 
Other values (9)
5908 

Length

Max length3
Median length3
Mean length2.9168
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row당진시
2nd row금산군
3rd row공주시
4th row서천군
5th row공주시

Common Values

ValueCountFrequency (%)
충남 832
 
8.3%
보령시 820
 
8.2%
논산시 817
 
8.2%
천안시 812
 
8.1%
서산시 811
 
8.1%
아산시 805
 
8.1%
계룡시 796
 
8.0%
공주시 783
 
7.8%
금산군 731
 
7.3%
동남구 694
 
6.9%
Other values (4) 2099
21.0%

Length

2024-01-14T15:17:16.598681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
충남 832
 
8.3%
보령시 820
 
8.2%
논산시 817
 
8.2%
천안시 812
 
8.1%
서산시 811
 
8.1%
아산시 805
 
8.1%
계룡시 796
 
8.0%
공주시 783
 
7.8%
금산군 731
 
7.3%
동남구 694
 
6.9%
Other values (4) 2099
21.0%

조사분기
Real number (ℝ)

Distinct198
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean201425.11
Minimum200601
Maximum202206
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-14T15:17:16.830969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200601
5-th percentile200704.95
Q1201011
median201409
Q3201808
95-th percentile202109
Maximum202206
Range1605
Interquartile range (IQR)797

Descriptive statistics

Standard deviation456.77679
Coefficient of variation (CV)0.0022677252
Kurtosis-1.1386289
Mean201425.11
Median Absolute Deviation (MAD)399
Skewness-0.046693445
Sum2.014251 × 109
Variance208645.04
MonotonicityNot monotonic
2024-01-14T15:17:17.139803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
201211 61
 
0.6%
201301 60
 
0.6%
201303 60
 
0.6%
201310 60
 
0.6%
201202 59
 
0.6%
202008 59
 
0.6%
201504 59
 
0.6%
202006 59
 
0.6%
201706 59
 
0.6%
201204 59
 
0.6%
Other values (188) 9405
94.0%
ValueCountFrequency (%)
200601 15
0.1%
200602 18
0.2%
200603 24
0.2%
200604 30
0.3%
200605 25
0.2%
200606 33
0.3%
200607 25
0.2%
200608 27
0.3%
200609 34
0.3%
200610 37
0.4%
ValueCountFrequency (%)
202206 55
0.5%
202205 51
0.5%
202204 54
0.5%
202203 51
0.5%
202202 52
0.5%
202201 50
0.5%
202112 55
0.5%
202111 53
0.5%
202110 50
0.5%
202109 53
0.5%

거래유형
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
2106 
2
2025 
3
2009 
4
1949 
5
1911 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row1
3rd row2
4th row3
5th row2

Common Values

ValueCountFrequency (%)
1 2106
21.1%
2 2025
20.2%
3 2009
20.1%
4 1949
19.5%
5 1911
19.1%

Length

2024-01-14T15:17:17.416159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-14T15:17:17.621441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 2106
21.1%
2 2025
20.2%
3 2009
20.1%
4 1949
19.5%
5 1911
19.1%

외국인거래_면적
Real number (ℝ)

ZEROS 

Distinct3243
Distinct (%)32.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6082.7011
Minimum0
Maximum913608
Zeros5783
Zeros (%)57.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-14T15:17:17.873460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3834
95-th percentile27995.995
Maximum913608
Range913608
Interquartile range (IQR)834

Descriptive statistics

Standard deviation31582.274
Coefficient of variation (CV)5.1921462
Kurtosis200.59219
Mean6082.7011
Median Absolute Deviation (MAD)0
Skewness11.98755
Sum60827011
Variance9.9744001 × 108
MonotonicityNot monotonic
2024-01-14T15:17:18.155994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 5783
57.8%
85.0 24
 
0.2%
60.0 20
 
0.2%
40.0 12
 
0.1%
145.0 11
 
0.1%
98.0 9
 
0.1%
50.0 9
 
0.1%
102.0 8
 
0.1%
170.0 8
 
0.1%
159.0 8
 
0.1%
Other values (3233) 4108
41.1%
ValueCountFrequency (%)
0.0 5783
57.8%
1.0 2
 
< 0.1%
3.0 1
 
< 0.1%
5.0 1
 
< 0.1%
7.0 1
 
< 0.1%
8.0 2
 
< 0.1%
9.612 1
 
< 0.1%
9.80859 1
 
< 0.1%
11.0 1
 
< 0.1%
13.0 1
 
< 0.1%
ValueCountFrequency (%)
913608.0 1
< 0.1%
637531.87575 1
< 0.1%
633646.0 1
< 0.1%
579920.5 1
< 0.1%
513287.0 2
< 0.1%
503241.0 1
< 0.1%
489857.937544 1
< 0.1%
487100.0 1
< 0.1%
486495.539744 1
< 0.1%
486025.0 1
< 0.1%

지역구분 레벨
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
7782 
2
1386 
0
832 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 7782
77.8%
2 1386
 
13.9%
0 832
 
8.3%

Length

2024-01-14T15:17:18.400158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-14T15:17:18.763224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 7782
77.8%
2 1386
 
13.9%
0 832
 
8.3%

Interactions

2024-01-14T15:17:14.159640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T15:17:10.745757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T15:17:11.962330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T15:17:13.276647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T15:17:14.337216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T15:17:11.094197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T15:17:12.441317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T15:17:13.496898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T15:17:14.540242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T15:17:11.409787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T15:17:12.744038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T15:17:13.729781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T15:17:14.741507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T15:17:11.715354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T15:17:13.085296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T15:17:13.964841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-14T15:17:18.922310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호지역코드지역명조사분기거래유형외국인거래_면적지역구분 레벨
번호1.0000.9710.9690.2930.1640.2080.922
지역코드0.9711.0001.0000.1250.0470.0370.815
지역명0.9691.0001.0000.2090.0940.2481.000
조사분기0.2930.1250.2091.0000.0000.0870.140
거래유형0.1640.0470.0940.0001.0000.1170.000
외국인거래_면적0.2080.0370.2480.0870.1171.0000.319
지역구분 레벨0.9220.8151.0000.1400.0000.3191.000
2024-01-14T15:17:19.156138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
거래유형지역명지역구분 레벨
거래유형1.0000.0490.000
지역명0.0491.0000.999
지역구분 레벨0.0000.9991.000
2024-01-14T15:17:19.346797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호지역코드조사분기외국인거래_면적지역명거래유형지역구분 레벨
번호1.0000.9970.074-0.2370.8650.0690.891
지역코드0.9971.0000.010-0.2371.0000.0310.827
조사분기0.0740.0101.0000.1330.0860.0000.085
외국인거래_면적-0.237-0.2370.1331.0000.1120.0720.213
지역명0.8651.0000.0860.1121.0000.0490.999
거래유형0.0690.0310.0000.0720.0491.0000.000
지역구분 레벨0.8910.8270.0850.2130.9990.0001.000

Missing values

2024-01-14T15:17:15.007033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-14T15:17:15.266356image/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

번호지역코드지역명조사분기거래유형외국인거래_면적지역구분 레벨
9967996844270당진시20200440.01
105371053844710금산군20151110.01
3705370644150공주시20060720.01
117371173844770서천군20081230.01
3852385344150공주시20060520.01
7513751444210서산시2021083773.451
1554155544130천안시20151224208.01
6280628144200아산시20180617154.96691
1901190244130천안시2021012198.01
103011030244710금산군20120940.01
번호지역코드지역명조사분기거래유형외국인거래_면적지역구분 레벨
4873487444180보령시2006011102.01
2703270444131동남구20200950.02
6238623944200아산시20180250.01
12212344000충남201111126265.00
2807280844131동남구20220526250.02
3046304744133서북구20101050.02
1385138644130천안시20130940.01
7660766144230논산시20120930.01
103181031944710금산군20120150.01
7766776744230논산시20121110.01