Overview

Dataset statistics

Number of variables5
Number of observations2051
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory86.3 KiB
Average record size in memory43.1 B

Variable types

Categorical3
Numeric2

Dataset

Description전국 신규 아파트 분양가격 동향 현황
Author주택도시보증공사
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=8U2TFJRK5O1NO7KZTDB420919759&infSeq=1

Reproduction

Analysis started2023-12-10 21:27:01.565273
Analysis finished2023-12-10 21:27:02.202743
Duration0.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

집계년도
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
2016
984 
2017
824 
2015
243 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2017
2nd row2017
3rd row2017
4th row2017
5th row2017

Common Values

ValueCountFrequency (%)
2016 984
48.0%
2017 824
40.2%
2015 243
 
11.8%

Length

2023-12-11T06:27:02.255116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:27:02.345795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2016 984
48.0%
2017 824
40.2%
2015 243
 
11.8%

집계월
Real number (ℝ)

Distinct12
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.6367626
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.2 KiB
2023-12-11T06:27:02.459562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median7
Q310
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.4541165
Coefficient of variation (CV)0.52045203
Kurtosis-1.2405298
Mean6.6367626
Median Absolute Deviation (MAD)3
Skewness-0.076683842
Sum13612
Variance11.930921
MonotonicityNot monotonic
2023-12-11T06:27:02.554772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
10 245
11.9%
4 166
8.1%
6 165
8.0%
5 165
8.0%
1 165
8.0%
12 165
8.0%
11 165
8.0%
8 164
8.0%
7 164
8.0%
2 164
8.0%
Other values (2) 323
15.7%
ValueCountFrequency (%)
1 165
8.0%
2 164
8.0%
3 162
7.9%
4 166
8.1%
5 165
8.0%
6 165
8.0%
7 164
8.0%
8 164
8.0%
9 161
7.8%
10 245
11.9%
ValueCountFrequency (%)
12 165
8.0%
11 165
8.0%
10 245
11.9%
9 161
7.8%
8 164
8.0%
7 164
8.0%
6 165
8.0%
5 165
8.0%
4 166
8.1%
3 162
7.9%

시도명
Categorical

Distinct17
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
경남
 
125
부산
 
125
서울
 
125
세종
 
125
경기
 
125
Other values (12)
1426 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경남
2nd row경남
3rd row경남
4th row경남
5th row제주

Common Values

ValueCountFrequency (%)
경남 125
 
6.1%
부산 125
 
6.1%
서울 125
 
6.1%
세종 125
 
6.1%
경기 125
 
6.1%
인천 125
 
6.1%
경북 125
 
6.1%
충북 125
 
6.1%
충남 125
 
6.1%
전남 125
 
6.1%
Other values (7) 801
39.1%

Length

2023-12-11T06:27:02.649000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경남 125
 
6.1%
경북 125
 
6.1%
전남 125
 
6.1%
부산 125
 
6.1%
충북 125
 
6.1%
충남 125
 
6.1%
인천 125
 
6.1%
경기 125
 
6.1%
세종 125
 
6.1%
서울 125
 
6.1%
Other values (7) 801
39.1%

규모구분명
Categorical

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
전용면적 60㎡초과 85㎡이하
425 
전체
425 
전용면적 60㎡이하
414 
전용면적 102㎡초과
403 
전용면적 85㎡초과 102㎡이하
384 

Length

Max length17
Median length11
Mean length11.092638
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전용면적 60㎡이하
2nd row전용면적 60㎡초과 85㎡이하
3rd row전용면적 85㎡초과 102㎡이하
4th row전용면적 102㎡초과
5th row전체

Common Values

ValueCountFrequency (%)
전용면적 60㎡초과 85㎡이하 425
20.7%
전체 425
20.7%
전용면적 60㎡이하 414
20.2%
전용면적 102㎡초과 403
19.6%
전용면적 85㎡초과 102㎡이하 384
18.7%

Length

2023-12-11T06:27:02.744559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:27:02.858317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전용면적 1626
36.2%
60㎡초과 425
 
9.5%
85㎡이하 425
 
9.5%
전체 425
 
9.5%
60㎡이하 414
 
9.2%
102㎡초과 403
 
9.0%
85㎡초과 384
 
8.6%
102㎡이하 384
 
8.6%

분양가격(천원/㎡)
Real number (ℝ)

Distinct1013
Distinct (%)49.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2996.8557
Minimum1868
Maximum8096
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.2 KiB
2023-12-11T06:27:02.967160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1868
5-th percentile2017
Q12304
median2703
Q33238.5
95-th percentile6213
Maximum8096
Range6228
Interquartile range (IQR)934.5

Descriptive statistics

Standard deviation1079.5471
Coefficient of variation (CV)0.36022658
Kurtosis5.1021759
Mean2996.8557
Median Absolute Deviation (MAD)441
Skewness2.2291003
Sum6146551
Variance1165421.9
MonotonicityNot monotonic
2023-12-11T06:27:03.100610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2221 13
 
0.6%
2663 12
 
0.6%
4328 12
 
0.6%
2600 11
 
0.5%
2743 11
 
0.5%
2963 10
 
0.5%
3045 10
 
0.5%
2557 10
 
0.5%
2690 10
 
0.5%
2321 9
 
0.4%
Other values (1003) 1943
94.7%
ValueCountFrequency (%)
1868 1
 
< 0.1%
1900 1
 
< 0.1%
1906 3
0.1%
1908 2
 
0.1%
1909 6
0.3%
1910 1
 
< 0.1%
1915 1
 
< 0.1%
1916 1
 
< 0.1%
1919 2
 
0.1%
1921 3
0.1%
ValueCountFrequency (%)
8096 1
< 0.1%
7887 1
< 0.1%
7732 2
0.1%
7725 1
< 0.1%
7415 1
< 0.1%
7400 1
< 0.1%
7274 1
< 0.1%
7270 1
< 0.1%
7241 1
< 0.1%
7179 1
< 0.1%

Interactions

2023-12-11T06:27:01.903974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:27:01.756183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:27:01.979524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:27:01.826024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:27:03.184275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
집계년도집계월시도명규모구분명분양가격(천원/㎡)
집계년도1.0000.6040.0000.0000.245
집계월0.6041.0000.0000.0000.000
시도명0.0000.0001.0000.0000.815
규모구분명0.0000.0000.0001.0000.468
분양가격(천원/㎡)0.2450.0000.8150.4681.000
2023-12-11T06:27:03.514333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도명집계년도규모구분명
시도명1.0000.0000.000
집계년도0.0001.0000.000
규모구분명0.0000.0001.000
2023-12-11T06:27:03.621611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
집계월분양가격(천원/㎡)집계년도시도명규모구분명
집계월1.000-0.0040.4480.0000.000
분양가격(천원/㎡)-0.0041.0000.1510.4910.212
집계년도0.4480.1511.0000.0000.000
시도명0.0000.4910.0001.0000.000
규모구분명0.0000.2120.0000.0001.000

Missing values

2023-12-11T06:27:02.076255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:27:02.170977image/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

집계년도집계월시도명규모구분명분양가격(천원/㎡)
0201710경남전용면적 60㎡이하2582
1201710경남전용면적 60㎡초과 85㎡이하2414
2201710경남전용면적 85㎡초과 102㎡이하2971
3201710경남전용면적 102㎡초과2984
4201710제주전체3222
5201710제주전용면적 60㎡이하5380
6201710제주전용면적 60㎡초과 85㎡이하3150
7201710서울전체6578
8201710서울전용면적 60㎡이하6815
9201710서울전용면적 60㎡초과 85㎡이하5934
집계년도집계월시도명규모구분명분양가격(천원/㎡)
2041201510전북전용면적 60㎡이하2127
2042201510전북전용면적 60㎡초과 85㎡이하2056
2043201510전북전용면적 85㎡초과 102㎡이하2377
2044201510전북전용면적 102㎡초과2250
2045201510전남전체1925
2046201510전남전용면적 60㎡이하1999
2047201510전남전용면적 60㎡초과 85㎡이하1922
2048201510전남전용면적 85㎡초과 102㎡이하2262
2049201510전남전용면적 102㎡초과2292
2050201510경북전체2148