Overview

Dataset statistics

Number of variables13
Number of observations1843
Missing cells2218
Missing cells (%)9.3%
Duplicate rows16
Duplicate rows (%)0.9%
Total size in memory194.5 KiB
Average record size in memory108.1 B

Variable types

Categorical3
Text2
DateTime4
Numeric4

Dataset

Description경기주택도시공사 공급용지 입찰공고 및 개찰결과 현황
Author경기주택도시공사
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=MOBCXXOL6LVMVZTDHN6T31486690&infSeq=1

Alerts

Dataset has 16 (0.9%) duplicate rowsDuplicates
면적(제곱미터) is highly overall correlated with 공급예정가액(원) and 2 other fieldsHigh correlation
공급예정가액(원) is highly overall correlated with 면적(제곱미터) and 2 other fieldsHigh correlation
입찰금액(원) is highly overall correlated with 면적(제곱미터) and 3 other fieldsHigh correlation
낙찰률(퍼센트) is highly overall correlated with 입찰금액(원) and 1 other fieldsHigh correlation
사업지구명 is highly overall correlated with 공급방법High correlation
공급방법 is highly overall correlated with 낙찰률(퍼센트) and 2 other fieldsHigh correlation
토지용도 is highly overall correlated with 면적(제곱미터) and 3 other fieldsHigh correlation
사업지구명 is highly imbalanced (52.7%)Imbalance
공급방법 is highly imbalanced (96.8%)Imbalance
면적(제곱미터) has 38 (2.1%) missing valuesMissing
입찰금액(원) has 1081 (58.7%) missing valuesMissing
낙찰률(퍼센트) has 1087 (59.0%) missing valuesMissing

Reproduction

Analysis started2024-03-23 01:57:45.755077
Analysis finished2024-03-23 01:57:52.768968
Duration7.01 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업지구명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct30
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
화성동탄(2) 택지개발사업
907 
광교지구 택지개발사업
389 
남양주 다산진건주택지구
182 
고덕국제화계획지구
151 
남양주 다산지금 주택지구
 
87
Other values (25)
127 

Length

Max length24
Median length18
Mean length12.684753
Min length5

Unique

Unique15 ?
Unique (%)0.8%

Sample

1st row화성동탄(2) 택지개발사업
2nd row화성동탄(2) 택지개발사업
3rd row화성동탄(2) 택지개발사업
4th row화성동탄(2) 택지개발사업
5th row화성동탄(2) 택지개발사업

Common Values

ValueCountFrequency (%)
화성동탄(2) 택지개발사업 907
49.2%
광교지구 택지개발사업 389
21.1%
남양주 다산진건주택지구 182
 
9.9%
고덕국제화계획지구 151
 
8.2%
남양주 다산지금 주택지구 87
 
4.7%
고양관광문화단지(택지) 37
 
2.0%
연천BIX(은통산업단지) 조성사업 16
 
0.9%
광주역세권 도시개발사업 14
 
0.8%
남양주 다산진건지구 12
 
0.7%
판교제2테크노밸리 도시첨단산업단지 9
 
0.5%
Other values (20) 39
 
2.1%

Length

2024-03-23T01:57:53.061394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
택지개발사업 1319
36.6%
화성동탄(2 907
25.2%
광교지구 389
 
10.8%
남양주 291
 
8.1%
다산진건주택지구 182
 
5.0%
고덕국제화계획지구 151
 
4.2%
주택지구 95
 
2.6%
다산지금 87
 
2.4%
고양관광문화단지(택지 37
 
1.0%
광주역세권 20
 
0.6%
Other values (28) 127
 
3.5%
Distinct152
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
2024-03-23T01:57:53.460927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length36
Mean length29.673359
Min length14

Characters and Unicode

Total characters54688
Distinct characters150
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

Unique44 ?
Unique (%)2.4%

Sample

1st row화성동탄(2) 점포겸용 단독주택용지 공급 공고(일반실수요자)
2nd row화성동탄(2) 점포겸용 단독주택용지 공급 공고(일반실수요자)
3rd row화성동탄(2) 점포겸용 단독주택용지 공급 공고(일반실수요자)
4th row화성동탄(2) 점포겸용 단독주택용지 공급 공고(일반실수요자)
5th row화성동탄(2) 점포겸용 단독주택용지 공급 공고(일반실수요자)
ValueCountFrequency (%)
점포겸용 885
 
10.9%
화성동탄(2 879
 
10.8%
단독주택용지 863
 
10.6%
공급공고 489
 
6.0%
공급 476
 
5.9%
근린생활시설용지 314
 
3.9%
공고 305
 
3.8%
광교 266
 
3.3%
252
 
3.1%
재공급공고(d20,d21 211
 
2.6%
Other values (181) 3182
39.2%
2024-03-23T01:57:54.476390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6324
 
11.6%
3478
 
6.4%
2915
 
5.3%
2877
 
5.3%
( 1921
 
3.5%
) 1921
 
3.5%
1846
 
3.4%
2 1810
 
3.3%
1748
 
3.2%
1457
 
2.7%
Other values (140) 28391
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 38336
70.1%
Space Separator 6324
 
11.6%
Decimal Number 3622
 
6.6%
Open Punctuation 1956
 
3.6%
Close Punctuation 1956
 
3.6%
Other Punctuation 1398
 
2.6%
Uppercase Letter 998
 
1.8%
Dash Punctuation 76
 
0.1%
Math Symbol 22
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3478
 
9.1%
2915
 
7.6%
2877
 
7.5%
1846
 
4.8%
1748
 
4.6%
1457
 
3.8%
1213
 
3.2%
1149
 
3.0%
1100
 
2.9%
1012
 
2.6%
Other values (111) 19541
51.0%
Decimal Number
ValueCountFrequency (%)
2 1810
50.0%
1 588
 
16.2%
0 459
 
12.7%
7 349
 
9.6%
3 183
 
5.1%
4 84
 
2.3%
6 60
 
1.7%
5 58
 
1.6%
8 26
 
0.7%
9 5
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
D 856
85.8%
F 68
 
6.8%
C 23
 
2.3%
X 16
 
1.6%
I 16
 
1.6%
B 16
 
1.6%
A 2
 
0.2%
M 1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
, 1258
90.0%
/ 123
 
8.8%
. 12
 
0.9%
· 5
 
0.4%
Open Punctuation
ValueCountFrequency (%)
( 1921
98.2%
[ 35
 
1.8%
Close Punctuation
ValueCountFrequency (%)
) 1921
98.2%
] 35
 
1.8%
Space Separator
ValueCountFrequency (%)
6324
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 76
100.0%
Math Symbol
ValueCountFrequency (%)
~ 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 38336
70.1%
Common 15354
28.1%
Latin 998
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3478
 
9.1%
2915
 
7.6%
2877
 
7.5%
1846
 
4.8%
1748
 
4.6%
1457
 
3.8%
1213
 
3.2%
1149
 
3.0%
1100
 
2.9%
1012
 
2.6%
Other values (111) 19541
51.0%
Common
ValueCountFrequency (%)
6324
41.2%
( 1921
 
12.5%
) 1921
 
12.5%
2 1810
 
11.8%
, 1258
 
8.2%
1 588
 
3.8%
0 459
 
3.0%
7 349
 
2.3%
3 183
 
1.2%
/ 123
 
0.8%
Other values (11) 418
 
2.7%
Latin
ValueCountFrequency (%)
D 856
85.8%
F 68
 
6.8%
C 23
 
2.3%
X 16
 
1.6%
I 16
 
1.6%
B 16
 
1.6%
A 2
 
0.2%
M 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 38336
70.1%
ASCII 16347
29.9%
None 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6324
38.7%
( 1921
 
11.8%
) 1921
 
11.8%
2 1810
 
11.1%
, 1258
 
7.7%
D 856
 
5.2%
1 588
 
3.6%
0 459
 
2.8%
7 349
 
2.1%
3 183
 
1.1%
Other values (18) 678
 
4.1%
Hangul
ValueCountFrequency (%)
3478
 
9.1%
2915
 
7.6%
2877
 
7.5%
1846
 
4.8%
1748
 
4.6%
1457
 
3.8%
1213
 
3.2%
1149
 
3.0%
1100
 
2.9%
1012
 
2.6%
Other values (111) 19541
51.0%
None
ValueCountFrequency (%)
· 5
100.0%

공급방법
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
입찰
1837 
경쟁입찰
 
6

Length

Max length4
Median length2
Mean length2.0065111
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
입찰 1837
99.7%
경쟁입찰 6
 
0.3%

Length

2024-03-23T01:57:55.163688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T01:57:55.598419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
입찰 1837
99.7%
경쟁입찰 6
 
0.3%
Distinct122
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
Minimum2008-11-20 00:00:00
Maximum2024-02-22 00:00:00
2024-03-23T01:57:55.977603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:57:56.493960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct126
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
Minimum2008-12-05 00:00:00
Maximum2024-03-04 00:00:00
2024-03-23T01:57:56.971034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:57:57.457378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct127
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
Minimum2008-12-05 00:00:00
Maximum2024-03-04 00:00:00
2024-03-23T01:57:58.150736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:57:58.589102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct127
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
Minimum2008-12-17 00:00:00
Maximum2024-03-04 00:00:00
2024-03-23T01:57:58.961642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:57:59.477239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

토지용도
Categorical

HIGH CORRELATION 

Distinct40
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
단독주택
712 
근린생활시설
217 
단독주택용지(점포겸용)
153 
근린생활시설(일반)
133 
도시지원시설용지
121 
Other values (35)
507 

Length

Max length24
Median length13
Mean length6.1741725
Min length3

Unique

Unique10 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
단독주택 712
38.6%
근린생활시설 217
 
11.8%
단독주택용지(점포겸용) 153
 
8.3%
근린생활시설(일반) 133
 
7.2%
도시지원시설용지 121
 
6.6%
주차장 79
 
4.3%
근린상업용지 46
 
2.5%
근린생활시설용지 46
 
2.5%
상업용지 45
 
2.4%
업무시설용지 40
 
2.2%
Other values (30) 251
 
13.6%

Length

2024-03-23T01:57:59.856298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
단독주택 712
38.6%
근린생활시설 217
 
11.8%
단독주택용지(점포겸용 153
 
8.3%
근린생활시설(일반 133
 
7.2%
도시지원시설용지 121
 
6.6%
주차장 79
 
4.3%
근린상업용지 46
 
2.5%
근린생활시설용지 46
 
2.5%
상업용지 45
 
2.4%
업무시설용지 40
 
2.2%
Other values (29) 251
 
13.6%
Distinct1054
Distinct (%)57.2%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
2024-03-23T01:58:00.651952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length6.4856213
Min length2

Characters and Unicode

Total characters11953
Distinct characters65
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique621 ?
Unique (%)33.7%

Sample

1st row420-102
2nd row420-103
3rd row420-104
4th row420-105
5th row420-106
ValueCountFrequency (%)
f-3 43
 
2.2%
f-1 37
 
1.9%
f-2 18
 
0.9%
근생5 14
 
0.7%
근생71-3 7
 
0.4%
근생72-3 7
 
0.4%
근생71-5 7
 
0.4%
근생72-4 7
 
0.4%
근생71-4 7
 
0.4%
근생72-2 7
 
0.4%
Other values (1027) 1819
92.2%
2024-03-23T01:58:01.788306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 2075
17.4%
1 2014
16.8%
2 1418
11.9%
0 1254
10.5%
4 1167
9.8%
3 610
 
5.1%
7 405
 
3.4%
5 396
 
3.3%
375
 
3.1%
337
 
2.8%
Other values (55) 1902
15.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7949
66.5%
Dash Punctuation 2075
 
17.4%
Other Letter 1518
 
12.7%
Uppercase Letter 190
 
1.6%
Space Separator 130
 
1.1%
Other Number 63
 
0.5%
Close Punctuation 11
 
0.1%
Open Punctuation 11
 
0.1%
Lowercase Letter 5
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
375
24.7%
337
22.2%
144
 
9.5%
141
 
9.3%
121
 
8.0%
121
 
8.0%
78
 
5.1%
68
 
4.5%
27
 
1.8%
19
 
1.3%
Other values (22) 87
 
5.7%
Decimal Number
ValueCountFrequency (%)
1 2014
25.3%
2 1418
17.8%
0 1254
15.8%
4 1167
14.7%
3 610
 
7.7%
7 405
 
5.1%
5 396
 
5.0%
6 276
 
3.5%
8 211
 
2.7%
9 198
 
2.5%
Uppercase Letter
ValueCountFrequency (%)
F 114
60.0%
C 22
 
11.6%
R 18
 
9.5%
D 11
 
5.8%
A 8
 
4.2%
M 5
 
2.6%
H 5
 
2.6%
O 4
 
2.1%
B 3
 
1.6%
Other Number
ValueCountFrequency (%)
24
38.1%
11
17.5%
9
 
14.3%
6
 
9.5%
4
 
6.3%
4
 
6.3%
3
 
4.8%
2
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 2075
100.0%
Space Separator
ValueCountFrequency (%)
130
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Lowercase Letter
ValueCountFrequency (%)
d 5
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10240
85.7%
Hangul 1518
 
12.7%
Latin 195
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
375
24.7%
337
22.2%
144
 
9.5%
141
 
9.3%
121
 
8.0%
121
 
8.0%
78
 
5.1%
68
 
4.5%
27
 
1.8%
19
 
1.3%
Other values (22) 87
 
5.7%
Common
ValueCountFrequency (%)
- 2075
20.3%
1 2014
19.7%
2 1418
13.8%
0 1254
12.2%
4 1167
11.4%
3 610
 
6.0%
7 405
 
4.0%
5 396
 
3.9%
6 276
 
2.7%
8 211
 
2.1%
Other values (13) 414
 
4.0%
Latin
ValueCountFrequency (%)
F 114
58.5%
C 22
 
11.3%
R 18
 
9.2%
D 11
 
5.6%
A 8
 
4.1%
M 5
 
2.6%
H 5
 
2.6%
d 5
 
2.6%
O 4
 
2.1%
B 3
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10372
86.8%
Hangul 1518
 
12.7%
Enclosed Alphanum 63
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 2075
20.0%
1 2014
19.4%
2 1418
13.7%
0 1254
12.1%
4 1167
11.3%
3 610
 
5.9%
7 405
 
3.9%
5 396
 
3.8%
6 276
 
2.7%
8 211
 
2.0%
Other values (15) 546
 
5.3%
Hangul
ValueCountFrequency (%)
375
24.7%
337
22.2%
144
 
9.5%
141
 
9.3%
121
 
8.0%
121
 
8.0%
78
 
5.1%
68
 
4.5%
27
 
1.8%
19
 
1.3%
Other values (22) 87
 
5.7%
Enclosed Alphanum
ValueCountFrequency (%)
24
38.1%
11
17.5%
9
 
14.3%
6
 
9.5%
4
 
6.3%
4
 
6.3%
3
 
4.8%
2
 
3.2%

면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct635
Distinct (%)35.2%
Missing38
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean2057.2606
Minimum164.5
Maximum89283
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.3 KiB
2024-03-23T01:58:02.208809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum164.5
5-th percentile205
Q1253
median573
Q31077
95-th percentile8084.7
Maximum89283
Range89118.5
Interquartile range (IQR)824

Descriptive statistics

Standard deviation6703.7867
Coefficient of variation (CV)3.2585987
Kurtosis65.34651
Mean2057.2606
Median Absolute Deviation (MAD)333.3
Skewness7.4164678
Sum3713355.4
Variance44940757
MonotonicityNot monotonic
2024-03-23T01:58:02.714862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
232.0 39
 
2.1%
247.0 31
 
1.7%
262.0 28
 
1.5%
267.0 26
 
1.4%
234.0 24
 
1.3%
265.1 24
 
1.3%
266.0 22
 
1.2%
265.0 17
 
0.9%
264.0 16
 
0.9%
861.0 16
 
0.9%
Other values (625) 1562
84.8%
(Missing) 38
 
2.1%
ValueCountFrequency (%)
164.5 3
0.2%
164.6 2
 
0.1%
164.8 1
 
0.1%
165.0 1
 
0.1%
170.0 1
 
0.1%
171.0 1
 
0.1%
176.0 3
0.2%
180.0 4
0.2%
181.0 5
0.3%
186.0 6
0.3%
ValueCountFrequency (%)
89283.0 1
 
0.1%
84479.0 1
 
0.1%
77722.0 1
 
0.1%
60175.4 1
 
0.1%
59228.0 3
0.2%
50957.3 6
0.3%
50266.7 1
 
0.1%
46561.9 2
 
0.1%
41130.2 4
0.2%
38570.0 4
0.2%

공급예정가액(원)
Real number (ℝ)

HIGH CORRELATION 

Distinct808
Distinct (%)44.1%
Missing12
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean7.0007442 × 109
Minimum1.34366 × 108
Maximum5.64 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.3 KiB
2024-03-23T01:58:03.172697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.34366 × 108
5-th percentile5.19507 × 108
Q16.46259 × 108
median8.8088 × 108
Q34 × 109
95-th percentile1.7645067 × 1010
Maximum5.64 × 1011
Range5.6386563 × 1011
Interquartile range (IQR)3.353741 × 109

Descriptive statistics

Standard deviation2.9217233 × 1010
Coefficient of variation (CV)4.1734467
Kurtosis124.3768
Mean7.0007442 × 109
Median Absolute Deviation (MAD)4.01484 × 108
Skewness9.8248394
Sum1.2818363 × 1013
Variance8.536467 × 1020
MonotonicityNot monotonic
2024-03-23T01:58:03.967867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
700000000 134
 
7.3%
3000000000 78
 
4.2%
600000000 59
 
3.2%
4000000000 43
 
2.3%
800000000 42
 
2.3%
5000000000 31
 
1.7%
10000000000 22
 
1.2%
6000000000 18
 
1.0%
680636000 16
 
0.9%
7000000000 13
 
0.7%
Other values (798) 1375
74.6%
(Missing) 12
 
0.7%
ValueCountFrequency (%)
134366000 1
0.1%
299466000 1
0.1%
312144000 2
0.1%
312800000 1
0.1%
323000000 1
0.1%
323469000 1
0.1%
326136000 1
0.1%
329565000 1
0.1%
334443000 2
0.1%
334935000 1
0.1%
ValueCountFrequency (%)
564000000000 1
 
0.1%
409000000000 1
 
0.1%
279000000000 3
0.2%
257000000000 3
0.2%
242000000000 2
0.1%
203000000000 2
0.1%
196000000000 4
0.2%
171000000000 2
0.1%
157000000000 2
0.1%
145000000000 3
0.2%

입찰금액(원)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct598
Distinct (%)78.5%
Missing1081
Missing (%)58.7%
Infinite0
Infinite (%)0.0%
Mean7.9695878 × 109
Minimum88000000
Maximum7.51 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.3 KiB
2024-03-23T01:58:04.740983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum88000000
5-th percentile6 × 108
Q17.5 × 108
median1.0593 × 109
Q37 × 109
95-th percentile2.215885 × 1010
Maximum7.51 × 1011
Range7.50912 × 1011
Interquartile range (IQR)6.25 × 109

Descriptive statistics

Standard deviation3.2566874 × 1010
Coefficient of variation (CV)4.0863937
Kurtosis363.25036
Mean7.9695878 × 109
Median Absolute Deviation (MAD)5.120475 × 108
Skewness16.935764
Sum6.0728259 × 1012
Variance1.0606013 × 1021
MonotonicityNot monotonic
2024-03-23T01:58:05.403315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10000000000 31
 
1.7%
20000000000 18
 
1.0%
8000000000 15
 
0.8%
7000000000 11
 
0.6%
4000000000 10
 
0.5%
9000000000 8
 
0.4%
1000000000 7
 
0.4%
2000000000 6
 
0.3%
5000000000 6
 
0.3%
800000000 5
 
0.3%
Other values (588) 645
35.0%
(Missing) 1081
58.7%
ValueCountFrequency (%)
88000000 1
0.1%
352000000 1
0.1%
496900000 1
0.1%
502400000 1
0.1%
510900000 1
0.1%
515190000 1
0.1%
515500000 1
0.1%
519900000 1
0.1%
521100000 1
0.1%
524000000 1
0.1%
ValueCountFrequency (%)
751000000000 1
0.1%
257000000000 1
0.1%
171000000000 1
0.1%
168000000000 1
0.1%
145000000000 1
0.1%
142000000000 1
0.1%
114000000000 1
0.1%
96879582000 1
0.1%
80000000000 1
0.1%
78142770000 1
0.1%

낙찰률(퍼센트)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct166
Distinct (%)22.0%
Missing1087
Missing (%)59.0%
Infinite0
Infinite (%)0.0%
Mean143.17447
Minimum11
Maximum520
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.3 KiB
2024-03-23T01:58:05.991741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile100
Q1108
median121
Q3151.25
95-th percentile258.25
Maximum520
Range509
Interquartile range (IQR)43.25

Descriptive statistics

Standard deviation55.987215
Coefficient of variation (CV)0.39104188
Kurtosis6.0917147
Mean143.17447
Median Absolute Deviation (MAD)16
Skewness2.1707589
Sum108239.9
Variance3134.5682
MonotonicityNot monotonic
2024-03-23T01:58:06.677125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100.0 52
 
2.8%
120.0 29
 
1.6%
110.0 25
 
1.4%
106.0 24
 
1.3%
105.0 24
 
1.3%
113.0 23
 
1.2%
103.0 21
 
1.1%
128.0 20
 
1.1%
101.0 17
 
0.9%
108.0 17
 
0.9%
Other values (156) 504
27.3%
(Missing) 1087
59.0%
ValueCountFrequency (%)
11.0 1
 
0.1%
100.0 52
2.8%
100.1 1
 
0.1%
100.2 1
 
0.1%
100.6 1
 
0.1%
101.0 17
 
0.9%
102.0 13
 
0.7%
103.0 21
1.1%
104.0 10
 
0.5%
105.0 24
1.3%
ValueCountFrequency (%)
520.0 1
0.1%
464.0 1
0.1%
407.0 1
0.1%
360.0 1
0.1%
356.0 1
0.1%
355.0 1
0.1%
354.0 1
0.1%
351.0 1
0.1%
346.0 1
0.1%
340.0 1
0.1%

Interactions

2024-03-23T01:57:50.294900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:57:46.942055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:57:47.994740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:57:49.154095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:57:50.557283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:57:47.181759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:57:48.285580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:57:49.417141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:57:50.858024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:57:47.434037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:57:48.556697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:57:49.696151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:57:51.142144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:57:47.725267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:57:48.884529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:57:49.999778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T01:58:06.974289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업지구명공급방법토지용도면적(제곱미터)공급예정가액(원)입찰금액(원)낙찰률(퍼센트)
사업지구명1.0000.7850.9180.2830.0140.0000.504
공급방법0.7851.0000.9120.0000.0000.000NaN
토지용도0.9180.9121.0000.9190.9030.8980.780
면적(제곱미터)0.2830.0000.9191.0000.9370.8600.000
공급예정가액(원)0.0140.0000.9030.9371.0000.9110.000
입찰금액(원)0.0000.0000.8980.8600.9111.0000.047
낙찰률(퍼센트)0.504NaN0.7800.0000.0000.0471.000
2024-03-23T01:58:07.286680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공급방법사업지구명토지용도
공급방법1.0000.6410.779
사업지구명0.6411.0000.432
토지용도0.7790.4321.000
2024-03-23T01:58:07.641501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
면적(제곱미터)공급예정가액(원)입찰금액(원)낙찰률(퍼센트)사업지구명공급방법토지용도
면적(제곱미터)1.0000.9330.9020.2700.1010.0000.646
공급예정가액(원)0.9331.0000.9430.3130.0060.0000.648
입찰금액(원)0.9020.9431.0000.5420.0000.0000.687
낙찰률(퍼센트)0.2700.3130.5421.0000.2181.0000.410
사업지구명0.1010.0060.0000.2181.0000.6410.432
공급방법0.0000.0000.0001.0000.6411.0000.779
토지용도0.6460.6480.6870.4100.4320.7791.000

Missing values

2024-03-23T01:57:51.529302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T01:57:52.185458image/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.
2024-03-23T01:57:52.582797image/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

사업지구명공고명공급방법모집공고일공고접수시작일공고접수종료일개찰일자토지용도가지번면적(제곱미터)공급예정가액(원)입찰금액(원)낙찰률(퍼센트)
0화성동탄(2) 택지개발사업화성동탄(2) 점포겸용 단독주택용지 공급 공고(일반실수요자)입찰2018-10-052018-10-222018-10-252018-10-26단독주택420-102258.0664453000850606000128.0
1화성동탄(2) 택지개발사업화성동탄(2) 점포겸용 단독주택용지 공급 공고(일반실수요자)입찰2018-10-052018-10-222018-10-252018-10-26단독주택420-103261.0672179000860497000128.0
2화성동탄(2) 택지개발사업화성동탄(2) 점포겸용 단독주택용지 공급 공고(일반실수요자)입찰2018-10-052018-10-222018-10-252018-10-26단독주택420-104261.0672179000900000000134.0
3화성동탄(2) 택지개발사업화성동탄(2) 점포겸용 단독주택용지 공급 공고(일반실수요자)입찰2018-10-052018-10-222018-10-252018-10-26단독주택420-105261.06721790001000000000149.0
4화성동탄(2) 택지개발사업화성동탄(2) 점포겸용 단독주택용지 공급 공고(일반실수요자)입찰2018-10-052018-10-222018-10-252018-10-26단독주택420-106241.0639228000817756000128.0
5화성동탄(2) 택지개발사업화성동탄(2) 점포겸용 단독주택용지 공급 공고(일반실수요자)입찰2018-10-052018-10-222018-10-252018-10-26단독주택420-201238.0631271000812190000129.0
6화성동탄(2) 택지개발사업화성동탄(2) 점포겸용 단독주택용지 공급 공고(일반실수요자)입찰2018-10-052018-10-222018-10-252018-10-26단독주택420-202252.0640584000820069000128.0
7화성동탄(2) 택지개발사업화성동탄(2) 점포겸용 단독주택용지 공급 공고(일반실수요자)입찰2018-10-052018-10-222018-10-252018-10-26단독주택420-203253.0643126000823323000128.0
8화성동탄(2) 택지개발사업화성동탄(2) 점포겸용 단독주택용지 공급 공고(일반실수요자)입찰2018-10-052018-10-222018-10-252018-10-26단독주택420-204260.0660920000846103000128.0
9화성동탄(2) 택지개발사업화성동탄(2) 점포겸용 단독주택용지 공급 공고(일반실수요자)입찰2018-10-052018-10-222018-10-252018-10-26단독주택420-205276.0701592000898171000128.0
사업지구명공고명공급방법모집공고일공고접수시작일공고접수종료일개찰일자토지용도가지번면적(제곱미터)공급예정가액(원)입찰금액(원)낙찰률(퍼센트)
1833화성동탄(2) 택지개발사업화성동탄(2) 점포겸용 단독주택용지 재공급공고(D20,D21)입찰2021-02-252021-03-102021-03-102021-03-10단독주택420-307275.0714890000750000000105.0
1834화성동탄(2) 택지개발사업화성동탄(2) 점포겸용 단독주택용지 재공급공고(D20,D21)입찰2021-02-252021-03-102021-03-102021-03-10단독주택420-308278.0708678000<NA><NA>
1835화성동탄(2) 택지개발사업화성동탄(2) 점포겸용 단독주택용지 재공급공고(D20,D21)입찰2021-02-252021-03-102021-03-102021-03-10단독주택420-309274.0698481000<NA><NA>
1836화성동탄(2) 택지개발사업화성동탄(2) 점포겸용 단독주택용지 재공급공고(D20,D21)입찰2021-02-252021-03-102021-03-102021-03-10단독주택420-310270.0688284000<NA><NA>
1837화성동탄(2) 택지개발사업화성동탄(2) 점포겸용 단독주택용지 재공급공고(D20,D21)입찰2021-02-252021-03-102021-03-102021-03-10단독주택420-312256.0692378000900000000130.0
1838화성동탄(2) 택지개발사업화성동탄(2) 점포겸용 단독주택용지 재공급공고(D20,D21)입찰2021-02-252021-03-102021-03-102021-03-10단독주택420-401255.06829920001011000000148.0
1839화성동탄(2) 택지개발사업화성동탄(2) 점포겸용 단독주택용지 재공급공고(D20,D21)입찰2021-02-252021-03-102021-03-102021-03-10단독주택420-402261.0658816000681110000103.0
1840화성동탄(2) 택지개발사업화성동탄(2) 점포겸용 단독주택용지 재공급공고(D20,D21)입찰2021-02-252021-03-102021-03-102021-03-10단독주택420-403262.0661340000682000000103.0
1841화성동탄(2) 택지개발사업화성동탄(2) 점포겸용 단독주택용지 재공급공고(D20,D21)입찰2021-02-252021-03-102021-03-102021-03-10단독주택420-404262.0661340000<NA><NA>
1842화성동탄(2) 택지개발사업화성동탄(2) 점포겸용 단독주택용지 재공급공고(D20,D21)입찰2021-02-252021-03-102021-03-102021-03-10단독주택420-405262.0661340000<NA><NA>

Duplicate rows

Most frequently occurring

사업지구명공고명공급방법모집공고일공고접수시작일공고접수종료일개찰일자토지용도가지번면적(제곱미터)공급예정가액(원)입찰금액(원)낙찰률(퍼센트)# duplicates
0고덕국제화계획지구고덕국제화계획지구 업무시설용지 공급 공고입찰2023-09-182023-10-112023-10-112023-10-11업무시설용지업무1-1-51822.011500000000<NA><NA>2
1광교지구 택지개발사업광교 도시지원시설용지(도시17블록) 공급공고입찰2015-01-092015-01-232015-01-232015-01-23도시지원시설용지도시1721380.044846670000<NA><NA>2
2광교지구 택지개발사업광교 업무복합(D3) 및 도시지원시설용지(도시8~10)블록 공급안내입찰2014-02-172014-02-272014-02-272014-02-27업무복합용지D350957.3257000000000<NA><NA>2
3광교지구 택지개발사업광교 업무복합,공동주택,업무시설,도시지원시설,근린생활시설,주차장,단독주택,종교,문화복지시설용지 공급공고입찰2011-06-242011-07-042011-07-042011-07-04업무시설업무2-3-1869.031631600004475700000141.02
4광교지구 택지개발사업광교 업무복합,공동주택,중심상업,의료시설용지 공급공고입찰2011-10-272011-11-102011-11-112011-11-11업무복합용지D350957.3279000000000<NA><NA>2
5광교지구 택지개발사업광교지구 유치원 및 근생용지 신규공급 및 수의계약 대상부지 공급 안내입찰2012-04-132012-04-232012-04-232012-04-23도시지원시설용지도시14-115237.022855500000<NA><NA>2
6광교지구 택지개발사업광교지구 유치원 및 근생용지 신규공급 및 수의계약 대상부지 공급 안내입찰2012-04-132012-04-232012-04-232012-04-23도시지원시설용지도시14-2-17967.513732500000<NA><NA>2
7광교지구 택지개발사업광교지구 유치원 및 근생용지 신규공급 및 수의계약 대상부지 공급 안내입찰2012-04-132012-04-232012-04-232012-04-23도시지원시설용지도시14-2-26209.010058580000<NA><NA>2
8광교지구 택지개발사업광교지구 유치원 및 근생용지 신규공급 및 수의계약 대상부지 공급 안내입찰2012-04-132012-04-232012-04-232012-04-23도시지원시설용지도시14-2-35962.79776700000<NA><NA>2
9광교지구 택지개발사업광교지구 유치원 및 근생용지 신규공급 및 수의계약 대상부지 공급 안내입찰2012-04-132012-04-232012-04-232012-04-23도시지원시설용지도시14-3-13599.05686420000<NA><NA>2