Overview

Dataset statistics

Number of variables15
Number of observations443
Missing cells497
Missing cells (%)7.5%
Duplicate rows24
Duplicate rows (%)5.4%
Total size in memory53.8 KiB
Average record size in memory124.3 B

Variable types

Categorical5
Text4
Numeric3
DateTime2
Unsupported1

Dataset

Description경기도_공동주택 미분양 현황
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=EF0EEXM6XLFQK6DWAKUT18918283&infSeq=1

Alerts

임대분양구분명 has constant value ""Constant
Dataset has 24 (5.4%) duplicate rowsDuplicates
관할군구명 is highly overall correlated with 시군명 and 1 other fieldsHigh correlation
시군명 is highly overall correlated with 관할군구명 and 2 other fieldsHigh correlation
민간공공구분명 is highly overall correlated with 시군명High correlation
준공여부구분명 is highly overall correlated with 시군명 and 1 other fieldsHigh correlation
관할군구명 is highly imbalanced (58.4%)Imbalance
민간공공구분명 is highly imbalanced (91.7%)Imbalance
관할읍면동명 has 23 (5.2%) missing valuesMissing
시공소재지위치 has 7 (1.6%) missing valuesMissing
분양청약일자 has 24 (5.4%) missing valuesMissing
비고 has 443 (100.0%) missing valuesMissing
비고 is an unsupported type, check if it needs cleaning or further analysisUnsupported
당월미분양가구수(개) has 114 (25.7%) zerosZeros

Reproduction

Analysis started2024-03-16 04:16:07.346244
Analysis finished2024-03-16 04:16:14.798926
Duration7.45 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
양주시
91 
용인시
61 
화성시
39 
부천시
39 
평택시
38 
Other values (18)
175 

Length

Max length4
Median length3
Mean length3.1422122
Min length3

Unique

Unique2 ?
Unique (%)0.5%

Sample

1st row가평군
2nd row고양시
3rd row고양시
4th row고양시
5th row고양시

Common Values

ValueCountFrequency (%)
양주시 91
20.5%
용인시 61
13.8%
화성시 39
8.8%
부천시 39
8.8%
평택시 38
8.6%
의정부시 34
 
7.7%
남양주시 22
 
5.0%
성남시 20
 
4.5%
김포시 17
 
3.8%
안성시 15
 
3.4%
Other values (13) 67
15.1%

Length

2024-03-16T04:16:15.042749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
양주시 91
20.5%
용인시 61
13.8%
화성시 39
8.8%
부천시 39
8.8%
평택시 38
8.6%
의정부시 34
 
7.7%
남양주시 22
 
5.0%
성남시 20
 
4.5%
김포시 17
 
3.8%
안성시 15
 
3.4%
Other values (13) 67
15.1%

관할군구명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct10
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
343 
기흥구
36 
중원구
 
20
수지구
 
9
처인구
 
9
Other values (5)
 
26

Length

Max length4
Median length4
Mean length3.7832957
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row일산동구
3rd row일산동구
4th row덕양구
5th row덕양구

Common Values

ValueCountFrequency (%)
<NA> 343
77.4%
기흥구 36
 
8.1%
중원구 20
 
4.5%
수지구 9
 
2.0%
처인구 9
 
2.0%
덕양구 7
 
1.6%
권선구 7
 
1.6%
동안구 5
 
1.1%
일산동구 4
 
0.9%
팔달구 3
 
0.7%

Length

2024-03-16T04:16:15.674144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T04:16:16.301860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 343
77.4%
기흥구 36
 
8.1%
중원구 20
 
4.5%
수지구 9
 
2.0%
처인구 9
 
2.0%
덕양구 7
 
1.6%
권선구 7
 
1.6%
동안구 5
 
1.1%
일산동구 4
 
0.9%
팔달구 3
 
0.7%

관할읍면동명
Text

MISSING 

Distinct56
Distinct (%)13.3%
Missing23
Missing (%)5.2%
Memory size3.6 KiB
2024-03-16T04:16:16.855232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.1190476
Min length2

Characters and Unicode

Total characters1310
Distinct characters85
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)2.1%

Sample

1st row가평읍
2nd row풍동
3rd row풍동
4th row삼송동
5th row삼송동
ValueCountFrequency (%)
옥정동 84
20.0%
마북동 32
 
7.6%
현덕면 21
 
5.0%
의정부동 20
 
4.8%
공도읍 15
 
3.6%
하대원동 15
 
3.6%
오산동 15
 
3.6%
원종동 12
 
2.9%
장기동 11
 
2.6%
권선동 10
 
2.4%
Other values (46) 185
44.0%
2024-03-16T04:16:18.520557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 306
23.4%
정 114
 
8.7%
옥 84
 
6.4%
읍 83
 
6.3%
면 34
 
2.6%
마 32
 
2.4%
북 32
 
2.4%
현 28
 
2.1%
부 28
 
2.1%
원 27
 
2.1%
Other values (75) 542
41.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1307
99.8%
Decimal Number 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 306
23.4%
정 114
 
8.7%
옥 84
 
6.4%
읍 83
 
6.4%
면 34
 
2.6%
마 32
 
2.4%
북 32
 
2.4%
현 28
 
2.1%
부 28
 
2.1%
원 27
 
2.1%
Other values (74) 539
41.2%
Decimal Number
ValueCountFrequency (%)
1 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1307
99.8%
Common 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 306
23.4%
정 114
 
8.7%
옥 84
 
6.4%
읍 83
 
6.4%
면 34
 
2.6%
마 32
 
2.4%
북 32
 
2.4%
현 28
 
2.1%
부 28
 
2.1%
원 27
 
2.1%
Other values (74) 539
41.2%
Common
ValueCountFrequency (%)
1 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1307
99.8%
ASCII 3
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 306
23.4%
정 114
 
8.7%
옥 84
 
6.4%
읍 83
 
6.4%
면 34
 
2.6%
마 32
 
2.4%
북 32
 
2.4%
현 28
 
2.1%
부 28
 
2.1%
원 27
 
2.1%
Other values (74) 539
41.2%
ASCII
ValueCountFrequency (%)
1 3
100.0%

시공소재지위치
Text

MISSING 

Distinct91
Distinct (%)20.9%
Missing7
Missing (%)1.6%
Memory size3.6 KiB
2024-03-16T04:16:19.179343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length34
Mean length22
Min length11

Characters and Unicode

Total characters9592
Distinct characters185
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)3.9%

Sample

1st row경기도 가평군 읍내리 766-3(가평블루핀)
2nd row경기도 고양시 일산동구 풍동 655-18번지 일원(요진 Y-HAUS)
3rd row경기도 고양시 일산동구 풍동 655-18번지 일원(요진 Y-HAUS)
4th row경기도 고양시 덕양구 삼송동 삼송택지개발지구 B-5블럭
5th row경기도 고양시 덕양구 삼송동 삼송택지개발지구 B-5블럭
ValueCountFrequency (%)
경기도 436
 
21.0%
양주시 91
 
4.4%
옥정동 84
 
4.1%
용인시 54
 
2.6%
화성시 39
 
1.9%
부천시 39
 
1.9%
평택시 38
 
1.8%
기흥구 36
 
1.7%
의정부시 34
 
1.6%
마북동 32
 
1.5%
Other values (224) 1191
57.4%
2024-03-16T04:16:20.348546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1640
 
17.1%
기 486
 
5.1%
도 480
 
5.0%
시 452
 
4.7%
경 436
 
4.5%
동 336
 
3.5%
- 335
 
3.5%
1 277
 
2.9%
지 271
 
2.8%
2 244
 
2.5%
Other values (175) 4635
48.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5817
60.6%
Space Separator 1640
 
17.1%
Decimal Number 1321
 
13.8%
Uppercase Letter 394
 
4.1%
Dash Punctuation 335
 
3.5%
Close Punctuation 33
 
0.3%
Open Punctuation 33
 
0.3%
Lowercase Letter 19
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 486
 
8.4%
도 480
 
8.3%
시 452
 
7.8%
경 436
 
7.5%
동 336
 
5.8%
지 271
 
4.7%
구 237
 
4.1%
정 233
 
4.0%
양 182
 
3.1%
옥 168
 
2.9%
Other values (147) 2536
43.6%
Decimal Number
ValueCountFrequency (%)
1 277
21.0%
2 244
18.5%
3 166
12.6%
4 135
10.2%
5 131
9.9%
9 97
 
7.3%
7 85
 
6.4%
8 75
 
5.7%
6 67
 
5.1%
0 44
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
B 208
52.8%
L 125
31.7%
D 28
 
7.1%
A 13
 
3.3%
U 4
 
1.0%
S 4
 
1.0%
H 4
 
1.0%
Y 4
 
1.0%
C 2
 
0.5%
E 2
 
0.5%
Lowercase Letter
ValueCountFrequency (%)
c 11
57.9%
a 4
 
21.1%
l 2
 
10.5%
b 2
 
10.5%
Space Separator
ValueCountFrequency (%)
1640
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 335
100.0%
Close Punctuation
ValueCountFrequency (%)
) 33
100.0%
Open Punctuation
ValueCountFrequency (%)
( 33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5817
60.6%
Common 3362
35.1%
Latin 413
 
4.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 486
 
8.4%
도 480
 
8.3%
시 452
 
7.8%
경 436
 
7.5%
동 336
 
5.8%
지 271
 
4.7%
구 237
 
4.1%
정 233
 
4.0%
양 182
 
3.1%
옥 168
 
2.9%
Other values (147) 2536
43.6%
Common
ValueCountFrequency (%)
1640
48.8%
- 335
 
10.0%
1 277
 
8.2%
2 244
 
7.3%
3 166
 
4.9%
4 135
 
4.0%
5 131
 
3.9%
9 97
 
2.9%
7 85
 
2.5%
8 75
 
2.2%
Other values (4) 177
 
5.3%
Latin
ValueCountFrequency (%)
B 208
50.4%
L 125
30.3%
D 28
 
6.8%
A 13
 
3.1%
c 11
 
2.7%
U 4
 
1.0%
S 4
 
1.0%
H 4
 
1.0%
Y 4
 
1.0%
a 4
 
1.0%
Other values (4) 8
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5817
60.6%
ASCII 3775
39.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1640
43.4%
- 335
 
8.9%
1 277
 
7.3%
2 244
 
6.5%
B 208
 
5.5%
3 166
 
4.4%
4 135
 
3.6%
5 131
 
3.5%
L 125
 
3.3%
9 97
 
2.6%
Other values (18) 417
 
11.0%
Hangul
ValueCountFrequency (%)
기 486
 
8.4%
도 480
 
8.3%
시 452
 
7.8%
경 436
 
7.5%
동 336
 
5.8%
지 271
 
4.7%
구 237
 
4.1%
정 233
 
4.0%
양 182
 
3.1%
옥 168
 
2.9%
Other values (147) 2536
43.6%

시공사정보
Text

Distinct74
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2024-03-16T04:16:21.115802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length16
Mean length6.1534989
Min length3

Characters and Unicode

Total characters2726
Distinct characters115
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)2.7%

Sample

1st row㈜홍성건설
2nd row요진건설산업㈜
3rd row요진건설산업㈜
4th row㈜대송
5th row㈜대송
ValueCountFrequency (%)
㈜현대건설 63
 
14.0%
동부건설㈜ 22
 
4.9%
㈜케이씨씨건설 21
 
4.7%
대우산업개발주식회사 20
 
4.5%
현대엔지니어링㈜ 12
 
2.7%
㈜서희건설 12
 
2.7%
범양건영㈜ 11
 
2.4%
㈜dl이앤씨 10
 
2.2%
dl이엔씨 10
 
2.2%
㈜한양 9
 
2.0%
Other values (66) 259
57.7%
2024-03-16T04:16:22.138068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 332
 
12.2%
건 318
 
11.7%
설 283
 
10.4%
대 138
 
5.1%
이 89
 
3.3%
씨 81
 
3.0%
현 80
 
2.9%
업 65
 
2.4%
산 53
 
1.9%
주 46
 
1.7%
Other values (105) 1241
45.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2240
82.2%
Other Symbol 332
 
12.2%
Uppercase Letter 54
 
2.0%
Lowercase Letter 26
 
1.0%
Close Punctuation 21
 
0.8%
Open Punctuation 21
 
0.8%
Decimal Number 14
 
0.5%
Other Punctuation 12
 
0.4%
Space Separator 6
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
건 318
 
14.2%
설 283
 
12.6%
대 138
 
6.2%
이 89
 
4.0%
씨 81
 
3.6%
현 80
 
3.6%
업 65
 
2.9%
산 53
 
2.4%
주 46
 
2.1%
합 38
 
1.7%
Other values (87) 1049
46.8%
Uppercase Letter
ValueCountFrequency (%)
D 16
29.6%
L 12
22.2%
G 7
13.0%
S 7
13.0%
C 6
 
11.1%
H 4
 
7.4%
E 2
 
3.7%
Lowercase Letter
ValueCountFrequency (%)
d 10
38.5%
l 10
38.5%
c 4
 
15.4%
k 2
 
7.7%
Other Punctuation
ValueCountFrequency (%)
, 10
83.3%
& 2
 
16.7%
Other Symbol
ValueCountFrequency (%)
㈜ 332
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Decimal Number
ValueCountFrequency (%)
0 14
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2572
94.4%
Latin 80
 
2.9%
Common 74
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 332
 
12.9%
건 318
 
12.4%
설 283
 
11.0%
대 138
 
5.4%
이 89
 
3.5%
씨 81
 
3.1%
현 80
 
3.1%
업 65
 
2.5%
산 53
 
2.1%
주 46
 
1.8%
Other values (88) 1087
42.3%
Latin
ValueCountFrequency (%)
D 16
20.0%
L 12
15.0%
d 10
12.5%
l 10
12.5%
G 7
8.8%
S 7
8.8%
C 6
 
7.5%
c 4
 
5.0%
H 4
 
5.0%
E 2
 
2.5%
Common
ValueCountFrequency (%)
) 21
28.4%
( 21
28.4%
0 14
18.9%
, 10
13.5%
6
 
8.1%
& 2
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2240
82.2%
None 332
 
12.2%
ASCII 154
 
5.6%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 332
100.0%
Hangul
ValueCountFrequency (%)
건 318
 
14.2%
설 283
 
12.6%
대 138
 
6.2%
이 89
 
4.0%
씨 81
 
3.6%
현 80
 
3.6%
업 65
 
2.9%
산 53
 
2.4%
주 46
 
2.1%
합 38
 
1.7%
Other values (87) 1049
46.8%
ASCII
ValueCountFrequency (%)
) 21
13.6%
( 21
13.6%
D 16
10.4%
0 14
9.1%
L 12
7.8%
, 10
 
6.5%
d 10
 
6.5%
l 10
 
6.5%
G 7
 
4.5%
S 7
 
4.5%
Other values (7) 26
16.9%

시행사정보
Text

Distinct72
Distinct (%)16.3%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2024-03-16T04:16:22.634446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length25
Mean length7.4446953
Min length3

Characters and Unicode

Total characters3298
Distinct characters147
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)2.5%

Sample

1st row대한토지신탁㈜
2nd row요진개발㈜
3rd row요진개발㈜
4th row㈜생보부동산신탁
5th row㈜생보부동산신탁
ValueCountFrequency (%)
㈜무궁화신탁 68
 
14.4%
한국자산신탁㈜ 22
 
4.7%
㈜하나자신탁 22
 
4.7%
kb부동산신탁㈜ 15
 
3.2%
교보자산신탁㈜ 14
 
3.0%
우리자산신탁㈜ 14
 
3.0%
대한토지신탁 11
 
2.3%
온동네디엔아이㈜ 11
 
2.3%
엠디엠 10
 
2.1%
㈜dl이앤씨 10
 
2.1%
Other values (73) 276
58.4%
2024-03-16T04:16:23.708173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 296
 
9.0%
신 265
 
8.0%
탁 241
 
7.3%
산 141
 
4.3%
자 109
 
3.3%
주 83
 
2.5%
화 77
 
2.3%
궁 74
 
2.2%
무 74
 
2.2%
한 69
 
2.1%
Other values (137) 1869
56.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2795
84.7%
Other Symbol 296
 
9.0%
Uppercase Letter 91
 
2.8%
Decimal Number 38
 
1.2%
Space Separator 30
 
0.9%
Other Punctuation 28
 
0.8%
Open Punctuation 7
 
0.2%
Close Punctuation 7
 
0.2%
Lowercase Letter 6
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
신 265
 
9.5%
탁 241
 
8.6%
산 141
 
5.0%
자 109
 
3.9%
주 83
 
3.0%
화 77
 
2.8%
궁 74
 
2.6%
무 74
 
2.6%
한 69
 
2.5%
택 65
 
2.3%
Other values (115) 1597
57.1%
Uppercase Letter
ValueCountFrequency (%)
B 15
16.5%
K 15
16.5%
L 14
15.4%
D 14
15.4%
H 8
8.8%
F 7
7.7%
P 7
7.7%
V 7
7.7%
C 4
 
4.4%
Decimal Number
ValueCountFrequency (%)
0 14
36.8%
3 13
34.2%
2 8
21.1%
8 3
 
7.9%
Other Punctuation
ValueCountFrequency (%)
/ 11
39.3%
* 10
35.7%
, 7
25.0%
Lowercase Letter
ValueCountFrequency (%)
l 3
50.0%
b 3
50.0%
Other Symbol
ValueCountFrequency (%)
㈜ 296
100.0%
Space Separator
ValueCountFrequency (%)
30
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3091
93.7%
Common 110
 
3.3%
Latin 97
 
2.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 296
 
9.6%
신 265
 
8.6%
탁 241
 
7.8%
산 141
 
4.6%
자 109
 
3.5%
주 83
 
2.7%
화 77
 
2.5%
궁 74
 
2.4%
무 74
 
2.4%
한 69
 
2.2%
Other values (116) 1662
53.8%
Latin
ValueCountFrequency (%)
B 15
15.5%
K 15
15.5%
L 14
14.4%
D 14
14.4%
H 8
8.2%
F 7
7.2%
P 7
7.2%
V 7
7.2%
C 4
 
4.1%
l 3
 
3.1%
Common
ValueCountFrequency (%)
30
27.3%
0 14
12.7%
3 13
11.8%
/ 11
 
10.0%
* 10
 
9.1%
2 8
 
7.3%
, 7
 
6.4%
( 7
 
6.4%
) 7
 
6.4%
8 3
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2795
84.7%
None 296
 
9.0%
ASCII 207
 
6.3%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 296
100.0%
Hangul
ValueCountFrequency (%)
신 265
 
9.5%
탁 241
 
8.6%
산 141
 
5.0%
자 109
 
3.9%
주 83
 
3.0%
화 77
 
2.8%
궁 74
 
2.6%
무 74
 
2.6%
한 69
 
2.5%
택 65
 
2.3%
Other values (115) 1597
57.1%
ASCII
ValueCountFrequency (%)
30
14.5%
B 15
 
7.2%
K 15
 
7.2%
0 14
 
6.8%
L 14
 
6.8%
D 14
 
6.8%
3 13
 
6.3%
/ 11
 
5.3%
* 10
 
4.8%
H 8
 
3.9%
Other values (11) 63
30.4%

민간공공구분명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
민간
436 
트라이버
 
5
국민
 
2

Length

Max length4
Median length2
Mean length2.0225734
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
민간 436
98.4%
트라이버 5
 
1.1%
국민 2
 
0.5%

Length

2024-03-16T04:16:24.192290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T04:16:24.536919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
민간 436
98.4%
트라이버 5
 
1.1%
국민 2
 
0.5%

임대분양구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
분양
443 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
분양 443
100.0%

Length

2024-03-16T04:16:24.905863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T04:16:25.291077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
분양 443
100.0%

규모별면적(㎥)
Real number (ℝ)

Distinct137
Distinct (%)30.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean80.536783
Minimum13.2
Maximum524
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-03-16T04:16:25.696523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum13.2
5-th percentile40.086
Q165.495
median84
Q384.9
95-th percentile130.9
Maximum524
Range510.8
Interquartile range (IQR)19.405

Descriptive statistics

Standard deviation33.568937
Coefficient of variation (CV)0.41681497
Kurtosis69.979027
Mean80.536783
Median Absolute Deviation (MAD)3
Skewness5.7941903
Sum35677.795
Variance1126.8735
MonotonicityNot monotonic
2024-03-16T04:16:26.357393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
84.0 150
33.9%
59.0 27
 
6.1%
84.97 20
 
4.5%
74.0 15
 
3.4%
84.9 14
 
3.2%
99.0 9
 
2.0%
84.96 9
 
2.0%
84.46 6
 
1.4%
84.98 6
 
1.4%
45.0 4
 
0.9%
Other values (127) 183
41.3%
ValueCountFrequency (%)
13.2 1
0.2%
13.25 1
0.2%
13.31 1
0.2%
13.78 1
0.2%
13.91 1
0.2%
19.0 1
0.2%
19.6 1
0.2%
20.0 2
0.5%
23.0 1
0.2%
25.71 1
0.2%
ValueCountFrequency (%)
524.0 1
0.2%
220.4 1
0.2%
201.0 1
0.2%
195.0 1
0.2%
192.0 1
0.2%
174.0 1
0.2%
173.0 1
0.2%
170.0 1
0.2%
165.0 1
0.2%
162.0 1
0.2%

총분양가구수(개)
Real number (ℝ)

Distinct152
Distinct (%)34.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean72.76298
Minimum1
Maximum929
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-03-16T04:16:26.827427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q18
median24
Q380
95-th percentile325.8
Maximum929
Range928
Interquartile range (IQR)72

Descriptive statistics

Standard deviation121.55454
Coefficient of variation (CV)1.6705548
Kurtosis14.029847
Mean72.76298
Median Absolute Deviation (MAD)21
Skewness3.3247867
Sum32234
Variance14775.507
MonotonicityNot monotonic
2024-03-16T04:16:27.487121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 24
 
5.4%
2 21
 
4.7%
18 15
 
3.4%
3 14
 
3.2%
6 14
 
3.2%
5 13
 
2.9%
4 13
 
2.9%
20 12
 
2.7%
13 12
 
2.7%
16 11
 
2.5%
Other values (142) 294
66.4%
ValueCountFrequency (%)
1 24
5.4%
2 21
4.7%
3 14
3.2%
4 13
2.9%
5 13
2.9%
6 14
3.2%
7 4
 
0.9%
8 9
 
2.0%
9 10
2.3%
10 10
2.3%
ValueCountFrequency (%)
929 1
0.2%
819 1
0.2%
728 1
0.2%
681 1
0.2%
638 1
0.2%
622 1
0.2%
522 1
0.2%
520 1
0.2%
465 1
0.2%
461 1
0.2%

당월미분양가구수(개)
Real number (ℝ)

ZEROS 

Distinct74
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.699774
Minimum0
Maximum217
Zeros114
Zeros (%)25.7%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-03-16T04:16:27.990753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q313.5
95-th percentile64.9
Maximum217
Range217
Interquartile range (IQR)13.5

Descriptive statistics

Standard deviation28.585154
Coefficient of variation (CV)2.086542
Kurtosis19.146893
Mean13.699774
Median Absolute Deviation (MAD)3
Skewness3.9650574
Sum6069
Variance817.11102
MonotonicityNot monotonic
2024-03-16T04:16:28.445947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 114
25.7%
1 65
14.7%
2 25
 
5.6%
3 22
 
5.0%
4 21
 
4.7%
5 20
 
4.5%
6 15
 
3.4%
18 10
 
2.3%
9 10
 
2.3%
7 9
 
2.0%
Other values (64) 132
29.8%
ValueCountFrequency (%)
0 114
25.7%
1 65
14.7%
2 25
 
5.6%
3 22
 
5.0%
4 21
 
4.7%
5 20
 
4.5%
6 15
 
3.4%
7 9
 
2.0%
8 8
 
1.8%
9 10
 
2.3%
ValueCountFrequency (%)
217 1
0.2%
200 1
0.2%
190 1
0.2%
184 1
0.2%
178 1
0.2%
130 1
0.2%
122 1
0.2%
121 1
0.2%
116 1
0.2%
114 1
0.2%

분양청약일자
Date

MISSING 

Distinct12
Distinct (%)2.9%
Missing24
Missing (%)5.4%
Memory size3.6 KiB
Minimum2024-01-01 00:00:00
Maximum2024-12-01 00:00:00
2024-03-16T04:16:28.815631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:16:29.219265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)

입주예정일자
Date

Distinct17
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
Minimum2000-01-01 00:00:00
Maximum2026-11-01 00:00:00
2024-03-16T04:16:29.555918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:16:29.896766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)

준공여부구분명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
미준공
303 
준공
140 

Length

Max length3
Median length3
Mean length2.6839729
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
미준공 303
68.4%
준공 140
31.6%

Length

2024-03-16T04:16:30.318305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T04:16:30.664323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미준공 303
68.4%
준공 140
31.6%

비고
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing443
Missing (%)100.0%
Memory size4.0 KiB

Interactions

2024-03-16T04:16:12.056512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:16:10.311201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:16:11.198560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:16:12.306979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:16:10.618327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:16:11.536902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:16:12.571275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:16:10.934928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:16:11.785194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-16T04:16:30.862997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명관할군구명관할읍면동명시공소재지위치시공사정보시행사정보민간공공구분명규모별면적(㎥)총분양가구수(개)당월미분양가구수(개)분양청약일자입주예정일자준공여부구분명
시군명1.0001.0001.0001.0000.9970.9990.9070.6840.4100.0000.8550.8700.815
관할군구명1.0001.0000.9800.9910.9870.9870.3770.7600.3820.2640.8960.9220.801
관할읍면동명1.0000.9801.0001.0000.9990.9991.0000.8370.8320.6350.9780.9840.960
시공소재지위치1.0000.9911.0001.0001.0001.0001.0000.8800.8760.5870.9980.9981.000
시공사정보0.9970.9870.9991.0001.0001.0001.0000.8800.8110.6190.9960.9961.000
시행사정보0.9990.9870.9991.0001.0001.0001.0000.8990.8580.4640.9930.9960.999
민간공공구분명0.9070.3771.0001.0001.0001.0001.0000.0000.0000.0000.4840.2970.105
규모별면적(㎥)0.6840.7600.8370.8800.8800.8990.0001.0000.0290.0000.4090.5820.586
총분양가구수(개)0.4100.3820.8320.8760.8110.8580.0000.0291.0000.5390.3790.1990.086
당월미분양가구수(개)0.0000.2640.6350.5870.6190.4640.0000.0000.5391.0000.2080.5470.113
분양청약일자0.8550.8960.9780.9980.9960.9930.4840.4090.3790.2081.0000.8400.695
입주예정일자0.8700.9220.9840.9980.9960.9960.2970.5820.1990.5470.8401.0000.686
준공여부구분명0.8150.8010.9601.0001.0000.9990.1050.5860.0860.1130.6950.6861.000
2024-03-16T04:16:31.293122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관할군구명민간공공구분명시군명준공여부구분명
관할군구명1.0000.3620.9790.794
민간공공구분명0.3621.0000.7570.174
시군명0.9790.7571.0000.723
준공여부구분명0.7940.1740.7231.000
2024-03-16T04:16:31.630496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
규모별면적(㎥)총분양가구수(개)당월미분양가구수(개)시군명관할군구명민간공공구분명준공여부구분명
규모별면적(㎥)1.000-0.003-0.1330.3840.4490.0000.424
총분양가구수(개)-0.0031.0000.2830.1610.2250.0000.065
당월미분양가구수(개)-0.1330.2831.0000.0000.1370.0000.084
시군명0.3840.1610.0001.0000.9790.7570.723
관할군구명0.4490.2250.1370.9791.0000.3620.794
민간공공구분명0.0000.0000.0000.7570.3621.0000.174
준공여부구분명0.4240.0650.0840.7230.7940.1741.000

Missing values

2024-03-16T04:16:12.997670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-16T04:16:13.751428image/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.
2024-03-16T04:16:14.472494image/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

시군명관할군구명관할읍면동명시공소재지위치시공사정보시행사정보민간공공구분명임대분양구분명규모별면적(㎥)총분양가구수(개)당월미분양가구수(개)분양청약일자입주예정일자준공여부구분명비고
0가평군<NA>가평읍경기도 가평군 읍내리 766-3(가평블루핀)㈜홍성건설대한토지신탁㈜민간분양84.04902024-082024-10준공<NA>
1고양시일산동구풍동경기도 고양시 일산동구 풍동 655-18번지 일원(요진 Y-HAUS)요진건설산업㈜요진개발㈜민간분양60.02402024-032024-04준공<NA>
2고양시일산동구풍동경기도 고양시 일산동구 풍동 655-18번지 일원(요진 Y-HAUS)요진건설산업㈜요진개발㈜민간분양39.97402024-032024-04준공<NA>
3고양시덕양구삼송동경기도 고양시 덕양구 삼송동 삼송택지개발지구 B-5블럭㈜대송㈜생보부동산신탁민간분양84.7420162024-062024-11준공<NA>
4고양시덕양구삼송동경기도 고양시 덕양구 삼송동 삼송택지개발지구 B-5블럭㈜대송㈜생보부동산신탁민간분양84.6320152024-062024-11준공<NA>
5고양시덕양구삼송동경기도 고양시 덕양구 삼송동 삼송택지개발지구 B-5블럭㈜대송㈜생보부동산신탁민간분양84.9640172024-062024-11준공<NA>
6고양시덕양구지축동경기도 고양시 덕양구 지축동 지축택지개발지구 B-2블록한림건설㈜한림건설㈜민간분양84.9733742024-092024-01준공<NA>
7고양시덕양구지축동경기도 고양시 덕양구 지축동 지축택지개발지구 B-2블록한림건설㈜한림건설㈜민간분양84.9833742024-092024-01준공<NA>
8고양시덕양구지축동경기도 고양시 덕양구 지축동 지축택지개발지구 B-2블록한림건설㈜한림건설㈜민간분양72.9521452024-092024-01준공<NA>
9고양시덕양구지축동경기도 고양시 덕양구 지축동 지축택지개발지구 B-2블록한림건설㈜한림건설㈜민간분양72.9421422024-092024-01준공<NA>
시군명관할군구명관할읍면동명시공소재지위치시공사정보시행사정보민간공공구분명임대분양구분명규모별면적(㎥)총분양가구수(개)당월미분양가구수(개)분양청약일자입주예정일자준공여부구분명비고
433화성시<NA>오산동경기도 화성시 오산동㈜DL이앤씨㈜DL이앤씨민간분양115.01202024-042024-12미준공<NA>
434화성시<NA>오산동경기도 화성시 오산동㈜DL이앤씨㈜DL이앤씨민간분양115.01202024-042024-12미준공<NA>
435화성시<NA>봉담읍경기도 화성시 동화지구a-2블록중흥토건㈜더뉴봉담㈜민간분양88.03602024-042024-12미준공<NA>
436화성시<NA>봉담읍경기도 화성시 동화지구a-2블록중흥토건㈜더뉴봉담㈜민간분양524.032702024-042024-12미준공<NA>
437화성시<NA>봉담읍경기도 화성시 동화지구a-2블록중흥토건㈜더뉴봉담㈜민간분양104.09102024-042024-12미준공<NA>
438화성시<NA>봉담읍경기도 화성시 동화지구a-2블록중흥토건㈜더뉴봉담㈜민간분양90.05102024-042024-12미준공<NA>
439화성시<NA>향남읍경기도 화성시 향남읍 상신지구 A1-1블럭(주)한양코리아신탁(주)민간분양61.06362024-052024-02미준공<NA>
440화성시<NA>향남읍경기도 화성시 향남읍 상신지구 A1-1블럭(주)한양코리아신탁(주)민간분양61.06362024-052024-02미준공<NA>
441화성시<NA>향남읍경기도 화성시 향남읍 상신지구 A1-1블럭(주)한양코리아신탁(주)민간분양84.01022024-052024-02미준공<NA>
442화성시<NA>향남읍경기도 화성시 향남읍 상신지구 A1-1블럭(주)한양코리아신탁(주)민간분양84.01252024-052024-02미준공<NA>

Duplicate rows

Most frequently occurring

시군명관할군구명관할읍면동명시공소재지위치시공사정보시행사정보민간공공구분명임대분양구분명규모별면적(㎥)총분양가구수(개)당월미분양가구수(개)분양청약일자입주예정일자준공여부구분명# duplicates
12양주시<NA>옥정동경기도 양주시 옥정동 옥정지구D-1BL㈜케이씨씨건설㈜하나자신탁민간분양84.0332024-112024-03미준공4
15용인시기흥구마북동경기도 용인시 기흥구 마북동 212-1동부건설㈜한국자산신탁㈜민간분양84.0112024-082024-10준공4
0김포시<NA>장기동경기도 김포시 김포한강신도시 Bc-04BL (김포시 장기동 1894-9)범양건영㈜온동네디엔아이㈜민간분양84.9602024-082024-06미준공2
1김포시<NA>장기동경기도 김포시 김포한강신도시 Bc-04BL (김포시 장기동 1894-9)범양건영㈜온동네디엔아이㈜민간분양84.9702024-082024-06미준공2
2부천시<NA>심곡본동경기도 부천시 심곡본동 776-2더원건설무궁화신탁민간분양59.02002024-082024-08준공2
3부천시<NA>심곡본동경기도 부천시 심곡본동 776-2더원건설무궁화신탁민간분양63.02002024-082024-08준공2
4부천시<NA>원종동경기도 부천시 원종동 316외 1필지 주상복합(도)도원종합건설도원주택건설민간분양70.024182024-032024-04준공2
5양주시<NA>옥정동경기도 양주시 옥정동 옥정지구B-10BL㈜현대건설㈜무궁화신탁민간분양84.02502024-052024-06미준공2
6양주시<NA>옥정동경기도 양주시 옥정동 옥정지구B-5BL㈜현대건설㈜무궁화신탁민간분양84.0502024-052024-06미준공2
7양주시<NA>옥정동경기도 양주시 옥정동 옥정지구B-5BL㈜현대건설㈜무궁화신탁민간분양84.020102024-052024-06미준공2