Overview

Dataset statistics

Number of variables28
Number of observations500
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory113.4 KiB
Average record size in memory232.3 B

Variable types

Categorical14
Numeric4
Text6
Boolean4

Dataset

Description해당 파일 데이터는 신용보증기금의 국가계정과목코드에 대한 정보를 확인하실 수 있는 자료이니 데이터 활용에 참고하여 주시기 바랍니다.
Author신용보증기금
URLhttps://www.data.go.kr/data/15092793/fileData.do

Alerts

개시년월일 has constant value ""Constant
종료년월일 has constant value ""Constant
유효개시일자 has constant value ""Constant
유효종료일자 has constant value ""Constant
국가거래구분코드 is highly imbalanced (77.6%)Imbalance
외화관리여부 is highly imbalanced (75.8%)Imbalance
처리직원번호 is highly imbalanced (53.1%)Imbalance
최초처리시각 is highly imbalanced (53.2%)Imbalance

Reproduction

Analysis started2024-04-18 07:49:54.866307
Analysis finished2024-04-18 07:49:55.782691
Duration0.92 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

국가결산회계구분코드
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
578
253 
574
247 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row574
2nd row578
3rd row578
4th row574
5th row574

Common Values

ValueCountFrequency (%)
578 253
50.6%
574 247
49.4%

Length

2024-04-18T16:49:55.834859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T16:49:55.916729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
578 253
50.6%
574 247
49.4%

국가계정과목코드
Real number (ℝ)

Distinct196
Distinct (%)39.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21456864
Minimum11010206
Maximum63060604
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-18T16:49:56.035170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11010206
5-th percentile11080100
Q113180500
median14170202
Q314180903
95-th percentile61041106
Maximum63060604
Range52050398
Interquartile range (IQR)1000403

Descriptive statistics

Standard deviation16054919
Coefficient of variation (CV)0.74824161
Kurtosis0.73756275
Mean21456864
Median Absolute Deviation (MAD)20098
Skewness1.562477
Sum1.0728432 × 1010
Variance2.5776041 × 1014
MonotonicityNot monotonic
2024-04-18T16:49:56.192466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14150303 10
 
2.0%
11100100 8
 
1.6%
12060100 8
 
1.6%
12030100 8
 
1.6%
11080100 8
 
1.6%
14150302 6
 
1.2%
41040302 6
 
1.2%
14150304 6
 
1.2%
14150301 6
 
1.2%
41040305 6
 
1.2%
Other values (186) 428
85.6%
ValueCountFrequency (%)
11010206 2
 
0.4%
11070100 2
 
0.4%
11070102 2
 
0.4%
11070200 2
 
0.4%
11070201 4
0.8%
11070202 2
 
0.4%
11070203 4
0.8%
11080100 8
1.6%
11080200 2
 
0.4%
11080300 4
0.8%
ValueCountFrequency (%)
63060604 2
0.4%
63060603 2
0.4%
63060602 2
0.4%
63060601 2
0.4%
63060600 2
0.4%
63060504 2
0.4%
63060503 2
0.4%
63060502 2
0.4%
63060501 2
0.4%
63060500 2
0.4%

이력일련번호
Real number (ℝ)

Distinct8
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.576
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-18T16:49:56.308859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile4
Maximum8
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.2804308
Coefficient of variation (CV)0.81245608
Kurtosis7.7936068
Mean1.576
Median Absolute Deviation (MAD)0
Skewness2.6939787
Sum788
Variance1.639503
MonotonicityNot monotonic
2024-04-18T16:49:56.404081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 386
77.2%
3 48
 
9.6%
2 26
 
5.2%
4 20
 
4.0%
5 6
 
1.2%
6 6
 
1.2%
8 4
 
0.8%
7 4
 
0.8%
ValueCountFrequency (%)
1 386
77.2%
2 26
 
5.2%
3 48
 
9.6%
4 20
 
4.0%
5 6
 
1.2%
6 6
 
1.2%
7 4
 
0.8%
8 4
 
0.8%
ValueCountFrequency (%)
8 4
 
0.8%
7 4
 
0.8%
6 6
 
1.2%
5 6
 
1.2%
4 20
 
4.0%
3 48
 
9.6%
2 26
 
5.2%
1 386
77.2%

상위국가계정과목코드
Real number (ℝ)

Distinct75
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21445591
Minimum11010200
Maximum63060600
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-18T16:49:56.528935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11010200
5-th percentile11080000
Q113180000
median14170100
Q314180900
95-th percentile61041105
Maximum63060600
Range52050400
Interquartile range (IQR)1000900

Descriptive statistics

Standard deviation16059487
Coefficient of variation (CV)0.74884796
Kurtosis0.7376092
Mean21445591
Median Absolute Deviation (MAD)170100
Skewness1.5626664
Sum1.0722795 × 1010
Variance2.5790712 × 1014
MonotonicityNot monotonic
2024-04-18T16:49:56.652126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14000000 34
 
6.8%
14150300 28
 
5.6%
14180000 20
 
4.0%
14170300 16
 
3.2%
14180900 12
 
2.4%
12060000 12
 
2.4%
41040300 12
 
2.4%
11080000 12
 
2.4%
11100000 12
 
2.4%
12030000 12
 
2.4%
Other values (65) 330
66.0%
ValueCountFrequency (%)
11010200 2
 
0.4%
11070000 6
1.2%
11070100 4
 
0.8%
11070200 6
1.2%
11080000 12
2.4%
11080300 8
1.6%
11080400 4
 
0.8%
11090700 4
 
0.8%
11100000 12
2.4%
11100200 4
 
0.8%
ValueCountFrequency (%)
63060600 8
1.6%
63060500 8
1.6%
63060000 4
0.8%
61170000 1
 
0.2%
61110000 1
 
0.2%
61041400 1
 
0.2%
61041300 1
 
0.2%
61041200 1
 
0.2%
61041100 1
 
0.2%
51330300 4
0.8%

국가계정과목구분코드
Categorical

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
394 
5
54 
4
 
26
6
 
26

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row4
3rd row5
4th row5
5th row1

Common Values

ValueCountFrequency (%)
1 394
78.8%
5 54
 
10.8%
4 26
 
5.2%
6 26
 
5.2%

Length

2024-04-18T16:49:56.763921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T16:49:56.849837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 394
78.8%
5 54
 
10.8%
4 26
 
5.2%
6 26
 
5.2%

국가계정과목레벨코드
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
4
238 
5
228 
3
34 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
4 238
47.6%
5 228
45.6%
3 34
 
6.8%

Length

2024-04-18T16:49:56.957500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T16:49:57.062097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4 238
47.6%
5 228
45.6%
3 34
 
6.8%

한글회계계정과목명
Text

Distinct121
Distinct (%)24.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2024-04-18T16:49:57.259852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length7.466
Min length2

Characters and Unicode

Total characters3733
Distinct characters112
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.4%

Sample

1st row퇴직수당충당부채환입액
2nd row퇴직수당충당부채환입액
3rd row퇴직수당충당부채전입액
4th row퇴직수당충당부채전입액
5th row선급임차료
ValueCountFrequency (%)
구축물 36
 
7.2%
기타 34
 
6.8%
토지 34
 
6.8%
건물 32
 
6.4%
건물사용수익권 10
 
2.0%
구축물감가상각누계액 10
 
2.0%
기타감가상각누계액 10
 
2.0%
토지사용수익권 10
 
2.0%
건물감가상각누계액 10
 
2.0%
구축물사용수익권 10
 
2.0%
Other values (111) 304
60.8%
2024-04-18T16:49:57.588257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
금 237
 
6.3%
기 229
 
6.1%
대 142
 
3.8%
수 140
 
3.8%
가 111
 
3.0%
물 108
 
2.9%
익 90
 
2.4%
타 85
 
2.3%
사 82
 
2.2%
당 80
 
2.1%
Other values (102) 2429
65.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3725
99.8%
Close Punctuation 4
 
0.1%
Open Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
금 237
 
6.4%
기 229
 
6.1%
대 142
 
3.8%
수 140
 
3.8%
가 111
 
3.0%
물 108
 
2.9%
익 90
 
2.4%
타 85
 
2.3%
사 82
 
2.2%
당 80
 
2.1%
Other values (100) 2421
65.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3725
99.8%
Common 8
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
금 237
 
6.4%
기 229
 
6.1%
대 142
 
3.8%
수 140
 
3.8%
가 111
 
3.0%
물 108
 
2.9%
익 90
 
2.4%
타 85
 
2.3%
사 82
 
2.2%
당 80
 
2.1%
Other values (100) 2421
65.0%
Common
ValueCountFrequency (%)
) 4
50.0%
( 4
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3725
99.8%
ASCII 8
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
금 237
 
6.4%
기 229
 
6.1%
대 142
 
3.8%
수 140
 
3.8%
가 111
 
3.0%
물 108
 
2.9%
익 90
 
2.4%
타 85
 
2.3%
사 82
 
2.2%
당 80
 
2.1%
Other values (100) 2421
65.0%
ASCII
ValueCountFrequency (%)
) 4
50.0%
( 4
50.0%

대표계정과목명
Text

Distinct200
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2024-04-18T16:49:57.808220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length15
Mean length10.762
Min length2

Characters and Unicode

Total characters5381
Distinct characters116
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)1.2%

Sample

1st row퇴직수당충당부채환입액
2nd row퇴직수당충당부채환입액
3rd row퇴직수당충당부채전입액
4th row퇴직수당충당부채전입액
5th row선급임차료
ValueCountFrequency (%)
구축물/기타사회기반시설 10
 
2.0%
건물/기타사회기반시설 6
 
1.2%
기타사회기반시설 6
 
1.2%
정부외단기대여금현재가치할인차금 6
 
1.2%
정부외장기대여금현재가치할인차금 6
 
1.2%
토지/기타사회기반시설 6
 
1.2%
기타/기타사회기반시설 6
 
1.2%
구축물사용수익권/기타사회기반시설 4
 
0.8%
건물사용수익권/기타사회기반시설 4
 
0.8%
장기일반대여금현재가치할인차금 4
 
0.8%
Other values (190) 442
88.4%
2024-04-18T16:49:58.138645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 365
 
6.8%
금 237
 
4.4%
/ 228
 
4.2%
설 198
 
3.7%
수 178
 
3.3%
건 158
 
2.9%
타 153
 
2.8%
인 152
 
2.8%
사 150
 
2.8%
대 142
 
2.6%
Other values (106) 3420
63.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5113
95.0%
Other Punctuation 228
 
4.2%
Open Punctuation 20
 
0.4%
Close Punctuation 20
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 365
 
7.1%
금 237
 
4.6%
설 198
 
3.9%
수 178
 
3.5%
건 158
 
3.1%
타 153
 
3.0%
인 152
 
3.0%
사 150
 
2.9%
대 142
 
2.8%
가 141
 
2.8%
Other values (103) 3239
63.3%
Other Punctuation
ValueCountFrequency (%)
/ 228
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5113
95.0%
Common 268
 
5.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 365
 
7.1%
금 237
 
4.6%
설 198
 
3.9%
수 178
 
3.5%
건 158
 
3.1%
타 153
 
3.0%
인 152
 
3.0%
사 150
 
2.9%
대 142
 
2.8%
가 141
 
2.8%
Other values (103) 3239
63.3%
Common
ValueCountFrequency (%)
/ 228
85.1%
( 20
 
7.5%
) 20
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5113
95.0%
ASCII 268
 
5.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 365
 
7.1%
금 237
 
4.6%
설 198
 
3.9%
수 178
 
3.5%
건 158
 
3.1%
타 153
 
3.0%
인 152
 
3.0%
사 150
 
2.9%
대 142
 
2.8%
가 141
 
2.8%
Other values (103) 3239
63.3%
ASCII
ValueCountFrequency (%)
/ 228
85.1%
( 20
 
7.5%
) 20
 
7.5%

한글약어명
Text

Distinct121
Distinct (%)24.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2024-04-18T16:49:58.331572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length7.466
Min length2

Characters and Unicode

Total characters3733
Distinct characters112
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.4%

Sample

1st row퇴직수당충당부채환입액
2nd row퇴직수당충당부채환입액
3rd row퇴직수당충당부채전입액
4th row퇴직수당충당부채전입액
5th row선급임차료
ValueCountFrequency (%)
구축물 36
 
7.2%
기타 34
 
6.8%
토지 34
 
6.8%
건물 32
 
6.4%
건물사용수익권 10
 
2.0%
구축물감가상각누계액 10
 
2.0%
기타감가상각누계액 10
 
2.0%
토지사용수익권 10
 
2.0%
건물감가상각누계액 10
 
2.0%
구축물사용수익권 10
 
2.0%
Other values (111) 304
60.8%
2024-04-18T16:49:58.663281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
금 237
 
6.3%
기 229
 
6.1%
대 142
 
3.8%
수 140
 
3.8%
가 111
 
3.0%
물 108
 
2.9%
익 90
 
2.4%
타 85
 
2.3%
사 82
 
2.2%
당 80
 
2.1%
Other values (102) 2429
65.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3725
99.8%
Close Punctuation 4
 
0.1%
Open Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
금 237
 
6.4%
기 229
 
6.1%
대 142
 
3.8%
수 140
 
3.8%
가 111
 
3.0%
물 108
 
2.9%
익 90
 
2.4%
타 85
 
2.3%
사 82
 
2.2%
당 80
 
2.1%
Other values (100) 2421
65.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3725
99.8%
Common 8
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
금 237
 
6.4%
기 229
 
6.1%
대 142
 
3.8%
수 140
 
3.8%
가 111
 
3.0%
물 108
 
2.9%
익 90
 
2.4%
타 85
 
2.3%
사 82
 
2.2%
당 80
 
2.1%
Other values (100) 2421
65.0%
Common
ValueCountFrequency (%)
) 4
50.0%
( 4
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3725
99.8%
ASCII 8
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
금 237
 
6.4%
기 229
 
6.1%
대 142
 
3.8%
수 140
 
3.8%
가 111
 
3.0%
물 108
 
2.9%
익 90
 
2.4%
타 85
 
2.3%
사 82
 
2.2%
당 80
 
2.1%
Other values (100) 2421
65.0%
ASCII
ValueCountFrequency (%)
) 4
50.0%
( 4
50.0%

영문회계계정과목명
Text

Distinct121
Distinct (%)24.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2024-04-18T16:49:58.865827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length7.466
Min length2

Characters and Unicode

Total characters3733
Distinct characters112
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.4%

Sample

1st row퇴직수당충당부채환입액
2nd row퇴직수당충당부채환입액
3rd row퇴직수당충당부채전입액
4th row퇴직수당충당부채전입액
5th row선급임차료
ValueCountFrequency (%)
구축물 36
 
7.2%
기타 34
 
6.8%
토지 34
 
6.8%
건물 32
 
6.4%
건물사용수익권 10
 
2.0%
구축물감가상각누계액 10
 
2.0%
기타감가상각누계액 10
 
2.0%
토지사용수익권 10
 
2.0%
건물감가상각누계액 10
 
2.0%
구축물사용수익권 10
 
2.0%
Other values (111) 304
60.8%
2024-04-18T16:49:59.181879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
금 237
 
6.3%
기 229
 
6.1%
대 142
 
3.8%
수 140
 
3.8%
가 111
 
3.0%
물 108
 
2.9%
익 90
 
2.4%
타 85
 
2.3%
사 82
 
2.2%
당 80
 
2.1%
Other values (102) 2429
65.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3725
99.8%
Close Punctuation 4
 
0.1%
Open Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
금 237
 
6.4%
기 229
 
6.1%
대 142
 
3.8%
수 140
 
3.8%
가 111
 
3.0%
물 108
 
2.9%
익 90
 
2.4%
타 85
 
2.3%
사 82
 
2.2%
당 80
 
2.1%
Other values (100) 2421
65.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3725
99.8%
Common 8
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
금 237
 
6.4%
기 229
 
6.1%
대 142
 
3.8%
수 140
 
3.8%
가 111
 
3.0%
물 108
 
2.9%
익 90
 
2.4%
타 85
 
2.3%
사 82
 
2.2%
당 80
 
2.1%
Other values (100) 2421
65.0%
Common
ValueCountFrequency (%)
) 4
50.0%
( 4
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3725
99.8%
ASCII 8
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
금 237
 
6.4%
기 229
 
6.1%
대 142
 
3.8%
수 140
 
3.8%
가 111
 
3.0%
물 108
 
2.9%
익 90
 
2.4%
타 85
 
2.3%
사 82
 
2.2%
당 80
 
2.1%
Other values (100) 2421
65.0%
ASCII
ValueCountFrequency (%)
) 4
50.0%
( 4
50.0%

검색회계계정과목명
Text

Distinct121
Distinct (%)24.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2024-04-18T16:49:59.422388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length7.466
Min length2

Characters and Unicode

Total characters3733
Distinct characters112
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.4%

Sample

1st row퇴직수당충당부채환입액
2nd row퇴직수당충당부채환입액
3rd row퇴직수당충당부채전입액
4th row퇴직수당충당부채전입액
5th row선급임차료
ValueCountFrequency (%)
구축물 36
 
7.2%
기타 34
 
6.8%
토지 34
 
6.8%
건물 32
 
6.4%
건물사용수익권 10
 
2.0%
구축물감가상각누계액 10
 
2.0%
기타감가상각누계액 10
 
2.0%
토지사용수익권 10
 
2.0%
건물감가상각누계액 10
 
2.0%
구축물사용수익권 10
 
2.0%
Other values (111) 304
60.8%
2024-04-18T16:49:59.747324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
금 237
 
6.3%
기 229
 
6.1%
대 142
 
3.8%
수 140
 
3.8%
가 111
 
3.0%
물 108
 
2.9%
익 90
 
2.4%
타 85
 
2.3%
사 82
 
2.2%
당 80
 
2.1%
Other values (102) 2429
65.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3725
99.8%
Close Punctuation 4
 
0.1%
Open Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
금 237
 
6.4%
기 229
 
6.1%
대 142
 
3.8%
수 140
 
3.8%
가 111
 
3.0%
물 108
 
2.9%
익 90
 
2.4%
타 85
 
2.3%
사 82
 
2.2%
당 80
 
2.1%
Other values (100) 2421
65.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3725
99.8%
Common 8
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
금 237
 
6.4%
기 229
 
6.1%
대 142
 
3.8%
수 140
 
3.8%
가 111
 
3.0%
물 108
 
2.9%
익 90
 
2.4%
타 85
 
2.3%
사 82
 
2.2%
당 80
 
2.1%
Other values (100) 2421
65.0%
Common
ValueCountFrequency (%)
) 4
50.0%
( 4
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3725
99.8%
ASCII 8
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
금 237
 
6.4%
기 229
 
6.1%
대 142
 
3.8%
수 140
 
3.8%
가 111
 
3.0%
물 108
 
2.9%
익 90
 
2.4%
타 85
 
2.3%
사 82
 
2.2%
당 80
 
2.1%
Other values (100) 2421
65.0%
ASCII
ValueCountFrequency (%)
) 4
50.0%
( 4
50.0%

국가차대구분코드
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
D
278 
C
222 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowC
2nd rowC
3rd rowD
4th rowD
5th rowD

Common Values

ValueCountFrequency (%)
D 278
55.6%
C 222
44.4%

Length

2024-04-18T16:49:59.880613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T16:49:59.965184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
d 278
55.6%
c 222
44.4%

사용여부
Boolean

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size632.0 B
True
432 
False
68 
ValueCountFrequency (%)
True 432
86.4%
False 68
 
13.6%
2024-04-18T16:50:00.035024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

전표기표여부
Boolean

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size632.0 B
True
404 
False
96 
ValueCountFrequency (%)
True 404
80.8%
False 96
 
19.2%
2024-04-18T16:50:00.108741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

국가거래구분코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
482 
1
 
18

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 482
96.4%
1 18
 
3.6%

Length

2024-04-18T16:50:00.194005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T16:50:00.272841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 482
96.4%
1 18
 
3.6%

기준국가계정과목코드
Categorical

Distinct31
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
322 
11070202
 
14
12020202
 
14
12020203
 
12
12020200
 
12
Other values (26)
126 

Length

Max length8
Median length1
Mean length3.492
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
322
64.4%
11070202 14
 
2.8%
12020202 14
 
2.8%
12020203 12
 
2.4%
12020200 12
 
2.4%
11070200 12
 
2.4%
11070203 12
 
2.4%
14150303 8
 
1.6%
14150304 8
 
1.6%
14150302 8
 
1.6%
Other values (21) 78
 
15.6%

Length

2024-04-18T16:50:00.364154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
11070202 14
 
7.9%
12020202 14
 
7.9%
12020203 12
 
6.7%
12020200 12
 
6.7%
11070200 12
 
6.7%
11070203 12
 
6.7%
14150303 8
 
4.5%
14150304 8
 
4.5%
14150302 8
 
4.5%
14150104 4
 
2.2%
Other values (20) 74
41.6%

개시년월일
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

2024-04-18T16:50:00.465372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T16:50:00.542553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00.0 500
100.0%

종료년월일
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

2024-04-18T16:50:00.622666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T16:50:00.698892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00.0 500
100.0%

미결관리여부
Boolean

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size632.0 B
True
344 
False
156 
ValueCountFrequency (%)
True 344
68.8%
False 156
31.2%
2024-04-18T16:50:00.773977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

외화관리여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size632.0 B
False
480 
True
 
20
ValueCountFrequency (%)
False 480
96.0%
True 20
 
4.0%
2024-04-18T16:50:00.842762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

관리국가계정과목코드
Text

Distinct190
Distinct (%)38.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2024-04-18T16:50:01.095637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.944
Min length1

Characters and Unicode

Total characters3972
Distinct characters11
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

Unique0 ?
Unique (%)0.0%

Sample

1st row41082000
2nd row41082000
3rd row51332100
4th row51332100
5th row11100703
ValueCountFrequency (%)
99999999 12
 
2.4%
14190300 10
 
2.0%
14190200 6
 
1.2%
11090100 6
 
1.2%
12040100 6
 
1.2%
41050304 6
 
1.2%
12050100 6
 
1.2%
14190100 6
 
1.2%
14190400 6
 
1.2%
11080100 6
 
1.2%
Other values (179) 426
85.9%
2024-04-18T16:50:01.527539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1448
36.5%
1 790
19.9%
2 464
 
11.7%
4 420
 
10.6%
3 198
 
5.0%
8 164
 
4.1%
9 162
 
4.1%
5 160
 
4.0%
6 82
 
2.1%
7 80
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3968
99.9%
Space Separator 4
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1448
36.5%
1 790
19.9%
2 464
 
11.7%
4 420
 
10.6%
3 198
 
5.0%
8 164
 
4.1%
9 162
 
4.1%
5 160
 
4.0%
6 82
 
2.1%
7 80
 
2.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3972
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1448
36.5%
1 790
19.9%
2 464
 
11.7%
4 420
 
10.6%
3 198
 
5.0%
8 164
 
4.1%
9 162
 
4.1%
5 160
 
4.0%
6 82
 
2.1%
7 80
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3972
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1448
36.5%
1 790
19.9%
2 464
 
11.7%
4 420
 
10.6%
3 198
 
5.0%
8 164
 
4.1%
9 162
 
4.1%
5 160
 
4.0%
6 82
 
2.1%
7 80
 
2.0%

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

2024-04-18T16:50:01.651362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T16:50:01.728062image/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

2024-04-18T16:50:01.807148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T16:50:01.901041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00.0 500
100.0%

최종수정수
Real number (ℝ)

Distinct8
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.276
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-18T16:50:01.988258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q33
95-th percentile4
Maximum8
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.1359599
Coefficient of variation (CV)0.49910363
Kurtosis7.2516647
Mean2.276
Median Absolute Deviation (MAD)0
Skewness2.2597879
Sum1138
Variance1.2904048
MonotonicityNot monotonic
2024-04-18T16:50:02.080982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2 290
58.0%
1 84
 
16.8%
3 80
 
16.0%
4 22
 
4.4%
5 10
 
2.0%
6 6
 
1.2%
8 4
 
0.8%
7 4
 
0.8%
ValueCountFrequency (%)
1 84
 
16.8%
2 290
58.0%
3 80
 
16.0%
4 22
 
4.4%
5 10
 
2.0%
6 6
 
1.2%
7 4
 
0.8%
8 4
 
0.8%
ValueCountFrequency (%)
8 4
 
0.8%
7 4
 
0.8%
6 6
 
1.2%
5 10
 
2.0%
4 22
 
4.4%
3 80
 
16.0%
2 290
58.0%
1 84
 
16.8%

처리시각
Categorical

Distinct40
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
00:19.7
60 
00:19.6
41 
00:19.3
40 
00:30.3
38 
00:19.4
36 
Other values (35)
285 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique11 ?
Unique (%)2.2%

Sample

1st row00:26.0
2nd row00:26.0
3rd row00:33.4
4th row25:34.0
5th row00:27.8

Common Values

ValueCountFrequency (%)
00:19.7 60
 
12.0%
00:19.6 41
 
8.2%
00:19.3 40
 
8.0%
00:30.3 38
 
7.6%
00:19.4 36
 
7.2%
00:18.9 20
 
4.0%
00:18.6 20
 
4.0%
00:17.9 20
 
4.0%
00:19.2 18
 
3.6%
00:20.1 18
 
3.6%
Other values (30) 189
37.8%

Length

2024-04-18T16:50:02.193088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
00:19.7 60
 
12.0%
00:19.6 41
 
8.2%
00:19.3 40
 
8.0%
00:30.3 38
 
7.6%
00:19.4 36
 
7.2%
00:18.9 20
 
4.0%
00:18.6 20
 
4.0%
00:17.9 20
 
4.0%
00:19.5 18
 
3.6%
00:20.1 18
 
3.6%
Other values (30) 189
37.8%

처리직원번호
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
ACR04
450 
BATCH
50 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
ACR04 450
90.0%
BATCH 50
 
10.0%

Length

2024-04-18T16:50:02.297796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T16:50:02.380050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
acr04 450
90.0%
batch 50
 
10.0%

최초처리시각
Categorical

IMBALANCE 

Distinct28
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
00:00.0
332 
00:30.3
42 
00:18.6
 
20
00:19.5
 
19
00:19.2
 
8
Other values (23)
79 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique3 ?
Unique (%)0.6%

Sample

1st row00:16.3
2nd row00:17.0
3rd row00:17.0
4th row00:16.3
5th row00:30.3

Common Values

ValueCountFrequency (%)
00:00.0 332
66.4%
00:30.3 42
 
8.4%
00:18.6 20
 
4.0%
00:19.5 19
 
3.8%
00:19.2 8
 
1.6%
00:18.5 8
 
1.6%
00:20.9 8
 
1.6%
00:21.7 8
 
1.6%
00:18.8 5
 
1.0%
00:19.6 5
 
1.0%
Other values (18) 45
 
9.0%

Length

2024-04-18T16:50:02.464911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
00:00.0 332
66.4%
00:30.3 42
 
8.4%
00:18.6 20
 
4.0%
00:19.5 19
 
3.8%
00:19.2 8
 
1.6%
00:18.5 8
 
1.6%
00:20.9 8
 
1.6%
00:21.7 8
 
1.6%
00:18.8 5
 
1.0%
00:19.6 5
 
1.0%
Other values (18) 45
 
9.0%

최초처리직원번호
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
TEST1
332 
ACR04
126 
BATCH
42 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowACR04
2nd rowACR04
3rd rowACR04
4th rowACR04
5th rowBATCH

Common Values

ValueCountFrequency (%)
TEST1 332
66.4%
ACR04 126
 
25.2%
BATCH 42
 
8.4%

Length

2024-04-18T16:50:02.562560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T16:50:02.656430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
test1 332
66.4%
acr04 126
 
25.2%
batch 42
 
8.4%

Sample

국가결산회계구분코드국가계정과목코드이력일련번호상위국가계정과목코드국가계정과목구분코드국가계정과목레벨코드한글회계계정과목명대표계정과목명한글약어명영문회계계정과목명검색회계계정과목명국가차대구분코드사용여부전표기표여부국가거래구분코드기준국가계정과목코드개시년월일종료년월일미결관리여부외화관리여부관리국가계정과목코드유효개시일자유효종료일자최종수정수처리시각처리직원번호최초처리시각최초처리직원번호
05744108200014107000044퇴직수당충당부채환입액퇴직수당충당부채환입액퇴직수당충당부채환입액퇴직수당충당부채환입액퇴직수당충당부채환입액CYY100:00.000:00.0NN4108200000:00.000:00.0400:26.0BATCH00:16.3ACR04
15784108200014107000044퇴직수당충당부채환입액퇴직수당충당부채환입액퇴직수당충당부채환입액퇴직수당충당부채환입액퇴직수당충당부채환입액CYY100:00.000:00.0NN4108200000:00.000:00.0400:26.0BATCH00:17.0ACR04
25785133210015131000054퇴직수당충당부채전입액퇴직수당충당부채전입액퇴직수당충당부채전입액퇴직수당충당부채전입액퇴직수당충당부채전입액DYY000:00.000:00.0NN5133210000:00.000:00.0400:33.4BATCH00:17.0ACR04
35745133210015131000054퇴직수당충당부채전입액퇴직수당충당부채전입액퇴직수당충당부채전입액퇴직수당충당부채전입액퇴직수당충당부채전입액DYY000:00.000:00.0NN5133210000:00.000:00.0425:34.0BATCH00:16.3ACR04
45741109070311109070015선급임차료선급임차료선급임차료선급임차료선급임차료DYY000:00.000:00.0YN1110070300:00.000:00.0200:27.8BATCH00:30.3BATCH
55781604020311604020015장기선급임차료장기선급임차료장기선급임차료장기선급임차료장기선급임차료DYY000:00.000:00.0YN1604020300:00.000:00.0200:27.8BATCH00:30.3BATCH
65781319030011319000014임차개량자산감가상각누계액임차개량자산감가상각누계액임차개량자산감가상각누계액임차개량자산감가상각누계액임차개량자산감가상각누계액CYY01318050000:00.000:00.0YN1316030000:00.000:00.0200:27.8BATCH00:30.3BATCH
75781318050011318000014임차개량자산임차개량자산임차개량자산임차개량자산임차개량자산DYY000:00.000:00.0YN1315050000:00.000:00.0200:27.8BATCH00:30.3BATCH
85781109070311109070015선급임차료선급임차료선급임차료선급임차료선급임차료DYY000:00.000:00.0YN1110070300:00.000:00.0200:27.8BATCH00:30.3BATCH
95741604020311604020015장기선급임차료장기선급임차료장기선급임차료장기선급임차료장기선급임차료DYY000:00.000:00.0YN1604020300:00.000:00.0200:27.8BATCH00:30.3BATCH
국가결산회계구분코드국가계정과목코드이력일련번호상위국가계정과목코드국가계정과목구분코드국가계정과목레벨코드한글회계계정과목명대표계정과목명한글약어명영문회계계정과목명검색회계계정과목명국가차대구분코드사용여부전표기표여부국가거래구분코드기준국가계정과목코드개시년월일종료년월일미결관리여부외화관리여부관리국가계정과목코드유효개시일자유효종료일자최종수정수처리시각처리직원번호최초처리시각최초처리직원번호
4905786104130116104130065가산금수익가산금수익/재원의조달가산금수익가산금수익가산금수익CNY000:00.000:00.0NN9999999900:00.000:00.0300:17.1ACR0400:15.5ACR04
4915786104120116104120065위약금수익위약금수익/재원의조달위약금수익위약금수익위약금수익CNY000:00.000:00.0NN9999999900:00.000:00.0300:17.1ACR0400:15.5ACR04
4925786104110116104110065변상금수익변상금수익/재원의조달변상금수익변상금수익변상금수익CNY000:00.000:00.0NN9999999900:00.000:00.0300:17.1ACR0400:15.4ACR04
4935784204140114204140045벌금수익벌금수익/비교환수익등벌금수익벌금수익벌금수익CNY000:00.000:00.0NN9999999900:00.000:00.0300:17.1ACR0400:15.4ACR04
4945784204130114204130045가산금수익가산금수익/비교환수익등가산금수익가산금수익가산금수익CNY000:00.000:00.0NN9999999900:00.000:00.0300:17.1ACR0400:15.4ACR04
4955784204120114204120045위약금수익위약금수익/비교환수익등위약금수익위약금수익위약금수익CNY000:00.000:00.0NN9999999900:00.000:00.0300:17.1ACR0400:15.3ACR04
4965744204110114204110045변상금수익변상금수익/비교환수익등변상금수익변상금수익변상금수익CNY000:00.000:00.0NN00:00.000:00.0400:16.8ACR0400:14.7ACR04
4975744204140114204140045벌금수익벌금수익/비교환수익등벌금수익벌금수익벌금수익CNY000:00.000:00.0NN9999999900:00.000:00.0300:16.8ACR0400:15.2ACR04
4985744204130114204130045가산금수익가산금수익/비교환수익등가산금수익가산금수익가산금수익CNY000:00.000:00.0NN9999999900:00.000:00.0300:16.8ACR0400:15.2ACR04
4995744204120114204120045위약금수익위약금수익/비교환수익등위약금수익위약금수익위약금수익CNY000:00.000:00.0NN9999999900:00.000:00.0300:16.8ACR0400:14.7ACR04