Overview

Dataset statistics

Number of variables14
Number of observations1008
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory121.2 KiB
Average record size in memory123.1 B

Variable types

Numeric8
Categorical6

Dataset

Description한국부동산원(구.한국감정원)에서 제공하는 전국주택가격동향조사 통계를 조회할 수 있는 서비스로 월간동향으로 구성되어있습니다. 해당 서비스에서는 충남에 대한 해당기간, 지역, 주택유형의 주택가격 5분위 배율 정보를 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/bigdata/collect/view.chungnam?menuCd=DOM_000000201001001000&apiIdx=2546

Alerts

지역구분 레벨 has constant value ""Constant
정렬순서 is highly overall correlated with 1분위수 and 7 other fieldsHigh correlation
지역명 is highly overall correlated with 1분위수 and 7 other fieldsHigh correlation
지역코드 is highly overall correlated with 1분위수 and 7 other fieldsHigh correlation
조사일자 is highly overall correlated with 5분위수High correlation
1분위수 is highly overall correlated with 2분위수 and 7 other fieldsHigh correlation
2분위수 is highly overall correlated with 1분위수 and 7 other fieldsHigh correlation
3분위수 is highly overall correlated with 1분위수 and 6 other fieldsHigh correlation
4분위수 is highly overall correlated with 1분위수 and 6 other fieldsHigh correlation
5분위수 is highly overall correlated with 조사일자 and 8 other fieldsHigh correlation
변동률 is highly overall correlated with 1분위수 and 5 other fieldsHigh correlation
주택유형구분 is highly overall correlated with 변동률High correlation
매매전세구분 is highly overall correlated with 5분위수High correlation
번호 has unique valuesUnique
1분위수 has unique valuesUnique
2분위수 has unique valuesUnique
4분위수 has unique valuesUnique
5분위수 has unique valuesUnique
변동률 has unique valuesUnique

Reproduction

Analysis started2024-01-09 22:26:05.331069
Analysis finished2024-01-09 22:26:11.342562
Duration6.01 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct1008
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean504.5
Minimum1
Maximum1008
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.0 KiB
2024-01-10T07:26:11.400329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile51.35
Q1252.75
median504.5
Q3756.25
95-th percentile957.65
Maximum1008
Range1007
Interquartile range (IQR)503.5

Descriptive statistics

Standard deviation291.12884
Coefficient of variation (CV)0.5770641
Kurtosis-1.2
Mean504.5
Median Absolute Deviation (MAD)252
Skewness0
Sum508536
Variance84756
MonotonicityStrictly increasing
2024-01-10T07:26:11.507050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
679 1
 
0.1%
666 1
 
0.1%
667 1
 
0.1%
668 1
 
0.1%
669 1
 
0.1%
670 1
 
0.1%
671 1
 
0.1%
672 1
 
0.1%
673 1
 
0.1%
Other values (998) 998
99.0%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1008 1
0.1%
1007 1
0.1%
1006 1
0.1%
1005 1
0.1%
1004 1
0.1%
1003 1
0.1%
1002 1
0.1%
1001 1
0.1%
1000 1
0.1%
999 1
0.1%

지역코드
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
A1000
504 
11000
504 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowA1000
2nd row11000
3rd rowA1000
4th row11000
5th rowA1000

Common Values

ValueCountFrequency (%)
A1000 504
50.0%
11000 504
50.0%

Length

2024-01-10T07:26:11.604284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:26:11.673558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
a1000 504
50.0%
11000 504
50.0%

지역명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
전국
504 
서울
504 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전국
2nd row서울
3rd row전국
4th row서울
5th row전국

Common Values

ValueCountFrequency (%)
전국 504
50.0%
서울 504
50.0%

Length

2024-01-10T07:26:11.745465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:26:11.815900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전국 504
50.0%
서울 504
50.0%

조사일자
Real number (ℝ)

HIGH CORRELATION 

Distinct126
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean201682.55
Minimum201201
Maximum202206
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.0 KiB
2024-01-10T07:26:11.899725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201201
5-th percentile201207
Q1201408
median201703.5
Q3201911
95-th percentile202112
Maximum202206
Range1005
Interquartile range (IQR)503

Descriptive statistics

Standard deviation303.71697
Coefficient of variation (CV)0.001505916
Kurtosis-1.1930803
Mean201682.55
Median Absolute Deviation (MAD)294
Skewness0.020591559
Sum2.0329601 × 108
Variance92243.998
MonotonicityNot monotonic
2024-01-10T07:26:12.032206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
201610 8
 
0.8%
202206 8
 
0.8%
202006 8
 
0.8%
201903 8
 
0.8%
201801 8
 
0.8%
201805 8
 
0.8%
201812 8
 
0.8%
201803 8
 
0.8%
202104 8
 
0.8%
202010 8
 
0.8%
Other values (116) 928
92.1%
ValueCountFrequency (%)
201201 8
0.8%
201202 8
0.8%
201203 8
0.8%
201204 8
0.8%
201205 8
0.8%
201206 8
0.8%
201207 8
0.8%
201208 8
0.8%
201209 8
0.8%
201210 8
0.8%
ValueCountFrequency (%)
202206 8
0.8%
202205 8
0.8%
202204 8
0.8%
202203 8
0.8%
202202 8
0.8%
202201 8
0.8%
202112 8
0.8%
202111 8
0.8%
202110 8
0.8%
202109 8
0.8%

주택유형구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
1
504 
0
504 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row0
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 504
50.0%
0 504
50.0%

Length

2024-01-10T07:26:12.127643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:26:12.198349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 504
50.0%
0 504
50.0%

매매전세구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
S
504 
D
504 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowS
2nd rowS
3rd rowD
4th rowD
5th rowD

Common Values

ValueCountFrequency (%)
S 504
50.0%
D 504
50.0%

Length

2024-01-10T07:26:12.271901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:26:12.349324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
s 504
50.0%
d 504
50.0%

1분위수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1008
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean120081.22
Minimum32287.313
Maximum446752.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.0 KiB
2024-01-10T07:26:12.435739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum32287.313
5-th percentile35290.688
Q158118.923
median92326.059
Q3169348.51
95-th percentile268075.81
Maximum446752.4
Range414465.09
Interquartile range (IQR)111229.59

Descriptive statistics

Standard deviation79805.159
Coefficient of variation (CV)0.66459319
Kurtosis2.0039187
Mean120081.22
Median Absolute Deviation (MAD)44781.916
Skewness1.3341927
Sum1.2104187 × 108
Variance6.3688634 × 109
MonotonicityNot monotonic
2024-01-10T07:26:12.538806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
77732.14629451395 1
 
0.1%
297166.4855072464 1
 
0.1%
157857.6427829699 1
 
0.1%
85199.77966635191 1
 
0.1%
64953.36690909091 1
 
0.1%
63475.74171029669 1
 
0.1%
160844.9851042701 1
 
0.1%
305492.7536231884 1
 
0.1%
306092.39130434784 1
 
0.1%
42482.95133991537 1
 
0.1%
Other values (998) 998
99.0%
ValueCountFrequency (%)
32287.31306 1
0.1%
32368.96207 1
0.1%
32405.12508 1
0.1%
32505.92498 1
0.1%
32599.13573 1
0.1%
32668.66459 1
0.1%
32718.8409 1
0.1%
32808.39313 1
0.1%
32877.15157 1
0.1%
32902.22696 1
0.1%
ValueCountFrequency (%)
446752.4038461539 1
0.1%
446614.7115384616 1
0.1%
446244.5192307693 1
0.1%
446042.4038461539 1
0.1%
445877.4038461539 1
0.1%
445720.6730769231 1
0.1%
445702.8846153846 1
0.1%
445285.3846153846 1
0.1%
443709.1346153846 1
0.1%
440791.3461538461 1
0.1%

2분위수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1008
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean208815.43
Minimum68247.712
Maximum742748.08
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.0 KiB
2024-01-10T07:26:12.637482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum68247.712
5-th percentile74026.395
Q1115265.7
median168775.6
Q3275919.13
95-th percentile502166.69
Maximum742748.08
Range674500.36
Interquartile range (IQR)160653.42

Descriptive statistics

Standard deviation124835.9
Coefficient of variation (CV)0.5978289
Kurtosis3.1371524
Mean208815.43
Median Absolute Deviation (MAD)65905.505
Skewness1.5809546
Sum2.1048595 × 108
Variance1.5584002 × 1010
MonotonicityNot monotonic
2024-01-10T07:26:12.745529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
149908.59525336753 1
 
0.1%
532717.3913043478 1
 
0.1%
275372.8526970954 1
 
0.1%
161568.14604973246 1
 
0.1%
131100.2 1
 
0.1%
127427.57417102969 1
 
0.1%
293570.0099304866 1
 
0.1%
546114.1304347826 1
 
0.1%
547688.4057971014 1
 
0.1%
91518.47672778562 1
 
0.1%
Other values (998) 998
99.0%
ValueCountFrequency (%)
68247.71194 1
0.1%
68428.11036 1
0.1%
68634.75434 1
0.1%
68803.01466 1
0.1%
68987.33808 1
0.1%
69066.28995 1
0.1%
69084.95716 1
0.1%
69128.39889 1
0.1%
69350.65027 1
0.1%
69450.23949 1
0.1%
ValueCountFrequency (%)
742748.0769230769 1
0.1%
742601.9230769231 1
0.1%
741993.2692307692 1
0.1%
741295.1923076923 1
0.1%
741105.7692307692 1
0.1%
740746.1538461539 1
0.1%
740321.1538461539 1
0.1%
739887.5 1
0.1%
737307.6923076923 1
0.1%
731475.0 1
0.1%

3분위수
Real number (ℝ)

HIGH CORRELATION 

Distinct1007
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean295302.67
Minimum106170.39
Maximum974935.64
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.0 KiB
2024-01-10T07:26:12.855948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum106170.39
5-th percentile122006.25
Q1179534.88
median242706.6
Q3383279.37
95-th percentile669472.75
Maximum974935.64
Range868765.25
Interquartile range (IQR)203744.49

Descriptive statistics

Standard deviation164204.65
Coefficient of variation (CV)0.55605543
Kurtosis3.1430519
Mean295302.67
Median Absolute Deviation (MAD)85805.827
Skewness1.6131933
Sum2.9766509 × 108
Variance2.6963168 × 1010
MonotonicityNot monotonic
2024-01-10T07:26:12.960542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
161785.0497273019 2
 
0.2%
215752.00513314083 1
 
0.1%
721743.21880651 1
 
0.1%
417563.1360332295 1
 
0.1%
236546.4274472773 1
 
0.1%
204619.10561716053 1
 
0.1%
186619.69168121 1
 
0.1%
502870.4843870683 1
 
0.1%
740068.7160940325 1
 
0.1%
742538.8788426763 1
 
0.1%
Other values (997) 997
98.9%
ValueCountFrequency (%)
106170.3892 1
0.1%
106454.6878 1
0.1%
106772.2062 1
0.1%
106904.6541 1
0.1%
106969.5234 1
0.1%
106984.1103 1
0.1%
107131.7869 1
0.1%
107177.498 1
0.1%
107203.5387 1
0.1%
107605.3818 1
0.1%
ValueCountFrequency (%)
974935.6388088376 1
0.1%
974825.1681075888 1
0.1%
973911.6234390008 1
0.1%
973060.5187319884 1
0.1%
972994.2363112392 1
0.1%
972517.7713736792 1
0.1%
972002.8818443804 1
0.1%
970510.0864553314 1
0.1%
967458.213256484 1
0.1%
959675.3121998078 1
0.1%

4분위수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1008
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean411426.4
Minimum150900.99
Maximum1325797.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.0 KiB
2024-01-10T07:26:13.064238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum150900.99
5-th percentile169139.34
Q1257614.91
median343357.37
Q3517379.1
95-th percentile872864.22
Maximum1325797.1
Range1174896.1
Interquartile range (IQR)259764.19

Descriptive statistics

Standard deviation223270.75
Coefficient of variation (CV)0.54267483
Kurtosis3.2998263
Mean411426.4
Median Absolute Deviation (MAD)118281.83
Skewness1.6628283
Sum4.1471781 × 108
Variance4.9849828 × 1010
MonotonicityNot monotonic
2024-01-10T07:26:13.182137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
299487.17126363056 1
 
0.1%
988293.4782608696 1
 
0.1%
613522.8215767635 1
 
0.1%
344868.42933585146 1
 
0.1%
317845.0 1
 
0.1%
268456.2245491565 1
 
0.1%
779125.1241310824 1
 
0.1%
1008766.304347826 1
 
0.1%
1011237.3188405796 1
 
0.1%
243774.5063469676 1
 
0.1%
Other values (998) 998
99.0%
ValueCountFrequency (%)
150900.9925 1
0.1%
151121.6208 1
0.1%
151202.1135 1
0.1%
151209.0983 1
0.1%
151357.5622 1
0.1%
151430.0657 1
0.1%
151502.071 1
0.1%
151524.1741 1
0.1%
151540.8954 1
0.1%
151795.2986 1
0.1%
ValueCountFrequency (%)
1325797.1153846155 1
0.1%
1325564.423076923 1
0.1%
1324936.5384615385 1
0.1%
1323714.423076923 1
0.1%
1323503.8461538462 1
0.1%
1323478.8461538462 1
0.1%
1322532.6923076925 1
0.1%
1322290.3846153845 1
0.1%
1314639.423076923 1
0.1%
1304620.1923076925 1
0.1%

5분위수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1008
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean779563.91
Minimum269675.1
Maximum2268530.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.0 KiB
2024-01-10T07:26:13.291567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum269675.1
5-th percentile303731.95
Q1501939.53
median662028.42
Q3965735.57
95-th percentile1629309.1
Maximum2268530.3
Range1998855.2
Interquartile range (IQR)463796.04

Descriptive statistics

Standard deviation412266.45
Coefficient of variation (CV)0.52884241
Kurtosis1.8420358
Mean779563.91
Median Absolute Deviation (MAD)216227.3
Skewness1.3657421
Sum7.8580042 × 108
Variance1.6996363 × 1011
MonotonicityNot monotonic
2024-01-10T07:26:13.405893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
566489.4162924952 1
 
0.1%
1775085.4081200354 1
 
0.1%
1293349.5850622407 1
 
0.1%
741069.2259282568 1
 
0.1%
772823.304853663 1
 
0.1%
513530.8318789994 1
 
0.1%
1611104.3955261705 1
 
0.1%
1809837.2513562387 1
 
0.1%
1816320.0723327303 1
 
0.1%
503457.51057827927 1
 
0.1%
Other values (998) 998
99.0%
ValueCountFrequency (%)
269675.0995 1
0.1%
270218.3241 1
0.1%
270512.2553 1
0.1%
271352.4447 1
0.1%
271777.3306 1
0.1%
272079.8674 1
0.1%
272697.6055 1
0.1%
272947.8243 1
0.1%
273431.2699 1
0.1%
273626.5593 1
0.1%
ValueCountFrequency (%)
2268530.259365994 1
0.1%
2267717.5792507203 1
0.1%
2266589.817483189 1
0.1%
2266219.980787704 1
0.1%
2265969.260326609 1
0.1%
2262197.8866474545 1
0.1%
2261615.7540826127 1
0.1%
2257950.04803074 1
0.1%
2239290.1056676274 1
0.1%
2214692.60326609 1
0.1%

변동률
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1008
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.5044993
Minimum3.6079798
Maximum15.99424
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.0 KiB
2024-01-10T07:26:13.518163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.6079798
5-th percentile3.7145427
Q15.1260621
median7.1127411
Q39.4116486
95-th percentile12.531499
Maximum15.99424
Range12.38626
Interquartile range (IQR)4.2855865

Descriptive statistics

Standard deviation2.714601
Coefficient of variation (CV)0.3617298
Kurtosis0.022671056
Mean7.5044993
Median Absolute Deviation (MAD)2.025012
Skewness0.65773854
Sum7564.5353
Variance7.3690587
MonotonicityNot monotonic
2024-01-10T07:26:13.629797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.287710983126114 1
 
0.1%
5.97337012984511 1
 
0.1%
8.193138844980718 1
 
0.1%
8.69801810321968 1
 
0.1%
11.898125403342227 1
 
0.1%
8.090190331650701 1
 
0.1%
10.016503744159312 1
 
0.1%
5.924321378793134 1
 
0.1%
5.933894875964958 1
 
0.1%
11.850812966123888 1
 
0.1%
Other values (998) 998
99.0%
ValueCountFrequency (%)
3.607979767076276 1
0.1%
3.609630480502106 1
0.1%
3.610815701412755 1
0.1%
3.613659568 1
0.1%
3.619076116760101 1
0.1%
3.630413243 1
0.1%
3.637773111 1
0.1%
3.6394422431113473 1
0.1%
3.65375553 1
0.1%
3.654798612737616 1
0.1%
ValueCountFrequency (%)
15.994239572496618 1
0.1%
15.990570325552152 1
0.1%
15.96889679492171 1
0.1%
15.944135416346462 1
0.1%
15.934991981373338 1
0.1%
15.901745438486788 1
0.1%
15.88651869848412 1
0.1%
15.857224260645143 1
0.1%
15.827353864996656 1
0.1%
15.80881778347434 1
0.1%

지역구분 레벨
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
0
1008 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1008
100.0%

Length

2024-01-10T07:26:13.728599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:26:14.024112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1008
100.0%

정렬순서
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
1
504 
8
504 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row8
3rd row1
4th row8
5th row1

Common Values

ValueCountFrequency (%)
1 504
50.0%
8 504
50.0%

Length

2024-01-10T07:26:14.092866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:26:14.163095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 504
50.0%
8 504
50.0%

Interactions

2024-01-10T07:26:10.530054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:05.943080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:06.522574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:07.124837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:07.701264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:08.291600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:08.854442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:09.554911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:10.597837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:06.007321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:06.591059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:07.210044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:07.771796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:08.358158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:08.923896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:09.653464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:10.670690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:06.082373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:06.658987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:07.290977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:07.841471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:08.426232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:08.994146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:09.753173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:10.740939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:06.149898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:06.723962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:07.349715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:07.905505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:08.491307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:09.074279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:09.846202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:10.815091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:06.223884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:06.794978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:07.422260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:07.978972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:08.565083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:09.174233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:09.947783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:10.889860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:06.292848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:06.864159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:07.488615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:08.050409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:08.637121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:09.262178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:10.292807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:10.960343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:06.370004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:06.933033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:07.557781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:08.127156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:08.704926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:09.353001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:10.368417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:11.041525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:06.449357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:07.029742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:07.634274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:08.213512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:08.784861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:09.460456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:26:10.452177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T07:26:14.219106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호지역코드지역명조사일자주택유형구분매매전세구분1분위수2분위수3분위수4분위수5분위수변동률정렬순서
번호1.0000.0000.0000.3270.0000.0000.1180.1060.1120.1470.2220.2040.000
지역코드0.0001.0001.0000.0000.0000.0000.9860.8170.7820.9080.7240.8941.000
지역명0.0001.0001.0000.0000.0000.0000.9860.8170.7820.9080.7240.8941.000
조사일자0.3270.0000.0001.0000.0000.0000.4170.4840.4500.6610.7920.6980.000
주택유형구분0.0000.0000.0000.0001.0000.0000.4800.3040.3290.3510.1710.7280.000
매매전세구분0.0000.0000.0000.0000.0001.0000.4640.3530.3820.6160.8150.3950.000
1분위수0.1180.9860.9860.4170.4800.4641.0000.9350.8900.8940.8120.6430.986
2분위수0.1060.8170.8170.4840.3040.3530.9351.0000.9790.9050.8210.6310.817
3분위수0.1120.7820.7820.4500.3290.3820.8900.9791.0000.9600.8620.6310.782
4분위수0.1470.9080.9080.6610.3510.6160.8940.9050.9601.0000.9680.7580.908
5분위수0.2220.7240.7240.7920.1710.8150.8120.8210.8620.9681.0000.7200.724
변동률0.2040.8940.8940.6980.7280.3950.6430.6310.6310.7580.7201.0000.894
정렬순서0.0001.0001.0000.0000.0000.0000.9860.8170.7820.9080.7240.8941.000
2024-01-10T07:26:14.331530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주택유형구분매매전세구분정렬순서지역명지역코드
주택유형구분1.0000.0000.0000.0000.000
매매전세구분0.0001.0000.0000.0000.000
정렬순서0.0000.0001.0000.9980.998
지역명0.0000.0000.9981.0000.998
지역코드0.0000.0000.9980.9981.000
2024-01-10T07:26:14.425006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호조사일자1분위수2분위수3분위수4분위수5분위수변동률지역코드지역명주택유형구분매매전세구분정렬순서
번호1.0000.025-0.012-0.0050.0030.0160.0200.0400.0000.0000.0000.0000.000
조사일자0.0251.0000.1810.2770.3840.4660.5080.3880.0000.0000.0000.0000.000
1분위수-0.0120.1811.0000.9900.9580.9070.814-0.6480.8910.8910.3600.3480.891
2분위수-0.0050.2770.9901.0000.9850.9490.867-0.5680.8400.8400.3030.3520.840
3분위수0.0030.3840.9580.9851.0000.9860.925-0.4390.8000.8000.3280.3820.800
4분위수0.0160.4660.9070.9490.9861.0000.970-0.3010.7450.7450.2690.4750.745
5분위수0.0200.5080.8140.8670.9250.9701.000-0.1170.5650.5650.1320.6460.565
변동률0.0400.388-0.648-0.568-0.439-0.301-0.1171.0000.7270.7270.5680.3020.727
지역코드0.0000.0000.8910.8400.8000.7450.5650.7271.0000.9980.0000.0000.998
지역명0.0000.0000.8910.8400.8000.7450.5650.7270.9981.0000.0000.0000.998
주택유형구분0.0000.0000.3600.3030.3280.2690.1320.5680.0000.0001.0000.0000.000
매매전세구분0.0000.0000.3480.3520.3820.4750.6460.3020.0000.0000.0001.0000.000
정렬순서0.0000.0000.8910.8400.8000.7450.5650.7270.9980.9980.0000.0001.000

Missing values

2024-01-10T07:26:11.152028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:26:11.289445image/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

번호지역코드지역명조사일자주택유형구분매매전세구분1분위수2분위수3분위수4분위수5분위수변동률지역구분 레벨정렬순서
01A1000전국2016101S77732.146295149908.595253215752.005133299487.171264566489.4162927.28771101
1211000서울2017040S151111.2922263787.543655375998.253783520832.3632131067055.8789297.06139108
23A1000전국2016070D35392.61678573681.472684122742.141726187798.495645366911.12430710.36688301
3411000서울2017071D183560.927152272969.094923336097.130243421205.298013682640.9691633.7188808
45A1000전국2017071D55561.693936110960.840282161690.407443226691.148172404166.1321367.27418701
56A1000전국2017070S57956.710326114884.646043181467.539863273587.872462582432.71968110.04944401
67A1000전국2015110S57848.258116114070.783848179138.974663267303.147268561913.8954879.71358401
78A1000전국2015111S77902.995392149475.485357213768.015795295760.776571555961.8295497.13659101
8911000서울2016081S245478.747204350821.029083436693.512304568239.3736021070696.4285714.36166708
91011000서울2016060D93067.882353168349.411765248968.27262339758.823529611360.7520566.56897708
번호지역코드지역명조사일자주택유형구분매매전세구분1분위수2분위수3분위수4분위수5분위수변동률지역구분 레벨정렬순서
998999A1000전국2021081D71381.392857156476.928571255893.428571378643.285714695383.2142869.74179901
9991000A1000전국2021081S96739.485714211207.0361278.214286593163.7142861228718.64285712.70131501
1000100111000서울2021050D115941.509434203168.818272308242.303873449487.586892826640.8730167.12980908
1001100211000서울2021101D247353.365385425891.346154555580.211335714858.6538461201230.547554.85633408
10021003A1000전국2021100S73290.446069171558.094305699.169374532428.9473681171956.03205515.9905701
1003100411000서울2021100D149408.975218292904.219692455087.407904632110.515741101653.949137.37341208
10041005A1000전국2021101S98571.4216329.0372201.357143608278.4285711253359.012.7152401
10051006A1000전국2021120D48159.377301120155.753736213930.382283343839.34373666579.59714113.84111701
10061007A1000전국2022050D48545.099632121549.812649214941.747888339652.739874661604.2668413.62865201
10071008A1000전국2021091S97629.7213467.0366681.428571601158.5714291241668.71428612.71814501