Overview

Dataset statistics

Number of variables11
Number of observations676
Missing cells125
Missing cells (%)1.7%
Duplicate rows1
Duplicate rows (%)0.1%
Total size in memory58.9 KiB
Average record size in memory89.2 B

Variable types

Numeric1
Text4
DateTime4
Boolean1
Categorical1

Dataset

Description경기주택도시공사 토지분양시스템의 청약홈페이지에 공고되는 분양공고정보로써 공고명, 모집공고일, 접수시작일, 접수마감일 등의 정보를 포함하고 있습니다.
URLhttps://www.data.go.kr/data/15119759/fileData.do

Alerts

기타유의사항 has constant value ""Constant
Dataset has 1 (0.1%) duplicate rowsDuplicates
수정일시 has 124 (18.3%) missing valuesMissing

Reproduction

Analysis started2023-12-12 19:10:26.152621
Analysis finished2023-12-12 19:10:27.143058
Duration0.99 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

공고일련번호
Real number (ℝ)

Distinct629
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean651.79142
Minimum301
Maximum1067
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.1 KiB
2023-12-13T04:10:27.230409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum301
5-th percentile331.5
Q1446.75
median615.5
Q3852.25
95-th percentile1030.25
Maximum1067
Range766
Interquartile range (IQR)405.5

Descriptive statistics

Standard deviation230.81312
Coefficient of variation (CV)0.35412114
Kurtosis-1.229111
Mean651.79142
Median Absolute Deviation (MAD)199
Skewness0.24266534
Sum440611
Variance53274.696
MonotonicityIncreasing
2023-12-13T04:10:27.406877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
555 2
 
0.3%
396 2
 
0.3%
618 2
 
0.3%
617 2
 
0.3%
339 2
 
0.3%
615 2
 
0.3%
393 2
 
0.3%
344 2
 
0.3%
345 2
 
0.3%
390 2
 
0.3%
Other values (619) 656
97.0%
ValueCountFrequency (%)
301 1
0.1%
302 2
0.3%
303 2
0.3%
304 1
0.1%
306 2
0.3%
307 1
0.1%
308 1
0.1%
309 1
0.1%
310 1
0.1%
311 2
0.3%
ValueCountFrequency (%)
1067 1
0.1%
1066 1
0.1%
1065 1
0.1%
1064 1
0.1%
1063 1
0.1%
1062 1
0.1%
1061 1
0.1%
1060 1
0.1%
1059 1
0.1%
1058 1
0.1%
Distinct559
Distinct (%)82.7%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
2023-12-13T04:10:27.716329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length49
Mean length28.961538
Min length12

Characters and Unicode

Total characters19578
Distinct characters293
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique464 ?
Unique (%)68.6%

Sample

1st row오산가장 산업단지 생산시설용지 분양공고
2nd row오산가장 산업단지 생산시설용지 분양공고
3rd row광교신도시 공동주택용지 공급공고
4th row광교신도시 공동주택용지 공급공고
5th row광교신도시 공동주택용지 공급공고
ValueCountFrequency (%)
공급공고 211
 
6.4%
공고 157
 
4.8%
수의계약 110
 
3.3%
광교 88
 
2.7%
공급 84
 
2.5%
78
 
2.4%
주차장용지 71
 
2.2%
70
 
2.1%
화성동탄(2 64
 
1.9%
단독주택용지 48
 
1.5%
Other values (671) 2316
70.2%
2023-12-13T04:10:28.153546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2621
 
13.4%
1266
 
6.5%
1251
 
6.4%
652
 
3.3%
614
 
3.1%
515
 
2.6%
494
 
2.5%
478
 
2.4%
385
 
2.0%
) 375
 
1.9%
Other values (283) 10927
55.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14849
75.8%
Space Separator 2621
 
13.4%
Decimal Number 609
 
3.1%
Close Punctuation 417
 
2.1%
Open Punctuation 417
 
2.1%
Other Punctuation 367
 
1.9%
Uppercase Letter 262
 
1.3%
Dash Punctuation 23
 
0.1%
Lowercase Letter 11
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1266
 
8.5%
1251
 
8.4%
652
 
4.4%
614
 
4.1%
515
 
3.5%
494
 
3.3%
478
 
3.2%
385
 
2.6%
309
 
2.1%
307
 
2.1%
Other values (240) 8578
57.8%
Decimal Number
ValueCountFrequency (%)
2 196
32.2%
1 104
17.1%
3 62
 
10.2%
0 51
 
8.4%
4 48
 
7.9%
7 47
 
7.7%
5 43
 
7.1%
6 24
 
3.9%
8 19
 
3.1%
9 15
 
2.5%
Uppercase Letter
ValueCountFrequency (%)
B 74
28.2%
I 44
16.8%
X 44
16.8%
D 37
14.1%
A 31
11.8%
C 17
 
6.5%
L 8
 
3.1%
F 4
 
1.5%
S 2
 
0.8%
M 1
 
0.4%
Other Punctuation
ValueCountFrequency (%)
, 250
68.1%
/ 40
 
10.9%
. 38
 
10.4%
· 29
 
7.9%
& 6
 
1.6%
' 2
 
0.5%
: 2
 
0.5%
Close Punctuation
ValueCountFrequency (%)
) 375
89.9%
21
 
5.0%
] 20
 
4.8%
1
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 375
89.9%
21
 
5.0%
[ 20
 
4.8%
1
 
0.2%
Lowercase Letter
ValueCountFrequency (%)
e 6
54.5%
d 3
27.3%
l 1
 
9.1%
b 1
 
9.1%
Space Separator
ValueCountFrequency (%)
2621
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14849
75.8%
Common 4456
 
22.8%
Latin 273
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1266
 
8.5%
1251
 
8.4%
652
 
4.4%
614
 
4.1%
515
 
3.5%
494
 
3.3%
478
 
3.2%
385
 
2.6%
309
 
2.1%
307
 
2.1%
Other values (240) 8578
57.8%
Common
ValueCountFrequency (%)
2621
58.8%
) 375
 
8.4%
( 375
 
8.4%
, 250
 
5.6%
2 196
 
4.4%
1 104
 
2.3%
3 62
 
1.4%
0 51
 
1.1%
4 48
 
1.1%
7 47
 
1.1%
Other values (19) 327
 
7.3%
Latin
ValueCountFrequency (%)
B 74
27.1%
I 44
16.1%
X 44
16.1%
D 37
13.6%
A 31
11.4%
C 17
 
6.2%
L 8
 
2.9%
e 6
 
2.2%
F 4
 
1.5%
d 3
 
1.1%
Other values (4) 5
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14846
75.8%
ASCII 4656
 
23.8%
None 73
 
0.4%
Compat Jamo 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2621
56.3%
) 375
 
8.1%
( 375
 
8.1%
, 250
 
5.4%
2 196
 
4.2%
1 104
 
2.2%
B 74
 
1.6%
3 62
 
1.3%
0 51
 
1.1%
4 48
 
1.0%
Other values (28) 500
 
10.7%
Hangul
ValueCountFrequency (%)
1266
 
8.5%
1251
 
8.4%
652
 
4.4%
614
 
4.1%
515
 
3.5%
494
 
3.3%
478
 
3.2%
385
 
2.6%
309
 
2.1%
307
 
2.1%
Other values (239) 8575
57.8%
None
ValueCountFrequency (%)
· 29
39.7%
21
28.8%
21
28.8%
1
 
1.4%
1
 
1.4%
Compat Jamo
ValueCountFrequency (%)
3
100.0%
Distinct453
Distinct (%)67.0%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
Minimum2007-07-06 00:00:00
Maximum2023-08-22 00:00:00
2023-12-13T04:10:28.300098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:10:28.453966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct470
Distinct (%)69.5%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
Minimum2007-07-07 00:00:00
Maximum2023-09-05 00:00:00
2023-12-13T04:10:28.626988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:10:28.831394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct458
Distinct (%)67.9%
Missing1
Missing (%)0.1%
Memory size5.4 KiB
2023-12-13T04:10:29.182387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters6750
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique336 ?
Unique (%)49.8%

Sample

1st row2007-08-23
2nd row2007-07-07
3rd row2007-10-25
4th row2007-10-25
5th row2007-10-25
ValueCountFrequency (%)
2023-07-17 12
 
1.8%
2021-03-28 9
 
1.3%
2023-07-19 8
 
1.2%
2022-10-07 7
 
1.0%
2013-05-29 6
 
0.9%
2010-09-10 6
 
0.9%
2023-06-14 6
 
0.9%
2009-09-29 5
 
0.7%
2010-06-30 5
 
0.7%
2023-06-30 4
 
0.6%
Other values (448) 607
89.9%
2023-12-13T04:10:29.711684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1531
22.7%
2 1416
21.0%
- 1350
20.0%
1 1163
17.2%
3 307
 
4.5%
9 219
 
3.2%
7 195
 
2.9%
6 152
 
2.3%
4 150
 
2.2%
5 138
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5400
80.0%
Dash Punctuation 1350
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1531
28.4%
2 1416
26.2%
1 1163
21.5%
3 307
 
5.7%
9 219
 
4.1%
7 195
 
3.6%
6 152
 
2.8%
4 150
 
2.8%
5 138
 
2.6%
8 129
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 1350
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6750
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1531
22.7%
2 1416
21.0%
- 1350
20.0%
1 1163
17.2%
3 307
 
4.5%
9 219
 
3.2%
7 195
 
2.9%
6 152
 
2.3%
4 150
 
2.2%
5 138
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6750
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1531
22.7%
2 1416
21.0%
- 1350
20.0%
1 1163
17.2%
3 307
 
4.5%
9 219
 
3.2%
7 195
 
2.9%
6 152
 
2.3%
4 150
 
2.2%
5 138
 
2.0%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size808.0 B
True
582 
False
94 
ValueCountFrequency (%)
True 582
86.1%
False 94
 
13.9%
2023-12-13T04:10:29.857884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Distinct466
Distinct (%)68.9%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
2023-12-13T04:10:30.145211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length43
Mean length21.016272
Min length5

Characters and Unicode

Total characters14207
Distinct characters282
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique391 ?
Unique (%)57.8%

Sample

1st row공급공고[1].htm
2nd row_공고.htm
3rd row_공고.htm
4th row게시공고문[1].htm
5th row정정공고문.htm
ValueCountFrequency (%)
공고문.htm 66
 
4.1%
수의계약 36
 
2.2%
참조.htm 31
 
1.9%
화성동탄.htm 31
 
1.9%
공급공고문 27
 
1.7%
1 24
 
1.5%
공급공고문.htm 22
 
1.4%
단독주택용지 19
 
1.2%
공급 17
 
1.1%
단지내상가 17
 
1.1%
Other values (717) 1320
82.0%
2023-12-13T04:10:30.654849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
934
 
6.6%
854
 
6.0%
. 826
 
5.8%
m 687
 
4.8%
h 682
 
4.8%
t 680
 
4.8%
591
 
4.2%
1 543
 
3.8%
0 457
 
3.2%
438
 
3.1%
Other values (272) 7515
52.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7298
51.4%
Lowercase Letter 2110
 
14.9%
Decimal Number 1801
 
12.7%
Space Separator 934
 
6.6%
Other Punctuation 874
 
6.2%
Open Punctuation 382
 
2.7%
Close Punctuation 380
 
2.7%
Connector Punctuation 199
 
1.4%
Uppercase Letter 141
 
1.0%
Dash Punctuation 82
 
0.6%
Other values (2) 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
854
 
11.7%
591
 
8.1%
438
 
6.0%
344
 
4.7%
246
 
3.4%
175
 
2.4%
129
 
1.8%
125
 
1.7%
125
 
1.7%
121
 
1.7%
Other values (218) 4150
56.9%
Lowercase Letter
ValueCountFrequency (%)
m 687
32.6%
h 682
32.3%
t 680
32.2%
l 12
 
0.6%
o 9
 
0.4%
p 7
 
0.3%
i 6
 
0.3%
j 5
 
0.2%
g 4
 
0.2%
v 3
 
0.1%
Other values (7) 15
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
B 41
29.1%
A 23
16.3%
X 22
15.6%
I 22
15.6%
C 8
 
5.7%
L 5
 
3.5%
D 4
 
2.8%
T 4
 
2.8%
M 4
 
2.8%
H 4
 
2.8%
Other values (2) 4
 
2.8%
Decimal Number
ValueCountFrequency (%)
1 543
30.1%
0 457
25.4%
2 340
18.9%
4 94
 
5.2%
3 91
 
5.1%
9 66
 
3.7%
8 63
 
3.5%
5 57
 
3.2%
7 49
 
2.7%
6 41
 
2.3%
Other Punctuation
ValueCountFrequency (%)
. 826
94.5%
, 40
 
4.6%
& 7
 
0.8%
' 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 342
89.5%
[ 40
 
10.5%
Close Punctuation
ValueCountFrequency (%)
) 340
89.5%
] 40
 
10.5%
Math Symbol
ValueCountFrequency (%)
+ 3
75.0%
~ 1
 
25.0%
Other Symbol
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
934
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 199
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 82
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7298
51.4%
Common 4658
32.8%
Latin 2251
 
15.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
854
 
11.7%
591
 
8.1%
438
 
6.0%
344
 
4.7%
246
 
3.4%
175
 
2.4%
129
 
1.8%
125
 
1.7%
125
 
1.7%
121
 
1.7%
Other values (218) 4150
56.9%
Latin
ValueCountFrequency (%)
m 687
30.5%
h 682
30.3%
t 680
30.2%
B 41
 
1.8%
A 23
 
1.0%
X 22
 
1.0%
I 22
 
1.0%
l 12
 
0.5%
o 9
 
0.4%
C 8
 
0.4%
Other values (19) 65
 
2.9%
Common
ValueCountFrequency (%)
934
20.1%
. 826
17.7%
1 543
11.7%
0 457
9.8%
( 342
 
7.3%
) 340
 
7.3%
2 340
 
7.3%
_ 199
 
4.3%
4 94
 
2.0%
3 91
 
2.0%
Other values (15) 492
10.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7297
51.4%
ASCII 6907
48.6%
Geometric Shapes 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
934
13.5%
. 826
12.0%
m 687
9.9%
h 682
9.9%
t 680
9.8%
1 543
7.9%
0 457
6.6%
( 342
 
5.0%
) 340
 
4.9%
2 340
 
4.9%
Other values (42) 1076
15.6%
Hangul
ValueCountFrequency (%)
854
 
11.7%
591
 
8.1%
438
 
6.0%
344
 
4.7%
246
 
3.4%
175
 
2.4%
129
 
1.8%
125
 
1.7%
125
 
1.7%
121
 
1.7%
Other values (217) 4149
56.9%
Geometric Shapes
ValueCountFrequency (%)
1
50.0%
1
50.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%
Distinct659
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
2023-12-13T04:10:30.954599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length25
Mean length25.007396
Min length25

Characters and Unicode

Total characters16905
Distinct characters26
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique642 ?
Unique (%)95.0%

Sample

1st rowdev_user_200709041557471.jsp
2nd row00425_200710081727171.jsp
3rd row00425_200710081727171.jsp
4th row00311_200710111410071.jsp
5th row00425_200710191426221.jsp
ValueCountFrequency (%)
00218_201610271851491.jsp 2
 
0.3%
00340_201705101520021.jsp 2
 
0.3%
00514_201804041543111.jsp 2
 
0.3%
00420_202209191346541.jsp 2
 
0.3%
00688_201406051804191.jsp 2
 
0.3%
00021_201008061634591.jsp 2
 
0.3%
00505_201505181716371.jsp 2
 
0.3%
00520_200911031111371.jsp 2
 
0.3%
00358_201407090937151.jsp 2
 
0.3%
00432_201006211802381.jsp 2
 
0.3%
Other values (649) 656
97.0%
2023-12-13T04:10:31.349910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3725
22.0%
1 2952
17.5%
2 2020
11.9%
4 887
 
5.2%
3 836
 
4.9%
5 827
 
4.9%
_ 677
 
4.0%
. 676
 
4.0%
p 675
 
4.0%
s 674
 
4.0%
Other values (16) 2956
17.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13515
79.9%
Lowercase Letter 2037
 
12.0%
Connector Punctuation 677
 
4.0%
Other Punctuation 676
 
4.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p 675
33.1%
s 674
33.1%
j 673
33.0%
h 3
 
0.1%
w 2
 
0.1%
e 2
 
0.1%
d 1
 
< 0.1%
u 1
 
< 0.1%
v 1
 
< 0.1%
x 1
 
< 0.1%
Other values (4) 4
 
0.2%
Decimal Number
ValueCountFrequency (%)
0 3725
27.6%
1 2952
21.8%
2 2020
14.9%
4 887
 
6.6%
3 836
 
6.2%
5 827
 
6.1%
9 602
 
4.5%
6 574
 
4.2%
8 568
 
4.2%
7 524
 
3.9%
Connector Punctuation
ValueCountFrequency (%)
_ 677
100.0%
Other Punctuation
ValueCountFrequency (%)
. 676
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14868
88.0%
Latin 2037
 
12.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
p 675
33.1%
s 674
33.1%
j 673
33.0%
h 3
 
0.1%
w 2
 
0.1%
e 2
 
0.1%
d 1
 
< 0.1%
u 1
 
< 0.1%
v 1
 
< 0.1%
x 1
 
< 0.1%
Other values (4) 4
 
0.2%
Common
ValueCountFrequency (%)
0 3725
25.1%
1 2952
19.9%
2 2020
13.6%
4 887
 
6.0%
3 836
 
5.6%
5 827
 
5.6%
_ 677
 
4.6%
. 676
 
4.5%
9 602
 
4.0%
6 574
 
3.9%
Other values (2) 1092
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16905
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3725
22.0%
1 2952
17.5%
2 2020
11.9%
4 887
 
5.2%
3 836
 
4.9%
5 827
 
4.9%
_ 677
 
4.0%
. 676
 
4.0%
p 675
 
4.0%
s 674
 
4.0%
Other values (16) 2956
17.5%
Distinct628
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
Minimum2007-09-04 10:59:49
Maximum2023-08-21 15:41:55
2023-12-13T04:10:31.508987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:10:31.665036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

수정일시
Date

MISSING 

Distinct551
Distinct (%)99.8%
Missing124
Missing (%)18.3%
Memory size5.4 KiB
Minimum2007-10-08 20:34:22
Maximum2023-08-21 15:37:59
2023-12-13T04:10:32.072828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:10:32.194209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

기타유의사항
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
공란은 데이터 미존재, 데이터 기준일과 파일 내 등록일, 수정일은 다를 수 있음
676 

Length

Max length44
Median length44
Mean length44
Min length44

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row공란은 데이터 미존재, 데이터 기준일과 파일 내 등록일, 수정일은 다를 수 있음
2nd row공란은 데이터 미존재, 데이터 기준일과 파일 내 등록일, 수정일은 다를 수 있음
3rd row공란은 데이터 미존재, 데이터 기준일과 파일 내 등록일, 수정일은 다를 수 있음
4th row공란은 데이터 미존재, 데이터 기준일과 파일 내 등록일, 수정일은 다를 수 있음
5th row공란은 데이터 미존재, 데이터 기준일과 파일 내 등록일, 수정일은 다를 수 있음

Common Values

ValueCountFrequency (%)
공란은 데이터 미존재, 데이터 기준일과 파일 내 등록일, 수정일은 다를 수 있음 676
100.0%

Length

2023-12-13T04:10:32.310054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:10:32.395010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
데이터 1352
16.7%
공란은 676
8.3%
미존재 676
8.3%
기준일과 676
8.3%
파일 676
8.3%
676
8.3%
등록일 676
8.3%
수정일은 676
8.3%
다를 676
8.3%
676
8.3%

Interactions

2023-12-13T04:10:26.654968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T04:10:32.449512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공고일련번호게시여부
공고일련번호1.0000.156
게시여부0.1561.000
2023-12-13T04:10:32.537749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공고일련번호게시여부
공고일련번호1.0000.117
게시여부0.1171.000

Missing values

2023-12-13T04:10:26.801003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:10:26.967760image/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.
2023-12-13T04:10:27.090338image/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

공고일련번호공고명모집공고일접수시작일접수마감일게시여부HTML논리적파일명HTML물리적파일명등록일시수정일시기타유의사항
0301오산가장 산업단지 생산시설용지 분양공고2007-07-312007-08-202007-08-23Y공급공고[1].htmdev_user_200709041557471.jsp2007-09-04 10:59:492007-10-09 10:25:49공란은 데이터 미존재, 데이터 기준일과 파일 내 등록일, 수정일은 다를 수 있음
1302오산가장 산업단지 생산시설용지 분양공고2007-07-062007-07-072007-07-07N_공고.htm00425_200710081727171.jsp2007-10-08 16:50:242007-10-10 09:56:31공란은 데이터 미존재, 데이터 기준일과 파일 내 등록일, 수정일은 다를 수 있음
2302광교신도시 공동주택용지 공급공고2007-10-112007-10-232007-10-25Y_공고.htm00425_200710081727171.jsp2007-10-08 16:50:242007-10-08 20:34:22공란은 데이터 미존재, 데이터 기준일과 파일 내 등록일, 수정일은 다를 수 있음
3303광교신도시 공동주택용지 공급공고2007-10-112007-10-232007-10-25Y게시공고문[1].htm00311_200710111410071.jsp2007-10-09 16:42:262007-10-15 14:26:47공란은 데이터 미존재, 데이터 기준일과 파일 내 등록일, 수정일은 다를 수 있음
4303광교신도시 공동주택용지 공급공고2007-10-112007-10-232007-10-25Y정정공고문.htm00425_200710191426221.jsp2007-10-09 16:42:262007-10-19 14:25:48공란은 데이터 미존재, 데이터 기준일과 파일 내 등록일, 수정일은 다를 수 있음
5304오산가장 산업단지 내 지원시설용지 공급공고2007-10-152007-10-292007-10-30Y지원시설용지공급공고문.htm00430_200710120952251.jsp2007-10-12 09:52:052007-10-25 16:15:32공란은 데이터 미존재, 데이터 기준일과 파일 내 등록일, 수정일은 다를 수 있음
6306광교신도시 공동주택용지 2차 공급 공고2007-12-142007-12-242007-12-26Y01 주상복합용지 등 공급공고문(20100824).htm00607_201008241943001.jsp2007-11-22 15:50:322010-08-24 19:42:59공란은 데이터 미존재, 데이터 기준일과 파일 내 등록일, 수정일은 다를 수 있음
7306광교신도시 공동주택용지 2차 공급 공고2007-12-142007-12-242007-12-26Y광교신도시 공동주택용지 게시공고[1].htm00425_200712141853051.jsp2007-11-22 15:50:322007-12-17 10:10:58공란은 데이터 미존재, 데이터 기준일과 파일 내 등록일, 수정일은 다를 수 있음
8307오산가장 산업단지 내 지원시설용지 공급공고2007-11-302007-12-172007-12-18Y지원시설용지 공급공고문.htm00430_200712031047031.jsp2007-12-03 10:46:342007-12-17 10:55:36공란은 데이터 미존재, 데이터 기준일과 파일 내 등록일, 수정일은 다를 수 있음
9308김포양촌산업단지 연구시설용지 및 폐기물처리시설용지 공급공고2008-06-302008-06-302008-07-31Y김포양촌산단 연구시설용지등 공급공고(게시용 ).htm00021_200807011313391.jsp2008-06-30 14:33:042008-07-01 13:13:22공란은 데이터 미존재, 데이터 기준일과 파일 내 등록일, 수정일은 다를 수 있음
공고일련번호공고명모집공고일접수시작일접수마감일게시여부HTML논리적파일명HTML물리적파일명등록일시수정일시기타유의사항
6661058광주역세권 단독주택용지(주거전용) 수의계약 공급공고2023-07-282023-08-092023-11-30Y광주역세권 단독주택용지 수의계약.htm00520_202307281340171.jsp2023-07-28 13:40:182023-07-28 13:46:15공란은 데이터 미존재, 데이터 기준일과 파일 내 등록일, 수정일은 다를 수 있음
6671059평택고덕국제화계획지구 업무시설용지 재공급공고2023-08-012023-08-162023-08-16Y평택고덕국제화계획지구.htm01174_202307310943471.jsp2023-07-31 09:43:472023-08-01 10:11:26공란은 데이터 미존재, 데이터 기준일과 파일 내 등록일, 수정일은 다를 수 있음
6681060파주 문산첨단산업단지(선유) 주차장, 지원시설용지 수의계약 공고2023-08-012023-08-082024-12-31Y파주 문산첨단산업단지.htm00788_202307311414121.jsp2023-07-31 14:14:122023-08-01 09:03:12공란은 데이터 미존재, 데이터 기준일과 파일 내 등록일, 수정일은 다를 수 있음
6691061화성동탄(2)근린생활시설용지 및 근린상업용지 공급 공고2023-08-012023-08-162023-08-16Y화성동탄.htm00737_202307311649081.jsp2023-07-31 16:49:102023-08-01 11:11:26공란은 데이터 미존재, 데이터 기준일과 파일 내 등록일, 수정일은 다를 수 있음
6701062안성원곡물류단지 지원시설용지(주거시설) 수의계약 공급공고2023-08-012023-08-082999-12-31Y안성원곡물류단지 단독주택용지 수의계약 공고.htm01084_202307311748591.jsp2023-07-31 17:48:592023-07-31 17:55:01공란은 데이터 미존재, 데이터 기준일과 파일 내 등록일, 수정일은 다를 수 있음
6711063평택오성 일반산업단지 지원시설용지 수의계약 공급공고2023-08-012023-08-082033-08-31Y[붙임1]평택오성 산업단지 지원시설용지 수의계약 공급공고.htm00857_202308010924581.jsp2023-08-01 09:24:582023-08-01 09:25:51공란은 데이터 미존재, 데이터 기준일과 파일 내 등록일, 수정일은 다를 수 있음
6721064다산신도시 지금지구 업무시설용지 재공급 수정공고[1차]2023-08-032023-08-172023-08-18Y다산신도시 업무시설용지 수정공고문을 붙임과 같이 게시합니다.htm00520_202308171615101.jsp2023-08-02 15:59:342023-08-17 16:39:24공란은 데이터 미존재, 데이터 기준일과 파일 내 등록일, 수정일은 다를 수 있음
6731065평택고덕국제화계획지구 종교시설용지 수의계약 공급공고2023-08-222023-09-052023-11-30N평택고덕국제화계획지구.htm01174_202308211530111.jsp2023-08-21 15:30:12<NA>공란은 데이터 미존재, 데이터 기준일과 파일 내 등록일, 수정일은 다를 수 있음
6741066화성동탄(2) 유치원용지 수의계약 공급공고2023-08-222023-09-052023-11-30N화성동탄0001.htm00737_202308211537541.jsp2023-08-21 15:37:552023-08-21 15:37:59공란은 데이터 미존재, 데이터 기준일과 파일 내 등록일, 수정일은 다를 수 있음
6751067화성동탄(2) 근린생활시설용지 수의계약 공고2023-08-222023-09-052023-11-30N화성동탄0001.htm00737_202308211541531.jsp2023-08-21 15:41:55<NA>공란은 데이터 미존재, 데이터 기준일과 파일 내 등록일, 수정일은 다를 수 있음

Duplicate rows

Most frequently occurring

공고일련번호공고명모집공고일접수시작일접수마감일게시여부HTML논리적파일명HTML물리적파일명등록일시수정일시기타유의사항# duplicates
0361광교 연립주택용지 공급공고2010-06-092010-06-232010-06-24Y100621 정정공고(게시).htm00432_201006211802381.jsp2010-06-08 23:06:302010-06-21 18:02:54공란은 데이터 미존재, 데이터 기준일과 파일 내 등록일, 수정일은 다를 수 있음2