Overview

Dataset statistics

Number of variables7
Number of observations683
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory40.1 KiB
Average record size in memory60.2 B

Variable types

DateTime1
Categorical2
Numeric4

Dataset

Description한국부동산원(구.한국감정원)의 청약홈에서 제공하는 가점제 당첨자의 점수 현황입니다.※ 매월 25일, 전월까지의 데이터를 제공하며 전월 데이터는 향후 변동될 수 있습니다.※ "23.1월의 경우 가점제 당첨자가 발생하지 않아 데이터를 제공하지 않습니다.
Author한국부동산원
URLhttps://www.data.go.kr/data/15110991/fileData.do

Alerts

평균 is highly overall correlated with 중위수 and 2 other fieldsHigh correlation
중위수 is highly overall correlated with 평균 and 2 other fieldsHigh correlation
최고 is highly overall correlated with 평균 and 1 other fieldsHigh correlation
최저 is highly overall correlated with 평균 and 1 other fieldsHigh correlation

Reproduction

Analysis started2024-04-29 23:03:23.574749
Analysis finished2024-04-29 23:03:27.341257
Duration3.77 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연월
Date

Distinct49
Distinct (%)7.2%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
Minimum2020-02-01 00:00:00
Maximum2024-03-01 00:00:00
2024-04-30T08:03:27.419096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:03:27.593921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)

지역
Categorical

Distinct17
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
경기
134 
인천
69 
서울
52 
충남
51 
부산
49 
Other values (12)
328 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부산
2nd row대구
3rd row인천
4th row인천
5th row경기

Common Values

ValueCountFrequency (%)
경기 134
19.6%
인천 69
10.1%
서울 52
 
7.6%
충남 51
 
7.5%
부산 49
 
7.2%
전북 36
 
5.3%
경북 35
 
5.1%
경남 34
 
5.0%
강원 33
 
4.8%
전남 29
 
4.2%
Other values (7) 161
23.6%

Length

2024-04-30T08:03:27.743194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기 134
19.6%
인천 69
10.1%
서울 52
 
7.6%
충남 51
 
7.5%
부산 49
 
7.2%
전북 36
 
5.3%
경북 35
 
5.1%
경남 34
 
5.0%
강원 33
 
4.8%
전남 29
 
4.2%
Other values (7) 161
23.6%

청약지역
Categorical

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
해당지역
464 
기타지역
181 
기타경기
 
38

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row해당지역
2nd row해당지역
3rd row해당지역
4th row기타지역
5th row해당지역

Common Values

ValueCountFrequency (%)
해당지역 464
67.9%
기타지역 181
 
26.5%
기타경기 38
 
5.6%

Length

2024-04-30T08:03:27.885028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T08:03:27.987399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당지역 464
67.9%
기타지역 181
 
26.5%
기타경기 38
 
5.6%

평균
Real number (ℝ)

HIGH CORRELATION 

Distinct599
Distinct (%)87.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47.553748
Minimum16
Maximum73.92
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.1 KiB
2024-04-30T08:03:28.103526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16
5-th percentile31.172
Q140.475
median47.26
Q354.51
95-th percentile64.939
Maximum73.92
Range57.92
Interquartile range (IQR)14.035

Descriptive statistics

Standard deviation10.405887
Coefficient of variation (CV)0.21882369
Kurtosis-0.20990852
Mean47.553748
Median Absolute Deviation (MAD)7.06
Skewness-0.060284416
Sum32479.21
Variance108.28248
MonotonicityNot monotonic
2024-04-30T08:03:28.250578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.0 6
 
0.9%
43.0 4
 
0.6%
56.0 3
 
0.4%
52.18 3
 
0.4%
37.0 3
 
0.4%
34.0 3
 
0.4%
44.0 3
 
0.4%
36.5 2
 
0.3%
52.56 2
 
0.3%
59.45 2
 
0.3%
Other values (589) 652
95.5%
ValueCountFrequency (%)
16.0 1
0.1%
17.5 1
0.1%
18.0 1
0.1%
18.75 1
0.1%
19.0 1
0.1%
21.0 1
0.1%
23.5 1
0.1%
23.75 1
0.1%
24.0 1
0.1%
24.3 1
0.1%
ValueCountFrequency (%)
73.92 1
0.1%
72.91 1
0.1%
71.03 1
0.1%
70.75 2
0.3%
70.52 1
0.1%
70.47 1
0.1%
70.36 1
0.1%
70.21 1
0.1%
69.32 1
0.1%
69.17 1
0.1%

중위수
Real number (ℝ)

HIGH CORRELATION 

Distinct94
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47.367496
Minimum16
Maximum74
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.1 KiB
2024-04-30T08:03:28.386512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16
5-th percentile29
Q139
median48
Q355.75
95-th percentile66
Maximum74
Range58
Interquartile range (IQR)16.75

Descriptive statistics

Standard deviation11.458279
Coefficient of variation (CV)0.24190173
Kurtosis-0.50770158
Mean47.367496
Median Absolute Deviation (MAD)8
Skewness-0.1463995
Sum32352
Variance131.29217
MonotonicityNot monotonic
2024-04-30T08:03:28.525461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
51.0 28
 
4.1%
52.0 23
 
3.4%
43.0 22
 
3.2%
49.0 20
 
2.9%
54.0 20
 
2.9%
58.0 20
 
2.9%
45.0 19
 
2.8%
53.0 19
 
2.8%
46.0 19
 
2.8%
55.0 18
 
2.6%
Other values (84) 475
69.5%
ValueCountFrequency (%)
16.0 1
 
0.1%
17.5 1
 
0.1%
18.0 1
 
0.1%
19.0 2
 
0.3%
21.0 3
0.4%
21.5 2
 
0.3%
23.0 2
 
0.3%
23.5 1
 
0.1%
24.0 6
0.9%
24.5 1
 
0.1%
ValueCountFrequency (%)
74.0 1
 
0.1%
73.0 2
 
0.3%
70.0 2
 
0.3%
69.0 17
2.5%
68.5 1
 
0.1%
68.0 2
 
0.3%
67.0 6
 
0.9%
66.5 1
 
0.1%
66.0 7
1.0%
65.5 1
 
0.1%

최고
Real number (ℝ)

HIGH CORRELATION 

Distinct57
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67.402635
Minimum16
Maximum84
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.1 KiB
2024-04-30T08:03:28.896953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16
5-th percentile46
Q163
median69
Q374
95-th percentile79.9
Maximum84
Range68
Interquartile range (IQR)11

Descriptive statistics

Standard deviation11.017999
Coefficient of variation (CV)0.1634654
Kurtosis3.6404399
Mean67.402635
Median Absolute Deviation (MAD)5
Skewness-1.5858086
Sum46036
Variance121.3963
MonotonicityNot monotonic
2024-04-30T08:03:29.033724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
69 80
 
11.7%
74 76
 
11.1%
79 54
 
7.9%
68 28
 
4.1%
71 25
 
3.7%
65 24
 
3.5%
75 24
 
3.5%
72 23
 
3.4%
70 23
 
3.4%
64 20
 
2.9%
Other values (47) 306
44.8%
ValueCountFrequency (%)
16 1
0.1%
18 1
0.1%
19 2
0.3%
21 1
0.1%
22 1
0.1%
24 2
0.3%
26 1
0.1%
27 1
0.1%
29 1
0.1%
33 1
0.1%
ValueCountFrequency (%)
84 11
 
1.6%
83 3
 
0.4%
82 4
 
0.6%
81 8
 
1.2%
80 9
 
1.3%
79 54
7.9%
78 13
 
1.9%
77 16
 
2.3%
76 16
 
2.3%
75 24
3.5%

최저
Real number (ℝ)

HIGH CORRELATION 

Distinct59
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.913616
Minimum9
Maximum69
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.1 KiB
2024-04-30T08:03:29.176343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile12
Q122
median28
Q338
95-th percentile57.9
Maximum69
Range60
Interquartile range (IQR)16

Descriptive statistics

Standard deviation13.196346
Coefficient of variation (CV)0.42687811
Kurtosis-0.0058358759
Mean30.913616
Median Absolute Deviation (MAD)7
Skewness0.73326394
Sum21114
Variance174.14355
MonotonicityNot monotonic
2024-04-30T08:03:29.467489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25 37
 
5.4%
27 35
 
5.1%
26 30
 
4.4%
29 30
 
4.4%
23 29
 
4.2%
24 25
 
3.7%
28 24
 
3.5%
32 23
 
3.4%
30 22
 
3.2%
22 21
 
3.1%
Other values (49) 407
59.6%
ValueCountFrequency (%)
9 8
1.2%
10 10
1.5%
11 10
1.5%
12 11
1.6%
13 10
1.5%
14 8
1.2%
15 12
1.8%
16 15
2.2%
17 7
1.0%
18 11
1.6%
ValueCountFrequency (%)
69 3
0.4%
67 1
 
0.1%
66 3
0.4%
64 3
0.4%
63 4
0.6%
62 3
0.4%
61 4
0.6%
60 1
 
0.1%
59 6
0.9%
58 7
1.0%

Interactions

2024-04-30T08:03:26.772209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:03:25.408750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:03:25.992259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:03:26.408438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:03:26.861238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:03:25.550607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:03:26.085194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:03:26.499797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:03:26.944834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:03:25.782294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:03:26.192224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:03:26.587222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:03:27.041858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:03:25.895112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:03:26.313084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:03:26.680904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-30T08:03:29.607637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연월지역청약지역평균중위수최고최저
연월1.0000.0000.0000.3400.1920.3350.214
지역0.0001.0000.5730.4160.3860.3410.387
청약지역0.0000.5731.0000.3330.3650.4250.193
평균0.3400.4160.3331.0000.9730.8580.846
중위수0.1920.3860.3650.9731.0000.7970.762
최고0.3350.3410.4250.8580.7971.0000.376
최저0.2140.3870.1930.8460.7620.3761.000
2024-04-30T08:03:29.734172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
청약지역지역
청약지역1.0000.373
지역0.3731.000
2024-04-30T08:03:29.848668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
평균중위수최고최저지역청약지역
평균1.0000.9850.6440.6200.1740.211
중위수0.9851.0000.6410.5580.1600.234
최고0.6440.6411.0000.0700.1390.281
최저0.6200.5580.0701.0000.1600.116
지역0.1740.1600.1390.1601.0000.373
청약지역0.2110.2340.2810.1160.3731.000

Missing values

2024-04-30T08:03:27.166830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-30T08:03:27.292026image/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

연월지역청약지역평균중위수최고최저
02020-02부산해당지역49.5249.07130
12020-02대구해당지역66.3766.07959
22020-02인천해당지역42.0541.55624
32020-02인천기타지역50.6149.06945
42020-02경기해당지역60.5762.08421
52020-02경기기타경기68.4869.07446
62020-02경기기타지역67.4469.07956
72020-02충남해당지역43.4544.56922
82020-02충남기타지역64.064.06464
92020-02전남해당지역43.8742.05637
연월지역청약지역평균중위수최고최저
6732024-02경기해당지역45.8144.07126
6742024-02경기기타지역44.3442.56333
6752024-02충북해당지역39.0337.07525
6762024-02전북해당지역64.8466.07952
6772024-02경남해당지역41.835.06531
6782024-02제주해당지역52.2352.07440
6792024-03대구해당지역51.8251.57436
6802024-03대전해당지역33.1831.05224
6812024-03대전기타지역37.037.04628
6822024-03충남해당지역65.2566.07358