Overview

Dataset statistics

Number of variables15
Number of observations500
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory62.1 KiB
Average record size in memory127.3 B

Variable types

DateTime3
Categorical8
Numeric4

Dataset

Description해당 파일 데이터는 신용보증기금의 공통전자문서관리통계현황정보에 대해 확인하실 수 있는 자료이니 데이터 활용에 참고하여 주시기 바랍니다.
Author신용보증기금
URLhttps://www.data.go.kr/data/15093143/fileData.do

Alerts

기준일자 has constant value ""Constant
통계구분코드 has constant value ""Constant
작업시작일자 has constant value ""Constant
작업종료일자 has constant value ""Constant
최종수정수 has constant value ""Constant
처리시각 has constant value ""Constant
전자문서업무구분코드 is highly overall correlated with 공통커버페이지구분코드High correlation
공통커버페이지구분코드 is highly overall correlated with 서식코드 and 1 other fieldsHigh correlation
기준부점코드 is highly overall correlated with 관할영업본부부점코드 and 1 other fieldsHigh correlation
부점지역구분코드 is highly overall correlated with 기준부점코드 and 1 other fieldsHigh correlation
관할영업본부부점코드 is highly overall correlated with 기준부점코드 and 1 other fieldsHigh correlation
서식코드 is highly overall correlated with 공통커버페이지구분코드High correlation
OASIS등록건수 is highly overall correlated with 전자문서관리시스템등록건수 and 1 other fieldsHigh correlation
전자문서관리시스템등록건수 is highly overall correlated with OASIS등록건수 and 1 other fieldsHigh correlation
전자문서관리시스템등록이미지건수 is highly overall correlated with OASIS등록건수 and 1 other fieldsHigh correlation

Reproduction

Analysis started2023-12-12 23:34:01.498631
Analysis finished2023-12-12 23:34:03.927705
Duration2.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
Minimum2023-12-13 00:00:00
Maximum2023-12-13 00:00:00
2023-12-13T08:34:03.969970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:34:04.059430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

기준부점코드
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
THL
44 
THG
40 
THK
38 
THV
37 
THT
37 
Other values (11)
304 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowTHD
2nd rowTHY
3rd rowTHY
4th rowTHY
5th rowTHY

Common Values

ValueCountFrequency (%)
THL 44
 
8.8%
THG 40
 
8.0%
THK 38
 
7.6%
THV 37
 
7.4%
THT 37
 
7.4%
THQ 37
 
7.4%
THS 35
 
7.0%
THO 35
 
7.0%
THW 34
 
6.8%
THU 34
 
6.8%
Other values (6) 129
25.8%

Length

2023-12-13T08:34:04.152404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
thl 44
 
8.8%
thg 40
 
8.0%
thk 38
 
7.6%
thv 37
 
7.4%
tht 37
 
7.4%
thq 37
 
7.4%
ths 35
 
7.0%
tho 35
 
7.0%
thw 34
 
6.8%
thu 34
 
6.8%
Other values (6) 129
25.8%

전자문서업무구분코드
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2
384 
1
116 

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 (%)
2 384
76.8%
1 116
 
23.2%

Length

2023-12-13T08:34:04.270330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:34:04.361703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 384
76.8%
1 116
 
23.2%

서식코드
Real number (ℝ)

HIGH CORRELATION 

Distinct48
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean214574.73
Minimum110515
Maximum220678
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T08:34:04.775082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum110515
5-th percentile210162
Q1210456
median220073
Q3220112
95-th percentile220243
Maximum220678
Range110163
Interquartile range (IQR)9656

Descriptive statistics

Standard deviation18776.395
Coefficient of variation (CV)0.087505154
Kurtosis25.689095
Mean214574.73
Median Absolute Deviation (MAD)49
Skewness-5.1208837
Sum1.0728736 × 108
Variance3.52553 × 108
MonotonicityNot monotonic
2023-12-13T08:34:04.896765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
220120 19
 
3.8%
220119 16
 
3.2%
110515 15
 
3.0%
210456 15
 
3.0%
220100 15
 
3.0%
210226 15
 
3.0%
210206 15
 
3.0%
220084 14
 
2.8%
220160 14
 
2.8%
220004 14
 
2.8%
Other values (38) 348
69.6%
ValueCountFrequency (%)
110515 15
3.0%
210162 14
2.8%
210206 15
3.0%
210226 15
3.0%
210298 14
2.8%
210307 14
2.8%
210353 14
2.8%
210391 14
2.8%
210456 15
3.0%
220002 14
2.8%
ValueCountFrequency (%)
220678 14
2.8%
220676 10
2.0%
220243 13
2.6%
220161 1
 
0.2%
220160 14
2.8%
220122 7
 
1.4%
220121 9
1.8%
220120 19
3.8%
220119 16
3.2%
220118 4
 
0.8%

통계구분코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2
500 

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 (%)
2 500
100.0%

Length

2023-12-13T08:34:05.018239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:34:05.136576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 500
100.0%

작업시작일자
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
Minimum2023-12-13 00:00:00
Maximum2023-12-13 00:00:00
2023-12-13T08:34:05.221412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:34:05.302323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

작업종료일자
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
Minimum2023-12-13 00:00:00
Maximum2023-12-13 00:00:00
2023-12-13T08:34:05.385662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:34:05.480530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

관할영업본부부점코드
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
THE
243 
TID
143 
TAB
81 
TAA
33 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowTHE
2nd rowTAB
3rd rowTAB
4th rowTAB
5th rowTAB

Common Values

ValueCountFrequency (%)
THE 243
48.6%
TID 143
28.6%
TAB 81
 
16.2%
TAA 33
 
6.6%

Length

2023-12-13T08:34:05.588870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:34:05.679512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
the 243
48.6%
tid 143
28.6%
tab 81
 
16.2%
taa 33
 
6.6%

부점지역구분코드
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
B1
243 
G1
143 
A2
81 
A1
33 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowB1
2nd rowA2
3rd rowA2
4th rowA2
5th rowA2

Common Values

ValueCountFrequency (%)
B1 243
48.6%
G1 143
28.6%
A2 81
 
16.2%
A1 33
 
6.6%

Length

2023-12-13T08:34:05.801547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:34:05.907554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
b1 243
48.6%
g1 143
28.6%
a2 81
 
16.2%
a1 33
 
6.6%

공통커버페이지구분코드
Categorical

HIGH CORRELATION 

Distinct36
Distinct (%)7.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1030101
56 
2030101
53 
2070101
36 
2050301
 
26
 
16
Other values (31)
313 

Length

Max length7
Median length7
Mean length6.808
Min length1

Unique

Unique3 ?
Unique (%)0.6%

Sample

1st row2030301
2nd row2030101
3rd row2030101
4th row2040201
5th row2040501

Common Values

ValueCountFrequency (%)
1030101 56
 
11.2%
2030101 53
 
10.6%
2070101 36
 
7.2%
2050301 26
 
5.2%
16
 
3.2%
2040501 15
 
3.0%
1010201 15
 
3.0%
1010401 15
 
3.0%
1010301 15
 
3.0%
2050201 14
 
2.8%
Other values (26) 239
47.8%

Length

2023-12-13T08:34:06.029449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1030101 56
 
11.6%
2030101 53
 
11.0%
2070101 36
 
7.4%
2050301 26
 
5.4%
2040501 15
 
3.1%
1010201 15
 
3.1%
1010401 15
 
3.1%
1010301 15
 
3.1%
2050201 14
 
2.9%
2070201 14
 
2.9%
Other values (25) 225
46.5%

OASIS등록건수
Real number (ℝ)

HIGH CORRELATION 

Distinct143
Distinct (%)28.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean910.386
Minimum1
Maximum31789
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T08:34:06.150252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median10
Q350
95-th percentile6547.05
Maximum31789
Range31788
Interquartile range (IQR)48

Descriptive statistics

Standard deviation3922.1157
Coefficient of variation (CV)4.3081898
Kurtosis29.254888
Mean910.386
Median Absolute Deviation (MAD)9
Skewness5.2696855
Sum455193
Variance15382992
MonotonicityNot monotonic
2023-12-13T08:34:06.295515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 89
 
17.8%
2 50
 
10.0%
3 27
 
5.4%
4 22
 
4.4%
5 15
 
3.0%
6 12
 
2.4%
10 11
 
2.2%
11 11
 
2.2%
8 11
 
2.2%
12 11
 
2.2%
Other values (133) 241
48.2%
ValueCountFrequency (%)
1 89
17.8%
2 50
10.0%
3 27
 
5.4%
4 22
 
4.4%
5 15
 
3.0%
6 12
 
2.4%
7 7
 
1.4%
8 11
 
2.2%
9 8
 
1.6%
10 11
 
2.2%
ValueCountFrequency (%)
31789 1
0.2%
28570 1
0.2%
28480 1
0.2%
25515 1
0.2%
23316 1
0.2%
22171 1
0.2%
21330 1
0.2%
20613 1
0.2%
20082 1
0.2%
20070 1
0.2%

전자문서관리시스템등록건수
Real number (ℝ)

HIGH CORRELATION 

Distinct140
Distinct (%)28.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean827.446
Minimum0
Maximum28100
Zeros4
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T08:34:06.434097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median10
Q347
95-th percentile6175.45
Maximum28100
Range28100
Interquartile range (IQR)45

Descriptive statistics

Standard deviation3500.9172
Coefficient of variation (CV)4.2309917
Kurtosis27.999388
Mean827.446
Median Absolute Deviation (MAD)9
Skewness5.1513393
Sum413723
Variance12256421
MonotonicityNot monotonic
2023-12-13T08:34:06.561705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 89
 
17.8%
2 48
 
9.6%
3 28
 
5.6%
4 23
 
4.6%
5 14
 
2.8%
8 13
 
2.6%
10 12
 
2.4%
6 12
 
2.4%
9 11
 
2.2%
11 11
 
2.2%
Other values (130) 239
47.8%
ValueCountFrequency (%)
0 4
 
0.8%
1 89
17.8%
2 48
9.6%
3 28
 
5.6%
4 23
 
4.6%
5 14
 
2.8%
6 12
 
2.4%
7 5
 
1.0%
8 13
 
2.6%
9 11
 
2.2%
ValueCountFrequency (%)
28100 1
0.2%
25492 1
0.2%
25054 1
0.2%
22844 1
0.2%
20166 1
0.2%
19064 1
0.2%
18806 1
0.2%
18122 1
0.2%
17840 1
0.2%
17779 1
0.2%

전자문서관리시스템등록이미지건수
Real number (ℝ)

HIGH CORRELATION 

Distinct203
Distinct (%)40.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4282.53
Minimum0
Maximum119218
Zeros4
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T08:34:06.674494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q15
median23
Q3107.5
95-th percentile41331.65
Maximum119218
Range119218
Interquartile range (IQR)102.5

Descriptive statistics

Standard deviation16603.095
Coefficient of variation (CV)3.876936
Kurtosis20.371923
Mean4282.53
Median Absolute Deviation (MAD)21
Skewness4.4506264
Sum2141265
Variance2.7566276 × 108
MonotonicityNot monotonic
2023-12-13T08:34:06.796566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 42
 
8.4%
2 31
 
6.2%
4 23
 
4.6%
5 19
 
3.8%
3 18
 
3.6%
6 17
 
3.4%
7 10
 
2.0%
8 10
 
2.0%
12 10
 
2.0%
9 8
 
1.6%
Other values (193) 312
62.4%
ValueCountFrequency (%)
0 4
 
0.8%
1 42
8.4%
2 31
6.2%
3 18
3.6%
4 23
4.6%
5 19
3.8%
6 17
3.4%
7 10
 
2.0%
8 10
 
2.0%
9 8
 
1.6%
ValueCountFrequency (%)
119218 1
0.2%
112342 1
0.2%
109139 1
0.2%
105879 1
0.2%
80975 1
0.2%
79350 1
0.2%
78614 1
0.2%
76163 1
0.2%
74642 1
0.2%
74563 1
0.2%

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

2023-12-13T08:34:06.895598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:34:06.973293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 500
100.0%

처리시각
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
47:10.7
500 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row47:10.7
2nd row47:10.7
3rd row47:10.7
4th row47:10.7
5th row47:10.7

Common Values

ValueCountFrequency (%)
47:10.7 500
100.0%

Length

2023-12-13T08:34:07.046960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:34:07.115751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
47:10.7 500
100.0%

Interactions

2023-12-13T08:34:03.217618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:34:02.044218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:34:02.405448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:34:02.816097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:34:03.325676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:34:02.114138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:34:02.511972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:34:02.913204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:34:03.411378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:34:02.204183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:34:02.619291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:34:03.039670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:34:03.503376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:34:02.300508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:34:02.727072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:34:03.126184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:34:07.162725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준부점코드전자문서업무구분코드서식코드관할영업본부부점코드부점지역구분코드공통커버페이지구분코드OASIS등록건수전자문서관리시스템등록건수전자문서관리시스템등록이미지건수
기준부점코드1.0000.157NaN1.0001.0000.0000.0000.0000.000
전자문서업무구분코드0.1571.000NaN0.0000.0001.0000.5520.5520.501
서식코드NaNNaN1.000NaNNaNNaNNaNNaNNaN
관할영업본부부점코드1.0000.000NaN1.0001.0000.0000.0000.0000.000
부점지역구분코드1.0000.000NaN1.0001.0000.0000.0000.0000.000
공통커버페이지구분코드0.0001.000NaN0.0000.0001.0000.7410.7420.823
OASIS등록건수0.0000.552NaN0.0000.0000.7411.0000.9940.889
전자문서관리시스템등록건수0.0000.552NaN0.0000.0000.7420.9941.0000.904
전자문서관리시스템등록이미지건수0.0000.501NaN0.0000.0000.8230.8890.9041.000
2023-12-13T08:34:07.266003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전자문서업무구분코드공통커버페이지구분코드기준부점코드부점지역구분코드관할영업본부부점코드
전자문서업무구분코드1.0000.9600.1210.0000.000
공통커버페이지구분코드0.9601.0000.0000.0000.000
기준부점코드0.1210.0001.0000.9880.988
부점지역구분코드0.0000.0000.9881.0001.000
관할영업본부부점코드0.0000.0000.9881.0001.000
2023-12-13T08:34:07.349855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
서식코드OASIS등록건수전자문서관리시스템등록건수전자문서관리시스템등록이미지건수기준부점코드전자문서업무구분코드관할영업본부부점코드부점지역구분코드공통커버페이지구분코드
서식코드1.000-0.434-0.433-0.4580.0000.0700.0000.0000.965
OASIS등록건수-0.4341.0000.9980.9720.0000.4230.0000.0000.356
전자문서관리시스템등록건수-0.4330.9981.0000.9730.0000.4230.0000.0000.357
전자문서관리시스템등록이미지건수-0.4580.9720.9731.0000.0000.4990.0000.0000.425
기준부점코드0.0000.0000.0000.0001.0000.1210.9880.9880.000
전자문서업무구분코드0.0700.4230.4230.4990.1211.0000.0000.0000.960
관할영업본부부점코드0.0000.0000.0000.0000.9880.0001.0001.0000.000
부점지역구분코드0.0000.0000.0000.0000.9880.0001.0001.0000.000
공통커버페이지구분코드0.9650.3560.3570.4250.0000.9600.0000.0001.000

Missing values

2023-12-13T08:34:03.647426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:34:03.853757image/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

기준일자기준부점코드전자문서업무구분코드서식코드통계구분코드작업시작일자작업종료일자관할영업본부부점코드부점지역구분코드공통커버페이지구분코드OASIS등록건수전자문서관리시스템등록건수전자문서관리시스템등록이미지건수최종수정수처리시각
000:00.0THD2220084200:00.000:00.0THEB12030301202045147:10.7
100:00.0THY2220004200:00.000:00.0TABA22030101111126147:10.7
200:00.0THY2220002200:00.000:00.0TABA220301016262153147:10.7
300:00.0THY2210298200:00.000:00.0TABA22040201313144147:10.7
400:00.0THY2110515200:00.000:00.0TABA22040501193193808147:10.7
500:00.0THY1220120200:00.000:00.0TABA2433147:10.7
600:00.0THY1210456200:00.000:00.0TABA21010201190118277916147:10.7
700:00.0THY1210391200:00.000:00.0TABA21030101343175147:10.7
800:00.0THY1210353200:00.000:00.0TABA21030101668147:10.7
900:00.0THY1210307200:00.000:00.0TABA210301017165197147:10.7
기준일자기준부점코드전자문서업무구분코드서식코드통계구분코드작업시작일자작업종료일자관할영업본부부점코드부점지역구분코드공통커버페이지구분코드OASIS등록건수전자문서관리시스템등록건수전자문서관리시스템등록이미지건수최종수정수처리시각
49000:00.0THD2220120200:00.000:00.0THEB12110301446147:10.7
49100:00.0THD2220119200:00.000:00.0THEB12110201112147:10.7
49200:00.0THD2220113200:00.000:00.0THEB120401018786236147:10.7
49300:00.0THD2220112200:00.000:00.0THEB12010101104103183147:10.7
49400:00.0THD2220101200:00.000:00.0THEB12050301225147:10.7
49500:00.0THD2220100200:00.000:00.0THEB12050301434397147:10.7
49600:00.0THD2220093200:00.000:00.0THEB12050101111015147:10.7
49700:00.0THD2220091200:00.000:00.0THEB12050201323281147:10.7
49800:00.0THD2220086200:00.000:00.0THEB12030101224147:10.7
49900:00.0THD2220085200:00.000:00.0THEB120302015454101147:10.7