Overview

Dataset statistics

Number of variables7
Number of observations26
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 KiB
Average record size in memory63.1 B

Variable types

Numeric1
Text1
Categorical5

Dataset

Description대구도시개발공사 전세임대 기금유형코드 데이터 입니다. 메타데이터기반 공공데이터 개방자료이기 때문에 가공되지 않은 원본 테이블의 데이터가 등록되었습니다.
URLhttps://www.data.go.kr/data/15120618/fileData.do

Alerts

수정일시 is highly overall correlated with 유형구분 and 3 other fieldsHigh correlation
등록일시 is highly overall correlated with 유형구분 and 3 other fieldsHigh correlation
유형코드 is highly overall correlated with 유형구분 and 1 other fieldsHigh correlation
유형구분 is highly overall correlated with 유형코드 and 3 other fieldsHigh correlation
등록자번호 is highly overall correlated with 등록일시 and 2 other fieldsHigh correlation
수정자번호 is highly overall correlated with 유형코드 and 4 other fieldsHigh correlation
유형코드 has unique valuesUnique

Reproduction

Analysis started2023-12-12 13:07:13.507285
Analysis finished2023-12-12 13:07:14.108419
Duration0.6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

유형코드
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.653846
Minimum1
Maximum33
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T22:07:14.164701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.25
Q17.25
median14.5
Q321.75
95-th percentile31.75
Maximum33
Range32
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation10.201734
Coefficient of variation (CV)0.65170785
Kurtosis-1.1570307
Mean15.653846
Median Absolute Deviation (MAD)7.5
Skewness0.31858886
Sum407
Variance104.07538
MonotonicityNot monotonic
2023-12-12T22:07:14.305762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
17 1
 
3.8%
7 1
 
3.8%
12 1
 
3.8%
32 1
 
3.8%
13 1
 
3.8%
33 1
 
3.8%
31 1
 
3.8%
30 1
 
3.8%
11 1
 
3.8%
16 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
1 1
3.8%
2 1
3.8%
3 1
3.8%
4 1
3.8%
5 1
3.8%
6 1
3.8%
7 1
3.8%
8 1
3.8%
9 1
3.8%
10 1
3.8%
ValueCountFrequency (%)
33 1
3.8%
32 1
3.8%
31 1
3.8%
30 1
3.8%
29 1
3.8%
28 1
3.8%
22 1
3.8%
21 1
3.8%
20 1
3.8%
19 1
3.8%

유형명
Text

Distinct24
Distinct (%)92.3%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-12T22:07:14.498964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length8
Mean length5.7307692
Min length2

Characters and Unicode

Total characters149
Distinct characters45
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)84.6%

Sample

1st row전세보증금(대여금)
2nd row과오납
3rd row공사환급
4th row미수수익결산조정
5th row미수수익환원
ValueCountFrequency (%)
운영자금 2
 
7.1%
공사환급 2
 
7.1%
소송비 1
 
3.6%
수입이자재환원 1
 
3.6%
과수납(소송비 1
 
3.6%
재조정 1
 
3.6%
가수금 1
 
3.6%
이자수익 1
 
3.6%
수입이자환원 1
 
3.6%
미수수익(이자 1
 
3.6%
Other values (16) 16
57.1%
2023-12-12T22:07:14.827070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
수 17
 
11.4%
금 10
 
6.7%
자 9
 
6.0%
대 7
 
4.7%
환 7
 
4.7%
이 7
 
4.7%
) 5
 
3.4%
미 5
 
3.4%
익 5
 
3.4%
( 5
 
3.4%
Other values (35) 72
48.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 136
91.3%
Close Punctuation 5
 
3.4%
Open Punctuation 5
 
3.4%
Space Separator 2
 
1.3%
Connector Punctuation 1
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 17
 
12.5%
금 10
 
7.4%
자 9
 
6.6%
대 7
 
5.1%
환 7
 
5.1%
이 7
 
5.1%
미 5
 
3.7%
익 5
 
3.7%
원 4
 
2.9%
입 4
 
2.9%
Other values (31) 61
44.9%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 136
91.3%
Common 13
 
8.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 17
 
12.5%
금 10
 
7.4%
자 9
 
6.6%
대 7
 
5.1%
환 7
 
5.1%
이 7
 
5.1%
미 5
 
3.7%
익 5
 
3.7%
원 4
 
2.9%
입 4
 
2.9%
Other values (31) 61
44.9%
Common
ValueCountFrequency (%)
) 5
38.5%
( 5
38.5%
2
 
15.4%
_ 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 136
91.3%
ASCII 13
 
8.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
수 17
 
12.5%
금 10
 
7.4%
자 9
 
6.6%
대 7
 
5.1%
환 7
 
5.1%
이 7
 
5.1%
미 5
 
3.7%
익 5
 
3.7%
원 4
 
2.9%
입 4
 
2.9%
Other values (31) 61
44.9%
ASCII
ValueCountFrequency (%)
) 5
38.5%
( 5
38.5%
2
 
15.4%
_ 1
 
7.7%

유형구분
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Memory size340.0 B
1
13 
3
9 
2
4 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row3
5th row3

Common Values

ValueCountFrequency (%)
1 13
50.0%
3 9
34.6%
2 4
 
15.4%

Length

2023-12-12T22:07:14.961417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:07:15.085910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 13
50.0%
3 9
34.6%
2 4
 
15.4%

등록자번호
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)15.4%
Missing0
Missing (%)0.0%
Memory size340.0 B
SYSTEM
19 
99999992
5 
20040169
 
1
99999995
 
1

Length

Max length8
Median length6
Mean length6.5384615
Min length6

Unique

Unique2 ?
Unique (%)7.7%

Sample

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

Common Values

ValueCountFrequency (%)
SYSTEM 19
73.1%
99999992 5
 
19.2%
20040169 1
 
3.8%
99999995 1
 
3.8%

Length

2023-12-12T22:07:15.204562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:07:15.316658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
system 19
73.1%
99999992 5
 
19.2%
20040169 1
 
3.8%
99999995 1
 
3.8%

등록일시
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)46.2%
Missing0
Missing (%)0.0%
Memory size340.0 B
2017-09-11 09:51:03
8 
2017-09-11 09:53:52
5 
2017-09-11 09:52:44
3 
2017-09-11 09:51:02
2 
2017-09-11 09:52:45
1 
Other values (7)
7 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique8 ?
Unique (%)30.8%

Sample

1st row2017-09-11 09:52:44
2nd row2017-09-11 09:52:44
3rd row2017-09-11 09:52:45
4th row2017-09-11 09:53:52
5th row2017-09-11 09:53:52

Common Values

ValueCountFrequency (%)
2017-09-11 09:51:03 8
30.8%
2017-09-11 09:53:52 5
19.2%
2017-09-11 09:52:44 3
 
11.5%
2017-09-11 09:51:02 2
 
7.7%
2017-09-11 09:52:45 1
 
3.8%
2017-10-24 11:54:11 1
 
3.8%
2018-09-27 13:58:33 1
 
3.8%
2019-09-10 14:49:42 1
 
3.8%
2020-01-15 15:15:49 1
 
3.8%
2023-07-27 21:06:31 1
 
3.8%
Other values (2) 2
 
7.7%

Length

2023-12-12T22:07:15.426261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2017-09-11 19
36.5%
09:51:03 8
15.4%
09:53:52 5
 
9.6%
09:52:44 3
 
5.8%
09:51:02 2
 
3.8%
2019-09-10 2
 
3.8%
2020-01-15 1
 
1.9%
2019-01-07 1
 
1.9%
15:39:12 1
 
1.9%
21:06:31 1
 
1.9%
Other values (9) 9
17.3%

수정자번호
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)15.4%
Missing0
Missing (%)0.0%
Memory size340.0 B
20040169
12 
SYSTEM
8 
99999992
5 
99999995
 
1

Length

Max length8
Median length8
Mean length7.3846154
Min length6

Unique

Unique1 ?
Unique (%)3.8%

Sample

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

Common Values

ValueCountFrequency (%)
20040169 12
46.2%
SYSTEM 8
30.8%
99999992 5
19.2%
99999995 1
 
3.8%

Length

2023-12-12T22:07:15.564028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:07:15.676089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20040169 12
46.2%
system 8
30.8%
99999992 5
19.2%
99999995 1
 
3.8%

수정일시
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)46.2%
Missing0
Missing (%)0.0%
Memory size340.0 B
2017-10-24 10:22:50
10 
2017-09-11 09:53:52
4 
2017-09-11 09:52:44
3 
2017-09-11 09:52:45
 
1
2017-10-31 13:24:26
 
1
Other values (7)
7 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique9 ?
Unique (%)34.6%

Sample

1st row2017-09-11 09:52:44
2nd row2017-09-11 09:52:44
3rd row2017-09-11 09:52:45
4th row2017-09-11 09:53:52
5th row2017-09-11 09:53:52

Common Values

ValueCountFrequency (%)
2017-10-24 10:22:50 10
38.5%
2017-09-11 09:53:52 4
 
15.4%
2017-09-11 09:52:44 3
 
11.5%
2017-09-11 09:52:45 1
 
3.8%
2017-10-31 13:24:26 1
 
3.8%
2017-10-24 11:54:11 1
 
3.8%
2018-09-27 16:08:54 1
 
3.8%
2019-09-10 15:37:53 1
 
3.8%
2020-01-15 15:15:49 1
 
3.8%
2023-07-27 21:06:31 1
 
3.8%
Other values (2) 2
 
7.7%

Length

2023-12-12T22:07:15.810851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2017-10-24 11
21.2%
10:22:50 10
19.2%
2017-09-11 8
15.4%
09:53:52 4
 
7.7%
09:52:44 3
 
5.8%
2019-09-10 2
 
3.8%
2020-01-15 1
 
1.9%
2019-01-07 1
 
1.9%
15:39:12 1
 
1.9%
21:06:31 1
 
1.9%
Other values (10) 10
19.2%

Interactions

2023-12-12T22:07:13.835154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:07:15.888092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유형코드유형명유형구분등록자번호등록일시수정자번호수정일시
유형코드1.0000.0000.9930.7070.7170.8480.707
유형명0.0001.0000.0000.0000.5260.8900.580
유형구분0.9930.0001.0000.1871.0000.6211.000
등록자번호0.7070.0000.1871.0001.0000.9781.000
등록일시0.7170.5261.0001.0001.0000.9990.998
수정자번호0.8480.8900.6210.9780.9991.0001.000
수정일시0.7070.5801.0001.0000.9981.0001.000
2023-12-12T22:07:16.019341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유형구분등록자번호수정일시등록일시수정자번호
유형구분1.0000.1590.7800.7800.623
등록자번호0.1591.0000.7980.7980.797
수정일시0.7800.7981.0000.9150.798
등록일시0.7800.7980.9151.0000.757
수정자번호0.6230.7970.7980.7571.000
2023-12-12T22:07:16.404144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유형코드유형구분등록자번호등록일시수정자번호수정일시
유형코드1.0000.7800.4660.3910.6400.383
유형구분0.7801.0000.1590.7800.6230.780
등록자번호0.4660.1591.0000.7980.7970.798
등록일시0.3910.7800.7981.0000.7570.915
수정자번호0.6400.6230.7970.7571.0000.798
수정일시0.3830.7800.7980.9150.7981.000

Missing values

2023-12-12T22:07:13.946541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:07:14.063128image/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

유형코드유형명유형구분등록자번호등록일시수정자번호수정일시
017전세보증금(대여금)2SYSTEM2017-09-11 09:52:44SYSTEM2017-09-11 09:52:44
118과오납2SYSTEM2017-09-11 09:52:44SYSTEM2017-09-11 09:52:44
219공사환급2SYSTEM2017-09-11 09:52:45SYSTEM2017-09-11 09:52:45
320미수수익결산조정3SYSTEM2017-09-11 09:53:52SYSTEM2017-09-11 09:53:52
421미수수익환원3SYSTEM2017-09-11 09:53:52SYSTEM2017-09-11 09:53:52
522미수수익재환원3SYSTEM2017-09-11 09:53:52200401692017-10-31 13:24:26
628충당금설정3SYSTEM2017-09-11 09:53:52SYSTEM2017-09-11 09:53:52
729충당금환입3SYSTEM2017-09-11 09:53:52SYSTEM2017-09-11 09:53:52
81대여금1SYSTEM2017-09-11 09:51:02200401692017-10-24 10:22:50
92임대료1SYSTEM2017-09-11 09:51:02200401692017-10-24 10:22:50
유형코드유형명유형구분등록자번호등록일시수정자번호수정일시
169과수납(임대료)1SYSTEM2017-09-11 09:51:03200401692017-10-24 10:22:50
1710감액1SYSTEM2017-09-11 09:51:03200401692017-10-24 10:22:50
1816운영자금2SYSTEM2017-09-11 09:52:44SYSTEM2017-09-11 09:52:44
1911공사환급1200401692017-10-24 11:54:11200401692017-10-24 11:54:11
2030미수수익(이자)3999999922018-09-27 13:58:33999999922018-09-27 16:08:54
2131수입이자환원3999999922019-09-10 14:49:42999999922019-09-10 15:37:53
2233이자수익 가수금 재조정3999999922020-01-15 15:15:49999999922020-01-15 15:15:49
2313과수납(소송비)1999999952023-07-27 21:06:31999999952023-07-27 21:06:31
2432수입이자재환원3999999922019-09-10 15:39:12999999922019-09-10 15:39:12
2512임대료_미수1999999922019-01-07 19:26:12999999922019-01-07 19:26:12