Overview

Dataset statistics

Number of variables10
Number of observations500
Missing cells0
Missing cells (%)0.0%
Duplicate rows34
Duplicate rows (%)6.8%
Total size in memory41.6 KiB
Average record size in memory85.3 B

Variable types

Categorical4
Numeric4
Boolean1
Text1

Dataset

Description해당 파일 데이터는 신용보증기금의 공통기타휴일정보에 대해 확인하실 수 있는 자료이니 데이터 활용에 참고하여 주시기 바랍니다.
Author신용보증기금
URLhttps://www.data.go.kr/data/15093182/fileData.do

Alerts

기준일자 has constant value ""Constant
삭제여부 has constant value ""Constant
Dataset has 34 (6.8%) duplicate rowsDuplicates
영업일일련번호 is highly overall correlated with 최종수정수 and 1 other fieldsHigh correlation
최종수정수 is highly overall correlated with 영업일일련번호High correlation
일자설명내용 is highly overall correlated with 일자속성코드High correlation
일자속성코드 is highly overall correlated with 일자설명내용High correlation
처리직원번호 is highly overall correlated with 영업일일련번호High correlation
영업일일련번호 has 128 (25.6%) zerosZeros

Reproduction

Analysis started2023-12-12 16:15:29.684331
Analysis finished2023-12-12 16:15:32.096995
Duration2.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
00:00.0
500 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row00:00.0
2nd row00:00.0
3rd row00:00.0
4th row00:00.0
5th row00:00.0

Common Values

ValueCountFrequency (%)
00:00.0 500
100.0%

Length

2023-12-13T01:15:32.207415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:15:32.292656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00.0 500
100.0%

영업일일련번호
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct264
Distinct (%)52.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4790.718
Minimum0
Maximum12218
Zeros128
Zeros (%)25.6%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T01:15:32.397137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6248
Q38611
95-th percentile10409.05
Maximum12218
Range12218
Interquartile range (IQR)8611

Descriptive statistics

Standard deviation4232.4178
Coefficient of variation (CV)0.8834621
Kurtosis-1.7208149
Mean4790.718
Median Absolute Deviation (MAD)3822
Skewness-0.084265853
Sum2395359
Variance17913360
MonotonicityNot monotonic
2023-12-13T01:15:32.545569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 128
 
25.6%
7544 5
 
1.0%
9519 5
 
1.0%
8110 4
 
0.8%
7782 4
 
0.8%
8371 4
 
0.8%
8761 4
 
0.8%
7136 4
 
0.8%
8852 4
 
0.8%
9113 4
 
0.8%
Other values (254) 334
66.8%
ValueCountFrequency (%)
0 128
25.6%
1 1
 
0.2%
2 1
 
0.2%
3 1
 
0.2%
4 1
 
0.2%
5 1
 
0.2%
6 2
 
0.4%
7 1
 
0.2%
8 1
 
0.2%
9 1
 
0.2%
ValueCountFrequency (%)
12218 1
 
0.2%
11963 1
 
0.2%
11710 1
 
0.2%
11456 1
 
0.2%
11200 1
 
0.2%
10946 1
 
0.2%
10750 1
 
0.2%
10734 3
0.6%
10696 1
 
0.2%
10648 1
 
0.2%

일자설명내용
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
평일
345 
일요일
49 
법정공휴일
 
33
국경일
 
32
토요일
 
31
Other values (2)
 
10

Length

Max length5
Median length2
Mean length2.478
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
평일 345
69.0%
일요일 49
 
9.8%
법정공휴일 33
 
6.6%
국경일 32
 
6.4%
토요일 31
 
6.2%
임시공휴일 9
 
1.8%
영업일 1
 
0.2%

Length

2023-12-13T01:15:32.695084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:15:32.807698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
평일 345
69.0%
일요일 49
 
9.8%
법정공휴일 33
 
6.6%
국경일 32
 
6.4%
토요일 31
 
6.2%
임시공휴일 9
 
1.8%
영업일 1
 
0.2%

요일구분코드
Real number (ℝ)

Distinct7
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.794
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T01:15:32.901633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q36
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.0591367
Coefficient of variation (CV)0.54273504
Kurtosis-1.2983152
Mean3.794
Median Absolute Deviation (MAD)2
Skewness0.094699189
Sum1897
Variance4.2400441
MonotonicityNot monotonic
2023-12-13T01:15:33.005198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 99
19.8%
3 79
15.8%
6 69
13.8%
5 67
13.4%
7 64
12.8%
2 62
12.4%
4 60
12.0%
ValueCountFrequency (%)
1 99
19.8%
2 62
12.4%
3 79
15.8%
4 60
12.0%
5 67
13.4%
6 69
13.8%
7 64
12.8%
ValueCountFrequency (%)
7 64
12.8%
6 69
13.8%
5 67
13.4%
4 60
12.0%
3 79
15.8%
2 62
12.4%
1 99
19.8%

월주차구분코드
Real number (ℝ)

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.028
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T01:15:33.104219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum6
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.369294
Coefficient of variation (CV)0.45221068
Kurtosis-1.063881
Mean3.028
Median Absolute Deviation (MAD)1
Skewness0.19858807
Sum1514
Variance1.8749659
MonotonicityNot monotonic
2023-12-13T01:15:33.201673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2 140
28.0%
3 105
21.0%
5 90
18.0%
4 88
17.6%
1 69
13.8%
6 8
 
1.6%
ValueCountFrequency (%)
1 69
13.8%
2 140
28.0%
3 105
21.0%
4 88
17.6%
5 90
18.0%
6 8
 
1.6%
ValueCountFrequency (%)
6 8
 
1.6%
5 90
18.0%
4 88
17.6%
3 105
21.0%
2 140
28.0%
1 69
13.8%

일자속성코드
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
230 
2
184 
4
44 
3
 
22
1
 
20

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 230
46.0%
2 184
36.8%
4 44
 
8.8%
3 22
 
4.4%
1 20
 
4.0%

Length

2023-12-13T01:15:33.356025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:15:33.445290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 230
46.0%
2 184
36.8%
4 44
 
8.8%
3 22
 
4.4%
1 20
 
4.0%

삭제여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size632.0 B
False
500 
ValueCountFrequency (%)
False 500
100.0%
2023-12-13T01:15:33.542854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

최종수정수
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.334
Minimum1
Maximum59
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T01:15:33.619685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q32
95-th percentile5
Maximum59
Range58
Interquartile range (IQR)1

Descriptive statistics

Standard deviation4.1026952
Coefficient of variation (CV)1.7577957
Kurtosis102.31208
Mean2.334
Median Absolute Deviation (MAD)1
Skewness9.2285982
Sum1167
Variance16.832108
MonotonicityNot monotonic
2023-12-13T01:15:33.732282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
2 214
42.8%
1 208
41.6%
3 38
 
7.6%
5 21
 
4.2%
4 3
 
0.6%
9 3
 
0.6%
6 2
 
0.4%
39 2
 
0.4%
21 2
 
0.4%
29 1
 
0.2%
Other values (6) 6
 
1.2%
ValueCountFrequency (%)
1 208
41.6%
2 214
42.8%
3 38
 
7.6%
4 3
 
0.6%
5 21
 
4.2%
6 2
 
0.4%
7 1
 
0.2%
9 3
 
0.6%
10 1
 
0.2%
11 1
 
0.2%
ValueCountFrequency (%)
59 1
 
0.2%
39 2
0.4%
29 1
 
0.2%
21 2
0.4%
13 1
 
0.2%
12 1
 
0.2%
11 1
 
0.2%
10 1
 
0.2%
9 3
0.6%
7 1
 
0.2%

처리시각
Text

Distinct293
Distinct (%)58.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-13T01:15:34.094666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length7
Mean length14.904
Min length7

Characters and Unicode

Total characters7452
Distinct characters14
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique292 ?
Unique (%)58.4%

Sample

1st row44:18.6
2nd row41:45.3
3rd row38:41.2
4th row37:41.1
5th row36:27.1
ValueCountFrequency (%)
0001-01-01 208
29.4%
00:00:00.000000 208
29.4%
16:07.2 1
 
0.1%
25:52.7 1
 
0.1%
36:40.3 1
 
0.1%
37:09.3 1
 
0.1%
37:14.1 1
 
0.1%
37:17.2 1
 
0.1%
37:39.2 1
 
0.1%
37:46.3 1
 
0.1%
Other values (284) 284
40.1%
2023-12-13T01:15:34.632381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3702
49.7%
1 822
 
11.0%
: 708
 
9.5%
. 500
 
6.7%
- 416
 
5.6%
208
 
2.8%
4 204
 
2.7%
3 193
 
2.6%
2 188
 
2.5%
5 170
 
2.3%
Other values (4) 341
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5620
75.4%
Other Punctuation 1208
 
16.2%
Dash Punctuation 416
 
5.6%
Space Separator 208
 
2.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3702
65.9%
1 822
 
14.6%
4 204
 
3.6%
3 193
 
3.4%
2 188
 
3.3%
5 170
 
3.0%
8 100
 
1.8%
7 93
 
1.7%
6 78
 
1.4%
9 70
 
1.2%
Other Punctuation
ValueCountFrequency (%)
: 708
58.6%
. 500
41.4%
Dash Punctuation
ValueCountFrequency (%)
- 416
100.0%
Space Separator
ValueCountFrequency (%)
208
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7452
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3702
49.7%
1 822
 
11.0%
: 708
 
9.5%
. 500
 
6.7%
- 416
 
5.6%
208
 
2.8%
4 204
 
2.7%
3 193
 
2.6%
2 188
 
2.5%
5 170
 
2.3%
Other values (4) 341
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7452
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3702
49.7%
1 822
 
11.0%
: 708
 
9.5%
. 500
 
6.7%
- 416
 
5.6%
208
 
2.8%
4 204
 
2.7%
3 193
 
2.6%
2 188
 
2.5%
5 170
 
2.3%
Other values (4) 341
 
4.6%

처리직원번호
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
208 
5803
91 
4800
69 
3513
35 
5314
34 
Other values (7)
63 

Length

Max length5
Median length4
Mean length4.416
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row5803
2nd row5803
3rd row5803
4th row5803
5th row5803

Common Values

ValueCountFrequency (%)
208
41.6%
5803 91
18.2%
4800 69
 
13.8%
3513 35
 
7.0%
5314 34
 
6.8%
5099 26
 
5.2%
4169 11
 
2.2%
3682 8
 
1.6%
4062 8
 
1.6%
4451 7
 
1.4%
Other values (2) 3
 
0.6%

Length

2023-12-13T01:15:34.817712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5803 91
31.2%
4800 69
23.6%
3513 35
 
12.0%
5314 34
 
11.6%
5099 26
 
8.9%
4169 11
 
3.8%
3682 8
 
2.7%
4062 8
 
2.7%
4451 7
 
2.4%
3753 2
 
0.7%

Interactions

2023-12-13T01:15:31.549292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:15:30.378638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:15:30.832782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:15:31.194762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:15:31.631094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:15:30.489147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:15:30.936769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:15:31.289310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:15:31.713707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:15:30.615383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:15:31.024703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:15:31.383083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:15:31.790671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:15:30.720151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:15:31.105742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:15:31.464654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:15:34.924664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업일일련번호일자설명내용요일구분코드월주차구분코드일자속성코드최종수정수처리직원번호
영업일일련번호1.0000.4240.0730.1900.5680.4390.859
일자설명내용0.4241.0000.8410.3610.6640.5140.667
요일구분코드0.0730.8411.0000.1740.6430.0000.234
월주차구분코드0.1900.3610.1741.0000.2000.1380.430
일자속성코드0.5680.6640.6430.2001.0000.0000.718
최종수정수0.4390.5140.0000.1380.0001.0000.463
처리직원번호0.8590.6670.2340.4300.7180.4631.000
2023-12-13T01:15:35.093400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처리직원번호일자설명내용일자속성코드
처리직원번호1.0000.4020.500
일자설명내용0.4021.0000.507
일자속성코드0.5000.5071.000
2023-12-13T01:15:35.211983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업일일련번호요일구분코드월주차구분코드최종수정수일자설명내용일자속성코드처리직원번호
영업일일련번호1.000-0.140-0.1250.7700.2430.3930.579
요일구분코드-0.1401.000-0.1520.0210.4460.4840.115
월주차구분코드-0.125-0.1521.000-0.1610.2240.1360.181
최종수정수0.7700.021-0.1611.0000.2010.0000.245
일자설명내용0.2430.4460.2240.2011.0000.5070.402
일자속성코드0.3930.4840.1360.0000.5071.0000.500
처리직원번호0.5790.1150.1810.2450.4020.5001.000

Missing values

2023-12-13T01:15:31.901908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:15:32.044179image/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

기준일자영업일일련번호일자설명내용요일구분코드월주차구분코드일자속성코드삭제여부최종수정수처리시각처리직원번호
000:00.010068평일150N344:18.65803
100:00.010410평일140N341:45.35803
200:00.09673평일150N338:41.25803
300:00.09414평일220N337:41.15803
400:00.08938평일150N336:27.15803
500:00.08676평일130N335:37.55803
600:00.08834평일150N314:15.55803
700:00.08588평일150N313:55.65803
800:00.010646평일122N221:25.75314
900:00.010585평일222N220:12.95314
기준일자영업일일련번호일자설명내용요일구분코드월주차구분코드일자속성코드삭제여부최종수정수처리시각처리직원번호
49000:00.061평일130N10001-01-01 00:00:00.000000
49100:00.062평일230N10001-01-01 00:00:00.000000
49200:00.063평일330N10001-01-01 00:00:00.000000
49300:00.064평일430N10001-01-01 00:00:00.000000
49400:00.065평일530N10001-01-01 00:00:00.000000
49500:00.066평일630N10001-01-01 00:00:00.000000
49600:00.066일요일734N10001-01-01 00:00:00.000000
49700:00.067평일140N10001-01-01 00:00:00.000000
49800:00.068평일240N10001-01-01 00:00:00.000000
49900:00.069평일340N10001-01-01 00:00:00.000000

Duplicate rows

Most frequently occurring

기준일자영업일일련번호일자설명내용요일구분코드월주차구분코드일자속성코드삭제여부최종수정수처리시각처리직원번호# duplicates
1800:00.00평일350N10001-01-01 00:00:00.0000008
2800:00.00평일550N10001-01-01 00:00:00.0000008
2300:00.00평일450N10001-01-01 00:00:00.0000006
500:00.00토요일653N10001-01-01 00:00:00.0000005
1400:00.00평일250N10001-01-01 00:00:00.0000005
300:00.00일요일744N10001-01-01 00:00:00.0000004
400:00.00일요일754N10001-01-01 00:00:00.0000004
900:00.00평일150N10001-01-01 00:00:00.0000004
1000:00.00평일160N10001-01-01 00:00:00.0000004
2700:00.00평일540N10001-01-01 00:00:00.0000004