Overview

Dataset statistics

Number of variables6
Number of observations58
Missing cells2
Missing cells (%)0.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 KiB
Average record size in memory52.3 B

Variable types

Categorical4
Numeric2

Dataset

Description한국수자원공사의 사업지구별 분양계획을 아래와 같이 제공 합니다.제공정보- 용도, 분양시기, 사업지구, 공급방법, 필지수, 면적(천제곱미터) 등
Author한국수자원공사
URLhttps://www.data.go.kr/data/15054524/fileData.do

Alerts

필지수 has 1 (1.7%) missing valuesMissing
면적(천제곱미터) has 1 (1.7%) missing valuesMissing

Reproduction

Analysis started2024-04-21 01:21:35.065605
Analysis finished2024-04-21 01:21:37.286977
Duration2.22 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

용도
Categorical

Distinct6
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Memory size596.0 B
주거용지
16 
상업용지
15 
지원용지
13 
산업용지
8 
기타용지
5 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique1 ?
Unique (%)1.7%

Sample

1st row산업용지
2nd row상업용지
3rd row지원용지
4th row주거용지
5th row지원용지

Common Values

ValueCountFrequency (%)
주거용지 16
27.6%
상업용지 15
25.9%
지원용지 13
22.4%
산업용지 8
13.8%
기타용지 5
 
8.6%
<NA> 1
 
1.7%

Length

2024-04-21T10:21:37.343409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:21:37.434992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주거용지 16
27.6%
상업용지 15
25.9%
지원용지 13
22.4%
산업용지 8
13.8%
기타용지 5
 
8.6%
na 1
 
1.7%

분양시기
Categorical

Distinct17
Distinct (%)29.3%
Missing0
Missing (%)0.0%
Memory size596.0 B
2024-05-01
9 
2024-06-01
9 
2024-04-01
6 
2023-05-01
5 
2023-10-01
4 
Other values (12)
25 

Length

Max length10
Median length10
Mean length9.8965517
Min length4

Unique

Unique3 ?
Unique (%)5.2%

Sample

1st row2023-05-01
2nd row2023-05-01
3rd row2023-05-01
4th row2023-12-01
5th row2023-05-01

Common Values

ValueCountFrequency (%)
2024-05-01 9
15.5%
2024-06-01 9
15.5%
2024-04-01 6
10.3%
2023-05-01 5
8.6%
2023-10-01 4
 
6.9%
2023-07-01 4
 
6.9%
2024-09-01 3
 
5.2%
2024-10-01 3
 
5.2%
2023-04-01 2
 
3.4%
2024-07-01 2
 
3.4%
Other values (7) 11
19.0%

Length

2024-04-21T10:21:37.540861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2024-05-01 9
15.5%
2024-06-01 9
15.5%
2024-04-01 6
10.3%
2023-05-01 5
8.6%
2023-10-01 4
 
6.9%
2023-07-01 4
 
6.9%
2024-09-01 3
 
5.2%
2024-10-01 3
 
5.2%
2023-06-01 2
 
3.4%
2023-09-01 2
 
3.4%
Other values (7) 11
19.0%

사업지구
Categorical

Distinct8
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Memory size596.0 B
부산에코델타시티
20 
구미하이테크밸리
10 
구미확장단지
10 
송산그린시티
6 
시화MTV
4 
Other values (3)
8 

Length

Max length8
Median length8
Mean length6.9310345
Min length4

Unique

Unique1 ?
Unique (%)1.7%

Sample

1st row구미하이테크밸리
2nd row구미하이테크밸리
3rd row구미하이테크밸리
4th row구미하이테크밸리
5th row구미확장단지

Common Values

ValueCountFrequency (%)
부산에코델타시티 20
34.5%
구미하이테크밸리 10
17.2%
구미확장단지 10
17.2%
송산그린시티 6
 
10.3%
시화MTV 4
 
6.9%
나주노안지구 4
 
6.9%
부여규암지구 3
 
5.2%
<NA> 1
 
1.7%

Length

2024-04-21T10:21:37.707901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:21:37.814054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산에코델타시티 20
34.5%
구미하이테크밸리 10
17.2%
구미확장단지 10
17.2%
송산그린시티 6
 
10.3%
시화mtv 4
 
6.9%
나주노안지구 4
 
6.9%
부여규암지구 3
 
5.2%
na 1
 
1.7%

공급방법
Categorical

Distinct4
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size596.0 B
입찰
27 
기타
19 
추첨
11 
<NA>
 
1

Length

Max length4
Median length2
Mean length2.0344828
Min length2

Unique

Unique1 ?
Unique (%)1.7%

Sample

1st row추첨
2nd row입찰
3rd row입찰
4th row입찰
5th row기타

Common Values

ValueCountFrequency (%)
입찰 27
46.6%
기타 19
32.8%
추첨 11
19.0%
<NA> 1
 
1.7%

Length

2024-04-21T10:21:37.935414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:21:38.049952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
입찰 27
46.6%
기타 19
32.8%
추첨 11
19.0%
na 1
 
1.7%

필지수
Real number (ℝ)

MISSING 

Distinct23
Distinct (%)40.4%
Missing1
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean13.157895
Minimum1
Maximum119
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size654.0 B
2024-04-21T10:21:38.142514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q315
95-th percentile43.2
Maximum119
Range118
Interquartile range (IQR)13

Descriptive statistics

Standard deviation21.681781
Coefficient of variation (CV)1.6478154
Kurtosis12.757397
Mean13.157895
Median Absolute Deviation (MAD)3
Skewness3.387755
Sum750
Variance470.09962
MonotonicityNot monotonic
2024-04-21T10:21:38.249964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
1 9
15.5%
3 8
13.8%
2 7
12.1%
4 5
 
8.6%
22 4
 
6.9%
11 2
 
3.4%
6 2
 
3.4%
5 2
 
3.4%
15 2
 
3.4%
14 2
 
3.4%
Other values (13) 14
24.1%
ValueCountFrequency (%)
1 9
15.5%
2 7
12.1%
3 8
13.8%
4 5
8.6%
5 2
 
3.4%
6 2
 
3.4%
7 1
 
1.7%
8 2
 
3.4%
11 2
 
3.4%
12 1
 
1.7%
ValueCountFrequency (%)
119 1
 
1.7%
92 1
 
1.7%
72 1
 
1.7%
36 1
 
1.7%
31 1
 
1.7%
29 1
 
1.7%
24 1
 
1.7%
23 1
 
1.7%
22 4
6.9%
19 1
 
1.7%

면적(천제곱미터)
Real number (ℝ)

MISSING 

Distinct41
Distinct (%)71.9%
Missing1
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean72.929825
Minimum1
Maximum1132
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size654.0 B
2024-04-21T10:21:38.401075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q16
median22
Q357
95-th percentile206.6
Maximum1132
Range1131
Interquartile range (IQR)51

Descriptive statistics

Standard deviation179.16043
Coefficient of variation (CV)2.456614
Kurtosis25.459049
Mean72.929825
Median Absolute Deviation (MAD)19
Skewness4.8684787
Sum4157
Variance32098.459
MonotonicityNot monotonic
2024-04-21T10:21:38.542667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
2 5
 
8.6%
1 4
 
6.9%
6 3
 
5.2%
203 2
 
3.4%
50 2
 
3.4%
22 2
 
3.4%
3 2
 
3.4%
28 2
 
3.4%
11 2
 
3.4%
18 2
 
3.4%
Other values (31) 31
53.4%
ValueCountFrequency (%)
1 4
6.9%
2 5
8.6%
3 2
 
3.4%
4 1
 
1.7%
5 1
 
1.7%
6 3
5.2%
7 1
 
1.7%
11 2
 
3.4%
12 1
 
1.7%
13 1
 
1.7%
ValueCountFrequency (%)
1132 1
1.7%
761 1
1.7%
221 1
1.7%
203 2
3.4%
118 1
1.7%
111 1
1.7%
108 1
1.7%
105 1
1.7%
100 1
1.7%
96 1
1.7%

Interactions

2024-04-21T10:21:36.848001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:21:36.527371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:21:36.922173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:21:36.655236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T10:21:38.629853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
용도분양시기사업지구공급방법필지수면적(천제곱미터)
용도1.0000.0000.1210.5490.0000.000
분양시기0.0001.0000.7710.0000.4150.601
사업지구0.1210.7711.0000.4340.0000.403
공급방법0.5490.0000.4341.0000.5790.000
필지수0.0000.4150.0000.5791.0000.000
면적(천제곱미터)0.0000.6010.4030.0000.0001.000
2024-04-21T10:21:38.737725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분양시기용도공급방법사업지구
분양시기1.0000.0000.0000.442
용도0.0001.0000.4810.061
공급방법0.0000.4811.0000.309
사업지구0.4420.0610.3091.000
2024-04-21T10:21:38.841284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
필지수면적(천제곱미터)용도분양시기사업지구공급방법
필지수1.0000.0570.0000.1780.0000.278
면적(천제곱미터)0.0571.0000.0000.2750.2770.000
용도0.0000.0001.0000.0000.0610.481
분양시기0.1780.2750.0001.0000.4420.000
사업지구0.0000.2770.0610.4421.0000.309
공급방법0.2780.0000.4810.0000.3091.000

Missing values

2024-04-21T10:21:37.012121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T10:21:37.106363image/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.
2024-04-21T10:21:37.221518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

용도분양시기사업지구공급방법필지수면적(천제곱미터)
0산업용지2023-05-01구미하이테크밸리추첨4100
1상업용지2023-05-01구미하이테크밸리입찰2228
2지원용지2023-05-01구미하이테크밸리입찰2450
3주거용지2023-12-01구미하이테크밸리입찰822
4지원용지2023-05-01구미확장단지기타13
5상업용지2023-07-01구미확장단지입찰11
6주거용지2023-07-01구미확장단지추첨294
7주거용지2023-07-01구미확장단지입찰42
8지원용지2023-07-01구미확장단지입찰14118
9상업용지2023-11-01송산그린시티기타157
용도분양시기사업지구공급방법필지수면적(천제곱미터)
48기타용지2024-05-01부산에코델타시티입찰43
49기타용지2024-05-01부산에코델타시티기타26
50산업용지2024-06-01부산에코델타시티기타3105
51산업용지2024-06-01부산에코델타시티추첨311
52기타용지2024-07-01부산에코델타시티기타21
53산업용지2024-07-01부산에코델타시티추첨340
54주거용지2024-09-01부산에코델타시티추첨127
55주거용지2024-09-01부산에코델타시티기타2108
56주거용지2024-10-01부산에코델타시티기타9223
57<NA><NA><NA><NA><NA><NA>