Overview

Dataset statistics

Number of variables4
Number of observations132
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.6 KiB
Average record size in memory36.0 B

Variable types

Text1
Numeric3

Dataset

Description온비드 월별 입찰참가자 현황 및 추이 분석을 위한 2013년부터 2023년까지의 정보를 제공합니다. 월별 캠코공매물건, 이용기관공매물건의 입찰참가자 수의 정보를 담고 있습니다.
Author한국자산관리공사
URLhttps://www.data.go.kr/data/15120358/fileData.do

Alerts

이용기관공매물건 is highly overall correlated with 합계High correlation
합계 is highly overall correlated with 이용기관공매물건High correlation
연월 has unique valuesUnique
합계 has unique valuesUnique

Reproduction

Analysis started2024-03-14 14:23:39.253947
Analysis finished2024-03-14 14:23:42.044550
Duration2.79 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연월
Text

UNIQUE 

Distinct132
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-03-14T23:23:42.620327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length21
Mean length21
Min length21

Characters and Unicode

Total characters2772
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique132 ?
Unique (%)100.0%

Sample

1st row2013-01-01~2013-01-31
2nd row2013-02-01~2013-02-28
3rd row2013-03-01~2013-03-31
4th row2013-04-01~2013-04-30
5th row2013-05-01~2013-05-31
ValueCountFrequency (%)
2013-01-01~2013-01-31 1
 
0.8%
2019-11-01~2019-11-30 1
 
0.8%
2021-02-01~2021-02-29 1
 
0.8%
2021-01-01~2021-01-31 1
 
0.8%
2020-12-01~2020-12-31 1
 
0.8%
2020-11-01~2020-11-30 1
 
0.8%
2020-10-01~2020-10-31 1
 
0.8%
2020-09-01~2020-09-30 1
 
0.8%
2020-08-01~2020-08-31 1
 
0.8%
2020-07-01~2020-07-31 1
 
0.8%
Other values (122) 122
92.4%
2024-03-14T23:23:43.532643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 684
24.7%
- 528
19.0%
1 511
18.4%
2 439
15.8%
3 191
 
6.9%
~ 132
 
4.8%
9 54
 
1.9%
8 49
 
1.8%
4 46
 
1.7%
5 46
 
1.7%
Other values (2) 92
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2112
76.2%
Dash Punctuation 528
 
19.0%
Math Symbol 132
 
4.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 684
32.4%
1 511
24.2%
2 439
20.8%
3 191
 
9.0%
9 54
 
2.6%
8 49
 
2.3%
4 46
 
2.2%
5 46
 
2.2%
6 46
 
2.2%
7 46
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 528
100.0%
Math Symbol
ValueCountFrequency (%)
~ 132
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2772
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 684
24.7%
- 528
19.0%
1 511
18.4%
2 439
15.8%
3 191
 
6.9%
~ 132
 
4.8%
9 54
 
1.9%
8 49
 
1.8%
4 46
 
1.7%
5 46
 
1.7%
Other values (2) 92
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2772
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 684
24.7%
- 528
19.0%
1 511
18.4%
2 439
15.8%
3 191
 
6.9%
~ 132
 
4.8%
9 54
 
1.9%
8 49
 
1.8%
4 46
 
1.7%
5 46
 
1.7%
Other values (2) 92
 
3.3%

캠코공매물건
Real number (ℝ)

Distinct128
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2262.1667
Minimum844
Maximum6971
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-14T23:23:43.930873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum844
5-th percentile1252.85
Q11668.25
median2003
Q32555.75
95-th percentile4057.8
Maximum6971
Range6127
Interquartile range (IQR)887.5

Descriptive statistics

Standard deviation975.17835
Coefficient of variation (CV)0.43108157
Kurtosis6.5736504
Mean2262.1667
Median Absolute Deviation (MAD)415
Skewness2.1597789
Sum298606
Variance950972.81
MonotonicityNot monotonic
2024-03-14T23:23:44.366286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2144 2
 
1.5%
1367 2
 
1.5%
1990 2
 
1.5%
1447 2
 
1.5%
2103 1
 
0.8%
2105 1
 
0.8%
2620 1
 
0.8%
2349 1
 
0.8%
3349 1
 
0.8%
2728 1
 
0.8%
Other values (118) 118
89.4%
ValueCountFrequency (%)
844 1
0.8%
982 1
0.8%
1007 1
0.8%
1114 1
0.8%
1193 1
0.8%
1210 1
0.8%
1238 1
0.8%
1265 1
0.8%
1268 1
0.8%
1320 1
0.8%
ValueCountFrequency (%)
6971 1
0.8%
6505 1
0.8%
5283 1
0.8%
5144 1
0.8%
4781 1
0.8%
4102 1
0.8%
4060 1
0.8%
4056 1
0.8%
3888 1
0.8%
3790 1
0.8%

이용기관공매물건
Real number (ℝ)

HIGH CORRELATION 

Distinct131
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12270.674
Minimum5237
Maximum42863
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-14T23:23:44.790784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5237
5-th percentile6706.75
Q19753.5
median11667.5
Q313644.25
95-th percentile18581.4
Maximum42863
Range37626
Interquartile range (IQR)3890.75

Descriptive statistics

Standard deviation5162.6861
Coefficient of variation (CV)0.4207337
Kurtosis16.461605
Mean12270.674
Median Absolute Deviation (MAD)1977
Skewness3.3609155
Sum1619729
Variance26653328
MonotonicityNot monotonic
2024-03-14T23:23:45.239940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10663 2
 
1.5%
6671 1
 
0.8%
11752 1
 
0.8%
11308 1
 
0.8%
11742 1
 
0.8%
33340 1
 
0.8%
14001 1
 
0.8%
15092 1
 
0.8%
15548 1
 
0.8%
17601 1
 
0.8%
Other values (121) 121
91.7%
ValueCountFrequency (%)
5237 1
0.8%
5464 1
0.8%
5595 1
0.8%
5977 1
0.8%
6080 1
0.8%
6618 1
0.8%
6671 1
0.8%
6736 1
0.8%
6997 1
0.8%
7041 1
0.8%
ValueCountFrequency (%)
42863 1
0.8%
40369 1
0.8%
33340 1
0.8%
21431 1
0.8%
19848 1
0.8%
19582 1
0.8%
18940 1
0.8%
18288 1
0.8%
17716 1
0.8%
17601 1
0.8%

합계
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct132
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14532.841
Minimum6735
Maximum44611
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-14T23:23:45.652773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6735
5-th percentile8073.05
Q111608.25
median13635
Q316074.75
95-th percentile21313.1
Maximum44611
Range37876
Interquartile range (IQR)4466.5

Descriptive statistics

Standard deviation5413.6455
Coefficient of variation (CV)0.37251117
Kurtosis13.756637
Mean14532.841
Median Absolute Deviation (MAD)2213.5
Skewness2.9601346
Sum1918335
Variance29307558
MonotonicityNot monotonic
2024-03-14T23:23:46.110717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8087 1
 
0.8%
15801 1
 
0.8%
14305 1
 
0.8%
13320 1
 
0.8%
12292 1
 
0.8%
19695 1
 
0.8%
15896 1
 
0.8%
19600 1
 
0.8%
20004 1
 
0.8%
13855 1
 
0.8%
Other values (122) 122
92.4%
ValueCountFrequency (%)
6735 1
0.8%
6911 1
0.8%
6962 1
0.8%
6984 1
0.8%
7600 1
0.8%
7738 1
0.8%
8056 1
0.8%
8087 1
0.8%
8723 1
0.8%
9013 1
0.8%
ValueCountFrequency (%)
44611 1
0.8%
43846 1
0.8%
35445 1
0.8%
24369 1
0.8%
23334 1
0.8%
21813 1
0.8%
21499 1
0.8%
21161 1
0.8%
20289 1
0.8%
20049 1
0.8%

Interactions

2024-03-14T23:23:40.739686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:23:39.385767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:23:40.174606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:23:41.113393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:23:39.639635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:23:40.394089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:23:41.286436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:23:39.903158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:23:40.570918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T23:23:46.388962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
캠코공매물건이용기관공매물건합계
캠코공매물건1.0000.2680.493
이용기관공매물건0.2681.0000.991
합계0.4930.9911.000
2024-03-14T23:23:46.628224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
캠코공매물건이용기관공매물건합계
캠코공매물건1.0000.2880.464
이용기관공매물건0.2881.0000.969
합계0.4640.9691.000

Missing values

2024-03-14T23:23:41.647979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T23:23:41.931020image/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

연월캠코공매물건이용기관공매물건합계
02013-01-01~2013-01-31141666718087
12013-02-01~2013-02-2898266187600
22013-03-01~2013-03-31132067368056
32013-04-01~2013-04-30136780769443
42013-05-01~2013-05-312029895810987
52013-06-01~2013-06-301672930710979
62013-07-01~2013-07-311929867610605
72013-08-01~2013-08-312251816910420
82013-09-01~2013-09-30165860807738
92013-10-01~2013-10-31245870419499
연월캠코공매물건이용기관공매물건합계
1222023-03-01~2023-03-3116601283514495
1232023-04-01~2023-04-3016011380915410
1242023-05-01~2023-05-3119511204313994
1252023-06-01~2023-06-3024201013112551
1262023-07-01~2023-07-3119081131813226
1272023-08-01~2023-08-3121441404616190
1282023-09-01~2023-09-3018771248614363
1292023-10-01~2023-10-312497999312490
1302023-11-01~2023-11-3017031297514678
1312023-12-01~2023-12-3115291557917108