Overview

Dataset statistics

Number of variables10
Number of observations500
Missing cells0
Missing cells (%)0.0%
Duplicate rows26
Duplicate rows (%)5.2%
Total size in memory41.1 KiB
Average record size in memory84.3 B

Variable types

Categorical9
Boolean1

Dataset

Description해당 파일 데이터는 신용보증기금의 PCOFF 첨부파일 내역에 대해 확인하실 수 있는 자료이니 데이터 활용에 참고하여 주시기 바랍니다.
Author신용보증기금
URLhttps://www.data.go.kr/data/15093083/fileData.do

Alerts

일자 has constant value ""Constant
삭제여부 has constant value ""Constant
최종수정수 has constant value ""Constant
Dataset has 26 (5.2%) duplicate rowsDuplicates
최초처리직원번호 is highly overall correlated with 처리시각 and 2 other fieldsHigh correlation
시간외근무모니터링항목코드 is highly overall correlated with 연휴반나절연휴구분코드 and 3 other fieldsHigh correlation
연휴반나절연휴구분코드 is highly overall correlated with 시간외근무모니터링항목코드 and 3 other fieldsHigh correlation
PCOFF근무유형코드 is highly overall correlated with 시간외근무모니터링항목코드 and 3 other fieldsHigh correlation
최초처리시각 is highly overall correlated with 시간외근무모니터링항목코드 and 5 other fieldsHigh correlation
처리직원번호 is highly overall correlated with 처리시각 and 2 other fieldsHigh correlation
처리시각 is highly overall correlated with 시간외근무모니터링항목코드 and 5 other fieldsHigh correlation

Reproduction

Analysis started2023-12-12 21:47:17.837481
Analysis finished2023-12-12 21:47:18.656802
Duration0.82 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시간외근무모니터링항목코드
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
292 
149 
A1000
54 
A2100
 
3
A2400
 
1

Length

Max length5
Median length1
Mean length1.472
Min length1

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
0 292
58.4%
149
29.8%
A1000 54
 
10.8%
A2100 3
 
0.6%
A2400 1
 
0.2%
A2300 1
 
0.2%

Length

2023-12-13T06:47:18.723914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:47:18.831869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 292
83.2%
a1000 54
 
15.4%
a2100 3
 
0.9%
a2400 1
 
0.3%
a2300 1
 
0.3%

연휴반나절연휴구분코드
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
363 
1
72 
3
49 
5
 
16

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
363
72.6%
1 72
 
14.4%
3 49
 
9.8%
5 16
 
3.2%

Length

2023-12-13T06:47:18.936097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:47:19.041642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 72
52.6%
3 49
35.8%
5 16
 
11.7%

일자
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

2023-12-13T06:47:19.192309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:47:19.273004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00.0 500
100.0%

PCOFF근무유형코드
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
351 
2
149 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 351
70.2%
2 149
29.8%

Length

2023-12-13T06:47:19.357386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:47:19.445956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 351
70.2%
2 149
29.8%

삭제여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size632.0 B
False
500 
ValueCountFrequency (%)
False 500
100.0%
2023-12-13T06:47:19.535154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

최종수정수
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
500 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 500
100.0%

Length

2023-12-13T06:47:19.626740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:47:19.704955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 500
100.0%

처리시각
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
52:02.8
74 
55:28.7
58 
07:38.8
55 
25:24.0
54 
21:42.2
47 
Other values (15)
212 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique4 ?
Unique (%)0.8%

Sample

1st row48:10.7
2nd row48:10.7
3rd row48:10.7
4th row48:10.7
5th row48:10.7

Common Values

ValueCountFrequency (%)
52:02.8 74
14.8%
55:28.7 58
11.6%
07:38.8 55
11.0%
25:24.0 54
10.8%
21:42.2 47
9.4%
48:10.7 42
8.4%
11:19.1 38
7.6%
46:22.8 31
6.2%
11:19.2 25
 
5.0%
13:11.5 24
 
4.8%
Other values (10) 52
10.4%

Length

2023-12-13T06:47:19.799646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
52:02.8 74
14.8%
55:28.7 58
11.6%
07:38.8 55
11.0%
25:24.0 54
10.8%
21:42.2 47
9.4%
48:10.7 42
8.4%
11:19.1 38
7.6%
46:22.8 31
6.2%
11:19.2 25
 
5.0%
13:11.5 24
 
4.8%
Other values (10) 52
10.4%

처리직원번호
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
5439
267 
5351
170 
4805
63 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5439
2nd row5439
3rd row5439
4th row5439
5th row5439

Common Values

ValueCountFrequency (%)
5439 267
53.4%
5351 170
34.0%
4805 63
 
12.6%

Length

2023-12-13T06:47:19.931991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:47:20.040098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5439 267
53.4%
5351 170
34.0%
4805 63
 
12.6%

최초처리시각
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
52:02.8
74 
55:28.7
58 
07:38.8
55 
25:24.0
54 
21:42.2
47 
Other values (15)
212 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique4 ?
Unique (%)0.8%

Sample

1st row48:10.7
2nd row48:10.7
3rd row48:10.7
4th row48:10.7
5th row48:10.7

Common Values

ValueCountFrequency (%)
52:02.8 74
14.8%
55:28.7 58
11.6%
07:38.8 55
11.0%
25:24.0 54
10.8%
21:42.2 47
9.4%
48:10.7 42
8.4%
11:19.1 38
7.6%
46:22.8 31
6.2%
11:19.2 25
 
5.0%
13:11.5 24
 
4.8%
Other values (10) 52
10.4%

Length

2023-12-13T06:47:20.170514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
52:02.8 74
14.8%
55:28.7 58
11.6%
07:38.8 55
11.0%
25:24.0 54
10.8%
21:42.2 47
9.4%
48:10.7 42
8.4%
11:19.1 38
7.6%
46:22.8 31
6.2%
11:19.2 25
 
5.0%
13:11.5 24
 
4.8%
Other values (10) 52
10.4%

최초처리직원번호
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
5439
267 
5351
170 
4805
63 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5439
2nd row5439
3rd row5439
4th row5439
5th row5439

Common Values

ValueCountFrequency (%)
5439 267
53.4%
5351 170
34.0%
4805 63
 
12.6%

Length

2023-12-13T06:47:20.321965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:47:20.440532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5439 267
53.4%
5351 170
34.0%
4805 63
 
12.6%

Correlations

2023-12-13T06:47:20.517156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시간외근무모니터링항목코드연휴반나절연휴구분코드PCOFF근무유형코드처리시각처리직원번호최초처리시각최초처리직원번호
시간외근무모니터링항목코드1.0000.7061.0000.8680.8090.8680.809
연휴반나절연휴구분코드0.7061.0000.9960.8980.2150.8980.215
PCOFF근무유형코드1.0000.9961.0001.0000.1531.0000.153
처리시각0.8680.8981.0001.0001.0001.0001.000
처리직원번호0.8090.2150.1531.0001.0001.0001.000
최초처리시각0.8680.8981.0001.0001.0001.0001.000
최초처리직원번호0.8090.2150.1531.0001.0001.0001.000
2023-12-13T06:47:20.664187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
최초처리직원번호시간외근무모니터링항목코드연휴반나절연휴구분코드PCOFF근무유형코드최초처리시각처리직원번호처리시각
최초처리직원번호1.0000.4910.2040.2510.9831.0000.983
시간외근무모니터링항목코드0.4911.0000.5370.9960.6290.4910.629
연휴반나절연휴구분코드0.2040.5371.0000.9410.6300.2040.630
PCOFF근무유형코드0.2510.9960.9411.0000.9820.2510.982
최초처리시각0.9830.6290.6300.9821.0000.9831.000
처리직원번호1.0000.4910.2040.2510.9831.0000.983
처리시각0.9830.6290.6300.9821.0000.9831.000
2023-12-13T06:47:20.815501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시간외근무모니터링항목코드연휴반나절연휴구분코드PCOFF근무유형코드처리시각처리직원번호최초처리시각최초처리직원번호
시간외근무모니터링항목코드1.0000.5370.9960.6290.4910.6290.491
연휴반나절연휴구분코드0.5371.0000.9410.6300.2040.6300.204
PCOFF근무유형코드0.9960.9411.0000.9820.2510.9820.251
처리시각0.6290.6300.9821.0000.9831.0000.983
처리직원번호0.4910.2040.2510.9831.0000.9831.000
최초처리시각0.6290.6300.9821.0000.9831.0000.983
최초처리직원번호0.4910.2040.2510.9831.0000.9831.000

Missing values

2023-12-13T06:47:18.419943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:47:18.593115image/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

시간외근무모니터링항목코드연휴반나절연휴구분코드일자PCOFF근무유형코드삭제여부최종수정수처리시각처리직원번호최초처리시각최초처리직원번호
0100:00.02N148:10.7543948:10.75439
1100:00.02N148:10.7543948:10.75439
2100:00.02N148:10.7543948:10.75439
3100:00.02N148:10.7543948:10.75439
4100:00.02N148:10.7543948:10.75439
5500:00.02N148:10.7543948:10.75439
6300:00.02N148:10.7543948:10.75439
7100:00.02N148:10.7543948:10.75439
8100:00.02N148:10.7543948:10.75439
9100:00.02N148:10.7543948:10.75439
시간외근무모니터링항목코드연휴반나절연휴구분코드일자PCOFF근무유형코드삭제여부최종수정수처리시각처리직원번호최초처리시각최초처리직원번호
490000:00.01N111:19.1480511:19.14805
491A100000:00.01N111:19.1480511:19.14805
492A100000:00.01N111:19.1480511:19.14805
493000:00.01N111:19.1480511:19.14805
494A100000:00.01N111:19.1480511:19.14805
495000:00.01N111:19.1480511:19.14805
496000:00.01N111:19.1480511:19.14805
497A100000:00.01N111:19.1480511:19.14805
498A100000:00.01N111:19.1480511:19.14805
499A100000:00.01N111:19.1480511:19.14805

Duplicate rows

Most frequently occurring

시간외근무모니터링항목코드연휴반나절연휴구분코드일자PCOFF근무유형코드삭제여부최종수정수처리시각처리직원번호최초처리시각최초처리직원번호# duplicates
21000:00.01N152:02.8543952:02.8543974
22000:00.01N155:28.7535155:28.7535158
19000:00.01N125:24.0535125:24.0535154
18000:00.01N121:42.2543921:42.2543947
5100:00.02N148:10.7543948:10.7543934
20000:00.01N146:22.8543946:22.8543929
2100:00.02N107:38.8543907:38.8543926
24A100000:00.01N111:19.1480511:19.1480526
6300:00.02N107:38.8543907:38.8543923
25A100000:00.01N111:19.2480511:19.2480516