Overview

Dataset statistics

Number of variables49
Number of observations500
Missing cells998
Missing cells (%)4.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory203.3 KiB
Average record size in memory416.3 B

Variable types

Categorical30
DateTime5
Numeric9
Text4
Unsupported1

Dataset

Description해당 파일 데이터는 신용보증기금의 보험제수입금마스터에 대한 정보를 확인하실 수 있는 자료이니 데이터 활용에 참고하여 주시기 바랍니다.
Author신용보증기금
URLhttps://www.data.go.kr/data/15093305/fileData.do

Alerts

업무구분코드 has constant value ""Constant
제수입금기표일자 has constant value ""Constant
취소정당구분코드 has constant value ""Constant
통화코드 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
소송구분코드 has constant value ""Constant
회수보상금지지급부점코드 has constant value ""Constant
회수보상금지지급일시 has constant value ""Constant
구매기업고객ID has constant value ""Constant
자동연결처리시각 has constant value ""Constant
유효개시일자 has constant value ""Constant
유효종료일자 has constant value ""Constant
제수입금기표일련번호 is highly imbalanced (79.0%)Imbalance
이력일련번호 is highly imbalanced (90.6%)Imbalance
기산일자 is highly imbalanced (58.4%)Imbalance
제수입금구분코드 is highly imbalanced (78.1%)Imbalance
제수입금계정처리구분코드 is highly imbalanced (72.3%)Imbalance
환율 is highly imbalanced (96.2%)Imbalance
1일미만수수료 is highly imbalanced (97.9%)Imbalance
회수유형코드 is highly imbalanced (96.2%)Imbalance
회수기관코드 is highly imbalanced (96.2%)Imbalance
채무관계자구분코드 is highly imbalanced (96.2%)Imbalance
상환자고객ID is highly imbalanced (96.2%)Imbalance
인수해지기표일자 is highly imbalanced (96.2%)Imbalance
인수해지기표일련번호 is highly imbalanced (82.8%)Imbalance
회수활동직원번호 is highly imbalanced (96.2%)Imbalance
최종수정수 is highly imbalanced (53.1%)Imbalance
구매기업고객ID has 498 (99.6%) missing valuesMissing
어음번호 has 500 (100.0%) missing valuesMissing
어음번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
납입보험요율 has 6 (1.2%) zerosZeros

Reproduction

Analysis started2023-12-12 11:13:47.551254
Analysis finished2023-12-12 11:13:48.591480
Duration1.04 second
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
A
500 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
A 500
100.0%

Length

2023-12-12T20:13:48.719970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:13:48.886583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
a 500
100.0%

제수입금기표일자
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
Minimum2023-12-12 00:00:00
Maximum2023-12-12 00:00:00
2023-12-12T20:13:49.031254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:13:49.206768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

제수입금기표일련번호
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
472 
2
 
26
3
 
2

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 (%)
1 472
94.4%
2 26
 
5.2%
3 2
 
0.4%

Length

2023-12-12T20:13:49.445647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:13:49.681365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 472
94.4%
2 26
 
5.2%
3 2
 
0.4%

이력일련번호
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
494 
2
 
6

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 (%)
1 494
98.8%
2 6
 
1.2%

Length

2023-12-12T20:13:49.918296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:13:50.089432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 494
98.8%
2 6
 
1.2%

기산일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
00:00.0
458 
0001-01-01 00:00:00.000000
 
42

Length

Max length26
Median length7
Mean length8.596
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
00:00.0 458
91.6%
0001-01-01 00:00:00.000000 42
 
8.4%

Length

2023-12-12T20:13:50.885323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:13:51.143944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00.0 458
84.5%
0001-01-01 42
 
7.7%
00:00:00.000000 42
 
7.7%

제수입금구분코드
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
11
457 
12
 
34
34
 
6
21
 
2
18
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row11
2nd row11
3rd row11
4th row11
5th row12

Common Values

ValueCountFrequency (%)
11 457
91.4%
12 34
 
6.8%
34 6
 
1.2%
21 2
 
0.4%
18 1
 
0.2%

Length

2023-12-12T20:13:51.355800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:13:51.569397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11 457
91.4%
12 34
 
6.8%
34 6
 
1.2%
21 2
 
0.4%
18 1
 
0.2%

제수입금계정처리구분코드
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
11
458 
21
 
40
51
 
2

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row11
2nd row11
3rd row11
4th row11
5th row21

Common Values

ValueCountFrequency (%)
11 458
91.6%
21 40
 
8.0%
51 2
 
0.4%

Length

2023-12-12T20:13:51.792482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:13:51.991609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11 458
91.6%
21 40
 
8.0%
51 2
 
0.4%

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

2023-12-12T20:13:52.205698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:13:52.384936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
No values found.

통화코드
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
KRW 500
100.0%

Length

2023-12-12T20:13:52.570855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:13:52.797197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
krw 500
100.0%

대상금액
Real number (ℝ)

Distinct162
Distinct (%)32.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.829209 × 108
Minimum1000000
Maximum2.1469 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T20:13:52.989080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1000000
5-th percentile4000000
Q19000000
median30000000
Q32.1375 × 108
95-th percentile4.489 × 109
Maximum2.1469 × 1010
Range2.1468 × 1010
Interquartile range (IQR)2.0475 × 108

Descriptive statistics

Standard deviation2.3649904 × 109
Coefficient of variation (CV)3.0207272
Kurtosis36.947001
Mean7.829209 × 108
Median Absolute Deviation (MAD)23000000
Skewness5.4181353
Sum3.9146045 × 1011
Variance5.5931798 × 1018
MonotonicityNot monotonic
2023-12-12T20:13:53.209550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30000000 62
 
12.4%
10000000 46
 
9.2%
9000000 24
 
4.8%
5000000 23
 
4.6%
7000000 22
 
4.4%
4000000 21
 
4.2%
50000000 19
 
3.8%
20000000 16
 
3.2%
8000000 13
 
2.6%
3000000 11
 
2.2%
Other values (152) 243
48.6%
ValueCountFrequency (%)
1000000 5
 
1.0%
2000000 8
 
1.6%
3000000 11
2.2%
4000000 21
4.2%
4452350 1
 
0.2%
5000000 23
4.6%
6000000 9
 
1.8%
7000000 22
4.4%
8000000 13
2.6%
9000000 24
4.8%
ValueCountFrequency (%)
21469000000 2
0.4%
21010000000 1
0.2%
11986000000 1
0.2%
10141000000 1
0.2%
10111000000 2
0.4%
10063000000 1
0.2%
10000000000 1
0.2%
9614000000 1
0.2%
9290000000 1
0.2%
8493000000 1
0.2%

환율
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
498 
0
 
2

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 (%)
1 498
99.6%
0 2
 
0.4%

Length

2023-12-12T20:13:53.430569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:13:53.573850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 498
99.6%
0 2
 
0.4%

납입보험요율
Real number (ℝ)

ZEROS 

Distinct90
Distinct (%)18.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0621658
Minimum0
Maximum8
Zeros6
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T20:13:53.779977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.1
Q10.970735
median1.1
Q31.3
95-th percentile1.7
Maximum8
Range8
Interquartile range (IQR)0.329265

Descriptive statistics

Standard deviation0.64092736
Coefficient of variation (CV)0.60341557
Kurtosis39.917293
Mean1.0621658
Median Absolute Deviation (MAD)0.2
Skewness4.0283062
Sum531.08288
Variance0.41078788
MonotonicityNot monotonic
2023-12-12T20:13:54.055925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.3 112
22.4%
1.1 82
16.4%
1.0 63
12.6%
1.7 49
9.8%
1.4 35
 
7.0%
0.1 21
 
4.2%
1.2 19
 
3.8%
0.7 8
 
1.6%
0.0 6
 
1.2%
1.5 4
 
0.8%
Other values (80) 101
20.2%
ValueCountFrequency (%)
0.0 6
 
1.2%
0.1 21
4.2%
0.1006 2
 
0.4%
0.10148 1
 
0.2%
0.10432 1
 
0.2%
0.10688 2
 
0.4%
0.11026 1
 
0.2%
0.11806 1
 
0.2%
0.12755 1
 
0.2%
0.13086 2
 
0.4%
ValueCountFrequency (%)
8.0 1
 
0.2%
6.0 2
 
0.4%
1.8 1
 
0.2%
1.7 49
9.8%
1.562 2
 
0.4%
1.5 4
 
0.8%
1.4 35
 
7.0%
1.36345 1
 
0.2%
1.3 112
22.4%
1.26882 1
 
0.2%

대상기간시작일자
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
Minimum2023-12-12 00:00:00
Maximum2023-12-12 00:00:00
2023-12-12T20:13:54.291467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:13:54.459557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

대상기간종료일자
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
Minimum2023-12-12 00:00:00
Maximum2023-12-12 00:00:00
2023-12-12T20:13:54.601510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:13:54.754479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

일수
Real number (ℝ)

Distinct39
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean344.382
Minimum1
Maximum366
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T20:13:54.958408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile162.45
Q1365
median365
Q3365
95-th percentile365
Maximum366
Range365
Interquartile range (IQR)0

Descriptive statistics

Standard deviation71.426883
Coefficient of variation (CV)0.20740597
Kurtosis11.771344
Mean344.382
Median Absolute Deviation (MAD)0
Skewness-3.5697606
Sum172191
Variance5101.7997
MonotonicityNot monotonic
2023-12-12T20:13:55.200646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
365 451
90.2%
123 3
 
0.6%
324 3
 
0.6%
92 2
 
0.4%
2 2
 
0.4%
212 2
 
0.4%
366 2
 
0.4%
174 2
 
0.4%
283 2
 
0.4%
30 2
 
0.4%
Other values (29) 29
 
5.8%
ValueCountFrequency (%)
1 1
0.2%
2 2
0.4%
6 1
0.2%
15 1
0.2%
17 1
0.2%
18 1
0.2%
29 1
0.2%
30 2
0.4%
42 1
0.2%
58 1
0.2%
ValueCountFrequency (%)
366 2
 
0.4%
365 451
90.2%
355 1
 
0.2%
324 3
 
0.6%
297 1
 
0.2%
283 2
 
0.4%
266 1
 
0.2%
256 1
 
0.2%
250 1
 
0.2%
248 1
 
0.2%

통화별수수료
Real number (ℝ)

Distinct219
Distinct (%)43.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2173490.7
Minimum0
Maximum2.2961694 × 108
Zeros2
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T20:13:55.413921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile50000
Q1100000
median300000
Q31000000
95-th percentile8148672.5
Maximum2.2961694 × 108
Range2.2961694 × 108
Interquartile range (IQR)900000

Descriptive statistics

Standard deviation11053926
Coefficient of variation (CV)5.0857941
Kurtosis361.23021
Mean2173490.7
Median Absolute Deviation (MAD)200000
Skewness17.797727
Sum1.0867454 × 109
Variance1.2218928 × 1014
MonotonicityNot monotonic
2023-12-12T20:13:55.658547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100000 93
 
18.6%
50000 19
 
3.8%
510000 15
 
3.0%
170000 12
 
2.4%
390000 12
 
2.4%
300000 11
 
2.2%
330000 9
 
1.8%
110000 8
 
1.6%
600000 7
 
1.4%
650000 7
 
1.4%
Other values (209) 307
61.4%
ValueCountFrequency (%)
0 2
0.4%
3280 1
 
0.2%
8000 3
0.6%
9860 1
 
0.2%
10300 1
 
0.2%
16580 1
 
0.2%
18560 1
 
0.2%
20000 1
 
0.2%
21910 1
 
0.2%
38790 1
 
0.2%
ValueCountFrequency (%)
229616940 1
0.2%
39831400 1
0.2%
35296420 1
0.2%
31013030 1
0.2%
24578180 1
0.2%
24063110 1
0.2%
23623810 2
0.4%
23578180 1
0.2%
17505760 1
0.2%
14857950 1
0.2%

환산수수료
Real number (ℝ)

Distinct220
Distinct (%)44.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2173669.7
Minimum739
Maximum2.2961694 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T20:13:55.907721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum739
5-th percentile50000
Q1100000
median300000
Q31000000
95-th percentile8148672.5
Maximum2.2961694 × 108
Range2.296162 × 108
Interquartile range (IQR)900000

Descriptive statistics

Standard deviation11053892
Coefficient of variation (CV)5.0853593
Kurtosis361.2336
Mean2173669.7
Median Absolute Deviation (MAD)200000
Skewness17.797847
Sum1.0868349 × 109
Variance1.2218852 × 1014
MonotonicityNot monotonic
2023-12-12T20:13:56.136190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100000 93
 
18.6%
50000 19
 
3.8%
510000 15
 
3.0%
170000 12
 
2.4%
390000 12
 
2.4%
300000 11
 
2.2%
330000 9
 
1.8%
110000 8
 
1.6%
600000 7
 
1.4%
650000 7
 
1.4%
Other values (210) 307
61.4%
ValueCountFrequency (%)
739 1
 
0.2%
3280 1
 
0.2%
8000 3
0.6%
9860 1
 
0.2%
10300 1
 
0.2%
16580 1
 
0.2%
18560 1
 
0.2%
20000 1
 
0.2%
21910 1
 
0.2%
38790 1
 
0.2%
ValueCountFrequency (%)
229616940 1
0.2%
39831400 1
0.2%
35296420 1
0.2%
31013030 1
0.2%
24578180 1
0.2%
24063110 1
0.2%
23623810 2
0.4%
23578180 1
0.2%
17505760 1
0.2%
14857950 1
0.2%

계수증감금액
Real number (ℝ)

Distinct220
Distinct (%)44.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2173669.7
Minimum739
Maximum2.2961694 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T20:13:56.341577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum739
5-th percentile50000
Q1100000
median300000
Q31000000
95-th percentile8148672.5
Maximum2.2961694 × 108
Range2.296162 × 108
Interquartile range (IQR)900000

Descriptive statistics

Standard deviation11053892
Coefficient of variation (CV)5.0853593
Kurtosis361.2336
Mean2173669.7
Median Absolute Deviation (MAD)200000
Skewness17.797847
Sum1.0868349 × 109
Variance1.2218852 × 1014
MonotonicityNot monotonic
2023-12-12T20:13:56.529214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100000 93
 
18.6%
50000 19
 
3.8%
510000 15
 
3.0%
170000 12
 
2.4%
390000 12
 
2.4%
300000 11
 
2.2%
330000 9
 
1.8%
110000 8
 
1.6%
600000 7
 
1.4%
650000 7
 
1.4%
Other values (210) 307
61.4%
ValueCountFrequency (%)
739 1
 
0.2%
3280 1
 
0.2%
8000 3
0.6%
9860 1
 
0.2%
10300 1
 
0.2%
16580 1
 
0.2%
18560 1
 
0.2%
20000 1
 
0.2%
21910 1
 
0.2%
38790 1
 
0.2%
ValueCountFrequency (%)
229616940 1
0.2%
39831400 1
0.2%
35296420 1
0.2%
31013030 1
0.2%
24578180 1
0.2%
24063110 1
0.2%
23623810 2
0.4%
23578180 1
0.2%
17505760 1
0.2%
14857950 1
0.2%

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

2023-12-12T20:13:56.683915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:13:56.808587image/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

2023-12-12T20:13:56.941196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:13:57.049283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 500
100.0%

수수료처리코드
Categorical

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
10
286 
5
107 
4
67 
8
37 
3
 
3

Length

Max length2
Median length2
Mean length1.572
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row10
3rd row10
4th row5
5th row8

Common Values

ValueCountFrequency (%)
10 286
57.2%
5 107
 
21.4%
4 67
 
13.4%
8 37
 
7.4%
3 3
 
0.6%

Length

2023-12-12T20:13:57.174802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:13:57.319947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10 286
57.2%
5 107
 
21.4%
4 67
 
13.4%
8 37
 
7.4%
3 3
 
0.6%

1일미만수수료
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
499 
4192
 
1

Length

Max length4
Median length1
Mean length1.006
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 499
99.8%
4192 1
 
0.2%

Length

2023-12-12T20:13:57.492483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:13:57.634346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 499
99.8%
4192 1
 
0.2%

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

2023-12-12T20:13:57.796392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:13:57.951234image/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

2023-12-12T20:13:58.104572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:13:58.257503image/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

2023-12-12T20:13:58.461008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:13:58.615691image/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

2023-12-12T20:13:58.758138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:13:58.902498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 500
100.0%

소송구분코드
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

2023-12-12T20:13:59.063853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:13:59.239395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
No values found.

회수유형코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
498 
1
 
2

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 (%)
498
99.6%
1 2
 
0.4%

Length

2023-12-12T20:13:59.395669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:13:59.536370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 2
100.0%

회수기관코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
498 
1
 
2

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 (%)
498
99.6%
1 2
 
0.4%

Length

2023-12-12T20:13:59.709569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:13:59.879160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 2
100.0%

채무관계자구분코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
498 
91
 
2

Length

Max length2
Median length1
Mean length1.004
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
498
99.6%
91 2
 
0.4%

Length

2023-12-12T20:14:00.059529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:14:00.240516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
91 2
100.0%

상환자고객ID
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
498 
9dnMDoosfy
 
2

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
498
99.6%
9dnMDoosfy 2
 
0.4%

Length

2023-12-12T20:14:00.419221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:14:00.822724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
9dnmdoosfy 2
100.0%

인수해지기표일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
00:00.0
498 
0001-01-01 00:00:00.000000
 
2

Length

Max length26
Median length7
Mean length7.076
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 (%)
00:00.0 498
99.6%
0001-01-01 00:00:00.000000 2
 
0.4%

Length

2023-12-12T20:14:01.377424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:14:01.799489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00.0 498
99.2%
0001-01-01 2
 
0.4%
00:00:00.000000 2
 
0.4%

인수해지기표일련번호
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
472 
2
 
25
0
 
2
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 (%)
1 472
94.4%
2 25
 
5.0%
0 2
 
0.4%
3 1
 
0.2%

Length

2023-12-12T20:14:02.920735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:14:03.099756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 472
94.4%
2 25
 
5.0%
0 2
 
0.4%
3 1
 
0.2%

회수활동직원번호
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
498 
4067
 
2

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 498
99.6%
4067 2
 
0.4%

Length

2023-12-12T20:14:03.277251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:14:03.435999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 498
99.6%
4067 2
 
0.4%

회수보상금지지급부점코드
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

2023-12-12T20:14:03.604719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:14:03.765537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
No values found.

회수보상금지지급일시
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

2023-12-12T20:14:03.896532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:14:04.030372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0001-01-01 500
50.0%
00:00:00.000000 500
50.0%

구매기업고객ID
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)50.0%
Missing498
Missing (%)99.6%
Memory size4.0 KiB
2023-12-12T20:14:04.168978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters20
Distinct characters6
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

Unique0 ?
Unique (%)0.0%

Sample

1st rowaaaaac8SEm
2nd rowaaaaac8SEm
ValueCountFrequency (%)
aaaaac8sem 2
100.0%
2023-12-12T20:14:04.548404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 10
50.0%
c 2
 
10.0%
8 2
 
10.0%
S 2
 
10.0%
E 2
 
10.0%
m 2
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 14
70.0%
Uppercase Letter 4
 
20.0%
Decimal Number 2
 
10.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 10
71.4%
c 2
 
14.3%
m 2
 
14.3%
Uppercase Letter
ValueCountFrequency (%)
S 2
50.0%
E 2
50.0%
Decimal Number
ValueCountFrequency (%)
8 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 18
90.0%
Common 2
 
10.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 10
55.6%
c 2
 
11.1%
S 2
 
11.1%
E 2
 
11.1%
m 2
 
11.1%
Common
ValueCountFrequency (%)
8 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 10
50.0%
c 2
 
10.0%
8 2
 
10.0%
S 2
 
10.0%
E 2
 
10.0%
m 2
 
10.0%

어음번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

처리팀코드
Categorical

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
181 
2
139 
3
83 
4
61 
36 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row1
3rd row3
4th row2
5th row3

Common Values

ValueCountFrequency (%)
1 181
36.2%
2 139
27.8%
3 83
16.6%
4 61
 
12.2%
36
 
7.2%

Length

2023-12-12T20:14:04.738378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:14:04.938533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 181
39.0%
2 139
30.0%
3 83
17.9%
4 61
 
13.1%

입력직원번호
Real number (ℝ)

Distinct203
Distinct (%)40.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11296.916
Minimum2398
Maximum88889
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T20:14:05.140449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2398
5-th percentile3864.15
Q15011
median5455
Q35824
95-th percentile88889
Maximum88889
Range86491
Interquartile range (IQR)813

Descriptive statistics

Standard deviation21642.917
Coefficient of variation (CV)1.9158252
Kurtosis9.0502256
Mean11296.916
Median Absolute Deviation (MAD)392
Skewness3.3169219
Sum5648458
Variance4.6841585 × 108
MonotonicityNot monotonic
2023-12-12T20:14:05.359973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
88889 36
 
7.2%
3620 17
 
3.4%
5608 14
 
2.8%
5621 12
 
2.4%
5495 10
 
2.0%
5406 10
 
2.0%
5376 10
 
2.0%
5909 10
 
2.0%
5855 8
 
1.6%
5076 8
 
1.6%
Other values (193) 365
73.0%
ValueCountFrequency (%)
2398 1
 
0.2%
3447 1
 
0.2%
3590 2
 
0.4%
3593 1
 
0.2%
3611 1
 
0.2%
3613 1
 
0.2%
3616 1
 
0.2%
3620 17
3.4%
3877 1
 
0.2%
3977 5
 
1.0%
ValueCountFrequency (%)
88889 36
7.2%
6197 1
 
0.2%
6179 1
 
0.2%
6166 1
 
0.2%
6147 4
 
0.8%
6139 1
 
0.2%
6131 2
 
0.4%
6121 1
 
0.2%
6118 1
 
0.2%
6103 1
 
0.2%

자동연결처리시각
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

2023-12-12T20:14:05.567764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:14:05.779216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0001-01-01 500
50.0%
00:00:00.000000 500
50.0%

회계연결처리시각
Text

Distinct495
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-12T20:14:06.256017image/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 row45:14.4
2nd row39:44.2
3rd row35:30.4
4th row24:20.8
5th row23:03.4
ValueCountFrequency (%)
49:06.1 2
 
0.4%
16:46.9 2
 
0.4%
06:13.6 2
 
0.4%
33:06.4 2
 
0.4%
10:20.7 2
 
0.4%
38:38.2 1
 
0.2%
00:02.1 1
 
0.2%
33:11.4 1
 
0.2%
33:17.9 1
 
0.2%
35:15.8 1
 
0.2%
Other values (485) 485
97.0%
2023-12-12T20:14:07.008837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
0 334
9.5%
3 333
9.5%
4 307
8.8%
2 306
8.7%
5 304
8.7%
1 297
8.5%
9 187
 
5.3%
6 156
 
4.5%
Other values (2) 276
7.9%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 334
13.4%
3 333
13.3%
4 307
12.3%
2 306
12.2%
5 304
12.2%
1 297
11.9%
9 187
7.5%
6 156
6.2%
7 139
5.6%
8 137
5.5%
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%
0 334
9.5%
3 333
9.5%
4 307
8.8%
2 306
8.7%
5 304
8.7%
1 297
8.5%
9 187
 
5.3%
6 156
 
4.5%
Other values (2) 276
7.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
0 334
9.5%
3 333
9.5%
4 307
8.8%
2 306
8.7%
5 304
8.7%
1 297
8.5%
9 187
 
5.3%
6 156
 
4.5%
Other values (2) 276
7.9%

유효개시일자
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
Minimum2023-12-12 00:00:00
Maximum2023-12-12 00:00:00
2023-12-12T20:14:07.166613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:14:07.285577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

유효종료일자
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
Minimum2023-12-12 00:00:00
Maximum2023-12-12 00:00:00
2023-12-12T20:14:07.399998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:14:07.517727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

최종수정수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
450 
2
50 

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 (%)
1 450
90.0%
2 50
 
10.0%

Length

2023-12-12T20:14:07.672518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:14:07.805516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 450
90.0%
2 50
 
10.0%

처리시각
Text

Distinct495
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-12T20:14:08.285433image/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 row45:14.2
2nd row39:40.5
3rd row35:27.3
4th row24:18.6
5th row23:03.2
ValueCountFrequency (%)
06:11.9 2
 
0.4%
10:36.2 2
 
0.4%
43:09.7 2
 
0.4%
22:38.0 2
 
0.4%
16:46.9 2
 
0.4%
38:13.5 1
 
0.2%
57:30.3 1
 
0.2%
09:20.0 1
 
0.2%
25:47.8 1
 
0.2%
33:07.8 1
 
0.2%
Other values (485) 485
97.0%
2023-12-12T20:14:09.043955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
2 324
9.3%
0 316
9.0%
4 311
8.9%
3 311
8.9%
5 301
8.6%
1 292
8.3%
8 170
 
4.9%
9 167
 
4.8%
Other values (2) 308
8.8%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 324
13.0%
0 316
12.6%
4 311
12.4%
3 311
12.4%
5 301
12.0%
1 292
11.7%
8 170
6.8%
9 167
6.7%
6 164
6.6%
7 144
5.8%
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%
2 324
9.3%
0 316
9.0%
4 311
8.9%
3 311
8.9%
5 301
8.6%
1 292
8.3%
8 170
 
4.9%
9 167
 
4.8%
Other values (2) 308
8.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
2 324
9.3%
0 316
9.0%
4 311
8.9%
3 311
8.9%
5 301
8.6%
1 292
8.3%
8 170
 
4.9%
9 167
 
4.8%
Other values (2) 308
8.8%

처리직원번호
Real number (ℝ)

Distinct203
Distinct (%)40.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10963.388
Minimum2398
Maximum88889
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T20:14:09.329406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2398
5-th percentile3864.15
Q15011
median5447
Q35822
95-th percentile88889
Maximum88889
Range86491
Interquartile range (IQR)811

Descriptive statistics

Standard deviation21078.624
Coefficient of variation (CV)1.9226378
Kurtosis9.8683628
Mean10963.388
Median Absolute Deviation (MAD)391
Skewness3.4373654
Sum5481694
Variance4.443084 × 108
MonotonicityNot monotonic
2023-12-12T20:14:09.565879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
88889 34
 
6.8%
3620 17
 
3.4%
5608 15
 
3.0%
5621 12
 
2.4%
5406 11
 
2.2%
5495 10
 
2.0%
5376 10
 
2.0%
5909 10
 
2.0%
5855 8
 
1.6%
5076 8
 
1.6%
Other values (193) 365
73.0%
ValueCountFrequency (%)
2398 1
 
0.2%
3447 1
 
0.2%
3590 2
 
0.4%
3593 1
 
0.2%
3611 1
 
0.2%
3613 1
 
0.2%
3616 1
 
0.2%
3620 17
3.4%
3877 1
 
0.2%
3977 5
 
1.0%
ValueCountFrequency (%)
88889 34
6.8%
6197 1
 
0.2%
6179 1
 
0.2%
6166 1
 
0.2%
6147 4
 
0.8%
6139 1
 
0.2%
6131 2
 
0.4%
6121 1
 
0.2%
6118 1
 
0.2%
6103 1
 
0.2%

최초처리시각
Text

Distinct489
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-12T20:14:10.106125image/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

Unique478 ?
Unique (%)95.6%

Sample

1st row45:14.2
2nd row39:40.5
3rd row35:27.3
4th row24:18.6
5th row23:03.2
ValueCountFrequency (%)
11:17.8 2
 
0.4%
22:38.0 2
 
0.4%
27:42.5 2
 
0.4%
06:11.9 2
 
0.4%
17:15.4 2
 
0.4%
10:36.2 2
 
0.4%
43:09.7 2
 
0.4%
13:36.5 2
 
0.4%
16:46.9 2
 
0.4%
09:21.7 2
 
0.4%
Other values (479) 480
96.0%
2023-12-12T20:14:10.967868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
2 334
9.5%
0 317
9.1%
3 307
8.8%
4 305
8.7%
5 301
8.6%
1 294
8.4%
9 169
 
4.8%
8 165
 
4.7%
Other values (2) 308
8.8%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 334
13.4%
0 317
12.7%
3 307
12.3%
4 305
12.2%
5 301
12.0%
1 294
11.8%
9 169
6.8%
8 165
6.6%
6 163
6.5%
7 145
5.8%
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%
2 334
9.5%
0 317
9.1%
3 307
8.8%
4 305
8.7%
5 301
8.6%
1 294
8.4%
9 169
 
4.8%
8 165
 
4.7%
Other values (2) 308
8.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
2 334
9.5%
0 317
9.1%
3 307
8.8%
4 305
8.7%
5 301
8.6%
1 294
8.4%
9 169
 
4.8%
8 165
 
4.7%
Other values (2) 308
8.8%

최초처리직원번호
Real number (ℝ)

Distinct203
Distinct (%)40.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11296.916
Minimum2398
Maximum88889
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T20:14:11.212785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2398
5-th percentile3864.15
Q15011
median5455
Q35824
95-th percentile88889
Maximum88889
Range86491
Interquartile range (IQR)813

Descriptive statistics

Standard deviation21642.917
Coefficient of variation (CV)1.9158252
Kurtosis9.0502256
Mean11296.916
Median Absolute Deviation (MAD)392
Skewness3.3169219
Sum5648458
Variance4.6841585 × 108
MonotonicityNot monotonic
2023-12-12T20:14:11.455859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
88889 36
 
7.2%
3620 17
 
3.4%
5608 14
 
2.8%
5621 12
 
2.4%
5495 10
 
2.0%
5406 10
 
2.0%
5376 10
 
2.0%
5909 10
 
2.0%
5855 8
 
1.6%
5076 8
 
1.6%
Other values (193) 365
73.0%
ValueCountFrequency (%)
2398 1
 
0.2%
3447 1
 
0.2%
3590 2
 
0.4%
3593 1
 
0.2%
3611 1
 
0.2%
3613 1
 
0.2%
3616 1
 
0.2%
3620 17
3.4%
3877 1
 
0.2%
3977 5
 
1.0%
ValueCountFrequency (%)
88889 36
7.2%
6197 1
 
0.2%
6179 1
 
0.2%
6166 1
 
0.2%
6147 4
 
0.8%
6139 1
 
0.2%
6131 2
 
0.4%
6121 1
 
0.2%
6118 1
 
0.2%
6103 1
 
0.2%

Sample

업무구분코드제수입금기표일자제수입금기표일련번호이력일련번호기산일자제수입금구분코드제수입금계정처리구분코드취소정당구분코드통화코드대상금액환율납입보험요율대상기간시작일자대상기간종료일자일수통화별수수료환산수수료계수증감금액흑적구분코드당기전기구분코드수수료처리코드1일미만수수료취소원건기표일자취소원건기표일련번호본건취소기표일자본건취소기표일련번호소송구분코드회수유형코드회수기관코드채무관계자구분코드상환자고객ID인수해지기표일자인수해지기표일련번호회수활동직원번호회수보상금지지급부점코드회수보상금지지급일시구매기업고객ID어음번호처리팀코드입력직원번호자동연결처리시각회계연결처리시각유효개시일자유효종료일자최종수정수처리시각처리직원번호최초처리시각최초처리직원번호
0A00:00.0110001-01-01 00:00:00.0000001111KRW1198600000010.3605600:00.000:00.09211110840111108401111084011400001-01-01 00:00:00.00000000001-01-01 00:00:00.000000000:00.01<NA>0001-01-01 00:00:00.000000<NA><NA>352470001-01-01 00:00:00.00000045:14.400:00.000:00.0145:14.2524745:14.25247
1A00:00.01100:00.01111KRW8000000011.300:00.000:00.0365104000010400001040000111000001-01-01 00:00:00.00000000001-01-01 00:00:00.000000000:00.01<NA>0001-01-01 00:00:00.000000<NA><NA>160350001-01-01 00:00:00.00000039:44.200:00.000:00.0139:40.5603539:40.56035
2A00:00.01100:00.01111KRW162400000010.1701600:00.000:00.0365276339027633902763390111000001-01-01 00:00:00.00000000001-01-01 00:00:00.000000000:00.01<NA>0001-01-01 00:00:00.000000<NA><NA>354090001-01-01 00:00:00.00000035:30.400:00.000:00.0135:27.3540935:27.35409
3A00:00.01100:00.01111KRW400000011.300:00.000:00.036552000520005200011500001-01-01 00:00:00.00000000001-01-01 00:00:00.000000000:00.01<NA>0001-01-01 00:00:00.000000<NA><NA>242580001-01-01 00:00:00.00000024:20.800:00.000:00.0124:18.6425824:18.64258
4A00:00.0110001-01-01 00:00:00.0000001221KRW5000000011.200:00.000:00.0232803280328011800001-01-01 00:00:00.00000000001-01-01 00:00:00.000000000:00.01<NA>0001-01-01 00:00:00.000000<NA><NA>356420001-01-01 00:00:00.00000023:03.400:00.000:00.0123:03.2564223:03.25642
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6A00:00.0210001-01-01 00:00:00.0000001221KRW2900000011.56200:00.000:00.01518560185601856011800001-01-01 00:00:00.00000000001-01-01 00:00:00.000000000:00.01<NA>0001-01-01 00:00:00.000000<NA><NA>356420001-01-01 00:00:00.00000022:38.800:00.000:00.0122:38.0564222:38.05642
7A00:00.01100:00.01111KRW3000000011.100:00.000:00.036533000033000033000011500001-01-01 00:00:00.00000000001-01-01 00:00:00.000000000:00.01<NA>0001-01-01 00:00:00.000000<NA><NA>249930001-01-01 00:00:00.00000020:25.700:00.000:00.0120:23.2499320:23.24993
8A00:00.01100:00.01111KRW230500000010.32100:00.000:00.036573990507399050739905011500001-01-01 00:00:00.00000000001-01-01 00:00:00.000000000:00.01<NA>0001-01-01 00:00:00.000000<NA><NA>257990001-01-01 00:00:00.00000018:57.200:00.000:00.0118:52.9579918:52.95799
9A00:00.01100:00.01111KRW500000011.300:00.000:00.036565000650006500011400001-01-01 00:00:00.00000000001-01-01 00:00:00.000000000:00.01<NA>0001-01-01 00:00:00.000000<NA><NA>460720001-01-01 00:00:00.00000015:56.800:00.000:00.0115:54.8607215:54.86072
업무구분코드제수입금기표일자제수입금기표일련번호이력일련번호기산일자제수입금구분코드제수입금계정처리구분코드취소정당구분코드통화코드대상금액환율납입보험요율대상기간시작일자대상기간종료일자일수통화별수수료환산수수료계수증감금액흑적구분코드당기전기구분코드수수료처리코드1일미만수수료취소원건기표일자취소원건기표일련번호본건취소기표일자본건취소기표일련번호소송구분코드회수유형코드회수기관코드채무관계자구분코드상환자고객ID인수해지기표일자인수해지기표일련번호회수활동직원번호회수보상금지지급부점코드회수보상금지지급일시구매기업고객ID어음번호처리팀코드입력직원번호자동연결처리시각회계연결처리시각유효개시일자유효종료일자최종수정수처리시각처리직원번호최초처리시각최초처리직원번호
490A00:00.01100:00.01111KRW300000011.200:00.000:00.036510000010000010000011500001-01-01 00:00:00.00000000001-01-01 00:00:00.000000000:00.01<NA>0001-01-01 00:00:00.000000<NA><NA>146990001-01-01 00:00:00.00000036:32.200:00.000:00.0136:29.7469936:29.74699
491A00:00.01100:00.01111KRW3000000011.700:00.000:00.0365510000510000510000111000001-01-01 00:00:00.00000000001-01-01 00:00:00.000000000:00.01<NA>0001-01-01 00:00:00.000000<NA><NA>888890001-01-01 00:00:00.00000029:21.300:00.000:00.0129:19.28888929:19.288889
492A00:00.01100:00.01111KRW1011100000010.3153600:00.000:00.012310960420109604201096042011400001-01-01 00:00:00.00000000001-01-01 00:00:00.000000000:00.01<NA>0001-01-01 00:00:00.000000<NA><NA>356420001-01-01 00:00:00.00000007:30.600:00.000:00.0224:02.4564207:24.85642
493A00:00.01100:00.01111KRW900000011.100:00.000:00.0365990009900099000111000001-01-01 00:00:00.00000000001-01-01 00:00:00.000000000:00.01<NA>0001-01-01 00:00:00.000000<NA><NA>250760001-01-01 00:00:00.00000018:33.300:00.000:00.0118:31.2507618:31.25076
494A00:00.01100:00.01111KRW3000000011.800:00.000:00.036554000054000054000011400001-01-01 00:00:00.00000000001-01-01 00:00:00.000000000:00.01<NA>0001-01-01 00:00:00.000000<NA><NA>242580001-01-01 00:00:00.00000010:38.000:00.000:00.0110:35.8425810:35.84258
495A00:00.01100:00.01111KRW3000000011.100:00.000:00.036533000033000033000011400001-01-01 00:00:00.00000000001-01-01 00:00:00.000000000:00.01<NA>0001-01-01 00:00:00.000000<NA><NA>242580001-01-01 00:00:00.00000010:20.700:00.000:00.0110:18.8425810:18.84258
496A00:00.01100:00.01111KRW5100000010.1846700:00.000:00.0365100000100000100000111000001-01-01 00:00:00.00000000001-01-01 00:00:00.000000000:00.01<NA>0001-01-01 00:00:00.000000<NA><NA>254540001-01-01 00:00:00.00000002:05.800:00.000:00.0102:03.6545402:03.65454
497A00:00.01100:00.01111KRW300000011.100:00.000:00.0365500005000050000111000001-01-01 00:00:00.00000000001-01-01 00:00:00.000000000:00.01<NA>0001-01-01 00:00:00.000000<NA><NA>248770001-01-01 00:00:00.00000000:43.600:00.000:00.0100:41.3487700:41.34877
498A00:00.01100:00.01111KRW500000011.400:00.000:00.0365100000100000100000111000001-01-01 00:00:00.00000000001-01-01 00:00:00.000000000:00.01<NA>0001-01-01 00:00:00.000000<NA><NA>349710001-01-01 00:00:00.00000057:10.400:00.000:00.0157:08.6497157:08.64971
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