Overview

Dataset statistics

Number of variables22
Number of observations10000
Missing cells12075
Missing cells (%)5.5%
Duplicate rows3
Duplicate rows (%)< 0.1%
Total size in memory1.8 MiB
Average record size in memory188.0 B

Variable types

Categorical4
Text8
DateTime6
Numeric4

Dataset

Description한국토지주택공사에서 2016년~2020년 간 입찰 방식으로 공급한 토지 공고 내역(지역, 사업지구, 공급용도, 공급금액 등) 데이터를 제공합니다.
Author한국토지주택공사
URLhttps://www.data.go.kr/data/15072459/fileData.do

Alerts

Dataset has 3 (< 0.1%) duplicate rowsDuplicates
공고종류 is highly imbalanced (93.9%)Imbalance
공급방법 is highly imbalanced (61.1%)Imbalance
공급방법.1 is highly imbalanced (60.0%)Imbalance
개찰결과게시일시 has 118 (1.2%) missing valuesMissing
사업지구 has 120 (1.2%) missing valuesMissing
블록 has 172 (1.7%) missing valuesMissing
가구번호 has 358 (3.6%) missing valuesMissing
획지위치 has 1147 (11.5%) missing valuesMissing
예정지번 has 2919 (29.2%) missing valuesMissing
확정지번 has 6749 (67.5%) missing valuesMissing
공급용도 has 120 (1.2%) missing valuesMissing
가분할면적(제곱미터) has 120 (1.2%) missing valuesMissing
확정면적(제곱미터) has 120 (1.2%) missing valuesMissing
공급예정금액 has 120 (1.2%) missing valuesMissing
가분할면적(제곱미터) is highly skewed (γ1 = 29.08268628)Skewed
확정면적(제곱미터) is highly skewed (γ1 = 32.04421732)Skewed
공급예정금액 is highly skewed (γ1 = 23.48101727)Skewed
확정면적(제곱미터) has 6070 (60.7%) zerosZeros

Reproduction

Analysis started2023-12-12 00:43:53.665082
Analysis finished2023-12-12 00:43:55.369670
Duration1.7 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지역본부
Categorical

Distinct13
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
경기지역본부
1967 
인천지역본부
1710 
서울지역본부
1269 
대전충남지역본부
1257 
전북지역본부
706 
Other values (8)
3091 

Length

Max length11
Median length6
Mean length6.6142
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기지역본부
2nd row인천지역본부
3rd row경기지역본부
4th row경기지역본부
5th row전북지역본부

Common Values

ValueCountFrequency (%)
경기지역본부 1967
19.7%
인천지역본부 1710
17.1%
서울지역본부 1269
12.7%
대전충남지역본부 1257
12.6%
전북지역본부 706
 
7.1%
광주전남지역본부 675
 
6.8%
부산울산지역본부 598
 
6.0%
경남지역본부 556
 
5.6%
대구경북지역본부 536
 
5.4%
충북지역본부 345
 
3.5%
Other values (3) 381
 
3.8%

Length

2023-12-12T09:43:55.441822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기지역본부 1967
19.7%
인천지역본부 1710
17.1%
서울지역본부 1269
12.7%
대전충남지역본부 1257
12.6%
전북지역본부 706
 
7.1%
광주전남지역본부 675
 
6.8%
부산울산지역본부 598
 
6.0%
경남지역본부 556
 
5.6%
대구경북지역본부 536
 
5.4%
충북지역본부 345
 
3.5%
Other values (3) 381
 
3.8%

공고명
Text

Distinct1157
Distinct (%)11.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T09:43:55.678265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length94
Median length55
Mean length28.821
Min length12

Characters and Unicode

Total characters288210
Distinct characters318
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique355 ?
Unique (%)3.5%

Sample

1st row[첨부파일 정정공고] 성남여수 근린생활시설용지 및 종교시설용지 공급공고
2nd row부천오정물류단지 지원시설, 주차장용지 공급공고
3rd row화성향남2지구 상업용지 공급공고
4th row평택청북 근린상업용지,근린생활시설용지,준주거용지 공급공고
5th row정읍첨단 지원시설용지 공급 재공고
ValueCountFrequency (%)
공급공고 4866
 
10.2%
공고 3268
 
6.9%
공급 2281
 
4.8%
및 1871
 
3.9%
근린생활시설용지 1587
 
3.3%
점포겸용 1523
 
3.2%
주차장용지 998
 
2.1%
단독주택용지 969
 
2.0%
재공급 780
 
1.6%
상업용지 617
 
1.3%
Other values (875) 28818
60.6%
2023-12-12T09:43:56.129166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
37587
 
13.0%
공 19327
 
6.7%
지 17996
 
6.2%
용 15090
 
5.2%
고 10803
 
3.7%
주 9617
 
3.3%
급 9028
 
3.1%
시 7014
 
2.4%
, 5840
 
2.0%
업 5494
 
1.9%
Other values (308) 150414
52.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 229536
79.6%
Space Separator 37587
 
13.0%
Other Punctuation 8141
 
2.8%
Decimal Number 4417
 
1.5%
Close Punctuation 3908
 
1.4%
Open Punctuation 3908
 
1.4%
Uppercase Letter 596
 
0.2%
Dash Punctuation 97
 
< 0.1%
Lowercase Letter 13
 
< 0.1%
Math Symbol 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 19327
 
8.4%
지 17996
 
7.8%
용 15090
 
6.6%
고 10803
 
4.7%
주 9617
 
4.2%
급 9028
 
3.9%
시 7014
 
3.1%
업 5494
 
2.4%
설 5072
 
2.2%
구 4227
 
1.8%
Other values (269) 125868
54.8%
Uppercase Letter
ValueCountFrequency (%)
R 387
64.9%
C 45
 
7.6%
B 34
 
5.7%
L 26
 
4.4%
D 23
 
3.9%
P 19
 
3.2%
M 15
 
2.5%
H 14
 
2.3%
I 14
 
2.3%
E 10
 
1.7%
Other values (2) 9
 
1.5%
Decimal Number
ValueCountFrequency (%)
2 1636
37.0%
1 1007
22.8%
3 687
15.6%
4 269
 
6.1%
0 210
 
4.8%
7 168
 
3.8%
8 160
 
3.6%
5 120
 
2.7%
6 107
 
2.4%
9 53
 
1.2%
Other Punctuation
ValueCountFrequency (%)
, 5840
71.7%
· 1532
 
18.8%
/ 722
 
8.9%
% 24
 
0.3%
. 23
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 3594
92.0%
] 309
 
7.9%
〕 5
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 3594
92.0%
[ 309
 
7.9%
〔 5
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
n 9
69.2%
b 2
 
15.4%
c 2
 
15.4%
Space Separator
ValueCountFrequency (%)
37587
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 97
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 229536
79.6%
Common 58065
 
20.1%
Latin 609
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 19327
 
8.4%
지 17996
 
7.8%
용 15090
 
6.6%
고 10803
 
4.7%
주 9617
 
4.2%
급 9028
 
3.9%
시 7014
 
3.1%
업 5494
 
2.4%
설 5072
 
2.2%
구 4227
 
1.8%
Other values (269) 125868
54.8%
Common
ValueCountFrequency (%)
37587
64.7%
, 5840
 
10.1%
) 3594
 
6.2%
( 3594
 
6.2%
2 1636
 
2.8%
· 1532
 
2.6%
1 1007
 
1.7%
/ 722
 
1.2%
3 687
 
1.2%
[ 309
 
0.5%
Other values (14) 1557
 
2.7%
Latin
ValueCountFrequency (%)
R 387
63.5%
C 45
 
7.4%
B 34
 
5.6%
L 26
 
4.3%
D 23
 
3.8%
P 19
 
3.1%
M 15
 
2.5%
H 14
 
2.3%
I 14
 
2.3%
E 10
 
1.6%
Other values (5) 22
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 229517
79.6%
ASCII 57132
 
19.8%
None 1542
 
0.5%
Compat Jamo 19
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
37587
65.8%
, 5840
 
10.2%
) 3594
 
6.3%
( 3594
 
6.3%
2 1636
 
2.9%
1 1007
 
1.8%
/ 722
 
1.3%
3 687
 
1.2%
R 387
 
0.7%
[ 309
 
0.5%
Other values (26) 1769
 
3.1%
Hangul
ValueCountFrequency (%)
공 19327
 
8.4%
지 17996
 
7.8%
용 15090
 
6.6%
고 10803
 
4.7%
주 9617
 
4.2%
급 9028
 
3.9%
시 7014
 
3.1%
업 5494
 
2.4%
설 5072
 
2.2%
구 4227
 
1.8%
Other values (268) 125849
54.8%
None
ValueCountFrequency (%)
· 1532
99.4%
〕 5
 
0.3%
〔 5
 
0.3%
Compat Jamo
ValueCountFrequency (%)
ㆍ 19
100.0%

공고종류
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반공고
9882 
정정공고
 
111
취소공고
 
7

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row정정공고
2nd row일반공고
3rd row일반공고
4th row일반공고
5th row일반공고

Common Values

ValueCountFrequency (%)
일반공고 9882
98.8%
정정공고 111
 
1.1%
취소공고 7
 
0.1%

Length

2023-12-12T09:43:56.280136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:43:56.386655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반공고 9882
98.8%
정정공고 111
 
1.1%
취소공고 7
 
0.1%

공고게시일
Date

Distinct695
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2016-01-14 00:00:00
Maximum2020-12-29 00:00:00
2023-12-12T09:43:56.504140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:43:56.646796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

계약체결개시일
Date

Distinct611
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2016-01-21 00:00:00
Maximum2021-01-25 00:00:00
2023-12-12T09:43:56.794952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:43:56.958422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

계약체결종료일
Date

Distinct614
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2016-01-21 00:00:00
Maximum2021-01-27 00:00:00
2023-12-12T09:43:57.243728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:43:57.410049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

매물위치
Text

Distinct240
Distinct (%)2.4%
Missing10
Missing (%)0.1%
Memory size156.2 KiB
2023-12-12T09:43:57.669527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length6
Mean length7.8419419
Min length5

Characters and Unicode

Total characters78341
Distinct characters96
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

Unique33 ?
Unique (%)0.3%

Sample

1st row경기 성남시 용인시 수원시
2nd row경기 부천시
3rd row경기 화성시
4th row경기 평택시
5th row전북 정읍시
ValueCountFrequency (%)
경기 4316
 
17.1%
화성시 1310
 
5.2%
충남 967
 
3.8%
서구 783
 
3.1%
전북 706
 
2.8%
수원시 661
 
2.6%
인천 648
 
2.6%
북구 639
 
2.5%
경남 556
 
2.2%
양주시 550
 
2.2%
Other values (110) 14048
55.8%
2023-12-12T09:43:58.058341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15194
19.4%
시 10381
 
13.3%
경 5086
 
6.5%
구 4355
 
5.6%
기 4329
 
5.5%
남 2924
 
3.7%
산 2519
 
3.2%
주 2412
 
3.1%
성 2161
 
2.8%
북 1848
 
2.4%
Other values (86) 27132
34.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 63147
80.6%
Space Separator 15194
 
19.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 10381
16.4%
경 5086
 
8.1%
구 4355
 
6.9%
기 4329
 
6.9%
남 2924
 
4.6%
산 2519
 
4.0%
주 2412
 
3.8%
성 2161
 
3.4%
북 1848
 
2.9%
군 1650
 
2.6%
Other values (85) 25482
40.4%
Space Separator
ValueCountFrequency (%)
15194
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 63147
80.6%
Common 15194
 
19.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 10381
16.4%
경 5086
 
8.1%
구 4355
 
6.9%
기 4329
 
6.9%
남 2924
 
4.6%
산 2519
 
4.0%
주 2412
 
3.8%
성 2161
 
3.4%
북 1848
 
2.9%
군 1650
 
2.6%
Other values (85) 25482
40.4%
Common
ValueCountFrequency (%)
15194
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 63147
80.6%
ASCII 15194
 
19.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15194
100.0%
Hangul
ValueCountFrequency (%)
시 10381
16.4%
경 5086
 
8.1%
구 4355
 
6.9%
기 4329
 
6.9%
남 2924
 
4.6%
산 2519
 
4.0%
주 2412
 
3.8%
성 2161
 
3.4%
북 1848
 
2.9%
군 1650
 
2.6%
Other values (85) 25482
40.4%

공급방법
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
입찰
9238 
입찰 추첨
 
762

Length

Max length5
Median length2
Mean length2.2286
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
입찰 9238
92.4%
입찰 추첨 762
 
7.6%

Length

2023-12-12T09:43:58.191985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:43:58.297681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
입찰 10000
92.9%
추첨 762
 
7.1%

입찰신청접수개시일시
Date

Distinct799
Distinct (%)8.0%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
Minimum2016-01-19 15:00:00
Maximum2021-01-13 10:00:00
2023-12-12T09:43:58.398296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:43:58.518018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

입찰신청접수종료일시
Date

Distinct768
Distinct (%)7.7%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
Minimum2016-01-19 15:50:00
Maximum2021-01-13 16:00:00
2023-12-12T09:43:58.642063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:43:58.759638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

개찰결과게시일시
Date

MISSING 

Distinct943
Distinct (%)9.5%
Missing118
Missing (%)1.2%
Memory size156.2 KiB
Minimum2016-01-19 16:10:00
Maximum2021-01-13 18:00:00
2023-12-12T09:43:58.873569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:43:58.986055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

사업지구
Text

MISSING 

Distinct211
Distinct (%)2.1%
Missing120
Missing (%)1.2%
Memory size156.2 KiB
2023-12-12T09:43:59.209415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length15
Mean length7.2933198
Min length2

Characters and Unicode

Total characters72058
Distinct characters233
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

Unique33 ?
Unique (%)0.3%

Sample

1st row부천오정물류단지
2nd row화성향남2
3rd row평택청북
4th row정읍첨단
5th row남양뉴타운
ValueCountFrequency (%)
양주옥정 483
 
4.8%
인천영종 423
 
4.2%
남양뉴타운 336
 
3.4%
울산송정 324
 
3.2%
군산신역세권(05,택1 324
 
3.2%
빛그린 315
 
3.2%
창원가포 312
 
3.1%
보령명천 254
 
2.5%
아산탕정(05,택 235
 
2.4%
화성동탄2 227
 
2.3%
Other values (207) 6746
67.6%
2023-12-12T09:43:59.562651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 3643
 
5.1%
) 3643
 
5.1%
0 3258
 
4.5%
, 3133
 
4.3%
택 2244
 
3.1%
산 1992
 
2.8%
주 1986
 
2.8%
정 1576
 
2.2%
남 1501
 
2.1%
천 1493
 
2.1%
Other values (223) 47589
66.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 51406
71.3%
Decimal Number 9052
 
12.6%
Open Punctuation 3643
 
5.1%
Close Punctuation 3643
 
5.1%
Other Punctuation 3302
 
4.6%
Uppercase Letter 894
 
1.2%
Space Separator 99
 
0.1%
Letter Number 9
 
< 0.1%
Lowercase Letter 5
 
< 0.1%
Connector Punctuation 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
택 2244
 
4.4%
산 1992
 
3.9%
주 1986
 
3.9%
정 1576
 
3.1%
남 1501
 
2.9%
천 1493
 
2.9%
양 1451
 
2.8%
도 1075
 
2.1%
국 1057
 
2.1%
성 898
 
1.7%
Other values (198) 36133
70.3%
Decimal Number
ValueCountFrequency (%)
0 3258
36.0%
1 1314
14.5%
2 981
 
10.8%
5 976
 
10.8%
6 740
 
8.2%
9 571
 
6.3%
3 511
 
5.6%
7 328
 
3.6%
8 248
 
2.7%
4 125
 
1.4%
Uppercase Letter
ValueCountFrequency (%)
G 363
40.6%
B 363
40.6%
D 83
 
9.3%
R 83
 
9.3%
M 1
 
0.1%
P 1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
, 3133
94.9%
. 91
 
2.8%
& 78
 
2.4%
Open Punctuation
ValueCountFrequency (%)
( 3643
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3643
100.0%
Space Separator
ValueCountFrequency (%)
99
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 9
100.0%
Lowercase Letter
ValueCountFrequency (%)
n 5
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 51406
71.3%
Common 19744
 
27.4%
Latin 908
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
택 2244
 
4.4%
산 1992
 
3.9%
주 1986
 
3.9%
정 1576
 
3.1%
남 1501
 
2.9%
천 1493
 
2.9%
양 1451
 
2.8%
도 1075
 
2.1%
국 1057
 
2.1%
성 898
 
1.7%
Other values (198) 36133
70.3%
Common
ValueCountFrequency (%)
( 3643
18.5%
) 3643
18.5%
0 3258
16.5%
, 3133
15.9%
1 1314
 
6.7%
2 981
 
5.0%
5 976
 
4.9%
6 740
 
3.7%
9 571
 
2.9%
3 511
 
2.6%
Other values (7) 974
 
4.9%
Latin
ValueCountFrequency (%)
G 363
40.0%
B 363
40.0%
D 83
 
9.1%
R 83
 
9.1%
Ⅱ 9
 
1.0%
n 5
 
0.6%
M 1
 
0.1%
P 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 51406
71.3%
ASCII 20643
28.6%
Number Forms 9
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 3643
17.6%
) 3643
17.6%
0 3258
15.8%
, 3133
15.2%
1 1314
 
6.4%
2 981
 
4.8%
5 976
 
4.7%
6 740
 
3.6%
9 571
 
2.8%
3 511
 
2.5%
Other values (14) 1873
9.1%
Hangul
ValueCountFrequency (%)
택 2244
 
4.4%
산 1992
 
3.9%
주 1986
 
3.9%
정 1576
 
3.1%
남 1501
 
2.9%
천 1493
 
2.9%
양 1451
 
2.8%
도 1075
 
2.1%
국 1057
 
2.1%
성 898
 
1.7%
Other values (198) 36133
70.3%
Number Forms
ValueCountFrequency (%)
Ⅱ 9
100.0%

블록
Text

MISSING 

Distinct163
Distinct (%)1.7%
Missing172
Missing (%)1.7%
Memory size156.2 KiB
2023-12-12T09:43:59.725732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.1768417
Min length1

Characters and Unicode

Total characters11566
Distinct characters56
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)0.6%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 6837
69.6%
1 1013
 
10.3%
3 365
 
3.7%
2 320
 
3.3%
공공 117
 
1.2%
z 93
 
0.9%
5 87
 
0.9%
4 79
 
0.8%
근생 58
 
0.6%
2001 55
 
0.6%
Other values (153) 805
 
8.2%
2023-12-12T09:44:00.022029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7045
60.9%
1 1342
 
11.6%
3 528
 
4.6%
2 515
 
4.5%
공 234
 
2.0%
4 212
 
1.8%
상 205
 
1.8%
5 192
 
1.7%
근 190
 
1.6%
생 135
 
1.2%
Other values (46) 968
 
8.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9969
86.2%
Other Letter 1082
 
9.4%
Uppercase Letter 392
 
3.4%
Lowercase Letter 63
 
0.5%
Dash Punctuation 48
 
0.4%
Other Punctuation 11
 
0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 234
21.6%
상 205
18.9%
근 190
17.6%
생 135
12.5%
주 87
 
8.0%
일 75
 
6.9%
택 42
 
3.9%
업 28
 
2.6%
잔 13
 
1.2%
교 11
 
1.0%
Other values (15) 62
 
5.7%
Uppercase Letter
ValueCountFrequency (%)
Z 93
23.7%
H 83
21.2%
D 77
19.6%
C 69
17.6%
B 38
9.7%
R 10
 
2.6%
M 7
 
1.8%
G 5
 
1.3%
A 5
 
1.3%
L 2
 
0.5%
Other values (2) 3
 
0.8%
Decimal Number
ValueCountFrequency (%)
0 7045
70.7%
1 1342
 
13.5%
3 528
 
5.3%
2 515
 
5.2%
4 212
 
2.1%
5 192
 
1.9%
6 75
 
0.8%
9 22
 
0.2%
7 22
 
0.2%
8 16
 
0.2%
Lowercase Letter
ValueCountFrequency (%)
p 19
30.2%
r 19
30.2%
k 19
30.2%
i 2
 
3.2%
b 2
 
3.2%
c 2
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%
Other Punctuation
ValueCountFrequency (%)
* 11
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10029
86.7%
Hangul 1082
 
9.4%
Latin 455
 
3.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 234
21.6%
상 205
18.9%
근 190
17.6%
생 135
12.5%
주 87
 
8.0%
일 75
 
6.9%
택 42
 
3.9%
업 28
 
2.6%
잔 13
 
1.2%
교 11
 
1.0%
Other values (15) 62
 
5.7%
Latin
ValueCountFrequency (%)
Z 93
20.4%
H 83
18.2%
D 77
16.9%
C 69
15.2%
B 38
8.4%
p 19
 
4.2%
r 19
 
4.2%
k 19
 
4.2%
R 10
 
2.2%
M 7
 
1.5%
Other values (8) 21
 
4.6%
Common
ValueCountFrequency (%)
0 7045
70.2%
1 1342
 
13.4%
3 528
 
5.3%
2 515
 
5.1%
4 212
 
2.1%
5 192
 
1.9%
6 75
 
0.7%
- 48
 
0.5%
9 22
 
0.2%
7 22
 
0.2%
Other values (3) 28
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10484
90.6%
Hangul 1082
 
9.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7045
67.2%
1 1342
 
12.8%
3 528
 
5.0%
2 515
 
4.9%
4 212
 
2.0%
5 192
 
1.8%
Z 93
 
0.9%
H 83
 
0.8%
D 77
 
0.7%
6 75
 
0.7%
Other values (21) 322
 
3.1%
Hangul
ValueCountFrequency (%)
공 234
21.6%
상 205
18.9%
근 190
17.6%
생 135
12.5%
주 87
 
8.0%
일 75
 
6.9%
택 42
 
3.9%
업 28
 
2.6%
잔 13
 
1.2%
교 11
 
1.0%
Other values (15) 62
 
5.7%

가구번호
Text

MISSING 

Distinct1280
Distinct (%)13.3%
Missing358
Missing (%)3.6%
Memory size156.2 KiB
2023-12-12T09:44:00.349566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length3.13296
Min length1

Characters and Unicode

Total characters30208
Distinct characters93
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique360 ?
Unique (%)3.7%

Sample

1st row31
2nd row35
3rd row31
4th row58
5th row32
ValueCountFrequency (%)
31 590
 
6.1%
34 549
 
5.7%
110 368
 
3.8%
32 268
 
2.8%
3 250
 
2.6%
58 159
 
1.6%
39 149
 
1.5%
9 124
 
1.3%
169 98
 
1.0%
35 93
 
1.0%
Other values (1263) 6994
72.5%
2023-12-12T09:44:00.793441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4775
15.8%
3 3641
 
12.1%
- 3311
 
11.0%
2 2381
 
7.9%
4 1610
 
5.3%
5 1319
 
4.4%
9 1001
 
3.3%
6 858
 
2.8%
근 805
 
2.7%
0 804
 
2.7%
Other values (83) 9703
32.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17736
58.7%
Other Letter 5394
 
17.9%
Dash Punctuation 3311
 
11.0%
Uppercase Letter 3095
 
10.2%
Other Number 537
 
1.8%
Lowercase Letter 135
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
근 805
14.9%
상 714
13.2%
생 570
10.6%
단 562
10.4%
독 516
9.6%
주 485
9.0%
업 270
 
5.0%
준 195
 
3.6%
이 178
 
3.3%
지 138
 
2.6%
Other values (36) 961
17.8%
Uppercase Letter
ValueCountFrequency (%)
D 693
22.4%
C 624
20.2%
R 342
11.1%
F 297
9.6%
E 272
 
8.8%
N 176
 
5.7%
A 155
 
5.0%
B 150
 
4.8%
G 133
 
4.3%
S 94
 
3.0%
Other values (8) 159
 
5.1%
Other Number
ValueCountFrequency (%)
③ 113
21.0%
② 97
18.1%
① 85
15.8%
④ 71
13.2%
⑤ 48
8.9%
⑥ 31
 
5.8%
⑦ 22
 
4.1%
⑧ 16
 
3.0%
⑩ 12
 
2.2%
⑪ 11
 
2.0%
Other values (5) 31
 
5.8%
Decimal Number
ValueCountFrequency (%)
1 4775
26.9%
3 3641
20.5%
2 2381
13.4%
4 1610
 
9.1%
5 1319
 
7.4%
9 1001
 
5.6%
6 858
 
4.8%
0 804
 
4.5%
8 786
 
4.4%
7 561
 
3.2%
Lowercase Letter
ValueCountFrequency (%)
d 94
69.6%
c 39
28.9%
b 2
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 3311
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 21584
71.5%
Hangul 5394
 
17.9%
Latin 3230
 
10.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
근 805
14.9%
상 714
13.2%
생 570
10.6%
단 562
10.4%
독 516
9.6%
주 485
9.0%
업 270
 
5.0%
준 195
 
3.6%
이 178
 
3.3%
지 138
 
2.6%
Other values (36) 961
17.8%
Common
ValueCountFrequency (%)
1 4775
22.1%
3 3641
16.9%
- 3311
15.3%
2 2381
11.0%
4 1610
 
7.5%
5 1319
 
6.1%
9 1001
 
4.6%
6 858
 
4.0%
0 804
 
3.7%
8 786
 
3.6%
Other values (16) 1098
 
5.1%
Latin
ValueCountFrequency (%)
D 693
21.5%
C 624
19.3%
R 342
10.6%
F 297
9.2%
E 272
 
8.4%
N 176
 
5.4%
A 155
 
4.8%
B 150
 
4.6%
G 133
 
4.1%
S 94
 
2.9%
Other values (11) 294
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24277
80.4%
Hangul 5394
 
17.9%
Enclosed Alphanum 537
 
1.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4775
19.7%
3 3641
15.0%
- 3311
13.6%
2 2381
9.8%
4 1610
 
6.6%
5 1319
 
5.4%
9 1001
 
4.1%
6 858
 
3.5%
0 804
 
3.3%
8 786
 
3.2%
Other values (22) 3791
15.6%
Hangul
ValueCountFrequency (%)
근 805
14.9%
상 714
13.2%
생 570
10.6%
단 562
10.4%
독 516
9.6%
주 485
9.0%
업 270
 
5.0%
준 195
 
3.6%
이 178
 
3.3%
지 138
 
2.6%
Other values (36) 961
17.8%
Enclosed Alphanum
ValueCountFrequency (%)
③ 113
21.0%
② 97
18.1%
① 85
15.8%
④ 71
13.2%
⑤ 48
8.9%
⑥ 31
 
5.8%
⑦ 22
 
4.1%
⑧ 16
 
3.0%
⑩ 12
 
2.2%
⑪ 11
 
2.0%
Other values (5) 31
 
5.8%

획지위치
Real number (ℝ)

MISSING 

Distinct297
Distinct (%)3.4%
Missing1147
Missing (%)11.5%
Infinite0
Infinite (%)0.0%
Mean24.684627
Minimum-6
Maximum1303
Zeros59
Zeros (%)0.6%
Negative77
Negative (%)0.8%
Memory size166.0 KiB
2023-12-12T09:44:00.923513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-6
5-th percentile1
Q12
median4
Q310
95-th percentile82
Maximum1303
Range1309
Interquartile range (IQR)8

Descriptive statistics

Standard deviation95.576729
Coefficient of variation (CV)3.8719131
Kurtosis61.148053
Mean24.684627
Median Absolute Deviation (MAD)3
Skewness7.3726107
Sum218533
Variance9134.9111
MonotonicityNot monotonic
2023-12-12T09:44:01.049316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1531
15.3%
2 1439
14.4%
3 1116
11.2%
4 757
 
7.6%
5 459
 
4.6%
6 377
 
3.8%
7 262
 
2.6%
8 234
 
2.3%
9 180
 
1.8%
10 157
 
1.6%
Other values (287) 2341
23.4%
(Missing) 1147
11.5%
ValueCountFrequency (%)
-6 2
 
< 0.1%
-5 4
 
< 0.1%
-4 7
 
0.1%
-3 10
 
0.1%
-2 27
 
0.3%
-1 27
 
0.3%
0 59
 
0.6%
1 1531
15.3%
2 1439
14.4%
3 1116
11.2%
ValueCountFrequency (%)
1303 1
< 0.1%
1302 1
< 0.1%
1301 1
< 0.1%
1106 1
< 0.1%
1105 1
< 0.1%
1104 1
< 0.1%
1103 1
< 0.1%
1102 1
< 0.1%
1101 1
< 0.1%
1004 1
< 0.1%

예정지번
Text

MISSING 

Distinct3599
Distinct (%)50.8%
Missing2919
Missing (%)29.2%
Memory size156.2 KiB
2023-12-12T09:44:01.399811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length5.4728146
Min length3

Characters and Unicode

Total characters38753
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

Unique2026 ?
Unique (%)28.6%

Sample

1st row421-3
2nd row210-1
3rd row933-10
4th row424-2
5th row940-7
ValueCountFrequency (%)
13-0 14
 
0.2%
302-2 14
 
0.2%
517-1 12
 
0.2%
504-1 11
 
0.2%
306-2 11
 
0.2%
800-2 11
 
0.2%
116-2 10
 
0.1%
5-0 10
 
0.1%
116-1 10
 
0.1%
206-3 10
 
0.1%
Other values (3589) 6968
98.4%
2023-12-12T09:44:01.973866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 7081
18.3%
1 6755
17.4%
0 6109
15.8%
2 4278
11.0%
3 3732
9.6%
4 2358
 
6.1%
5 2326
 
6.0%
6 2264
 
5.8%
8 1382
 
3.6%
7 1339
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31672
81.7%
Dash Punctuation 7081
 
18.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6755
21.3%
0 6109
19.3%
2 4278
13.5%
3 3732
11.8%
4 2358
 
7.4%
5 2326
 
7.3%
6 2264
 
7.1%
8 1382
 
4.4%
7 1339
 
4.2%
9 1129
 
3.6%
Dash Punctuation
ValueCountFrequency (%)
- 7081
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 38753
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 7081
18.3%
1 6755
17.4%
0 6109
15.8%
2 4278
11.0%
3 3732
9.6%
4 2358
 
6.1%
5 2326
 
6.0%
6 2264
 
5.8%
8 1382
 
3.6%
7 1339
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38753
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 7081
18.3%
1 6755
17.4%
0 6109
15.8%
2 4278
11.0%
3 3732
9.6%
4 2358
 
6.1%
5 2326
 
6.0%
6 2264
 
5.8%
8 1382
 
3.6%
7 1339
 
3.5%

확정지번
Text

MISSING 

Distinct1762
Distinct (%)54.2%
Missing6749
Missing (%)67.5%
Memory size156.2 KiB
2023-12-12T09:44:02.366733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.4918487
Min length1

Characters and Unicode

Total characters17854
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

Unique944 ?
Unique (%)29.0%

Sample

1st row1466-5
2nd row1118-1
3rd row1496-8
4th row570-0
5th row1151-1
ValueCountFrequency (%)
0-0 98
 
3.0%
680-0 11
 
0.3%
0 9
 
0.3%
1151-1 8
 
0.2%
517-1 8
 
0.2%
668-0 8
 
0.2%
978-3 8
 
0.2%
1151-2 8
 
0.2%
978-2 7
 
0.2%
592-2 7
 
0.2%
Other values (1752) 3079
94.7%
2023-12-12T09:44:03.025572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3303
18.5%
- 3242
18.2%
0 2272
12.7%
6 1458
8.2%
2 1358
7.6%
5 1212
 
6.8%
3 1139
 
6.4%
4 1087
 
6.1%
8 946
 
5.3%
9 942
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14612
81.8%
Dash Punctuation 3242
 
18.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3303
22.6%
0 2272
15.5%
6 1458
10.0%
2 1358
9.3%
5 1212
 
8.3%
3 1139
 
7.8%
4 1087
 
7.4%
8 946
 
6.5%
9 942
 
6.4%
7 895
 
6.1%
Dash Punctuation
ValueCountFrequency (%)
- 3242
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17854
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3303
18.5%
- 3242
18.2%
0 2272
12.7%
6 1458
8.2%
2 1358
7.6%
5 1212
 
6.8%
3 1139
 
6.4%
4 1087
 
6.1%
8 946
 
5.3%
9 942
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17854
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3303
18.5%
- 3242
18.2%
0 2272
12.7%
6 1458
8.2%
2 1358
7.6%
5 1212
 
6.8%
3 1139
 
6.4%
4 1087
 
6.1%
8 946
 
5.3%
9 942
 
5.3%

공급용도
Text

MISSING 

Distinct69
Distinct (%)0.7%
Missing120
Missing (%)1.2%
Memory size156.2 KiB
2023-12-12T09:44:03.246125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length19
Mean length7.130668
Min length2

Characters and Unicode

Total characters70451
Distinct characters116
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)0.1%

Sample

1st row지원시설용지(산단)
2nd row중심상업용지
3rd row근린생활시설
4th row지원시설용지(산단)
5th row준주거용지
ValueCountFrequency (%)
점포겸용 2593
20.4%
실수요자택지 2582
20.3%
근린생활시설 1987
15.6%
일반상업용지 1525
12.0%
주차장 765
 
6.0%
준주거용지 617
 
4.9%
근린상업용지 459
 
3.6%
일반업무시설 328
 
2.6%
지원시설용지(산단 282
 
2.2%
중심상업용지 186
 
1.5%
Other values (67) 1397
11.0%
2023-12-12T09:44:03.882696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 6698
 
9.5%
용 6341
 
9.0%
설 3132
 
4.4%
시 3131
 
4.4%
2841
 
4.0%
자 2837
 
4.0%
택 2741
 
3.9%
업 2683
 
3.8%
겸 2593
 
3.7%
포 2593
 
3.7%
Other values (106) 34861
49.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 66635
94.6%
Space Separator 2841
 
4.0%
Close Punctuation 338
 
0.5%
Open Punctuation 338
 
0.5%
Decimal Number 176
 
0.2%
Other Symbol 50
 
0.1%
Math Symbol 34
 
< 0.1%
Other Punctuation 31
 
< 0.1%
Dash Punctuation 5
 
< 0.1%
Uppercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 6698
 
10.1%
용 6341
 
9.5%
설 3132
 
4.7%
시 3131
 
4.7%
자 2837
 
4.3%
택 2741
 
4.1%
업 2683
 
4.0%
겸 2593
 
3.9%
포 2593
 
3.9%
점 2593
 
3.9%
Other values (90) 31293
47.0%
Decimal Number
ValueCountFrequency (%)
5 47
26.7%
8 46
26.1%
0 41
23.3%
6 40
22.7%
1 1
 
0.6%
2 1
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
S 1
33.3%
O 1
33.3%
C 1
33.3%
Space Separator
ValueCountFrequency (%)
2841
100.0%
Close Punctuation
ValueCountFrequency (%)
) 338
100.0%
Open Punctuation
ValueCountFrequency (%)
( 338
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 50
100.0%
Math Symbol
ValueCountFrequency (%)
~ 34
100.0%
Other Punctuation
ValueCountFrequency (%)
· 31
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 66635
94.6%
Common 3813
 
5.4%
Latin 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 6698
 
10.1%
용 6341
 
9.5%
설 3132
 
4.7%
시 3131
 
4.7%
자 2837
 
4.3%
택 2741
 
4.1%
업 2683
 
4.0%
겸 2593
 
3.9%
포 2593
 
3.9%
점 2593
 
3.9%
Other values (90) 31293
47.0%
Common
ValueCountFrequency (%)
2841
74.5%
) 338
 
8.9%
( 338
 
8.9%
㎡ 50
 
1.3%
5 47
 
1.2%
8 46
 
1.2%
0 41
 
1.1%
6 40
 
1.0%
~ 34
 
0.9%
· 31
 
0.8%
Other values (3) 7
 
0.2%
Latin
ValueCountFrequency (%)
S 1
33.3%
O 1
33.3%
C 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 66635
94.6%
ASCII 3735
 
5.3%
CJK Compat 50
 
0.1%
None 31
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 6698
 
10.1%
용 6341
 
9.5%
설 3132
 
4.7%
시 3131
 
4.7%
자 2837
 
4.3%
택 2741
 
4.1%
업 2683
 
4.0%
겸 2593
 
3.9%
포 2593
 
3.9%
점 2593
 
3.9%
Other values (90) 31293
47.0%
ASCII
ValueCountFrequency (%)
2841
76.1%
) 338
 
9.0%
( 338
 
9.0%
5 47
 
1.3%
8 46
 
1.2%
0 41
 
1.1%
6 40
 
1.1%
~ 34
 
0.9%
- 5
 
0.1%
1 1
 
< 0.1%
Other values (4) 4
 
0.1%
CJK Compat
ValueCountFrequency (%)
㎡ 50
100.0%
None
ValueCountFrequency (%)
· 31
100.0%

공급방법.1
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반경쟁입찰
6984 
입찰후수의
1953 
분양후수의
724 
<NA>
 
138
입찰
 
109
Other values (5)
 
92

Length

Max length6
Median length6
Mean length5.6457
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row입찰후수의
3rd row일반경쟁입찰
4th row분양후수의
5th row입찰후수의

Common Values

ValueCountFrequency (%)
일반경쟁입찰 6984
69.8%
입찰후수의 1953
 
19.5%
분양후수의 724
 
7.2%
<NA> 138
 
1.4%
입찰 109
 
1.1%
순수수의 58
 
0.6%
제한경쟁입찰 15
 
0.1%
추첨분양 15
 
0.1%
지명경쟁입찰 2
 
< 0.1%
기타 2
 
< 0.1%

Length

2023-12-12T09:44:04.054340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:44:04.209847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반경쟁입찰 6984
69.8%
입찰후수의 1953
 
19.5%
분양후수의 724
 
7.2%
na 138
 
1.4%
입찰 109
 
1.1%
순수수의 58
 
0.6%
제한경쟁입찰 15
 
0.1%
추첨분양 15
 
0.1%
지명경쟁입찰 2
 
< 0.1%
기타 2
 
< 0.1%

가분할면적(제곱미터)
Real number (ℝ)

MISSING  SKEWED 

Distinct2559
Distinct (%)25.9%
Missing120
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean2340.4618
Minimum14.9
Maximum690855
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:44:04.373257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14.9
5-th percentile248
Q1316.1
median751
Q31324
95-th percentile5725.2
Maximum690855
Range690840.1
Interquartile range (IQR)1007.9

Descriptive statistics

Standard deviation18284.557
Coefficient of variation (CV)7.8123716
Kurtosis964.96088
Mean2340.4618
Median Absolute Deviation (MAD)454
Skewness29.082686
Sum23123763
Variance3.3432504 × 108
MonotonicityNot monotonic
2023-12-12T09:44:04.545781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
265.0 117
 
1.2%
266.0 76
 
0.8%
297.0 71
 
0.7%
259.0 66
 
0.7%
220.0 59
 
0.6%
260.0 58
 
0.6%
252.0 57
 
0.6%
285.0 55
 
0.5%
248.0 49
 
0.5%
284.0 48
 
0.5%
Other values (2549) 9224
92.2%
(Missing) 120
 
1.2%
ValueCountFrequency (%)
14.9 1
 
< 0.1%
26.0 2
< 0.1%
29.0 1
 
< 0.1%
42.0 2
< 0.1%
47.0 1
 
< 0.1%
52.5565 1
 
< 0.1%
70.0 2
< 0.1%
79.0 2
< 0.1%
82.0 4
< 0.1%
123.0 2
< 0.1%
ValueCountFrequency (%)
690855.0 4
< 0.1%
405445.0 4
< 0.1%
382799.0 1
 
< 0.1%
373040.0 2
< 0.1%
213452.0 2
< 0.1%
102189.5 1
 
< 0.1%
97694.0 4
< 0.1%
97391.0 3
< 0.1%
93460.0 2
< 0.1%
70422.0 1
 
< 0.1%

확정면적(제곱미터)
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct1938
Distinct (%)19.6%
Missing120
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean1364.595
Minimum0
Maximum691083.1
Zeros6070
Zeros (%)60.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:44:04.730921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3569.95
95-th percentile2844.57
Maximum691083.1
Range691083.1
Interquartile range (IQR)569.95

Descriptive statistics

Standard deviation17521.332
Coefficient of variation (CV)12.83995
Kurtosis1129.8906
Mean1364.595
Median Absolute Deviation (MAD)0
Skewness32.044217
Sum13482199
Variance3.0699707 × 108
MonotonicityNot monotonic
2023-12-12T09:44:04.897765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 6070
60.7%
280.8 15
 
0.1%
250.7 15
 
0.1%
296.7 14
 
0.1%
283.9 11
 
0.1%
270.0 11
 
0.1%
271.9 10
 
0.1%
288.0 10
 
0.1%
606.0 9
 
0.1%
299.7 9
 
0.1%
Other values (1928) 3706
37.1%
(Missing) 120
 
1.2%
ValueCountFrequency (%)
0.0 6070
60.7%
14.9 1
 
< 0.1%
26.0 2
 
< 0.1%
29.0 1
 
< 0.1%
42.0 2
 
< 0.1%
47.0 1
 
< 0.1%
52.5565 1
 
< 0.1%
70.0 2
 
< 0.1%
79.0 2
 
< 0.1%
82.0 4
 
< 0.1%
ValueCountFrequency (%)
691083.1 4
< 0.1%
405225.3 4
< 0.1%
373040.0 2
 
< 0.1%
212884.7 2
 
< 0.1%
102189.5 1
 
< 0.1%
93460.0 2
 
< 0.1%
89979.8 1
 
< 0.1%
74968.2 1
 
< 0.1%
40671.1 1
 
< 0.1%
37159.1 5
0.1%

공급예정금액
Real number (ℝ)

MISSING  SKEWED 

Distinct5985
Distinct (%)60.6%
Missing120
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean3.861044 × 109
Minimum2460000
Maximum8.03 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:44:05.138287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2460000
5-th percentile1.53068 × 108
Q14.250034 × 108
median1.20638 × 109
Q33.1917862 × 109
95-th percentile1.10205 × 1010
Maximum8.03 × 1011
Range8.0299754 × 1011
Interquartile range (IQR)2.7667828 × 109

Descriptive statistics

Standard deviation1.7128416 × 1010
Coefficient of variation (CV)4.4362135
Kurtosis803.14417
Mean3.861044 × 109
Median Absolute Deviation (MAD)8.897802 × 108
Skewness23.481017
Sum3.8147115 × 1013
Variance2.9338262 × 1020
MonotonicityNot monotonic
2023-12-12T09:44:05.310850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
70760000 28
 
0.3%
419370000 18
 
0.2%
170130000 16
 
0.2%
531500000 15
 
0.1%
692300000 14
 
0.1%
173840000 14
 
0.1%
4412500000 12
 
0.1%
325000000 12
 
0.1%
418950000 12
 
0.1%
383620000 12
 
0.1%
Other values (5975) 9727
97.3%
(Missing) 120
 
1.2%
ValueCountFrequency (%)
2460000 1
< 0.1%
6407000 1
< 0.1%
6707100 1
< 0.1%
7728000 2
< 0.1%
8282000 1
< 0.1%
9460000 1
< 0.1%
11310000 1
< 0.1%
13234000 2
< 0.1%
13930000 2
< 0.1%
14536000 2
< 0.1%
ValueCountFrequency (%)
803000000000 1
< 0.1%
613000000000 1
< 0.1%
454000000000 1
< 0.1%
430000000000 1
< 0.1%
411000000000 1
< 0.1%
269000000000 1
< 0.1%
258000000000 1
< 0.1%
256000000000 2
< 0.1%
243000000000 2
< 0.1%
223000000000 1
< 0.1%

Sample

지역본부공고명공고종류공고게시일계약체결개시일계약체결종료일매물위치공급방법입찰신청접수개시일시입찰신청접수종료일시개찰결과게시일시사업지구블록가구번호획지위치예정지번확정지번공급용도공급방법.1가분할면적(제곱미터)확정면적(제곱미터)공급예정금액
3830경기지역본부[첨부파일 정정공고] 성남여수 근린생활시설용지 및 종교시설용지 공급공고정정공고2019-05-092019-05-302019-06-05경기 성남시 용인시 수원시입찰 추첨2019-05-22 10:002019-05-23 15:00<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1195인천지역본부부천오정물류단지 지원시설, 주차장용지 공급공고일반공고2020-05-222020-06-292020-06-30경기 부천시입찰2020-06-22 10:002020-06-22 16:002020-06-22 17:00부천오정물류단지0319421-3<NA>지원시설용지(산단)입찰후수의1221.00.03003660000
10413경기지역본부화성향남2지구 상업용지 공급공고일반공고2016-01-142016-01-282016-01-28경기 화성시입찰2016-01-21 10:002016-01-21 16:002016-01-21 17:30화성향남203524<NA>1466-5중심상업용지일반경쟁입찰969.8969.83248830000
7308경기지역본부평택청북 근린상업용지,근린생활시설용지,준주거용지 공급공고일반공고2017-10-182017-11-022017-11-02경기 평택시입찰2017-10-26 10:002017-10-26 15:002017-10-26 17:30평택청북03115210-11118-1근린생활시설분양후수의746.0746.3865800000
5483전북지역본부정읍첨단 지원시설용지 공급 재공고일반공고2018-10-152018-11-052018-11-07전북 정읍시입찰2018-10-30 10:002018-10-31 16:002018-10-31 18:00정읍첨단0585<NA>1496-8지원시설용지(산단)입찰후수의2044.02043.8392410000
2814경기지역본부화성 남양뉴타운지구 준주거용지 공급공고일반공고2019-08-022019-09-032019-09-09경기 화성시입찰2019-08-19 09:002019-08-19 15:002019-08-19 16:30남양뉴타운03285933-10<NA>준주거용지입찰후수의403.0403.0814060000
10320대구경북지역본부경산3일반산업단지 주차장용지 재입찰공고일반공고2016-02-262016-03-212016-03-22대구 동구입찰2016-03-11 10:002016-03-11 16:002016-03-11 18:00경산진량201101<NA>570-0주차장입찰후수의4684.04683.7749400000
7058대구경북지역본부대구신서혁신도시 유통업무용지 공급공고일반공고2017-11-282017-12-122017-12-14대구 동구입찰2017-12-05 10:002017-12-06 16:002017-12-06 18:00대구신서2632424-21151-1유통업무시설입찰후수의8508.08508.011060400000
6642경기지역본부화성 남양뉴타운 준주거·일반상업·주차장용지 공급공고일반공고2018-04-122018-05-142018-05-15경기 화성시입찰2018-05-02 10:002018-05-03 14:002018-05-03 17:30남양뉴타운03253940-7<NA>준주거용지일반경쟁입찰385.00.0873950000
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