Overview

Dataset statistics

Number of variables38
Number of observations500
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory156.4 KiB
Average record size in memory320.3 B

Variable types

Categorical23
Numeric9
Text6

Dataset

Description해당 파일 데이터는 신용보증기금의 보증부문과 관련하여 보증료 관련 제반 데이터를 확인하실 수 있으니 참고바랍니다.
Author신용보증기금
URLhttps://www.data.go.kr/data/15092622/fileData.do

Alerts

업무구분코드 has constant value ""Constant
제수입금기표일자 has constant value ""Constant
기산일자 has constant value ""Constant
취소정당구분코드 has constant value ""Constant
대상기간시작일자 has constant value ""Constant
대상기간종료일자 has constant value ""Constant
흑적구분코드 has constant value ""Constant
당기전기구분코드 has constant value ""Constant
취소원건기표일자 has constant value ""Constant
취소원건기표일련번호 has constant value ""Constant
본건취소기표일자 has constant value ""Constant
본건취소기표일련번호 has constant value ""Constant
유효개시일자 has constant value ""Constant
유효종료일자 has constant value ""Constant
이력일련번호 is highly imbalanced (94.4%)Imbalance
제수입금계정처리구분코드 is highly imbalanced (94.7%)Imbalance
통화코드 is highly imbalanced (97.9%)Imbalance
환율 is highly imbalanced (95.3%)Imbalance
고정보증료율적용대상코드 is highly imbalanced (75.6%)Imbalance
차감보증료율적용대상코드 is highly imbalanced (56.0%)Imbalance
실행해지기표일자 is highly imbalanced (88.2%)Imbalance
최종수정수 is highly imbalanced (65.8%)Imbalance
보증료율 has 16 (3.2%) zerosZeros
통화별수수료 has 223 (44.6%) zerosZeros
환산수수료 has 16 (3.2%) zerosZeros
계수증감금액 has 16 (3.2%) zerosZeros
실행해지기표일련번호 has 8 (1.6%) zerosZeros

Reproduction

Analysis started2023-12-12 12:41:21.541528
Analysis finished2023-12-12 12:41:22.066967
Duration0.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업무구분코드
Categorical

CONSTANT 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
G 500
100.0%

Length

2023-12-12T21:41:22.150706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:41:22.269293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
g 500
100.0%

제수입금기표일자
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

2023-12-12T21:41:22.393132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:41:22.519874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00.0 500
100.0%

제수입금기표일련번호
Real number (ℝ)

Distinct41
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.154
Minimum1
Maximum41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T21:41:22.645324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile16.05
Maximum41
Range40
Interquartile range (IQR)1

Descriptive statistics

Standard deviation6.4790617
Coefficient of variation (CV)2.0542364
Kurtosis16.108002
Mean3.154
Median Absolute Deviation (MAD)0
Skewness4.0028835
Sum1577
Variance41.97824
MonotonicityNot monotonic
2023-12-12T21:41:22.824005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
1 329
65.8%
2 90
 
18.0%
3 18
 
3.6%
4 13
 
2.6%
5 4
 
0.8%
6 3
 
0.6%
13 2
 
0.4%
11 2
 
0.4%
10 2
 
0.4%
9 2
 
0.4%
Other values (31) 35
 
7.0%
ValueCountFrequency (%)
1 329
65.8%
2 90
 
18.0%
3 18
 
3.6%
4 13
 
2.6%
5 4
 
0.8%
6 3
 
0.6%
7 2
 
0.4%
8 2
 
0.4%
9 2
 
0.4%
10 2
 
0.4%
ValueCountFrequency (%)
41 1
0.2%
40 1
0.2%
39 1
0.2%
38 1
0.2%
37 1
0.2%
36 1
0.2%
35 1
0.2%
34 1
0.2%
33 1
0.2%
32 1
0.2%

이력일련번호
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
495 
2
 
4
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
1 495
99.0%
2 4
 
0.8%
3 1
 
0.2%

Length

2023-12-12T21:41:23.002009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:41:23.099577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 495
99.0%
2 4
 
0.8%
3 1
 
0.2%

기산일자
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

2023-12-12T21:41:23.221317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:41:23.352664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00.0 500
100.0%

제수입금구분코드
Real number (ℝ)

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.87
Minimum1
Maximum21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T21:41:23.441465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile9
Maximum21
Range20
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.361409
Coefficient of variation (CV)1.2627856
Kurtosis27.924173
Mean1.87
Median Absolute Deviation (MAD)0
Skewness4.7309195
Sum935
Variance5.5762525
MonotonicityNot monotonic
2023-12-12T21:41:23.551910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 325
65.0%
2 139
27.8%
9 28
 
5.6%
3 3
 
0.6%
21 3
 
0.6%
4 2
 
0.4%
ValueCountFrequency (%)
1 325
65.0%
2 139
27.8%
3 3
 
0.6%
4 2
 
0.4%
9 28
 
5.6%
21 3
 
0.6%
ValueCountFrequency (%)
21 3
 
0.6%
9 28
 
5.6%
4 2
 
0.4%
3 3
 
0.6%
2 139
27.8%
1 325
65.0%

제수입금계정처리구분코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
497 
81
 
3

Length

Max length2
Median length1
Mean length1.006
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
497
99.4%
81 3
 
0.6%

Length

2023-12-12T21:41:23.692252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:41:23.790633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
81 3
100.0%

취소정당구분코드
Categorical

CONSTANT 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
500
100.0%

Length

2023-12-12T21:41:23.920130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:41:24.043216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
No values found.

통화코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
KRW
499 
USD
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
KRW 499
99.8%
USD 1
 
0.2%

Length

2023-12-12T21:41:24.138893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:41:24.247708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
krw 499
99.8%
usd 1
 
0.2%

환율
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
496 
0
 
3
1194
 
1

Length

Max length4
Median length1
Mean length1.006
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
1 496
99.2%
0 3
 
0.6%
1194 1
 
0.2%

Length

2023-12-12T21:41:24.388694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:41:24.524506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 496
99.2%
0 3
 
0.6%
1194 1
 
0.2%

보증료율
Real number (ℝ)

ZEROS 

Distinct21
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0652
Minimum0
Maximum10
Zeros16
Zeros (%)3.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T21:41:24.647771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.3
Q10.7
median1
Q31.3
95-th percentile1.7
Maximum10
Range10
Interquartile range (IQR)0.6

Descriptive statistics

Standard deviation1.0698589
Coefficient of variation (CV)1.0043738
Kurtosis56.262283
Mean1.0652
Median Absolute Deviation (MAD)0.3
Skewness6.9713808
Sum532.6
Variance1.1445982
MonotonicityNot monotonic
2023-12-12T21:41:24.788196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1.3 76
15.2%
1.0 68
13.6%
1.1 57
11.4%
0.9 54
10.8%
0.3 48
9.6%
0.8 35
 
7.0%
1.2 19
 
3.8%
0.7 18
 
3.6%
0.0 16
 
3.2%
0.4 16
 
3.2%
Other values (11) 93
18.6%
ValueCountFrequency (%)
0.0 16
 
3.2%
0.3 48
9.6%
0.4 16
 
3.2%
0.5 16
 
3.2%
0.6 12
 
2.4%
0.7 18
 
3.6%
0.8 35
7.0%
0.9 54
10.8%
1.0 68
13.6%
1.1 57
11.4%
ValueCountFrequency (%)
10.0 6
 
1.2%
2.1 1
 
0.2%
2.0 3
 
0.6%
1.9 5
 
1.0%
1.8 7
 
1.4%
1.7 5
 
1.0%
1.6 10
 
2.0%
1.5 12
 
2.4%
1.4 16
 
3.2%
1.3 76
15.2%

대상기간시작일자
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

2023-12-12T21:41:24.940914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:41:25.051587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00.0 500
100.0%

대상기간종료일자
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

2023-12-12T21:41:25.173324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:41:25.291250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00.0 500
100.0%

일수
Real number (ℝ)

Distinct106
Distinct (%)21.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean395.574
Minimum1
Maximum1824
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T21:41:25.397415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q1215.25
median364
Q3365
95-th percentile1459
Maximum1824
Range1823
Interquartile range (IQR)149.75

Descriptive statistics

Standard deviation351.23324
Coefficient of variation (CV)0.8879078
Kurtosis3.5729286
Mean395.574
Median Absolute Deviation (MAD)20
Skewness1.9287754
Sum197787
Variance123364.79
MonotonicityNot monotonic
2023-12-12T21:41:25.581246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
364 135
27.0%
365 102
20.4%
1459 22
 
4.4%
730 16
 
3.2%
90 15
 
3.0%
300 14
 
2.8%
454 13
 
2.6%
65 12
 
2.4%
1094 12
 
2.4%
3 10
 
2.0%
Other values (96) 149
29.8%
ValueCountFrequency (%)
1 7
1.4%
2 5
1.0%
3 10
2.0%
4 8
1.6%
5 1
 
0.2%
6 2
 
0.4%
7 1
 
0.2%
8 1
 
0.2%
9 1
 
0.2%
11 1
 
0.2%
ValueCountFrequency (%)
1824 1
 
0.2%
1462 5
 
1.0%
1461 3
 
0.6%
1459 22
4.4%
1368 1
 
0.2%
1097 4
 
0.8%
1094 12
2.4%
1067 1
 
0.2%
730 16
3.2%
544 2
 
0.4%

통화별수수료
Real number (ℝ)

ZEROS 

Distinct186
Distinct (%)37.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean340981.64
Minimum0
Maximum35872823
Zeros223
Zeros (%)44.6%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T21:41:25.755113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2558.895
Q357000
95-th percentile1138899
Maximum35872823
Range35872823
Interquartile range (IQR)57000

Descriptive statistics

Standard deviation2330069.8
Coefficient of variation (CV)6.8334173
Kurtosis216.50008
Mean340981.64
Median Absolute Deviation (MAD)2558.895
Skewness14.351622
Sum1.7049082 × 108
Variance5.4292253 × 1012
MonotonicityNot monotonic
2023-12-12T21:41:25.945160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 223
44.6%
57000.0 23
 
4.6%
683531.5 19
 
3.8%
13561.63 13
 
2.6%
2938.35 11
 
2.2%
113895.89 6
 
1.2%
684936.98 5
 
1.0%
227791.78 5
 
1.0%
270.68 4
 
0.8%
607.12 2
 
0.4%
Other values (176) 189
37.8%
ValueCountFrequency (%)
0.0 223
44.6%
53.42 1
 
0.2%
68.2 1
 
0.2%
135.61 1
 
0.2%
204.91 1
 
0.2%
242.19 2
 
0.4%
270.68 4
 
0.8%
330.56 1
 
0.2%
451.19 1
 
0.2%
607.12 2
 
0.4%
ValueCountFrequency (%)
35872822.67 2
0.4%
5899400.0 1
0.2%
5334575.34 1
0.2%
4931506.84 1
0.2%
3562520.54 1
0.2%
3506250.59 1
0.2%
3135000.0 1
0.2%
2785808.21 1
0.2%
2130410.95 2
0.4%
2120547.94 1
0.2%

환산수수료
Real number (ℝ)

ZEROS 

Distinct339
Distinct (%)67.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1230390.7
Minimum0
Maximum26714550
Zeros16
Zeros (%)3.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T21:41:26.152170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile270
Q115052.5
median401095
Q31395580
95-th percentile4936234.5
Maximum26714550
Range26714550
Interquartile range (IQR)1380527.5

Descriptive statistics

Standard deviation2718385.2
Coefficient of variation (CV)2.2093675
Kurtosis40.485904
Mean1230390.7
Median Absolute Deviation (MAD)395720
Skewness5.6715674
Sum6.1519534 × 108
Variance7.3896178 × 1012
MonotonicityNot monotonic
2023-12-12T21:41:26.329093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
57000 23
 
4.6%
683530 19
 
3.8%
0 16
 
3.2%
13560 14
 
2.8%
2930 12
 
2.4%
950000 8
 
1.6%
113890 6
 
1.2%
227790 5
 
1.0%
684930 5
 
1.0%
270 4
 
0.8%
Other values (329) 388
77.6%
ValueCountFrequency (%)
0 16
3.2%
50 1
 
0.2%
60 1
 
0.2%
130 1
 
0.2%
200 1
 
0.2%
240 2
 
0.4%
270 4
 
0.8%
330 1
 
0.2%
450 1
 
0.2%
476 1
 
0.2%
ValueCountFrequency (%)
26714550 1
0.2%
24876710 1
0.2%
21393970 1
0.2%
17936410 2
0.4%
17735270 1
0.2%
13500000 1
0.2%
8597390 2
0.4%
7595830 1
0.2%
7479450 1
0.2%
7020000 2
0.4%

계수증감금액
Real number (ℝ)

ZEROS 

Distinct339
Distinct (%)67.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1230390.7
Minimum0
Maximum26714550
Zeros16
Zeros (%)3.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T21:41:26.517819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile270
Q115052.5
median401095
Q31395580
95-th percentile4936234.5
Maximum26714550
Range26714550
Interquartile range (IQR)1380527.5

Descriptive statistics

Standard deviation2718385.2
Coefficient of variation (CV)2.2093675
Kurtosis40.485904
Mean1230390.7
Median Absolute Deviation (MAD)395720
Skewness5.6715674
Sum6.1519534 × 108
Variance7.3896178 × 1012
MonotonicityNot monotonic
2023-12-12T21:41:26.693680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
57000 23
 
4.6%
683530 19
 
3.8%
0 16
 
3.2%
13560 14
 
2.8%
2930 12
 
2.4%
950000 8
 
1.6%
113890 6
 
1.2%
227790 5
 
1.0%
684930 5
 
1.0%
270 4
 
0.8%
Other values (329) 388
77.6%
ValueCountFrequency (%)
0 16
3.2%
50 1
 
0.2%
60 1
 
0.2%
130 1
 
0.2%
200 1
 
0.2%
240 2
 
0.4%
270 4
 
0.8%
330 1
 
0.2%
450 1
 
0.2%
476 1
 
0.2%
ValueCountFrequency (%)
26714550 1
0.2%
24876710 1
0.2%
21393970 1
0.2%
17936410 2
0.4%
17735270 1
0.2%
13500000 1
0.2%
8597390 2
0.4%
7595830 1
0.2%
7479450 1
0.2%
7020000 2
0.4%

흑적구분코드
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

2023-12-12T21:41:26.861392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:41:26.979769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 500
100.0%

당기전기구분코드
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

2023-12-12T21:41:27.092208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:41:27.198970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 500
100.0%

수수료처리코드
Real number (ℝ)

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.94
Minimum2
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T21:41:27.278582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q14
median8
Q310
95-th percentile10
Maximum10
Range8
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.1170229
Coefficient of variation (CV)0.44913874
Kurtosis-1.7488752
Mean6.94
Median Absolute Deviation (MAD)2
Skewness-0.22504172
Sum3470
Variance9.7158317
MonotonicityNot monotonic
2023-12-12T21:41:27.416719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
10 227
45.4%
4 145
29.0%
8 52
 
10.4%
3 43
 
8.6%
2 30
 
6.0%
5 3
 
0.6%
ValueCountFrequency (%)
2 30
 
6.0%
3 43
 
8.6%
4 145
29.0%
5 3
 
0.6%
8 52
 
10.4%
10 227
45.4%
ValueCountFrequency (%)
10 227
45.4%
8 52
 
10.4%
5 3
 
0.6%
4 145
29.0%
3 43
 
8.6%
2 30
 
6.0%

취소원건기표일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0001-01-01 00:00:00.000000
500 

Length

Max length26
Median length26
Mean length26
Min length26

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0001-01-01 00:00:00.000000 500
100.0%

Length

2023-12-12T21:41:27.575532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:41:27.685071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0001-01-01 500
50.0%
00:00:00.000000 500
50.0%

취소원건기표일련번호
Categorical

CONSTANT 

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

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 (%)
0 500
100.0%

Length

2023-12-12T21:41:27.781462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:41:27.868893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 500
100.0%

본건취소기표일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0001-01-01 00:00:00.000000
500 

Length

Max length26
Median length26
Mean length26
Min length26

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0001-01-01 00:00:00.000000 500
100.0%

Length

2023-12-12T21:41:27.959412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:41:28.067996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0001-01-01 500
50.0%
00:00:00.000000 500
50.0%

본건취소기표일련번호
Categorical

CONSTANT 

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

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 (%)
0 500
100.0%

Length

2023-12-12T21:41:28.184894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:41:28.309745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 500
100.0%

고정보증료율적용여부
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
N
254 
172 
Y
74 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 254
50.8%
172
34.4%
Y 74
 
14.8%

Length

2023-12-12T21:41:28.421681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:41:28.521546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 254
77.4%
y 74
 
22.6%

고정보증료율적용대상코드
Categorical

IMBALANCE 

Distinct15
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
428 
25
 
29
38
 
17
37
 
14
86
 
2
Other values (10)
 
10

Length

Max length2
Median length1
Mean length1.144
Min length1

Unique

Unique10 ?
Unique (%)2.0%

Sample

1st row38
2nd row
3rd row
4th row
5th row37

Common Values

ValueCountFrequency (%)
428
85.6%
25 29
 
5.8%
38 17
 
3.4%
37 14
 
2.8%
86 2
 
0.4%
77 1
 
0.2%
54 1
 
0.2%
30 1
 
0.2%
17 1
 
0.2%
69 1
 
0.2%
Other values (5) 5
 
1.0%

Length

2023-12-12T21:41:28.938734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
25 29
40.3%
38 17
23.6%
37 14
19.4%
86 2
 
2.8%
77 1
 
1.4%
54 1
 
1.4%
30 1
 
1.4%
17 1
 
1.4%
69 1
 
1.4%
47 1
 
1.4%
Other values (4) 4
 
5.6%

차감보증료율적용대상코드
Categorical

IMBALANCE 

Distinct41
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
341 
Q8
 
23
R1
 
13
J4
 
13
G8
 
13
Other values (36)
97 

Length

Max length2
Median length1
Mean length1.318
Min length1

Unique

Unique16 ?
Unique (%)3.2%

Sample

1st row
2nd row
3rd rowN7
4th rowJ4
5th row

Common Values

ValueCountFrequency (%)
341
68.2%
Q8 23
 
4.6%
R1 13
 
2.6%
J4 13
 
2.6%
G8 13
 
2.6%
45 11
 
2.2%
17 9
 
1.8%
H3 7
 
1.4%
23 7
 
1.4%
N7 6
 
1.2%
Other values (31) 57
 
11.4%

Length

2023-12-12T21:41:29.058294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
q8 23
14.5%
g8 13
 
8.2%
r1 13
 
8.2%
j4 13
 
8.2%
45 11
 
6.9%
17 9
 
5.7%
h3 7
 
4.4%
23 7
 
4.4%
n7 6
 
3.8%
46 5
 
3.1%
Other values (30) 52
32.7%

실행해지기표일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
00:00.0
492 
0001-01-01 00:00:00.000000
 
8

Length

Max length26
Median length7
Mean length7.304
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 (%)
00:00.0 492
98.4%
0001-01-01 00:00:00.000000 8
 
1.6%

Length

2023-12-12T21:41:29.184848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:41:29.296983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00.0 492
96.9%
0001-01-01 8
 
1.6%
00:00:00.000000 8
 
1.6%

실행해지기표일련번호
Real number (ℝ)

ZEROS 

Distinct13
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.898
Minimum0
Maximum12
Zeros8
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T21:41:29.385455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q32
95-th percentile5
Maximum12
Range12
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.590174
Coefficient of variation (CV)0.83781559
Kurtosis11.187143
Mean1.898
Median Absolute Deviation (MAD)1
Skewness3.0441759
Sum949
Variance2.5286533
MonotonicityNot monotonic
2023-12-12T21:41:29.556982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
1 246
49.2%
2 176
35.2%
3 23
 
4.6%
4 18
 
3.6%
0 8
 
1.6%
6 8
 
1.6%
8 5
 
1.0%
5 5
 
1.0%
9 4
 
0.8%
7 4
 
0.8%
Other values (3) 3
 
0.6%
ValueCountFrequency (%)
0 8
 
1.6%
1 246
49.2%
2 176
35.2%
3 23
 
4.6%
4 18
 
3.6%
5 5
 
1.0%
6 8
 
1.6%
7 4
 
0.8%
8 5
 
1.0%
9 4
 
0.8%
ValueCountFrequency (%)
12 1
 
0.2%
11 1
 
0.2%
10 1
 
0.2%
9 4
 
0.8%
8 5
 
1.0%
7 4
 
0.8%
6 8
 
1.6%
5 5
 
1.0%
4 18
3.6%
3 23
4.6%

자동연결처리시각
Text

Distinct177
Distinct (%)35.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-12T21:41:29.978706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length26
Mean length17.83
Min length7

Characters and Unicode

Total characters8915
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

Unique146 ?
Unique (%)29.2%

Sample

1st row03:49.8
2nd row0001-01-01 00:00:00.000000
3rd row18:35.8
4th row18:28.1
5th row0001-01-01 00:00:00.000000
ValueCountFrequency (%)
0001-01-01 285
36.3%
00:00:00.000000 285
36.3%
57:05.9 4
 
0.5%
58:57.7 4
 
0.5%
42:20.5 3
 
0.4%
11:22.1 3
 
0.4%
47:00.8 3
 
0.4%
59:24.7 3
 
0.4%
08:27.1 3
 
0.4%
08:04.8 2
 
0.3%
Other values (168) 190
24.2%
2023-12-12T21:41:30.599861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4991
56.0%
1 1016
 
11.4%
: 785
 
8.8%
- 570
 
6.4%
. 500
 
5.6%
285
 
3.2%
4 134
 
1.5%
5 127
 
1.4%
2 119
 
1.3%
3 116
 
1.3%
Other values (4) 272
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6775
76.0%
Other Punctuation 1285
 
14.4%
Dash Punctuation 570
 
6.4%
Space Separator 285
 
3.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4991
73.7%
1 1016
 
15.0%
4 134
 
2.0%
5 127
 
1.9%
2 119
 
1.8%
3 116
 
1.7%
8 78
 
1.2%
7 75
 
1.1%
9 60
 
0.9%
6 59
 
0.9%
Other Punctuation
ValueCountFrequency (%)
: 785
61.1%
. 500
38.9%
Dash Punctuation
ValueCountFrequency (%)
- 570
100.0%
Space Separator
ValueCountFrequency (%)
285
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8915
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4991
56.0%
1 1016
 
11.4%
: 785
 
8.8%
- 570
 
6.4%
. 500
 
5.6%
285
 
3.2%
4 134
 
1.5%
5 127
 
1.4%
2 119
 
1.3%
3 116
 
1.3%
Other values (4) 272
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8915
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4991
56.0%
1 1016
 
11.4%
: 785
 
8.8%
- 570
 
6.4%
. 500
 
5.6%
285
 
3.2%
4 134
 
1.5%
5 127
 
1.4%
2 119
 
1.3%
3 116
 
1.3%
Other values (4) 272
 
3.1%

회계연결처리시각
Text

Distinct481
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-12T21:41:30.975533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length7
Mean length7.608
Min length7

Characters and Unicode

Total characters3804
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

Unique477 ?
Unique (%)95.4%

Sample

1st row03:52.2
2nd row18:42.7
3rd row18:39.6
4th row18:30.9
5th row18:25.1
ValueCountFrequency (%)
0001-01-01 16
 
3.1%
00:00:00.000000 16
 
3.1%
41:45.0 3
 
0.6%
03:50.5 2
 
0.4%
12:53.7 2
 
0.4%
47:31.4 1
 
0.2%
47:32.6 1
 
0.2%
47:32.4 1
 
0.2%
47:32.2 1
 
0.2%
47:32.0 1
 
0.2%
Other values (472) 472
91.5%
2023-12-12T21:41:31.562888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 593
15.6%
: 516
13.6%
. 500
13.1%
1 338
8.9%
4 334
8.8%
5 305
8.0%
3 277
7.3%
2 262
6.9%
7 168
 
4.4%
6 164
 
4.3%
Other values (4) 347
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2740
72.0%
Other Punctuation 1016
 
26.7%
Dash Punctuation 32
 
0.8%
Space Separator 16
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 593
21.6%
1 338
12.3%
4 334
12.2%
5 305
11.1%
3 277
10.1%
2 262
9.6%
7 168
 
6.1%
6 164
 
6.0%
9 158
 
5.8%
8 141
 
5.1%
Other Punctuation
ValueCountFrequency (%)
: 516
50.8%
. 500
49.2%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%
Space Separator
ValueCountFrequency (%)
16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3804
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 593
15.6%
: 516
13.6%
. 500
13.1%
1 338
8.9%
4 334
8.8%
5 305
8.0%
3 277
7.3%
2 262
6.9%
7 168
 
4.4%
6 164
 
4.3%
Other values (4) 347
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3804
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 593
15.6%
: 516
13.6%
. 500
13.1%
1 338
8.9%
4 334
8.8%
5 305
8.0%
3 277
7.3%
2 262
6.9%
7 168
 
4.4%
6 164
 
4.3%
Other values (4) 347
9.1%

유효개시일자
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

2023-12-12T21:41:31.752362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:41:31.909679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00.0 500
100.0%

유효종료일자
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

2023-12-12T21:41:32.048077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:41:32.175144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00.0 500
100.0%

최종수정수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
445 
2
51 
3
 
4

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 (%)
1 445
89.0%
2 51
 
10.2%
3 4
 
0.8%

Length

2023-12-12T21:41:32.292234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:41:32.397496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 445
89.0%
2 51
 
10.2%
3 4
 
0.8%

처리시각
Text

Distinct357
Distinct (%)71.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-12T21:41:32.645556image/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

Unique276 ?
Unique (%)55.2%

Sample

1st row18:53.6
2nd row18:42.3
3rd row18:35.8
4th row18:28.1
5th row18:23.5
ValueCountFrequency (%)
47:21.7 41
 
8.2%
06:24.6 13
 
2.6%
57:05.9 5
 
1.0%
03:49.6 4
 
0.8%
58:57.7 4
 
0.8%
34:39.4 4
 
0.8%
08:27.1 3
 
0.6%
41:44.1 3
 
0.6%
42:20.5 3
 
0.6%
37:02.4 2
 
0.4%
Other values (347) 418
83.6%
2023-12-12T21:41:33.071522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
4 361
10.3%
1 347
9.9%
0 304
8.7%
5 298
8.5%
3 265
7.6%
2 257
7.3%
7 230
6.6%
6 154
 
4.4%
Other values (2) 284
8.1%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 361
14.4%
1 347
13.9%
0 304
12.2%
5 298
11.9%
3 265
10.6%
2 257
10.3%
7 230
9.2%
6 154
6.2%
8 150
6.0%
9 134
 
5.4%
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%
4 361
10.3%
1 347
9.9%
0 304
8.7%
5 298
8.5%
3 265
7.6%
2 257
7.3%
7 230
6.6%
6 154
 
4.4%
Other values (2) 284
8.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
4 361
10.3%
1 347
9.9%
0 304
8.7%
5 298
8.5%
3 265
7.6%
2 257
7.3%
7 230
6.6%
6 154
 
4.4%
Other values (2) 284
8.1%

처리직원번호
Text

Distinct185
Distinct (%)37.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-12T21:41:33.477399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.378
Min length4

Characters and Unicode

Total characters2189
Distinct characters11
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

Unique90 ?
Unique (%)18.0%

Sample

1st row6094
2nd row5143
3rd row4492
4th row9C706
5th row5931
ValueCountFrequency (%)
4615 43
 
8.6%
99006 36
 
7.2%
5145 14
 
2.8%
99001 14
 
2.8%
6131 11
 
2.2%
4456 10
 
2.0%
99002 10
 
2.0%
4351 8
 
1.6%
99007 8
 
1.6%
9c778 7
 
1.4%
Other values (175) 339
67.8%
2023-12-12T21:41:34.009259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 354
16.2%
6 315
14.4%
5 258
11.8%
0 253
11.6%
4 230
10.5%
1 206
9.4%
7 142
6.5%
3 128
 
5.8%
C 109
 
5.0%
2 104
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2080
95.0%
Uppercase Letter 109
 
5.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 354
17.0%
6 315
15.1%
5 258
12.4%
0 253
12.2%
4 230
11.1%
1 206
9.9%
7 142
6.8%
3 128
 
6.2%
2 104
 
5.0%
8 90
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
C 109
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2080
95.0%
Latin 109
 
5.0%

Most frequent character per script

Common
ValueCountFrequency (%)
9 354
17.0%
6 315
15.1%
5 258
12.4%
0 253
12.2%
4 230
11.1%
1 206
9.9%
7 142
6.8%
3 128
 
6.2%
2 104
 
5.0%
8 90
 
4.3%
Latin
ValueCountFrequency (%)
C 109
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2189
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 354
16.2%
6 315
14.4%
5 258
11.8%
0 253
11.6%
4 230
10.5%
1 206
9.4%
7 142
6.5%
3 128
 
5.8%
C 109
 
5.0%
2 104
 
4.8%

최초처리시각
Text

Distinct350
Distinct (%)70.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-12T21:41:34.339692image/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

Unique264 ?
Unique (%)52.8%

Sample

1st row03:49.8
2nd row18:42.3
3rd row18:35.8
4th row18:28.1
5th row18:23.5
ValueCountFrequency (%)
47:21.7 41
 
8.2%
06:24.6 13
 
2.6%
58:57.7 4
 
0.8%
34:39.4 4
 
0.8%
57:05.9 4
 
0.8%
03:49.6 4
 
0.8%
42:20.5 3
 
0.6%
59:24.7 3
 
0.6%
47:00.8 3
 
0.6%
11:22.1 3
 
0.6%
Other values (340) 418
83.6%
2023-12-12T21:41:34.831165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
4 350
10.0%
1 349
10.0%
0 303
8.7%
5 300
8.6%
2 269
7.7%
3 264
7.5%
7 226
6.5%
6 156
 
4.5%
Other values (2) 283
8.1%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 350
14.0%
1 349
14.0%
0 303
12.1%
5 300
12.0%
2 269
10.8%
3 264
10.6%
7 226
9.0%
6 156
6.2%
8 149
6.0%
9 134
 
5.4%
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%
4 350
10.0%
1 349
10.0%
0 303
8.7%
5 300
8.6%
2 269
7.7%
3 264
7.5%
7 226
6.5%
6 156
 
4.5%
Other values (2) 283
8.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
4 350
10.0%
1 349
10.0%
0 303
8.7%
5 300
8.6%
2 269
7.7%
3 264
7.5%
7 226
6.5%
6 156
 
4.5%
Other values (2) 283
8.1%

최초처리직원번호
Text

Distinct185
Distinct (%)37.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-12T21:41:35.333645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.378
Min length4

Characters and Unicode

Total characters2189
Distinct characters11
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

Unique90 ?
Unique (%)18.0%

Sample

1st row6094
2nd row5143
3rd row4492
4th row9C706
5th row5931
ValueCountFrequency (%)
4615 43
 
8.6%
99006 36
 
7.2%
5145 14
 
2.8%
99001 14
 
2.8%
6131 11
 
2.2%
4456 10
 
2.0%
99002 10
 
2.0%
4351 8
 
1.6%
99007 8
 
1.6%
9c778 7
 
1.4%
Other values (175) 339
67.8%
2023-12-12T21:41:35.908232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 354
16.2%
6 315
14.4%
5 258
11.8%
0 253
11.6%
4 230
10.5%
1 206
9.4%
7 142
6.5%
3 128
 
5.8%
C 109
 
5.0%
2 104
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2080
95.0%
Uppercase Letter 109
 
5.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 354
17.0%
6 315
15.1%
5 258
12.4%
0 253
12.2%
4 230
11.1%
1 206
9.9%
7 142
6.8%
3 128
 
6.2%
2 104
 
5.0%
8 90
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
C 109
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2080
95.0%
Latin 109
 
5.0%

Most frequent character per script

Common
ValueCountFrequency (%)
9 354
17.0%
6 315
15.1%
5 258
12.4%
0 253
12.2%
4 230
11.1%
1 206
9.9%
7 142
6.8%
3 128
 
6.2%
2 104
 
5.0%
8 90
 
4.3%
Latin
ValueCountFrequency (%)
C 109
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2189
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 354
16.2%
6 315
14.4%
5 258
11.8%
0 253
11.6%
4 230
10.5%
1 206
9.4%
7 142
6.5%
3 128
 
5.8%
C 109
 
5.0%
2 104
 
4.8%

Sample

업무구분코드제수입금기표일자제수입금기표일련번호이력일련번호기산일자제수입금구분코드제수입금계정처리구분코드취소정당구분코드통화코드환율보증료율대상기간시작일자대상기간종료일자일수통화별수수료환산수수료계수증감금액흑적구분코드당기전기구분코드수수료처리코드취소원건기표일자취소원건기표일련번호본건취소기표일자본건취소기표일련번호고정보증료율적용여부고정보증료율적용대상코드차감보증료율적용대상코드실행해지기표일자실행해지기표일련번호자동연결처리시각회계연결처리시각유효개시일자유효종료일자최종수정수처리시각처리직원번호최초처리시각최초처리직원번호
0G00:00.01100:00.01KRW11.000:00.000:00.03640.02842190284219011100001-01-01 00:00:00.00000000001-01-01 00:00:00.0000000Y3800:00.0203:49.803:52.200:00.000:00.0218:53.6609403:49.86094
1G00:00.01100:00.02KRW11.400:00.000:00.036511620.011620116201180001-01-01 00:00:00.00000000001-01-01 00:00:00.000000000:00.010001-01-01 00:00:00.00000018:42.700:00.000:00.0118:42.3514318:42.35143
2G00:00.01100:00.01KRW11.000:00.000:00.03650.01425000142500011100001-01-01 00:00:00.00000000001-01-01 00:00:00.0000000NN700:00.0218:35.818:39.600:00.000:00.0118:35.8449218:35.84492
3G00:00.01100:00.01KRW11.600:00.000:00.03640.01763150176315011100001-01-01 00:00:00.00000000001-01-01 00:00:00.0000000NJ400:00.0218:28.118:30.900:00.000:00.0118:28.19C70618:28.19C706
4G00:00.01100:00.01KRW10.300:00.000:00.03640.029917029917011100001-01-01 00:00:00.00000000001-01-01 00:00:00.0000000Y3700:00.010001-01-01 00:00:00.00000018:25.100:00.000:00.0118:23.5593118:23.55931
5G00:00.01100:00.01KRW12.000:00.000:00.03640.05086020508602011100001-01-01 00:00:00.00000000001-01-01 00:00:00.0000000N4500:00.0218:14.318:17.400:00.000:00.0118:14.39C73918:14.39C739
6G00:00.01100:00.01KRW11.100:00.000:00.03640.01480930148093011100001-01-01 00:00:00.00000000001-01-01 00:00:00.0000000NN700:00.0218:11.518:14.000:00.000:00.0118:11.59C73018:11.59C730
7G00:00.01100:00.02KRW11.200:00.000:00.090583495.895834905834901120001-01-01 00:00:00.00000000001-01-01 00:00:00.000000000:00.0118:07.718:10.500:00.000:00.0118:07.7590318:07.75903
8G00:00.02100:00.01KRW11.200:00.000:00.04540.0294341029434101140001-01-01 00:00:00.00000000001-01-01 00:00:00.0000000NH300:00.0218:07.718:12.700:00.000:00.0118:07.7590318:07.75903
9G00:00.01100:00.01KRW10.000:00.000:00.07300.0001140001-01-01 00:00:00.00000000001-01-01 00:00:00.0000000N00:00.010001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000:00.000:00.0118:06.99900218:06.999002
업무구분코드제수입금기표일자제수입금기표일련번호이력일련번호기산일자제수입금구분코드제수입금계정처리구분코드취소정당구분코드통화코드환율보증료율대상기간시작일자대상기간종료일자일수통화별수수료환산수수료계수증감금액흑적구분코드당기전기구분코드수수료처리코드취소원건기표일자취소원건기표일련번호본건취소기표일자본건취소기표일련번호고정보증료율적용여부고정보증료율적용대상코드차감보증료율적용대상코드실행해지기표일자실행해지기표일련번호자동연결처리시각회계연결처리시각유효개시일자유효종료일자최종수정수처리시각처리직원번호최초처리시각최초처리직원번호
490G00:00.02100:00.02KRW10.900:00.000:00.01461684468.496844606844601120001-01-01 00:00:00.00000000001-01-01 00:00:00.000000000:00.010001-01-01 00:00:00.00000033:29.600:00.000:00.0133:29.0620233:29.06202
491G00:00.01100:00.02KRW11.900:00.000:00.016012743.0112740127401180001-01-01 00:00:00.00000000001-01-01 00:00:00.000000000:00.010001-01-01 00:00:00.00000033:19.500:00.000:00.0133:18.9613133:18.96131
492G00:00.01100:00.01KRW10.000:00.000:00.07300.0001140001-01-01 00:00:00.00000000001-01-01 00:00:00.0000000N00:00.010001-01-01 00:00:00.0000000001-01-01 00:00:00.00000000:00.000:00.0133:17.99900633:17.999006
493G00:00.02100:00.01KRW10.400:00.000:00.01094227791.782277902277901140001-01-01 00:00:00.00000000001-01-01 00:00:00.0000000N00:00.010001-01-01 00:00:00.00000033:20.500:00.000:00.0133:17.99900633:17.999006
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