Overview

Dataset statistics

Number of variables5
Number of observations1732
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory71.2 KiB
Average record size in memory42.1 B

Variable types

Numeric2
Text2
Categorical1

Dataset

Description한국자산관리공사법(제2조1호, 26조제1항제5호 및 제11호) 및 동법시행령에 따라 금융기관 등으로부터 매각 위탁 받은 자산의 공고 정보입니다.
Author한국자산관리공사
URLhttps://www.data.go.kr/data/15012310/fileData.do

Alerts

최저매매가격 is highly overall correlated with 위임기관High correlation
위임기관 is highly overall correlated with 최저매매가격High correlation
위임기관 is highly imbalanced (53.5%)Imbalance

Reproduction

Analysis started2024-03-14 21:05:39.465935
Analysis finished2024-03-14 21:05:41.369563
Duration1.9 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

공고회차
Real number (ℝ)

Distinct12
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.3770208
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.3 KiB
2024-03-15T06:05:41.475957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q15
median8
Q310
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.2360267
Coefficient of variation (CV)0.43866309
Kurtosis-1.0115029
Mean7.3770208
Median Absolute Deviation (MAD)3
Skewness-0.25455009
Sum12777
Variance10.471869
MonotonicityIncreasing
2024-03-15T06:05:41.676368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
12 200
11.5%
10 187
10.8%
11 172
9.9%
8 166
9.6%
9 162
9.4%
6 159
9.2%
7 154
8.9%
4 149
8.6%
3 131
7.6%
5 131
7.6%
Other values (2) 121
7.0%
ValueCountFrequency (%)
1 89
5.1%
2 32
 
1.8%
3 131
7.6%
4 149
8.6%
5 131
7.6%
6 159
9.2%
7 154
8.9%
8 166
9.6%
9 162
9.4%
10 187
10.8%
ValueCountFrequency (%)
12 200
11.5%
11 172
9.9%
10 187
10.8%
9 162
9.4%
8 166
9.6%
7 154
8.9%
6 159
9.2%
5 131
7.6%
4 149
8.6%
3 131
7.6%

물건번호
Text

Distinct269
Distinct (%)15.5%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
2024-03-15T06:05:42.757609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters24248
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

Unique26 ?
Unique (%)1.5%

Sample

1st row2022-00002-001
2nd row2022-00030-001
3rd row2022-00033-001
4th row2022-00039-001
5th row2022-00039-002
ValueCountFrequency (%)
2018-00023-001 12
 
0.7%
2022-00047-001 11
 
0.6%
2022-00047-013 11
 
0.6%
2022-00047-014 11
 
0.6%
2022-00039-038 11
 
0.6%
2022-00047-032 11
 
0.6%
2022-00047-002 11
 
0.6%
2022-00047-003 11
 
0.6%
2022-00047-004 11
 
0.6%
2022-00047-006 11
 
0.6%
Other values (259) 1621
93.6%
2024-03-15T06:05:43.943409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10309
42.5%
2 4534
18.7%
- 3464
 
14.3%
3 1549
 
6.4%
1 1280
 
5.3%
4 1195
 
4.9%
7 551
 
2.3%
9 530
 
2.2%
5 327
 
1.3%
6 263
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20784
85.7%
Dash Punctuation 3464
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10309
49.6%
2 4534
21.8%
3 1549
 
7.5%
1 1280
 
6.2%
4 1195
 
5.7%
7 551
 
2.7%
9 530
 
2.6%
5 327
 
1.6%
6 263
 
1.3%
8 246
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 3464
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24248
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10309
42.5%
2 4534
18.7%
- 3464
 
14.3%
3 1549
 
6.4%
1 1280
 
5.3%
4 1195
 
4.9%
7 551
 
2.3%
9 530
 
2.2%
5 327
 
1.3%
6 263
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24248
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10309
42.5%
2 4534
18.7%
- 3464
 
14.3%
3 1549
 
6.4%
1 1280
 
5.3%
4 1195
 
4.9%
7 551
 
2.3%
9 530
 
2.2%
5 327
 
1.3%
6 263
 
1.1%

위임기관
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct48
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
한국수력원자력주식회사
1132 
기술보증기금
 
70
한국전력
 
66
대한지적공사
 
54
양도세
 
31
Other values (43)
379 

Length

Max length11
Median length11
Mean length9.3285219
Min length3

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row한국수력원자력주식회사
2nd row한국과학기술정보연구원
3rd row양도세
4th row한국수력원자력주식회사
5th row한국수력원자력주식회사

Common Values

ValueCountFrequency (%)
한국수력원자력주식회사 1132
65.4%
기술보증기금 70
 
4.0%
한국전력 66
 
3.8%
대한지적공사 54
 
3.1%
양도세 31
 
1.8%
송라신용협동조합 30
 
1.7%
가스공사 28
 
1.6%
한국남동발전(주) 27
 
1.6%
한국과학기술정보연구원 25
 
1.4%
머스트삼일저축 23
 
1.3%
Other values (38) 246
 
14.2%

Length

2024-03-15T06:05:44.420940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한국수력원자력주식회사 1132
65.4%
기술보증기금 70
 
4.0%
한국전력 66
 
3.8%
대한지적공사 54
 
3.1%
양도세 31
 
1.8%
송라신용협동조합 30
 
1.7%
가스공사 28
 
1.6%
한국남동발전(주 27
 
1.6%
한국과학기술정보연구원 25
 
1.4%
머스트삼일저축 23
 
1.3%
Other values (38) 246
 
14.2%

소재지
Text

Distinct244
Distinct (%)14.1%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
2024-03-15T06:05:46.033413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length143
Median length71
Mean length38.107968
Min length23

Characters and Unicode

Total characters66003
Distinct characters275
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)0.9%

Sample

1st row경기도 가평군 청평면 청평리 691-5번지 691-6, 691-10, 691-15, 714-1 (청평면)
2nd row대구광역시 남구 봉덕동 산89-3번지 외 5필지 미리내아파트 제7동 제9층 제901호
3rd row서울특별시 구로구 구로동 (1265번지) 제110동 제14층 제 1405호 구로두산아파트 (구로동)
4th row경상북도 영덕군 영덕읍 노물리 265-1번지외 10필지(영덕읍)
5th row경상북도 영덕군 영덕읍 노물리 296번지외 2필지 (영덕읍)
ValueCountFrequency (%)
영덕읍 2233
 
17.2%
경상북도 1212
 
9.3%
영덕군 1122
 
8.6%
노물리 398
 
3.1%
석리 368
 
2.8%
매정리 356
 
2.7%
경상남도 154
 
1.2%
90
 
0.7%
등 87
 
0.7%
경기도 83
 
0.6%
Other values (733) 6911
53.1%
2024-03-15T06:05:47.673094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12236
 
18.5%
영 3435
 
5.2%
덕 3399
 
5.1%
읍 2277
 
3.4%
1 2178
 
3.3%
지 1984
 
3.0%
) 1886
 
2.9%
( 1886
 
2.9%
도 1800
 
2.7%
번 1753
 
2.7%
Other values (265) 33169
50.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 36479
55.3%
Space Separator 12236
 
18.5%
Decimal Number 11327
 
17.2%
Close Punctuation 1891
 
2.9%
Open Punctuation 1891
 
2.9%
Other Punctuation 1102
 
1.7%
Dash Punctuation 981
 
1.5%
Uppercase Letter 80
 
0.1%
Math Symbol 10
 
< 0.1%
Lowercase Letter 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 3435
 
9.4%
덕 3399
 
9.3%
읍 2277
 
6.2%
지 1984
 
5.4%
도 1800
 
4.9%
번 1753
 
4.8%
리 1529
 
4.2%
경 1449
 
4.0%
상 1407
 
3.9%
북 1337
 
3.7%
Other values (238) 16109
44.2%
Decimal Number
ValueCountFrequency (%)
1 2178
19.2%
2 1550
13.7%
3 1392
12.3%
5 1172
10.3%
4 1090
9.6%
0 1000
8.8%
6 989
8.7%
8 697
 
6.2%
9 649
 
5.7%
7 610
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
H 31
38.8%
E 28
35.0%
S 6
 
7.5%
K 6
 
7.5%
U 3
 
3.8%
B 3
 
3.8%
Y 3
 
3.8%
Close Punctuation
ValueCountFrequency (%)
) 1886
99.7%
] 5
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 1886
99.7%
[ 5
 
0.3%
Lowercase Letter
ValueCountFrequency (%)
s 3
50.0%
k 3
50.0%
Space Separator
ValueCountFrequency (%)
12236
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1102
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 981
100.0%
Math Symbol
ValueCountFrequency (%)
~ 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 36479
55.3%
Common 29438
44.6%
Latin 86
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 3435
 
9.4%
덕 3399
 
9.3%
읍 2277
 
6.2%
지 1984
 
5.4%
도 1800
 
4.9%
번 1753
 
4.8%
리 1529
 
4.2%
경 1449
 
4.0%
상 1407
 
3.9%
북 1337
 
3.7%
Other values (238) 16109
44.2%
Common
ValueCountFrequency (%)
12236
41.6%
1 2178
 
7.4%
) 1886
 
6.4%
( 1886
 
6.4%
2 1550
 
5.3%
3 1392
 
4.7%
5 1172
 
4.0%
, 1102
 
3.7%
4 1090
 
3.7%
0 1000
 
3.4%
Other values (8) 3946
 
13.4%
Latin
ValueCountFrequency (%)
H 31
36.0%
E 28
32.6%
S 6
 
7.0%
K 6
 
7.0%
s 3
 
3.5%
U 3
 
3.5%
k 3
 
3.5%
B 3
 
3.5%
Y 3
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 36479
55.3%
ASCII 29524
44.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12236
41.4%
1 2178
 
7.4%
) 1886
 
6.4%
( 1886
 
6.4%
2 1550
 
5.2%
3 1392
 
4.7%
5 1172
 
4.0%
, 1102
 
3.7%
4 1090
 
3.7%
0 1000
 
3.4%
Other values (17) 4032
 
13.7%
Hangul
ValueCountFrequency (%)
영 3435
 
9.4%
덕 3399
 
9.3%
읍 2277
 
6.2%
지 1984
 
5.4%
도 1800
 
4.9%
번 1753
 
4.8%
리 1529
 
4.2%
경 1449
 
4.0%
상 1407
 
3.9%
북 1337
 
3.7%
Other values (238) 16109
44.2%

최저매매가격
Real number (ℝ)

HIGH CORRELATION 

Distinct410
Distinct (%)23.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1511415 × 108
Minimum1560000
Maximum7 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.3 KiB
2024-03-15T06:05:47.935533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1560000
5-th percentile9970935
Q138200000
median1.0193755 × 108
Q33.1882625 × 108
95-th percentile1.162882 × 109
Maximum7 × 109
Range6.99844 × 109
Interquartile range (IQR)2.8062625 × 108

Descriptive statistics

Standard deviation6.3147201 × 108
Coefficient of variation (CV)2.0039469
Kurtosis42.29603
Mean3.1511415 × 108
Median Absolute Deviation (MAD)75547900
Skewness5.4209903
Sum5.4577771 × 1011
Variance3.987569 × 1017
MonotonicityNot monotonic
2024-03-15T06:05:48.286443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
38200000 54
 
3.1%
39000000 20
 
1.2%
162500000 20
 
1.2%
14750000 19
 
1.1%
89000000 12
 
0.7%
642900000 12
 
0.7%
71948800 11
 
0.6%
22554800 11
 
0.6%
10238250 11
 
0.6%
2818832740 11
 
0.6%
Other values (400) 1551
89.5%
ValueCountFrequency (%)
1560000 4
 
0.2%
1755000 4
 
0.2%
1950000 8
0.5%
2000000 10
0.6%
2800000 2
 
0.1%
3150000 2
 
0.1%
3410400 2
 
0.1%
3500000 4
 
0.2%
3996200 10
0.6%
5237700 10
0.6%
ValueCountFrequency (%)
7000000000 5
0.3%
5236000000 1
 
0.1%
3512706000 1
 
0.1%
3472000000 5
0.3%
3161435000 1
 
0.1%
3000000000 1
 
0.1%
2850000000 1
 
0.1%
2845291000 1
 
0.1%
2818832740 11
0.6%
2707500000 1
 
0.1%

Interactions

2024-03-15T06:05:40.365918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T06:05:39.831000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T06:05:40.633596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T06:05:40.093242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T06:05:48.479034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공고회차위임기관최저매매가격
공고회차1.0000.3600.000
위임기관0.3601.0000.914
최저매매가격0.0000.9141.000
2024-03-15T06:05:48.641717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공고회차최저매매가격위임기관
공고회차1.000-0.0600.130
최저매매가격-0.0601.0000.641
위임기관0.1300.6411.000

Missing values

2024-03-15T06:05:41.040127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T06:05:41.298756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

공고회차물건번호위임기관소재지최저매매가격
012022-00002-001한국수력원자력주식회사경기도 가평군 청평면 청평리 691-5번지 691-6, 691-10, 691-15, 714-1 (청평면)2135243500
112022-00030-001한국과학기술정보연구원대구광역시 남구 봉덕동 산89-3번지 외 5필지 미리내아파트 제7동 제9층 제901호197224000
212022-00033-001양도세서울특별시 구로구 구로동 (1265번지) 제110동 제14층 제 1405호 구로두산아파트 (구로동)543305000
312022-00039-001한국수력원자력주식회사경상북도 영덕군 영덕읍 노물리 265-1번지외 10필지(영덕읍)599899000
412022-00039-002한국수력원자력주식회사경상북도 영덕군 영덕읍 노물리 296번지외 2필지 (영덕읍)120527000
512022-00039-003한국수력원자력주식회사경상북도 영덕군 영덕읍 노물리 307번지 (영덕읍)80649000
612022-00039-004한국수력원자력주식회사경상북도 영덕군 영덕읍 노물리 308-1번지 (영덕읍)67392000
712022-00039-005한국수력원자력주식회사경상북도 영덕군 영덕읍 노물리 347, 348번지 (영덕읍)332052000
812022-00039-006한국수력원자력주식회사경상북도 영덕군 영덕읍 노물리 352번지 (영덕읍)17585000
912022-00039-008한국수력원자력주식회사경상북도 영덕군 영덕읍 노물리 356, 371, 374, 376번지 (영덕읍)322125000
공고회차물건번호위임기관소재지최저매매가격
1722122016-00024-001교보생명경상남도 통영시 무전동 안개2길 6, (991-7번지) 제5층 제501호 무전빌딩 (무전동)162500000
1723122016-00024-002교보생명경상남도 통영시 무전동 안개2길 6, (991-7번지) 제6층 제601호 무전빌딩 (무전동)162500000
1724122016-00024-003교보생명경상남도 통영시 무전동 안개2길 6, (991-7번지) 제7층 제701호 무전빌딩 (무전동)162500000
1725122016-00024-004교보생명경상남도 통영시 무전동 안개2길 6, (991-7번지) 제8층 제801호 무전빌딩 (무전동)162500000
1726122016-00151-001한국전력충청남도 아산시 영인면 아산리 8번지 , 9-1422950226
1727122015-00007-001더블저축은행전라북도 고창군 고창읍 석정리 627번지150000000
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1730122015-00195-001머스트삼일저축경상북도 포항시 북구 여천동 63-2번지 (지하1층~지상3층)[중앙로298번길 7-4]730000000
1731122011-00108-001청주남부신협충청북도 청주시 상당구 용담동 378번지 올림피아 제6층 제603호69711390