Overview

Dataset statistics

Number of variables8
Number of observations592
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory39.4 KiB
Average record size in memory68.2 B

Variable types

Categorical2
Numeric4
Text2

Dataset

Description한국부동산원(구.한국감정원)의 청약홈에서 제공하는 지역별 청약 경쟁률 현황입니다.※ 매월 25일, 전월까지의 데이터를 제공하며 전월 데이터는 향후 변동될 수 있습니다.
Author한국부동산원
URLhttps://www.data.go.kr/data/15110988/fileData.do

Alerts

특별공급 공급세대수 is highly overall correlated with 특별공급 접수건수 and 2 other fieldsHigh correlation
특별공급 접수건수 is highly overall correlated with 특별공급 공급세대수 and 2 other fieldsHigh correlation
일반공급 공급세대수 is highly overall correlated with 특별공급 공급세대수 and 2 other fieldsHigh correlation
일반공급 접수건수 is highly overall correlated with 특별공급 공급세대수 and 2 other fieldsHigh correlation
특별공급 공급세대수 has 48 (8.1%) zerosZeros
특별공급 접수건수 has 67 (11.3%) zerosZeros

Reproduction

Analysis started2024-04-29 23:03:11.546824
Analysis finished2024-04-29 23:03:15.329337
Duration3.78 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연월
Categorical

Distinct50
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
2021-12
 
16
2021-07
 
16
2022-03
 
15
2022-10
 
15
2022-07
 
15
Other values (45)
515 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-02
2nd row2020-02
3rd row2020-02
4th row2020-02
5th row2020-02

Common Values

ValueCountFrequency (%)
2021-12 16
 
2.7%
2021-07 16
 
2.7%
2022-03 15
 
2.5%
2022-10 15
 
2.5%
2022-07 15
 
2.5%
2022-06 15
 
2.5%
2022-12 15
 
2.5%
2021-11 15
 
2.5%
2022-08 15
 
2.5%
2020-05 15
 
2.5%
Other values (40) 440
74.3%

Length

2024-04-30T08:03:15.402054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2021-12 16
 
2.7%
2021-07 16
 
2.7%
2022-03 15
 
2.5%
2022-10 15
 
2.5%
2022-07 15
 
2.5%
2022-06 15
 
2.5%
2022-12 15
 
2.5%
2021-11 15
 
2.5%
2022-08 15
 
2.5%
2020-05 15
 
2.5%
Other values (40) 440
74.3%

시도
Categorical

Distinct17
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
경기
49 
부산
43 
인천
43 
서울
42 
충남
42 
Other values (12)
373 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기 49
 
8.3%
부산 43
 
7.3%
인천 43
 
7.3%
서울 42
 
7.1%
충남 42
 
7.1%
대구 38
 
6.4%
경남 38
 
6.4%
경북 37
 
6.2%
강원 35
 
5.9%
전북 35
 
5.9%
Other values (7) 190
32.1%

Length

2024-04-30T08:03:15.513218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기 49
 
8.3%
인천 43
 
7.3%
부산 43
 
7.3%
서울 42
 
7.1%
충남 42
 
7.1%
대구 38
 
6.4%
경남 38
 
6.4%
경북 37
 
6.2%
전남 35
 
5.9%
강원 35
 
5.9%
Other values (7) 190
32.1%

특별공급 공급세대수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct449
Distinct (%)75.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean654.95608
Minimum0
Maximum5260
Zeros48
Zeros (%)8.1%
Negative0
Negative (%)0.0%
Memory size5.3 KiB
2024-04-30T08:03:15.626465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1109.75
median367
Q3857
95-th percentile2342.1
Maximum5260
Range5260
Interquartile range (IQR)747.25

Descriptive statistics

Standard deviation835.38052
Coefficient of variation (CV)1.2754756
Kurtosis7.0105999
Mean654.95608
Median Absolute Deviation (MAD)299
Skewness2.4134633
Sum387734
Variance697860.62
MonotonicityNot monotonic
2024-04-30T08:03:15.763169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 48
 
8.1%
117 4
 
0.7%
244 3
 
0.5%
360 3
 
0.5%
31 3
 
0.5%
20 3
 
0.5%
106 3
 
0.5%
322 3
 
0.5%
84 3
 
0.5%
48 3
 
0.5%
Other values (439) 516
87.2%
ValueCountFrequency (%)
0 48
8.1%
3 1
 
0.2%
4 1
 
0.2%
8 1
 
0.2%
11 1
 
0.2%
13 1
 
0.2%
16 2
 
0.3%
18 2
 
0.3%
20 3
 
0.5%
21 1
 
0.2%
ValueCountFrequency (%)
5260 1
0.2%
5067 1
0.2%
4711 1
0.2%
4592 1
0.2%
4336 1
0.2%
4195 1
0.2%
4046 1
0.2%
4020 1
0.2%
3780 1
0.2%
3750 1
0.2%

특별공급 접수건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct417
Distinct (%)70.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2931.3649
Minimum0
Maximum147566
Zeros67
Zeros (%)11.3%
Negative0
Negative (%)0.0%
Memory size5.3 KiB
2024-04-30T08:03:15.906814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q126
median294
Q31949.25
95-th percentile16552.05
Maximum147566
Range147566
Interquartile range (IQR)1923.25

Descriptive statistics

Standard deviation8698.6549
Coefficient of variation (CV)2.9674419
Kurtosis133.39014
Mean2931.3649
Median Absolute Deviation (MAD)294
Skewness9.2744475
Sum1735368
Variance75666597
MonotonicityNot monotonic
2024-04-30T08:03:16.053308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 67
 
11.3%
6 8
 
1.4%
1 8
 
1.4%
4 7
 
1.2%
2 6
 
1.0%
3 5
 
0.8%
13 5
 
0.8%
7 4
 
0.7%
15 4
 
0.7%
16 4
 
0.7%
Other values (407) 474
80.1%
ValueCountFrequency (%)
0 67
11.3%
1 8
 
1.4%
2 6
 
1.0%
3 5
 
0.8%
4 7
 
1.2%
5 3
 
0.5%
6 8
 
1.4%
7 4
 
0.7%
8 1
 
0.2%
9 2
 
0.3%
ValueCountFrequency (%)
147566 1
0.2%
50235 1
0.2%
43830 1
0.2%
41953 1
0.2%
40185 1
0.2%
39825 1
0.2%
34021 1
0.2%
30335 1
0.2%
29826 1
0.2%
27916 1
0.2%

특별공급 경쟁률
Text

Distinct457
Distinct (%)77.2%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
2024-04-30T08:03:16.434938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length5.0185811
Min length4

Characters and Unicode

Total characters2971
Distinct characters15
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique379 ?
Unique (%)64.0%

Sample

1st row22.68
2nd row1.32
3rd row10.34
4th row(△151)
5th row0.00
ValueCountFrequency (%)
0.00 48
 
8.1%
△43 3
 
0.5%
△117 3
 
0.5%
2.32 3
 
0.5%
3.02 3
 
0.5%
5.00 3
 
0.5%
△270 3
 
0.5%
2.18 3
 
0.5%
△26 3
 
0.5%
△28 3
 
0.5%
Other values (447) 517
87.3%
2024-04-30T08:03:17.125133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 304
10.2%
1 292
9.8%
0 288
9.7%
( 288
9.7%
△ 288
9.7%
) 288
9.7%
2 217
7.3%
3 171
 
5.8%
4 165
 
5.6%
5 160
 
5.4%
Other values (5) 510
17.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1786
60.1%
Other Punctuation 321
 
10.8%
Open Punctuation 288
 
9.7%
Other Symbol 288
 
9.7%
Close Punctuation 288
 
9.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 292
16.3%
0 288
16.1%
2 217
12.2%
3 171
9.6%
4 165
9.2%
5 160
9.0%
7 128
7.2%
6 125
7.0%
8 123
6.9%
9 117
6.6%
Other Punctuation
ValueCountFrequency (%)
. 304
94.7%
, 17
 
5.3%
Open Punctuation
ValueCountFrequency (%)
( 288
100.0%
Other Symbol
ValueCountFrequency (%)
△ 288
100.0%
Close Punctuation
ValueCountFrequency (%)
) 288
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2971
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 304
10.2%
1 292
9.8%
0 288
9.7%
( 288
9.7%
△ 288
9.7%
) 288
9.7%
2 217
7.3%
3 171
 
5.8%
4 165
 
5.6%
5 160
 
5.4%
Other values (5) 510
17.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2683
90.3%
Geometric Shapes 288
 
9.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 304
11.3%
1 292
10.9%
0 288
10.7%
( 288
10.7%
) 288
10.7%
2 217
8.1%
3 171
6.4%
4 165
6.1%
5 160
6.0%
7 128
 
4.8%
Other values (4) 382
14.2%
Geometric Shapes
ValueCountFrequency (%)
△ 288
100.0%

일반공급 공급세대수
Real number (ℝ)

HIGH CORRELATION 

Distinct484
Distinct (%)81.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean747.75845
Minimum1
Maximum5788
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 KiB
2024-04-30T08:03:17.299049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile50.55
Q1152.5
median416.5
Q3982.25
95-th percentile2742.9
Maximum5788
Range5787
Interquartile range (IQR)829.75

Descriptive statistics

Standard deviation931.20531
Coefficient of variation (CV)1.245329
Kurtosis8.1060596
Mean747.75845
Median Absolute Deviation (MAD)305.5
Skewness2.5863199
Sum442673
Variance867143.32
MonotonicityNot monotonic
2024-04-30T08:03:17.449083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
55 4
 
0.7%
134 3
 
0.5%
425 3
 
0.5%
394 3
 
0.5%
71 3
 
0.5%
56 3
 
0.5%
66 3
 
0.5%
106 3
 
0.5%
116 3
 
0.5%
182 3
 
0.5%
Other values (474) 561
94.8%
ValueCountFrequency (%)
1 1
0.2%
14 1
0.2%
17 1
0.2%
18 1
0.2%
19 2
0.3%
24 1
0.2%
25 2
0.3%
29 1
0.2%
33 2
0.3%
34 2
0.3%
ValueCountFrequency (%)
5788 1
0.2%
5664 1
0.2%
5348 1
0.2%
5205 1
0.2%
5135 1
0.2%
5106 1
0.2%
5005 1
0.2%
4883 1
0.2%
4829 1
0.2%
4174 1
0.2%

일반공급 접수건수
Real number (ℝ)

HIGH CORRELATION 

Distinct546
Distinct (%)92.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17305.005
Minimum0
Maximum718747
Zeros2
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size5.3 KiB
2024-04-30T08:03:17.598758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile13
Q1459.5
median3777
Q318185.5
95-th percentile75199.5
Maximum718747
Range718747
Interquartile range (IQR)17726

Descriptive statistics

Standard deviation42589.083
Coefficient of variation (CV)2.4610847
Kurtosis129.27885
Mean17305.005
Median Absolute Deviation (MAD)3718
Skewness9.0903689
Sum10244563
Variance1.81383 × 109
MonotonicityNot monotonic
2024-04-30T08:03:17.739431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 5
 
0.8%
13 4
 
0.7%
7 4
 
0.7%
10 4
 
0.7%
25 4
 
0.7%
29 3
 
0.5%
96 3
 
0.5%
24 3
 
0.5%
16 3
 
0.5%
7637 2
 
0.3%
Other values (536) 557
94.1%
ValueCountFrequency (%)
0 2
 
0.3%
1 2
 
0.3%
2 1
 
0.2%
3 2
 
0.3%
5 2
 
0.3%
6 5
0.8%
7 4
0.7%
8 1
 
0.2%
9 2
 
0.3%
10 4
0.7%
ValueCountFrequency (%)
718747 1
0.2%
273396 1
0.2%
234575 1
0.2%
220843 1
0.2%
190117 1
0.2%
178571 1
0.2%
170421 1
0.2%
163412 1
0.2%
142657 1
0.2%
139740 1
0.2%

일반공급 경쟁률
Text

Distinct534
Distinct (%)90.2%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
2024-04-30T08:03:18.122539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.7618243
Min length4

Characters and Unicode

Total characters2819
Distinct characters15
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique483 ?
Unique (%)81.6%

Sample

1st row146.82
2nd row33.92
3rd row141.40
4th row19.79
5th row(△49)
ValueCountFrequency (%)
△64 3
 
0.5%
1.10 3
 
0.5%
△37 3
 
0.5%
3.77 3
 
0.5%
△27 3
 
0.5%
1.86 3
 
0.5%
1.19 3
 
0.5%
△28 2
 
0.3%
△36 2
 
0.3%
△32 2
 
0.3%
Other values (524) 565
95.4%
2024-04-30T08:03:18.776115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 483
17.1%
1 341
12.1%
2 254
9.0%
3 232
8.2%
4 201
7.1%
7 180
 
6.4%
5 177
 
6.3%
6 176
 
6.2%
9 158
 
5.6%
8 158
 
5.6%
Other values (5) 459
16.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2006
71.2%
Other Punctuation 486
 
17.2%
Open Punctuation 109
 
3.9%
Other Symbol 109
 
3.9%
Close Punctuation 109
 
3.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 341
17.0%
2 254
12.7%
3 232
11.6%
4 201
10.0%
7 180
9.0%
5 177
8.8%
6 176
8.8%
9 158
7.9%
8 158
7.9%
0 129
 
6.4%
Other Punctuation
ValueCountFrequency (%)
. 483
99.4%
, 3
 
0.6%
Open Punctuation
ValueCountFrequency (%)
( 109
100.0%
Other Symbol
ValueCountFrequency (%)
△ 109
100.0%
Close Punctuation
ValueCountFrequency (%)
) 109
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2819
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 483
17.1%
1 341
12.1%
2 254
9.0%
3 232
8.2%
4 201
7.1%
7 180
 
6.4%
5 177
 
6.3%
6 176
 
6.2%
9 158
 
5.6%
8 158
 
5.6%
Other values (5) 459
16.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2710
96.1%
Geometric Shapes 109
 
3.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 483
17.8%
1 341
12.6%
2 254
9.4%
3 232
8.6%
4 201
7.4%
7 180
 
6.6%
5 177
 
6.5%
6 176
 
6.5%
9 158
 
5.8%
8 158
 
5.8%
Other values (4) 350
12.9%
Geometric Shapes
ValueCountFrequency (%)
△ 109
100.0%

Interactions

2024-04-30T08:03:14.755131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:03:13.490718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:03:13.904095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:03:14.327962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:03:14.844533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:03:13.629739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:03:14.002554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:03:14.431289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:03:14.954755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:03:13.716950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:03:14.108319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:03:14.544214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:03:15.042932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:03:13.812080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:03:14.222696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:03:14.660483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-30T08:03:19.131496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연월시도특별공급 공급세대수특별공급 접수건수일반공급 공급세대수일반공급 접수건수
연월1.0000.0000.0000.0000.0000.325
시도0.0001.0000.4550.3970.4760.288
특별공급 공급세대수0.0000.4551.0000.7220.9300.708
특별공급 접수건수0.0000.3970.7221.0000.6840.944
일반공급 공급세대수0.0000.4760.9300.6841.0000.763
일반공급 접수건수0.3250.2880.7080.9440.7631.000
2024-04-30T08:03:19.239388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연월시도
연월1.0000.000
시도0.0001.000
2024-04-30T08:03:19.320756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
특별공급 공급세대수특별공급 접수건수일반공급 공급세대수일반공급 접수건수연월시도
특별공급 공급세대수1.0000.6730.8890.6690.0000.194
특별공급 접수건수0.6731.0000.6020.9110.0000.215
일반공급 공급세대수0.8890.6021.0000.6860.0000.205
일반공급 접수건수0.6690.9110.6861.0000.1410.151
연월0.0000.0000.0000.1411.0000.000
시도0.1940.2150.2050.1510.0001.000

Missing values

2024-04-30T08:03:15.157170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-30T08:03:15.276544image/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

연월시도특별공급 공급세대수특별공급 접수건수특별공급 경쟁률일반공급 공급세대수일반공급 접수건수일반공급 경쟁률
02020-02서울7101610622.6825236999146.82
12020-02부산3674841.324891658833.92
22020-02대구262271010.3439455710141.40
32020-02인천251100(△151)8001583319.79
42020-02울산000.006920(△49)
52020-02경기21022735013.01273323457585.83
62020-02강원23729(△208)4914971.01
72020-02충남9362(△31)58925944.40
82020-02전남2117(△204)2876192.16
92020-02경북6133(△28)12511208.96
연월시도특별공급 공급세대수특별공급 접수건수특별공급 경쟁률일반공급 공급세대수일반공급 접수건수일반공급 경쟁률
5822024-02강원000.00827(△75)
5832024-02충북775553(△222)90045615.07
5842024-02충남56561(△504)7257321.01
5852024-02전북58136816.346443579755.59
5862024-02경북000.0012325(△98)
5872024-02경남1174(△113)1151391.21
5882024-02제주000.006537761.19
5892024-03대구721031.4371137019.30
5902024-03대전232164(△68)2634601.75
5912024-03충남000.004417929407.48