Overview

Dataset statistics

Number of variables22
Number of observations500
Missing cells997
Missing cells (%)9.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory88.5 KiB
Average record size in memory181.3 B

Variable types

Text7
Categorical9
Boolean3
Unsupported1
DateTime2

Dataset

Description해당 파일 데이터는 신용보증기금의 공통전자결재개별결재정보에 대해 확인하실 수 있는 자료이니 데이터 활용에 참고하여 주시기 바랍니다.
Author신용보증기금
URLhttps://www.data.go.kr/data/15093201/fileData.do

Alerts

그룹웨어등록여부 has constant value ""Constant
결재신청일자 has constant value ""Constant
전자결재부점구분코드 is highly imbalanced (94.7%)Imbalance
전자결재구분코드 is highly imbalanced (93.3%)Imbalance
전자결재전자수기구분코드 is highly imbalanced (81.6%)Imbalance
첨부파일유무 is highly imbalanced (96.2%)Imbalance
그룹웨어문서상태코드값 is highly imbalanced (56.6%)Imbalance
삭제여부 is highly imbalanced (90.6%)Imbalance
본건문서그룹웨어결재KEY명 has 497 (99.4%) missing valuesMissing
문서요약상세내용 has 500 (100.0%) missing valuesMissing
전자결재개별결재ID has unique valuesUnique
그룹웨어결재KEY명 has unique valuesUnique
문서요약상세내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 12:24:44.231108
Analysis finished2023-12-12 12:24:44.737699
Duration0.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

전자결재개별결재ID
Text

UNIQUE 

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-12T21:24:44.963187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters5000
Distinct characters62
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique500 ?
Unique (%)100.0%

Sample

1st row9dnS0BwbwB
2nd row9dnS0SdHkZ
3rd row9dnS0P5RLG
4th row9dnS0RQV0P
5th row9dnS0RRuMK
ValueCountFrequency (%)
9dns0bwbwb 1
 
0.2%
9dnsyrivz7 1
 
0.2%
9dnsx4i1so 1
 
0.2%
9dnsxv4jyg 1
 
0.2%
9dnsvmgnhp 1
 
0.2%
9dnsyuexuw 1
 
0.2%
9dnshvie14 1
 
0.2%
9dnsxgfyw4 1
 
0.2%
9dnsnuzjdl 1
 
0.2%
9dnsxlkrfw 1
 
0.2%
Other values (490) 490
98.0%
2023-12-12T21:24:45.481572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 539
 
10.8%
d 539
 
10.8%
n 538
 
10.8%
S 508
 
10.2%
Z 149
 
3.0%
Y 135
 
2.7%
X 119
 
2.4%
0 119
 
2.4%
V 68
 
1.4%
O 63
 
1.3%
Other values (52) 2223
44.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2084
41.7%
Uppercase Letter 1909
38.2%
Decimal Number 1007
20.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
d 539
25.9%
n 538
25.8%
u 51
 
2.4%
m 50
 
2.4%
e 50
 
2.4%
o 50
 
2.4%
j 46
 
2.2%
t 45
 
2.2%
z 45
 
2.2%
r 45
 
2.2%
Other values (16) 625
30.0%
Uppercase Letter
ValueCountFrequency (%)
S 508
26.6%
Z 149
 
7.8%
Y 135
 
7.1%
X 119
 
6.2%
V 68
 
3.6%
O 63
 
3.3%
N 56
 
2.9%
W 50
 
2.6%
U 50
 
2.6%
L 49
 
2.6%
Other values (16) 662
34.7%
Decimal Number
ValueCountFrequency (%)
9 539
53.5%
0 119
 
11.8%
1 52
 
5.2%
5 46
 
4.6%
4 45
 
4.5%
3 45
 
4.5%
6 43
 
4.3%
2 43
 
4.3%
8 39
 
3.9%
7 36
 
3.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 3993
79.9%
Common 1007
 
20.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
d 539
 
13.5%
n 538
 
13.5%
S 508
 
12.7%
Z 149
 
3.7%
Y 135
 
3.4%
X 119
 
3.0%
V 68
 
1.7%
O 63
 
1.6%
N 56
 
1.4%
u 51
 
1.3%
Other values (42) 1767
44.3%
Common
ValueCountFrequency (%)
9 539
53.5%
0 119
 
11.8%
1 52
 
5.2%
5 46
 
4.6%
4 45
 
4.5%
3 45
 
4.5%
6 43
 
4.3%
2 43
 
4.3%
8 39
 
3.9%
7 36
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 539
 
10.8%
d 539
 
10.8%
n 538
 
10.8%
S 508
 
10.2%
Z 149
 
3.0%
Y 135
 
2.7%
X 119
 
2.4%
0 119
 
2.4%
V 68
 
1.4%
O 63
 
1.3%
Other values (52) 2223
44.5%

전자결재ID
Text

Distinct496
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-12T21:24:45.873141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters5000
Distinct characters62
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique492 ?
Unique (%)98.4%

Sample

1st row9dnS0BwbwB
2nd row9dnS0SdHkZ
3rd row9dnS0P5RLG
4th row9dnS0RQV0P
5th row9dnS0RRuMK
ValueCountFrequency (%)
9dnskmd5xl 2
 
0.4%
9dnj1pjkir 2
 
0.4%
9dnsnf2xs9 2
 
0.4%
9dnsjpuah1 2
 
0.4%
9dnsyjhdrm 1
 
0.2%
9dnsxgfyw4 1
 
0.2%
9dnsydseum 1
 
0.2%
9dnsnqy2np 1
 
0.2%
9dnsxlkrfw 1
 
0.2%
9dnsnuzjdl 1
 
0.2%
Other values (486) 486
97.2%
2023-12-12T21:24:46.399321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 540
 
10.8%
n 538
 
10.8%
d 537
 
10.7%
S 505
 
10.1%
Z 145
 
2.9%
Y 135
 
2.7%
X 118
 
2.4%
0 118
 
2.4%
V 70
 
1.4%
O 64
 
1.3%
Other values (52) 2230
44.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2078
41.6%
Uppercase Letter 1914
38.3%
Decimal Number 1008
20.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 538
25.9%
d 537
25.8%
o 52
 
2.5%
e 51
 
2.5%
m 48
 
2.3%
j 47
 
2.3%
u 47
 
2.3%
r 46
 
2.2%
t 45
 
2.2%
k 44
 
2.1%
Other values (16) 623
30.0%
Uppercase Letter
ValueCountFrequency (%)
S 505
26.4%
Z 145
 
7.6%
Y 135
 
7.1%
X 118
 
6.2%
V 70
 
3.7%
O 64
 
3.3%
N 54
 
2.8%
U 51
 
2.7%
J 51
 
2.7%
W 51
 
2.7%
Other values (16) 670
35.0%
Decimal Number
ValueCountFrequency (%)
9 540
53.6%
0 118
 
11.7%
1 54
 
5.4%
5 47
 
4.7%
3 45
 
4.5%
2 44
 
4.4%
4 43
 
4.3%
6 43
 
4.3%
7 37
 
3.7%
8 37
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 3992
79.8%
Common 1008
 
20.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 538
 
13.5%
d 537
 
13.5%
S 505
 
12.7%
Z 145
 
3.6%
Y 135
 
3.4%
X 118
 
3.0%
V 70
 
1.8%
O 64
 
1.6%
N 54
 
1.4%
o 52
 
1.3%
Other values (42) 1774
44.4%
Common
ValueCountFrequency (%)
9 540
53.6%
0 118
 
11.7%
1 54
 
5.4%
5 47
 
4.7%
3 45
 
4.5%
2 44
 
4.4%
4 43
 
4.3%
6 43
 
4.3%
7 37
 
3.7%
8 37
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 540
 
10.8%
n 538
 
10.8%
d 537
 
10.7%
S 505
 
10.1%
Z 145
 
2.9%
Y 135
 
2.7%
X 118
 
2.4%
0 118
 
2.4%
V 70
 
1.4%
O 64
 
1.3%
Other values (52) 2230
44.6%

전자결재부점구분코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
497 
2
 
3

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 (%)
1 497
99.4%
2 3
 
0.6%

Length

2023-12-12T21:24:46.622287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:24:46.770011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 497
99.4%
2 3
 
0.6%

전자결재구분코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
496 
2
 
4

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 (%)
1 496
99.2%
2 4
 
0.8%

Length

2023-12-12T21:24:47.244520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:24:47.380825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 496
99.2%
2 4
 
0.8%

전자결재전자수기구분코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
486 
3
 
14

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 (%)
1 486
97.2%
3 14
 
2.8%

Length

2023-12-12T21:24:47.507776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:24:47.632611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 486
97.2%
3 14
 
2.8%

그룹웨어등록여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size632.0 B
True
500 
ValueCountFrequency (%)
True 500
100.0%
2023-12-12T21:24:47.733113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

본건문서그룹웨어결재KEY명
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing497
Missing (%)99.4%
Memory size4.0 KiB
2023-12-12T21:24:47.934480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length40
Mean length40
Min length40

Characters and Unicode

Total characters120
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st rowE211018_F0062FBE887A378E49258772000757D9
2nd rowE211018_50D0E46076761238492587720008AA2F
3rd rowE211018_072F2B546FDE34E549258772000CB597
ValueCountFrequency (%)
e211018_f0062fbe887a378e49258772000757d9 1
33.3%
e211018_50d0e46076761238492587720008aa2f 1
33.3%
e211018_072f2b546fde34e549258772000cb597 1
33.3%
2023-12-12T21:24:48.326298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18
15.0%
2 14
11.7%
7 14
11.7%
8 11
9.2%
1 10
8.3%
E 8
 
6.7%
5 8
 
6.7%
4 6
 
5.0%
F 5
 
4.2%
6 5
 
4.2%
Other values (7) 21
17.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 94
78.3%
Uppercase Letter 23
 
19.2%
Connector Punctuation 3
 
2.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 18
19.1%
2 14
14.9%
7 14
14.9%
8 11
11.7%
1 10
10.6%
5 8
8.5%
4 6
 
6.4%
6 5
 
5.3%
9 5
 
5.3%
3 3
 
3.2%
Uppercase Letter
ValueCountFrequency (%)
E 8
34.8%
F 5
21.7%
D 3
 
13.0%
B 3
 
13.0%
A 3
 
13.0%
C 1
 
4.3%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 97
80.8%
Latin 23
 
19.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 18
18.6%
2 14
14.4%
7 14
14.4%
8 11
11.3%
1 10
10.3%
5 8
8.2%
4 6
 
6.2%
6 5
 
5.2%
9 5
 
5.2%
3 3
 
3.1%
Latin
ValueCountFrequency (%)
E 8
34.8%
F 5
21.7%
D 3
 
13.0%
B 3
 
13.0%
A 3
 
13.0%
C 1
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 120
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18
15.0%
2 14
11.7%
7 14
11.7%
8 11
9.2%
1 10
8.3%
E 8
 
6.7%
5 8
 
6.7%
4 6
 
5.0%
F 5
 
4.2%
6 5
 
4.2%
Other values (7) 21
17.5%

그룹웨어결재KEY명
Text

UNIQUE 

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-12T21:24:48.622846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length40
Mean length40
Min length40

Characters and Unicode

Total characters20000
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique500 ?
Unique (%)100.0%

Sample

1st rowE211018_E8E75F1C580666E049258772001EC4AC
2nd rowE211018_EA8DCB694E03D7D449258772001F258E
3rd rowE211018_0DEA08E412F5A4E749258772001F17DE
4th rowE211018_B5966D353747520249258772001F231D
5th rowE211018_68957919A1E238C949258772001F23AA
ValueCountFrequency (%)
e211018_e8e75f1c580666e049258772001ec4ac 1
 
0.2%
e211018_9cc0675544e73d5549258772001bc059 1
 
0.2%
e211018_8d3edb206e9d856e49258772001b3d7c 1
 
0.2%
e211018_4edb98a233d7e00849258772001a748d 1
 
0.2%
e211018_f536146860290970492587720017710c 1
 
0.2%
e211018_89de150342b3e0d349258772001bce40 1
 
0.2%
e211018_bd8880162ba4ba6f492587720004aabd 1
 
0.2%
e211018_6a914f153883db3349258772001ab150 1
 
0.2%
e211018_b058df0f4f09ec6c49258772000d0a55 1
 
0.2%
e211018_63fc68d175d519dc49258772001a34fa 1
 
0.2%
Other values (490) 490
98.0%
2023-12-12T21:24:49.117572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2573
12.9%
0 2208
11.0%
2 2146
10.7%
8 1583
 
7.9%
7 1582
 
7.9%
E 1177
 
5.9%
5 1143
 
5.7%
4 1134
 
5.7%
9 1094
 
5.5%
D 737
 
3.7%
Other values (7) 4623
23.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14839
74.2%
Uppercase Letter 4661
 
23.3%
Connector Punctuation 500
 
2.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2573
17.3%
0 2208
14.9%
2 2146
14.5%
8 1583
10.7%
7 1582
10.7%
5 1143
7.7%
4 1134
7.6%
9 1094
7.4%
6 715
 
4.8%
3 661
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
E 1177
25.3%
D 737
15.8%
A 714
15.3%
B 693
14.9%
C 688
14.8%
F 652
14.0%
Connector Punctuation
ValueCountFrequency (%)
_ 500
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15339
76.7%
Latin 4661
 
23.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2573
16.8%
0 2208
14.4%
2 2146
14.0%
8 1583
10.3%
7 1582
10.3%
5 1143
7.5%
4 1134
7.4%
9 1094
7.1%
6 715
 
4.7%
3 661
 
4.3%
Latin
ValueCountFrequency (%)
E 1177
25.3%
D 737
15.8%
A 714
15.3%
B 693
14.9%
C 688
14.8%
F 652
14.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2573
12.9%
0 2208
11.0%
2 2146
10.7%
8 1583
 
7.9%
7 1582
 
7.9%
E 1177
 
5.9%
5 1143
 
5.7%
4 1134
 
5.7%
9 1094
 
5.5%
D 737
 
3.7%
Other values (7) 4623
23.1%

결재데이터베이스경로명
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
sbo/global/eip/aprv/repository/doc/aprvregfile2021.nsf
354 
sbo/global/eip/aprv/approve.nsf
144 
sbo/global/eip/aprv/aprvreject.nsf
 
2

Length

Max length54
Median length54
Mean length47.296
Min length31

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowsbo/global/eip/aprv/repository/doc/aprvregfile2021.nsf
2nd rowsbo/global/eip/aprv/approve.nsf
3rd rowsbo/global/eip/aprv/repository/doc/aprvregfile2021.nsf
4th rowsbo/global/eip/aprv/approve.nsf
5th rowsbo/global/eip/aprv/approve.nsf

Common Values

ValueCountFrequency (%)
sbo/global/eip/aprv/repository/doc/aprvregfile2021.nsf 354
70.8%
sbo/global/eip/aprv/approve.nsf 144
28.8%
sbo/global/eip/aprv/aprvreject.nsf 2
 
0.4%

Length

2023-12-12T21:24:49.317672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:24:49.451819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
sbo/global/eip/aprv/repository/doc/aprvregfile2021.nsf 354
70.8%
sbo/global/eip/aprv/approve.nsf 144
28.8%
sbo/global/eip/aprv/aprvreject.nsf 2
 
0.4%

문서요약상세내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing500
Missing (%)100.0%
Memory size4.5 KiB

첨부파일유무
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size632.0 B
False
498 
True
 
2
ValueCountFrequency (%)
False 498
99.6%
True 2
 
0.4%
2023-12-12T21:24:49.575488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

기안직원번호
Text

Distinct322
Distinct (%)64.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-12T21:24:50.013480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.062
Min length4

Characters and Unicode

Total characters2031
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique210 ?
Unique (%)42.0%

Sample

1st row3621
2nd row3026
3rd row4008
4th row3368
5th row4866
ValueCountFrequency (%)
92980 12
 
2.4%
4400 8
 
1.6%
4755 7
 
1.4%
2655 6
 
1.2%
5626 6
 
1.2%
4794 6
 
1.2%
4720 5
 
1.0%
5091 5
 
1.0%
5691 4
 
0.8%
5715 4
 
0.8%
Other values (312) 437
87.4%
2023-12-12T21:24:50.622627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 327
16.1%
4 311
15.3%
0 216
10.6%
6 199
9.8%
9 183
9.0%
3 174
8.6%
2 167
8.2%
1 159
7.8%
7 152
7.5%
8 131
6.5%
Other values (2) 12
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2019
99.4%
Uppercase Letter 12
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 327
16.2%
4 311
15.4%
0 216
10.7%
6 199
9.9%
9 183
9.1%
3 174
8.6%
2 167
8.3%
1 159
7.9%
7 152
7.5%
8 131
6.5%
Uppercase Letter
ValueCountFrequency (%)
C 9
75.0%
A 3
 
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2019
99.4%
Latin 12
 
0.6%

Most frequent character per script

Common
ValueCountFrequency (%)
5 327
16.2%
4 311
15.4%
0 216
10.7%
6 199
9.9%
9 183
9.1%
3 174
8.6%
2 167
8.3%
1 159
7.9%
7 152
7.5%
8 131
6.5%
Latin
ValueCountFrequency (%)
C 9
75.0%
A 3
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2031
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 327
16.1%
4 311
15.3%
0 216
10.6%
6 199
9.8%
9 183
9.0%
3 174
8.6%
2 167
8.2%
1 159
7.8%
7 152
7.5%
8 131
6.5%
Other values (2) 12
 
0.6%

결재신청일자
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

2023-12-12T21:24:50.779100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:24:50.895460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00.0 500
100.0%

결재신청처리시간
Date

Distinct474
Distinct (%)94.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
Minimum2023-12-12 00:00:00
Maximum2023-12-12 18:08:08
2023-12-12T21:24:51.010919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:24:51.185975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

최종결재일자
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
00:00.0
365 
0001-01-01 00:00:00.000000
135 

Length

Max length26
Median length7
Mean length12.13
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row00:00.0
2nd row0001-01-01 00:00:00.000000
3rd row00:00.0
4th row0001-01-01 00:00:00.000000
5th row0001-01-01 00:00:00.000000

Common Values

ValueCountFrequency (%)
00:00.0 365
73.0%
0001-01-01 00:00:00.000000 135
 
27.0%

Length

2023-12-12T21:24:51.346421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:24:51.505464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00.0 365
57.5%
0001-01-01 135
 
21.3%
00:00:00.000000 135
 
21.3%

최종결재처리시간
Date

Distinct327
Distinct (%)65.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
Minimum2023-12-12 00:00:00
Maximum2023-12-12 14:40:29
2023-12-12T21:24:51.637746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:24:51.798299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

그룹웨어문서상태코드값
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
appr70
354 
appr20
135 
appr15
 
8
appr50
 
2
appr31
 
1

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st rowappr70
2nd rowappr20
3rd rowappr70
4th rowappr20
5th rowappr20

Common Values

ValueCountFrequency (%)
appr70 354
70.8%
appr20 135
 
27.0%
appr15 8
 
1.6%
appr50 2
 
0.4%
appr31 1
 
0.2%

Length

2023-12-12T21:24:51.965984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:24:52.078883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
appr70 354
70.8%
appr20 135
 
27.0%
appr15 8
 
1.6%
appr50 2
 
0.4%
appr31 1
 
0.2%

전자결재최종상태코드
Categorical

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
3
353 
2
135 
4
 
6
 
6

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 353
70.6%
2 135
 
27.0%
4 6
 
1.2%
6
 
1.2%

Length

2023-12-12T21:24:52.209764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:24:52.324679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 353
71.5%
2 135
 
27.3%
4 6
 
1.2%

삭제여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size632.0 B
False
494 
True
 
6
ValueCountFrequency (%)
False 494
98.8%
True 6
 
1.2%
2023-12-12T21:24:52.463181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

최종수정수
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2
340 
1
151 
3
 
9

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
2 340
68.0%
1 151
30.2%
3 9
 
1.8%

Length

2023-12-12T21:24:52.601533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:24:52.707228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 340
68.0%
1 151
30.2%
3 9
 
1.8%

처리시각
Text

Distinct495
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-12T21:24:53.072198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters3500
Distinct characters12
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

Unique490 ?
Unique (%)98.0%

Sample

1st row40:29.7
2nd row40:27.1
3rd row40:22.7
4th row40:22.2
5th row40:21.2
ValueCountFrequency (%)
24:12.7 2
 
0.4%
13:37.5 2
 
0.4%
52:08.3 2
 
0.4%
31:50.6 2
 
0.4%
27:42.7 2
 
0.4%
06:02.0 1
 
0.2%
07:13.7 1
 
0.2%
07:01.3 1
 
0.2%
05:55.0 1
 
0.2%
05:56.4 1
 
0.2%
Other values (485) 485
97.0%
2023-12-12T21:24:53.601388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
0 358
10.2%
3 343
9.8%
2 342
9.8%
1 320
9.1%
5 310
8.9%
4 243
6.9%
7 160
 
4.6%
8 157
 
4.5%
Other values (2) 267
7.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2500
71.4%
Other Punctuation 1000
 
28.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 358
14.3%
3 343
13.7%
2 342
13.7%
1 320
12.8%
5 310
12.4%
4 243
9.7%
7 160
6.4%
8 157
6.3%
6 135
 
5.4%
9 132
 
5.3%
Other Punctuation
ValueCountFrequency (%)
: 500
50.0%
. 500
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3500
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
0 358
10.2%
3 343
9.8%
2 342
9.8%
1 320
9.1%
5 310
8.9%
4 243
6.9%
7 160
 
4.6%
8 157
 
4.5%
Other values (2) 267
7.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
0 358
10.2%
3 343
9.8%
2 342
9.8%
1 320
9.1%
5 310
8.9%
4 243
6.9%
7 160
 
4.6%
8 157
 
4.5%
Other values (2) 267
7.6%

처리직원번호
Text

Distinct322
Distinct (%)64.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-12T21:24:54.071182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.062
Min length4

Characters and Unicode

Total characters2031
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique213 ?
Unique (%)42.6%

Sample

1st row3621
2nd row3026
3rd row4008
4th row3368
5th row4866
ValueCountFrequency (%)
92980 12
 
2.4%
4400 8
 
1.6%
4755 7
 
1.4%
2655 6
 
1.2%
4493 6
 
1.2%
4794 6
 
1.2%
5626 6
 
1.2%
5091 5
 
1.0%
4720 5
 
1.0%
5691 4
 
0.8%
Other values (312) 435
87.0%
2023-12-12T21:24:54.679849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 326
16.1%
4 316
15.6%
0 214
10.5%
6 197
9.7%
9 185
9.1%
3 175
8.6%
2 166
8.2%
1 158
7.8%
7 151
7.4%
8 131
6.5%
Other values (2) 12
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2019
99.4%
Uppercase Letter 12
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 326
16.1%
4 316
15.7%
0 214
10.6%
6 197
9.8%
9 185
9.2%
3 175
8.7%
2 166
8.2%
1 158
7.8%
7 151
7.5%
8 131
6.5%
Uppercase Letter
ValueCountFrequency (%)
C 9
75.0%
A 3
 
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2019
99.4%
Latin 12
 
0.6%

Most frequent character per script

Common
ValueCountFrequency (%)
5 326
16.1%
4 316
15.7%
0 214
10.6%
6 197
9.8%
9 185
9.2%
3 175
8.7%
2 166
8.2%
1 158
7.8%
7 151
7.5%
8 131
6.5%
Latin
ValueCountFrequency (%)
C 9
75.0%
A 3
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2031
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 326
16.1%
4 316
15.6%
0 214
10.5%
6 197
9.7%
9 185
9.1%
3 175
8.6%
2 166
8.2%
1 158
7.8%
7 151
7.4%
8 131
6.5%
Other values (2) 12
 
0.6%

Sample

전자결재개별결재ID전자결재ID전자결재부점구분코드전자결재구분코드전자결재전자수기구분코드그룹웨어등록여부본건문서그룹웨어결재KEY명그룹웨어결재KEY명결재데이터베이스경로명문서요약상세내용첨부파일유무기안직원번호결재신청일자결재신청처리시간최종결재일자최종결재처리시간그룹웨어문서상태코드값전자결재최종상태코드삭제여부최종수정수처리시각처리직원번호
09dnS0BwbwB9dnS0BwbwB111Y<NA>E211018_E8E75F1C580666E049258772001EC4ACsbo/global/eip/aprv/repository/doc/aprvregfile2021.nsf<NA>N362100:00.014:36:3400:00.014:40:29appr703N240:29.73621
19dnS0SdHkZ9dnS0SdHkZ111Y<NA>E211018_EA8DCB694E03D7D449258772001F258Esbo/global/eip/aprv/approve.nsf<NA>N302600:00.014:40:270001-01-01 00:00:00.0000000:00:00appr202N140:27.13026
29dnS0P5RLG9dnS0P5RLG111Y<NA>E211018_0DEA08E412F5A4E749258772001F17DEsbo/global/eip/aprv/repository/doc/aprvregfile2021.nsf<NA>N400800:00.014:40:2200:00.014:40:22appr703N140:22.74008
39dnS0RQV0P9dnS0RQV0P111Y<NA>E211018_B5966D353747520249258772001F231Dsbo/global/eip/aprv/approve.nsf<NA>N336800:00.014:40:220001-01-01 00:00:00.0000000:00:00appr202N140:22.23368
49dnS0RRuMK9dnS0RRuMK111Y<NA>E211018_68957919A1E238C949258772001F23AAsbo/global/eip/aprv/approve.nsf<NA>N486600:00.014:40:210001-01-01 00:00:00.0000000:00:00appr202N140:21.24866
59dnS0RQJEB9dnS0RQJEB111Y<NA>E211018_ABC8C2B594D1D71049258772001F2321sbo/global/eip/aprv/approve.nsf<NA>N359300:00.014:40:150001-01-01 00:00:00.0000000:00:00appr202N140:15.63593
69dnS0P4mCU9dnS0P4mCU111Y<NA>E211018_A9CF3DB1B84ED76649258772001F188Dsbo/global/eip/aprv/approve.nsf<NA>N525300:00.014:40:130001-01-01 00:00:00.0000000:00:00appr202N140:13.05253
79dnS0RyglY9dnS0RyglY111Y<NA>E211018_1EEAB9AECBD9D67A49258772001F205Bsbo/global/eip/aprv/approve.nsf<NA>N509100:00.014:40:100001-01-01 00:00:00.0000000:00:00appr202N140:10.65091
89dnS0KhhPS9dnS0KhhPS111Y<NA>E211018_FB3D512135EB589D49258772001EF6BEsbo/global/eip/aprv/approve.nsf<NA>N9A06700:00.014:40:030001-01-01 00:00:00.0000000:00:00appr202N140:03.09A067
99dnS0Q8s9N9dnS0Q8s9N111Y<NA>E211018_ECDCFCD3E039C8B149258772001F1E0Csbo/global/eip/aprv/approve.nsf<NA>N569100:00.014:40:010001-01-01 00:00:00.0000000:00:00appr202N140:01.45691
전자결재개별결재ID전자결재ID전자결재부점구분코드전자결재구분코드전자결재전자수기구분코드그룹웨어등록여부본건문서그룹웨어결재KEY명그룹웨어결재KEY명결재데이터베이스경로명문서요약상세내용첨부파일유무기안직원번호결재신청일자결재신청처리시간최종결재일자최종결재처리시간그룹웨어문서상태코드값전자결재최종상태코드삭제여부최종수정수처리시각처리직원번호
4909dnSWxr0pm9dnSWxr0pm111Y<NA>E211018_F9474C01F7E03CC14925877200191508sbo/global/eip/aprv/repository/doc/aprvregfile2021.nsf<NA>N516200:00.013:34:4500:00.013:51:08appr703N251:08.35162
4919dnSWGfREl9dnSWGfREl111Y<NA>E211018_D6D2B3BD89E8A9414925877200194D7Fsbo/global/eip/aprv/repository/doc/aprvregfile2021.nsf<NA>N444500:00.013:36:3700:00.013:50:39appr703N250:39.24445
4929dnSXACEXt9dnSXACEXt111Y<NA>E211018_CD69486F36BBB29B49258772001A9026sbo/global/eip/aprv/approve.nsf<NA>N460500:00.013:50:380001-01-01 00:00:00.0000000:00:00appr202N150:38.24605
4939dnSPBcwFU9dnSPBcwFU111Y<NA>E211018_EDAC28654F49CA8049258772000F61ABsbo/global/eip/aprv/repository/doc/aprvregfile2021.nsf<NA>N376500:00.011:48:1000:00.013:50:25appr703N250:25.23765
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